Hostname: page-component-76d6cb85b7-vdhp9 Total loading time: 0 Render date: 2026-07-16T01:29:04.539Z Has data issue: false hasContentIssue false
  • English
  • Français

Parenting and adolescents’ psychological adjustment: Longitudinal moderation by adolescents’ genetic sensitivity

Published online by Cambridge University Press:  28 December 2016

Clare M. Stocker ,
April S. Masarik ,
Keith F. Widaman ,
Ben T. Reeb ,
Jason D. Boardman ,
Andrew Smolen ,
Tricia K. Neppl  and
Katherine J. Conger
Clare M. Stocker*
Affiliation:
University of Denver
April S. Masarik
Affiliation:
Boise State University
Keith F. Widaman
Affiliation:
University of California, Riverside
Ben T. Reeb
Affiliation:
University of California, Davis
Jason D. Boardman
Affiliation:
University of Colorado
Andrew Smolen
Affiliation:
University of Colorado
Tricia K. Neppl
Affiliation:
Iowa State University
Katherine J. Conger
Affiliation:
University of California, Davis
*
Address correspondence and reprint requests to: Clare Stocker, Department of Psychology, University of Denver, 2155 Race Street, Denver, CO 80208; E-mail: cstocker@du.edu.
Get access Rights & Permissions [Opens in a new window]

Abstract

We examined whether adolescents’ genetic sensitivity, measured by a polygenic index score, moderated the longitudinal associations between parenting and adolescents’ psychological adjustment. The sample included 323 mothers, fathers, and adolescents (177 female, 146 male; Time 1 [T1] average age = 12.61 years, SD = 0.54 years; Time 2 [T2] average age = 13.59 years, SD = 0.59 years). Parents’ warmth and hostility were rated by trained, independent observers using videotapes of family discussions. Adolescents reported their symptoms of anxiety, depressed mood, and hostility at T1 and T2. The results from autoregressive linear regression models showed that adolescents’ genetic sensitivity moderated associations between observations of both mothers’ and fathers’ T1 parenting and adolescents’ T2 composite maladjustment, depression, anxiety, and hostility. Compared to adolescents with low genetic sensitivity, adolescents with high genetic sensitivity had worse adjustment outcomes when parenting was low on warmth and high on hostility. When parenting was characterized by high warmth and low hostility, adolescents with high genetic sensitivity had better adjustment outcomes than their counterparts with low genetic sensitivity. The results support the differential susceptibility model and highlight the complex ways that genes and environment interact to influence development.

Information

Type
Regular Articles
Information
Development and Psychopathology , Volume 29 , Issue 4 , October 2017 , pp. 1289 - 1304
Copyright
Copyright © Cambridge University Press 2016 

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.)

Article purchase

Temporarily unavailable

Footnotes

This research is currently supported by a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD064687) and from the National Science Foundation (1327768) and a research project award from the California Agricultural Experiment Station (CA-D-HCE-7709-H, to K.J.C.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding sources. Support for earlier years of the study also came from multiple sources, including the National Institute of Mental Health (MH00567, MH19734, MH43270, MH59355, MH62989, MH48165, MH051361), the National Institute on Drug Abuse (DA05347), the National Institute of Child Health and Human Development (HD027724, HD051746, HD047573), the Bureau of Maternal and Child Health (MCJ-109572), and the MacArthur Foundation Research Network on Successful Adolescent Development Among Youth in High-Risk Settings.

