Utility of the SWAN Scale for ADHD Trait-Based Genetic Research: A Validity and Polygenic Risk Study

Abstract

BackgroundValid and genetically-informative trait measures of psychopathology collected in the general population would provide a powerful complement to case/control genetic designs. We report the convergent, predictive and discriminant validity of the parent- and the self-report versions of the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Rating Scale (SWAN) for attention-deficit/hyperactivity disorder (ADHD) traits. We tested if SWAN ADHD scores were associated with ADHD diagnosis, ADHD polygenic risk, as well as with traits and polygenic risk for co-occurring disorders such as anxiety and obsessive-compulsive disorder (OCD).\n\nMethodsWe collected parent- and self-report SWAN scores in a community sample (n=15,560; 6-18 years of age) and created norms. Sensitivity-specificity analyses determined SWAN cut-points that discriminated those with a community ADHD diagnosis (n=972) from those without a community diagnosis. We validated cut-points from the community sample in a clinical sample (266 ADHD cases; 36 controls). We tested if SWAN scores were associated with anxiety and obsessive-compulsive (OC) traits and polygenic risk for ADHD, OCD and anxiety disorders.\n\nResultsBoth the parent- and the self-report SWAN measures showed high convergent validity with established ADHD measures and distinguished ADHD participants with high sensitivity and specificity in the community sample. Cut-points established in the community sample discriminated ADHD clinic cases from controls with a sensitivity of 86% and specificity of 94%. High parent- and self-report SWAN scores and scores above the community-based cut-points were associated with polygenic risk for ADHD. High ADHD traits were associated with high anxiety traits, but not OC traits. SWAN scores were not associated with OCD or anxiety disorder polygenic risk.\n\nConclusionThe parent- and self-report SWAN are potentially useful in genetic research because they predict ADHD diagnoses and are associated with ADHD polygenic risk.