Polygenic risk scores and brain structures both contribute to externalizing behavior in childhood - A study in the Adolescent Brain and Cognitive Development (ABCD) cohort

Neuroscience Applied, vol. 2, pp. 101128

Abstract

Introduction: Externalizing behaviors are defined as behaviors violating social norms and can be harmful to self and others. Predicting the escalation of externalizing behaviors in children would allow for early interventions to prevent the occurrence of antisocial and criminal acts. Externalizing behaviors are heritable traits, and have been associated with structures of the brain. Brain structure, in turn, is also influenced by genetics. Here, we investigated the association of genetic and brain structural variation with externalizing behaviors in late childhood, and we assessed potential mediating effects. Methods: Data was collected for 11,878 children aged 9-10 years old from the Adolescent Brain Cognitive Development (ABCD) cohort. We extracted data on externalizing behaviors measured by the parent-reported Child Behavior Checklist (CBCL), brain volumes and white matter integrity measured by magnetic resonance imaging (MRI), and polygenic risk scores (PRS) for (i) antisocial behaviors, (ii) attention-deficit/hyperactivity disorder comorbid with disruptive behavior disorder (ADHD ​+ ​DBD), (iii) irritability, and (iv) traits related to self-regulation & addiction. We examined the associations between brain structures, PRS, and externalizing behavior, and to what extent brain structures mediate the association between PRS and externalizing behavior. Phenotypic associations between brain structures and externalizing behaviors were validated in an independent cohort of 150 adolescents aged 12-21 years enriched for individuals with antisocial behavior. Results: Increasing levels of externalizing behaviors were associated with reduced total brain and focal gray matter volumes, but not with white matter integrity. These results could not be validated in the independent cohort, except for a good correlation of several effect sizes between the cohorts. Higher PRS for externalizing behaviors were associated with lower cortical gray matter volume, larger subcortical gray matter volume, larger white matter volume, and reduced global white matter fractional anisotropy. Genetic and brain structural variation, combined with sociodemographic factors, explained up to 7% of variation in externalizing behaviors in late childhood; brain structures and PRS each explained up to ∼0.5% of variation. A multivariate model with all sociodemographic factors, brain structures and PRS combined explained up to 11.9% (+5%). Total cortical gray matter volume mediated the association between PRS for ADHD ​+ ​DBD and externalizing behavior in late childhood. However, a large proportion of individual variation in externalizing behavior remained unidentified (∼90%). Brain function and interaction effects with the environment are surmised as potential sources of additional variation.

Authors 8

1. Jalmar Teeuw corresponding

   University Medical Center Utrecht

   Affiliation as printed

   Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands

2. Nina Roth Mota

   Radboud University Nijmegen · Radboud University Medical Center · Donders Institute for Brain, Cognition and Behaviour

   Affiliation as printed

   Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands

   Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands

3. Marieke Klein

   Radboud University Nijmegen · Radboud University Medical Center · University of California San Diego · Donders Institute for Brain, Cognition and Behaviour

   Affiliation as printed

   Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands

   Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States

   Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands

4. Neeltje E. Blankenstein Aachen Department of Developmental and Educational Psychology Institute of Psychology, Leiden University

   Leiden University · Amsterdam University Medical Centers · Vrije Universiteit Amsterdam

   Affiliation as printed

   Department of Child and Adolescent Psychiatry and Psychosocial Care, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands

   Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, the Netherlands

5. Jorim J. Tielbeek

   Amsterdam University Medical Centers · Vrije Universiteit Amsterdam

   Affiliation as printed

   Department of Child and Adolescent Psychiatry and Psychosocial Care, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands

6. Lucres M. C. Jansen

   Amsterdam University Medical Centers · Vrije Universiteit Amsterdam

   Affiliation as printed

   Department of Child and Adolescent Psychiatry and Psychosocial Care, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands

7. Barbara Franke

   Radboud University Nijmegen · Radboud University Medical Center · Donders Institute for Brain, Cognition and Behaviour

   Affiliation as printed

   Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands

   Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands

   Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands

8. Hilleke E. Hulshoff Pol

   Utrecht University · University Medical Center Utrecht

   Affiliation as printed

   Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, the Netherlands

   Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands