Genetic correlations estimated from GWAS reveal pervasive pleiotropy across a wide variety of phenotypes. We introduce genomic structural equation modeling (Genomic SEM), a multivariate method for analyzing the joint genetic architecture of complex traits. Genomic SEM synthesizes genetic correlations and SNP-heritabilities inferred from GWAS summary statistics of individual traits from samples with varying and unknown degrees of overlap. Genomic SEM can be used to model multivariate genetic associations among phenotypes, identify variants with effects on general dimensions of cross-trait liability, calculate more predictive polygenic scores, and identify loci that cause divergence between traits. We demonstrate several applications of Genomic SEM, including a joint analysis of summary statistics from five psychiatric traits. We identify 27 independent SNPs not previously identified in the contributing univariate GWASs. Polygenic scores from Genomic SEM consistently outperform those from univariate GWAS. Genomic SEM is flexible, open ended, and allows for continuous innovation in multivariate genetic analysis.

Consistent with social neuroscience perspectives on adolescent development, previous cross-sectional research has found diverging mean age-related trends for sensation seeking and impulsivity during adolescence. The present study uses longitudinal data on 7,640 youth from the National Longitudinal Study of Youth Children and Young Adults, a nationally representative sample assessed biennially from 1994 to 2006. Latent growth curve models were used to investigate mean age-related changes in self-reports of impulsivity and sensation seeking from ages 12 to 24 years, as well individual differences in these changes. Three novel findings are reported. First, impulsivity and sensation seeking showed diverging patterns of longitudinal change at the population level. Second, there was substantial person-to-person variation in the magnitudes of developmental change in both impulsivity and sensation seeking, with some teenagers showing rapid changes as they matured and others maintaining relatively constant levels with age. Finally, the correlation between age-related changes in impulsivity and sensation seeking was modest and not significant. Together, these results constitute the first support for the dual systems model of adolescent development to derive from longitudinal behavioral data.

Previous studies have documented that smoking during pregnancy (SDP) is associated with offspring externalizing problems, even when measured covariates were used to control for possible confounds. However, the association may be due to non-measured environmental and genetic factors that increase risk for offspring externalizing problems. The current project used the National Longitudinal Survey of Youth and their children, ages 4-10 years, to explore the relations between SDP and offspring conduct problems (CP), oppositional-defiant problems (ODP), and attention deficit hyperactivity problems (ADHP) using methodological and statistical controls for confounds. When offspring were compared to their own siblings who differed in their exposure to prenatal nicotine, there was no effect of SDP on offspring CP and ODP. This suggests that SDP does not have a causal effect on offspring CP and ODP. There was a small association between SDP and ADHP, consistent with a causal effect of SDP, but the magnitude of the association was greatly reduced by methodological and statistical controls. Genetically informed analyses suggest that unmeasured environmental variables influencing both SDP and offspring externalizing behaviors account for the previously observed associations. That is, the current analyses imply that important unidentified environmental factors account for the association between SDP and offspring externalizing problems, not teratogenic effects of SDP. Keywordssmoking during pregnancy; conduct problems; externalizing problems; ADHD; children of twins; causation Smoking during pregnancy (SDP) has been consistently linked with externalizing problems in offspring, particularly in males (reviews in Cnattingius, 2004;Huizink & Mulder, 2005;Wakschlag & Hans, 2002;Wakschlag, Pickett, Cook, Benowitz, & Leventhal, 2002). SDP has been associated with parent-reported conduct problems (Ernst, 2001), arrest history from national crime registries (Brennan, Grekin, & Mednick, 1999;Rasanen et al., 1999), contact 2 All correspondence should be sent to: Brian D'Onofrio, PhD, Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN 47405, bmdonofr@indiana.edu. NIH Public Access Author ManuscriptDev Psychopathol. Author manuscript; available in PMC 2013 August 08. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscriptwith police obtained by city police records (Gibson, Piquero, & Tibbets, 2000), Oppositional Defiant Disorder (Wakschlag & Keenan, 2001), Conduct Disorder (Fergusson, Woodward, & Horwood, 1998;Wakschlag & Hans, 2002;Wakschlag & Keenan, 2001;Wakschlag et al., 1997;Weissman, Warner, Wickramaratne, & Kandel, 1999) and Attention-Deficit/ Hyperactivity Disorder (Mick, Biederman, Faraone, Sayer, & Kleinman, 2002;Rodriguez & Bohlin, 2005).Reviews of the literature note that the association is consistent with a causal connection because the association is specific to externalizing problems, has been found across diverse samples and measures, demonstr...

Genes account for between approximately 50% and 70% of the variation in cognition at the population level. However, population-level estimates of heritability potentially mask marked subgroup differences. We review the body of empirical evidence indicating that (a) genetic influences on cognition increase from infancy to adulthood, and (b) genetic influences on cognition are maximized in more advantaged socioeconomic contexts (i.e., a Gene × Socioeconomic Status interaction). We discuss potential mechanisms underlying these effects, particularly transactional models of cognitive development. Transactional models predict that people in high-opportunity contexts actively evoke and select positive learning experiences on the basis of their genetic predispositions; these learning experiences, in turn, reciprocally influence cognition. The net result of this transactional process is increasing genetic influence with increasing age and increasing environmental opportunity.

Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used Genomic Structural Equation Modeling and prior genome-wide association studies (GWAS) of educational attainment ( n = 1,131,881) and cognitive test performance ( n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability.We identified 157 genome-wide significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Non-cognitive genetics were enriched in the same brain tissues and cell types as cognitive performance but showed different associations with gray-matter brain volumes. Non-cognitive genetics were further distinguished by associations with personality traits, less risky behavior,and increased risk for certain psychiatric disorders.For socioeconomic success and longevity, non-cognitive and cognitive-performance genetics demonstrated similar-magnitude associations. By conducting a GWAS of a phenotype that was not directly measured, we offer a first view of genetic architecture of non-cognitive skills influencing educational success.