Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-26T03:45:25.009Z Has data issue: false hasContentIssue false
  • English
  • Français

Latent trajectories of alcohol use from early adolescence to young adulthood: Interaction effects between 5-HTTLPR and parenting quality and gender differences

Published online by Cambridge University Press:  13 June 2018

Jinni Su ,
Andrew J. Supple ,
Esther M. Leerkes  and
Sally I-Chun Kuo
Jinni Su*
Affiliation:
Virginia Commonwealth University
Andrew J. Supple
Affiliation:
University of North Carolina at Greensboro
Esther M. Leerkes
Affiliation:
University of North Carolina at Greensboro
Sally I-Chun Kuo
Affiliation:
Virginia Commonwealth University
*
Address correspondence and reprint requests to: Jinni Su, Department of Psychology, Virginia Commonwealth University, PO Box 842509, Richmond, VA 23284; E-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Using a large and nationally representative sample, we examined how adolescents’ 5-HTTLPR genotype and perceived parenting quality independently and interactively associated with trajectories of alcohol use from early adolescence to young adulthood and whether/how gender may moderate these associations. The sample for this study included 13,749 adolescents (53.3% female; 56.3% non-Hispanic White, 21.5% Black, 16.0% Hispanic, and 6.1% Asian) followed prospectively from adolescence to young adulthood. Using growth mixture modeling, we identified four distinct trajectories of alcohol use (i.e., persistent heavy alcohol use, developmentally limited alcohol use, late-onset heavy alcohol use, and non/light alcohol use). Results indicated that the short allele of 5-HTTLPR was associated with higher risk of membership in the persistent and the late-onset heavy alcohol use trajectories. Parenting quality was associated with lower likelihoods of following the persistent heavy and the developmentally limited alcohol use trajectories but was not associated with risk of membership for the late-onset heavy drinking trajectory. 5-HTTLPR interacted with parenting quality to predict membership in the persistent heavy alcohol use trajectory for males but not for females. Findings highlighted the importance of considering the heterogeneity in trajectories of alcohol use across development and gender in the study of Gene Environment interactions in alcohol use.

Type
Regular Articles
Information
Development and Psychopathology , Volume 31 , Issue 2 , May 2019 , pp. 457 - 469
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

This study uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill. Add Health is funded by Grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from Grant P01-HD31921 for this analysis.

