Hostname: page-component-7c8c6479df-xxrs7 Total loading time: 0 Render date: 2024-03-19T07:33:33.474Z Has data issue: false hasContentIssue false

Overlap of heritable influences between cannabis use disorder, frequency of use and opportunity to use cannabis: trivariate twin modelling and implications for genetic design

Published online by Cambridge University Press:  13 March 2018

Lindsey A. Hines*
Affiliation:
Addictions Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England Centre for Adolescent Health, Royal Children's Hospital, Murdoch Children Research Institute, Parkville, Victoria, Australia
Katherine I. Morley
Affiliation:
Addictions Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Australia
Fruhling Rijsdijk
Affiliation:
Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
John Strang
Affiliation:
Addictions Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
Arpana Agrawal
Affiliation:
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
Elliot C. Nelson
Affiliation:
Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
Dixie Statham
Affiliation:
School of Social Sciences, University of the Sunshine Coast, Queensland, Australia
Nicholas G. Martin
Affiliation:
QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
Michael T. Lynskey
Affiliation:
Addictions Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
*
Author for correspondence: Lindsey A Hines, E-mail: lindsey.a.hines@kcl.ac.uk

Abstract

Background

The genetic component of Cannabis Use Disorder may overlap with influences acting more generally on early stages of cannabis use. This paper aims to determine the extent to which genetic influences on the development of cannabis abuse/dependence are correlated with those acting on the opportunity to use cannabis and frequency of use.

Methods

A cross-sectional study of 3303 Australian twins, measuring age of onset of cannabis use opportunity, lifetime frequency of cannabis use, and lifetime DSM-IV cannabis abuse/dependence. A trivariate Cholesky decomposition estimated additive genetic (A), shared environment (C) and unique environment (E) contributions to the opportunity to use cannabis, the frequency of cannabis use, cannabis abuse/dependence, and the extent of overlap between genetic and environmental factors associated with each phenotype.

Results

Variance components estimates were A = 0.64 [95% confidence interval (CI) 0.58–0.70] and E = 0.36 (95% CI 0.29–0.42) for age of opportunity to use cannabis, A = 0.74 (95% CI 0.66–0.80) and E = 0.26 (95% CI 0.20–0.34) for cannabis use frequency, and A = 0.78 (95% CI 0.65–0.88) and E = 0.22 (95% CI 0.12–0.35) for cannabis abuse/dependence. Opportunity shares 45% of genetic influences with the frequency of use, and only 17% of additive genetic influences are unique to abuse/dependence from those acting on opportunity and frequency.

