Childhood aggression and the co-occurrence of behavioural and emotional problems: results across ages 3–16years from multiple raters in six cohorts in the EU-ACTION project

Childhood aggression and the co-occurrence of behavioural and emotional problems: results across... Childhood aggression and its resulting consequences inflict a huge burden on affected children, their relatives, teachers, peers and society as a whole. Aggression during childhood rarely occurs in isolation and is correlated with other symptoms of childhood psychopathology. In this paper, we aim to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychopathology. We focus on the co-occurrence of aggression and other childhood behavioural and emotional problems, including other externalising problems, attention problems and anxiety–depression. The data were brought together within the EU-ACTION (Aggression in Children: unravelling gene-environment interplay to inform Treatment and InterventiON strategies) project. We analysed the co-occurrence of aggression and other childhood behavioural and emotional problems as a function of the child’s age (ages 3 through 16 years), gender, the person rating the behaviour (father, mother or self) and assessment instrument. The data came from six large population-based European cohort studies from the Netherlands (2x), the UK, Finland and Sweden (2x). Multiple assessment instruments, including the Child Behaviour Checklist (CBCL), the Strengths and Difficulties Questionnaire (SDQ) and Multidimensional Peer Nomi- nation Inventory (MPNI), were used. There was a good representation of boys and girls in each age category, with data for 30,523 3- to 4-year-olds (49.5% boys), 20,958 5- to 6-year-olds (49.6% boys), 18,291 7- to 8-year-olds (49.0% boys), 27,218 9- to 10-year-olds (49.4% boys), 18,543 12- to 13-year-olds (48.9% boys) and 10,088 15- to 16-year-olds (46.6% boys). We replicated the well-established gender differences in average aggression scores at most ages for parental ratings. The gender differences decreased with age and were not present for self-reports. Aggression co-occurred with the majority of other behavioural and social problems, from both externalising and internalising domains. At each age, the co-occurrence was particularly prevalent for aggression and oppositional and ADHD-related problems, with correlations of around 0.5 in general. Aggression also showed substantial associations with anxiety–depression and other internalizing symptoms (correlations around 0.4). Co-occurrence for self-reported problems was somewhat higher than for parental reports, but we found neither rater differences, nor differences across assessment instruments in co-occurrence patterns. There were large similarities in co-occurrence patterns across the different European countries. Finally, co-occurrence was generally stable across age and sex, and if any change was observed, it indicated stronger correlations when children grew older. We present an online tool to visualise these associations as a function of rater, gender, instrument and cohort. In addition, we present a description of the full EU-ACTION projects, its first results and the future perspectives. This article is part of the focused issue ‘Conduct Disorder and Aggressive Behaviour in Children and Adolescents’. Extended author information available on the last page of the article Vol.:(0123456789) 1 3 1106 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Keywords Aggression · Childhood · Comorbidity · Co-occurence · Behavioural and emotional problems of differences in aggression between children by unravelling Introduction its genetic architecture using univariate, multivariate and longitudinal genetic and epigenetic modelling in twin and Prevention strategies and behavioural and pharmacological genetic and epigenetic association studies. A strong focus interventions for aggressive behaviour and conduct disor- of ACTION includes biomarker and metabolomics research der are effective in some children, although a substantial [21]. number of children do not respond to prevention strate- In the current study, the aim is to describe and improve gies, do not benefit from interventions or may even expe- the understanding of the co-occurrence of aggression with rience an escalation of symptom [9, 10]. One reason for other forms of childhood psychopathology by analysing this might be the heterogeneity of aggression. A second data from the large ACTION phenotype databases in large reason, which is related to the heterogeneous nature and samples of children. We analysed data on aggression and occurrence of childhood aggressive problems, might be that common emotional and behavioural problems in children children with aggressive problems often have co-occurring aged 3–16 years. Multiple raters, i.e. fathers and mothers problems. Due to a multitude of problems, children may during childhood and also youngsters themselves during not respond to prevention or intervention targeting aggres- adolescence, provided information on different aggression sion, or the co-occurring problems may mask aggression, measures. The two Dutch cohorts (The Netherlands Twin leaving it untreated. In 12 year olds, Bartels and colleagues Register and Generation R) used the Achenbach System [11] observed that at least half of the children who were of Empirically Based Assessment (ASEBA [22]), which deviant on aggressive behaviour (T score ≥ 67) also were included the Child Behaviour Checklist (CBCL) and the deviant on rule-breaking behaviour, i.e. at least 50% of the Youth Self-Report (YSR). The UK-based Twins Early children with clinical levels of aggression also showed a Development Study employed the Strengths and Difficulties co-occurrence of clinically relevant rule-breaking behaviour. Questionnaire (SDQ [23]). The Swedish Twin study of Child Strong links between aggression and attention-deficit/hyper - and Adolescent Development used the Autism–Tics, ADHD activity disorder (ADHD) [12] are often seen in the clinical and other Comorbidities inventory (A-TAC [24]), and the presentation of ADHD [13], and it has been suggested that Swedish Child and Adolescent Twin Study the ASEBA the strong association between ADHD and aggression may questionnaires. In Finland, the Multidimensional Peer Nom- explain gender differences in clinical referral. For example, ination Inventory (MPNI) was employed. For several age teachers rated boys with a DSM-based ADHD diagnosis as groups from different countries, aggression assessed with having higher levels of attention problems and aggression identical instruments was available. For example, parental than girls with a similar ADHD diagnosis [14]. Aggression ratings with the CBCL were available for 7- to 8-year-olds not only co-occurs with psychopathologies on the exter- and 12- to 13-year-olds in the Netherlands (NTR) and Swe- nalizing spectrum. Aggression also tends to co-occur with den (TCHAD). In addition to indicators of aggression, all anxiety, and it has been proposed that anxiety needs to be instruments provided quantitative scores on other childhood given a central role in the treatment of aggression [15]. In psychopathologies from the externalising and internalising more extreme cases, aggression was not found to co-occur spectrum. We investigated patterns of co-occurrence across solely with ADHD symptoms, such as attention problems, or age, rater, instrument and gender. anxiety but rather with both of these forms of psychopathol- ogy. This pattern of behavioural problems is referred to as the dysregulation profile [16–18], and has been described as Methods a potential marker for severe childhood psychopathologies [19, 20]. Participants To gain insight into the aetiology of individual differences in childhood aggression and in co-occurring behavioural and Six large population-based cohorts (NTR and GenR from emotional problems, ACTION (Aggression in Children: the Netherlands, TEDS from the UK, CATSS and TCHAD unravelling gene-environment interplay to inform Treatment from Sweden and FinnTwin12 from Finland) analysed the and InterventiON strategies; http://www.actio n-eupro ject. co-occurrence of aggression measures with other psycho- eu/) created a consortium with access to large childhood pathologies. For a link to cohort-specific websites, see prospective twin, population-based and clinical cohorts. Table 1 and for a detailed description of the cohorts, please ACTION brings together multiple large cohort studies in also see Appendix I. The twin cohorts were requested to genetically informative populations (see Table 1 and Appen- randomly select one of the twins per pair, with an equal dix 1). The focus of ACTION is to inform on the aetiology 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1107 representation of first- and second-born children, to obtain parameter estimates that were not biased due to effects of family clustering. In our previous work [25], we have shown that children with an illness or disability that interfered with daily function tend to display more than twice as much problem behaviour across the entire age range compared to other twins, so they were excluded. Age-, gender- and rater- specific sample sizes are presented in Tables  2, 3, 4 and 5. Data were available for 30,523 3- to 4-year-olds (49.5% boys), 20,958 5- to 6-year-olds (49.6% boys), 18,291 7- to 8-year-olds 49% boys), 27,218 9- to 10-year-olds (49.4% boys), 18,543 11- to 12-year-olds (48.9% boys) and 10,088 15- to 16-year- olds (46.6% boys). Due to the longitudinal structure of most cohorts, these data points are not statisti- cally independent observations, since overlapping groups of children were assessed at multiple ages. All data used in the current analyses were collected under protocols that have been approved by the appropriate ethics committees, and studies were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Measures The Child Behaviour Checklist (CBCL) 1,5–5 [26] and 6–18 [22] were used by GenR (age 6 and 10), TCHAD (ages 8, 13 and 16) and NTR (ages 3, 7, 9 and 12). The Youth Self- Report (YSR) [22] was used by TCHAD (ages 13 and 16). The CBCL and YSR are part of the Achenbach System of Empirical-Based Assessment and designed to measure childhood and adolescent behavioural and emotional prob- lems. The response format was on a three-point scale (with response options ‘not true’, ‘somewhat true or sometimes true’ and ‘very or often true’). With the CBCL 1,5–5 seven syndrome scales are obtained (emotionally reactive, anx- ious–depressed, somatic complaints, withdrawn, overactive behaviour, aggressive behaviour, sleep problems), while with the CBCL 6–18 eight syndrome scales are obtained (anxious–depressed, withdrawn, somatic complaints, social problems, thought problems, attention problems, rule-break- ing behaviour, aggressive behaviour). With the YSR, eight syndrome scales are obtained (anxious–depressed, somatic complaints, withdrawn–depressed, social problems, thought problems, attention problems, rule-breaking behaviour and aggressive behaviour). The Strengths and Difficulties Questionnaire (SDQ) [ 23] was used by TEDs (ages 4, 7, 9, 16) and CATSS (age 15). The SDQ is a 25-item questionnaire designed to measure common mental health problems during childhood and ado- lescence. Ratings were on a three-point scale (with response options ‘not true’, ‘somewhat true’ and ‘certainly true’). The 25 items form 5 scales, emotional symptoms, conduct prob- lems, hyperactivity/inattention, peer relationship problem 1 3 Table 1 Sample sizes for different age groups of the ACTION cohort Register Age Webpages 1–2 3–4 5–6 7–8 9–10 11–12 13–14 15–16 17–18 19–20 21–22 NTR 106.7 37.9 31.2 23.2 18.1 15.1 8.0 5.7 1.7 6.0http://www.Tweel ingen regis ter.org Qtwin 2.4 1.4 1.8 0.9http://www.qimrb ergho fer.edu.au/qtwin / TEDS 12.6 28.4 29.2 6.8 11.8 6.7 10.2 http://www.Teds.ac.uk TCHAD 2.0 2.0 2.0 2.0http://ki.se/en/meb/twin-study -of-child -and-adole scent -devel opmen t-tchad CATSS 22.3 6.5 11.1 8.7http://ki.se/en/meb/the-child -and-adole scent -twin-study -in-swede n-catss FT12 5.3 4.7 4.2 1.3https ://wiki.helsi nki.fi/displ ay/twine ng/Twins tudy GenR 4.5 5.2 7.8 5.0http://www.gener ation r.nl Indiv (x 1000) 123.8 71.5 39 54.4 40.4 45 22.8 24.7 8.1 8 2.2 1108 European Child & Adolescent Psychiatry (2018) 27:1105–1121 and prosocial behaviour. The conduct problem scale was used as a proxy for aggressive behaviour. NTR used the short Devereux Child Behaviour (DCB) rating scale for 5 year olds. The DCB consists of questions about problem behaviour in children rated by the parents [27]. The short version includes 42 items that measure seven different aspects of problem behaviour in children. Parents were asked to indicate on a five-point scale whether the statements were applicable (0 = never, 1 = rarely, 2 = occa- sionally, 3 = frequently, 4 = very frequently). The items of the questionnaire cover the following aspects of problem behaviour: emotional liability (five items, e.g. “markedly impatient”), social isolation (three items, e.g. “quite timid or shy”), aggressive behaviour (seven items, e.g. “hits, bites and scratches other children”), attention problems (five items, e.g. “jumps from one activity to another”), depend- ency (five items, e.g. “does not want to do things for him- self”), anxiety problems (six items, e.g. “concern about his physical health”) and physical coordination (five items, e.g. “gets dirty and untidy”). In 9- and 12-year-old in the CATSS sample from Sweden, information on ODD/CD and other psychopathologies was gathered through a telephone interview with parents, using The Autism–Tics, ADHD and other Comorbidities inven- tory (A-TAC) [24]. A-TAC is a comprehensive screening interview for autism spectrum disorders (ASDs), attention- deficit/hyperactivity disorder (AD/HD), tic disorders (TD), developmental coordination disorder (DCD), learning dis- orders (LD) and other childhood mental disorders that have been associated with these neurodevelopmental disorders. In the FinnTwin12 sample from Finland, aggressive behaviour was assessed at ages 12, 14 and 17 by versions of the Multidimensional Peer Nomination Inventory (MPNI). The MPNI includes 37 items comprising three subscales, the two subscales used here include: externalising behavioural problems (aggression, hyperactivity–impulsivity and inat- tention) and internalising emotional problems (anxiety and depression) [28]. For each question (e.g. ‘Does the child tease smaller or weaker children?’), the informant rated how well the description fit the twin in question on a scale from 0 (the characteristic does not fit the child at all) to 3 (the characteristic fits the child very well). Parents rated the children at age 12, and the child rated him or herself at ages 14 and 17 years. Analyses To ensure homogenous handling of data and identical analy- ses, all cohorts received a standard operating procedure that specified details of the comorbidity analyses. Following the SOP average scores and Pearson correlations for aggres- sion with all other scales assessing psychopathology was obtained by a local analyst using their preferred statistical 1 3 Table 2 Means and standard deviations for the empirical scales of the Child Behaviour Checklist (CBCL) 1.5–5 ASEBA- Rater Age Sex N Aggressive behaviour Attention problems Withdrawn Anxious– depressed Emotional reactivity Somatic complaints Sleep problems CBCL 1.5–5 Gen R Mother 3 Boy 2271 7.58 (5.37) 1.56 (1.64) 0.98 (1.43) 1.08 (1.56) 1.67 (1.82) 1.61 (1.61) 1.98 (2.16) 3 Girl 2246 6.37 (4.91) 1.44 (1.56) 0.84 (1.24) 0.99 (1.48) 1.55 (1.79) 1.57 (1.74) 1.92 (2.09) Gen R Father 3 Boy 1840 8.24 (5.60) 1.80 (1.72) 1.03 (1.40) 1.16 (1.54) 1.86 (1.99) 1.64 (1.79) 2.08 (2.24) 3 Girl 1897 7.14 (5.03) 1.55 (1.61) 0.93 (1.27) 1.10 (1.52) 1.67 (1.89) 1.52 (1.67) 1.91 (2.04) NTR