Unique prediction of developmental psychopathology from genetic and familial risk

Abstract

BackgroundEarly detection is critical for easing the rising burden of psychiatric disorders. However, the specificity of psychopathological measurements and genetic predictors is unclear among youth. MethodsWe measured associations between genetic risk for psychopathology (polygenic risk scores (PRS) and family history (FH) measures) and a wide range of behavioral measures in a large sample (n=5204) of early adolescent participants (9-11 years) from the Adolescent Brain and Cognitive Development (ABCD) StudySM. Associations were measured both with and without taking into consideration shared variance across measures of genetic risk. ResultsPolygenic risk for Attention Deficit Hyperactivity Disorder (ADHD) and depression (DEP) shared many significant associations with externalizing, internalizing and psychosis-related behaviors. However, when accounting for all measures of genetic and familial risk these two PRS also showed clear, unique patterns of association: the DEP PRS showed significantly stronger associations with somatic complaints and depression symptoms; whereas the ADHD PRS showed stronger associations with ADHD symptoms, impulsivity and prodromal psychosis. The Schizophrenia PRS showed a unique negative association with performance on cognitive tasks measuring fluid abilities, such as working memory and executive function, that was not accounted for by other measures of genetic risk. FH accounted for unique variability in behavior above and beyond PRS and vice versa with FH measures explaining a greater proportion of unique variability compared to the PRS. ConclusionOur results indicate that, among youth, many behaviors show shared genetic influences; however, there is also specificity in the profile of emerging psychopathologies for individuals with high genetic risk for particular disorders. This may be useful for quantifying early, differential risk for psychopathology in development. FundingThe ABCD Study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041022, U01DA041028, U01DA041048, U01DA041089, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147, U01DA041093, and U01DA041025. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. R.L was supported by Kavli Innovative Research Grant under award number 2019-1624. C.F. was supported by grant R01MH122688 and RF1MH120025 funded by the National Institute for Mental Health (NIMH).