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.Google Scholar
Aquilino, W. S., & Supple, A. J. (2001). Long-term effects of parenting practices during adolescence on well-being: Outcomes in young adulthood. Journal of Family Issues, 22, 289–308. doi:10.1177/019251301022003002Google Scholar
Barnes, G. M., Reifman, A. S., Farrell, M. P., & Dintcheff, B. A. (2000). The effects of parenting on the development of adolescent alcohol misuse: A six-wave latent growth model. Journal of Marriage and Family, 62, 175–186. doi:10.1111/j.1741-3737.2000.001Google Scholar
Barnholtz-Sloan, J. S., McEvoy, B., Shriver, M. D., & Rebbeck, T. R. (2008). Ancestry estimation and correction for population stratification in molecular epidemiologic association studies. Cancer Epidemiology Biomarkers and Prevention, 17, 471–477.Google Scholar
Beaver, K. M., & Belsky, J. (2012). Gene-environment interaction and the intergenerational transmission of parenting: Testing the differential-susceptibility hypothesis. Psychiatric Quarterly, 83, 29–40. doi:10.1007/s11126-011-9180-4Google Scholar
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908. doi:10.1037/a0017376Google Scholar
Brody, G. H., Beach, S. H., Philibert, R. A., Chen, Y., Lei, M., Murry, V., & Brown, A. C. (2009). Parenting moderates a genetic vulnerability factor in longitudinal increases in youths' substance use. Journal of Consulting and Clinical Psychology, 77, 1–11. doi:10.1037/a0012996Google Scholar
Brummett, B. H., Boyle, S. H., Siegler, I. C., Kuhn, C. M., Ashley-Koch, A., Jonassaint, C. R., … Williams, R. B. (2008). Effects of environmental stress and gender on associations among symptoms of depression and the serotonin transporter gene linked polymorphic region (5-HTTLPR). Behavior Genetics, 38, 34–43.Google Scholar
Center for Behavioral Health Statistics and Quality. (2015). Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health (HHS Publication No. SMA 15-4927, NSDUH Series H-50). Retrieved from http://www.samhsa.gov/data/Google Scholar
Chassin, L., Flora, D. B., & King, K. M. (2004). Trajectories of alcohol and drug use and dependence from adolescence to adulthood: The effects of family alcoholism and personality. Journal of Abnormal Psychology, 113, 483–498. doi:10.1037/0021-843X.113.4.483Google Scholar
Chassin, L., Pitts, S. C., & Prost, J. (2002). Binge drinking trajectories from adolescence to emerging adulthood in a high-risk sample: Predictors and substance abuse outcomes. Journal of Consulting and Clinical Psychology, 70, 67–78. doi:10.1037/0022-006X.70.1.67Google Scholar
Chen, P., & Jacobson, K. C. (2012). Developmental trajectories of substance use from early adolescence to young adulthood: Gender and racial/ethnic differences. Journal of Adolescent Health, 50, 154–163. doi:10.1016/j.jadohealth.2011.05.013Google Scholar
Clark, S., & Muthén, B. (2009). Relating latent class analysis results to variables not included in the analysis. Retrieved from https://www.statmodel.com/download/relatinglca.pdfGoogle Scholar
Covault, J., Tennen, H., Armeli, S., Conner, T. S., Herman, A. I., Cillessen, A. N., & Kranzler, H. R. (2007). Interactive effects of the serotonin transporter 5-HTTLPR polymorphism and stressful life events on college student drinking and drug use. Biological Psychiatry, 61, 609–616. doi:10.1016/j.biopsych.2006.05.018Google Scholar
Daw, N. D., Kakade, S., & Dayan, P. (2002). Opponent interactions between serotonin and dopamine. Neural Networks, 15, 603–616. doi:10.1016/S0893-6080(02)00052-7Google Scholar
Dick, D. M., Cho, S. B., Latendresse, S. J., Aliev, F., Nurnberger, J. I. Jr., Edenberg, H. J., … Kuperman, S. (2014). Genetic influences on alcohol use across stages of development: GABRA2 and longitudinal trajectories of drunkenness from adolescence to young adulthood. Addiction Biology, 19, 1055–1064. doi:10.1111/adb.12066Google Scholar
Dick, D. M., Plunkett, J., Hamlin, D., Nurnberger, J. R., Kuperman, S., Schuckit, M., … Bierut, L. (2007). Association analyses of the serotonin transporter gene with lifetime depression and alcohol dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) sample. Psychiatric Genetics, 17, 35–38.Google Scholar
