Skip to main content
Log in

Genetic Moderation of the Association Between Early Family Instability and Trajectories of Aggressive Behaviors from Middle Childhood to Adolescence

  • Original Research
  • Published:
Behavior Genetics Aims and scope Submit manuscript

Abstract

The present study tested models of polygenic by environment interaction between early childhood family instability and polygenic risk for aggression predicting developmental trajectories of aggression from middle childhood to adolescence. With a longitudinal sample of 515 racially and ethnically diverse children from low-income families, primary caregivers reported on multiple components of family instability annually from child ages 2–5 years. A conservative polygenic risk score (p = 0.05) was generated based on a prior meta-genome wide association study. Trajectories of aggression were identified using a curve of factors model based on a composite of primary caregiver, alternate caregiver, and teacher reports at five ages from 7.5 to 14 years. The family instability by polygenic interaction predicted growth in children’s aggression such that children with lower levels of family instability and lower polygenic risk exhibited a steeper decline in aggression from 7.5 to 14. Findings support the need to model gene-environment interplay to elucidate the role of genetics in the development of aggressive behaviors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data Availability

The data that support the findings of this study are available from the principal investigators, [DS, MW, and KL], upon reasonable request.

Code Availability

The R code that supports the findings of this study is available from the corresponding author [SW], upon reasonable request.

References

  • Achenbach TM, Rescorla L (2001) Manual for the ASEBA school-age forms & profiles: an integrated system of multi-informant assessment. ASEBA, Burlington

    Google Scholar 

  • Ackerman BP, Kogos J, Youngstrom E, Schoff K, Izard C (1999) Family instability and the problem behaviors of children from economically disadvantaged families. Dev Psychol 35(1):258–268

    Article  PubMed  Google Scholar 

  • Bares CB, Chartier KG, Karriker-Jaffe KJ, Aliev F, Mustanski B, Dick D (2020) Exploring how family and neighborhood stressors influence genetic risk for adolescent conduct problems and alcohol use. J Youth Adol 49:1365–1378

    Article  Google Scholar 

  • Belsky J, Pluess M (2009) Beyond diathesis stress: differential susceptibility to environmental influences. Psychol Bull 135(6):885–908

    Article  PubMed  Google Scholar 

  • Belsky J, Schlomer GL, Ellis BJ (2012) Beyond cumulative risk: distinguishing harshness and unpredictability as determinants of parenting and early life history strategy. Dev Psychol 48(3):662–673

    Article  PubMed  Google Scholar 

  • Brick LA, Keller MC, Knopik VS, McGeary JE, Palmer RH (2019) Shared additive genetic variation for alcohol dependence among subjects of African and European ancestry. Addict Biol 24(1):132–144

    Article  PubMed  Google Scholar 

  • Bronfenbrenner U, Ceci SJ (1994) Nature-nurture reconceptualized in developmental perspective: a bioecological model. Psychol Rev 101(4):568–586

    Article  PubMed  Google Scholar 

  • Bubier JL, Drabick DA (2009) Co-occurring anxiety and disruptive behavior disorders: the roles of anxious symptoms, reactive aggression, and shared risk processes. Clin Psychol Rev 29(7):658–669

    Article  PubMed  PubMed Central  Google Scholar 

  • Burt SA, Klump KL (2014) Parent–child conflict as an etiological moderator of childhood conduct problems: an example of a ‘bioecological’ gene–environment interaction. Psychol Med 44(5):1065–1076

    Article  PubMed  Google Scholar 

  • Button TMM, Scourfield J, Martin N, Purcell S, McGuffin P (2005) Family dysfunction interacts with genes in the causation of antisocial symptoms. Behav Genet 35(2):115–120

    Article  PubMed  Google Scholar 

  • Campbell S, Stauffenberg CV (2008) Child characteristics and family processes that predict behavioral readiness for school. In: Booth A, Crouter A-C (eds) The Penn State University family issues symposia series. Disparities in school readiness: how families contribute to transitions in school. England, Taylor & Francis Group/Lawrence Erlbaum Associates, pp 225–258

