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Parent and peer influences on emerging adult substance use disorder: A genetically informed study

Published online by Cambridge University Press:  12 January 2016

Kaitlin Bountress ,
Laurie Chassin  and
Kathryn Lemery-Chalfant
Kaitlin Bountress*
Affiliation:
Medical University of South Carolina
Laurie Chassin
Affiliation:
Arizona State University
Kathryn Lemery-Chalfant
Affiliation:
Arizona State University
*
Address correspondence and reprint requests to: Kaitlin Bountress, National Crime Victim Research and Treatment Center, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, 67 President Street, Charleston, SC 29425; E-mail: bountres@musc.edu.
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Abstract

The present study utilizes longitudinal data from a high-risk community sample to examine the unique effects of genetic risk, parental knowledge about the daily activities of adolescents, and peer substance use on emerging adult substance use disorders (SUDs). These effects are examined over and above a polygenic risk score. In addition, this polygenic risk score is used to examine gene–environment correlation and interaction. The results show that during older adolescence, higher adolescent genetic risk for SUDs predicts less parental knowledge, but this relation is nonsignificant in younger adolescence. Parental knowledge (using mother report) mediates the effects of parental alcohol use disorder (AUD) and adolescent genetic risk on risk for SUD, and peer substance use mediates the effect of parent AUD on offspring SUD. Finally, there are significant gene–environment interactions such that, for those at the highest levels of genetic risk, less parental knowledge and more peer substance use confers greater risk for SUDs. However, for those at medium and low genetic risk, these effects are attenuated. These findings suggest that the evocative effects of adolescent genetic risk on parenting increase with age across adolescence. They also suggest that some of the most important environmental risk factors for SUDs exert effects that vary across level of genetic propensity.

Type
Regular Articles
Information
Development and Psychopathology , Volume 29 , Special Issue 1: Developmental and Social–Ecological Perspectives on Children, Political Violence, and Armed Conflict , February 2017 , pp. 121 - 142
Copyright
Copyright © Cambridge University Press 2016 

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References

Abar, C., & Turrisi, R. (2008). How important are parents during the college years? A longitudinal perspective of indirect influences parents yield on their college teens’ alcohol use. Addictive Behaviors, 33, 1360–1368.Google Scholar
Agrawal, A., Balasubramanian, S., Smith, E. K., Pamela, A. F., Bucholz, K. K., Heath, A. C., et al. (2010). Peer substance involvement modifies genetic influences on regular substance involvement in young women. Addiction, 105, 1844–1853.Google Scholar
Avinum, R., & Knafo, A. (2013). Parenting as a reaction evoked by children's genotype: A meta-analysis of children-as-twins studies. Personality and Social Psychology, 18, 86–103.Google Scholar
Beaver, K. M., Shutt, J. E., Boutwell, B. B., Ratchford, M., Roberts, K., & Barnes, J. C. (2009). Genetic and environmental influences on levels of self-control and delinquent peer affiliation: Results from a longitudinal sample of adolescent twins. Criminal Justice and Behavior, 36, 41–60.Google Scholar
Bierut, L. J. (2011). Genetic vulnerability and susceptibility to substance dependence. Neuron Cell Press, 69, 618–627.Google Scholar
Borsari, B., & Carey, K. B. (2001). Peer influences on college drinking: A review of the research. Journal of Substance Abuse, 13, 391–424.CrossRefGoogle ScholarPubMed