Mother 3 Boy 9277 11.48 (6.85) 2.34 (1.97) 1.47 (1.69) 1.95 (1.99) 2.92 (2.66) 1.76 (1.84) 1.86 (2.18) 3 Girl 9360 9.95 (6.30) 2.03 (1.84) 1.39 (1.56) 2.05 (2.00) 2.96 (2.57) 1.86 (1.92) 1.93 (2.20) Gen R Mother 6 Boy 2887 6.65 (5.79) 1.84 (1.85) 1.33 (1.64) 1.51 (1.93) 1.97 (2.38) 1.56 (1.89) 1.49 (1.93) 6 Girl 2856 5.93 (4.90) 1.30 (1.59) 1.02 (1.35) 1.46 (1.83) 1.68 (2.06) 1.61 (1.89) 1.51 (1.93) European Child & Adolescent Psychiatry (2018) 27:1105–1121 1109 1 3 Table 3 Means and standard deviations for the empirical scales of the ASEBA taxonomy (CBCL and YSR) ASEBA Rater age Sex N Aggressive Attention Rule breaking Social problems Anxious– Withdrawn– Thought problems Somatic complaints 6–18 behaviour problems depressed depressed NTR Mother 7 Boy 5720 5.74 (5.29) 3.48 (3.13) 1.58 (2.02) 2.17 (2.48) 2.12 (2.53) 1.14 (1.63) 1.66 (2.14) 1.10 (1.57) 7 Girl 5853 4.38 (4.28) 2.56 (2.79) 1.07 (1.55) 1.91 (2.24) 2.31 (2.58) 1.09 (1.53) 1.29 (1.77) 1.26 (1.68) NTR Father 7 Boy 4134 4.98 (4.75) 3.13 (2.97) 1.37 (1.85) 1.80 (2.18) 1.62 (2.04) 0.95 (1.45) 1.33 (1.85) 0.81 (1.28) 7 Girl 4182 3.81 (4.01) 2.26 (2.59) 0.95 (1.47) 1.58 (1.95) 1.77 (2.19) 0.86 (1.36) 0.91 (1.46) 0.91 (1.39) TCHAD Parent 8 Boy 552 5.49 (5.42) 1.91 (2.40) 1.18 (1.63) 0.99 (1.57) 1.74 (2.61) 0.99 (1.24) 0.13 (0.59) 0.56 (1.04) 8 Girl 534 4.77 (4.89) 1.32 (2.07) 0.79 (1.28) 0.84 (1.52) 2.01 (2.75) 1.13 (1.35) 0.13 (0.53) 0.75 (1.28) NTR Mother 9 Boy 4543 5.09 (5.16) 3.43 (3.21) 1.43 (2.06) 2.05 (2.54) 2.14 (2.67) 1.24 (1.75) 1.61 (2.14) 1.07 (1.59) 9 Girl 4689 3.94 (4.20) 2.42 (2.75) 0.93 (1.55) 1.83 (2.34) 2.39 (2.80) 1.13 (1.64) 1.25 (1.80) 1.28 (1.78) NTR Father 9 Boy 3210 4.18 (4.57) 3.07 (3.11) 1.17 (1.78) 1.72 (2.33) 1.65 (2.21) 1.00 (1.60) 1.27 (1.88) 0.83 (1.38) 9 Girl 3255 3.34 (3.82) 2.17 (2.64) 0.79 (1.38) 1.55 (2.07) 1.86 (2.33) 0.91 (1.46) 0.93 (1.48) 0.88 (1.39) Gen R Mother 10 Boy 2250 3.26 (4.08) 3.76 (3.35) 1.24 (1.67) 1.84 (2.35) 2.14 (2.72) 1.29 (1.78) 1.80 (2.36) 1.34 (1.92) 10 Girl 2310 2.54 (3.34) 2.81 (3.00) 0.81 (1.27) 1.62 (2.13) 2.28 (2.64) 1.01 (1.48) 1.50 (2.01) 1.59 (2.02) Gen R Father 10 Boy 1624 3.28 (4.16) 3.81 (3.31) 1.36 (1.69) 1.96 (2.35) 2.05 (2.54) 1.36 (1.74) 1.92 (2.39) 1.25 (1.72) 10 Girl 1670 1.47 (3.24 2.87 (2.81) 0.89 (1.30) 1.71 (2.01) 2.11 (2.58) 1.00 (1.48) 1.43 (1.82) 1.41 (1.80) NTR Mother 12 Boy 3870 4.18 (4.63) 3.21 (3.20) 1.28 (1.87) 1.72 (2.45) 1.90 (2.56) 1.25 (1.81) 1.36 (2.02) 0.89 (1.41) 12 Girl 4010 3.27 (3.82) 2.12 (2.59) 0.79 (1.37) 1.46 (2.17) 2.18 (2.70) 1.10 (1.76) 1.03 (1.64) 1.03 (1.58) NTR Father 12 Boy 2764 3.65 (4.36) 3.02 (3.14) 1.15 (1.78) 1.58 (2.39) 1.59 (2.39) 1.10 (1.76) 1.12 (1.77) 0.72 (1.26) 12 Girl 2839 2.80 (3.52) 1.95 (2.49) 0.71 (1.29) 1.23 (1.90) 1.70 (2.29) 0.95 (1.58) 0.77 (1.35) 0.73 (1.26) TCHAD Parent 13 Boy 535 3.90 (4.30) 1.59 (2.08) 1.14 (1.56) 0.79 (1.29) 1.28 (2.01) 1.01 (1.31) 0.13 (0.60) 0.62 (1.13) 13 Girl 522 3.71 (4.60) 1.21 (1.97) 0.82 (1.52) 0.75 (1.53) 2.06 (3.31) 1.27 (1.64) 0.18 (0.67) 0.78 (1.37) TCHAD Self 13 Boy 560 8.07 (4.96) 3.57 (2.78) 2.94 (2.26) 2.02 (2.05) 3.78 (3.72) 2.12 (1.88) 1.31 (1.53) 1.47 (1.76) 13 Girl 551 7.94 (4.33) 3.75 (2.64) 2.64 (2.36) 1.89 (1.80) 5.09 (4.75) 2.42 (1.91) 1.76 (1.98) 2.19 (2.36) TCHAD Parent 16 Boy 532 3.06 (3.83) 1.24 (1.85) 1.12 (1.54) 0.57 (1.08) 1.14 (1.87) 0.90 (1.27) 0.10 (0.41) 0.65 (1.15) 16 Girl 507 3.25 (3.97) 1.21 (1.98) 1.11 (1.94) 0.55 (1.17) 2.18 (3.44) 1.11 (1.51) 0.18 (0.68) 1.09 (1.78) TCHAD Self 16 Boy 583 7.10 (4.38) 3.44 (2.69) 2.93 (2.23) 1.77 (1.91) 2.97 (3.61) 2.01 (1.89) 1.08 (1.65) 1.21 (1.60) 16 Girl 606 7.77 (4.41) 4.14 (2.69) 3.02 (2.39) 1.78 (1.76) 5.60 (4.66) 2.85 (2.07) 1.45 (1.78) 2.34 (2.50) 1110 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Table 4 Means and standard deviations for the scales of the Strengths and Difficulties Questionnaire (SDQ) SDQ Rater Age Sex N Conduct problems Hyperactivity Peer problems Emotion–anxiety Prosocial TEDS Parent 4 Boy 3581 2.23 (1.58) 4.35 (2.34) 1.58 (1.51) 1.35 (1.39) 7.07 (1.85) 4 Girl 3788 1.93 (1.49) 3.64 (2.20) 1.34 (1.41) 1.42 (1.47) 7.66 (1.77) TEDS Parent 7 Boy 2740 1.89 (1.73) 3.94 (2.61) 1.05 (1.46) 2.02 (1.74) 7.93 (1.84) 7 Girl 2892 1.45 (1.47) 3.09 (2.35) 0.83 (1.23) 2.28 (1.82) 8.54 (1.55) TEDS Parent 9 Boy 1055 1.35 (1.43) 3.56 (2.45) 1.05 (1.56) 1.47 (1.67) 7.91 (1.85) 9 Girl 1245 1.08 (1.30) 2.68 (2.08) 0.91 (1.33) 1.82 (1.88) 8.67 (1.48) TEDS Self 9 Boy 1055 2.39 (1.89) 4.13 (2.72) 1.93 (1.74) 2.99 (2.28) 7.39 (1.95) 9 Girl 1245 1.92 (1.69) 3.43 (2.15) 1.76 (1.71) 3.38 (2.40) 8.38 (1.62) TEDS Parent 12 Boy 1828 1.42 (1.48) 3.33 (2.36) 1.18 (1.58) 1.67 (1.80) 8.25 (1.74) 12 Girl 2117 1.16 (1.33) 2.28 (1.99) 0.93 (1.35) 1.90 (1.94) 8.86 (1.50) TEDS Self 12 Boy 1828 2.09 (1.48) 3.85 (2.33) 1.47 (1.63) 1.94 (1.93) 6.98 (1.96) 12 Girls 2117 1.64 (1.50) 3.09 (2.16) 1.22 (1.48) 2.43 (2.10) 7.95 (1.69) CATSS Parent 15 Boys 2083 0.93 (1.21) 2.34 (2.23) 1.29 (1.66) 0.83 (1.34) 8.03 (1.85) 15 Girls 2199 0.99 (1.30) 1.72 (1.93) 1.21 (1.61) 1.43 (1.76) 8.49 (1.80) CATSS Self 15 Boys 2258 1.78 (1.52) 3.42 (2.19) 1.79 (1.55) 2.00 (1.80) 7.37 (1.88) 15 Girls 2806 1.73 (1.39) 3.42 (2.19) 1.79 (1.55) 2.00 (1.80) 7.37 (1.88) TEDS Parent 16 Boys 2134 1.26 (1.40) 2.58 (2.08) 7.92 (2.00) 16 Girls 2632 1.18 (1.35) 1.93 (1.80) 8.50 (1.83) TEDS Self 16 Boys 2134 1.78 (1.52) 3.60 (2.32) 1.58 (1.46) 1.95 (1.86) 6.52 (1.97) 16 Girls 2632 1.58 (1.44) 3.50 (2.28) 1.53 (1.46) 3.43 (3.32) 7.64 (1.77) software. Average scores and correlations were computed aggression based on maternal ratings of 7-year-old boys in by gender and age of children, separately for each rater and the Netherlands was 5.74 (SD 5.29), while mean level of country. Results were uploaded to a shared server. Given the aggression based on parental ratings of 8-year-old boys in large datasets included in these analyses, leading to signifi- Sweden was 5.49 (SD 5.42). cance even if differences between average scores or between We observed differences between raters in nearly every correlations being relatively small, we interpreted all results country in the same direction. Based on maternal ratings, relative to each other and took the 95% confidence intervals higher levels of psychopathology were seen than when based into account. With the multi-instrument, multi-rater and on paternal ratings. These differences were observed both multi-age assessments of aggression and of other emotional for boys and girls, at ages 3–12 for the CBCL and SDQ. The and behavioural problems, we established whether co-occur- exception was an absence of differences in maternal and rence was stronger or weaker given different measurement paternal ratings when using the Devereux Child Behaviour instruments, raters and ages. rating scale. With respect to our main question of the co-occurrence of aggression and other behavioural and emotional problems, Results findings are presented in Tables  6, 7, 8 and 9. Strong correla- tions were found between aggression and other externalising Tables 2, 3, 4 and 5 provide an overview of the sample sizes traits, especially rule-breaking behaviour. Correlations of and mean levels of aggression and all other traits. We rep- almost similar strength were also observed for aggression licated the well-established gender differences in average and attention problems and hyperactivity. However, cor- aggression scores at most ages for parental ratings. The relations were lower between aggression and internalising gender difference was smaller or close to absent for self- behaviours including withdrawn–depression and somatic reports. For example, while the difference between boys and complaints. Correlations between aggression and all other girls is in general about 1.5–2 points on the CBCL and SDQ emotional and behavioural problems and their 95% confi- parental reports, the differences based on self-report ranged dence intervals are also provided in an interactive applica- between 0.05 and 0.67. tion which can be found at http://www.actio n-eupro ject.eu/ Mean levels based on similar instruments across coun-Comor bidit yChil dAggr essio n. tries were almost identical. For example, the mean level of 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1111 Some more remarkable findings included the relatively low correlation between aggression and obsessive–compul- sive behaviour and the similarly relatively low correlation between aggression and social isolation and aggression and dependency. We, furthermore, observed a relatively low correlation between aggression and peer problems from the SDQ (ranging from 0.18 to 31). However, CBCL social problems showed stronger correlations with aggression (ranging from 0.34 to 0.66). The overarching picture that emerged suggests that corre- lations are largely stable across rater and age. If any change is observed, it is indicative of stronger correlations when children grow older. The correlations patterns of boys are markedly similar to the correlational patterns of girls. The only exception was the ATAC-based correlation between ODD/CD and OCD based on parental ratings at age 12. Correlations were stronger when based on the CBCL in comparison to the other measures, especially for parental ratings, while the ATAC, which is a clinical interview rather than a survey, provided somewhat lower correlations. The Devereux Child Behaviour (DCB) rating scale provides the interesting finding of similar strength in correlations between aggressive behaviour and attention problems and anxiety problems, but also with physical coordination problems. Discussion One of the aims of ACTION is to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychopathology. Here, we presented the correlations of aggression with other psychopatholo- gies in large European samples of children between ages 3 and 16 years old. We showed that aggression co-occurred with almost all other behavioural and social problems. More specifically, aggression co-occurred with oppositional and ADHD-related problems, and at later ages with rule-break- ing. In addition to the high correlations of aggression with externalising problems, we also observed substantial asso- ciations with anxiety–depression and other internalising symptoms. This co-occurrence of internalising and exter- nalising problems has previously been shown to persist over childhood and adolescence [29]. Both for externalising and internalising problems, the patterns of co-occurrence were largely gender and rater independent, and were similar even when aggression and the other psychopathologies were assessed by different instruments, such as the CBCL and the SDQ. Also, there were large similarities in co-occurrence patterns across countries in the Northern part of Europe. In ACTION, we compared co-occurrence patterns across different countries and cultures. These comparisons are somewhat hampered by the fact that in almost all cases 1 3 Table 5 Means and standard deviations for the scales of the Devereux Child Behaviour rating scale (DCB), Autism–Tics, ADHD and other Comorbidities inventory (A-TAC) and Multidimen- sional Peer Nomination Inventory (MPNI) DCB Rater Age Sex N Aggressive behaviour Attention problems Social isolation Anxiety problems Emotion liability Dependency Physical skill NTR Mother 5 Boy 7520 12.35 (3.77) 11.87 (3.57) 4.26 (1.45) 10.66 (3.29) 11.67 (3.50) 11.45 (3.05) 9.86 (3.13) 5 Girl 7695 11.68 (3.42) 11.32 (3.44) 4.36 (1.40) 10.99 (3.40) 11.19 (3.33) 10.73 (2.87) 8.45 (2.71) NTR Father 5 Boy 6808 12.65 (3.84) 12.02 (3.34) 4.40 (1.47) 10.84 (3.22) 11.78 (3.29) 11.70 (3.03) 10.26 (3.13) 5 Girl 6985 12.05 (3.55) 11.61 (3.26) 4.46 (1.43) 11.23 (3.30) 11.40 (3.22) 11.11 (2.85) 9.05 (2.88) A-TAC Rater Age Sex N CD ADHD Autism ODD CATSS Parent 9 Boy 5610 0.11 (0.39) 2.50 (3.42) 1.00 (1.83) 0.52 (0.91) 9 Girl 5516 0.08 (0.32) 1.65 (2.72) 0.63 (1.33) 0.41 (0.81) CATSS Parent 12 Boy 1649 0.11 (0.11) 2.39 (3.25) 0.99 (1.82) 0.49 (0.87) 12 Girl 1598 0.05 (0.24) 1.36 (2.34) 0.60 (1.24) 0.32 (0.66) MPNI Rater Age Sex N Aggression Inattention Hyperactive– Social anxiety Depression Prosocial impulsivity FT12 Parent 12 Boy 1188 0.63 (0.42) 0.82 (0.52) 0.82 (0.54) 0.79 (0.61) 0.75 (0.43) 1.93 (0.37) 12 Girl 1173 0.54 (0.39) 0.57 (0.45) 0.63 (0.47) 0.87 (0.61) 0.78 (0.43) 2.03 (0.37) 1112 European Child & Adolescent Psychiatry (2018) 27:1105–1121 more than one parameter varies between the different coun- tries and cultures. For example, both NTR, a Dutch sample, and TEDs, a UK sample, have parental ratings at age 9, but NTR used the CBCL while TEDS used the SDQ. Any dif- ferences in correlations may thus be attributable to cultural differences or country differences between the Netherlands and the UK, instrument differences or any other protocol or unobserved difference. However, given all these sources of difference in this large co-occurrence study, it is even more striking that most correlations are so similar. The large associations of aggression with other emotional and behavioural problems may form one of the obstacles for prevention and treatment of aggression. These findings indicate that an exclusive focus on aggression might not be the most feasible approach for the development of effective prevention and intervention programs. The complexity of psychopathology, partly due to the co-occurrence of behav- ioural and emotional problems, needs to be addressed and its aetiology explored through genetic, longitudinal and causal modelling: do the strong associations of aggression and other emotional and behavioural problems reflect a shared genetic vulnerability for multiple disorders, or do some dis- orders causally lead to other problems? The absence of rater differences in co-occurrence patterns does not imply that rater’s views are interchangeable. Pre- vious research suggested that, in general, mothers observe more behaviour problems in their children than fathers do [30]. We also see this pattern in the current paper, and con- sistently observe it across all counties. The differences in assessment between fathers and mothers in the levels of behavioural problems they observe may indicate that they both introduce their rater-specific view on the behaviour of the child [31], or that fathers and mothers interact with their offspring in different contexts. The similarities across raters and countries indicate that large-scale gene-finding efforts of aggressive behaviour and its co-occurring psychopathologies across multiple cohorts will be feasible/successful. Such an effort is currently in pro- gress within the ACTION consortium in collaboration with other cohorts and consortia that have collected measures of aggression in children as well as DNA samples for geno- typing [32]. The results of this international genome-wide association meta-analysis (GWAMA) are expected to yield insight into the genetic variants that influence aggression across childhood and offer possibilities for the construction of polygenic scores which may be used in prediction models [33, 34] and gene-environment modelling [35]. Besides a GWAMA approach, which includes samples from multiple age groups, genome-wide epigenetic profiling will be done to compare methylation in several statistically well-powered contrasts (such as genetically identical twin pairs discordant for aggression) in children. Monozygotic (MZ) twins pairs who are longitudinally discordant of aggression, also offer 1 3 Table 6 Phenotypic correlations between aggression and other empirical scales of the Child Behaviour Checklist (CBCL) 1.5-5 ASBA- Rater Age Sex N Attention problems Withdrawn Anxious– depressed Emotional reactivity Somatic complaints Sleep problems CBCL 1.5–5 Gen R Mother 3 Boys 2271 0.60 [0.57, 0.63] 0.43 [0.39, 0.47] 0.44 [0.40, 0.48] 0.67 [0.64, 0.70] 0.39 [0.35, 0.43] 0.38 [0.34, 0.42] 3 Girls 2246 0.59 [0.56, 0.62] 0.42 [0.38, 0.46] 0.46 [0.42, 0.50] 0.68 [0.65, 0.71] 