    Google Scholar 

  • Cavanagh SE, Huston AC (2008) The timing of family instability and children’s social development. J Mar Fam 70(5):1258–1270

    Article  Google Scholar 

  • Das S, Forer L, Schönherr S, Sidorem C, Locke AE, Kwong A, Vrieze S, Chew EY, Levy S, McGue M, Schlessinger D, Stambolian D, Loh PR, Iacono WG, Swaroop A, Scott LJ, Cucca F, Kronenberg F, Boehnke M, Abecasis GR, Fuchsberger C (2016) Next-generation genotype imputation service and methods. Nat Gen 48(10):1284–1287

    Article  Google Scholar 

  • Del Giudice M, Ellis BJ, Shirtcliff EA (2011) The adaptive calibration model of stress responsivity. Neurosci Biobeh Rev 35(7):1562–1592

    Article  Google Scholar 

  • Dishion TJ, Shaw D, Connell A, Gardner F, Weaver C, Wilson M (2008) The family check-up with high-risk indigent families: preventing problem behavior by increasing parents’ positive behavior support in early childhood. Child Dev 79(5):1395–1414

    Article  PubMed  PubMed Central  Google Scholar 

  • Duncan LE, Keller MC (2011) A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry. Am J Psychiatry 168(10):1041–1049

    Article  PubMed  PubMed Central  Google Scholar 

  • Duncan L, Shen H, Gelaye B, Meijsen J, Ressler K, Feldman M, Peterson R, Domingue B (2019) Analysis of polygenic risk score usage and performance in diverse human populations. Nat Commun 10(1):1–9

    Article  Google Scholar 

  • Elliott DS, Ageton SS, Huizinga D (1985) Explaining delinquency and drug use. Sage, Beverly Hills

    Google Scholar 

  • Ellis BJ, Del Giudice M (2014) Beyond allostatic load: rethinking the role of stress in regulating human development. Dev Psychopathol 26(1):1–20

    Article  PubMed  Google Scholar 

  • Ellis BJ, Del Giudice M (2019) Developmental adaptation to stress: an evolutionary perspective. Ann Rev Psychol 70:111–139

    Article  Google Scholar 

  • Euesden J, Lewis CM, O’Reilly PF (2015) PRSice: polygenic risk score software. Bioinformatics 31(9):1466–1468

    Article  PubMed  Google Scholar 

  • Fanti KA, Frick PJ, Georgiou S (2009) Linking callous-unemotional traits to instrumental and non-instrumental forms of aggression. J Psychopathol Beh Assess 31(4):285–298

    Article  Google Scholar 

  • Forman EM, Davies PT (2003) Family instability and young adolescent maladjustment: the mediating effects of parenting quality and adolescent appraisals of family security. J Clin Child Adolesc Psychol 32(1):94–105

    Article  PubMed  Google Scholar 

  • Fowler PJ, Henry DB, Schoeny M, Taylor J, Chavira D (2014) Developmental timing of housing mobility: longitudinal effects on externalizing behaviors among at-risk youth. J Am Acad Child Psychiatry 53(2):199–208

    Article  Google Scholar 

  • Gelhorn H, Stallings M, Young S, Corley R, Rhee SH, Christian H, Hewitt J (2006) Common and specific genetic influences on aggressive and nonaggressive conduct disorder domains. J Am Acad Child Psychiatry 45(5):570–577

    Article  Google Scholar 

  • Hardt J, Rutter M (2004) Validity of adult retrospective reports of adverse childhood experiences: review of the evidence. J Child Psychol Psychiatry 45(2):260–273

    Article  PubMed  Google Scholar 

  • Ip HF, van der Laan CM, Krapohl EM, Brikell I, Sánchez-Mora C, Nolte IM, St Pourcain B, Bolhuis K, Palviainen T, Zafarmand H, Colodro-Conde L, Gordon S, Zayats T, Aliev F, Jiang C, Wang CA, Saunders G, Karhunen V, Hammerschlag AR et al (2021) Genetic association study of childhood aggression across raters instruments and age. BioRxiv. https://doi.org/10.1101/854927