Brady, K. T., & Sinha, R. (2005). Co-occurring mental and substance use disorders: The neurobiological effects of chronic stress. American Journal of Psychiatry, 162, 1483–1493.Google Scholar
Brody, G. H., Chen, Y., & Beach, S. R. H. (2013). Differential suceptibility to prevention: GABAergic, dopaminergic, and multilocus effects. Journal of Child Psychology and Psychiatry, 54, 1–9.Google Scholar
Chassin, L., Barrera, M., Bech, K., & Kossak-Fuller, J. (1992). Recruiting a community sample of adolescent children of alcoholics: A comparison of three subject sources. Journal of Studies on Alcohol and Drugs, 53, 316–319.Google Scholar
Chassin, L., Lee, M., Cho, Y., Wang, F. L., Agrawal, A., Sher, K. J., et al. (2012). Testing multiple levels of influence in the intergenerational transmission of alcohol disorders from a developmental perspective: The example of alcohol using peers and mu-opioid reception M1 variation. Development and Psychopathology, 24, 953–967.Google Scholar
Chassin, L., Pillow, D. R., Curran, P. J., Molina, B. S., & Barrera, M. (1993). Relations of parental alcoholism to early adolescent substance use: A test of three mediating mechanisms. Journal of Abnormal Psychology, 102, 3–19.Google Scholar
Christakis, N. A., & Fowler, J. H. (2014). Friendship and natural selection. Proceedings of the National Academy of Sciences, 111, 10796–10801.Google Scholar
Cohen, J., Cohen, P., West, S., & Aiken, L. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.Google Scholar
Costa, B., Giagnoni, G., & Colleoni, M. (2000). Precipitated and spontaneous withdrawal in rats tolerant to anandamide. Psychopharmacology, 149, 121–128.Google Scholar
Crosnoe, J., & Johnson, M. (2011). Research on adolescence in the twenty-first century. Annual Review of Sociology, 37, 439–460.Google Scholar
Davis, C., & Loxton, N. J. (2013). Addictive behaviors and addiction-prone personality traits: Associations with a dopamine multilocus genetic profile. Addictive Behaviors, 38, 2306–2312.Google Scholar
Derringer, J., Krueger, R. F., Dick, D. M., Aliev, F., Grucza, R. A., Saccone, S., et al. (2012). The aggregate effect of dopamine genes on dependence symptoms among cocaine users: Cross-validation of a candidate system scoring approach. Behavior Genetics, 42, 626–635.Google Scholar
Dick, D. M. (2011). Gene–environment interaction in psychological traits and disorders. Annual Review of Clinical Psychology, 7, 383–409.CrossRefGoogle ScholarPubMed
Dick, D. M., Agrawal, A., Keller, M. C., Adkina, A., Aliev, F., Monroe, S., et al. (2015). Candidate gene–environment interaction research: Reflections and recommendations. Perspectives on Psychological Science, 10, 37–59.CrossRefGoogle ScholarPubMed
Dick, D. M., Wang, J. C., Plunkett, J., Aliev, F., Hinrichs, A., Bertelsen, S., et al. (2007). Family-based association analyses of alcohol dependence phenotypes across DRD2 and neighboring gene ANKK1. Alcoholism: Clinical and Experimental Research, 31, 1645–1653.CrossRefGoogle ScholarPubMed
Dishion, T. J., Capaldi, D., Spracklin, K. M., & Li, F. (1995). Peer ecology of male adolescent drug use. Development and Psychopathology, 7, 803–824.Google Scholar
Dishion, T. J., Nelson, S. N., & Bullock, B. M. (2004). Premature adolescent autonomy: Parent disengagement and deviant peer process in the amplification of problem behavior. Journal on Adolescence, 27, 515–530.Google Scholar
Dishion, T. J., & Owen, L. (2002). A longitudinal analysis of friendships and substance use: Bidirectional influence from adolescence to adulthood. Developmental Psychology, 38, 480–491.CrossRefGoogle ScholarPubMed
Ehlers, C. L., Lind, P. A., & Wilhelmsen, K. C. (2008). Association between single nucleotide polymorphisms in the mu opioid receptor gene (OPRM1) and self-reported responses to alcohol in American Indians. BioMed Central Medical Genetics, 9, 1–11.Google Scholar
