Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32 330 subjects from the International Cannabis Consortium.
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- Stringer, S; MinicΔ, C C; Verweij, K J H; Mbarek, H; Bernard, M; Derringer, J; van Eijk, K R; Isen, J D; Loukola, A; Maciejewski, D F; Mihailov, E; van der Most, P J; SΓ‘nchez-Mora, C; Roos, L; Sherva, R; Walters, R; Ware, J J; Abdellaoui, A; Bigdeli, T B; Branje, S J T; Brown, S A; Bruinenberg, M; Casas, M; Esko, T; Garcia-Martinez, I; Gordon, S D; Harris, J M; Hartman, C A; Henders, A K; Heath, A C; Hickie, I B; Hickman, M; Hopfer, C J; Hottenga, J J; Huizink, A C; Irons, D E; Kahn, R S; Korhonen, T; Kranzler, H R; Krauter, K; van Lier, P A C; Lubke, G H; Madden, P A F; MΓ€gi, R; McGue, M K; Medland, S E; Meeus, W H J; Miller, M B; Montgomery, G W; Nivard, M G; Nolte, I M; Oldehinkel, A J; Pausova, Z; Qaiser, B; Quaye, L; Ramos-Quiroga, J A; Richarte, V; Rose, R J; Shin, J; Stallings, M C; Stiby, A I; Wall, T L; Wright, M J; Koot, H M; Paus, T; Hewitt, J K; RibasΓ©s, M; Kaprio, J; Boks, M P; Snieder, H; Spector, T; MunafΓ², M R; Metspalu, A; Gelernter, J; Boomsma, D I; Iacono, W G; Martin, N G; Gillespie, N A; Derks, E M; Vink, J M
- Year
- 2016
- Journal
- Translational psychiatry
- PMID
- 27023175
- DOI
- 10.1038/tp.2016.36
- PMCID
- PMC4872459
Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40-48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32 330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13-20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 Γ 10(-8)) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.
The Manhattan (a) and the QQ plot (b) based on results of the gene-based analysis performed in the discovery sample using HYST (hybrid set-based test).
LLM interpretation
Figure (a) is a Manhattan plot showing $-\log_{10}(P)$ values across chromosomes, with significant peaks labeled for genes *KCNT2*, *CADM2*, *SCOC/SCOC-AS1*, and *NCAM1*. Figure (b) is a QQ plot comparing observed versus expected $-\log_{10}(P)$ values for the HYST set-based test (blue) and a gene-based test (magenta). In the QQ plot, both test curves deviate upward from the diagonal null line, indicating a higher-than-expected number of significant associations.
Forest plot for the top-SNP rs4471463 in the NCAM1 gene on chromosome 11. SNP, single-nucleotide polymorphism.
LLM interpretation
This is a forest plot showing the effect of the SNP rs4471463 (11:112983534 [T]) in the NCAM1 gene across 14 different samples and a final meta-analysis. The x-axis represents the log(Odds Ratio), with individual sample effects shown as points with 95% confidence interval bars. The meta-analysis result, indicated by a red diamond, shows a combined log(Odds Ratio) of -0.10 [-0.14, -0.06], which does not cross the zero line of no effect.
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| Citation | PMID | DOI | Status |
|---|---|---|---|
| Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE et al. An integrated map of genetic variation from 1092 human genomes. Nature 2012; 491: 56β65.2312822610.1038/nature11632PMC3498066 | β | β | β |
| Aggarwal SK, Carter GT, Sullivan MD, ZumBrunnen C, Morrill R, Mayer JD. Medicinal use of cannabis in the United States: historical perspectives, current trends, and future directions. J Opioid Manag 2009; 5: 153β168.1966292510.5055/jom.2009.0016 | β | β | β |
| Agrawal A, Lynskey MT, Hinrichs A, Grucza R, Saccone SF, Krueger R et al. A genome-wide association study of DSM-IV cannabis dependence. Addict Biol 2011; 16: 514β518.2166879710.1111/j.1369-1600.2010.00255.xPMC3117436 | β | β | β |
| Agrawal A, Lynskey MT, Pergadia ML, Bucholz KK, Heath AC, Martin NG et al. Early cannabis use and DSM-IV nicotine dependence: a twin study. Addiction 2008; 103: 1896β1904.1903253910.1111/j.1360-0443.2008.02354.xPMC2596656 | β | β | β |
| Agrawal A, Lynskey MT. Candidate genes for cannabis use disorders: findings, challenges and directions. Addiction 2009; 104: 518β532.1933565110.1111/j.1360-0443.2009.02504.xPMC2703791 | β | β | β |
| Agrawal A, Morley KI, Hansell NK, Pergadia ML, Montgomery GW, Statham DJ et al. Autosomal linkage analysis for cannabis use behaviors in Australian adults. Drug Alcohol Depend 2008; 98: 185β190.1860650310.1016/j.drugalcdep.2008.05.009PMC2584346 | β | β | β |