0.38 [0.34, 0.42] 0.40 [0.36, 0.44] Gen R Father 3 Boys 1840 0.67 [0.64, 0.70] 0.45 [0.41, 0.49] 0.47 [0.43, 0.51] 0.69 [0.66, 0.72] 0.39 [0.35, 0.43] 0.41 [0.37, 0.45] 3 Girls 1897 0.59 [0.55, 0.63] 0.44 [0.40, 0.48] 0.50 [0.46, 0.54] 0.71 [0.68, 0.74] 0.39 [0.35, 0.43] 0.42 [0.38, 0.46] NTR Mother 3 Boys 9277 0.58 [0.56, 0.60] 0.45 [0.43, 0.47] 0.47 [0.45, 0.49] 0.64 [0.62, 0.66] 0.36 [0.34, 0.38] 0.35 [0.33, 0.37] 3 Girls 9360 0.55 [0.53, 0.57] 0.41 [0.39, 0.43] 0.48 [0.46, 0.50] 0.65 [0.63, 0.67] 0.37 [0.35, 0.39] 0.38 [0.36, 0.40] Gen R Mother 6 Boys 2887 0.59 [0.56, 0.62] 0.58 [0.55, 0.61] 0.55 [0.52, 0.58] 0.73 [0.71, 0.75] 0.40 [0.37, 0.43] 0.41 [0.38, 0.44] 6 Girls 2856 0.55 [0.52, 0.58] 0.50 [0.47, 0.53] 0.55 [0.52, 0.58] 0.75 [0.73, 0.77] 0.42 [0.39, 0.45] 0.41 [0.38, 0.44] European Child & Adolescent Psychiatry (2018) 27:1105–1121 1113 1 3 Table 7 Phenotypic correlations between aggression and other empirical scales of the achenbach system of empirically based assessment (ASEBA) 6–18 ASEBA Rater Age Sex N Attention problems Rule breaking Social problems Anxious– depressed Withdrawn –depressed Thought problems Somatic complaints 6–18 NTR Mother 7 Boys 5720 0.56 [0.54, 0.58] 0.69 [0.67, 0.71] 0.63 [0.61, 0.65] 0.48 [0.46, 0.50] 0.36 [0.34, 0.38] 0.47 [0.45, 0.49] 0.30 [0.28, 0.32] 7 Girls 5853 0.53 [0.51, 0.55] 0.66 [0.64, 0.68] 0.63 [0.61, 0.65] 0.47 [0.45, 0.49] 0.36 [0.34, 0.38] 0.47 [0.45, 0.49] 0.32 [0.30, 0.34] NTR Father 7 Boys 4134 0.58 [0.56, 0.60] 0.66 [0.64, 0.68] 0.59 [0.57, 0.61] 0.46 [0.43, 0.49] 0.34 [0.31, 0.37] 0.44 [0.41, 0.47] 0.29 [0.26, 0.32] 7 Girls 4182 0.55 [0.52, 0.58] 0.61 [0.59, 0.63] 0.63 [0.61, 0.65] 0.49 [0.46, 0.52] 0.40 [0.37, 0.43] 0.45 [0.42, 0.48] 0.32 [0.29, 0.35] TCHAD Parent 8 Boys 552 0.66 [0.60, 0.72] 0.72 [0.66, 0.78] 0.58 [0.51, 0.65] 0.55 [0.48, 0.62] 0.36 [0.28, 0.44] 0.38 [0.30, 0.46] 0.23 [0.15, 0.31] 8 Girls 534 0.56 [0.49, 0.63] 0.64 [0.57, 0.71] 0.58 [0.51, 0.65] 0.50 [0.43, 0.57] 0.41 [0.33, 0.49] 0.36 [0.28, 0.44] 0.29 [0.21, 0.37] NTR Mother 9 Boys 4543 0.54 [0.52, 0.56] 0.70 [0.68, 0.72] 0.63 [0.61, 0.65] 0.49 [0.46, 0.52] 0.38 [0.35, 0.41] 0.44 [0.41, 0.47] 0.27 [0.24, 0.30] 9 Girls 4689 0.54 [0.52, 0.56] 0.67 [0.65, 0.69] 0.66 [0.64, 0.68] 0.53 [0.51, 0.55] 0.43 [0.40, 0.46] 0.47 [0.44, 0.50] 0.31 [0.28, 0.34] NTR Father 9 Boys 3210 0.54 [0.51, 0.57] 0.70 [0.68, 0.72] 0.60 [0.57, 0.63] 0.49 [0.46, 0.52] 0.40 [0.37, 0.43] 0.48 [0.54, 0.51] 0.27 [0.24, 0.30] 9 Girls 3255 0.53 [0.50, 0.56] 0.63 [0.60, 0.66] 0.63 [0.60, 0.66] 0.52 [0.49, 0.55] 0.43 [0.40, 0.46] 0.44 [0.41, 0.47] 0.30 [0.27, 0.33] Gen R Mother 10 Boys 2250 0.57 [0.54, 0.60] 0.72 [0.69, 0.75] 0.64 [0.61, 0.67] 0.52 [0.48, 0.56] 0.43 [0.39, 0.47] 0.56 [0.53, 0.59] 0.31 [0.27, 0.35] 10 Girls 2310 0.53 [0.50, 0.56] 0.63 [0.60, 0.66] 0.64 [0.61, 0.67] 0.53 [0.50, 0.56] 0.42 [0.38, 0.46] 0.54 [0.51, 0.57] 0.33 [0.29, 0.37] Gen R Father 10 Boys 1624 0.60 [0.56, 0.64] 0.72 [0.69, 0.75] 0.64 [0.60, 0.68] 0.51 [0.47, 0.55] 0.47 [0.43, 0.51] 0.60 [0.56, 0.64] 0.28 [0.23, 0.33] 10 Girls 1670 0.52 [0.48, 0.56] 0.62 [0.58, 0.66] 0.60 [0.56, 0.64] 0.54 [0.50, 0.58] 0.42 [0.38, 0.46] 0.57 [0.53, 0.61] 0.27 [0.22, 0.32] NTR Mother 12 Boys 3870 0.56 [0.53, 0.59] 0.71 [0.69, 0.73] 0.60 [0.57, 0.63] 0.51 [0.48, 0.54] 0.42 [0.39, 0.45] 0.46 [0.43, 0.49] 0.28 [0.25, 0.31] 12 Girls 4010 0.54 [0.51, 0.57] 0.66 [0.64, 0.68] 0.62 [0.60, 0.64] 0.55 [0.52, 0.58] 0.43 [0.40, 0.46] 0.41 [0.38, 0.44] 0.33 [0.30, 0.36] NTR Father 12 Boys 2764 0.60 [0.57, 0.63] 0.73 [0.70, 0.76] 0.61 [0.58, 0.64] 0.49 [0.46, 0.52] 0.42 [0.39, 0.45] 0.48 [0.45, 0.51] 0.32 [0.28, 0.36] 12 Girls 2839 0.55 [0.52, 0.58] 0.64 [0.61, 0.67] 0.63 [0.60, 0.66] 0.51 [0.48, 0.54] 0.43 [0.40, 0.46] 0.39 [0.36, 0.42] 0.30 [0.26, 0.34] TCHAD Parent 13 Boys 535 0.59 [0.52, 0.66] 0.60 [0.53, 0.67] 0.46 [0.38, 0.54] 0.51 [0.44, 0.58] 0.31 [0.23, 0.39] 0.22 [0.14, 0.30] 0.28 [0.20, 0.36] 13 Girls 522 0.70 [0.64, 0.76] 0.68 [0.62, 0.74] 0.62 [0.55, 0.69] 0.67 [0.61, 0.73] 0.52 [0.45, 0.59] 0.39 [0.31, 0.47] 0.44 [0.36, 0.52] TCHAD Self 13 Boys 560 0.58 [0.51, 0.65] 0.58 [0.51, 0.65] 0.44 [0.37, 0.51] 0.46 [0.39, 0.53] 0.31 [0.23, 0.39] 0.31 [0.23, 0.39] 0.35 [0.27, 0.43] 13 Girls 551 0.54 [0.47, 0.61] 0.52 [0.45, 0.59] 0.34 [0.26, 0.42] 0.43 [0.35, 0.51] 0.21 [0.13, 0.29] 0.38 [0.30, 0.46] 0.35 [0.27, 0.43] TCHAD Parent 16 Boys 532 0.58 [0.51, 0.65] 0.62 [0.55, 0.69] 0.41 [0.33, 0.49] 0.47 [0.39, 0.55] 0.30 [0.22, 0.38] 0.28 [0.20, 0.36] 0.36 [0.28, 0.44] 16 Girls 507 0.67 [0.61, 0.73] 0.73 [0.67, 0.79] 0.43 [0.35, 0.51] 0.49 [0.41, 0.57] 0.43 [0.35, 0.51] 0.34 [0.26, 0.42] 0.34 [0.26, 0.42] TCHAD Self 16 Boys 583 0.56 [0.49, 0.63] 0.56 [0.49, 0.63] 0.40 [0.33, 0.47] 0.38 [0.30, 0.46] 0.24 [0.16, 0.32] 0.39 [0.32, 0.46] 0.29 [0.21, 0.37] 16 Girls 606 0.56 [0.49, 0.63] 0.52 [0.45, 0.59] 0.36 [0.29, 0.43] 0.34 [0.27, 0.41] 0.22 [0.14, 0.30] 0.35 [0.28, 0.42] 0.34 [0.27, 0.41] 1114 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Table 8 Phenotypic correlations between aggression and other scales of the Strengths and Difficulties Questionnaire (SDQ) SDQ Rater Age Sex N Hyperactivity Peer problems Emotion–anxiety Prosocial TEDS Parent 4 Boys 3581 0.43 [0.40, 0.46] 0.22 [0.19, 0.25] 0.24 [0.21, 0.27] − 0.29 [− 0.32, − 0.26] 4 Girls 3788 0.41 [0.38, 0.44] 0.21 [0.18, 0.24] 0.26 [0.23, 0.29] − 0.30 [− 0.33, − 0.27] TEDS Parent 7 Boys 2740 0.44 [0.41, 0.47] 0.26 [0.22, 0.30] 0.24 [0.20, 0.28] − 0.26 [− 0.30, − 0.22] 7 Girls 2892 0.40 [0.37, 0.43] 0.23 [0.19, 0.27] 0.26 [0.22, 0.30] − 0.26 [− 0.30, − 0.22] TEDS Parent 9 Boys 1055 0.44 [0.39, 0.49] 0.27 [0.21, 0.33] 0.33 [0.27, 0.39] − 0.25 [− 0.31, − 0.19] 9 Girls 1245 0.45 [0.40, 0.50] 0.31 [0.26, 0.36] 0.28 [0.23, 0.33] − 0.27 [− 0.32, − 0.22] TEDS Self 9 Boys 1055 0.45 [0.40, 0.50] 0.26 [0.20, 0.32] 0.34 [0.28, 0.40] − 0.27 [− 0.33, − 0.21] 9 Girls 1245 0.43 [0.38, 0.48] 0.29 [0.24, 0.34] 0.37 [0.32, 0.42] − 0.23 [− 0.28, − 0.18] TEDS Parent 12 Boys 1828 0.46 [0.42, 0.50] 0.28 [0.24, 0.32] 0.29 [0.25, 0.33] − 0.29 [− 0.33, − 0.25] 12 Girls 2117 0.44 [0.40, 0.48] 0.27 [0.23, 0.31] 0.29 [0.25, 0.33] − 0.34 [− 0.38, − 0.30] TEDS Self 12 Boys 1828 0.53 [0.49, 0.57] 0.27 [0.23, 0.31] 0.28 [0.24, 0.32] − 0.26 [− 0.30, − 0.22] 12 Girls 2117 0.50 [0.46, 0.54] 0.29 [0.25, 0.33] 0.36 [0.32, 0.40] − 0.24 [− 0.28, − 0.20] CATSS Parent 15 Boys 2083 0.52 [0.48, 0.56] 0.25 [0.21, 0.29] 0.29 [0.25, 0.33] − 0.36 [− 0.40, − 0.32] 15 Girls 2199 0.58 [0.48, 0.56] 0.28 [0.24, 0.32] 0.39 [0.35, 0.43] − 0.45 [− 0.49, − 0.41] CATSS Self 15 Boys 2258 0.43 [0.39, 0.47] 0.21 [0.17, 0.25] 0.24 [0.20, 0.28] − 0.24 [-0.28, − 0.20] 15 Girls 2806 0.44 [0.41, 0.47] 0.19 [0.15, 0.23] 0.29 [0.28, 0.29] − 0.31 [− 0.35, − 0.27] TEDS Parent 16 Boys 2134 0.54 [0.50, 0.58] − 0.38 [− 0.42, − 0.34] 16 Girls 2632 0.51 [0.48, 0.54] − 0.42 [− 0.45, − 0.39] TEDS Self 16 Boys 2134 0.45 [0.41, 0.49] 0.18 [0.14, 0.22] 0.26 [0.22, 0.30] − 0.22 [− 0.26, − 0.18] 16 Girls 2632 0.46 [0.43, 0.49] 0.25 [0.21, 0.29] 0.27 [0.23, 0.31] − 0.25 [− 0.29, − 0.21] a unique possibility to gain an understanding of the environ- sequential effects of the comorbid disorders. If one disor - mental risk factors associated with complex behaviour such der also is found to precede another disorder, treatment can as aggression [36]. be adjusted and specified. To be able to initiate such treat- Genetic and epigenetic effects do not act in isolation, ment specificity, we need to conduct cross-lag longitudinal so the results of these studies will need to be investigated analyses to examine whether aggression is driving the other in (epi)gene x environmental interplay models to under- psychopathologies, or if aggression is a result or outing of stand the differences between children in aggression. Twin other problems. If one set of symptoms drives the rest, then data may offer a first insight into the importance of gene- intervention should focus on early detection and prevention. environment dependencies. Analyses of behavioural prob- We conclude that childhood aggression co-occurs with lems in 5-year-old twins showed strong evidence for larger nearly all other behavioural, emotional and social problems, environmental influences in children who were genetically from both externalising and internalising domains, regard- more at risk for problem behaviour [37]. The available large- less of rater, gender, measurement instrument or country. scale phenotypic, environmental and genotypic databases These findings indicate that aggression during childhood and in ACTION will allow the development and application adolescence rarely occur in isolation, and that other behav- of these methods for gene-environment interaction and ioural and emotional problems are common in children with correlation. aggressive problems. Although it is known that co-occurrence is a risk fac- tor for persisting symptoms (e.g. [38]), the implications for treatment are under-investigated. The current paper under- Future progress lines that co-occurrence of behavioural and emotional prob- lems with childhood aggression is highly prevalent. Instead The finding that aggression co-occurs with nearly all other of excluding children with multiple problems, specific trials behavioural, emotional and social problems during child- should be undertaken to investigate the effectiveness of treat- hood puts aggression in the centre of scientific attention. ment and improve treatment for this group that requires our If and when causes of differences in aggression during utmost attention. Of course, the question then arises what childhood are better understood, this information may aid would be more effective, e.g. treatment targeting all psycho- in the development of prevention and intervention strate- pathologies at the same time or treatment at symptom level. gies. To this end, we designed the EU-ACTION project It is essential to gain knowledge about the etiological and (see Fig. 1). The main objective of ACTION is to improve 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1115 1 3 Table 9 Phenotypic correlations between aggression and other scales of the Devereux Child Behaviour rating scale (DCB), Autism–Tics, ADHD and other Comorbidities inventory (A-TAC) and multidimensional peer nomination inventory (MPNI) DCB Rater Age Sex N Attention problems Social isolation Anxiety problems Emotional lability Dependency Physical coordi- nation problems NTR Mother 5 Boys 7520 0.37 [0.35, 0.39] 0.14 [0.12, 0.16] 0.35 [0.33, 0.37] 0.52 [0.50, 0.54] 0.05 [0.03, 0.07] 0.30 [0.28, 0.32] 5 Girls 7695 0.36 [0.34, 0.38] 0.07 [0.05, 0.09] 0.34 [0.32, 0.36] 0.52 [0.50, 0.54] 0.03 [0.01, 0.05] 0.29 [0.27, 0.31] NTR Father 5 Boys 6808 0.36 [0.34, 0.38] 0.15 [0.13, 0.17] 0.36 [0.34, 0.38] 0.50 [0.48, 0.52] 0.05 [0.03, 0.07] 0.33 [0.31, 0.35] 5 Girls 6985 0.37 [0.35, 0.39] 0.09 [0.07, 0.11] 0.39 [0.37, 0.41] 0.53 [0.51, 0.55] 0.06 [0.04, 0.08] 0.32 [0.30, 0.34] A-TAC Rater Age Boys girls N ADHD ODD Autism OCD CATSS Parent 9 Boys 5610 0.46 [0.44, 0.48] 0.51 [0.49, 0.43] 0.46 [0.44, 0.48] 0.19 [0.16, 0.22] 9 Girls 5516 0.45 [0.43, 0.47] 0.49 [0.47, 0.51] 0.44 [0.42, 0.46] 0.17 [0.14, 0.20] CATS Parent 12 Boys 1649 0.38 [0.34, 0.42] 0.47 [0.43, 0.51] 0.38 [0.34, 0.42] 0.16 [0.11, 0.21] 12 Girls 1598 0.37 [0.32, 0.42] 0.41 [0.37, 0.45] 0.32 [0.27, 0.37] 0.05 [0.00, 0.10] MPNI Rater Age Sex N Inattention Hyperactive– Social anxiety Depression Prosocial impulsivity FT12 Parent 12 Boys 1188 0.38 [0.33, 0.43] 0.52 [0.47, 0.57] 0.14 [0.08, 0.20] 0.27 [0.22, 0.32] − 0.34 [− 0.39, − 0.29] 12 Girls 1173 0.41 [0.36, 0.46] 0.50 [0.45, 0.55] 0.14 [0.08, 0.20] 0.29 [0.24, 0.34] − 0.30 [− 0.35, − 0.25] 1116 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Fig. 1 Work plan strategy of ACTION the understanding of the causes of individual differences in gender differences in the magnitude of genetic effects. In aggression among children to better inform the development boys, shared environment explained around 20% of the vari- of prevention and treatment strategies. ation in aggression across all ages, while in girls its influ- ACTION has described current clinical practices in ence was absent around age 7 and only came into play at Europe with respect to childhood aggression and identified later ages. Longitudinal genetic correlations explained most drawbacks in prevention and intervention of clinical aggres- of the stability of aggressive behaviour. These results are sion (also known as paediatric conduct disorders). An online encouraging for gene-finding studies. In earlier work, the semi-structured questionnaire investigating the status of first molecular genetic evidence for aggression in child- national guidelines (N = 29 academic experts; 23 countries) hood was reported [40]. Using genomic relationship matrix and an online semi-structured questionnaire exploring clini- restricted maximum likelihood (GREML) analyses signifi- cal practices (N = 94 clinicians; 22 countries) on diagnos- cant influences of common SNPs were estimated for exter - ing and treating children with severe behavioural problems nalising problems (SNP h = 0.44), for attention problems 2 2 across Europe were developed. Several countries have offi- (SNP h = 0.37–0.71) and total problems (SNP h = 0.18). cial clinical guidelines, while others have at least some unof- A previous attempt to discover genomic locations of interest ficial documents. In general, primary and secondary pre- for childhood and adolescent aggression (N = 18,988) iden- ventions were absent or poorly developed, whereas specific tified one region in chromosome 2 (2p12) at near genome- − 8 interventions for severe behavioural problems were very wide significance (top SNP rs11126630, P = 5.30 × 10 ). diverse across Europe. Improving parent–child interactions, The gene-based analysis indicated association with vari- parent/teacher interventions and collaborative approaches ation within AVPR1A with aggressive behaviour. It was were most frequently identified as successful treatment concluded that common variants at 2p12 show suggestive elements. Several needs were listed by experts and clini- evidence for association with childhood aggression [41]. To cians, which will fuel further research within ACTION and replicate this finding and to initiate new findings we will use beyond. The current findings on co-occurrence of aggression newly developed multivariate genome-wide meta-analysis indicates that information on these current drawbacks could methodology, in which the power of sample overlap (e.g. also be informative for other psychopathologies. due to having a paternal and maternal rating of the same A challenge in combining large cohort studies carried child at the same age) is leveraged instead of omitted [42]. In out in different countries is the assessment of aggression. line with the results, we include ADHD and ADHD-related Within different countries and cohorts, different instruments problems, as well aggressive behaviour in this collaborative are used. In a subsample of the Netherlands Twin Register, project. With this approach, we will be able to identify not we have invited a group of parents of 9-year-old twins to only genomic regions of interest for aggression or ADHD, complete multiple assessment instruments to have a ‘refer- but also genomic regions that play a role in the co-occur- ence set’ or ‘backbone’ for phenotype imputation. rence of these psychopathologies. The first results with respect to genetic and environmental In addition to existing genotype datasets, new DNA sam- contributions to the variation and longitudinal stability in ples are collected for epigenetic research in clinical cases childhood aggressive behaviour [39] indicated high stability (children that are referred to child psychiatric clinics in the and heritability of aggressive behavioural problems. Herit- Netherlands) and in identical twins concordant and