Enders, K. E., & Bandalos, D. L. (2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 8, 430–457.Google Scholar
Endicott, J., Andreason, N., & Spitzer, R. (1975). Family history research diagnostic criteria. New York: New York State Psychiatric Institute, Biometrics Research Department.Google Scholar
Enoch, M., Hodgkinson, C. A., Yuan, Q., Shen, P., Goldman, D., & Roy, A. (2010). The influence of GABRA2, childhood trauma, and their interaction of alcohol, heroin, and cocaine dependence. Biological Psychiatry, 1, 20–27.Google Scholar
Foley, P. F., Loh, E. W., Innes, D. J., Williams, S. M., Tannenberg, A. E. G., Harper, C. G., et al. (2004). Association studies of neurotransmitter gene polymorphisms in alcoholic Caucasians. Annals New York Academy of Science, 1025, 39–46.CrossRefGoogle ScholarPubMed
Fowler, J. H., Settle, J. E., & Christakis, N. A. (2011). Correlated genotypes in friendship networks. Proceedings of the National Academy of Sciences, 108, 1993–1997.Google Scholar
Fowler, T., Shelton, K., Lifford, K., Rice, F., McBride, A., Ivan, N., et al. (2007). Genetic and environmental influences on the relationship between peer alcohol use and own alcohol use in adolescents. Addiction, 102, 894–903.Google Scholar
Granic, I., Dishion, T. J., Hollenstein, T., & Patterson, G. R. (2003). Longitudinal analysis of flexibility and reorganization in early adolescence: A dynamic systems study of family interactions. Developmental Psychology, 39, 606–617.CrossRefGoogle ScholarPubMed
Hartman, C. A., Hopfer, C. J., Haberstick, B., Rhee, S. H., Crowley, T. J., Corley, R. P., 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, 11–16.Google Scholar
Haworth, C. M. A., Wright, M. J., Luciano, M., Martin, N. G., Geus, E. J. C., Beijsterveldt, C. E. M., et al. (2009). The heritability of general cognitive ability increases linearly from childhood to young adulthood. Molecular Psychiatry, 15, 1112–1120.Google Scholar
Hicks, B. M., Krueger, R. F., Iacano, W. G., McGue, M., & Patrick, C. J. (2004). Family transmission and heritability of externalizing disorders. Archives of General Psychiatry, 61, 922–928.Google Scholar
Hicks, B. M., South, S. C., DiRago, A. C., Iacano, W. G., & McGue, M. (2009). Environmental adversity and increasing genetic risk for externalizing disorders. Journal of the American Medical Association Psychiatry, 66, 640–648.Google Scholar
Hu, L., & Bentler, A. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.Google Scholar
Iervolino, A. C., Pike, A., Manke, B., Reiss, D., Hetherington, E. M., & Plomin, R. (2002). Genetic and environmental influences in adolescent peer socialization: Evidence from two genetically sensitive designs. Child Development, 73, 162–174.Google Scholar
Johnston, L. D., O'Malley, P. M., & Bachman, J. G. (1988). National Survey Results on Drug Use, 1975–1983. Washington, DC: National Institute on Drug Abuse.Google Scholar
Keller, M. (2014). Gene x environment interaction studies have not properly controlled for potential confounders: The problem and the (simple) solution. Biological Psychiatry, 75, 18–24.Google Scholar
Kendler, K. S., Chen, X., Dick, D., Maes, H., Gillespie, N., Neale, M. C., et al. (2012). Recent advances in the genetic epidemiology and molecular genetics of substance use disorders. Nature Neuroscience, 15, 181–189.Google Scholar
Kendler, K. S., Jacobsen, K. C., Gardner, C. O., Gillespie, N., Aggen, S. A., & Prescott, C. A. (2007). Creating a social world. A developmental twin study of peer-group deviance. Archives of General Psychiatry, 64, 938–965.Google Scholar
Kerr, M., & Stattin, H. (2003). Parenting of adolescents: Action or reaction? In Crouter, A. C. & Booth, A. (Eds.), Children's influence on family dynamics: The neglected side of family relationships (pp. 121–151). Mahwah, NJ: Erlbaum.Google Scholar
