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Rare, low frequency and common coding variants in CHRNA5 and their contribution to nicotine dependence in European and African Americans

Molecular Psychiatry volume 21, pages 601–607 (2016)Cite this article

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Abstract

The common nonsynonymous variant rs16969968 in the α5 nicotinic receptor subunit gene (CHRNA5) is the strongest genetic risk factor for nicotine dependence in European Americans and contributes to risk in African Americans. To comprehensively examine whether other CHRNA5 coding variation influences nicotine dependence risk, we performed targeted sequencing on 1582 nicotine-dependent cases (Fagerström Test for Nicotine Dependence score⩾4) and 1238 non-dependent controls, with independent replication of common and low frequency variants using 12 studies with exome chip data. Nicotine dependence was examined using logistic regression with individual common variants (minor allele frequency (MAF)⩾0.05), aggregate low frequency variants (0.05>MAF⩾0.005) and aggregate rare variants (MAF<0.005). Meta-analysis of primary results was performed with replication studies containing 12 174 heavy and 11 290 light smokers. Next-generation sequencing with 180 × coverage identified 24 nonsynonymous variants and 2 frameshift deletions in CHRNA5, including 9 novel variants in the 2820 subjects. Meta-analysis confirmed the risk effect of the only common variant (rs16969968, European ancestry: odds ratio (OR)=1.3, P=3.5 × 10−11; African ancestry: OR=1.3, P=0.01) and demonstrated that three low frequency variants contributed an independent risk (aggregate term, European ancestry: OR=1.3, P=0.005; African ancestry: OR=1.4, P=0.0006). The remaining 22 rare coding variants were associated with increased risk of nicotine dependence in the European American primary sample (OR=12.9, P=0.01) and in the same risk direction in African Americans (OR=1.5, P=0.37). Our results indicate that common, low frequency and rare CHRNA5 coding variants are independently associated with nicotine dependence risk. These newly identified variants likely influence the risk for smoking-related diseases such as lung cancer.

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Acknowledgements

This work was supported by the National Institutes of Health: grant numbers T32GM07200, UL1TR000448, TL1TR000449 and F30AA023685 to EO; grant numbers K08 DA030398 and R01 DA038076 to LC; and grant number U19CA148172 to LJB. Grant number R01 HL118305 from the National Institutes of Health supported the replication analyses. Grants and contracts from the National Institutes of Health supported the following studies and groups: COGEND (P01CA89392), AAND (R01DA025888), CIDR (HHSN268201100011I), ARIC (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, HHSN268201100012C, R01HL087641, R01HL59367, R01HL086694, U01HG004402, HHSN268200625226C, UL1RR025005, 5RC2HL102419), CHS (HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, R01HL085251, R01HL068986, R01AG023629, UL1TR000124, DK063491), COGA (U10AA008401), FamHS (R01HL118305, R01DK089256), GENOA (HL054464, HL054457, HL054481, HL071917, NS041558, HL87660, HL119443, HL118305), HyperGEN (HL54471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515, R01HL55673, R01HL055673, R01HL118305, U01HL54473, R01HL055673, R01HL118305), JHS (HSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, HHSN268201300050C, HL103010, HL118305), MESA (N01HC95159, N01HC95160, N01HC95161, N01HC95162, N01HC95163, N01HC95164, N01HC95165, N01HC95166, N01HC95167, N01HC95168, N01HC95169, UL1TR000040, UL1RR025005, R01HL071051, R01HL071205, R01HL071250, R01HL071251, R01HL071252, R01HL071258, R01HL071259, UL1RR025005, N02HL64278, UL1TR000124, DK063491), WGHS (HL043851, HL080467, CA047988), WHI (HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSN271201100004C, R21HL123677, R01HL118305). Erasmus Rucphen Family Study was supported by the following grants: European Commission FP6 STRP grant number 018947 (LSHG-CT-2006-01947); European Community's Seventh Framework Program (FP7/2007–2013, HEALTH-F4-2007-201413); Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043); ZonMw grant (project 91111025). Rotterdam Study was supported by Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012). This study was also funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project nr. 050-060-810 and Netherlands Consortium for Healthy Ageing (NCHA). Please see Supplementary Materials for acknowledgements listed by study.