| Agrawal A, Neale MC, Jacobson KC, Prescott CA, Kendler KS. Illicit drug use and abuse/dependence: modeling of two-stage variables using the CCC approach. Addict Behav 2005; 30: 1043β1048.1589310210.1016/j.addbeh.2004.09.007 | β | β | β |
| Agrawal A, Pergadia ML, Saccone SF, Lynskey MT, Wang JC, Martin NG et al. An autosomal linkage scan for cannabis use disorders in the nicotine addiction genetics project. Arch Gen Psychiatry 2008; 65: 713β722.1851982910.1001/archpsyc.65.6.713 | β | β | β |
| Agrawal A, Silberg JL, Lynskey MT, Maes HH, Eaves LJ. Mechanisms underlying the lifetime co-occurrence of tobacco and cannabis use in adolescent and young adult twins. Drug Alcohol Depend 2010; 108: 49β55.2004780110.1016/j.drugalcdep.2009.11.016PMC2835808 | β | β | β |
| Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 1995; 57: 289β300. | β | β | β |
| Bidwell LC, McGeary JE, Gray JC, Palmer RH, Knopik VS, MacKillop J. NCAM1-TTC12-ANKK1-DRD2 variants and smoking motives as intermediate phenotypes for nicotine dependence. Psychopharmacology 2015; 232: 1177β1186.2527337510.1007/s00213-014-3748-2PMC4361268 | β | β | β |
| Bulik-Sullivan BK, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR et al. An atlas of genetic correlations across human diseases and traits. Nat Genet 2015; 47: 1236β1241.2641467610.1038/ng.3406PMC4797329 | β | β | β |
| Bulik-Sullivan BK, Loh PR, Finucane HK, Ripke S, Yang J. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet 2015; 47: 291β295.2564263010.1038/ng.3211PMC4495769 | β | β | β |
| Casey JP, Magalhaes T, Conroy JM, Regan R, Shah N, Anney R et al. A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder. Hum Genet 2012; 131: 565β579.2199675610.1007/s00439-011-1094-6PMC3303079 | β | β | β |
| Cressey D. The cannabis experiment. Nature 2015; 524: 280β283.2629508410.1038/524280a | β | β | β |
| De Alwis D, Agrawal A, Reiersen AM, Constantino JN, Henders A, Martin NG et al. ADHD symptoms, autistic traits, and substance use and misuse in adult Australian twins. J Stud Alcohol Drugs 2014; 75: 211β221.2465081410.15288/jsad.2014.75.211PMC3965675 | β | β | β |
| Ducci F, Kaakinen M, Pouta A, Hartikainen AL, Veijola J, Isohanni M et al. TTC12-ANKK1-DRD2 and CHRNA5-CHRNA3-CHRNB4 influence different pathways leading to smoking behavior from adolescence to mid-adulthood. Biol Psychiatry 2011; 69: 650β660.2116812510.1016/j.biopsych.2010.09.055PMC3058144 | β | β | β |
| Ehlers CL, Gilder DA, Gizer IR, Wilhelmsen KC. Heritability and a genome-wide linkage analysis of a Type II/B cluster construct for cannabis dependence in an American Indian community. Addict Biol 2009; 14: 338β348.1941356210.1111/j.1369-1600.2009.00160.xPMC2850263 | β | β | β |
| Ehlers CL, Gizer IR, Vieten C, Wilhelmsen KC. Linkage analyses of cannabis dependence, craving, and withdrawal in the San Francisco Family Study. Am J Med Genet B Neuropsychiatr Genet 2010; 153B: 802β811.1993797810.1002/ajmg.b.31050PMC2940710 | β | β | β |
| French L, Gray C, Leonard G, Perron M, Pike GB, Richer L et al. Early cannabis use, polygenic risk score for schizophrenia and brain maturation in adolescence. JAMA Psychiatry 2015; 72: 1002β1011.2630896610.1001/jamapsychiatry.2015.1131PMC5075969 | β | β | β |
| Furberg H, Kim Y, Dackor J, Boerwinkle E, Franceschini N, Ardissino D et al. Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat Genet 2010; 42: 441βU134.2041889010.1038/ng.571PMC2914600 | β | β | β |
| Gelernter J, Kranzler HR, Sherva R, Koesterer R, Almasy L, Zhao H et al. Genome-wide association study of opioid dependence: multiple associations mapped to calcium and potassium pathways. Biol Psychiatry 2014; 76: 66β74.2414388210.1016/j.biopsych.2013.08.034PMC3992201 | β | β | β |
| Gelernter J, Panhuysen C, Weiss R, Brady K, Poling J, Krauthammer M et al. Genomewide linkage scan for nicotine dependence: identification of a chromosome 5 risk locus. Biol Psychiatry 2007; 61: 119β126.1708150410.1016/j.biopsych.2006.08.023 | β | β | β |
| Gelernter J, Sherva R, Koesterer R, Almasy L, Zhao H, Kranzler HR et al. Genome-wide association study of cocaine dependence and related traits: FAM53B identified as a risk gene. Mol Psychiatry 2014; 19: 717β723.2395896210.1038/mp.2013.99PMC3865158 | β | β | β |
| Gelernter J, Yu Y, Weiss R, Brady K, Panhuysen C, Yang BZ et al. Haplotype spanning TTC12 and ANKK1, flanked by the DRD2 and NCAM1 loci, is strongly associated to nicotine dependence in two distinct American populations. Hum Mol Genet 2006; 15: 3498β3507.1708548410.1093/hmg/ddl426 | β | β | β |
