Objectives: The study aimed to examine genetic and environmental influences on the covariation of autistic- and ADHD-like behaviours in early adolescence, a period associated with heightened risk of mental health problems. It also aimed to use longitudinal statistical modelling to examine how traits of ASD and ADHD directly influence one another across ages. This longitudinal association was examined in relation to total scales as well as in relation to specific subscales.
Methods: Participants came from the Twins’ Early Development Study, a longitudinal, general population UK-based sample of monozygotic and dizygotic twin pairs. Autistic traits were measured using parent ratings on the Childhood Autism Spectrum Test (CAST), while traits of ADHD were measured using the Conners’ DSM-IV ADHD Subscales. Data were collected when twins were aged 8- and 12-years. Bivariate twin modelling enabled estimates of parameters relating to shared genetic and environmental influences. Longitudinal associations were tested using cross-lagged modelling, which enabled a consideration of the relationship between traits across time when the existing association at the first timepoint was taken into account.
Results: Bivariate twin model fitting on 12-year data suggested that the best fitting model was one that included additive genetic influences, and shared and nonshared environment, and separate estimates for males and females. The degree of genetic overlap between traits of ASD and ADHD was modest (genetic correlations = 0.41 for males, 0.23 for females) and nonshared environmental influences also showed moderate overlap (nonshared environmental correlations = 0.23 for males, 0.21 for females). Cross-lagged modelling suggested that both autistic- and ADHD-like traits influence each other across development. ADHD traits at age 8 were comparably more predictive of autistic traits at age 12 than autistic traits at age 8 were predictive of ADHD traits at age 12. Modest genetic influences were transmitted across time, while entirely different nonshared environmental influences operated on the traits at each age. Modelling by subscale suggested that autistic-like communication difficulties were more strongly predicted by ADHD scales than autistic-like social impairments or restricted, repetitive behaviours and interests. Cross-lagged associations were equally strong for both subdomains of the ADHD trait measure (inattention and hyperactivity/impulsivity).
Conclusions: Cross-lagged modelling suggested that autistic traits and traits of ADHD influence one another across time; this suggests that comorbidity in ASD is not a static phenomenon. These findings demonstrate that a greater understanding of the relationship between comorbid traits can arise from studying them within a longitudinal developmental design.