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

Nature Human Behaviour (2024)Cite this article

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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.

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Fig. 1: Overview of the cohorts, analysis pipeline and genetic correlations among the sites.
Fig. 2: Manhattan and porcupine plots for the TUD-multi meta-analysis and ancestry-specific GWAS.
Fig. 3: Integration with functional genomic data implicated 461 unique TUD candidate risk genes.
Fig. 4: Sankey diagram showing drug-repurposing results from S-PrediXcan brain tissues.
Fig. 5: FDR-significant genetic correlations between TUD-EUR and 113 complex traits, including smoking and related phenotypes.
Fig. 6: Phenome-wide association studies of TUD PGS.

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Data availability

Summary statistics can be accessed at the PsycheMERGE website (https://psychemerge.com) or by emailing the corresponding author (sanchezroige@ucsd.edu). The following datasets were retrieved for secondary analyses: Ensembl build 85 (https://www.ebi.ac.uk/about/news/updates-from-data-resources/ensembl-version-85/), Msigdb v.7.0 (https://data.broadinstitute.org/gsea-msigdb/msigdb/release/7.0/), Genotype–Tissue Expression (GTEx) v.8 project database (https://www.gtexportal.org/), PredictDB Data Repository (http://predictdb.hakyimlab.org/), BrainQTL (http://predictdb.hakyimlab.org/), BrainXcan database (https://zenodo.org/record/4895174), LINCs L1000 database (https://commonfund.nih.gov/LINCS), Drug Gene Interaction Database (https://repo-hub.broadinstitute.org/repurposing#download-data), 1000 Genomes Project phase 3 (https://internationalgenome.org/data-portal/sample), BrainSpan (http://www.brainspan.org/), H-MAGMA four Hi-C datasets provided with the software (https://github.com/thewonlab/H-MAGMA/tree/master/Input_Files) and PredictDB Data Repository (http://predictdb.org/).

Code availability

All software used to generate results has been previously published and corresponding citations are provided in Methods; that is, SAIGE v.0.44.6.5, PLINK v.1.9/v.2.080, LDSC v.1.0.1, cov-LDSC (https://github.com/yang-luo-lab/cov-ldsc), METAL 2020-05-05 (https://github.com/statgen/METAL), FUMA v.1.3.6a (https://fuma.ctglab.nl/), COJO in GCTA v.1.94.1, FINEMAP v.1.4.2, PAINTOR v.3.1, MAGMA v.1.08, H-MAGMA v.1.08, S-MultiXcan v.0.7.0, S-PrediXcan v.0.6.2, BrainXcan (https://github.com/hakyimlab/brainxcan), metafor package (v.3.8-1), DRUGSETS (https://github.com/nybell/drugsets), POPCORN (https://github.com/brielin/Popcorn), mtCOJO in GCTA v.1.94.1, cluster package v.2.1.4, PheWAS package v.0.12, LDpred2 from the bigsnpr package v.1.10.4, PRS-CS/PRS-CSx v.1.0.0 (https://github.com/getian107) and MendelianRandomization package v.0.9.0.