| Gibbs M, Winsper C, Marwaha S, Gilbert E, Broome M, Singh SP. Cannabis use and mania symptoms: a systematic review and meta-analysis. J Affect Disord 2014; 171c: 39β47.10.1016/j.jad.2014.09.01625285897 | β | β | β |
| Gillespie NA, Lubke GH, Gardner CO, Neale MC, Kendler KS. Two-part random effects growth modeling to identify risks associated with alcohol and cannabis initiation, initial average use and changes in drug consumption in a sample of adult, male twins. Drug Alcohol Depend 2012; 123: 220β228.2217789610.1016/j.drugalcdep.2011.11.015PMC3442360 | β | β | β |
| Gillespie NA, Neale MC, Kendler KS. Pathways to cannabis abuse: a multi-stage model from cannabis availability, cannabis initiation and progression to abuse. Addiction 2009; 104: 430β438.1920735110.1111/j.1360-0443.2008.02456.xPMC2844887 | β | β | β |
| Grant JD, Lynskey MT, Scherrer JF, Agrawal A, Heath AC, Bucholz KK. A cotwin-control analysis of drug use and abuse/dependence risk associated with early-onset cannabis use. Addict Behav 2010; 35: 35β41.1971724210.1016/j.addbeh.2009.08.006PMC2799337 | β | β | β |
| Hall W, Babor TF. Cannabis use and public health: assessing the burden. Addiction 2000; 95: 485β490.1082932510.1046/j.1360-0443.2000.9544851.x | β | β | β |
| Hall W, Solowij N. Adverse effects of cannabis. Lancet 1998; 352: 1611β1616.984312110.1016/S0140-6736(98)05021-1 | β | β | β |
| Hall W. What has research over the past two decades revealed about the adverse health effects of recreational cannabis use? Addiction 2014; 110: 19β35.2528788310.1111/add.12703 | β | β | β |
| Haughey HM, Marshall E, Schacht JP, Louis A, Hutchison KE. Marijuana withdrawal and craving: influence of the cannabinoid receptor 1 (CNR1) and fatty acid amide hydrolase (FAAH) genes. Addiction 2008; 103: 1678β1686.1870568810.1111/j.1360-0443.2008.02292.xPMC2873690 | β | β | β |
| Hayatbakhsh MR, O'Callaghan MJ, Mamun AA, Williams GM, Clavarino A, Najman JM. Cannabis use and obesity and young adults. Am J Drug Alcohol Abuse 2010; 36: 350β356.2093699110.3109/00952990.2010.500438 | β | β | β |
| Hopfer CJ, Lessem JM, Hartman CA, Stallings MC, Cherny SS, Corley RP et al. A genome-wide scan for loci influencing adolescent cannabis dependence symptoms: evidence for linkage on chromosomes 3 and 9. Drug Alcohol Depend 2007; 89: 34β41.1716950410.1016/j.drugalcdep.2006.11.015PMC1892279 | β | β | β |
| Ibrahim-Verbaas CA, Bressler J, Debette S, Schuur M, Smith AV, Bis JC et al. GWAS for executive function and processing speed suggests involvement of the CADM2 gene. Mol Psychiatry 2015; 21: 189β197.2586980410.1038/mp.2015.37PMC4722802 | β | β | β |
| Kelleher LM, Stough C, Sergejew AA, Rolfe T. The effects of cannabis on information-processing speed. Addict Behav 2004; 29: 1213β1219.1523682510.1016/j.addbeh.2004.03.039 | β | β | β |
| Kendler KS, Karkowski LM, Corey LA, Prescott CA, Neale MC. Genetic and environmental risk factors in the aetiology of illicit drug initiation and subsequent misuse in women. Br J Psychiatry 1999; 175: 351β356.1078930310.1192/bjp.175.4.351 | β | β | β |
| Kendler KS, Schmitt E, Aggen SH, Prescott CA. Genetic and environmental influences on alcohol, caffeine, cannabis, and nicotine use from early adolescence to middle adulthood. Arch Gen Psychiatry 2008; 65: 674β682.1851982510.1001/archpsyc.65.6.674PMC2844891 | β | β | β |
| Laucht M, Becker K, Frank J, Schmidt MH, Esser G, Treutlein J et al. Genetic variation in dopamine pathways differentially associated with smoking progression in adolescence. J Am Acad Child Adolesc Psychiatry 2008; 47: 673β681.1843492110.1097/CHI.0b013e31816bff77 | β | β | β |
| Li MX, Gui HS, Kwan JS, Sham PC. GATES: a rapid and powerful gene-based association test using extended Simes procedure. Am J Hum Genet 2011; 88: 283β293.2139706010.1016/j.ajhg.2011.01.019PMC3059433 | β | β | β |
| Li MX, Kwan JS, Sham PC. HYST: a hybrid set-based test for genome-wide association studies, with application to protein-protein interaction-based association analysis. Am J Hum Genet 2012; 91: 478β488.2295890010.1016/j.ajhg.2012.08.004PMC3511992 | β | β | β |
| Lind PA, Macgregor S, Agrawal A, Montgomery GW, Heath AC, Martin NG et al. The role of GABRA2 in alcohol dependence, smoking, and illicit drug use in an Australian population sample. Alcohol Clin Exp Res 2008; 32: 1721β1731.1872768810.1111/j.1530-0277.2008.00768.xPMC2575093 | β | β | β |