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.Google Scholar
Aliev, F., Latendresse, S. J., Bacanu, S., Neale, M. C., & Dick, D. M. (2014). Testing for measured gene-environment interaction: Problems with the use of cross-product terms and a regression model reparameterization solution. Behavioral Genetics, 44, 165–181.Google Scholar
Barber, B. K., Stolz, H. E., & Olsen, J. A. (2005). Parental support, psychological control, and behavioral control: Assessing relevance across time, method, and culture. Monographs of the Society for Research in Child Development, 70, 73–103.Google Scholar
Beach, S. R., Brody, G. H., Todorov, A. A., Gunter, T. D., & Philibert, R. A. (2010). Methylation at SLC6A4 is linked to family history of child abuse: An examination of the Iowa Adoptee sample. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 153, 710–713.Google Scholar
Beevers, C. G., Wells, T. T., Ellis, A. J., & McGeary, J. E. (2009). Association of the serotonin transporter gene promoter region (5-HTTLPR) polymorphism with biased attention for emotional stimuli. Journal of Abnormal Psychology, 118, 670–681.Google Scholar
Belsky, D. W., & Israel, S. (2014). Integrating genetics and social science: Genetic risk scores. Biodemography and Social Biology, 60, 137–155.Google Scholar
Belsky, J., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2007). For better and for worse: Differential susceptibility to environmental influences. Current Directions in Psychological Science, 16, 300–304.Google Scholar
Belsky, J., & Beaver, K. M. (2011). Cumulative genetic plasticity, parenting and adolescent self-regulation. Journal of Child Psychology and Psychiatry, 52, 619–626.Google Scholar
Belsky, J., & Pluess, M. (2009). Beyond diathesis-stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908.Google Scholar
Belsky, J., & Pluess, M. (2013). Beyond risk, resilience, and dysregulation: Phenotypic plasticity and human development. Development and Psychopathology, 25, 1243–1261.Google Scholar
Belsky, J., Pluess, M., & Widaman, K. F. (2013). Confirmatory and competitive evaluation of alternative gene-environment interaction hypotheses. Journal of Child Psychology and Psychiatry, 54, 1135–1143.CrossRefGoogle ScholarPubMed
Berg-Nielsen, T. S., Vikan, A., & Dahl, A. A. (2002). Parenting related to child and parental psychopathology: A descriptive review of the literature. Clinical Child Psychology and Psychiatry, 7, 529–552.Google Scholar
Boyce, W. T., & Ellis, B. J. (2005). Biological sensitivity to context: I. An evolutionary–developmental theory of the origins and functions of stress reactivity. Development and Psychopathology, 17, 271–301.Google Scholar
Brody, G. H., Chen, Y. F., Kogan, S. M., Yu, T., Molgaard, V. K., DiClemente, R. J., & Wingood, G. M. (2012). Family-centered program to prevent substance use, conduct problems, and depressive symptoms in Black adolescents. Pediatrics, 129, 108–115.Google Scholar
Cardon, L. R., & Palmer, L. J. (2003). Population stratification and spurious allelic association. Lancet, 361, 598–604.Google Scholar
Caspi, A., Hariri, A. R., Holmes, A., Uher, R., & Moffitt, T. E. (2010). Genetic sensitivity to the environment: The case of the serotonin transporter gene and its implications for studying complex diseases and traits. American Journal of Psychiatry, 167, 509–527.Google Scholar
Caspi, A., & Moffitt, T. E. (2006). Gene-environment interactions in psychiatry: Joining forces with neuroscience. National Review of Neuroscience, 7, 583–590.Google Scholar
Choukalas, C. G., Melby, J. N., & Lorenz, F. O. (2000). Technical Report: Intraclass correlation coefficients in SPSS. Unpublished manuscript, Iowa State University, Institute for Social and Behavioral Research.Google Scholar
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation: Analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.Google Scholar
