Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-25T02:01:57.680Z Has data issue: false hasContentIssue false
  • English
  • Français

The gene–environmental architecture of the development of adolescent substance use

Published online by Cambridge University Press:  19 February 2018

Frank Vitaro ,
Daniel J. Dickson ,
Mara Brendgen ,
Brett Laursen ,
Ginette Dionne  and
Michel Boivin
Frank Vitaro*
Affiliation:
School of Psycho-Education, University of Montreal, Montreal, Canada
Daniel J. Dickson
Affiliation:
Department of Psychology, Florida Atlantic University, Boca Raton, USA
Mara Brendgen
Affiliation:
Department of Psychology, University of Quebec at Montreal, Montreal, Canada
Brett Laursen
Affiliation:
Department of Psychology, Florida Atlantic University, Boca Raton, USA
Ginette Dionne
Affiliation:
School of Psychology, Laval University, Quebec City, Canada
Michel Boivin
Affiliation:
School of Psychology, Laval University, Quebec City, Canada
*
Author for correspondence: Frank Vitaro, E-mail: frank.vitaro@umontreal.ca
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Using a longitudinal twin design and a latent growth curve/autoregressive approach, this study examined the genetic–environmental architecture of substance use across adolescence.

Methods

Self-reports of substance use (i.e. alcohol, marijuana) were collected at ages 13, 14, 15, and 17 years from 476 twin pairs (475 boys, 477 girls) living in the Province of Quebec, Canada. Substance use increased linearly across the adolescent years.

Results

ACE modeling revealed that genetic, as well as shared and non-shared environmental factors explained the overall level of substance use and that these same factors also partly accounted for growth in substance use from age 13 to 17. Additional genetic factors predicted the growth in substance use. Finally, autoregressive effects revealed age-specific non-shared environmental influences and, to a lesser degree, age-specific genetic influences, which together accounted for the stability of substance use across adolescence.

Conclusions

The results support and expand the notion that genetic and environmental influences on substance use during adolescence are both developmentally stable and developmentally dynamic.

Keywords

Adolescencegenetic and environmental influencesgrowth curve modelingsubstance usetwin design
Type
Original Articles
Information
Psychological Medicine , Volume 48 , Issue 15 , November 2018 , pp. 2500 - 2507
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.)

Footnotes

None of the authors declares any conflict of interest. Frank Vitaro wrote the first draft of this manuscript. No honorarium, grant, or other form of payment was given to anyone to produce the manuscript.