discord- ability was on average around 60–80% without any large ant for aggression. While DNA collection and epigenetic 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1117 profiling in these children is in progress, we gained ini- human aggressive behaviour is heterogeneous and that most tial insight into the association between aggression and effective therapeutic agents only work on the serotonergic DNA methylation patterns by analysing available data on system a comprehensive study of the role of the amino acid aggression available for adults [43]. DNA methylation was neurotransmitters (including both their precursors and deg- measured in whole blood by the Illumina HM450k array radation metabolites) and peptide-based neurotransmitters is in more than 2000 adults for whom Adult Self-Report [44] warranted. In addition to this biomarker approach, ACTION data on aggression were available. No genome-wide sig- will include a metabolomics approach and the platforms we nificant methylation hits were identified, but gene-ontology are measuring include amines, organic acids and steroids. (GO) analysis, in which categories of genes rather than Results from ACTION will be integrated into an empir- single methylation sites were tested, highlighted that genes ical-based framework of aggression. The sample sizes of involved in developmental and central nervous system pro- ACTION will allow us to examine the interplay between cesses are enriched among the higher-ranking genes from risk factors and test hypotheses to identify modifiable risk the epigenome-wide meta-analysis (EWAS). This study factors for childhood aggression. Thereby, our findings may is now followed by a meta-analysis EWAS (EWAMA) in inform prevention and treatment strategies, and assist in children and adults across multiple cohorts. This EWAMA individual risk profiles based on combination of modifiable includes multiple cohorts with a sample size of over 10.000. and non-modifiable risk indicators. Translation of results In addition to genetic and environmental factors acting will be supported by several internet applications and dis- additively to the development of childhood aggression, seminating the results via the ACTION website (http://www. genes and environment may interact. Such interactions can actio n-eupro ject.eu/). be thought of as genes controlling sensitivity to the environ- Acknowledgements The ACTION consortium is supported by funding ment, or as the environment controlling the expression of from the European Union Seventh Framework Program (FP7/2007– genes. Genes and environment may also be correlated when 2013) under Grant agreement no. 602768. Data collection in the NTR genes alter the exposure to relevant environmental risk fac- was supported by NWO: Twin-family database for behavior genet- ics and genomics studies (480-04-004); “Spinozapremie” (NWO/SPI tors. We know that for traits such as aggression children are 56-464-14192; “Genetic and Family influences on Adolescent psy - not randomly distributed over environments and describing chopathology and Wellness” (NWO 463-06-001); “A twin-sib study environmental effects as “causal” may lead to wrong con- of adolescent wellness” (NWO-VENI 451-04-034); ZonMW “Genetic clusions/interventions. Several mechanisms can be at play influences on stability and change in psychopathology from child- hood to young adulthood” (912-10-020); “Netherlands Twin Registry to explain the non-random distribution of genotypes over Repository” (480-15-001/674) and KNAW Academy Professor Award environments [45]: children who inherit genes that make (PAH/6635) to DIB. We warmly thank all participating twin families. them susceptible to exhibiting aggression are likely to grow Data collection in Finntwin12 has been supported by ENGAGE— up in aggressive homes (passive rGE), their genotypes may European Network for Genetic and Genomic Epidemiology, FP7- HEALTH-F4-2007, grant agreement number 201413, National Institute trigger aggression in others (reactive rGE) and they may of Alcohol Abuse and Alcoholism (Grants AA-12502, AA-00145 and seek out aggressive peer groups (active rGE). The analyses AA-09203 to RJ Rose), the Academy of Finland Center of Excellence of rGE thus are closely related to issues of gene-environment Program (Grants 213506, 129680 to JK) and the Academy of Finland independence and to questions of causality. The analyses (Grants 100499, 205585, 118555, 141054, 265240, 263278 and 264146 to JK). The Child and Adolescent Twin Study (CATSS) in Sweden of GxE interaction will employ several approaches that can study was supported by the Swedish Council for Working Life, funds make use of the large existing datasets. The first approach under the ALF agreement, the Söderström-Königska Foundation and focuses on the estimation of the total contribution of genes the Swedish Research Council (Medicine and SIMSAM). The Swed- when environmental exposures have been measured. In this ish Twin study of Child and Adolescent Development (TCHAD) was supported by the Swedish Council for Working Life and the Swedish approach genotypes and other, non-measured, influences Research Council (Medicine and SIMSAM). Twins Early Development are modelled as latent factors. Because of the presence of Study (TEDS) is supported by a program grant from the UK Medi- genome-wide marker data, a second approach is to estimate cal Research Council (MR/M021475/1). The Generation R Study is GxE interaction in a design with measured genotypes and made possible by financial support from: Erasmus Medical Center, Rotterdam and the Netherlands Organization for Health Research and environmental exposures (note that because of the twin Development (ZonMw). H. Tiemeier is supported by grants of the design the remaining variance can still be attributed to latent Dutch Ministry of Education, Culture and Science (Gravity Grant No. G and E). The causal relation of environmental exposure 024.001.003, Consortium on Individual Development) and a NWO- and later outcome may be complex, but longitudinal twin VICI grant (NWO-ZonMW: 016.VICI.170.200). data offer excellent opportunities to test models of causal- ity versus other models of association between genes and Compliance with ethical standards environment [46, 47]. A final piece of the puzzle is sought in the assessment Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest. if biomarker and metabolomics profiles in clinical cases and MZ twins discordant for aggression. Given the fact that 1 3 1118 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Open Access This article is distributed under the terms of the Crea- The Swedish Twin Register (STR) was established in tive Commons Attribution 4.0 International License (http://creat iveco 1961 and includes all 200,000 + twins born in Sweden since mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- 1886. In the Swedish Twin study of Child and Adolescent tion, and reproduction in any medium, provided you give appropriate Development (TCHAD), we have followed 1,500 twin pairs credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. from age 8 to age 20 with 4 waves of questionnaires to both parents and twins (1994, 1999, 2002, 2006) and we just com- pleted a follow-up (November 2013) at age 26. Information on behavioural and emotional problems throughout child- Appendix 1 hood is obtained by assessment with the Child Behaviour Checklist (CBCL), Teacher Report Form (TRF) and Youth Participating cohorts Self-Report (YRF), together with more in-depth assess- ments of for example aggression (Youth Psychopathic traits The Netherlands Twin Register (NTR) was established in Inventory, YPI; aggressive behaviour in youth). In the ongo- 1987 and collects data in twins and multiples from birth ing Child and Adolescent Twin Study in Sweden (CATSS) onwards. Nationwide data collection is by mailed surveys study, initiated in 2004, we conduct a psychiatric telephone to the parents of twins until age 12, and to twins after age interview with parents of all 1,400 twin pairs born in Swe- 14. At age 14, siblings of twins are also invited to take part den annually in connection with their 9th birthdays. By May and at age 18 twins and their siblings and parent are invited 2016, we have performed 28,168 interviews with a very high to complete a series of self-report questionnaires. Parents of response rate (more than 76%), and we have collected DNA twins receive questionnaires when their twins are aged 1, 2, from the twins (current N ≈ 14,500 individuals). We follow 3, 5, 7, 10 and 12 years of age. After 25 years of research, these families with questionnaires to parents and twins at large datasets have been obtained. Information on behav- age 15 (CATSS-15; current N = 11,148) and 18 (CATSS- ioural and emotional problems throughout childhood is 18; current N = 7143 twins). Information on behavioural and obtained by assessment with the Child Behaviour Check- emotional problems at age 9 is gathered through a telephone list (CBCL), Teacher Report Form (TRF), Devereux Child interview with parents using the A-TAC instrument which Behaviour (DCB) rating scale and Youth Self-Report (YSR). among others include ODD/CD modules. Aggression and This longitudinal data collection strategy has the advantage criminality are measured through questionnaires to both that multiple informant assessment can be easily combined, parents and twins at age 15 and 18. due to overlapping items by gender, informant and age. For The FinnTwin12 study was started in September 1994 each age group, items can be summed to form longitudi- to examine genetic and environmental determinants of nal syndrome scales and a total problem score. When twins precursors to health-related behaviours, with a particular reach age 18, they and their parents and siblings are invited focus on the use and abuse of alcohol, in initially 11- to to take part in the data collection as adult twin families. 12-year-old twins. This research is cast within the perspec- They receive an extensive survey, that includes the Adult tive of developmental genetic epidemiology, asking whether Self-Report (ASR). precursors of risk behaviours are evident to parents, teach- The Twins Early Development Study (TEDS) was ers and classroom peers as early as age 12. Information on established in 1995 with three birth cohorts (1994–1996) behavioural and emotional problems throughout childhood obtained from UK birth records. In infancy and early child- is obtained from in-person psychiatric interviews using the hood, questionnaires were posted to parents and teachers Semi-Structured Assessment for the Genetics of Alcohol- (with permission from parents), and school achievement ism (SSAGA) and by questionnaire assessment with the records were also obtained. Data were also obtained from Multidimensional Peer Nomination Inventory (MPNI). The telephone interviews and increasingly from online internet MPNI was designed by Finnish psychologist Dr Lea Pulk- assessment. The measure used consistently at all ages and kinen, arising from work started in 1968, and evolved into from all sources (including the twins themselves beginning the 37 item questionnaire used in the first three waves of at age 10) is the Strength and Difficulties Questionnaire assessment. The MPNI gathers information on three major (SDQ). The SDQ is particularly useful for combining infor- dimensions: Behavioural Problems (aggression [both direct mation across informants and across ages. At various ages, and indirect], hyperactivity–impulsivity and inattention), we have assessed using a battery of measures other aggres- Emotional Problems (depression, social anxiety and vic- sion-relevant domains, most notably psychopathic symptoms timisation) and Adjustment (constructiveness, compliance, and attention-deficit/hyperactivity disorder symptoms. We helping behaviour and social activity). The study has a two- are currently collecting only minimal information at age 18 stage sampling design. The larger, first-stage study is an and plan a major follow-up at age 21, which will serve our epidemiological investigation of five consecutive and com- ACTION collaboration. plete birth cohorts (1983–1987) of Finnish twins, including 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1119 questionnaire assessments of both twins and parents at References baseline, starting with a family questionnaire (returned by 1. Foster EM, Jones DE (2005) The high costs of aggression: public 2,724 families, 87% participation rate) that was mailed late expenditures resulting from conduct disorder. Am J Public Health in the year before the twins reached age 12, with follow-up 95:1767–1772. https ://doi.org/10.2105/AJPH.2004.06142 4 of all twins at age 14 and 17½, as well as a later collection 2. 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Front Genet 3:4. https :// abstractsdoi.org/10.3389/fgene .2012.00004 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1121 Affiliations 1,2,3 1,2 4 5 6 7 Meike Bartels  · Anne Hendriks  · Matteo Mauri  · Eva Krapohl  · Alyce Whipp  · Koen Bolhuis  · 8 9 1,2 1,2 10 Lucia Colodro Conde  · Justin Luningham  · Hill Fung Ip  · Fiona Hagenbeek  · Peter Roetman  · 10 10 1,2 1,2 11 1,3,12 Raluca Gatej  · Audri Lamers  · Michel Nivard  · Jenny van Dongen  · Yi Lu  · Christel Middeldorp  · 1,2 10,13 14 15 8 Toos van Beijsterveldt  · Robert Vermeiren  · Thomas Hankemeijer  · Cees Kluft  · Sarah Medland  · 16,17 18 19 6,20 6,20,21 Sebastian Lundström  · Richard Rose  · Lea Pulkkinen  · Eero Vuoksimaa  · Tellervo Korhonen  · 22 9 1,23 4 7,24,25 Nicholas G. Martin  · Gitta Lubke  · Catrin Finkenauer  · Vassilios Fanos  · Henning Tiemeier  · 11 5 6,20 1,2,3 Paul Lichtenstein  · Robert Plomin  · Jaakko Kaprio  · Dorret I. Boomsma * Meike Bartels VU Medical Centre, Amsterdam, The Netherlands m.bartels@vu.nl Division of Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands Twin Register, Department of Biological The Netherlands Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands Good Biomarker Sciences, Leiden, The Netherlands 2 16 Amsterdam Public Health Research Institute, Faculty Gillberg Neuropsychiatry Centre, University of Gothenburg, of Behavioural and Movement Sciences, Vrije Universiteit Gothenburg, Sweden Amsterdam, Amsterdam, The Netherlands Centre for Ethics, Law and Mental Health (CELAM), Amsterdam Neuroscience, Amsterdam, The Netherlands University of Gothenburg, Gothenburg, Sweden 4 18 University of Cagliari, Cagliari, Italy Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA Medical Research Council Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Department of Psychology, University of Jyvaskyla, Psychology, and Neuroscience, King’s College London, Jyvaskyla, Finland London, UK Department of Public Health, University of Helsinki, Institute for Molecular Medicine Finland, University Helsinki, Finland of Helsinki, Helsinki, Finland Institute of Public Health and Clinical Nutrition, University Department of Epidemiology, Erasmus Medical Center, of Eastern Finland, Kuopio, Finland Rotterdam, The Netherlands QIMR Berghofer Medical Research Institute, Brisbane, QLD, Psychiatric Genetics Laboratory, QIMR Berghofer Medical Australia Research Institute, Brisbane, Australia Youth Studies, Interdisciplinary Center, Utrecht University, Department of Psychology, University of Notre Dame, Utrecht, The Netherlands Notre Dame, USA Department of Child and Adolescent Psychiatry, Erasmus Curium-LUMC, Academic Centre of Child and Youth Medical Center, Rotterdam, The Netherlands Psychiatry, Leiden University Medical Center, Leiden, Department of Psychiatry, Erasmus Medical Center, The Netherlands Rotterdam, The Netherlands Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden University of Queensland, Brisbane, Australia 1 3 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Child & Adolescent Psychiatry Springer Journals