    Article  Google Scholar 

  • Jorgensen TD, Pornprasertmanit S, Schoemann AM, Rosseel Y, Miller P, Quick C, Garnier-Villarreal M, Selig J, Boulton A, Preacher K, Coffman D, Rhemtulla M, Robitzsch A, Enders C, Arslan R, Clinton B, Panko P, Merkle E, Chesnut S et al (2020) Package ‘semTools’. Retrieved May 27, 2020 from http://ftp5.gwdg.de/pub/misc/cran/web/packages/semTools/semTools.pdf

  • Keller MC (2014) Gene environment interaction studies have not properly controlled for potential confounders: the problem and the simple solution. Biol Psychiatry 75(1):18–24

    Article  PubMed  Google Scholar 

  • Kong A, Thorleifsson G, Frigge ML, Vilhjalmsson BJ, Young AI, Thorgeirsson TE, Benonisdottir S, Oddsson A, Halldorsson BV, Masson G, Gudbjartsson DF, Helgason DF, Helgason A, Bjornsdottir G, Thorsteinsdottir U, Gudbjartsson DF (2018) The nature of nurture: effects of parental genotypes. Science 359(6374):424–428

    Article  PubMed  Google Scholar 

  • Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, Nguyen-Viet TA, Bowers P, Sidorenko J, Linnér RK, Fontana MA, Kundu T, Lee C, Li H, Li R, Royer R, Timshel PN, Walters RK, Willoughby EA, Yengo L, 23andMe Research Team et al (2018) Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment. Nat Genet 50(8):1112–1121

    Article  PubMed  PubMed Central  Google Scholar 

  • Linnér RK, Mallard TT, Barr PB, Sanchez-Roige S, Madole JW, Driver MN, Poore HE, Grotzinger AD, Tielbeek JJ, Johnson EC, Liu M, Zhou H, Kember RL, Pasman JA, Verweij KJH, Liu DJ, Vrieze S, COGA Collaborators, Kranzler HR, Gelernter J, Harris KM, Tucker-Drob EM, Waldman I, Palmer AA, Harden KP, Koellinger PD, Dick DM et al (2020) Multivariate genomic analysis of 1.5 million people identifies genes related to addiction, antisocial behaviour, and health. BioRxiv. https://doi.org/10.1101/2020.10.16.342501

    Article  Google Scholar 

  • Luthar SS, Cicchetti D, Becker B (2000) The construct of resilience: a critical evaluation and guidelines for future work. Child Dev 71(3):543–562

    Article  PubMed  PubMed Central  Google Scholar 

  • Matheny AP Jr, Wachs TD, Ludwig JL, Phillips K (1995) Bringing order out of chaos: psychometric characteristics of the confusion, hubbub, and order scale. J Appl Dev Psychol 16(3):429–444

    Article  Google Scholar 

  • McArdle JJ (1988) Dynamic but structural modeling of repeated measures data. In: Nesselroade J-R, Cattell R-B (eds) The handbook of multivariate psychology, 2nd edn. Springer, New York, pp 561–614

    Chapter  Google Scholar 

  • McClain LR (2011) Better parents, more stable partners: union transitions among cohabiting parents. J Mar Fam 73(5):889–901

    Article  Google Scholar 

  • Middeldorp CM, Lamb DJ, Vink JM, Bartels M, van Beijsterveldt CE, Boomsma DI (2014) Child care, socio-economic status and problem behavior: a study of gene–environment interaction in young Dutch twins. Behav Genet 44(4):314–325

    Article  PubMed  Google Scholar 

  • Milan S, Pinderhughes EE, Conduct Problems Prevention Research Group (2006) Family instability and child maladjustment trajectories during elementary school. J Abnor Child Psychol 34(1):40–53

    Article  Google Scholar 

  • Monroe SM, Simons AD (1991) Diathesis-stress theories in the context of life stress research: implications for the depressive disorders. Psychol Bull 110(3):406–425

