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Aim Few personalised medicine investigations have been conducted for mental health. We aimed to generate and validate a risk tool that predicts adult attention-deficit/hyperactivity disorder (ADHD). Methods Using logistic regression models, we generated a risk tool in a representative population cohort (ALSPAC – UK, 5113 participants, followed from birth to age 17) using childhood clinical and sociodemographic data with internal validation. Predictors included sex, socioeconomic status, single-parent family, ADHD symptoms, comorbid disruptive disorders, childhood maltreatment, ADHD symptoms, depressive symptoms, mother's depression and intelligence quotient. The outcome was defined as a categorical diagnosis of ADHD in young adulthood without requiring age at onset criteria. We also tested Machine Learning approaches for developing the risk models: Random Forest, Stochastic Gradient Boosting and Artificial Neural Network. The risk tool was externally validated in the E-Risk cohort (UK, 2040 participants, birth to age 18), the 1993 Pelotas Birth Cohort (Brazil, 3911 participants, birth to age 18) and the MTA clinical sample (USA, 476 children with ADHD and 241 controls followed for 16 years from a minimum of 8 and a maximum of 26 years old). Results The overall prevalence of adult ADHD ranged from 8.1 to 12% in the population-based samples, and was 28.6% in the clinical sample. The internal performance of the model in the generating sample was good, with an area under the curve (AUC) for predicting adult ADHD of 0.82 (95% confidence interval (CI) 0.79–0.83). Calibration plots showed good agreement between predicted and observed event frequencies from 0 to 60% probability. In the UK birth cohort test sample, the AUC was 0.75 (95% CI 0.71–0.78). In the Brazilian birth cohort test sample, the AUC was significantly lower –0.57 (95% CI 0.54–0.60). In the clinical trial test sample, the AUC was 0.76 (95% CI 0.73–0.80). The risk model did not predict adult anxiety or major depressive disorder. Machine Learning approaches did not outperform logistic regression models. An open-source and free risk calculator was generated for clinical use and is available online at https://ufrgs.br/prodah/adhd-calculator/. Conclusions The risk tool based on childhood characteristics specifically predicts adult ADHD in European and North-American population-based and clinical samples with comparable discrimination to commonly used clinical tools in internal medicine and higher than most previous attempts for mental and neurological disorders. However, its use in middle-income settings requires caution.

Drawing on psychological and sociological theories of crime causation, we tested the hypothesis that genetic risk for low educational attainment (assessed via a genome-wide polygenic score) predicts offending. We further tested hypotheses of how polygenic risk relates to the development of antisocial behavior from childhood through adulthood. Across the Dunedin and E-Risk birth cohorts of individuals growing up 20 years and 20,000 kilometres apart, education polygenic scores predicted risk of a criminal record, with modest effects. Polygenic risk manifested during primary schooling, in lower cognitive abilities, lower self-control, academic difficulties, and truancy, and predicted a life-course persistent pattern of antisocial behavior that onsets in childhood and persists into adulthood. Crime is central in the nature/nurture debate, and findings reported here demonstrate how molecular-genetic discoveries can be incorporated into established theories of antisocial behavior. They also suggest the hypothesis that improving school experiences might prevent genetic influences on crime from unfolding. Keywords: crime, genetics, antisocial behavior, longitudinal

Background The presence of callous-unemotional (CU) traits designates an important subgroup of antisocial youth at risk for severe, persistent, and impairing conduct problems. As a result, the fifth revision of the Diagnostic and Statistical Manual includes a specifier for youth meeting diagnostic criteria for Conduct Disorder who show elevated CU traits. The current study evaluated the DSM-5 criteria using Item Response Theory (IRT) analyses and evaluated two methods for using a self-report measure of CU traits to make this diagnosis. Methods The sample included 2257 adolescent (M age = 15.64, SD = 1.69 years) boys (53%) and girls (47%) from community and incarcerated settings in the United States and the European countries of Belgium, Germany, and Cyprus. Results IRT analyses suggested that four- or eight-item sets from the self-report measure (comparable to the symptoms used by the DSM-5 specifier) provided good model fit, suggesting that they assess a single underlying CU construct. Further, the most stringent method of scoring the self-report scale (i.e. taking only the most extreme responses) to approximate symptom presence provided the best discrimination in IRT analyses, showed reasonable prevalence rates of the specifier, and designated community adolescents who were highly antisocial, whereas the less stringent method best discriminated detained youth. Conclusions Refined self-report scales developed on the basis of IRT findings provided good assessments of most of the symptoms used in the DSM-5 criteria. These scales may be used as one component of a multimethod assessment of the 'With Limited Prosocial Emotions' specifier for Conduct Disorder. © 2014 Association for Child and Adolescent Mental Health. 56 11 1249 1261 J2: J. Child Psychol. Psychiatry Allied Discip.; Cited By :9; Export Date: 12 July 2017; CODEN: JPPDA; Correspondence Address: Kimonis, E.R.; School of Psychology, University of New South WalesAustralia

A previous finding from our group indicated that teacher-rated antisocial behaviour (AB) among 7-year-olds is particularly heritable in the presence of callous-unemotional (CU) traits. Using a sample of 1865 same-sex twin pairs, we employed DeFries-Fulker extremes analysis to investigate whether teacher-rated AB with/without CU traits also shows aetiological differences among 9-year-olds. Furthermore, we assessed whether the differences in the magnitude of heritability would be evident even when hyperactive symptoms were controlled for in the statistical analysis. AB among 9-year-olds was more heritable with than without concomitant CU. The heritability difference was even more pronounced in magnitude when hyperactive symptoms were controlled. CU traits thus appear to index one valid way of sub-typing children with early-onset AB.