1. Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes
- Author
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Toikumo, Sylvanus, Jennings, Mariela V, Pham, Benjamin K, Lee, Hyunjoon, Mallard, Travis T, Bianchi, Sevim B, Meredith, John J, Vilar-Ribó, Laura, Xu, Heng, Hatoum, Alexander S, Johnson, Emma C, Pazdernik, Vanessa K, Jinwala, Zeal, Pakala, Shreya R, Leger, Brittany S, Niarchou, Maria, Ehinmowo, Michael, Jenkins, Greg D, Batzler, Anthony, Pendegraft, Richard, Palmer, Abraham A, Zhou, Hang, Biernacka, Joanna M, Coombes, Brandon J, Gelernter, Joel, Xu, Ke, Hancock, Dana B, Cox, Nancy J, Smoller, Jordan W, Davis, Lea K, Justice, Amy C, Kranzler, Henry R, Kember, Rachel L, and Sanchez-Roige, Sandra
- Subjects
Biomedical and Clinical Sciences ,Health Sciences ,Drug Abuse (NIDA only) ,Human Genome ,Prevention ,Genetics ,Tobacco ,Substance Misuse ,Brain Disorders ,Tobacco Smoke and Health ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Humans ,Tobacco Use Disorder ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,United States ,Male ,Female ,Electronic Health Records ,Penn Medicine BioBank ,Biomedical and clinical sciences ,Health sciences ,Psychology - Abstract
Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.
- Published
- 2024