1. Multi-ancestry meta-analysis of tobacco use disorders based on electronic health record data prioritizes novel candidate risk genes and reveals associations with numerous health outcomes
- Author
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Toikumo, Sylvanus, Jennings, Mariela V, Pham, Benjamin, Lee, Hyunjoon, Mallard, Travis T, Bianchi, Sevim B, Meredith, John J, Vilar-Ribó, Laura, Xu, Heng, Hatoum, Alexander S, Johnson, Emma C, Pazdernik, Vanessa, Jinwala, Zeal, Leger, Brittany S, Niarchou, Maria, Ehinmowo, Michael, BioBank, Penn Medicine, Veteran, Million, 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
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Article - Abstract
Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records,EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 72 independent risk loci; integration with functional genomic tools uncovered 330 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain.
- Published
- 2023
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