Genetic and brain similarity independently predict childhood anthropometrics and socioeconomic markers

Linking the developing brain with individual differences in clinical and demographic traits is challenging due to the substantial interindividual heterogeneity of brain anatomy and organization. Here we employ a novel approach that parses individual differences in both cortical thickness and common genetic variants, and assess their effects on a wide set of childhood traits. The approach uses a linear mixed model framework to obtain the unique effects of each type of similarity, as well as their covariance, with the assumption that similarity in cortical thickness may in part be driven by similarity in genetic variants. We employ this approach in a sample of 7760 unrelated children in the ABCD cohort baseline sample (mean age 9.9, 46.8% female). In general, significant associations between cortical thickness similarity and traits were limited to anthropometrics such as height (r2 = 0.11, SE = 0.01), weight (r2 = 0.12, SE = 0.01), and birth weight (r2 = 0.19, SE = 0.01), as well as markers of socioeconomic status such as local area deprivation (r2 = 0.06, SE = 0.01). Analyses of the contribution from common genetic variants to traits revealed contributions across included outcomes, albeit somewhat lower than previous reports, possibly due to the young age of the sample. No significant covariance of the effects of genetic and cortical thickness similarity was found. The present findings highlight the connection between anthropometrics as well as socioeconomic factors and the developing brain, which appear to be independent from individual differences in common genetic variants in this population-based sample. The approach provides a promising framework for analyses of neuroimaging genetics cohorts, which can be further expanded by including imaging derived phenotypes beyond cortical thickness.