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Acknowledgements

M.V.J., S.B.B., S.R.P. and S.S.-R. were supported by funds from the California Tobacco-Related Disease Research Program (grant nos T29KT0526 and T32IR5226). S.B.B. was also supported by P50DA037844. B.K.P., J.J.M. and S.S.-R. were supported by NIH/NIDA DP1DA054394. A.S.H. was supported by NIAAA AA030083. T.T.M. was supported by NHGRI T32HG010464. E.C.J. was supported by K01DA051759. J.G. was supported by VA Merit Award CX001849-01 and 5R01DA054869. D.B.H. was supported by R01 DA042090 and R01 DA051913. L.K.D. was supported by R01 MH113362. H.R.K. was supported by the Veterans Integrated Service Network 4 Mental Illness Research, Education and Clinical Center. R.L.K. was supported by NIAAA K01 AA028292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. CTSA (SD, Vanderbilt Resources): The project described was supported by the National Center for Research Resources, grant UL1RR024975-01 and is now at the National Center for Advancing Translational Sciences, grant 2 UL1TR000445-06. BioVU: The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center’s BioVU which is supported by numerous sources: institutional funding, private agencies and federal grants. These include the NIH funded Shared Instrumentation grant S10RR025141; and CTSA grants UL1TR002243, UL1TR000445 and UL1RR024975. Genomic data are also supported by investigator-led projects that include U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962 amd R01HD074711; and additional funding sources listed at https://victr.vumc.org/biovu-funding/. This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration and was supported by funding from the Department of Veterans Affairs Office of Research and Development, Million Veteran Program grant no. I01 BX004820. This publication does not represent the views of the Department of Veterans Affairs or the United States Government. We acknowledge the Penn Medicine BioBank and the Mayo Clinic Biobank for providing data and thank the patient-participants of Penn Medicine and Mayo Clinic who consented to participate in this research programme. We also thank the Penn Medicine BioBank team and Regeneron Genetics Center for providing genetic variant data for analysis. The PMBB is approved under IRB protocol no. 813913 and supported by Perelman School of Medicine at University of Pennsylvania, a gift from the Smilow family and the National Center for Advancing Translational Sciences of the NIH under CTSA award no. UL1TR001878. Data used in the preparation of this article were obtained from the ABCD study (https://abcdstudy.org), held in the NIMH Data Archive. This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 years and follow them over 10 years into early adulthood. The ABCD study is supported by the NIH and additional federal partners under award nos. U01DA041022, U01DA041028, U01DA041048, U01DA041089, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147, U01DA041093 and U01DA041025. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/Consortium_Members. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. We also thank the Externalizing Consortium for sharing the GWAS summary statistics of externalizing. The Externalizing Consortium comprises: principal investigators D. M. Dick, P. Koellinger, K. P. Harden, A A.P.; lead analysts R. K. Linnér, T.T.M., P. B. Barr and S.S.-R; contributor I. D. Waldman. The Externalizing Consortium has been supported by the National Institute on Alcohol Abuse and Alcoholism (R01AA015416—administrative supplement) and the National Institute on Drug Abuse (R01DA050721). Additional funding for investigator effort has been provided by K02AA018755, U10AA008401 and P50AA022537, as well as a European Research Council Consolidator grant (647648 EdGe to P. Koellinger). The content is solely the responsibility of the authors and does not necessarily represent the official views of the above funding bodies. The Externalizing Consortium would like to thank the following groups for making the research possible: 23andMe, Add Health, Vanderbilt University Medical Center’s BioVU, Collaborative Study on the Genetics of Alcoholism (COGA), the Psychiatric Genomics Consortium’s SUDs working group, UK10K Consortium, UK Biobank and Philadelphia Neurodevelopmental Cohort. We thank B. Quach and J. Marks for their help in supplying portions of the data needed to create Supplementary Fig. 1.

Author information

Author notes

  1. These authors contributed equally: Sylvanus Toikumo, Mariela V. Jennings.

  2. Full lists of members and their affiliations appear in the Supplementary Information.

Authors and Affiliations

  1. Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA

    Sylvanus Toikumo, Henry R. Kranzler & Rachel L. Kember

  2. Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA

    Sylvanus Toikumo, Zeal Jinwala, Henry R. Kranzler & Rachel L. Kember

  3. Department of Psychiatry, University of California San Diego, La Jolla, CA, USA

    Mariela V. Jennings, Benjamin K. Pham, Sevim B. Bianchi, John J. Meredith, Heng Xu, Shreya R. Pakala, Brittany S. Leger, Abraham A. Palmer & Sandra Sanchez-Roige

  4. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA

    Hyunjoon Lee & Lea K. Davis

  5. Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA

    Travis T. Mallard & Jordan W. Smoller

  6. Department of Psychiatry, Harvard Medical School, Boston, MA, USA

    Travis T. Mallard & Jordan W. Smoller

  7. Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA

    Travis T. Mallard & Jordan W. Smoller

  8. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA

    Travis T. Mallard & Jordan W. Smoller

  9. Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain

    Laura Vilar-Ribó

  10. Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA

    Alexander S. Hatoum & Emma C. Johnson

  11. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA

    Vanessa K. Pazdernik, Greg D. Jenkins, Anthony Batzler, Richard Pendegraft, Joanna M. Biernacka & Brandon J. Coombes