| Liu JZ, Tozzi F, Waterworth DM, Pillai SG, Muglia P, Middleton L et al. Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nat Genet 2010; 42: 366β368.2041888910.1038/ng.572PMC3612983 | β | β | β |
| Lynskey MT, Vink JM, Boomsma DI. Early onset cannabis use and progression to other drug use in a sample of Dutch twins. Behav Genet 2006; 36: 195β200.1640228610.1007/s10519-005-9023-x | β | β | β |
| Manchia M, Cullis J, Turecki G, Rouleau GA, Uher R, Alda M. The impact of phenotypic and genetic heterogeneity on results of genome wide association studies of complex diseases. PLoS One 2013; 8: e76295.2414685410.1371/journal.pone.0076295PMC3795757 | β | β | β |
| Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ et al. Finding the missing heritability of complex diseases. Nature 2009; 461: 747β753.1981266610.1038/nature08494PMC2831613 | β | β | β |
| Mason JM, Arndt KM. Coiled coil domains: stability, specificity, and biological implications. Chembiochem 2004; 5: 170β176.1476073710.1002/cbic.200300781 | β | β | β |
| MinicΔ CC, Dolan CV, Hottenga J-J, Pool R, Fedko IO, Mbarek H et al. Heritability, SNP-and gene-based analyses of cannabis use initiation and age at onset. Behav Genet 2015; 45: 503β513, 1-11.2598750710.1007/s10519-015-9723-9PMC4561059 | β | β | β |
| Munafo M, Clark T, Johnstone E, Murphy M, Walton R. The genetic basis for smoking behavior: a systematic review and meta-analysis. Nicotine Tob Res 2004; 6: 583β597.1537015510.1080/14622200410001734030 | β | β | β |
| Nelson EC, Lynskey MT, Heath AC, Wray N, Agrawal A, Shand FL et al. ANKK1, TTC12, and NCAM1 polymorphisms and heroin dependence: importance of considering drug exposure. JAMA Psychiatry 2013; 70: 325β333.2330348210.1001/jamapsychiatry.2013.282PMC3789525 | β | β | β |
| Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81: 559β575.1770190110.1086/519795PMC1950838 | β | β | β |
| Radhakrishnan R, Wilkinson ST, D'Souza DC. Gone to pot: a review of the association between cannabis and psychosis. Front Psychiatry 2014; 5: 54.2490443710.3389/fpsyt.2014.00054PMC4033190 | β | β | β |
| Rubinek T, Yu R, Hadani M, Barkai G, Nass D, Melmed S et al. The cell adhesion molecules N-cadherin and neural cell adhesion molecule regulate human growth hormone: a novel mechanism for regulating pituitary hormone secretion. J Clin Endocrinol Metab 2003; 88: 3724β3730.1291566110.1210/jc.2003-030090 | β | β | β |
| Saccone SF, Hinrichs AL, Saccone NL, Chase GA, Konvicka K, Madden PAF et al. Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs. Hum Mol Genet 2007; 16: 36β49.1713527810.1093/hmg/ddl438PMC2270437 | β | β | β |
| Sham PC, Purcell SM. Statistical power and significance testing in large-scale genetic studies. Nat Rev Genet 2014; 15: 335β346.2473967810.1038/nrg3706 | β | β | β |
| So HC, Li M, Sham PC. Uncovering the total heritability explained by all true susceptibility variants in a genome-wide association study. Genet Epidemiol 2011; 35: 447β456.2161860110.1002/gepi.20593 | β | β | β |
| Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010; 42: 937β948.2093563010.1038/ng.686PMC3014648 | β | β | β |
| Sullivan PF, Daly MJ, O'Donovan M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet 2012; 13: 537β551.2277712710.1038/nrg3240PMC4110909 | β | β | β |
| Thorgeirsson TE, Gudbjartsson DF, Surakka I, Vink JM, Amin N, Geller F et al. Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior. Nat Genet 2010; 42: 448βU135.2041888810.1038/ng.573PMC3080600 | β | β | β |
| United Nations Office on Drugs and Crime. 2010 World Drug Report, New York, USA, 2010. | β | β | β |
| Verweij KJH, Vinkhuyzen AAE, Benyamin B, Lynskey MT, Quaye L, Agrawal A et al. The genetic aetiology of cannabis use initiation: a meta-analysis of genome-wide association studies and a SNP-based heritability estimation. Addict Biol 2013; 18: 846β850.2282312410.1111/j.1369-1600.2012.00478.xPMC3548058 | β | β | β |
| Verweij KJH, Zietsch BP, Liu JZ, Medland SE, Lynskey MT, Madden PAF et al. No association of candidate genes with cannabis use in a large sample of Australian twin families. Addict Biol 2012; 17: 687β690.2150715410.1111/j.1369-1600.2011.00320.xPMC3393887 | β | β | β |
| Verweij KJH, Zietsch BP, Lynskey MT, Medland SE, Neale MC, Martin NG et al. Genetic and environmental influences on cannabis use initiation and problematic use: a meta-analysis of twin studies. Addiction 2010; 105: 417β430.2040298510.1111/j.1360-0443.2009.02831.xPMC2858354 | β | β | β |
| Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw 2010; 36: 1β48. | β | β | β |
| Volkow ND, Compton WM, Weiss SR. Adverse health effects of marijuana use. N Engl J Med 2014; 371: 879.10.1056/NEJMc140792825162899 | β | β | β |
| Whiting PF, Wolff RF, Deshpande S, Di Nisio M, Duffy S, Hernandez AV et al. Cannabinoids for medical use: a systematic review and meta-analysis. JAMA 2015; 313: 2456β2473.2610303010.1001/jama.2015.6358 | β | β | β |
| Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 2010; 26: 2190β2191.2061638210.1093/bioinformatics/btq340PMC2922887 | β | β | β |
| Yang BZ, Kranzler HR, Zhao H, Gruen JR, Luo X, Gelernter J. Haplotypic variants in DRD2, ANKK1, TTC12, and NCAM1 are associated with comorbid alcohol and drug dependence. Alcohol Clin Exp Res 2008; 32: 2117β2127.1882880110.1111/j.1530-0277.2008.00800.xPMC2975565 | β | β | β |
| Yang BZ, Kranzler HR, Zhao HY, Gruen JR, Luo XG, Gelernter J. Association of haplotypic variants in DRD2, ANKK1, TTC12 and NCAM1 to alcohol dependence in independent case-control and family samples. Hum Mol Genet 2007; 16: 2844β2853.1776168710.1093/hmg/ddm240 | β | β | β |
| Yang JA, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 2011; 88: 76β82.2116746810.1016/j.ajhg.2010.11.011PMC3014363 | β | β | β |
In this knowledge base
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Genome-wide association studies of lifetime and frequency of cannabis use in 131,895 individuals. | Thorpe HHA et al. | β | 2026 | β |
| The genetics of cannabis lifetime use. | Bright U et al. | β | 2026 | β |
| Addiction Susceptibility: Genetic Factors, Personality Traits, and Epigenetic Interactions with the Gut Microbiome. | Borrego-Ruiz A et al. | β | 2025 | β |
| Externalizing as a common genetic influence for a broad spectrum of substance use and behavioral conditions: A developmental perspective from the Avon Longitudinal Study of Parents and Children. | Deng WQ et al. | β | 2025 | β |
| Genetically predicted endogenous sex hormone levels with risk of eczema or dermatitis. | Zeng M et al. | β | 2025 | β |
| The influence of genetics on the endocannabinoid system gene expression and relevance for targeting reproductive conditions. | Tanaka K et al. | β | 2025 | β |
| A Bivariate Twin Study of Lifetime cannabis Initiation and Lifetime Regular Tobacco Smoking Across Three Different Countries. | Zellers S et al. | β | 2024 | β |
| Cardiovascular Disease, Genetic Susceptibility, and Risk of Psychiatric Disorders and Suicide Attempt: A Community-Based Matched Cohort Study Based on the UK Biobank. | Yang J et al. | β | 2024 | β |
| COLOCdb: a comprehensive resource for multi-model colocalization of complex traits. | Pan S et al. | β | 2024 | β |
| Disease trajectory of high neuroticism and the relevance to psychiatric disorders: A retro-prospective cohort study. | Xia D et al. | β | 2024 | β |
| The genetic landscape of substance use disorders. | Gerring ZF et al. | β | 2024 | β |
| The Role of 3' Regulatory Region Flanking Kinectin 1 Gene in Schizophrenia. | Guo X et al. | β | 2024 | β |
| "Weeding out" violence? Translational perspectives on the neuropsychobiological links between cannabis and aggression. | Bortolato M et al. | β | 2024 | β |
| A latent class analysis of patterns of tobacco and cannabis use in Australia and their health-related correlates. | Lim CCW et al. | β | 2023 | β |
| An Individuality of Response to Cannabinoids: Challenges in Safety and Efficacy of Cannabis Products. | Kitdumrongthum S et al. | β | 2023 | β |
| A significant, functional and replicable risk KTN1 variant block for schizophrenia. | Mao Q et al. | β | 2023 | β |
| Assessing the associations between known genetic variants and substance use in people with HIV in the United States. | Haas CB et al. | β | 2023 | β |
| Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits. | Pan S et al. | β | 2023 | β |
| Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G). | Koellinger PD et al. | β | 2023 | β |
| Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries. | An U et al. | β | 2023 | β |
| Genetic Determinants of the Association between Osteoarthritis and Psychiatric Disorders. | Chen W et al. | β | 2023 | β |
| Genetics of cannabis use in opioid use disorder: A genome-wide association and polygenic risk score study. | Hillmer A et al. | β | 2023 | β |