Conger, R. D., & Conger, K. J. (2002). Resilience in Midwestern families: Selected findings from the first decade of a prospective, longitudinal study. Journal of Marriage and Family, 64, 361–373.Google Scholar
Conger, R. D., Conger, K. J., & Martin, M. J. (2010). Socioeconomic status, family processes, and individual development. Journal of Marriage and Family, 72, 685–704.Google Scholar
Dalton, E. D., Hammen, C. L., Najman, J. M., & Brennan, P. A. (2014). Genetic susceptibility to family environment: BDNF Val66met and 5-HTTLPR influence depressive symptoms. Journal of Family Psychology, 28, 947–956.Google Scholar
Derogatis, L. R. (1983). SCL-90-R administration, scoring, and procedures: Manual II. Townsend, MD: Clinical Psychometric Research.Google Scholar
Dreher, J. C., Kohn, P., Kolachana, B., Weinberger, D. R., & Berman, K. F. (2009). Variation in dopamine genes influences responsivity of the human reward system. Proceeds for the National Academy of Sciences, 106, 617–622.CrossRefGoogle ScholarPubMed
Duncan, L. E., & Keller, M. C. (2011). A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry. American Journal of Psychiatry, 168, 1041–1049.Google Scholar
Eisenberg, D. T., MacKillop, J., Modi, M., Beauchemin, J., Dang, D., Lisman, S. A., … Wilson, D. S. (2007). Examining impulsivity as an endopheonotype using a behavioral approach: A DRD2 Taq1 A and DRD4 48-bp VNTR association study. Behavioral and Brain Functions, 3, 2.Google Scholar
Evans, G. W., Li, D., & Whipple, S. S. (2013). Cumulative risk and child development. Psychological Bulletin, 139, 1342–1396.Google Scholar
Gohier, B., Senior, C., Radua, J., El-Hage, W. Reichenberg, A., Proitsi, P., & Surquladze, S. A. (2014). Genetic modulation of the response bias towards facial displays of anger and happiness. European Psychiatry, 29, 197–201.Google Scholar
Haberstick, B. C., Smolen, A., Stetler, G., Tabor, J. W., Roy, T., Rick Casey, H., … Harris, K. M. (2014). Simple sequence repeats in the National Longitudinal Study of Adolescent Health: An ethnically diverse resource for genetic analysis of health and behavior. Behavior Genetics, 44, 487–497.CrossRefGoogle ScholarPubMed
Horwitz, B. N., & Neiderhiser, J. M. (2011). Gene-environment interplay, family relationships, and child adjustment. Journal of Marriage and Family, 73, 804–816.Google Scholar
Jaffee, S. R., & Price, T. S. (2007). Gene-environment correlations: A review of the evidence and implication for prevention of mental illness. Molecular Psychiatry, 12, 432–442.Google Scholar
Karg, K., Burmeister, M., Shedden, K., & Sen, S. (2011). The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: Evidence of genetic moderation. Archives of General Psychiatry, 68, 444–454.Google Scholar
Keller, M. C. (2014). Gene × Environment interaction studies have not properly controlled for potential confounders: The problem and the (simple) solution. Biological Psychiatry, 75, 18–24.Google Scholar
Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey replication. Archives of General Psychiatry, 62, 593–602.Google Scholar
Lee, S. H., Ham, B. J., Cho, Y. H., Lee, S. M., & Shim, S. H. (2007). Association study of dopamine receptor D2 TaqIA polymorphism and reward-related personality traits in healthy Korean young females. Neuropsychobiology, 56, 146–151.Google Scholar
Li, J. J., Berk, M. S., & Lee, S. S. (2013). Differential susceptibility in longitudinal models of gene–environment interaction for adolescent depression. Development and Psychopathology, 25, 991–1003.Google Scholar
Maccoby, E. E. (2000). Parenting and its effects on children: On reading and misreading behavior genetics. Annual Review of Psychology, 51, 1–27.Google Scholar
Masarik, A. S., Conger, R. D., Donnellan, M. B., Stallings, M. C., Martin, M. J., Schofield, T. J., … Widaman, K. F. (2014). For better and for worse: Genes and parenting interact to predict future behavior in romantic relationships. Journal of Family Psychology, 28, 357–367.Google Scholar