Dick, D. M., Viken, R., Purcell, S., Kaprio, J., Pulkkinen, L., & Rose, R. J. (2007). Parental monitoring moderates the importance of genetic and environmental influences on adolescent smoking. Journal of Abnormal Psychology, 116, 213–218. doi:10.1037/0021-843X.116.1.213Google Scholar
Feinn, R., Nellissery, M., & Kranzler, H. R. (2005). Meta-analysis of the association of a functional serotonin transporter promoter polymorphism with alcohol dependence. American Journal of Medical Genetics, 133B, 79–84.Google Scholar
Flory, K., Lynam, D., Milich, R., Leukefeld, C., & Clayton, R. (2004). Early adolescent through young adult alcohol and marijuana use trajectories: Early predictors, young adult outcomes, and predictive utility. Development and Psychopathology, 16, 193–213. doi:10.1017/S0954579404044475Google Scholar
Hammen, C., Brennan, P. A., Keenan-Miller, D., Hazel, N. A., & Najman, J. M. (2010). Chronic and acute stress, gender, and serotonin transporter gene-environment interactions predicting depression symptoms in youth. Journal of Child Psychology and Psychiatry, 51, 180–187. doi:10.1111/j.1469-7610.2009.02177.xGoogle Scholar
Hankin, B. L., Nederhof, E., Oppenheimer, C. W., Jenness, J., Young, J. F., Abela, J. R. Z., … Oldehinkel, A. J. (2011). Differential susceptibility in youth: Evidence that 5-HTTLPR × positive parenting is associated with positive affect “for better and worse.” Translational Psychiatry, 1, 1–7. doi:10.1038/tp.2011.44Google Scholar
Harden, K. P., Hill, J. E., Turkheimer, E., & Emery, R. E. (2008). Gene-environment correlation and interaction in peer effects on adolescent alcohol and tobacco use. Behavioral Genetics, 38, 339–347. doi:10.1007/s10519-008-9202-7Google Scholar
Harris, K. M. (2011). Design features of Add Health. Retrieved from https://www.cpc.unc.edu/projects/addhealth/data/guides/design%20paper%20WI-IV.pdfGoogle Scholar
Heils, A., Teufel, A., Petri, S., Stober, G., Riederer, P., Bengel, D., & Lesch, K. P. (1996). Allelic variation of human serotonin transporter gene expression. Journal of Neurochemistry, 56, 2621–2624.Google Scholar
Herman, A. I., Philbeck, J. W., Vasilopoulos, N. L., & Depetrillo, P. B. (2003). Serotonin transporter promoter polymorphism and differences in alcohol consumption behavior in a college student population. Alcohol and Alcoholism, 38, 446–449. doi:10.1093/alcalc/agg110Google Scholar
Hopfer, C. J., Crowley, T. J., & Hewitt, J. K. (2003). Review of twin and adoption studies of adolescent substance use. Journal of the American Academy of Child & Adolescent Psychiatry, 42, 710–719. doi:10.1097/01.CHI.0000046848.56865.54Google Scholar
Hu, X., Oroszi, G., Chun, J., Smith, T. L., Goldman, D., & Schuckit, M. A. (2005). An expanded evaluation of the relationship of four alleles to the level of response to alcohol and the alcoholism risk. Alcoholism, Clinical and Experimental Research, 29, 8–16.Google Scholar
Jackson, K. M., & Sher, K. J. (2005). Similarities and differences of longitudinal phenotypes across alternate indices of alcohol involvement: A methodologic comparison of trajectory approaches. Psychology of Addictive Behaviors, 19, 339–351. doi:10.1037/0893-164X.19.4.339Google Scholar
Kaufman, J., Yang, B., Douglas-Palumberi, H., Crouse-Artus, M., Lipschitz, D., Krystal, J. H., & Gelernter, J. (2007). Genetic and environmental predictors of early alcohol use. Biological Psychiatry, 61, 1228–1234. doi:10.1016/j.biopsych.2006.06.039Google Scholar
Keller, M. C. (2014). Gene-by-environment interaction studies have not properly controlled for potential confounders: The problem and the (simple) solution. Biological Psychiatry, 75. doi:10.1016/j.biopsych.2013.09.006Google Scholar
Kendler, K. S., Schmitt, E., Aggen, S. H., & Prescott, C. A. (2008). Genetic and environmental influences on alcohol, caffeine, cannabis, and nicotine use from early adolescence to middle adulthood. Archives of Genetic Psychiatry, 65, 674–682. doi:10.1001/archpsyc.65.6.674Google Scholar