| Invited Expert Opinion- Bioinformatic and Limitation Directives to Help Adopt Genetic Addiction Risk Screening and Identify Preaddictive Reward Dysregulation: Required Analytic Evidence to Induce Dopamine Homeostatsis. | Blum K et al. | β | 2023 | β |
| Lifetime cannabis use and childhood trauma associated with CNR1 genetic variants increase the risk of psychosis: findings from the STREAM study. | Loureiro CM et al. | β | 2023 | β |
| Polygenic contributions to performance on the Balloon Analogue Risk Task. | Nurmi EL et al. | β | 2023 | β |
| Suicidality risk after using cannabis and cannabinoids: An umbrella review. | Shamabadi A et al. | β | 2023 | β |
| Understanding the Mechanisms of Action and Effects of Drugs of Abuse. | CiucΔ Anghel DM et al. | β | 2023 | β |
| A Randomized Controlled Trial to Evaluate the Safety and Efficacy of a Novel Inhaled Biologic Therapeutic in Adults with Respiratory Distress Secondary to COVID-19 Infection. | Roshon M et al. | β | 2022 | β |
| Cannabis Use in Autism: Reasons for Concern about Risk for Psychosis. | Bortoletto R et al. | β | 2022 | β |
| Childhood maltreatment mediates the effect of the genetic background on psychosis risk in young adults. | Marchi M et al. | β | 2022 | β |
| Diminished Structural Brain Integrity in Long-term Cannabis Users Reflects a History of Polysubstance Use. | Knodt AR et al. | β | 2022 | β |
| Examining pathways between genetic liability for schizophrenia and patterns of tobacco and cannabis use in adolescence. | Jones HJ et al. | β | 2022 | β |
| Genetic predispositions to psychiatric disorders and the risk of COVID-19. | Chen W et al. | β | 2022 | β |
| Influences on the Genetic Relationship Between Cannabis Use and Schizophrenia: The Role of the Externalizing Spectrum. | Wormington B et al. | β | 2022 | β |
| Reward Deficiency Syndrome (RDS) Surprisingly Is Evolutionary and Found Everywhere: Is It "Blowin' in the Wind"? | Blum K et al. | β | 2022 | β |
| Strong and weak cross-inheritance of substance use disorders in a nationally representative sample. | Zhang H et al. | β | 2022 | β |
| The Autism-Psychosis Continuum Conundrum: Exploring the Role of the Endocannabinoid System. | Colizzi M et al. | β | 2022 | β |
| The genetic aetiology of cannabis use: from twin models to genome-wide association studies and beyond. | Verweij KJH et al. | β | 2022 | β |
| A Mapping Literature Review of Medical Cannabis Clinical Outcomes and Quality of Evidence in Approved Conditions in the USA from 2016 to 2019. | Jugl S et al. | β | 2021 | β |
| Associations between the CADM2 gene, substance use, risky sexual behavior, and self-control: A phenome-wide association study. | Arends RM et al. | β | 2021 | β |
| Cannabis use and cannabis use disorder. | Connor JP et al. | β | 2021 | β |
| Cannabis Use and the Risk of Cardiovascular Diseases: A Mendelian Randomization Study. | Zhao J et al. | β | 2021 | β |
| Cannabis use in college: Genetic predispositions, peers, and activity participation. | Thomas NS et al. | β | 2021 | β |
| Correlates of Cannabis Use Disorders among urban women of color: childhood abuse, relationship with spouse/partner, and media exposure. | Lee JY et al. | β | 2021 | β |
| Detection of altered methylation of MB-COMT promotor and DRD2 gene in cannabinoid or synthetic cannabinoid use disorder regarding gene variants and clinical parameters. | Oyaci Y et al. | β | 2021 | β |
| Genetic basis of cannabis use: a systematic review. | Hillmer A et al. | β | 2021 | β |
| Genetic Modulation of Initial Sensitivity to Ξ9-Tetrahydrocannabinol (THC) Among the BXD Family of Mice. | Parks C et al. | β | 2021 | β |
| Genetics of substance use disorders in the era of big data. | Gelernter J et al. | β | 2021 | β |
| Genome-wide association study of early-onset bipolar I disorder in the Han Taiwanese population. | Wu LS et al. | β | 2021 | β |
| Resource profile and user guide of the Polygenic Index Repository. | Becker J et al. | β | 2021 | β |
| Significant, replicable, and functional associations between KTN1 variants and alcohol and drug codependence. | Luo X et al. | β | 2021 | β |
| Sleep deficits and cannabis use behaviors: an analysis of shared genetics using linkage disequilibrium score regression and polygenic risk prediction. | Winiger EA et al. | β | 2021 | β |
| The intermediary role of adolescent temperamental and behavioral traits on the prospective associations between polygenic risk and cannabis use among young adults of European Ancestry. | Brick LA et al. | β | 2021 | β |