Melby, J. N., & Conger, R. D. (2001). The Iowa Family Interaction Rating Scales: Instrument summary. In Kerig, P. K. & Lindahl, K. M. (Eds.), Family observational coding systems: Resources for systematic research (pp. 33–57). Mahwah, NJ: Erlbaum.Google Scholar
Neville, M. J., Johnstone, E. C., & Walton, R. T. (2004). Identification and characterization of ANKK1: A novel kinase gene closely linked to DRD2 on chromosome Band 11q23.1. Human Mutation, 23, 540–545.Google Scholar
Nolen-Hoeksema, S., & Hilt, L. M. (2009). Gender differences in depression. In Gotlib, I. H. & Hammen, C. L. (Eds.), Handbook of depression (pp. 2386–2404). New York: Guilford Press.Google Scholar
Patterson, G. R., DeBaryshe, B. D., & Ramsey, E. (1989). A developmental perspective on antisocial behavior. American Psychologist, 44, 329–355.Google Scholar
Phares, V., Fields, S., Kamboukos, D., & Lopez, L. (2005). Still looking for Poppa. American Psychologist, 60, 735–736.Google Scholar
Plomin, R., DeFries, J. C., Knopik, V. S., & Neiderhiser, J. M. (2013). Behavioral genetics (6th ed.). New York: Worth.Google Scholar
Rajeevan, H., Soundararajan, U., Kidd, J. R., Pakstis, A. J., & Kidd, K. K. (2012). ALFRED: An allele frequency resource for research and teaching. Nucleic Acids Research, 40, 1–6.CrossRefGoogle ScholarPubMed
Reeb, B. T., & Conger, K. J. (2011). Paternal depression, family relationships, and offspring functioning: Processes of risk during adolescence. In Leyton, C. H. (Ed.), Fatherhood: Roles, responsibilities, and rewards (pp. 29–48). New York: Nova Science.Google Scholar
Simons, R. L., Lei, M. K., Stewart, E. A., Beach, S. R., Brody, G. H., Philibert, R. A., & Gibbons, F. X. (2012). Social adversity, genetic variation, street code, and aggression: A genetically informed model of violent behavior. Youth Violence Juvenile Justice, 10, 3–24.CrossRefGoogle ScholarPubMed
Stice, E., Yokum, S., Burger, K., Epstein, L., & Smolen, A. (2012). Multilocus genetic composite reflecting dopamine signaling capacity predicts reward circuitry responsivity. Journal of Neuroscience, 32, 10093–10100.Google Scholar
Sullivan, P. F., Daly, M. J., & O'Donovan, M. (2012). Genetic architectures of psychiatric disorders: The emerging picture and its implications. Nature Reviews Genetics, 13, 537–551.Google Scholar
Taylor, S. E., Way, B. M., Welch, W. T., Hilmert, C. J., Lehman, B. J., & Eisenberger, N. I. (2006). Early family environment, current adversity, the serotonin transporter promoter polymorphism, and depressive symptomology. Biological Psychiatry, 60, 671–676.Google Scholar
Thapar, A., Collishaw, S., Pine, D. S., & Thapar, A. K. (2012). Depression in adolescence. Lancet, 379, 1056–1067.CrossRefGoogle ScholarPubMed
van IJzendoorn, M. H., & Bakersman-Kranenburg, M. J. (2015). Genetic differential susceptibility on trial: Meta-analytic support from randomized controlled experiments. Development and Psychopathology, 27, 151–162.Google Scholar
Vijayendran, M., Beach, S., Plume, J. M., Brody, G., & Philibert, R. (2012). Effects of genotype and child abuse on DNA methylation and gene expression at the serotonin transporter. Frontiers in Psychiatry, 3, 55.Google Scholar
Walsh, N. D., Dalgleish, T., Dunn, V. J., Abbott, R., St. Clair, M. C., Owens, M., … Goodyer, I. M. (2012). 5-HTTLPR-environment interplay and its effects on neural reactivity in adolescents. NeuroImage, 63, 1670–1680.Google Scholar
Wickrama, K. A. S., & O'Neal, C. W. (2013). Family of origin, race/ethnicity, and socioeconomic attainment: Genotype and intraindividual processes. Journal of Marriage and Family, 75, 75–90.Google Scholar
Widaman, K. F., Helm, J. L., Castro-Schilo, L., Pluess, M., Stallings, M. C., & Belsky, J. (2012). Distinguishing ordinal and disordinal interactions. Psychological Methods, 17, 615–622.Google Scholar