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Medicine & Public Health; Psychiatry
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Abstract

Childhood aggression and its resulting consequences inflict a huge burden on affected children, their relatives, teachers, peers and society as a whole. Aggression during childhood rarely occurs in isolation and is correlated with other symptoms of childhood psychopathology. In this paper, we aim to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychopathology. We focus on the co-occurrence of aggression and other childhood behavioural and emotional problems, including other externalising problems, attention problems and anxiety–depression. The data were brought together within the EU-ACTION (Aggression in Children: unravelling gene-environment interplay to inform Treatment and InterventiON strategies) project. We analysed the co-occurrence of aggression and other childhood behavioural and emotional problems as a function of the child’s age (ages 3 through 16 years), gender, the person rating the behaviour (father, mother or self) and assessment instrument. The data came from six large population-based European cohort studies from the Netherlands (2x), the UK, Finland and Sweden (2x). Multiple assessment instruments, including the Child Behaviour Checklist (CBCL), the Strengths and Difficulties Questionnaire (SDQ) and Multidimensional Peer Nomi- nation Inventory (MPNI), were used. There was a good representation of boys and girls in each age category, with data for 30,523 3- to 4-year-olds (49.5% boys), 20,958 5- to 6-year-olds (49.6% boys), 18,291 7- to 8-year-olds (49.0% boys), 27,218 9- to 10-year-olds (49.4% boys), 18,543 12- to 13-year-olds (48.9% boys) and 10,088 15- to 16-year-olds (46.6% boys). We replicated the well-established gender differences in average aggression scores at most ages for parental ratings. The gender differences decreased with age and were not present for self-reports. Aggression co-occurred with the majority of other behavioural and social problems, from both externalising and internalising domains. At each age, the co-occurrence was particularly prevalent for aggression and oppositional and ADHD-related problems, with correlations of around 0.5 in general. Aggression also showed substantial associations with anxiety–depression and other internalizing symptoms (correlations around 0.4). Co-occurrence for self-reported problems was somewhat higher than for parental reports, but we found neither rater differences, nor differences across assessment instruments in co-occurrence patterns. There were large similarities in co-occurrence patterns across the different European countries. Finally, co-occurrence was generally stable across age and sex, and if any change was observed, it indicated stronger correlations when children grew older. We present an online tool to visualise these associations as a function of rater, gender, instrument and cohort. In addition, we present a description of the full EU-ACTION projects, its first results and the future perspectives. This article is part of the focused issue ‘Conduct Disorder and Aggressive Behaviour in Children and Adolescents’. Extended author information available on the last page of the article Vol.:(0123456789) 1 3 1106 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Keywords Aggression · Childhood · Comorbidity · Co-occurence · Behavioural and emotional problems of differences in aggression between children by unravelling Introduction its genetic architecture using univariate, multivariate and longitudinal genetic and epigenetic modelling in twin and Prevention strategies and behavioural and pharmacological genetic and epigenetic association studies. A strong focus interventions for aggressive behaviour and conduct disor- of ACTION includes biomarker and metabolomics research der are effective in some children, although a substantial [21]. number of children do not respond to prevention strate- In the current study, the aim is to describe and improve gies, do not benefit from interventions or may even expe- the understanding of the co-occurrence of aggression with rience an escalation of symptom [9, 10]. One reason for other forms of childhood psychopathology by analysing this might be the heterogeneity of aggression. A second data from the large ACTION phenotype databases in large reason, which is related to the heterogeneous nature and samples of children. We analysed data on aggression and occurrence of childhood aggressive problems, might be that common emotional and behavioural problems in children children with aggressive problems often have co-occurring aged 3–16 years. Multiple raters, i.e. fathers and mothers problems. Due to a multitude of problems, children may during childhood and also youngsters themselves during not respond to prevention or intervention targeting aggres- adolescence, provided information on different aggression sion, or the co-occurring problems may mask aggression, measures. The two Dutch cohorts (The Netherlands Twin leaving it untreated. In 12 year olds, Bartels and colleagues Register and Generation R) used the Achenbach System [11] observed that at least half of the children who were of Empirically Based Assessment (ASEBA [22]), which deviant on aggressive behaviour (T score ≥ 67) also were included the Child Behaviour Checklist (CBCL) and the deviant on rule-breaking behaviour, i.e. at least 50% of the Youth Self-Report (YSR). The UK-based Twins Early children with clinical levels of aggression also showed a Development Study employed the Strengths and Difficulties co-occurrence of clinically relevant rule-breaking behaviour. Questionnaire (SDQ [23]). The Swedish Twin study of Child Strong links between aggression and attention-deficit/hyper - and Adolescent Development used the Autism–Tics, ADHD activity disorder (ADHD) [12] are often seen in the clinical and other Comorbidities inventory (A-TAC [24]), and the presentation of ADHD [13], and it has been suggested that Swedish Child and Adolescent Twin Study the ASEBA the strong association between ADHD and aggression may questionnaires. In Finland, the Multidimensional Peer Nom- explain gender differences in clinical referral. For example, ination Inventory (MPNI) was employed. For several age teachers rated boys with a DSM-based ADHD diagnosis as groups from different countries, aggression assessed with having higher levels of attention problems and aggression identical instruments was available. For example, parental than girls with a similar ADHD diagnosis [14]. Aggression ratings with the CBCL were available for 7- to 8-year-olds not only co-occurs with psychopathologies on the exter- and 12- to 13-year-olds in the Netherlands (NTR) and Swe- nalizing spectrum. Aggression also tends to co-occur with den (TCHAD). In addition to indicators of aggression, all anxiety, and it has been proposed that anxiety needs to be instruments provided quantitative scores on other childhood given a central role in the treatment of aggression [15]. In psychopathologies from the externalising and internalising more extreme cases, aggression was not found to co-occur spectrum. We investigated patterns of co-occurrence across solely with ADHD symptoms, such as attention problems, or age, rater, instrument and gender. anxiety but rather with both of these forms of psychopathol- ogy. This pattern of behavioural problems is referred to as the dysregulation profile [16–18], and has been described as Methods a potential marker for severe childhood psychopathologies [19, 20]. Participants To gain insight into the aetiology of individual differences in childhood aggression and in co-occurring behavioural and Six large population-based cohorts (NTR and GenR from emotional problems, ACTION (Aggression in Children: the Netherlands, TEDS from the UK, CATSS and TCHAD unravelling gene-environment interplay to inform Treatment from Sweden and FinnTwin12 from Finland) analysed the and InterventiON strategies; http://www.actio n-eupro ject. co-occurrence of aggression measures with other psycho- eu/) created a consortium with access to large childhood pathologies. For a link to cohort-specific websites, see prospective twin, population-based and clinical cohorts. Table 1 and for a detailed description of the cohorts, please ACTION brings together multiple large cohort studies in also see Appendix I. The twin cohorts were requested to genetically informative populations (see Table 1 and Appen- randomly select one of the twins per pair, with an equal dix 1). The focus of ACTION is to inform on the aetiology 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1107 representation of first- and second-born children, to obtain parameter estimates that were not biased due to effects of family clustering. In our previous work [25], we have shown that children with an illness or disability that interfered with daily function tend to display more than twice as much problem behaviour across the entire age range compared to other twins, so they were excluded. Age-, gender- and rater- specific sample sizes are presented in Tables  2, 3, 4 and 5. Data were available for 30,523 3- to 4-year-olds (49.5% boys), 20,958 5- to 6-year-olds (49.6% boys), 18,291 7- to 8-year-olds 49% boys), 27,218 9- to 10-year-olds (49.4% boys), 18,543 11- to 12-year-olds (48.9% boys) and 10,088 15- to 16-year- olds (46.6% boys). Due to the longitudinal structure of most cohorts, these data points are not statisti- cally independent observations, since overlapping groups of children were assessed at multiple ages. All data used in the current analyses were collected under protocols that have been approved by the appropriate ethics committees, and studies were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Measures The Child Behaviour Checklist (CBCL) 1,5–5 [26] and 6–18 [22] were used by GenR (age 6 and 10), TCHAD (ages 8, 13 and 16) and NTR (ages 3, 7, 9 and 12). The Youth Self- Report (YSR) [22] was used by TCHAD (ages 13 and 16). The CBCL and YSR are part of the Achenbach System of Empirical-Based Assessment and designed to measure childhood and adolescent behavioural and emotional prob- lems. The response format was on a three-point scale (with response options ‘not true’, ‘somewhat true or sometimes true’ and ‘very or often true’). With the CBCL 1,5–5 seven syndrome scales are obtained (emotionally reactive, anx- ious–depressed, somatic complaints, withdrawn, overactive behaviour, aggressive behaviour, sleep problems), while with the CBCL 6–18 eight syndrome scales are obtained (anxious–depressed, withdrawn, somatic complaints, social problems, thought problems, attention problems, rule-break- ing behaviour, aggressive behaviour). With the YSR, eight syndrome scales are obtained (anxious–depressed, somatic complaints, withdrawn–depressed, social problems, thought problems, attention problems, rule-breaking behaviour and aggressive behaviour). The Strengths and Difficulties Questionnaire (SDQ) [ 23] was used by TEDs (ages 4, 7, 9, 16) and CATSS (age 15). The SDQ is a 25-item questionnaire designed to measure common mental health problems during childhood and ado- lescence. Ratings were on a three-point scale (with response options ‘not true’, ‘somewhat true’ and ‘certainly true’). The 25 items form 5 scales, emotional symptoms, conduct prob- lems, hyperactivity/inattention, peer relationship problem 1 3 Table 1 Sample sizes for different age groups of the ACTION cohort Register Age Webpages 1–2 3–4 5–6 7–8 9–10 11–12 13–14 15–16 17–18 19–20 21–22 NTR 106.7 37.9 31.2 23.2 18.1 15.1 8.0 5.7 1.7 6.0http://www.Tweel ingen regis ter.org Qtwin 2.4 1.4 1.8 0.9http://www.qimrb ergho fer.edu.au/qtwin / TEDS 12.6 28.4 29.2 6.8 11.8 6.7 10.2 http://www.Teds.ac.uk TCHAD 2.0 2.0 2.0 2.0http://ki.se/en/meb/twin-study -of-child -and-adole scent -devel opmen t-tchad CATSS 22.3 6.5 11.1 8.7http://ki.se/en/meb/the-child -and-adole scent -twin-study -in-swede n-catss FT12 5.3 4.7 4.2 1.3https ://wiki.helsi nki.fi/displ ay/twine ng/Twins tudy GenR 4.5 5.2 7.8 5.0http://www.gener ation r.nl Indiv (x 1000) 123.8 71.5 39 54.4 40.4 45 22.8 24.7 8.1 8 2.2 1108 European Child & Adolescent Psychiatry (2018) 27:1105–1121 and prosocial behaviour. The conduct problem scale was used as a proxy for aggressive behaviour. NTR used the short Devereux Child Behaviour (DCB) rating scale for 5 year olds. The DCB consists of questions about problem behaviour in children rated by the parents [27]. The short version includes 42 items that measure seven different aspects of problem behaviour in children. Parents were asked to indicate on a five-point scale whether the statements were applicable (0 = never, 1 = rarely, 2 = occa- sionally, 3 = frequently, 4 = very frequently). The items of the questionnaire cover the following aspects of problem behaviour: emotional liability (five items, e.g. “markedly impatient”), social isolation (three items, e.g. “quite timid or shy”), aggressive behaviour (seven items, e.g. “hits, bites and scratches other children”), attention problems (five items, e.g. “jumps from one activity to another”), depend- ency (five items, e.g. “does not want to do things for him- self”), anxiety problems (six items, e.g. “concern about his physical health”) and physical coordination (five items, e.g. “gets dirty and untidy”). In 9- and 12-year-old in the CATSS sample from Sweden, information on ODD/CD and other psychopathologies was gathered through a telephone interview with parents, using The Autism–Tics, ADHD and other Comorbidities inven- tory (A-TAC) [24]. A-TAC is a comprehensive screening interview for autism spectrum disorders (ASDs), attention- deficit/hyperactivity disorder (AD/HD), tic disorders (TD), developmental coordination disorder (DCD), learning dis- orders (LD) and other childhood mental disorders that have been associated with these neurodevelopmental disorders. In the FinnTwin12 sample from Finland, aggressive behaviour was assessed at ages 12, 14 and 17 by versions of the Multidimensional Peer Nomination Inventory (MPNI). The MPNI includes 37 items comprising three subscales, the two subscales used here include: externalising behavioural problems (aggression, hyperactivity–impulsivity and inat- tention) and internalising emotional problems (anxiety and depression) [28]. For each question (e.g. ‘Does the child tease smaller or weaker children?’), the informant rated how well the description fit the twin in question on a scale from 0 (the characteristic does not fit the child at all) to 3 (the characteristic fits the child very well). Parents rated the children at age 12, and the child rated him or herself at ages 14 and 17 years. Analyses To ensure homogenous handling of data and identical analy- ses, all cohorts received a standard operating procedure that specified details of the comorbidity analyses. Following the SOP average scores and Pearson correlations for aggres- sion with all other scales assessing psychopathology was obtained by a local analyst using their preferred statistical 1 3 Table 2 Means and standard deviations for the empirical scales of the Child Behaviour Checklist (CBCL) 1.5–5 ASEBA- Rater Age Sex N Aggressive behaviour Attention problems Withdrawn Anxious– depressed Emotional reactivity Somatic complaints Sleep problems CBCL 1.5–5 Gen R Mother 3 Boy 2271 7.58 (5.37) 1.56 (1.64) 0.98 (1.43) 1.08 (1.56) 1.67 (1.82) 1.61 (1.61) 1.98 (2.16) 3 Girl 2246 6.37 (4.91) 1.44 (1.56) 0.84 (1.24) 0.99 (1.48) 1.55 (1.79) 1.57 (1.74) 1.92 (2.09) Gen R Father 3 Boy 1840 8.24 (5.60) 1.80 (1.72) 1.03 (1.40) 1.16 (1.54) 1.86 (1.99) 1.64 (1.79) 2.08 (2.24) 3 Girl 1897 7.14 (5.03) 1.55 (1.61) 0.93 (1.27) 1.10 (1.52) 1.67 (1.89) 1.52 (1.67) 1.91 (2.04) NTR Mother 3 Boy 9277 11.48 (6.85) 2.34 (1.97) 1.47 (1.69) 1.95 (1.99) 2.92 (2.66) 1.76 (1.84) 