Author information

Authors and Affiliations

  1. Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA

    E Olfson, L-S Chen, L Fox, S Hartz, J Rice & L J Bierut

  2. Department of Genetics, Washington University School of Medicine, St Louis, MO, USA

    N L Saccone & S M Foltz

  3. Behavioral Health Epidemiology program, RTI International,, Research Triangle Park, NC, USA

    E O Johnson

  4. Department of Medicine and Division of Biostatistics, Washington University School of Medicine, St Louis, MO, USA

    R Culverhouse

  5. Center for Inherited Disease Research, Johns Hopkins University, Baltimore, MD, USA

    K Doheny, K Hetrick & B Marosy

  6. Department of Biostatistics, University of Washington, Seattle, WA, USA

    S M Gogarten, C C Laurie & K Rice

  7. Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands

    N Amin, C M van Duijn, O H Franco, A Hofman, A G Uitterlinden & D Vojinovic

  8. Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

    D Arnett

  9. Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY, USA

    R G Barr

  10. Departments of Medicine and Biostatistics, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA

    T M Bartz

  11. Department of Neurosciences, Icahn School of Medicine at Mt. Sinai, New York, NY, USA

    S Bertelsen, J-C Wang & A Goate

  12. Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St Louis, MO, USA

    I B Borecki & M F Feitosa

  13. Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA

    M R Brown, M L Grove & A C Morrison

  14. Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA

    D I Chasman, P M Ridker & L M Rose

  15. Harvard Medical School, Boston, MA, USA

    D I Chasman & P M Ridker

  16. University of Mississippi Medical Center, Jackson, MS, USA

    E R Fox & S K Musani

  17. Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA

    N Franceschini

  18. Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA

    X Guo & J Yao

  19. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA

    S L R Kardia, E B Ware & W Zhao

  20. Departments of Epidemiology, Cardiovascular Health Research Unit, Medicine and Health Services, University of Washington, Seattle, WA, USA

    B M Psaty

  21. Group Health Research Institute, Group Health, Seattle, WA, USA

    B M Psaty

  22. Division of Biostatistics, Washington University School of Medicine in St. Louis, St Louis, MO, USA

    D C Rao & K Schwander

  23. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    A P Reiner & U M Schick

  24. Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA

    A P Reiner

  25. Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands

    A G Uitterlinden

  26. Jackson State University, School of Public Service, Jackson, MS, USA

    G Wilson

  27. Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA

    N Breslau

  28. Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA

    D Hatsukami

  29. Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA

    J A Stitzel

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  1. E Olfson
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  2. N L Saccone
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  3. E O Johnson
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  18. S Bertelsen
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  29. A Hofman
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  42. D Vojinovic
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  47. W Zhao
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  48. N Breslau
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  49. D Hatsukami
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  50. J A Stitzel
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  51. J Rice
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  52. A Goate
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  53. L J Bierut
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Corresponding author

Correspondence to L J Bierut.

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Competing interests

LJB, AG and J-CW as well as the spouse of NLS are listed as inventors on Issued U.S. Patent 8,080,371, ‘Markers for Addiction’ covering the use of certain SNPs in determining the diagnosis, prognosis and treatment of addiction. JAS has received support from Pfizer, Inc. NA is supported by the Hersenstichting Nederland (project number F2013(1)-28). OHF works in ErasmusAGE, a center for aging research across the life course funded by Nestlé Nutrition (Nestec Ltd.), Metagenics Inc. and AXA. Nestlé Nutrition (Nestec Ltd.), Metagenics Inc. and AXA had no role in design and conduct of the study; collection, management, analysis and interpretation of the data; and preparation, review or approval of the manuscript. BMP serves on the DSMB of a clinical trial funded by the device manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson.

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Olfson, E., Saccone, N., Johnson, E. et al. Rare, low frequency and common coding variants in CHRNA5 and their contribution to nicotine dependence in European and African Americans. Mol Psychiatry 21, 601–607 (2016). https://doi.org/10.1038/mp.2015.105

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