A genetic epidemiological mega analysis of smoking initiation in adolescents

Introduction. Previous studies in adolescents were not adequately powered to accurately disentangle genetic and environmental influences on smoking initiation across adolescence. Methods. Mega-analysis of pooled genetically informative data on smoking initiation was performed, with structural equation modeling, to test equality of prevalence and correlations across cultural backgrounds, and to estimate the significance and effect size of genetic and environmental effects according to the classical twin study, in adolescent male and female twins from same-sex and opposite-sex twin pairs (N=19 313 pairs) between age 10 and 19, with 76 358 longitudinal assessments between 1983 and 2007, from 11 population-based twin samples from the US, Europe and Australia. Results. Although prevalences differed between samples, twin correlations did not, suggesting similar etiology of smoking initiation across developed countries. The estimate of additive genetic contributions to liability of smoking initiation increased from approximately 15% to 45% from age 13 to 19. Correspondingly, shared environmental factors accounted for a substantial proportion of variance in liability to smoking initiation at age 13 (70%) and gradually less by age 19 (40%). Conclusions. Both additive genetic and shared environmental factors significantly contribute to variance in smoking initiation throughout adolescence. The present study, the largest genetic epidemiological study on smoking initiation to date, found consistent results across 11 studies for the etiology of smoking initiation. Environmental factors, especially those shared by siblings in a family, primarily influence smoking initiation variance in early adolescence, while an increasing role of genetic factors is seen at later ages, which has important implications for prevention strategies. IMPLICATIONS: This is the first study to find evidence of genetic factors in liability to smoking initiation at ages as young as 12. It also shows the strongest evidence to date for decay of effects of the shared environment from early adolescence to young adulthood. We found remarkable consistency of twin correlations across studies reflecting similar etiology of liability to initiate smoking across different cultures and time periods. Thus familial factors strongly contribute to individual differences in who starts to smoke with a gradual increase in the impact of genetic factors and a corresponding decrease in that of the shared environment

Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10 <sup>-10</sup> ). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression r <sub>g</sub> = 0.63, insomnia r <sub>g</sub> = 0.47), physical health (overweight r <sub>g</sub> = 0.19, waist-to-hip ratio r <sub>g</sub> = 0.32), smoking (r <sub>g</sub> = 0.54), cognitive ability (intelligence r <sub>g</sub> = -0.40), educational attainment (years of schooling r <sub>g</sub> = -0.46) and reproductive traits (age at first birth r <sub>g</sub> = -0.58, father's age at death r <sub>g</sub> = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB

Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder

IMPORTANCE Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63 000 participants (including MDD cases). OBJECTIVES To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD. DESIGN, SETTING, AND PARTICIPANTS Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63 661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014. MAIN OUTCOMES AND MEASURES Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts. RESULTS A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15%of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P <.05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts. CONCLUSIONS AND RELEVANCE This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism