An Initial Genetic Correlation Analysis of Externalizing Behavior and Neuroimaging Phenotypes in the ABCD Cohort
TL;DR
Although several associations reached nominal significance, none remained significant after correction for multiple comparisons and the precision of the estimates was constrained by the available imaging GWAS sample size, uncertainty in SNP-heritability estimates, and the large number of regional comparisons.
Abstract
Adolescent externalizing behavior is a major risk factor for later substance use and other psychiatric outcomes. Understanding its genetic architecture and its relationship with brain imaging phenotypes requires scalable genome-wide methods applied to youth cohorts. Using data from the Adolescent Brain Cognitive Development (ABCD) Study, we implemented a pipeline for genome-wide association studies (GWAS) of longitudinally measured externalizing traits and multimodal neuroimaging-derived phenotypes (IDPs). We performed quality-controlled genotype processing and constructed harmonized phenotype and covariate datasets. GWAS analyses were conducted using REGENIE in a two-step framework, with Step 1 ridge regression models trained on LD-pruned variants and Step 2 association testing performed genome-wide. Externalizing traits measured at baseline and summarized as longitudinal means and slopes, together with approximately 200 IDPs measured at baseline and summarized as longitudinal means and slopes, were analyzed. We further constructed a custom linkage disequilibrium (LD) reference panel using unrelated individuals and computed LD scores using LDSC. Genetic correlations between externalizing traits and imaging phenotypes were estimated using LD Score Regression. This exploratory study systematically evaluated genome-wide genetic correlations between regional cortical morphology and externalizing phenotypes in adolescence. Although several associations reached nominal significance, none remained significant after correction for multiple comparisons. These findings should not be interpreted as demonstrating an absence of shared genetic architecture. Rather, the precision of the estimates was constrained by the available imaging GWAS sample size, uncertainty in SNP-heritability estimates, and the large number of regional comparisons. Larger imaging-genetics samples and independent replication will be required to determine whether modest or regionally specific genetic correlations exist.