References

Baker, JH, Maes, HH and Kendler, KS (2012) Shared environmental contributions to substance use. Behavior Genetics 42, 345–353.Google Scholar
Baker, JH, Maes, HH, Larsson, H, Lichtenstein, P and Kendler, KS (2011) Sex differences and developmental stability in genetic and environmental influences on psychoactive substance consumption from early adolescence to young adulthood. Psychological Medicine 41, 1907–1916.Google Scholar
Bezdjian, S, Baker, LA and Tuvblad, C (2011) Genetic and environmental influences on impulsivity: a meta-analysis of twin, family and adoption studies. Clinical Psychology Review 31, 1209–1223.Google Scholar
Boivin, M, Brendgen, M, Dionne, G, Dubois, L, Pérusse, D, Robaey, P et al. (2013) The Quebec newborn twin study into adolescence: 15 years later. Twin Research and Human Genetics 16, 64–69.Google Scholar
Boomsma, DI and Molenaar, PCM (1987) The genetic-analysis of repeated measures. 1. Simplex models. Behavior Genetics 17, 111–123.Google Scholar
Colder, CR, Campbell, RT, Ruel, E, Richardson, JL and Flay, BR (2002) A finite mixture model of growth trajectories of adolescent alcohol use: predictors and consequences. Journal of Consulting and Clinical Psychology 70, 976–985.Google Scholar
Duncan, SC and Duncan, TE (1996) A multivariate latent growth curve analysis of adolescent substance Use. Structural Equation Modeling – a Multidisciplinary Journal 3, 323–347.Google Scholar
Eaves, LJ, Long, J and Heath, AC (1986) A theory of developmental-change in quantitative phenotypes applied to cognitive-development. Behavior Genetics 16, 143–162.Google Scholar
Eaves, LJ, Gillespie, N and Verhulst, B (2016) Developmental Models. Power point presentation. Virginia Institute for Psychiatric and Behavioral Genetics. Available at http://ibg.colorado.edu/cdrom2016/gillespie/Development/Gillespie2016_Developmental_Models.pdf (Accessed 15 September 2017).Google Scholar
Edwards, AC and Kendler, KS (2013) Alcohol consumption in men is influenced by qualitatively different genetic factors in adolescence and adulthood. Psychological Medicine 43, 1857–1868.Google Scholar
Falconer, DS (1960) Introduction to Quantitative Genetics. New York, NY: Ronald Press.Google Scholar
Gillespie, NA, Eaves, LJ, Maes, H and Silberg, JL (2015) Testing models for the contributions of genes and environment to developmental change in adolescent depression. Behavior Genetics 45, 382–393.Google Scholar
Goldsmith, HH (1991) A zygosity questionnaire for young twins: a research note. Behavior Genetics 21, 257–269.Google Scholar
Han, C, McGue, MK and Iacono, WG (1999) Lifetime tobacco, alcohol and other substance use in adolescent Minnesota twins: univariate and multivariate behavioral genetic analyses. Addiction 94, 981–993.Google Scholar
Henly, GA and Winters, KC (1989) Development of psychosocial scales for the assessment of adolescent involved with alcohol and drugs. The International Journal of the Addictions 24, 973–1001.Google Scholar
Hingson, RW, Heeren, T and Winter, MR (2006) Age at drinking onset and alcohol dependence – age at onset, duration, and severity. Archives of Pediatrics & Adolescent Medicine 160, 739–746.Google Scholar
Hopfer, CJ, Crowley, TJ and Hewitt, JK (2003) Review of twin and adoption studies of adolescent substance use. Journal of the American Academy of Child & Adolescent Psychiatry 42, 710–719.Google Scholar
Jacobus, J, Bava, S, Cohen-Zion, M, Mahmood, O and Tapert, SF (2009) Functional consequences of marijuana use in adolescents. Pharmacology Biochemistry and Behavior 92, 559–565.Google Scholar
Johnston, LD, O'Malley, PM, Bachman, JG and Schulenberg, JE (2015) Monitoring the Future National Survey Results on Drug use, 1975–2014. Volume I: Secondary School Students. Ann Arbor, MI: Institute for Social Research, The University of Michigan.Google Scholar
Kendler, KS, Jacobson, KC, Gardner, CO, Gillespie, N, Aggen, SA and Prescott, CA (2007) Creating a social world – a developmental twin study of peer-group deviance. Archives of General Psychiatry 64, 958–965.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, 687–695.Google Scholar
Kendler, KS, Schmitt, E, Aggen, SH and Prescott, CA (2008) Genetic and environmental influences on alcohol, caffeine, cannabis, and nicotine use from early adolescence to middle adulthood. Archives of General Psychiatry 65, 674–682.Google Scholar