1.86 (2.18) 3 Girl 9360 9.95 (6.30) 2.03 (1.84) 1.39 (1.56) 2.05 (2.00) 2.96 (2.57) 1.86 (1.92) 1.93 (2.20) Gen R Mother 6 Boy 2887 6.65 (5.79) 1.84 (1.85) 1.33 (1.64) 1.51 (1.93) 1.97 (2.38) 1.56 (1.89) 1.49 (1.93) 6 Girl 2856 5.93 (4.90) 1.30 (1.59) 1.02 (1.35) 1.46 (1.83) 1.68 (2.06) 1.61 (1.89) 1.51 (1.93) European Child & Adolescent Psychiatry (2018) 27:1105–1121 1109 1 3 Table 3 Means and standard deviations for the empirical scales of the ASEBA taxonomy (CBCL and YSR) ASEBA Rater age Sex N Aggressive Attention Rule breaking Social problems Anxious– Withdrawn– Thought problems Somatic complaints 6–18 behaviour problems depressed depressed NTR Mother 7 Boy 5720 5.74 (5.29) 3.48 (3.13) 1.58 (2.02) 2.17 (2.48) 2.12 (2.53) 1.14 (1.63) 1.66 (2.14) 1.10 (1.57) 7 Girl 5853 4.38 (4.28) 2.56 (2.79) 1.07 (1.55) 1.91 (2.24) 2.31 (2.58) 1.09 (1.53) 1.29 (1.77) 1.26 (1.68) NTR Father 7 Boy 4134 4.98 (4.75) 3.13 (2.97) 1.37 (1.85) 1.80 (2.18) 1.62 (2.04) 0.95 (1.45) 1.33 (1.85) 0.81 (1.28) 7 Girl 4182 3.81 (4.01) 2.26 (2.59) 0.95 (1.47) 1.58 (1.95) 1.77 (2.19) 0.86 (1.36) 0.91 (1.46) 0.91 (1.39) TCHAD Parent 8 Boy 552 5.49 (5.42) 1.91 (2.40) 1.18 (1.63) 0.99 (1.57) 1.74 (2.61) 0.99 (1.24) 0.13 (0.59) 0.56 (1.04) 8 Girl 534 4.77 (4.89) 1.32 (2.07) 0.79 (1.28) 0.84 (1.52) 2.01 (2.75) 1.13 (1.35) 0.13 (0.53) 0.75 (1.28) NTR Mother 9 Boy 4543 5.09 (5.16) 3.43 (3.21) 1.43 (2.06) 2.05 (2.54) 2.14 (2.67) 1.24 (1.75) 1.61 (2.14) 1.07 (1.59) 9 Girl 4689 3.94 (4.20) 2.42 (2.75) 0.93 (1.55) 1.83 (2.34) 2.39 (2.80) 1.13 (1.64) 1.25 (1.80) 1.28 (1.78) NTR Father 9 Boy 3210 4.18 (4.57) 3.07 (3.11) 1.17 (1.78) 1.72 (2.33) 1.65 (2.21) 1.00 (1.60) 1.27 (1.88) 0.83 (1.38) 9 Girl 3255 3.34 (3.82) 2.17 (2.64) 0.79 (1.38) 1.55 (2.07) 1.86 (2.33) 0.91 (1.46) 0.93 (1.48) 0.88 (1.39) Gen R Mother 10 Boy 2250 3.26 (4.08) 3.76 (3.35) 1.24 (1.67) 1.84 (2.35) 2.14 (2.72) 1.29 (1.78) 1.80 (2.36) 1.34 (1.92) 10 Girl 2310 2.54 (3.34) 2.81 (3.00) 0.81 (1.27) 1.62 (2.13) 2.28 (2.64) 1.01 (1.48) 1.50 (2.01) 1.59 (2.02) Gen R Father 10 Boy 1624 3.28 (4.16) 3.81 (3.31) 1.36 (1.69) 1.96 (2.35) 2.05 (2.54) 1.36 (1.74) 1.92 (2.39) 1.25 (1.72) 10 Girl 1670 1.47 (3.24 2.87 (2.81) 0.89 (1.30) 1.71 (2.01) 2.11 (2.58) 1.00 (1.48) 1.43 (1.82) 1.41 (1.80) NTR Mother 12 Boy 3870 4.18 (4.63) 3.21 (3.20) 1.28 (1.87) 1.72 (2.45) 1.90 (2.56) 1.25 (1.81) 1.36 (2.02) 0.89 (1.41) 12 Girl 4010 3.27 (3.82) 2.12 (2.59) 0.79 (1.37) 1.46 (2.17) 2.18 (2.70) 1.10 (1.76) 1.03 (1.64) 1.03 (1.58) NTR Father 12 Boy 2764 3.65 (4.36) 3.02 (3.14) 1.15 (1.78) 1.58 (2.39) 1.59 (2.39) 1.10 (1.76) 1.12 (1.77) 0.72 (1.26) 12 Girl 2839 2.80 (3.52) 1.95 (2.49) 0.71 (1.29) 1.23 (1.90) 1.70 (2.29) 0.95 (1.58) 0.77 (1.35) 0.73 (1.26) TCHAD Parent 13 Boy 535 3.90 (4.30) 1.59 (2.08) 1.14 (1.56) 0.79 (1.29) 1.28 (2.01) 1.01 (1.31) 0.13 (0.60) 0.62 (1.13) 13 Girl 522 3.71 (4.60) 1.21 (1.97) 0.82 (1.52) 0.75 (1.53) 2.06 (3.31) 1.27 (1.64) 0.18 (0.67) 0.78 (1.37) TCHAD Self 13 Boy 560 8.07 (4.96) 3.57 (2.78) 2.94 (2.26) 2.02 (2.05) 3.78 (3.72) 2.12 (1.88) 1.31 (1.53) 1.47 (1.76) 13 Girl 551 7.94 (4.33) 3.75 (2.64) 2.64 (2.36) 1.89 (1.80) 5.09 (4.75) 2.42 (1.91) 1.76 (1.98) 2.19 (2.36) TCHAD Parent 16 Boy 532 3.06 (3.83) 1.24 (1.85) 1.12 (1.54) 0.57 (1.08) 1.14 (1.87) 0.90 (1.27) 0.10 (0.41) 0.65 (1.15) 16 Girl 507 3.25 (3.97) 1.21 (1.98) 1.11 (1.94) 0.55 (1.17) 2.18 (3.44) 1.11 (1.51) 0.18 (0.68) 1.09 (1.78) TCHAD Self 16 Boy 583 7.10 (4.38) 3.44 (2.69) 2.93 (2.23) 1.77 (1.91) 2.97 (3.61) 2.01 (1.89) 1.08 (1.65) 1.21 (1.60) 16 Girl 606 7.77 (4.41) 4.14 (2.69) 3.02 (2.39) 1.78 (1.76) 5.60 (4.66) 2.85 (2.07) 1.45 (1.78) 2.34 (2.50) 1110 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Table 4 Means and standard deviations for the scales of the Strengths and Difficulties Questionnaire (SDQ) SDQ Rater Age Sex N Conduct problems Hyperactivity Peer problems Emotion–anxiety Prosocial TEDS Parent 4 Boy 3581 2.23 (1.58) 4.35 (2.34) 1.58 (1.51) 1.35 (1.39) 7.07 (1.85) 4 Girl 3788 1.93 (1.49) 3.64 (2.20) 1.34 (1.41) 1.42 (1.47) 7.66 (1.77) TEDS Parent 7 Boy 2740 1.89 (1.73) 3.94 (2.61) 1.05 (1.46) 2.02 (1.74) 7.93 (1.84) 7 Girl 2892 1.45 (1.47) 3.09 (2.35) 0.83 (1.23) 2.28 (1.82) 8.54 (1.55) TEDS Parent 9 Boy 1055 1.35 (1.43) 3.56 (2.45) 1.05 (1.56) 1.47 (1.67) 7.91 (1.85) 9 Girl 1245 1.08 (1.30) 2.68 (2.08) 0.91 (1.33) 1.82 (1.88) 8.67 (1.48) TEDS Self 9 Boy 1055 2.39 (1.89) 4.13 (2.72) 1.93 (1.74) 2.99 (2.28) 7.39 (1.95) 9 Girl 1245 1.92 (1.69) 3.43 (2.15) 1.76 (1.71) 3.38 (2.40) 8.38 (1.62) TEDS Parent 12 Boy 1828 1.42 (1.48) 3.33 (2.36) 1.18 (1.58) 1.67 (1.80) 8.25 (1.74) 12 Girl 2117 1.16 (1.33) 2.28 (1.99) 0.93 (1.35) 1.90 (1.94) 8.86 (1.50) TEDS Self 12 Boy 1828 2.09 (1.48) 3.85 (2.33) 1.47 (1.63) 1.94 (1.93) 6.98 (1.96) 12 Girls 2117 1.64 (1.50) 3.09 (2.16) 1.22 (1.48) 2.43 (2.10) 7.95 (1.69) CATSS Parent 15 Boys 2083 0.93 (1.21) 2.34 (2.23) 1.29 (1.66) 0.83 (1.34) 8.03 (1.85) 15 Girls 2199 0.99 (1.30) 1.72 (1.93) 1.21 (1.61) 1.43 (1.76) 8.49 (1.80) CATSS Self 15 Boys 2258 1.78 (1.52) 3.42 (2.19) 1.79 (1.55) 2.00 (1.80) 7.37 (1.88) 15 Girls 2806 1.73 (1.39) 3.42 (2.19) 1.79 (1.55) 2.00 (1.80) 7.37 (1.88) TEDS Parent 16 Boys 2134 1.26 (1.40) 2.58 (2.08) 7.92 (2.00) 16 Girls 2632 1.18 (1.35) 1.93 (1.80) 8.50 (1.83) TEDS Self 16 Boys 2134 1.78 (1.52) 3.60 (2.32) 1.58 (1.46) 1.95 (1.86) 6.52 (1.97) 16 Girls 2632 1.58 (1.44) 3.50 (2.28) 1.53 (1.46) 3.43 (3.32) 7.64 (1.77) software. Average scores and correlations were computed aggression based on maternal ratings of 7-year-old boys in by gender and age of children, separately for each rater and the Netherlands was 5.74 (SD 5.29), while mean level of country. Results were uploaded to a shared server. Given the aggression based on parental ratings of 8-year-old boys in large datasets included in these analyses, leading to signifi- Sweden was 5.49 (SD 5.42). cance even if differences between average scores or between We observed differences between raters in nearly every correlations being relatively small, we interpreted all results country in the same direction. Based on maternal ratings, relative to each other and took the 95% confidence intervals higher levels of psychopathology were seen than when based into account. With the multi-instrument, multi-rater and on paternal ratings. These differences were observed both multi-age assessments of aggression and of other emotional for boys and girls, at ages 3–12 for the CBCL and SDQ. The and behavioural problems, we established whether co-occur- exception was an absence of differences in maternal and rence was stronger or weaker given different measurement paternal ratings when using the Devereux Child Behaviour instruments, raters and ages. rating scale. With respect to our main question of the co-occurrence of aggression and other behavioural and emotional problems, Results findings are presented in Tables  6, 7, 8 and 9. Strong correla- tions were found between aggression and other externalising Tables 2, 3, 4 and 5 provide an overview of the sample sizes traits, especially rule-breaking behaviour. Correlations of and mean levels of aggression and all other traits. We rep- almost similar strength were also observed for aggression licated the well-established gender differences in average and attention problems and hyperactivity. However, cor- aggression scores at most ages for parental ratings. The relations were lower between aggression and internalising gender difference was smaller or close to absent for self- behaviours including withdrawn–depression and somatic reports. For example, while the difference between boys and complaints. Correlations between aggression and all other girls is in general about 1.5–2 points on the CBCL and SDQ emotional and behavioural problems and their 95% confi- parental reports, the differences based on self-report ranged dence intervals are also provided in an interactive applica- between 0.05 and 0.67. tion which can be found at http://www.actio n-eupro ject.eu/ Mean levels based on similar instruments across coun-Comor bidit yChil dAggr essio n. tries were almost identical. For example, the mean level of 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1111 Some more remarkable findings included the relatively low correlation between aggression and obsessive–compul- sive behaviour and the similarly relatively low correlation between aggression and social isolation and aggression and dependency. We, furthermore, observed a relatively low correlation between aggression and peer problems from the SDQ (ranging from 0.18 to 31). However, CBCL social problems showed stronger correlations with aggression (ranging from 0.34 to 0.66). The overarching picture that emerged suggests that corre- lations are largely stable across rater and age. If any change is observed, it is indicative of stronger correlations when children grow older. The correlations patterns of boys are markedly similar to the correlational patterns of girls. The only exception was the ATAC-based correlation between ODD/CD and OCD based on parental ratings at age 12. Correlations were stronger when based on the CBCL in comparison to the other measures, especially for parental ratings, while the ATAC, which is a clinical interview rather than a survey, provided somewhat lower correlations. The Devereux Child Behaviour (DCB) rating scale provides the interesting finding of similar strength in correlations between aggressive behaviour and attention problems and anxiety problems, but also with physical coordination problems. Discussion One of the aims of ACTION is to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychopathology. Here, we presented the correlations of aggression with other psychopatholo- gies in large European samples of children between ages 3 and 16 years old. We showed that aggression co-occurred with almost all other behavioural and social problems. More specifically, aggression co-occurred with oppositional and ADHD-related problems, and at later ages with rule-break- ing. In addition to the high correlations of aggression with externalising problems, we also observed substantial asso- ciations with anxiety–depression and other internalising symptoms. This co-occurrence of internalising and exter- nalising problems has previously been shown to persist over childhood and adolescence [29]. Both for externalising and internalising problems, the patterns of co-occurrence were largely gender and rater independent, and were similar even when aggression and the other psychopathologies were assessed by different instruments, such as the CBCL and the SDQ. Also, there were large similarities in co-occurrence patterns across countries in the Northern part of Europe. In ACTION, we compared co-occurrence patterns across different countries and cultures. These comparisons are somewhat hampered by the fact that in almost all cases 1 3 Table 5 Means and standard deviations for the scales of the Devereux Child Behaviour rating scale (DCB), Autism–Tics, ADHD and other Comorbidities inventory (A-TAC) and Multidimen- sional Peer Nomination Inventory (MPNI) DCB Rater Age Sex N Aggressive behaviour Attention problems Social isolation Anxiety problems Emotion liability Dependency Physical skill NTR Mother 5 Boy 7520 12.35 (3.77) 11.87 (3.57) 4.26 (1.45) 10.66 (3.29) 11.67 (3.50) 11.45 (3.05) 9.86 (3.13) 5 Girl 7695 11.68 (3.42) 11.32 (3.44) 4.36 (1.40) 10.99 (3.40) 11.19 (3.33) 10.73 (2.87) 8.45 (2.71) NTR Father 5 Boy 6808 12.65 (3.84) 12.02 (3.34) 4.40 (1.47) 10.84 (3.22) 11.78 (3.29) 11.70 (3.03) 10.26 (3.13) 5 Girl 6985 12.05 (3.55) 11.61 (3.26) 4.46 (1.43) 11.23 (3.30) 11.40 (3.22) 11.11 (2.85) 9.05 (2.88) A-TAC Rater Age Sex N CD ADHD Autism ODD CATSS Parent 9 Boy 5610 0.11 (0.39) 2.50 (3.42) 1.00 (1.83) 0.52 (0.91) 9 Girl 5516 0.08 (0.32) 1.65 (2.72) 0.63 (1.33) 0.41 (0.81) CATSS Parent 12 Boy 1649 0.11 (0.11) 2.39 (3.25) 0.99 (1.82) 0.49 (0.87) 12 Girl 1598 0.05 (0.24) 1.36 (2.34) 0.60 (1.24) 0.32 (0.66) MPNI Rater Age Sex N Aggression Inattention Hyperactive– Social anxiety Depression Prosocial impulsivity FT12 Parent 12 Boy 1188 0.63 (0.42) 0.82 (0.52) 0.82 (0.54) 0.79 (0.61) 0.75 (0.43) 1.93 (0.37) 12 Girl 1173 0.54 (0.39) 0.57 (0.45) 0.63 (0.47) 0.87 (0.61) 0.78 (0.43) 2.03 (0.37) 1112 European Child & Adolescent Psychiatry (2018) 27:1105–1121 more than one parameter varies between the different coun- tries and cultures. For example, both NTR, a Dutch sample, and TEDs, a UK sample, have parental ratings at age 9, but NTR used the CBCL while TEDS used the SDQ. Any dif- ferences in correlations may thus be attributable to cultural differences or country differences between the Netherlands and the UK, instrument differences or any other protocol or unobserved difference. However, given all these sources of difference in this large co-occurrence study, it is even more striking that most correlations are so similar. The large associations of aggression with other emotional and behavioural problems may form one of the obstacles for prevention and treatment of aggression. These findings indicate that an exclusive focus on aggression might not be the most feasible approach for the development of effective prevention and intervention programs. The complexity of psychopathology, partly due to the co-occurrence of behav- ioural and emotional problems, needs to be addressed and its aetiology explored through genetic, longitudinal and causal modelling: do the strong associations of aggression and other emotional and behavioural problems reflect a shared genetic vulnerability for multiple disorders, or do some dis- orders causally lead to other problems? The absence of rater differences in co-occurrence patterns does not imply that rater’s views are interchangeable. Pre- vious research suggested that, in general, mothers observe more behaviour problems in their children than fathers do [30]. We also see this pattern in the current paper, and con- sistently observe it across all counties. The differences in assessment between fathers and mothers in the levels of behavioural problems they observe may indicate that they both introduce their rater-specific view on the behaviour of the child [31], or that fathers and mothers interact with their offspring in different contexts. The similarities across raters and countries indicate that large-scale gene-finding efforts of aggressive behaviour and its co-occurring psychopathologies across multiple cohorts will be feasible/successful. Such an effort is currently in pro- gress within the ACTION consortium in collaboration with other cohorts and consortia that have collected measures of aggression in children as well as DNA samples for geno- typing [32]. The results of this international genome-wide association meta-analysis (GWAMA) are expected to yield insight into the genetic variants that influence aggression across childhood and offer possibilities for the construction of polygenic scores which may be used in prediction models [33, 34] and gene-environment modelling [35]. Besides a GWAMA approach, which includes samples from multiple age groups, genome-wide epigenetic profiling will be done to compare methylation in several statistically well-powered contrasts (such as genetically identical twin pairs discordant for aggression) in children. Monozygotic (MZ) twins pairs who are longitudinally discordant of aggression, also offer 1 3 Table 6 Phenotypic correlations between aggression and other empirical scales of the Child Behaviour Checklist (CBCL) 1.5-5 ASBA- Rater Age Sex N Attention problems Withdrawn Anxious– depressed Emotional reactivity Somatic complaints Sleep problems CBCL 1.5–5 Gen R Mother 3 Boys 2271 0.60 [0.57, 0.63] 0.43 [0.39, 0.47] 0.44 [0.40, 0.48] 0.67 [0.64, 0.70] 0.39 [0.35, 0.43] 0.38 [0.34, 0.42] 3 Girls 2246 0.59 [0.56, 0.62] 0.42 [0.38, 0.46] 0.46 [0.42, 0.50] 0.68 [0.65, 0.71] 0.38 [0.34, 0.42] 0.40 [0.36, 0.44] Gen R Father 3 Boys 1840 0.67 [0.64, 0.70] 0.45 [0.41, 