| Title: | Identification of risk variants and cross-disorder pleiotropy through multi-ancestry genome-wide analysis of alcohol use disorder |
| Journal: | Nature Mental Health |
| Published: | 8 Jan 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40322774/ |
| DOI: | https://doi.org/10.1038/s44220-024-00353-8 |
| URL: | https://scholarworks.indianapolis.iu.edu/bitstreams/42c2663c-d4bd-4cdc-bff0-cb376c4bb5ae/download |
Publication 14875
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Abstract
Alcohol use disorder (AUD) is highly heritable and burdensome worldwide. Genome-wide association studies can provide new evidence regarding the etiology of AUD. We report a multi-ancestry genome-wide association study focusing on a narrow AUD phenotype, using novel statistical tools in a total sample of 1,041,450 individuals (102,079 cases; European, 75,583; African, 20,689 (mostly African American); Hispanic American, 3,449; East Asian, 2,254; South Asian, 104; descent). Cross-ancestry functional analyses were performed with European and African samples. Thirty-seven genome-wide significant loci (105 variants) were identified, of which seven were novel for AUD and six for other alcohol phenotypes. Loci were mapped to genes, which show altered expression in brain regions relevant for AUD (striatum, hypothalamus and prefrontal cortex) and encode potential drug targets (GABAergic, dopaminergic and serotonergic neurons). African-specific analysis yielded a unique pattern of immune-related gene sets. Polygenic overlap and positive genetic correlations showed extensive shared genetic architecture between AUD and both mental and general medical phenotypes, suggesting that they are not only complications of alcohol use but also share genetic liability with AUD. Leveraging a cross-ancestry approach allowed identification of novel genetic loci for AUD and underscores the value of multi-ancestry genetic studies. These findings advance our understanding of AUD risk and clinically relevant comorbidities.</p>
20 Authors
- Romain Icick
- Alexey Shadrin
- Børge Holen
- Naz Karadag
- Nadine Parker
- Kevin S. O'Connell
- Oleksandr Frei
- Shahram Bahrami
- Margrethe Collier Høegh
- Trine Vik Lagerberg
- Weiqiu Cheng
- Tyler M. Seibert
- Srdjan Djurovic
- Anders M. Dale
- Hang Zhou
- Howard J. Edenberg
- Joel Gelernter
- Olav B. Smeland
- Guy Hindley
- Ole A. Andreassen
1 Application
| Application ID | Title |
|---|---|
| 27412 | Boosting the power of GWAS using novel statistical tools |
Enabling scientific discoveries that improve human health