Kerr, M., Stattin, H., & Burke, W. J. (2010). A reinterpretation of parental monitoring in longitudinal perspective. Journal of Research on Adolescence, 20, 39–64.Google Scholar
Kerr, M., Stattin, H., & Pakalniskiene, V. (2008). Parents react to adolescent problem behaviors by worrying more and monitoring less. What can parents do? New insights into the role of parents in adolescent problem behaviors. London: Wiley.Google Scholar
Klahr, A. M., & Burt, A. (2014). Elucidating the etiology of individual differences in parenting: A meta-analysis of behavioral genetic research. Psychological Bulletin, 140, 544–586.Google Scholar
Koob, G. F. (1992). Drugs of abuse: Anatomy, pharmacology, and function of reward pathways. Trends in Pharmacological Sciences, 13, 177–184.Google Scholar
Lac, A., & Crano, W. D. (2009). Monitoring matters: Meta-analytic review reveals the reliable linkage of parental monitoring with adolescent marijuana use. Perspectives on Psychological Science, 4, 578–586.Google Scholar
Latendresse, S. J., Rose, R. J., Viken, R. J., Pulkkinen, L., Kaprio, J., & Dick, D. M. (2008). Parenting mechanisms in links between parents’ and adolescents’ alcohol use behaviors. Alcoholism: Clinical and Experimental Research, 32, 322–330.Google Scholar
Liu, J., Zhou, Z., Hodgkinson, C. A., Yuan, Q., Shen, P., Mulligan, C. J., et al. (2011). Haplotype-based study of the association of alcohol-metabolizing genes with alcohol dependence in four independent populations. Alcoholism: Clinical and Experimental Research, 35, 304–316.Google Scholar
MacGregor, S., Lind, P. A., Bucholz, K. K., Hansell, N. K., Madden, P. A. F., Richter, M. M., et al. (2008). Associations of ADH and ALDH2 gene variation with self-report alcohol reactions, consumption and dependence: An integrated analysis. Human Molecular Genetics, 18, 580–593.CrossRefGoogle ScholarPubMed
Miranda, R., Reynolds, E., Ray, L., Justus, A., Knopik, V. S., McGeary, J., et al. (2012). Preliminary evidence for a gene-environment interaction in predicting alcohol use disorders in adolescents. Alcoholism: Clinical and Experimental Research, 37, 325–331.Google Scholar
Morrison, A. C., Bare, L. A., Chambless, L .E., Ellis, S. G., Malloy, M., Kane, J. P., et al. (2007). Prediction of coronary heart disease using a genetic risk score: The atherosclerosis risk in communities study. American Journal of Epidemiology, 166, 28–35 Google Scholar
Muthén, B. O., & Muthén, L. K. (1998–2011). Mplus: Computer software and manual (Version 6.1) [Computer software]. Los Angeles: Author.Google Scholar
Muthén, B. O., & Satorra, A. (1995). Complex sample data in structural equation modeling. Sociological Methodology, 25, 267–316.CrossRefGoogle Scholar
Plomin, R., DeFries, J., & Loehlin, J. (1977). Genotype-environment interaction and correlation in the analysis of human behavior. Psychological Bulletin, 84, 309–322.Google Scholar
Plomin, R., Reiss, D., Hetherington, E. M., & Howe, G. W. (1994). Nature and nurture: Genetic contributions to measures of the family environment. Developmental Psychology, 30, 32–43.Google Scholar
Plomin, R., & Simpson, M. A. (2013). The future of genomics and developmentalists. Development and Psychopathology, 25, 1263–1278.Google Scholar
Preuss, U. W., Koller, G., Zill, P., Bondy, B., & Soyka, M. (2003). Alcoholism-related phenotypes and genetic variants of the CB1 receptor. European Archives of Psychiatry and Clinical Neuroscience, 253, 275–280.Google Scholar
Reiss, D., Neiderhiser, J. M., Hetherington, E. M., & Plomin, R. (2000). The relationship code: Deciphering genetic and social influences on adolescent development. Cambridge, MA: Harvard University Press.Google Scholar
Rice, F., Lewis, G., Harold, G. T., & Thapar, A. (2013). Examining the role of passive gene–environment correlation in childhood depression using a novel genetically sensitive design. Development and Psychopathology, 25, 37–50.Google Scholar
