Prediction of Aggression by ADHD subscales in children and adults

Based on Bayesian machine learning analysis performed in the MATRICS consortium, in clinical adolescent ADHD and population cohorts, differential associations between aggression and hyperactivity and between aggression and... [ view full abstract ]

Based on Bayesian machine learning analysis performed in the MATRICS consortium, in clinical adolescent ADHD and population cohorts, differential associations between aggression and hyperactivity and between aggression and inattention were suggested. We aimed to replicate these findings in the large population based Netherlands Twin Register in childhood (age 7-16 years) and in adulthood, employing both cross-sectional and longitudinal designs.

In children and in adults outcome and predictor variables were assessed by comparable instruments. Aggression was assessed by the Achenbach System of Empirically Based Assessment (ASEBA) age-appropriate inventories, namely the Child behavior Check List (CBCL), the Youth or the Adult Self Report (YSR / ASR). Hyperactivity and  inattention were assessed by the Conners Parent Rating Scale-Revised: Short version (CPRS-R:S) and the  Adult ADHD Rating Scales (CAARS).  

Based on linear regression analyses in which hyperactivity and inattention predicted aggression, we observed different results in children and in adults in a series of cross-sectional and longitudinal analyses. In children, hyperactivity was a stronger predictor of aggression than  inattention. However, in adults, inattention was the stronger predictor. As  data were collected in twin families, we next will estimate the extent to which genetic correlations between aggression and these ADHD subscales explain the observed associations .

ACTION (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies) and MATRICSMultidisciplinary Approaches to Translational Research In Conduct Syndromes) are supported by funding from the European Union Seventh Framework Program (FP7/2007-2013).