Conclusions

There are significant genetic contributions to lifetime cannabis abuse/dependence, but a large proportion of this overlaps with influences acting on opportunity and frequency of use. Individuals without drug use opportunity are uninformative, and studies of drug use disorders must incorporate individual exposure to accurately identify aetiology.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agrawal, A and Lynskey, MT (2006) The genetic epidemiology of cannabis use, abuse and dependence. Addiction 101, 801812.Google Scholar
Agrawal, A, Neale, MC, Jacobson, KC, Prescott, CA and Kendler, KS (2005) Illicit drug use and abuse/dependence: modeling of two-stage variables using the CCC approach. Addictive Behaviors 30, 10431048.Google Scholar
American Psychiatric Association (2000) Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR, 4th edn., text revision. Washington DC: American Psychiatric Association.Google Scholar
American Psychiatric Association, DSM-5 Task Force (2013) Diagnostic and Statistical Manual of Mental Disorders: DSM-5. Arlington, VA: American Psychiatric Publishing.Google Scholar
Anthony, JC (2006) The epidemiology of Cannabis dependence. In Roffman, RA and Stephens, RS (eds). Cannabis Dependence: Its Nature, Consequences, and Treatment. New York: Cambridge University Press, pp. 58105.Google Scholar
Belsky, DW, Moffitt, TE, Baker, TB, Biddle, AK, Evans, JP, Harrington, H, et al. (2013) Polygenic risk and the developmental progression to heavy, persistent smoking and nicotine dependence: evidence from a 4-decade longitudinal study. JAMA Psychiatry 70, 534542.Google Scholar
Benyamina, A, Bonhomme-Faivre, L, Picard, V, Sabbagh, A, Richard, D, Blecha, L et al. (2009) Association between ABCB1 C3435T polymorphism and increased risk of cannabis dependence. Progress in Neuro-Psychopharmacology and Biological Psychiatry 33, 12701274.Google Scholar
Boker, SM, Neale, MC, Maes, HH, Wilde, MJ, Spiegel, M, Brick, TR et al. (2011) Openmx: an open source extended structural equation modeling framework. Psychometrika 76, 306317.Google Scholar
Broms, U, Silventoinen, K, Madden, PAF, Heath, AC and Kaprio, J (2006) Genetic architecture of smoking behavior: a study of Finnish adult twins. Twin Research and Human Genetics 9, 6472.Google Scholar
Bucholz, KK, Cadoret, R, Cloninger, CR, Dinwiddie, SH, Hesselbrock, VM, Nurnberger, J et al. (1994) A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA. Journal of Studies on Alcohol and Drugs 55, 149.Google Scholar
Cederlof, R, Friberg, L, Jonsson, E and Kaij, L (1961) Studies on similarity diagnosis in twins with the aid of mailed questionnaires. Acta Genetica Et Statistica Medica 11, 338362.Google Scholar
Chen, K, Kandel, DB and Davies, M (1997) Relationships between frequency and quantity of marijuana use and last year proxy dependence among adolescents and adults in the United States. Drug and Alcohol Dependence 46, 5367.Google Scholar
Darke, S (1998) Self-report among injecting drug users: a review. Drug and Alcohol Dependence 51, 253263.Google Scholar
Degenhardt, L, Whiteford, H and Hall, WD (2014) The global burden of disease projects: what have we learned about illicit drug use and dependence and their contribution to the global burden of disease? Drug and Alcohol Review 33, 412.Google Scholar
Dick, DM, Cho, SB, Latendresse, SJ, Aliev, F, Nurnberger, JI, Edenberg, HJ et al. (2014) Genetic influences on alcohol use across stages of development: GABRA2 and longitudinal trajectories of drunkenness from adolescence to young adulthood. Addiction Biology 19, 10551064.Google Scholar
Ensminger, ME, Juon, H-S and Green, KM (2007) Consistency between adolescent reports and adult retrospective reports of adolescent marijuana use: explanations of inconsistent reporting among an African American population. Drug & Alcohol Dependence 89, 1323.Google Scholar
Fowler, T, Lifford, K, Shelton, K, Rice, F, Thapar, A, Neale, MC et al. (2007) Exploring the relationship between genetic and environmental influences on initiation and progression of substance use. Addiction 102, 413422.Google Scholar
Gillespie, NA, Neale, MC, Jacobson, K and Kendler, KS (2009a) Modeling the genetic and environmental association between peer group deviance and cannabis use in male twins. Addiction 104, 420429.Google Scholar
Gillespie, NA, Neale, MC and Kendler, KS (2009b) Pathways to cannabis abuse: a multi-stage model from cannabis availability, cannabis initiation and progression to abuse. Addiction 104, 430438.Google Scholar
