Associations between polygenic scores for cognitive and non-cognitive factors of educational attainment and measures of behavior, psychopathology, and neuroimaging in the adolescent brain cognitive development study.

Background: Educational attainment (EduA) is correlated with life outcomes, and EduA itself is influenced by both cognitive and non-cognitive factors. A recent study performed a 'genome-wide association study (GWAS) by subtraction,' subtracting genetic effects for cognitive performance from an educational attainment GWAS to create orthogonal 'cognitive' and 'non-cognitive' factors. These cognitive and non-cognitive factors showed associations with behavioral health outcomes in adults; however, whether these correlations are present during childhood is unclear.
Methods: Using data from up to 5517 youth (ages 9-11) of European ancestry from the ongoing Adolescent Brain Cognitive Development ^SM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and cognition, risk tolerance, decision-making & personality, substance initiation, psychopathology, and brain structure (e.g. volume, fractional anisotropy [FA]). Within-sibling analyses estimated whether observed genetic associations may be consistent with direct genetic effects.
Results: Both PGSs were associated with greater cognition and lower impulsivity, drive, and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk tolerance, increased odds of choosing delayed reward, and decreased likelihood of ADHD and bipolar disorder; the non-cognitive PGS was associated with lack of perseverance and reward responsiveness. Cognitive PGS were more strongly associated with larger regional cortical volumes; non-cognitive PGS were more strongly associated with higher FA. All associations were characterized by small effects.
Conclusions: While the small sizes of these associations suggest that they are not effective for prediction within individuals, cognitive and non-cognitive PGS show unique associations with phenotypes in childhood at the population level.