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The goal of ACTION project (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies) was to identify precursors, features, and consequences of childhood aggression using epidemiological and omics-driven studies. A considerable effort within ACTION was the collection of new omics data in children with low and high aggressive behavior. To this end, the ACTION project included large-scale collection of biological samples in children from the Netherlands Twin Register (NTR), a twin cohort from the general population, and a cohort of children referred for psychiatric treatment (LUMC-Curium). Together these cohorts comprise the ACTION Biomarker Study. This documentation describes the study design and data collection for the ACTION Biomarker Study.

In the classical twin design, researchers compare trait resemblance in cohorts of identical and non-identical twins to understand how genetic and environmental factors correlate with resemblance in behaviour and other phenotypes. The twin design is also a valuable tool for studying causality, intergenerational transmission, gene-environment correlation and interaction. Here we review recent developments in twin studies, recent results from twin studies of new phenotypes, and recent insights into twinning. We ask whether the results of existing twin studies are representative of the general population and of global diversity, and conclude that stronger efforts to increase representativeness are needed. We provide an updated overview of twin concordance and discordance for major diseases and mental disorders, which conveys a crucial message: genetic influences are not as deterministic as many believe. This has important implications for public understanding of genetic risk prediction tools, as the accuracy of genetic predictions can never exceed identical twin concordance rates.

This study introduces and illustrates the potential of an integrated multi-omics approach in investigating the underlying biology of complex traits such as childhood aggressive behavior. In 645 twins (cases = 42%), we trained single- and integrative multi-omics models to identify biomarkers for subclinical aggression and investigated the connections among these biomarkers. Our data comprised transmitted and two non-transmitted polygenic scores (PGSs) for 15 traits, 78,772 CpGs, and 90 metabolites. The single-omics models selected 31 PGSs, 1614 CpGs, and 90 metabolites, and the multi-omics model comprised 44 PGSs, 746 CpGs, and 90 metabolites. The predictive accuracy for these models in the test (N = 277, cases = 42%) and independent clinical data (N = 142, cases = 45%) ranged from 43 to 57%. We observed strong connections between DNA methylation, amino acids, and parental non-transmitted PGSs for ADHD, Autism Spectrum Disorder, intelligence, smoking initiation, and self-reported health. Aggression-related omics traits link to known and novel risk factors, including inflammation, carcinogens, and smoking.

The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores (PGS)), epigenomics and metabolomics data in a multi-omics framework to identify biomarkers for ADHD and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases=14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein familyTMEM, show that the DNA methylation of theMAD1L1gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of theSTAP2gene. Out-of-sample prediction in NTR participants (N=258, cases=14.3%) and in a clinical sample (N=145, cases=51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGS, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.

To investigate the biological etiology of human aggressive behavior through biomarker discovery and to explore the genetic etiology of variation in blood metabolite levels in humans, I analyzed twin-family data collected by the Netherlands Twin Register (NTR) and data of children referred to an academic centrum for child- and adolescent psychiatry. In my thesis, I argue for combining the classical twin design with genome-wide SNP (Single-Nucleotide Polymorphism) data to simultaneously estimate the total and SNP-based heritability. When analyzing 361 blood metabolites measured in a cohort of 5117 twin-family members, I applied this approach and found a stronger contribution of metabolite loci to lipids than to organic acids, and showed that the variance explained by metabolite loci differs significantly among metabolite classes and lipid species. These approaches based on measured SNPs are unsuitable for investigating the contribution of shared environmental factors. Therefore, I applied the classic twin design to 237 blood metabolite levels in 886 monozygotic (MZ) and 601 dizygotic (DZ) adult twin pairs, and reported significant estimates of the shared environment for only 6 out of 237 metabolites. To conclude, additive genetic factors contribute to approximately 50% of the individual variance in blood metabolites levels in adults. To look at aggression and biochemical biomarkers, I began with reviewing the existing literature for human aggression and related traits and found associations with biomarkers of multiple classes, including inflammation markers, neurotransmitters, lipoproteins, and thyroid and steroid hormones. However, I did not replicate the associations of lipid, inflammation, and related biomarkers with adult aggression in a twin-family cohort (N=5588), but found differences in glucose, fibrinogen, C-reactive protein, interleukin-6, and low-density lipoprotein cholesterol levels in the extremely discordant MZ twin pairs (12 pairs). I also tested the hypothesis that lipid CpG sites are differentially methylated in adult aggression, but this hypothesis was not supported. I coordinated the large-scale collection of urine and buccal-cell samples for (epi)genomic and metabolomic measurements in young twin pairs selected on aggression in the NTR, and share the protocols in my thesis. When analyzing these data, I observed associations of the urinary metabolites o-phosphoserine and gamma-L-glutamyl-L-alanine with childhood aggression in the discovery twin cohort (N=783). These findings did not replicate in an independent sample of discordant twin pairs (N=378) or in a cohort of clinical cases and matched twin controls (N=367). The top associated metabolites hint at a role of metabolic dysregulation of neurotransmission, energy metabolism, and oxidative stress in childhood aggression. Next, I performed an integrated multi-omics analysis of childhood aggression based on urinary metabolites, genome-wide DNA methylation, and SNP-based transmitted and non-transmitted polygenic scores for aggression and correlated traits. The metabolite data included a new platform targeting steroid hormones. Training of multi-omics models for childhood aggression showed good in-sample prediction through cross-validation (N=645), but out-of-sample prediction in hold-out (N=277) and clinical samples (N=142) was poor. The high correlations among the omics traits selected in the multi-omics models confirmed associations of childhood aggression with known risk factors and provided novel insight into the correlational structure of omics traits from different omics layers. For example, we showed that indirect genetic effects correlate most strongly with DNA methylation and amino acid levels, suggesting that parental genotypes influence offspring omics traits through the rearing environments parents create for their offspring. In summary, genetic factors influence on blood metabolite levels, and the shared environment contributes marginally to familial resemblance in blood metabolites. For childhood aggression, heritability is around 50%. When combining aggression and biomarker information, we see broad biological pathways that appear to play a role in human aggressive behavior, including dysregulation of neurotransmission, inflammation, and lipid, steroid hormone, and energy metabolism pathways.