0.49] 0.47 [0.43, 0.51] 0.69 [0.66, 0.72] 0.39 [0.35, 0.43] 0.41 [0.37, 0.45] 3 Girls 1897 0.59 [0.55, 0.63] 0.44 [0.40, 0.48] 0.50 [0.46, 0.54] 0.71 [0.68, 0.74] 0.39 [0.35, 0.43] 0.42 [0.38, 0.46] NTR Mother 3 Boys 9277 0.58 [0.56, 0.60] 0.45 [0.43, 0.47] 0.47 [0.45, 0.49] 0.64 [0.62, 0.66] 0.36 [0.34, 0.38] 0.35 [0.33, 0.37] 3 Girls 9360 0.55 [0.53, 0.57] 0.41 [0.39, 0.43] 0.48 [0.46, 0.50] 0.65 [0.63, 0.67] 0.37 [0.35, 0.39] 0.38 [0.36, 0.40] Gen R Mother 6 Boys 2887 0.59 [0.56, 0.62] 0.58 [0.55, 0.61] 0.55 [0.52, 0.58] 0.73 [0.71, 0.75] 0.40 [0.37, 0.43] 0.41 [0.38, 0.44] 6 Girls 2856 0.55 [0.52, 0.58] 0.50 [0.47, 0.53] 0.55 [0.52, 0.58] 0.75 [0.73, 0.77] 0.42 [0.39, 0.45] 0.41 [0.38, 0.44] European Child & Adolescent Psychiatry (2018) 27:1105–1121 1113 1 3 Table 7 Phenotypic correlations between aggression and other empirical scales of the achenbach system of empirically based assessment (ASEBA) 6–18 ASEBA Rater Age Sex N Attention problems Rule breaking Social problems Anxious– depressed Withdrawn –depressed Thought problems Somatic complaints 6–18 NTR Mother 7 Boys 5720 0.56 [0.54, 0.58] 0.69 [0.67, 0.71] 0.63 [0.61, 0.65] 0.48 [0.46, 0.50] 0.36 [0.34, 0.38] 0.47 [0.45, 0.49] 0.30 [0.28, 0.32] 7 Girls 5853 0.53 [0.51, 0.55] 0.66 [0.64, 0.68] 0.63 [0.61, 0.65] 0.47 [0.45, 0.49] 0.36 [0.34, 0.38] 0.47 [0.45, 0.49] 0.32 [0.30, 0.34] NTR Father 7 Boys 4134 0.58 [0.56, 0.60] 0.66 [0.64, 0.68] 0.59 [0.57, 0.61] 0.46 [0.43, 0.49] 0.34 [0.31, 0.37] 0.44 [0.41, 0.47] 0.29 [0.26, 0.32] 7 Girls 4182 0.55 [0.52, 0.58] 0.61 [0.59, 0.63] 0.63 [0.61, 0.65] 0.49 [0.46, 0.52] 0.40 [0.37, 0.43] 0.45 [0.42, 0.48] 0.32 [0.29, 0.35] TCHAD Parent 8 Boys 552 0.66 [0.60, 0.72] 0.72 [0.66, 0.78] 0.58 [0.51, 0.65] 0.55 [0.48, 0.62] 0.36 [0.28, 0.44] 0.38 [0.30, 0.46] 0.23 [0.15, 0.31] 8 Girls 534 0.56 [0.49, 0.63] 0.64 [0.57, 0.71] 0.58 [0.51, 0.65] 0.50 [0.43, 0.57] 0.41 [0.33, 0.49] 0.36 [0.28, 0.44] 0.29 [0.21, 0.37] NTR Mother 9 Boys 4543 0.54 [0.52, 0.56] 0.70 [0.68, 0.72] 0.63 [0.61, 0.65] 0.49 [0.46, 0.52] 0.38 [0.35, 0.41] 0.44 [0.41, 0.47] 0.27 [0.24, 0.30] 9 Girls 4689 0.54 [0.52, 0.56] 0.67 [0.65, 0.69] 0.66 [0.64, 0.68] 0.53 [0.51, 0.55] 0.43 [0.40, 0.46] 0.47 [0.44, 0.50] 0.31 [0.28, 0.34] NTR Father 9 Boys 3210 0.54 [0.51, 0.57] 0.70 [0.68, 0.72] 0.60 [0.57, 0.63] 0.49 [0.46, 0.52] 0.40 [0.37, 0.43] 0.48 [0.54, 0.51] 0.27 [0.24, 0.30] 9 Girls 3255 0.53 [0.50, 0.56] 0.63 [0.60, 0.66] 0.63 [0.60, 0.66] 0.52 [0.49, 0.55] 0.43 [0.40, 0.46] 0.44 [0.41, 0.47] 0.30 [0.27, 0.33] Gen R Mother 10 Boys 2250 0.57 [0.54, 0.60] 0.72 [0.69, 0.75] 0.64 [0.61, 0.67] 0.52 [0.48, 0.56] 0.43 [0.39, 0.47] 0.56 [0.53, 0.59] 0.31 [0.27, 0.35] 10 Girls 2310 0.53 [0.50, 0.56] 0.63 [0.60, 0.66] 0.64 [0.61, 0.67] 0.53 [0.50, 0.56] 0.42 [0.38, 0.46] 0.54 [0.51, 0.57] 0.33 [0.29, 0.37] Gen R Father 10 Boys 1624 0.60 [0.56, 0.64] 0.72 [0.69, 0.75] 0.64 [0.60, 0.68] 0.51 [0.47, 0.55] 0.47 [0.43, 0.51] 0.60 [0.56, 0.64] 0.28 [0.23, 0.33] 10 Girls 1670 0.52 [0.48, 0.56] 0.62 [0.58, 0.66] 0.60 [0.56, 0.64] 0.54 [0.50, 0.58] 0.42 [0.38, 0.46] 0.57 [0.53, 0.61] 0.27 [0.22, 0.32] NTR Mother 12 Boys 3870 0.56 [0.53, 0.59] 0.71 [0.69, 0.73] 0.60 [0.57, 0.63] 0.51 [0.48, 0.54] 0.42 [0.39, 0.45] 0.46 [0.43, 0.49] 0.28 [0.25, 0.31] 12 Girls 4010 0.54 [0.51, 0.57] 0.66 [0.64, 0.68] 0.62 [0.60, 0.64] 0.55 [0.52, 0.58] 0.43 [0.40, 0.46] 0.41 [0.38, 0.44] 0.33 [0.30, 0.36] NTR Father 12 Boys 2764 0.60 [0.57, 0.63] 0.73 [0.70, 0.76] 0.61 [0.58, 0.64] 0.49 [0.46, 0.52] 0.42 [0.39, 0.45] 0.48 [0.45, 0.51] 0.32 [0.28, 0.36] 12 Girls 2839 0.55 [0.52, 0.58] 0.64 [0.61, 0.67] 0.63 [0.60, 0.66] 0.51 [0.48, 0.54] 0.43 [0.40, 0.46] 0.39 [0.36, 0.42] 0.30 [0.26, 0.34] TCHAD Parent 13 Boys 535 0.59 [0.52, 0.66] 0.60 [0.53, 0.67] 0.46 [0.38, 0.54] 0.51 [0.44, 0.58] 0.31 [0.23, 0.39] 0.22 [0.14, 0.30] 0.28 [0.20, 0.36] 13 Girls 522 0.70 [0.64, 0.76] 0.68 [0.62, 0.74] 0.62 [0.55, 0.69] 0.67 [0.61, 0.73] 0.52 [0.45, 0.59] 0.39 [0.31, 0.47] 0.44 [0.36, 0.52] TCHAD Self 13 Boys 560 0.58 [0.51, 0.65] 0.58 [0.51, 0.65] 0.44 [0.37, 0.51] 0.46 [0.39, 0.53] 0.31 [0.23, 0.39] 0.31 [0.23, 0.39] 0.35 [0.27, 0.43] 13 Girls 551 0.54 [0.47, 0.61] 0.52 [0.45, 0.59] 0.34 [0.26, 0.42] 0.43 [0.35, 0.51] 0.21 [0.13, 0.29] 0.38 [0.30, 0.46] 0.35 [0.27, 0.43] TCHAD Parent 16 Boys 532 0.58 [0.51, 0.65] 0.62 [0.55, 0.69] 0.41 [0.33, 0.49] 0.47 [0.39, 0.55] 0.30 [0.22, 0.38] 0.28 [0.20, 0.36] 0.36 [0.28, 0.44] 16 Girls 507 0.67 [0.61, 0.73] 0.73 [0.67, 0.79] 0.43 [0.35, 0.51] 0.49 [0.41, 0.57] 0.43 [0.35, 0.51] 0.34 [0.26, 0.42] 0.34 [0.26, 0.42] TCHAD Self 16 Boys 583 0.56 [0.49, 0.63] 0.56 [0.49, 0.63] 0.40 [0.33, 0.47] 0.38 [0.30, 0.46] 0.24 [0.16, 0.32] 0.39 [0.32, 0.46] 0.29 [0.21, 0.37] 16 Girls 606 0.56 [0.49, 0.63] 0.52 [0.45, 0.59] 0.36 [0.29, 0.43] 0.34 [0.27, 0.41] 0.22 [0.14, 0.30] 0.35 [0.28, 0.42] 0.34 [0.27, 0.41] 1114 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Table 8 Phenotypic correlations between aggression and other scales of the Strengths and Difficulties Questionnaire (SDQ) SDQ Rater Age Sex N Hyperactivity Peer problems Emotion–anxiety Prosocial TEDS Parent 4 Boys 3581 0.43 [0.40, 0.46] 0.22 [0.19, 0.25] 0.24 [0.21, 0.27] − 0.29 [− 0.32, − 0.26] 4 Girls 3788 0.41 [0.38, 0.44] 0.21 [0.18, 0.24] 0.26 [0.23, 0.29] − 0.30 [− 0.33, − 0.27] TEDS Parent 7 Boys 2740 0.44 [0.41, 0.47] 0.26 [0.22, 0.30] 0.24 [0.20, 0.28] − 0.26 [− 0.30, − 0.22] 7 Girls 2892 0.40 [0.37, 0.43] 0.23 [0.19, 0.27] 0.26 [0.22, 0.30] − 0.26 [− 0.30, − 0.22] TEDS Parent 9 Boys 1055 0.44 [0.39, 0.49] 0.27 [0.21, 0.33] 0.33 [0.27, 0.39] − 0.25 [− 0.31, − 0.19] 9 Girls 1245 0.45 [0.40, 0.50] 0.31 [0.26, 0.36] 0.28 [0.23, 0.33] − 0.27 [− 0.32, − 0.22] TEDS Self 9 Boys 1055 0.45 [0.40, 0.50] 0.26 [0.20, 0.32] 0.34 [0.28, 0.40] − 0.27 [− 0.33, − 0.21] 9 Girls 1245 0.43 [0.38, 0.48] 0.29 [0.24, 0.34] 0.37 [0.32, 0.42] − 0.23 [− 0.28, − 0.18] TEDS Parent 12 Boys 1828 0.46 [0.42, 0.50] 0.28 [0.24, 0.32] 0.29 [0.25, 0.33] − 0.29 [− 0.33, − 0.25] 12 Girls 2117 0.44 [0.40, 0.48] 0.27 [0.23, 0.31] 0.29 [0.25, 0.33] − 0.34 [− 0.38, − 0.30] TEDS Self 12 Boys 1828 0.53 [0.49, 0.57] 0.27 [0.23, 0.31] 0.28 [0.24, 0.32] − 0.26 [− 0.30, − 0.22] 12 Girls 2117 0.50 [0.46, 0.54] 0.29 [0.25, 0.33] 0.36 [0.32, 0.40] − 0.24 [− 0.28, − 0.20] CATSS Parent 15 Boys 2083 0.52 [0.48, 0.56] 0.25 [0.21, 0.29] 0.29 [0.25, 0.33] − 0.36 [− 0.40, − 0.32] 15 Girls 2199 0.58 [0.48, 0.56] 0.28 [0.24, 0.32] 0.39 [0.35, 0.43] − 0.45 [− 0.49, − 0.41] CATSS Self 15 Boys 2258 0.43 [0.39, 0.47] 0.21 [0.17, 0.25] 0.24 [0.20, 0.28] − 0.24 [-0.28, − 0.20] 15 Girls 2806 0.44 [0.41, 0.47] 0.19 [0.15, 0.23] 0.29 [0.28, 0.29] − 0.31 [− 0.35, − 0.27] TEDS Parent 16 Boys 2134 0.54 [0.50, 0.58] − 0.38 [− 0.42, − 0.34] 16 Girls 2632 0.51 [0.48, 0.54] − 0.42 [− 0.45, − 0.39] TEDS Self 16 Boys 2134 0.45 [0.41, 0.49] 0.18 [0.14, 0.22] 0.26 [0.22, 0.30] − 0.22 [− 0.26, − 0.18] 16 Girls 2632 0.46 [0.43, 0.49] 0.25 [0.21, 0.29] 0.27 [0.23, 0.31] − 0.25 [− 0.29, − 0.21] a unique possibility to gain an understanding of the environ- sequential effects of the comorbid disorders. If one disor - mental risk factors associated with complex behaviour such der also is found to precede another disorder, treatment can as aggression [36]. be adjusted and specified. To be able to initiate such treat- Genetic and epigenetic effects do not act in isolation, ment specificity, we need to conduct cross-lag longitudinal so the results of these studies will need to be investigated analyses to examine whether aggression is driving the other in (epi)gene x environmental interplay models to under- psychopathologies, or if aggression is a result or outing of stand the differences between children in aggression. Twin other problems. If one set of symptoms drives the rest, then data may offer a first insight into the importance of gene- intervention should focus on early detection and prevention. environment dependencies. Analyses of behavioural prob- We conclude that childhood aggression co-occurs with lems in 5-year-old twins showed strong evidence for larger nearly all other behavioural, emotional and social problems, environmental influences in children who were genetically from both externalising and internalising domains, regard- more at risk for problem behaviour [37]. The available large- less of rater, gender, measurement instrument or country. scale phenotypic, environmental and genotypic databases These findings indicate that aggression during childhood and in ACTION will allow the development and application adolescence rarely occur in isolation, and that other behav- of these methods for gene-environment interaction and ioural and emotional problems are common in children with correlation. aggressive problems. Although it is known that co-occurrence is a risk fac- tor for persisting symptoms (e.g. [38]), the implications for treatment are under-investigated. The current paper under- Future progress lines that co-occurrence of behavioural and emotional prob- lems with childhood aggression is highly prevalent. Instead The finding that aggression co-occurs with nearly all other of excluding children with multiple problems, specific trials behavioural, emotional and social problems during child- should be undertaken to investigate the effectiveness of treat- hood puts aggression in the centre of scientific attention. ment and improve treatment for this group that requires our If and when causes of differences in aggression during utmost attention. Of course, the question then arises what childhood are better understood, this information may aid would be more effective, e.g. treatment targeting all psycho- in the development of prevention and intervention strate- pathologies at the same time or treatment at symptom level. gies. To this end, we designed the EU-ACTION project It is essential to gain knowledge about the etiological and (see Fig. 1). The main objective of ACTION is to improve 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1115 1 3 Table 9 Phenotypic correlations between aggression and other scales of the Devereux Child Behaviour rating scale (DCB), Autism–Tics, ADHD and other Comorbidities inventory (A-TAC) and multidimensional peer nomination inventory (MPNI) DCB Rater Age Sex N Attention problems Social isolation Anxiety problems Emotional lability Dependency Physical coordi- nation problems NTR Mother 5 Boys 7520 0.37 [0.35, 0.39] 0.14 [0.12, 0.16] 0.35 [0.33, 0.37] 0.52 [0.50, 0.54] 0.05 [0.03, 0.07] 0.30 [0.28, 0.32] 5 Girls 7695 0.36 [0.34, 0.38] 0.07 [0.05, 0.09] 0.34 [0.32, 0.36] 0.52 [0.50, 0.54] 0.03 [0.01, 0.05] 0.29 [0.27, 0.31] NTR Father 5 Boys 6808 0.36 [0.34, 0.38] 0.15 [0.13, 0.17] 0.36 [0.34, 0.38] 0.50 [0.48, 0.52] 0.05 [0.03, 0.07] 0.33 [0.31, 0.35] 5 Girls 6985 0.37 [0.35, 0.39] 0.09 [0.07, 0.11] 0.39 [0.37, 0.41] 0.53 [0.51, 0.55] 0.06 [0.04, 0.08] 0.32 [0.30, 0.34] A-TAC Rater Age Boys girls N ADHD ODD Autism OCD CATSS Parent 9 Boys 5610 0.46 [0.44, 0.48] 0.51 [0.49, 0.43] 0.46 [0.44, 0.48] 0.19 [0.16, 0.22] 9 Girls 5516 0.45 [0.43, 0.47] 0.49 [0.47, 0.51] 0.44 [0.42, 0.46] 0.17 [0.14, 0.20] CATS Parent 12 Boys 1649 0.38 [0.34, 0.42] 0.47 [0.43, 0.51] 0.38 [0.34, 0.42] 0.16 [0.11, 0.21] 12 Girls 1598 0.37 [0.32, 0.42] 0.41 [0.37, 0.45] 0.32 [0.27, 0.37] 0.05 [0.00, 0.10] MPNI Rater Age Sex N Inattention Hyperactive– Social anxiety Depression Prosocial impulsivity FT12 Parent 12 Boys 1188 0.38 [0.33, 0.43] 0.52 [0.47, 0.57] 0.14 [0.08, 0.20] 0.27 [0.22, 0.32] − 0.34 [− 0.39, − 0.29] 12 Girls 1173 0.41 [0.36, 0.46] 0.50 [0.45, 0.55] 0.14 [0.08, 0.20] 0.29 [0.24, 0.34] − 0.30 [− 0.35, − 0.25] 1116 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Fig. 1 Work plan strategy of ACTION the understanding of the causes of individual differences in gender differences in the magnitude of genetic effects. In aggression among children to better inform the development boys, shared environment explained around 20% of the vari- of prevention and treatment strategies. ation in aggression across all ages, while in girls its influ- ACTION has described current clinical practices in ence was absent around age 7 and only came into play at Europe with respect to childhood aggression and identified later ages. Longitudinal genetic correlations explained most drawbacks in prevention and intervention of clinical aggres- of the stability of aggressive behaviour. These results are sion (also known as paediatric conduct disorders). An online encouraging for gene-finding studies. In earlier work, the semi-structured questionnaire investigating the status of first molecular genetic evidence for aggression in child- national guidelines (N = 29 academic experts; 23 countries) hood was reported [40]. Using genomic relationship matrix and an online semi-structured questionnaire exploring clini- restricted maximum likelihood (GREML) analyses signifi- cal practices (N = 94 clinicians; 22 countries) on diagnos- cant influences of common SNPs were estimated for exter - ing and treating children with severe behavioural problems nalising problems (SNP h = 0.44), for attention problems 2 2 across Europe were developed. Several countries have offi- (SNP h = 0.37–0.71) and total problems (SNP h = 0.18). cial clinical guidelines, while others have at least some unof- A previous attempt to discover genomic locations of interest ficial documents. In general, primary and secondary pre- for childhood and adolescent aggression (N = 18,988) iden- ventions were absent or poorly developed, whereas specific tified one region in chromosome 2 (2p12) at near genome- − 8 interventions for severe behavioural problems were very wide significance (top SNP rs11126630, P = 5.30 × 10 ). diverse across Europe. Improving parent–child interactions, The gene-based analysis indicated association with vari- parent/teacher interventions and collaborative approaches ation within AVPR1A with aggressive behaviour. It was were most frequently identified as successful treatment concluded that common variants at 2p12 show suggestive elements. Several needs were listed by experts and clini- evidence for association with childhood aggression [41]. To cians, which will fuel further research within ACTION and replicate this finding and to initiate new findings we will use beyond. The current findings on co-occurrence of aggression newly developed multivariate genome-wide meta-analysis indicates that information on these current drawbacks could methodology, in which the power of sample overlap (e.g. also be informative for other psychopathologies. due to having a paternal and maternal rating of the same A challenge in combining large cohort studies carried child at the same age) is leveraged instead of omitted [42]. In out in different countries is the assessment of aggression. line with the results, we include ADHD and ADHD-related Within different countries and cohorts, different instruments problems, as well aggressive behaviour in this collaborative are used. In a subsample of the Netherlands Twin Register, project. With this approach, we will be able to identify not we have invited a group of parents of 9-year-old twins to only genomic regions of interest for aggression or ADHD, complete multiple assessment instruments to have a ‘refer- but also genomic regions that play a role in the co-occur- ence set’ or ‘backbone’ for phenotype imputation. rence of these psychopathologies. The first results with respect to genetic and environmental In addition to existing genotype datasets, new DNA sam- contributions to the variation and longitudinal stability in ples are collected for epigenetic research in clinical cases childhood aggressive behaviour [39] indicated high stability (children that are referred to child psychiatric clinics in the and heritability of aggressive behavioural problems. Herit- Netherlands) and in identical twins concordant and discord- ability was on average around 60–80% without any large ant for aggression. While