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
Toikumo, S.; Jennings, M. V.; Pham, B.; Lee, H.; Mallard, T. T.; Bianchi, S. B.; Meredith, J. J.; Vilar-Ribo, L.; Xu, H.; Hatoum, A. S.; Johnson, E. C.; Pazdernik, V.; Jinwala, Z.; Leger, B. S.; Niarchou, M.; Ehinmowo, M. I.; Penn Medicine BioBank, ; MVP, ; Psychemerge Substance Use Disorder, ; Jenkins, G. D.; Batzler, A.; Pendegraft, R.; Palmer, A. A.; Zhou, H.; Biernacka, J.; Coombes, B.; Gelernter, J.; Xu, K.; Hancock, D. B.; Nancy, C. J.; Smoller, J. W.; Davis, L. K.; Justice, A. C.; Kranzler, H. R.; Kember, R. L.; Sanchez-Roige, S.
Show 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 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 behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The impact of rare protein coding genetic variation on adult cognitive function 97%
- Genome-wide analysis of binge-eating disorder identifies the first three risk loci and implicates iron metabolism 96%
- Genome-wide landscape of RNA-binding protein dysregulation reveals a major impact on psychiatric disorder risk 96%
Similar papers in this journal
- Expanding the Genetic Architecture of Nicotine Dependence and its Shared Genetics with Multiple Traits: Findings from the Nicotine Dependence GenOmics (iNDiGO) Consortium 98%
- Whole Genome Sequencing Analysis Of Body Mass Index Identifies Novel African Ancestry-Specific Risk Allele 96%
- A blood- and brain-based EWAS of smoking 96%
Similar papers in this journal
- ExPRSweb - An Online Repository with Polygenic Risk Scores for Common Health-related Exposures 96%
- Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries 95%
- Brain eQTLs of European, African American, and Asian ancestry improve interpretation of schizophrenia GWAS 95%
Similar papers in this journal
- Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes 95%
- Variant-resolved prediction of context-specific isoform variation with a graph-based attention model 95%
- Characterizing the genetic architecture of drug response using gene-context interaction methods 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.