Kim, J., Park, A., Glatt, S. J., Eckert, T. L., Vanable, P. A., Scott-Sheldon, L. A., … Carey, M. P. (2015). Interaction effects between the 5-hydroxy tryptamine transporter-linked polymorphic region (5-HTTLPR) genotype and family conflict on adolescent alcohol use and misuse. Addiction, 110, 289–299. doi:10.1111/add.12753Google Scholar
LeMarquand, D., Pihl, R. O., & Benkelfat, C. (1994). Serotonin and alcohol intake, abuse, and dependence: Findings of animal studies. Biological Psychiatry, 36, 395–421.Google Scholar
Lesch, K., Bengel, D., Heils, A., Sabol, S. Z., Greenberg, B. D., Petri, S., … Murphy, D. L. (1996). Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science, 274, 1527–1531. doi:10.1126/science.274.5292.1527Google Scholar
Li, J. J., & Lee, S. S. (2010). Latent class analysis of antisocial behavior: Interaction of serotonin transporter genotype and maltreatment. Journal of Abnormal Child Psychology, 38, 789–801. doi:10.1007/s10802-010-9409-yGoogle Scholar
Little, T. D. (2013). Longitudinal structural equation modeling. New York: Guilford Press.Google Scholar
Merenäkk, L., Mäestu, J., Nordquist, N., Parik, J., Oreland, L., Loit, H., & Harro, J. (2011). Effects of the serotonin transporter (5-HTTLPR) and α[sub]2A[/sub]-adrenoceptor (C-1291G) genotypes on substance use in children and adolescents: A longitudinal study. Psychopharmacology, 215, 13–22. doi:10.1007/s00213-010-2109-zGoogle Scholar
Moffitt, T. E. (1993). Adolescence-limited and life-course-persistent antisocial behavior: A developmental taxonomy. Psychological Review, 100, 674–701. doi:10.1037/0033-295X.100.4.674Google Scholar
Mogro-Wilson, C. (2008). The influence of parental warmth and control on Latino adolescent alcohol use. Hispanic Journal of Behavioral Sciences, 30, 89–105. doi:10.1177/0739986307310881Google Scholar
Mrug, S., & Windle, M. (2014). DRD4 and susceptibility to peer influence on alcohol use from adolescence to adulthood. Drug and Alcohol Dependence, 145, 168–173. doi:10.1016/j.drugalcdep.2014.10.009Google Scholar
Muthén, B., & Muthén, L. (2000). Integrating person-centered and variable-centered analysis: Growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and Experimental Research, 24, 882–891.Google Scholar
Muthén, L. K., & Muthén, B. O. (1998–2012). Mplus user's guide (7th ed.). Los Angeles: Author.Google Scholar
Olsson, C. A., Byrnes, G. B., Lotfi-Miri, M. M., Collins, V. V., Williamson, R. R., Patton, C. C., & Anney, R. L. (2005). Association between 5-HTTLPR genotypes and persisting patterns of anxiety and alcohol use: Results from a 10-year longitudinal study of adolescent mental health. Molecular Psychiatry, 10, 868–876. doi:10.1038/sj.mp.4001677Google Scholar
Perry, B. (2013). Where is the gender in behavior genetics? The need for social epidemiology in research on gene-environment interactions. OA Genetics, 1, 1–6.Google Scholar
Plomin, R., Haworth, C. M. A., & Davis, O. S. P. (2009). Common disorders as quantitative traits. Nature Reviews Genetics, 10, 872–878. doi:10.1038/nrg2670Google Scholar
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569.Google Scholar
Rende, R., & Plomin, R. (1992). Diathesis-stress models of psychopathology: A quantitative genetic perspective. Applied and Preventive Psychology, 1, 177–182.Google Scholar
Roisman, G. I., Newman, D. A., Fraley, R. C., Haltigan, J. D., Groh, A. M., & Haydon, K. C. (2012). Distinguishing differential susceptibility from diathesis–stress: Recommendations for evaluating interaction effects. Development and Psychopathology, 24, 389–409.Google Scholar
Ryan, S. M., Jorm, A. F., & Lubman, D. I. (2010). Parenting factors associated with reduced adolescent alcohol use: A systematic review of longitudinal studies. Australian and New Zealand Journal of Psychiatry, 44, 774–783. doi:10.1080/00048674.2010.501759Google Scholar
Salvatore, J. E., Aliev, F., Edwards, A. C., Evans, D. M., Macleod, J., Hickman, M., … Dick, D. M. (2014). Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment. Genes (Basel), 5, 330–346. doi:10.3390/genes5020330Google Scholar
Salvatore, J. E., Cho, S. B., & Dick, D. M. (2017). Genes, environments, and sex differences in alcohol research. Journal of Studies on Alcohol and Drugs, 78, 494–501.Google Scholar