| Unraveling the Association Between Schizophrenia and Substance Use Disorder-Predictors, Mechanisms and Treatment Modifications: A Systematic Review. | Masroor A et al. | β | 2021 | β |
| Using Mendelian randomization analysis to better understand the relationship between mental health and substance use: a systematic review. | Treur JL et al. | β | 2021 | β |
| Attention-deficit/hyperactivity disorder and lifetime cannabis use: genetic overlap and causality. | Soler Artigas M et al. | β | 2020 | β |
| Cannabinoids and psychotic symptoms: A potential role for a genetic variant in the P2X purinoceptor 7 (P2RX7) gene. | Boks MP et al. | β | 2020 | β |
| Cannabis use, depression and self-harm: phenotypic and genetic relationships. | Hodgson K et al. | β | 2020 | β |
| Cocaine'omics: Genome-wide and transcriptome-wide analyses provide biological insight into cocaine use and dependence. | Huggett SB et al. | β | 2020 | β |
| Deconstructing the neurobiology of cannabis use disorder. | Ferland JN et al. | β | 2020 | β |
| Exploring Phenotypic and Genetic Overlap Between Cannabis Use and Schizotypy. | Vaissiere J et al. | β | 2020 | β |
| Genetic Associations Between Executive Functions and a General Factor of Psychopathology. | Harden KP et al. | β | 2020 | β |
| Genetic determinants of cannabis use: a systematic review protocol. | Hillmer A et al. | β | 2020 | β |
| Genome-wide DNA methylation analysis of heavy cannabis exposure in a New Zealand longitudinal cohort. | Osborne AJ et al. | β | 2020 | β |
| Identification of Functional Genetic Variants Associated With Alcohol Dependence and Related Phenotypes Using a High-Throughput Assay. | Thapa KS et al. | β | 2020 | β |
| <i>KTN1</i> Variants Underlying Putamen Gray Matter Volumes and Parkinson's Disease. | Mao Q et al. | β | 2020 | β |
| Onset of regular cannabis use and young adult insomnia: an analysis of shared genetic liability. | Winiger EA et al. | β | 2020 | β |
| Potential influence of socioeconomic status on genetic correlations between alcohol consumption measures and mental health. | Marees AT et al. | β | 2020 | β |
| Sex and Strain Variation in Initial Sensitivity and Rapid Tolerance to Ξ9-Tetrahydrocannabinol. | Parks C et al. | β | 2020 | β |
| Studying individual risk factors for self-harm in the UK Biobank: A polygenic scoring and Mendelian randomisation study. | Lim KX et al. | β | 2020 | β |
| A Contagion Model for Within-Family Transmission of Drug Abuse. | Kendler KS et al. | β | 2019 | β |
| Association between polygenic risk for tobacco or alcohol consumption and liability to licit and illicit substance use in young Australian adults. | Chang LH et al. | β | 2019 | β |
| Effects of DRD2 splicing-regulatory polymorphism and DRD4 48Β bp VNTR on crack cocaine addiction. | Stolf AR et al. | β | 2019 | β |
| Exploring the relationship between polygenic risk for cannabis use, peer cannabis use and the longitudinal course of cannabis involvement. | Johnson EC et al. | β | 2019 | β |
| Genetic and Environmental Risk Factors for Cannabis Use: Preliminary Results for the Role of Parental Care Perception. | Gerra MC et al. | β | 2019 | β |
| Genetic correlations of psychiatric traits with body composition and glycemic traits are sex- and age-dependent. | HΓΌbel C et al. | β | 2019 | β |
| Genetic determinants of beverage consumption: Implications for nutrition and health. | Cornelis MC | β | 2019 | β |
| Genetic Vulnerability for Smoking and Cannabis Use: Associations With E-Cigarette and Water Pipe Use. | Allegrini AG et al. | β | 2019 | β |
| Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. | Karlsson LinnΓ©r R et al. | β | 2019 | β |
| Genome-Wide Association Studies of Impulsive Personality Traits (BIS-11 and UPPS-P) and Drug Experimentation in up to 22,861 Adult Research Participants Identify Loci in the <i>CACNA1I</i> and <i>CADM2</i> genes. | Sanchez-Roige S et al. | β | 2019 | β |
| Genome-wide association study implicates CHRNA2 in cannabis use disorder. | Demontis D et al. | β | 2019 | β |
| GWAS of Behavioral Traits. | Mehta D et al. | β | 2019 | β |
| <i>CNR1</i> and <i>FAAH</i> variation and affective states induced by marijuana smoking. | Palmer RHC et al. | β | 2019 | β |
| Identifying Potential Causal Risk Factors for Self-Harm: A Polygenic Risk Scoring and Mendelian Randomisation Approach | Lim KX et al. | β | 2019 | β |