Hartman, CA, Hopfer, CJ, Haberstick, B, Rhee, SH, Crowley, TJ, Corley, RP et al. (2009) The association between cannabinoid receptor 1 gene (CNR1) and cannabis dependence symptoms in adolescents and young adults. Drug and Alcohol Dependence 104, 1116.Google Scholar
Hasin, DS, Saha, TD, Kerridge, BT, Goldstein, RB, Chou, SP, Zhang, H et al. (2015) Prevalence of marijuana use disorders in the United States between 2001–2002 and 2012–2013. JAMA Psychiatry 72, 12351242.Google Scholar
Heath, AC, Bucholz, KK, Madden, PA, Dinwiddie, SH, Slutske, WS, Bierut, LJ et al. (1997) Genetic and environmental contributions to alcohol dependence risk in a national twin sample: consistency of findings in women and men. Psychological Medicine 27, 13811396.Google Scholar
Heath, AC, Martin, NG, Lynskey, MT, Todorov, AA and Madden, PAF (2002) Estimating two-stage models for genetic influences on alcohol, tobacco or drug use initiation and dependence vulnerability in twin and family data. Twin Research: The Official Journal of the International Society for Twin Studies 5, 113124.Google Scholar
Hines, LA, Morley, KI, Mackie, C and Lynskey, M (2015a) Genetic and environmental interplay in adolescent substance use disorders. Current Addiction Reports 2, 122129.Google Scholar
Hines, LA, Morley, KI, Strang, J, Agrawal, A, Nelson, EC, Statham, D et al. (2015b) The association between speed of transition from initiation to subsequent use of cannabis and later problematic cannabis use, abuse and dependence. Addiction 110, 13111320.Google Scholar
Hines, LA, Morley, KI, Strang, J, Agrawal, A, Nelson, EC, Statham, D et al. (2016) Onset of opportunity to use cannabis and progression from opportunity to dependence: are influences consistent across transitions? Drug and Alcohol Dependence 160, 5764.Google Scholar
Hopfer, C (2014) Implications of marijuana legalization for adolescent substance use. Substance Abuse 35, 331335.Google Scholar
Johnson, TP and Mott, JA (2001) The reliability of self-reported age of onset of tobacco, alcohol and illicit drug use. Addiction (Abingdon, England) 96, 11871198.Google Scholar
Kasriel, J and Eaves, L (1976) The zygosity of twins: further evidence on the agreement between diagnosis by blood groups and written questionnaires. Journal of Biosocial Science 8, 263266.Google Scholar
Kendler, KS and Baker, JH (2007) Genetic influences on measures of the environment: a systematic review. Psychological Medicine 37, 615626.Google Scholar
Kendler, KS, Jacobson, KC, Prescott, CA and Neale, MC (2003) Specificity of genetic and environmental risk factors for use and abuse/dependence of cannabis, cocaine, hallucinogens, sedatives, stimulants, and opiates in male twins. American Journal of Psychiatry 160, 687695.Google Scholar
Kendler, KS, Neale, MC, Kessler, RC, Heath, AC and Eaves, LJ (1993) A test of the equal-environment assumption in twin studies of psychiatric illness. Behavior Genetics 23, 2127.Google Scholar
Kendler, KS, Neale, MC, Sullivan, P, Corey, LA, Gardner, CO and Prescott, CA (1999) A population-based twin study in women of smoking initiation and nicotine dependence. Psychological Medicine 29, 299308.Google Scholar
Kendler, KS, Pedersen, NL, Farahmand, BY and Persson, PG (1996) The treated incidence of psychotic and affective illness in twins compared with population expectation: a study in the Swedish Twin and Psychiatric Registries. Psychological Medicine 26, 11351144.Google Scholar
Laucht, M, Becker, K, Blomeyer, D and Schmidt, MH (2007) Novelty seeking involved in mediating the association between the dopamine D4 receptor gene exon III polymorphism and heavy drinking in male adolescents: results from a high-risk community sample. Biological Psychiatry 61, 8792.Google Scholar
Lynskey, MT and Agrawal, A (2009) Genetically informative studies of ‘environment’. Addiction 104, 439440.Google Scholar
Lynskey, MT, Agrawal, A, Henders, A, Nelson, EC, Madden, PAF and Martin, NG (2012) An Australian twin study of cannabis and other illicit drug use and misuse, and other psychopathology. Twin Research and Human Genetics 15, 631641.Google Scholar
Lynskey, MT, Heath, AC, Nelson, EC, Bucholz, KK, Madden, PAF, Slutske, WS et al. (2002) Genetic and environmental contributions to cannabis dependence in a national young adult twin sample. Psychological Medicine 32, 195207.Google Scholar