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York: Oxford University Press.Google Scholar
Skogen, J. C., Knudsen, A. K., Hysing, M., Wold, B., & Sivertsen, B. (2015). Trajectories of alcohol use and association with symptoms of depression from early to late adolescence: The Norwegian Longitudinal Health Behaviour Study. Drug and Alcohol Review. Advance online publication. doi:10.1111/dar.12350Google Scholar
Skowronek, M. H., Laucht, M., Hohm, E., Becker, K., & Schmidt, M. H. (2006). Interaction between the dopamine D4 receptor and the serotonin transporter promoter polymorphisms in alcohol and tobacco use among 15-year-olds. Neurogenetics, 7, 239–246. doi:10.1007/s10048-006-0050-4Google Scholar
Smolen, A., Whitsel, E. A., Tabor, J., Killeya-Jones, K. A., Cuthbertson, C. C., Hussey, J. M., … Harris, K. M. (2013). Add Health Wave IV documentation: Candidate genes. Retrieved from http://www.cpc.unc.edu/projects/addhealth/data/guides/DNA_documentation.pdfGoogle Scholar
Tucker, J. S., Ellickson, P. L., Orlando, M., Martino, S. C., & Klein, D. J. (2005). Substance use trajectories from early adolescence to emerging adulthood: A comparison of smoking, binge drinking, and marijuana use. Journal of Drug Issues, 35, 307–332.Google Scholar
Tung, I., & Lee, S. S. (2016). Latent trajectories of adolescent antisocial behavior: Serotonin transporter linked polymorphic region (5-HTTLPR) genotype influences sensitivity to perceived parental support. Development and Psychopathology. Advance online publication. doi:10.1017/S0954579416000031Google Scholar
van der Zwaluw, C. S., & Engels, R. C. M. E. (2009). Gene–environment interactions and alcohol use and dependence: Current status and future challenges. Addiction, 104, 907–914. doi:10.1111/j.1360-0443.2009.02563.xGoogle Scholar
van der Zwaluw, C. S., Engels, R. E., Vermulst, A. A., Rose, R. J., Verkes, R. J., Buitelaar, J., … Scholte, R. J. (2010). A serotonin transporter polymorphism (5-HTTLPR) predicts the development of adolescent alcohol use. Drug and Alcohol Dependence, 112, 134–139. doi:10.1016/j.drugalcdep.2010.06.001Google Scholar
van der Zwaluw, C. S., Otten, R., Kleinjan, M., & Engels, R. C. (2014). Different trajectories of adolescent alcohol use: Testing gene-environment interactions. Alcoholism: Clinical and Experimental Research, 38, 704–712. doi:10.1111/acer.12291Google Scholar
Vaske, J., Boisvert, D., Wright, J. P., & Beaver, K. M. (2013). A longitudinal analysis of the effects of a DRD4 polymorphism on marijuana use. Psychiatry Research, 210, 247–255. doi:10.1016/j.psychres.2013.04.022Google Scholar
Vaske, J., Newsome, J., & Wright, J. (2012). Interaction of serotonin transporter linked polymorphic region and childhood neglect on criminal behavior and substance use for males and females. Development and Psychopathology, 24, 181–193. doi:10.1017/S0954579411000769Google Scholar
Verona, E., Joiner, T. E., Johnson, F., & Bender, T. W. (2006). Gender specific gene-environment interactions on laboratory-assessed aggression. Biological Psychology, 71, 33–41. doi:10.1016/j.biopsycho.2005.02.001Google Scholar
Wang, M., & Bodner, T. E. (2007). Growth mixture modeling: Identifying and predicting unobserved subpopulations with longitudinal data. Organizational Research Methods, 10, 635–656. doi:10.1177/1094428106289397Google Scholar
Webb, J. A., Bray, J. H., Getz, J. G., & Adams, G. (2002). Gender, perceived parental monitoring and behavioral adjustment: Influences on adolescent alcohol use. American Journal of Orthopsychiatry, 72, 392–400. doi:10.1037/0002-9432.72.3.39Google Scholar
Wichers, M., Gillespie, N. A., & Kendler, K. S. (2013). Genetic and environmental predictors of latent trajectories of alcohol use from adolescence to adulthood: A male twin study. Alcoholism: Clinical and Experimental Research, 37, 498–506. doi:10.1111/j.1530-0277.2012.01939.x-9432.7Google Scholar
Supplementary material: File

Su et al. supplementary material 1

Supplementary Table

Download Su et al. supplementary material 1(File)
File 149.3 KB