| Onset of regular cannabis use and adult sleep duration: Genetic variation and the implications of a predictive relationship. | Winiger EA et al. | β | 2019 | β |
| Psychosocial moderation of polygenic risk for cannabis involvement: the role of trauma exposure and frequency of religious service attendance. | Meyers JL et al. | β | 2019 | β |
| The Colorado Twin Registry: 2019 Update. | Corley RP et al. | β | 2019 | β |
| The <i>CADM2</i> gene is associated with processing speed performance - evidence among elderly with type 2 diabetes. | Greenbaum L et al. | β | 2019 | β |
| Tobacco and cannabis use in college students are predicted by sex-dimorphic interactions between MAOA genotype and child abuse. | Fite PJ et al. | β | 2019 | β |
| Associations between personality disorders and cannabis use and cannabis use disorder: a population-based twin study. | Gillespie NA et al. | β | 2018 | β |
| Cannabis use and risk of schizophrenia: a Mendelian randomization study. | Vaucher J et al. | β | 2018 | β |
| Genetic vulnerability to schizophrenia is associated with cannabis use patterns during adolescence. | Hiemstra M et al. | β | 2018 | β |
| Gene variants and educational attainment in cannabis use: mediating role of DNA methylation. | Gerra MC et al. | β | 2018 | β |
| Genome-wide analysis of self-reported risk-taking behaviour and cross-disorder genetic correlations in the UK Biobank cohort. | Strawbridge RJ et al. | β | 2018 | β |
| Genome-wide association meta-analysis of age at first cannabis use. | MinicΔ CC et al. | β | 2018 | β |
| Genome-wide association study identifies a novel locus for cannabis dependence. | Agrawal A et al. | β | 2018 | β |
| GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia. | Pasman JA et al. | β | 2018 | β |
| Human Genetics of Addiction: New Insights and Future Directions. | Hancock DB et al. | β | 2018 | β |
| Investigating causal associations between use of nicotine, alcohol, caffeine and cannabis: a two-sample bidirectional Mendelian randomization study. | Verweij KJH et al. | β | 2018 | β |
| Patterns and Correlates of Tobacco and Cannabis co-use by Tobacco Product Type: Findings from the Virginia Youth Survey. | Cobb CO et al. | β | 2018 | β |
| THC exposure of human iPSC neurons impacts genes associated with neuropsychiatric disorders. | Guennewig B et al. | β | 2018 | β |
| The Modulating Role of Sex and Anabolic-Androgenic Steroid Hormones in Cannabinoid Sensitivity. | Struik D et al. | β | 2018 | β |
| The Role of Cell Adhesion Molecule Genes Regulating Neuroplasticity in Addiction. | Muskiewicz DE et al. | β | 2018 | β |
| Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. | Walters RK et al. | β | 2018 | β |
| Using genetic data to strengthen causal inference in observational research. | Pingault JB et al. | β | 2018 | β |
| Whole genome sequence study of cannabis dependence in two independent cohorts. | Gizer IR et al. | β | 2018 | β |
| Assessing causality in associations between cannabis use and schizophrenia risk: a two-sample Mendelian randomization study. | Gage SH et al. | β | 2017 | β |
| Developmentally Specific Associations Between CNR1 Genotype and Cannabis Use Across Emerging Adulthood. | Ashenhurst JR et al. | β | 2017 | β |
| Evidence for the Risks and Consequences of Adolescent Cannabis Exposure. | Levine A et al. | β | 2017 | β |
| Genetic influences on the human oral microbiome. | Demmitt BA et al. | β | 2017 | β |
| Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112β117). | Clarke TK et al. | β | 2017 | β |
| <i>S100A10</i> identified in a genome-wide gene Γ cannabis dependence interaction analysis of risky sexual behaviours. | Polimanti R et al. | β | 2017 | β |
| Schizophrenia and substance use comorbidity: a genome-wide perspective. | Polimanti R et al. | β | 2017 | β |
| Short communication: Genetic association between schizophrenia and cannabis use. | Verweij KJ et al. | β | 2017 | β |
| The genetic basis of the comorbidity between cannabis use and major depression. | Hodgson K et al. | β | 2017 | β |
| The genetic epidemiology of substance use disorder: A review. | Prom-Wormley EC et al. | β | 2017 | β |
| Connecting the dots, genome-wide association studies in substance use. | Nivard MG et al. | β | 2016 | β |
| Genetic variation in FAAH is associated with cannabis use disorders in a young adult sample of Mexican Americans. | Melroy-Greif WE et al. | β | 2016 | β |