Robins, L. N., Helzer, J. E., Croughan, J., & Ratcliff, K. S. (1981). National Institute of Mental Health Diagnostic Interview Schedule: Its history, characteristics, and validity. Archives of General Psychiatry, 38, 381–389.Google Scholar
Salvatore, J., Aliev, F., Bucholz, K., Agrawal, A., Hesselbrock, V., Hesselbrock, M., et al. (2014). Polygenic risk for externalizing disorders: Gene-by-development and gene-by-environment effects in adolescents and young adults. Clinical Psychological Science, 2, 1–13.Google Scholar
Salvatore, J. E., & Dick, D. M. (2015). Gene-environment interplay: Where we are, where we are going. Journal of Marriage and Family, 77, 344–350.Google Scholar
Scarr, S., & McCartney, K. (1983). How people make their own environments: A theory of genotype-environment effects. Child Development, 54, 424–435.Google Scholar
Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147–177.Google Scholar
Shabalina, S. A., Zaykin, D. V., Gris, P., Ogurtsov, A. Y., Gauthier, J., & Shibata, K. (2009). Expansion of the human mu-opioid receptor gene architecture: Novel functional variants. Human Molecular Genetics, 18, 1037–1951.Google Scholar
Sher, K. (1991). Children of alcoholics: A critical appraisal of theory and research. Chicago: University of Chicago Press.Google Scholar
Smelson, D., Yu, L., Buyske, S., Gonzalez, G., Tischfield, J., Deutsch, C. K., et al. (2012). Genetic association of GABA-A receptor alpha-2 and mu opioid receptor with cocaine cue-reactivity: Evidence for inhibitory synaptic neurotransmission involvement in cocaine dependence. American Journal on Addictions, 21, 411–415.Google Scholar
Stattin, H., & Kerr, M. (2000). Parental monitoring: A reinterpretation. Child Development, 71, 1072–1085.CrossRefGoogle ScholarPubMed
Steinberg, L., & Monahan, K. (2007). Age differences in resistance to peer influence. Developmental Psychology, 43, 1531–1543.Google Scholar
Tian, C., Hinds, D. A., Adler, S. G., Lee, A., Pahl, M. V., Silva, G., et al. (2007). A genome wide single nucleotide polymorphism panel for Mexican American admixture mapping. American Society for Human Genetics, 80, 1014–1023.Google Scholar
Tilton-Weaver, L. C., & Marshall, S. K. (2008). Adolescents’ agency in information management. In Kerr, M., Stattin, H., & Engels, R. C. M. E. (Eds.), What can parents do? New insights into the role of parents in adolescent problem behavior (pp. 11–41). West Sussex: Wiley.Google Scholar
Turrisi, R., & Ray, A. E. (2010). Sustained parenting and college drinking in first-year students. Developmental Psychobiology, 52, 286–294.Google Scholar
White, H. R., Johnson, V., & Buyske, S. (2000). Parental modeling and parenting behavior effects on offspring alcohol and cigarette use: A growth curve analysis. Journal of Substance Abuse, 12, 287–310.CrossRefGoogle ScholarPubMed
White, H. R., McMorris, B. J., Catalano, R. F., Fleming, C. B., Haggert, K. P., & Abbott, R. D. (2006). Increases in alcohol and marijuana use during the transition out of high school into emerging adulthood: The effects of leaving home, going to college, and high school protective factors. Journal of Studies on Alcohol, 67, 810–822.Google Scholar
World Health Organization. (2004). Global Status Report on Alcohol. Geneva: Author.Google Scholar
Yu, C. Y., & Muthén, B. (2002). Evaluation of model fit indices for latent variable models with categorical and continuous outcomes. Unpublished manuscript.Google Scholar
Zhang, H., Luo, X., Kranzler, H. R., Lappalainen, J., Yang, B., Krupitksy, E., et al. (2006). Association between two mu-opioid receptor gene (OPRM1) haplotype blocks and drug or alcohol dependence. Human Molecular Genetics, 15, 807–819.CrossRefGoogle ScholarPubMed