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Meta-Analysis
. 2020 Dec;7(12):1032-1045.
doi: 10.1016/S2215-0366(20)30339-4. Epub 2020 Oct 20.

A large-scale genome-wide association study meta-analysis of cannabis use disorder

Emma C Johnson  1 Ditte Demontis  2 Thorgeir E Thorgeirsson  3 Raymond K Walters  4 Renato Polimanti  5 Alexander S Hatoum  6 Sandra Sanchez-Roige  7 Sarah E Paul  8 Frank R Wendt  5 Toni-Kim Clarke  9 Dongbing Lai  10 Gunnar W Reginsson  3 Hang Zhou  5 June He  6 David A A Baranger  11 Daniel F Gudbjartsson  12 Robbee Wedow  4 Daniel E Adkins  13 Amy E Adkins  13 Jeffry Alexander  14 Silviu-Alin Bacanu  14 Tim B Bigdeli  15 Joseph Boden  16 Sandra A Brown  17 Kathleen K Bucholz  6 Jonas Bybjerg-Grauholm  18 Robin P Corley  19 Louisa Degenhardt  20 Danielle M Dick  21 Benjamin W Domingue  22 Louis Fox  6 Alison M Goate  23 Scott D Gordon  24 Laura M Hack  25 Dana B Hancock  26 Sarah M Hartz  6 Ian B Hickie  27 David M Hougaard  18 Kenneth Krauter  28 Penelope A Lind  24 Jeanette N McClintick  29 Matthew B McQueen  30 Jacquelyn L Meyers  31 Grant W Montgomery  32 Ole Mors  33 Preben B Mortensen  34 Merete Nordentoft  35 John F Pearson  36 Roseann E Peterson  37 Maureen D Reynolds  38 John P Rice  6 Valgerdur Runarsdottir  39 Nancy L Saccone  40 Richard Sherva  41 Judy L Silberg  42 Ralph E Tarter  38 Thorarinn Tyrfingsson  39 Tamara L Wall  43 Bradley T Webb  14 Thomas Werge  44 Leah Wetherill  10 Margaret J Wright  45 Stephanie Zellers  46 Mark J Adams  9 Laura J Bierut  6 Jason D Boardman  47 William E Copeland  48 Lindsay A Farrer  41 Tatiana M Foroud  10 Nathan A Gillespie  37 Richard A Grucza  6 Kathleen Mullan Harris  49 Andrew C Heath  6 Victor Hesselbrock  50 John K Hewitt  19 Christian J Hopfer  51 John Horwood  16 William G Iacono  46 Eric O Johnson  26 Kenneth S Kendler  37 Martin A Kennedy  52 Henry R Kranzler  53 Pamela A F Madden  6 Hermine H Maes  42 Brion S Maher  54 Nicholas G Martin  24 Matthew McGue  46 Andrew M McIntosh  9 Sarah E Medland  24 Elliot C Nelson  6 Bernice Porjesz  31 Brien P Riley  14 Michael C Stallings  19 Michael M Vanyukov  38 Scott Vrieze  46 Psychiatric Genomics Consortium Substance Use Disorders WorkgroupLea K Davis  55 Ryan Bogdan  8 Joel Gelernter  56 Howard J Edenberg  57 Kari Stefansson  58 Anders D Børglum  2 Arpana Agrawal  6
Collaborators, Affiliations
Meta-Analysis

A large-scale genome-wide association study meta-analysis of cannabis use disorder

Emma C Johnson et al. Lancet Psychiatry. 2020 Dec.

Erratum in

  • Correction to Lancet Psychiatry 2020; 7: 1032-45.
    [No authors listed] [No authors listed] Lancet Psychiatry. 2022 Apr;9(4):e12. doi: 10.1016/S2215-0366(22)00065-7. Epub 2022 Feb 24. Lancet Psychiatry. 2022. PMID: 35219447 Free PMC article. No abstract available.

Abstract

Background: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.

Methods: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations.

Findings: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia.

Interpretation: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.

Funding: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

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Figures

Figure 1
Figure 1
Manhattan plot of the European ancestry-only genome-wide meta-analysis
Figure 2
Figure 2
Genetic correlations between CUD, cannabis use, and other traits of interest CUD=cannabis use disorder. GWAS=genome-wide association studies. rg=genetic correlation. *Significantly genetically correlated with CUD. †Significantly different correlations between CUD and cannabis use (α=0·002).
Figure 3
Figure 3
PheWAS associations between polygenic risk for CUD and phenotypes in the BioVU biobank The 46 phenotypes shown are significantly associated with CUD (p<3·74 × 10−5, corrected for 1335 phenotypes tested). CUD=cannabis use disorder. PheWAS=phenotype-wide association study. NOS=not otherwise specified. SIRS=systemic inflammatory response syndrome.
Figure 4
Figure 4
Polygenic risk score associations with white matter volume in drug-naive children Total white matter volume was regressed on polygenic risk scores for CUD and cannabis use (in separate models). CUD=cannabis use disorder.

Comment in

  • Using genetic information to inform policy on cannabis.
    Hines LA, Treur JL, Jones HJ, Sallis HM, Munafò MR. Hines LA, et al. Lancet Psychiatry. 2020 Dec;7(12):1002-1003. doi: 10.1016/S2215-0366(20)30377-1. Epub 2020 Oct 20. Lancet Psychiatry. 2020. PMID: 33096047 No abstract available.

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