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Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes

Author

Listed:
  • Sylvanus Toikumo

    (Crescenz VAMC
    University of Pennsylvania Perelman School of Medicine)

  • Mariela V. Jennings

    (University of California San Diego)

  • Benjamin K. Pham

    (University of California San Diego)

  • Hyunjoon Lee

    (Vanderbilt University Medical Center)

  • Travis T. Mallard

    (Massachusetts General Hospital
    Harvard Medical School
    Massachusetts General Hospital
    Broad Institute of MIT and Harvard)

  • Sevim B. Bianchi

    (University of California San Diego)

  • John J. Meredith

    (University of California San Diego)

  • Laura Vilar-Ribó

    (Universitat Autònoma de Barcelona)

  • Heng Xu

    (University of California San Diego)

  • Alexander S. Hatoum

    (Washington University in St. Louis)

  • Emma C. Johnson

    (Washington University in St. Louis)

  • Vanessa K. Pazdernik

    (Mayo Clinic)

  • Zeal Jinwala

    (University of Pennsylvania Perelman School of Medicine)

  • Shreya R. Pakala

    (University of California San Diego)

  • Brittany S. Leger

    (University of California San Diego
    University of California San Diego)

  • Maria Niarchou

    (Vanderbilt University)

  • Michael Ehinmowo

    (University of Ibadan)

  • Greg D. Jenkins

    (Mayo Clinic)

  • Anthony Batzler

    (Mayo Clinic)

  • Richard Pendegraft

    (Mayo Clinic)

  • Abraham A. Palmer

    (University of California San Diego
    University of California San Diego)

  • Hang Zhou

    (Yale University School of Medicine
    Veterans Affairs Connecticut Healthcare System)

  • Joanna M. Biernacka

    (Mayo Clinic
    Mayo Clinic)

  • Brandon J. Coombes

    (Mayo Clinic)

  • Joel Gelernter

    (Yale University School of Medicine
    Veterans Affairs Connecticut Healthcare System)

  • Ke Xu

    (Yale University School of Medicine
    Veterans Affairs Connecticut Healthcare System)

  • Dana B. Hancock

    (RTI International)

  • Nancy J. Cox

    (Vanderbilt University Medical Center)

  • Jordan W. Smoller

    (Massachusetts General Hospital
    Harvard Medical School
    Massachusetts General Hospital
    Broad Institute of MIT and Harvard)

  • Lea K. Davis

    (Vanderbilt University Medical Center
    Vanderbilt University
    Vanderbilt University Medical Center)

  • Amy C. Justice

    (Veterans Affairs Connecticut Healthcare System
    Yale University School of Public Health
    Yale University School of Medicine)

  • Henry R. Kranzler

    (Crescenz VAMC
    University of Pennsylvania Perelman School of Medicine)

  • Rachel L. Kember

    (Crescenz VAMC
    University of Pennsylvania Perelman School of Medicine)

  • Sandra Sanchez-Roige

    (University of California San Diego
    Vanderbilt University
    University of California San Diego)

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.

Suggested Citation

  • Sylvanus Toikumo & Mariela V. Jennings & Benjamin K. Pham & Hyunjoon Lee & Travis T. Mallard & Sevim B. Bianchi & John J. Meredith & Laura Vilar-Ribó & Heng Xu & Alexander S. Hatoum & Emma C. Johnson , 2024. "Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes," Nature Human Behaviour, Nature, vol. 8(6), pages 1177-1193, June.
  • Handle: RePEc:nat:nathum:v:8:y:2024:i:6:d:10.1038_s41562-024-01851-6
    DOI: 10.1038/s41562-024-01851-6
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