DNA collection and epigenetic 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1117 profiling in these children is in progress, we gained ini- human aggressive behaviour is heterogeneous and that most tial insight into the association between aggression and effective therapeutic agents only work on the serotonergic DNA methylation patterns by analysing available data on system a comprehensive study of the role of the amino acid aggression available for adults [43]. DNA methylation was neurotransmitters (including both their precursors and deg- measured in whole blood by the Illumina HM450k array radation metabolites) and peptide-based neurotransmitters is in more than 2000 adults for whom Adult Self-Report [44] warranted. In addition to this biomarker approach, ACTION data on aggression were available. No genome-wide sig- will include a metabolomics approach and the platforms we nificant methylation hits were identified, but gene-ontology are measuring include amines, organic acids and steroids. (GO) analysis, in which categories of genes rather than Results from ACTION will be integrated into an empir- single methylation sites were tested, highlighted that genes ical-based framework of aggression. The sample sizes of involved in developmental and central nervous system pro- ACTION will allow us to examine the interplay between cesses are enriched among the higher-ranking genes from risk factors and test hypotheses to identify modifiable risk the epigenome-wide meta-analysis (EWAS). This study factors for childhood aggression. Thereby, our findings may is now followed by a meta-analysis EWAS (EWAMA) in inform prevention and treatment strategies, and assist in children and adults across multiple cohorts. This EWAMA individual risk profiles based on combination of modifiable includes multiple cohorts with a sample size of over 10.000. and non-modifiable risk indicators. Translation of results In addition to genetic and environmental factors acting will be supported by several internet applications and dis- additively to the development of childhood aggression, seminating the results via the ACTION website (http://www. genes and environment may interact. Such interactions can actio n-eupro ject.eu/). be thought of as genes controlling sensitivity to the environ- Acknowledgements The ACTION consortium is supported by funding ment, or as the environment controlling the expression of from the European Union Seventh Framework Program (FP7/2007– genes. Genes and environment may also be correlated when 2013) under Grant agreement no. 602768. Data collection in the NTR genes alter the exposure to relevant environmental risk fac- was supported by NWO: Twin-family database for behavior genet- ics and genomics studies (480-04-004); “Spinozapremie” (NWO/SPI tors. We know that for traits such as aggression children are 56-464-14192; “Genetic and Family influences on Adolescent psy - not randomly distributed over environments and describing chopathology and Wellness” (NWO 463-06-001); “A twin-sib study environmental effects as “causal” may lead to wrong con- of adolescent wellness” (NWO-VENI 451-04-034); ZonMW “Genetic clusions/interventions. Several mechanisms can be at play influences on stability and change in psychopathology from child- hood to young adulthood” (912-10-020); “Netherlands Twin Registry to explain the non-random distribution of genotypes over Repository” (480-15-001/674) and KNAW Academy Professor Award environments [45]: children who inherit genes that make (PAH/6635) to DIB. We warmly thank all participating twin families. them susceptible to exhibiting aggression are likely to grow Data collection in Finntwin12 has been supported by ENGAGE— up in aggressive homes (passive rGE), their genotypes may European Network for Genetic and Genomic Epidemiology, FP7- HEALTH-F4-2007, grant agreement number 201413, National Institute trigger aggression in others (reactive rGE) and they may of Alcohol Abuse and Alcoholism (Grants AA-12502, AA-00145 and seek out aggressive peer groups (active rGE). The analyses AA-09203 to RJ Rose), the Academy of Finland Center of Excellence of rGE thus are closely related to issues of gene-environment Program (Grants 213506, 129680 to JK) and the Academy of Finland independence and to questions of causality. The analyses (Grants 100499, 205585, 118555, 141054, 265240, 263278 and 264146 to JK). The Child and Adolescent Twin Study (CATSS) in Sweden of GxE interaction will employ several approaches that can study was supported by the Swedish Council for Working Life, funds make use of the large existing datasets. The first approach under the ALF agreement, the Söderström-Königska Foundation and focuses on the estimation of the total contribution of genes the Swedish Research Council (Medicine and SIMSAM). The Swed- when environmental exposures have been measured. In this ish Twin study of Child and Adolescent Development (TCHAD) was supported by the Swedish Council for Working Life and the Swedish approach genotypes and other, non-measured, influences Research Council (Medicine and SIMSAM). Twins Early Development are modelled as latent factors. Because of the presence of Study (TEDS) is supported by a program grant from the UK Medi- genome-wide marker data, a second approach is to estimate cal Research Council (MR/M021475/1). The Generation R Study is GxE interaction in a design with measured genotypes and made possible by financial support from: Erasmus Medical Center, Rotterdam and the Netherlands Organization for Health Research and environmental exposures (note that because of the twin Development (ZonMw). H. Tiemeier is supported by grants of the design the remaining variance can still be attributed to latent Dutch Ministry of Education, Culture and Science (Gravity Grant No. G and E). The causal relation of environmental exposure 024.001.003, Consortium on Individual Development) and a NWO- and later outcome may be complex, but longitudinal twin VICI grant (NWO-ZonMW: 016.VICI.170.200). data offer excellent opportunities to test models of causal- ity versus other models of association between genes and Compliance with ethical standards environment [46, 47]. A final piece of the puzzle is sought in the assessment Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest. if biomarker and metabolomics profiles in clinical cases and MZ twins discordant for aggression. Given the fact that 1 3 1118 European Child & Adolescent Psychiatry (2018) 27:1105–1121 Open Access This article is distributed under the terms of the Crea- The Swedish Twin Register (STR) was established in tive Commons Attribution 4.0 International License (http://creat iveco 1961 and includes all 200,000 + twins born in Sweden since mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- 1886. In the Swedish Twin study of Child and Adolescent tion, and reproduction in any medium, provided you give appropriate Development (TCHAD), we have followed 1,500 twin pairs credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. from age 8 to age 20 with 4 waves of questionnaires to both parents and twins (1994, 1999, 2002, 2006) and we just com- pleted a follow-up (November 2013) at age 26. Information on behavioural and emotional problems throughout child- Appendix 1 hood is obtained by assessment with the Child Behaviour Checklist (CBCL), Teacher Report Form (TRF) and Youth Participating cohorts Self-Report (YRF), together with more in-depth assess- ments of for example aggression (Youth Psychopathic traits The Netherlands Twin Register (NTR) was established in Inventory, YPI; aggressive behaviour in youth). In the ongo- 1987 and collects data in twins and multiples from birth ing Child and Adolescent Twin Study in Sweden (CATSS) onwards. Nationwide data collection is by mailed surveys study, initiated in 2004, we conduct a psychiatric telephone to the parents of twins until age 12, and to twins after age interview with parents of all 1,400 twin pairs born in Swe- 14. At age 14, siblings of twins are also invited to take part den annually in connection with their 9th birthdays. By May and at age 18 twins and their siblings and parent are invited 2016, we have performed 28,168 interviews with a very high to complete a series of self-report questionnaires. Parents of response rate (more than 76%), and we have collected DNA twins receive questionnaires when their twins are aged 1, 2, from the twins (current N ≈ 14,500 individuals). We follow 3, 5, 7, 10 and 12 years of age. After 25 years of research, these families with questionnaires to parents and twins at large datasets have been obtained. Information on behav- age 15 (CATSS-15; current N = 11,148) and 18 (CATSS- ioural and emotional problems throughout childhood is 18; current N = 7143 twins). Information on behavioural and obtained by assessment with the Child Behaviour Check- emotional problems at age 9 is gathered through a telephone list (CBCL), Teacher Report Form (TRF), Devereux Child interview with parents using the A-TAC instrument which Behaviour (DCB) rating scale and Youth Self-Report (YSR). among others include ODD/CD modules. Aggression and This longitudinal data collection strategy has the advantage criminality are measured through questionnaires to both that multiple informant assessment can be easily combined, parents and twins at age 15 and 18. due to overlapping items by gender, informant and age. For The FinnTwin12 study was started in September 1994 each age group, items can be summed to form longitudi- to examine genetic and environmental determinants of nal syndrome scales and a total problem score. When twins precursors to health-related behaviours, with a particular reach age 18, they and their parents and siblings are invited focus on the use and abuse of alcohol, in initially 11- to to take part in the data collection as adult twin families. 12-year-old twins. This research is cast within the perspec- They receive an extensive survey, that includes the Adult tive of developmental genetic epidemiology, asking whether Self-Report (ASR). precursors of risk behaviours are evident to parents, teach- The Twins Early Development Study (TEDS) was ers and classroom peers as early as age 12. Information on established in 1995 with three birth cohorts (1994–1996) behavioural and emotional problems throughout childhood obtained from UK birth records. In infancy and early child- is obtained from in-person psychiatric interviews using the hood, questionnaires were posted to parents and teachers Semi-Structured Assessment for the Genetics of Alcohol- (with permission from parents), and school achievement ism (SSAGA) and by questionnaire assessment with the records were also obtained. Data were also obtained from Multidimensional Peer Nomination Inventory (MPNI). The telephone interviews and increasingly from online internet MPNI was designed by Finnish psychologist Dr Lea Pulk- assessment. The measure used consistently at all ages and kinen, arising from work started in 1968, and evolved into from all sources (including the twins themselves beginning the 37 item questionnaire used in the first three waves of at age 10) is the Strength and Difficulties Questionnaire assessment. The MPNI gathers information on three major (SDQ). The SDQ is particularly useful for combining infor- dimensions: Behavioural Problems (aggression [both direct mation across informants and across ages. At various ages, and indirect], hyperactivity–impulsivity and inattention), we have assessed using a battery of measures other aggres- Emotional Problems (depression, social anxiety and vic- sion-relevant domains, most notably psychopathic symptoms timisation) and Adjustment (constructiveness, compliance, and attention-deficit/hyperactivity disorder symptoms. We helping behaviour and social activity). The study has a two- are currently collecting only minimal information at age 18 stage sampling design. The larger, first-stage study is an and plan a major follow-up at age 21, which will serve our epidemiological investigation of five consecutive and com- ACTION collaboration. plete birth cohorts (1983–1987) of Finnish twins, including 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1119 questionnaire assessments of both twins and parents at References baseline, starting with a family questionnaire (returned by 1. Foster EM, Jones DE (2005) The high costs of aggression: public 2,724 families, 87% participation rate) that was mailed late expenditures resulting from conduct disorder. Am J Public Health in the year before the twins reached age 12, with follow-up 95:1767–1772. https ://doi.org/10.2105/AJPH.2004.06142 4 of all twins at age 14 and 17½, as well as a later collection 2. 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Front Genet 3:4. https :// abstractsdoi.org/10.3389/fgene .2012.00004 1 3 European Child & Adolescent Psychiatry (2018) 27:1105–1121 1121 Affiliations 1,2,3 1,2 4 5 6 7 Meike Bartels  · Anne Hendriks  · Matteo Mauri  · Eva Krapohl  · Alyce Whipp  · Koen Bolhuis  · 8 9 1,2 1,2 10 Lucia Colodro Conde  · Justin Luningham  · Hill Fung Ip  · Fiona Hagenbeek  · Peter Roetman  · 10 10 1,2 1,2 11 1,3,12 Raluca Gatej  · Audri Lamers  · Michel Nivard  · Jenny van Dongen  · Yi Lu  · Christel Middeldorp  · 1,2 10,13 14 15 8 Toos van Beijsterveldt  · Robert Vermeiren  · Thomas Hankemeijer  · Cees Kluft  · Sarah Medland  · 16,17 18 19 6,20 6,20,21 Sebastian Lundström  · Richard Rose  · Lea Pulkkinen  · Eero Vuoksimaa  · Tellervo Korhonen  · 22 9 1,23 4 7,24,25 Nicholas G. Martin  · Gitta Lubke  · Catrin Finkenauer  · Vassilios Fanos  · Henning Tiemeier  · 11 5 6,20 1,2,3 Paul Lichtenstein  · Robert Plomin  · Jaakko Kaprio  · Dorret I. Boomsma * Meike Bartels VU Medical Centre, Amsterdam, The Netherlands m.bartels@vu.nl Division of Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands Twin Register, Department of Biological The Netherlands Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands Good Biomarker Sciences, Leiden, The Netherlands 2 16 Amsterdam Public Health Research Institute, Faculty Gillberg Neuropsychiatry Centre, University of Gothenburg, of Behavioural and Movement Sciences, Vrije Universiteit Gothenburg, Sweden Amsterdam, Amsterdam, The Netherlands Centre for Ethics, Law and Mental Health (CELAM), Amsterdam Neuroscience, Amsterdam, The Netherlands University of Gothenburg, Gothenburg, Sweden 4 18 University of Cagliari, Cagliari, Italy Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA Medical Research Council Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Department of Psychology, University of Jyvaskyla, Psychology, and Neuroscience, King’s College London, Jyvaskyla, Finland London, UK Department of Public Health, University of Helsinki, Institute for Molecular Medicine Finland, University Helsinki, Finland of Helsinki, Helsinki, Finland Institute of Public Health and Clinical Nutrition, University Department of Epidemiology, Erasmus Medical Center, of Eastern Finland, Kuopio, Finland Rotterdam, The Netherlands QIMR Berghofer Medical Research Institute, Brisbane, QLD, Psychiatric Genetics Laboratory, QIMR Berghofer Medical Australia Research Institute, Brisbane, Australia Youth Studies, Interdisciplinary Center, Utrecht University, Department of Psychology, University of Notre Dame, Utrecht, The Netherlands Notre Dame, USA Department of Child and Adolescent Psychiatry, Erasmus Curium-LUMC, Academic Centre of Child and Youth Medical Center, Rotterdam, The Netherlands Psychiatry, Leiden University Medical Center, Leiden, Department of Psychiatry, Erasmus Medical Center, The Netherlands Rotterdam, The Netherlands Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden University of Queensland, Brisbane, Australia 1 3

Journal

European Child & Adolescent PsychiatrySpringer Journals

Published: May 29, 2018

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