Malmberg, M, Overbeek, G, Monshouwer, K, Lammers, J, Vollebergh, WAM and Engels, RCME (2010) Substance use risk profiles and associations with early substance use in adolescence. Journal of Behavioral Medicine 33, 474485.Google Scholar
Morley, KI, Lynskey, MT, Madden, PAF, Treloar, SA, Heath, AC and Martin, NG (2007) Exploring the inter-relationship of smoking age-at-onset, cigarette consumption and smoking persistence: genes or environment? Psychological Medicine 37, 13571367.Google Scholar
Neale, M and Cardon, L (1992) Methodology for Genetic Studies of Twins and Families. Dordrecht, The Netherlands: Kluwer Academic Publications.Google Scholar
Neale, MC, Røysamb, E and Jacobson, K (2006) Multivariate genetic analysis of sex limitation and G × E interaction. Twin Research and Human Genetics: The Official Journal of the International Society for Twin Studies 9, 481489.Google Scholar
Nelson, EC, Lynskey, MT, Heath, AC, Wray, N, Agrawal, A, Shand, FL et al. (2013) ANKK1, TTC12, and NCAM1 polymorphisms and heroin dependence: importance of considering drug exposure. JAMA Psychiatry 70, 325333.Google Scholar
Neumark, Y, Lopez-Quintero, C and Bobashev, G (2012) Drug use opportunities as opportunities for drug use prevention: Bogota, Colombia a case in point. Drug and Alcohol Dependence 122, 127134.Google Scholar
Pagan, JL, Rose, RJ, Viken, RJ, Pulkkinen, L, Kaprio, J and Dick, DM (2006) Genetic and environmental influences on stages of alcohol use across adolescence and into young adulthood. Behavior Genetics 36, 483497.Google Scholar
Parra, GR, O'Neill, SE and Sher, KJ (2003) Reliability of self-reported age of substance involvement onset. Psychology of Addictive Behaviors 17, 211218.Google Scholar
Plomin, R, DeFries, JC, Knopik, VS and Neiderheiser, J (2013) Behavioral Genetics, 6th edn. New York: Worth Publishers.Google Scholar
R Core Team (2013) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.Google Scholar
Reboussin, BA, Ialongo, NS and Green, KM (2015) Influences of behavior and academic problems at school entry on marijuana use transitions during adolescence in an African American sample. Addictive Behaviors 41, 5157.Google Scholar
Reinartz, WJ, Haenlein, M and Henseler, J (2009) An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM. Rochester, NY: Social Science Research Network. SSRN Scholarly Paper 27 August no. ID 1462666.Google Scholar
Sarna, S, Kaprio, J, Sistonen, P and Koskenvuo, M (1978) Diagnosis of twin zygosity by mailed questionnaire. Human Heredity 28, 241254.Google Scholar
Sartor, CE, Lynskey, MT, Bucholz, KK, Madden, PAF, Martin, NG and Heath, AC (2009) Timing of first alcohol use and alcohol dependence: evidence of common genetic influences. Addiction 104, 15121518.Google Scholar
Sartor, CE, Lynskey, MT, Heath, AC, Jacob, T and True, W (2007) The role of childhood risk factors in initiation of alcohol use and progression to alcohol dependence. Addiction 102, 216225.Google Scholar
Shi, Y, Lenzi, M and An, R (2015) Cannabis liberalization and adolescent cannabis use: a cross-national study in 38 countries. PLoS ONE 10, e0143562.Google Scholar
Shillington, AM, Cottler, LB, Mager, DE and Compton, WM III (1995) Self-report stability for substance use over 10 years: data from the St. Louis epidemiologic catchment study. Drug and Alcohol Dependence 40, 103109.Google Scholar
Storr, CL, Wagner, FA, Chen, CY and Anthony, JC (2011) Childhood predictors of first chance to use and use of cannabis by young adulthood. Drug and Alcohol Dependence 117, 715.Google Scholar
Verweij, KJH, Zietsch, BP, Lynskey, MT, Medland, SE, Neale, MC, Martin, NG et al. (2010) Genetic and environmental influences on cannabis use initiation and problematic use: a meta-analysis of twin studies. Addiction 105, 417430.Google Scholar
Wagner, FA and Anthony, JC (2002) Into the world of illegal drug use: exposure opportunity and other mechanisms linking the use of alcohol, tobacco, marijuana, and cocaine. Journal of Epidemiology 155, 918925.Google Scholar
Ystrom, E, Reichborn-Kjennerud, T, Neale, MC and Kendler, KS (2014) Genetic and environmental risk factors for illicit substance use and use disorders: joint analysis of self and co-twin ratings. Behavior Genetics 44, 113.Google Scholar
Supplementary material: File

Hines et al. supplementary material 1

Hines et al. supplementary material

Download Hines et al. supplementary material 1(File)
File 13 KB