  12. Program in Biomedical Sciences, University of California San Diego, La Jolla, CA, USA

    Brittany S. Leger

  13. Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA

    Maria Niarchou, Lea K. Davis & Sandra Sanchez-Roige

  14. Department of Psychology, University of Ibadan, Ibadan, Nigeria

    Michael Ehinmowo

  15. Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA

    Abraham A. Palmer & Sandra Sanchez-Roige

  16. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA

    Hang Zhou, Joel Gelernter & Ke Xu

  17. Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA

    Hang Zhou, Joel Gelernter, Ke Xu & Amy C. Justice

  18. Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA

    Joanna M. Biernacka

  19. RTI International, Research Triangle Park, NC, USA

    Dana B. Hancock

  20. Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA

    Nancy J. Cox & Lea K. Davis

  21. Yale University School of Public Health, New Haven, CT, USA

    Amy C. Justice

  22. Yale University School of Medicine, New Haven, CT, USA

    Amy C. Justice

Authors
  1. Sylvanus Toikumo
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Consortia

Penn Medicine BioBank

  • Sylvanus Toikumo
  • , Rachel L. Kember

  • Million Veteran Program

    • Sylvanus Toikumo
    • , Hang Zhou
    • , Joel Gelernter
    • , Amy C. Justice
    • , Henry R. Kranzler
    •  & Rachel L. Kember

  • PsycheMERGE Substance Use Disorder Workgroup

    • Sylvanus Toikumo
    • , Mariela V. Jennings
    • , Hyunjoon Lee
    • , Travis T. Mallard
    • , Laura Vilar-Ribó
    • , Alexander S. Hatoum
    • , Maria Niarchou
    • , Brandon J. Coombes
    • , Jordan W. Smoller
    • , Lea K. Davis
    • , Rachel L. Kember
    •  & Sandra Sanchez-Roige

Contributions

S.S.-R. conceived the idea for the paper and wrote and edited the paper. S.T., M.V.J., B.K.P., H.L., T.T.M., S.B.B., L.V.-R., H.X., A.S.H., J.J.M., V.K.P., B.J.C. and R.LK. provided analyses. E.C.J., G.D.J., A.B., R.P., J.M.B., J.W.S., L.K.D., A.C.J. and R.L.K. contributed data. All contributing authors wrote and edited the paper.

Corresponding author

Correspondence to Sandra Sanchez-Roige.

Ethics declarations

Competing interests

J.W.S. is a member of the Scientific Advisory Board of Sensorium Therapeutics (with equity) and has received grant support from Biogen. He is Principal Investigator of a collaborative study of the genetics of depression and bipolar disorder sponsored by 23andMe for which 23andMe provides analysis time as in-kind support but no payments. H.R.K. is a member of advisory boards for Clearmind Medicine, Dicerna Pharmaceuticals, Sophrosyne Pharmaceuticals and Enthion Pharmaceuticals; a consultant to Sobrera Pharmaceuticals; the recipient of research funding and medication supplies for an investigator-initiated study from Alkermes; a member of the American Society of Clinical Psychopharmacology’s Alcohol Clinical Trials Initiative, which was supported in the last 3 years by Alkermes, Dicerna, Ethypharm, Lundbeck, Mitsubishi, Otsuka and Pear Therapeutics; and, with J.G., is a holder of US patent 10,900,082 titled: ‘Genotype-guided dosing of opioid agonists’ issued 26 January 2021. The other authors declare no competing interests.

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Supplementary information

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Additional authors and contributions, Supplementary Methods and Figs. 1–9.

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Toikumo, S., Jennings, M.V., Pham, B.K. et al. Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes. Nat Hum Behav (2024). https://doi.org/10.1038/s41562-024-01851-6

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