Individual Differences in The Intergenerational Transmission of Attention-Deficit/Hyperactivity Disorder: The Role of Genetic and Environmental Factors

Attention-deficit/hyperactivity disorder (ADHD) frequently runs in families, but the extent of intergenerational transmission remains highly variable. Prior work has emphasized direct genetic pathways, whereas broader environmental and polygenic influences are less understood. Here, we applied generalized random forest (GRF), a semi-parametric machine learning method for identifying individual-level differences in causal effects, to investigate the effect of parental ADHD on child ADHD symptoms in the Adolescent Brain Cognitive Development (ABCD) study. Leveraging GRF, we integrated genetic, environmental, and neuroimaging data to estimate both population-level and individualized effects. Parental ADHD consistently predicted elevated child ADHD symptoms across all models (p < .001). Critically, only the model combining environmental and genetic factors revealed significant heterogeneity in susceptibility to parental ADHD (p _European < .001, p _multiethnic = .002), with greater effects observed in children with sleep problems and higher polygenic scores for body mass index and smoking. In contrast, the polygenic score for ADHD or structural brain measures did not significantly moderate this effect. These findings suggest that sleep behaviors and polygenic liability for broader health-related traits, rather than disorder-specific genetics, may amplify susceptibility to parental ADHD and shape its intergenerational transmission. Recognizing such heterogeneity highlights potentially modifiable pathways that future work may explore in refining prevention and intervention strategies.