Objective: To investigate the genetic architecture of internalizing symptoms in childhood and adolescence. Method: In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument. Results: The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Conclusion: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success. Dr. Border has received support from the National Institutes of Health (NIH; MH100141 and MH016880 ). Dr. Peterson has received support from NIH (K01MH113848) and the Brain & Behavior Research Foundation Young Investigator Grant (28632). Drs. Sallis and Munafò have served as members of the MRC Integrative Epidemiology Unit at the University of Bristol (MC_UU_00011/7). Dr. Shabalin has received support from a NARSAD Young Investigator Award. Dr. Vilor-Tejedor has received support from a post-doctoral grant, Juan de la Cierva Programme (FJC2018-038085-I), Ministerio de Ciencia, Innovación y Universidades – Spanish State Research Agency. Her research has received additional support of “la Caixa” Foundation (LCF/PR/GN17/10300004) and the Health Department of the Catalan Government (Health Research and Innovation Strategic Plan (PERIS) 2016-2020 grant# SLT002/16/00201). She has acknowledged the support of the Spanish Ministry of Science, Innovation and Universities to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme/Generalitat de Catalunya. Dr. Alemany has received support from a Juan de la Cierva – Incorporación Postdoctoral Contract from Ministerio de Economía, Industria y Competitividad (IJCI-2017-34068). Dr. Corley has received support from NIH (DA011015, AG046938, and DA035804). Dr. Evans has received support from NIH (MH100141, DA044283, and AG046938). Dr. Havdahl has received support from the South-Eastern Norway Regional Health Authority (2018059) at Nic Waals Institute, Lovisenberg Diaconal Hospital. Dr. Rimfeld has received support from a Sir Henry Wellcome Postdoctoral Fellowship. Dr. Andreassen has served as a consultant to HealthLytix and has received funding from the Research Council of Norway (223273 and 273291) and KG Jebsen Stiftelsen. Dr. Boomsma has received support from the Royal Netherlands Academy of Science Professor Award (PAH/5535). Dr. Brown has received support from NIH (DA035804). Dr. Copeland has received support from NIH (MH117559 and HD093651). Dr. Dick has received support from a mid-career award NIH K02 AA018755, NIH R01 AA015416 (Finnish Twin Study), P50 AA022537 (Alcohol Research Center), R25 AA027402 (VCU GREAT), and U10 AA008401 (COGA) from the National Institute on Alcohol Abuse and Alcoholism. Drs. Hewitt, Krauter, Smolen, and Stallings have received support from NIH (DA011015 and DA035804). Dr. Hopfer has received support from NIH (DA042755, DA035804, and DA032555). Dr. Kaprio has received support from the Academy of Finland (grants 308248 and 312073). Dr. Larsson has served as a speaker for Evolan Pharma and Shire/Takeda and has received research grants from Shire/Takeda, all outside the submitted work. Dr. Lichtenstein has received support from the Swedish Research Council for Health, Working Life and Welfare (project 2012-1678) and the Swedish Research Council (2016-1989). Dr. Lundström has received support from the Swedish Research Council ( 2017-02552 ). Dr. Magnus has received support from the Research Council of Norway through its Centers of Excellence scheme, project no 262700. Dr. Njølstad has received support from the European Research Council (AdG #293574). Stiftelsen Kristian Gerhard Jebsen has received support from the Research Council of Norway (FRIPRO 240413), the Western Norway Regional Health Authority (Strategic Fund “Personalized Medicine for Children and Adults”) and the Novo Nordisk Foundation (54741). Dr. Plomin has received support from a MRC Professorship award (G19/2). Dr. Reichborn-Kjennerud has received support from the Research Council of Norway grant 274611 . Drs. Reynolds and Wadsworth have received support from NIH (AG046938). Dr. Rose has received support from a NIH Research Scientist Award (AA-000145). Dr. Wall has received support from NIH (DA03580 and DA021905). Dr. Whitehouse has received support from an Investigator Grant from the National Health and Medical Research Council. Dr. Ystrøm has received support from the Research Council of Norway (262177 and 288083). Dr. Nivard has received support from ZonMW (849200011), the Netherlands Organisation for Health Research and Development (531003014 937), a Jacobs Foundation Research Fellowship, and a VENI grant awarded by NWO (VI.Veni.191G.030). Dr. Bartels has received support from an ERC Consolidator Grant (WELL-BEING 771057). Ms. Hagenbeek and Mr. Ip have received support from the Aggression in Children: Unraveling gene-environment interplay to inform Treatment and Intervention strategies project (ACTION). ACTION received funding from the European Union Seventh Framework Program (FP7/2007-2013) under grant agreement no 602768