An Initial Genetic Correlation Analysis of Externalizing Behavior and Neuroimaging Phenotypes in the ABCD Cohort

Adolescent externalizing behavior is a major risk factor for later substance use and other psychiatric outcomes. Understanding its genetic architecture and its relationships with brain imaging phenotypes requires scalable genome-wide methods that can be applied to youth cohorts. Using data from the Adolescent Brain Cognitive Development (ABCD) Study(R), we implemented a pipeline for conducting genome-wide association studies (GWAS) of longitudinal externalizing traits and multimodal imaging-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. In Step 1, ridge regression prediction models were trained using linkage disequilibrium (LD)-pruned variants. In Step 2, genome-wide association testing was performed for each phenotype. The analyses included three externalizing phenotypes--baseline, longitudinal mean, and longitudinal slope--and approximately 200 IDPs measured at baseline or summarized using their longitudinal means and slopes. We additionally constructed a custom LD reference panel using unrelated individuals and calculated LD scores using LD Score Regression software (LDSC). Genome-wide genetic correlations between externalizing traits and imaging phenotypes were subsequently estimated using cross-trait LD Score Regression. This exploratory study systematically evaluated genome-wide genetic correlations between regional cortical morphology and externalizing phenotypes during adolescence. Although several associations reached nominal statistical significance, none remained significant after correction for multiple comparisons. These results should not be interpreted as evidence for the absence of shared genetic architecture. Instead, the precision of the genetic-correlation estimates was limited by the available imaging GWAS sample size, uncertainty in SNP-based heritability estimates, and the large number of regional comparisons. Larger imaging-genetics samples and independent replication studies will be required to determine whether modest or regionally specific genetic correlations exist.