Koopmans, JR, van Doornen, LJP and Boomsma, DI (1997) Association between alcohol use and smoking in adolescent and young adult twins: a bivariate genetic analysis. Alcoholism-Clinical and Experimental Research 21, 537–546.Google Scholar
Krueger, RF, Hicks, BM, Patrick, CJ, Carlson, SR, Iacono, WG and McGue, M (2002) Etiologic connections among substance dependence, antisocial behavior, and personality: modeling the externalizing spectrum. Journal of Abnormal Psychology 111, 411–424.Google Scholar
Krueger, RF, Markon, KE, Patrick, CJ, Benning, SD and Kramer, MD (2007) Linking antisocial behavior, substance use, and personality: an integrative quantitative model of the adult externalizing spectrum. Journal of Abnormal Psychology 116, 645–666.Google Scholar
Long, EC, Verhulst, B, Aggen, SH, Kendler, KS and Gillespie, NA (2017) Contributions of genes and environment to developmental change in alcohol use. Behavior Genetics 47, 498–506.Google Scholar
Lynskey, MT, Agrawal, A and Heath, AC (2010) Genetically informative research on adolescent substance use: methods, findings, and challenges. Journal of the American Academy of Child & Adolescent Psychiatry 49, 1202–1214.Google Scholar
MacKillop, J (2013) Integrating behavioral economics and behavioral genetics: delayed reward discounting as an endophenotype for addictive disorders. Journal of Experimental Analysis of Behavior 99, 14–31.Google Scholar
Magnusson, PKE, Almqvist, C, Rahman, I, Ganna, A, Viktorin, A, Walum, H et al. (2013) The Swedish twin registry: establishment of a biobank and other recent developments. Twin Research and Human Genetics 16, 317–329.Google Scholar
Malone, SM, Taylor, J, Marmorstein, NR, McGue, M and Iacono, WG (2004) Genetic and environmental influences on antisocial behavior and alcohol dependence from adolescence to early adulthood. Development and Psychopathology 16, 943–966.Google Scholar
Martino, SC, Ellickson, PL and McCaffrey, DE (2008) Developmental trajectories of substance use from early to late adolescence: a comparison of rural and urban youth. Journal of Studies on Alcohol and Drugs 69, 430–440.Google Scholar
McArdle, JJ (2009) Latent variable modeling of differences and changes with longitudinal data. Annual Review of Psychology 60, 577–605.Google Scholar
Miech, RA, Johnston, LD, O'Malley, PM, Bachman, JG, Schulenberg, JE and Patrick, ME (2017) Monitoring the Future National Survey Results on Drug use, 1975–2016: Volume I, Secondary School Students. Ann Arbor, MI: Institute for Social Research, The University of Michigan.Google Scholar
Muthén, LK and Muthén, BO (1998–2017) MPlus User's Guide, 8th edn. Los Angeles, CA: Muthén & Muthén.Google Scholar
Neale, MC and Cardon, LR (1992) Methodology for Genetic Studies in Twins and Families. Boston, MA: Kluwer Academic Publishers.Google Scholar
Peleg-Oren, N, Saint-Jean, G, Cardenas, GA, Tammara, H and Pierre, C (2009) Drinking alcohol before age 13 and negative outcomes in late adolescence. Alcoholism, Clinical and Experimental Research 33, 1966–1972.Google Scholar
Sartor, CE, Grant, JD, Bucholz, KK, Madden, PAF, Heath, AC, Agrawal, A et al. (2010) Common genetic contributions to alcohol and cannabis use and dependence symptomatology. Alcoholism-Clinical and Experimental Research 34, 545–554.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, 216–225.Google Scholar
Spitz, E, Moutier, R, Reed, T, Busnel, MC, Marchaland, C, Roubertoux, PL et al. (1996) Comparative diagnoses of twin zygosity by SSLP variant analysis, questionnaire, and dermatoglyphic analysis. Behavior Genetics 26, 55–63.Google Scholar
Swendsen, J, Burstein, M, Case, B, Conway, KP, Dierker, L, He, JP et al. (2012) Use and abuse of alcohol and illicit drugs in US adolescents results of the national comorbidity survey-adolescent supplement. Archives of General Psychiatry 69, 390–398.Google Scholar
Viken, RJ, Kaprio, J, Koskenvuo, M, and Rose, RJ (1999) Longitudinal analyses of the determinants of drinking and of drinking to intoxication in adolescent twins. Behavior Genetics 29, 455–461.Google Scholar
Winters, KC, Stinchfield, RD, Henly, GA and Schwartz, RH (1990–91) Validity of adolescent self-report of alcohol and other drug involvement. The International Journal of the Addictions 25, 1379–1395.Google Scholar
Young, SE, Rhee, SH, Stallings, MC, Corley, RP and Hewitt, JK (2006) Genetic and environmental vulnerabilities underlying adolescent substance use and problem use: general or specific? Behavior Genetics 36, 603–615.Google Scholar