    Article  PubMed  Google Scholar 

  • Murray GK, Lin T, Austin J, McGrath JJ, Hickie IB, Wray NR (2020) Could polygenic risk scores be useful in psychiatry?: a review. JAMA Psychiat 78(2):210–219

    Article  Google Scholar 

  • Musci RJ, Bettencourt AF, Sisto D, Maher B, Masyn K, Ialongo NS (2019) Violence exposure in an urban city: a GxE interaction with aggressive and impulsive behaviors. J Child Psychol Psychiatry 60(1):72–81

    Article  PubMed  Google Scholar 

  • Muthén LK, Muthén BO (2017) Mplus. Statistical analysis with latent variables. User’s guide, 8.

  • Odintsova VV, Roetman PJ, Ip HF, Pool R, Van der Laan CM, Tona KD, Vermeiren RRJM, Boomsma DI (2019) Genomics of human aggression: current state of genome-wide studies and an automated systematic review tool. Psychiatric Genet 29(5):170–190

    Article  Google Scholar 

  • Pappa I, St Pourcain B, Benke K, Cavadino A, Hakulinen C, Nivard MG, Nolte IM, Tiesler CMT, Bakermans-Kranenburg MJ, Davies GE, Evans DM, Geoffroy M-C, Grallert H, Groen-Blokhuis MM, Hudziak JJ, Kemp JP, Keltikangas-Järvinen L, McMahon G, Mileva-Seitz VR et al (2016) A genome-wide approach to children’s aggressive behavior: the EAGLE consortium. Am J of Med Genet B 171(5):562–572

    Article  Google Scholar 

  • Peterson RE, Kuchenbaecker K, Walters RK, Chen CY, Popejoy AB, Periyasamy S, Lam M, Iyegbe C, Strawbridge RJ, Brick L, Carey CE, Martin AR, Meyers JL, Su J, Chen J, Duncan LE (2019) Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. Cell 179(3):589–603

    Article  PubMed  PubMed Central  Google Scholar 

  • Pluess M, Belsky J (2013) Vantage sensitivity: individual differences in response to positive experiences. Psychol Bull 139(4):901–916

    Article  PubMed  Google Scholar 

  • Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D et al (2007) PLINK: a tool set for whole genome association and population-based linkage analyses. Am J Hum Genet 81(3):559–575

    Article  PubMed  PubMed Central  Google Scholar 

  • R Core Team (2020) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Retrieved August 4, 2020 from https://www.R-project.org/

  • Raine A (2002) Biosocial studies of antisocial and violent behavior in children and adults: a review. J Abnor Child Psychol 30(4):311–326

    Article  Google Scholar 

  • Rhee SH, Waldman ID (2002) Genetic and environmental influences on antisocial behavior: a meta-analysis of twin and adoption studies. Psychol Bull 128(3):490–529

    Article  PubMed  Google Scholar 

  • Rosseel Y (2012) Lavaan: an R package for structural equation modeling and more. Version 0.6–7 (BETA). J Stat Softw 48(2):1–36

    Article  Google Scholar 

  • Ruisch IH, Dietrich A, Klein M, Faraone SV, Oosterlaan J, Buitelaar JK, Hoekstra PJ (2020) Aggression based genome-wide, glutamatergic, dopaminergic and neuroendocrine polygenic risk scores predict callous-unemotional traits. Neuropsychopharmacology 45(5):761–769

    Article  PubMed  PubMed Central  Google Scholar 

  • Salvatore JE, Aliev F, Bucholz K, Agrawal A, Hesselbrock V, Hesselbrock M et al (2015) Polygenic risk for externalizing disorders: gene-by-development and gene-by-environment effects in adolescents and young adults. Clin Psychol Science 3(2):189–201

    Article  Google Scholar 

  • Simmons RG, Burgeson R, Carlton-Ford S, Blyth DA (1987) The impact of cumulative change in early adolescence. Child Dev 58(5):1220–1234

    Article  PubMed  Google Scholar 

  • Tasca M, Rodriguez N, Zatz MS (2011) Family and residential instability in the context of paternal and maternal incarceration. Crim Justice Behav 38(3):231–247

