Only two previous studies have used composite measures derived from factor models of externalizing phenotypes to test for association with individual genetic variants. First, Latendresse and colleagues tested for associations between a general problem behavior factor and a limited number of variants found within three candidate genes (CHRM2, GABRA2, and OPRM1) in a sample of African American adolescents (Latendresse et al., 2015). Although these authors implemented sophisticated techniques for modeling the broad problem behavior or externalizing phenotype, testing against only three genes likely limited the potential phenotypic variance explained, as compared to a more polygenic approach. At the other polygenic extreme, Salvatore and colleagues (2015) demonstrated the utility of a genome-wide polygenic risk score approach in relation to a composite score derived from a principal components analysis of symptoms of externalizing disorders. In this kind of analysis, researchers first conduct a genome wide association study (GWAS) between all available SNPs across the genome and phenotypes in a discovery sample. Then, beta weights for each SNP are used in a separate target sample to compute an additive “risk score” for all