    Article  Google Scholar 

  • ThermoFisher Scientific (2020) AxiomTM genotyping solution data analysis: user guide. Santa Clara. Retrieved July 29, 2020 from https://assets.thermofisher.com/TFS-Assets/LSG/manuals/axiom_genotyping_solution_analysis_guide.pdf

  • Tielbeek JJ, Johansson A, Polderman TJ, Rautiainen MR, Jansen P, Taylor M, Tong X, Lu Q, Burt AS, Tiemeier H, Viding E, Plomin R, Martin NG, Heath AC, Madden PAF, Montgomery G, Beaver KM, Waldman I, Gelernter J et al (2017) Genome-wide association studies of a broad spectrum of antisocial behavior. JAMA Psychiat 74(12):1242–1250

    Article  Google Scholar 

  • Tuvblad C, Grann M, Lichtenstein P (2006) Heritability for adolescent antisocial behavior differs with socioeconomic status: gene–environment interaction. J Child Psychol Psychiatry 47(7):734–743

    Article  PubMed  Google Scholar 

  • United States Census Bureau (2020) “Geographic mobility: 2019 to 2020” Table 1. 10 December 2020

  • Van Beijsterveldt CEM, Bartels M, Hudziak JJ, Boomsma DI (2003) Causes of stability of aggression from early childhood to adolescence: a longitudinal genetic analysis in Dutch twins. Behav Genet 33(5):591–605

    Article  PubMed  Google Scholar 

  • Veroude K, Zhang-James Y, Fernàndez-Castillo N, Bakker MJ, Cormand B, Faraone SV (2016) Genetics of aggressive behavior: an overview. Am J Med Genet B Neuropsychiatr Genet 171(1):3–43

    Article  Google Scholar 

  • Vierikko E, Pulkkinen L, Kaprio J, Rose RJ (2006) Genetic and environmental sources of continuity and change in teacher-rated aggression during early adolescence. Aggress Behav 32(4):308–320

    Article  Google Scholar 

  • West-Eberhard MJ (2003) Developmental plasticity and evolution. Oxford University Press, Oxford

    Book  Google Scholar 

  • Womack SR, Taraban L, Shaw DS, Wilson MN, Dishion TJ (2019) Family turbulence and child internalizing and externalizing behaviors: moderation of effects by race. Child Dev 90(6):e729–e744

    Article  PubMed  Google Scholar 

  • Zilanawala A, Sacker A, Kelly Y (2019) Internalising and externalising behaviour profiles across childhood: the consequences of changes in the family environment. Soc Sci Med 226:207–216

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This research was supported by grants from the National Institute on Drug Abuse (Grant Nos. DA022773, DA023245, and DA036832) awarded to Thomas J. Dishion, Daniel S. Shaw, and Melvin N. Wilson. We thank the families for their participation and the research staff for their help with data collection and management.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study conception and design. Data aggregation and analysis were performed by SW. The first draft of the manuscript was written by SW with substantial input from all authors. All authors commented on previous versions of the manuscript and have read and approved the final manuscript.

Corresponding author

Correspondence to Sean R. Womack.

Ethics declarations

Conflicts of interest

Sean Womack, Sierra Clifford, Melvin Wilson, Daniel Shaw, and Kathryn Lemery-Chalfant declare that they have no conflicts of interest.

Ethical Approval

All procedures performed in the current study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the University of Virginia Institutional Review Board (IRB# PRO19090045).

Consent to Participate

Written informed consent from primary caregivers at each wave, and verbal assent from youth beginning at age 14.

Consent for Publication

Not applicable.

Additional information

Edited by Lisabeth F. DiLalla

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 440 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Womack, S.R., Clifford, S., Wilson, M.N. et al. Genetic Moderation of the Association Between Early Family Instability and Trajectories of Aggressive Behaviors from Middle Childhood to Adolescence. Behav Genet 51, 476–491 (2021). https://doi.org/10.1007/s10519-021-10069-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10519-021-10069-5

Keywords

Navigation