A polygenic score for educational attainment partially predicts voter turnout.

Twin and adoption studies have shown that individual differences in political participation can be explained, in part, by genetic variation. However, these research designs cannot identify which genes are related to voting or the pathways through which they exert influence, and their conclusions rely on possibly restrictive assumptions. In this study, we use three different US samples and a Swedish sample to test whether genes that have been identified as associated with educational attainment, one of the strongest correlates of political participation, predict self-reported and validated voter turnout. We find that a polygenic score capturing individuals' genetic propensity to acquire education is significantly related to turnout. The strongest associations we observe are in second-order midterm elections in the United States and European Parliament elections in Sweden, which tend to be viewed as less important by voters, parties, and the media and thus present a more information-poor electoral environment for citizens to navigate. A within-family analysis suggests that individuals' education-linked genes directly affect their voting behavior, but, for second-order elections, it also reveals evidence of genetic nurture. Finally, a mediation analysis suggests that educational attainment and cognitive ability combine to account for between 41% and 63% of the relationship between the genetic propensity to acquire education and voter turnout.

Genome-wide association study identifies 74 loci associated with educational attainment.

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Replicability and robustness of genome-wide-association studies for behavioral traits.

A recent genome-wide-association study of educational attainment identified three single-nucleotide polymorphisms (SNPs) whose associations, despite their small effect sizes (each R (2) ≈ 0.02%), reached genome-wide significance (p < 5 × 10(-8)) in a large discovery sample and were replicated in an independent sample (p < .05). The study also reported associations between educational attainment and indices of SNPs called "polygenic scores." In three studies, we evaluated the robustness of these findings. Study 1 showed that the associations with all three SNPs were replicated in another large (N = 34,428) independent sample. We also found that the scores remained predictive (R (2) ≈ 2%) in regressions with stringent controls for stratification (Study 2) and in new within-family analyses (Study 3). Our results show that large and therefore well-powered genome-wide-association studies can identify replicable genetic associations with behavioral traits. The small effect sizes of individual SNPs are likely to be a major contributing factor explaining the striking contrast between our results and the disappointing replication record of most candidate-gene studies.

Genetic influences on political ideologies: twin analyses of 19 measures of political ideologies from five democracies and genome-wide findings from three populations.

Almost 40 years ago, evidence from large studies of adult twins and their relatives suggested that between 30 and 60% of the variance in social and political attitudes could be explained by genetic influences. However, these findings have not been widely accepted or incorporated into the dominant paradigms that explain the etiology of political ideology. This has been attributed in part to measurement and sample limitations, as well the relative absence of molecular genetic studies. Here we present results from original analyses of a combined sample of over 12,000 twins pairs, ascertained from nine different studies conducted in five democracies, sampled over the course of four decades. We provide evidence that genetic factors play a role in the formation of political ideology, regardless of how ideology is measured, the era, or the population sampled. The only exception is a question that explicitly uses the phrase "Left-Right". We then present results from one of the first genome-wide association studies on political ideology using data from three samples: a 1990 Australian sample involving 6,894 individuals from 3,516 families; a 2008 Australian sample of 1,160 related individuals from 635 families and a 2010 Swedish sample involving 3,334 individuals from 2,607 families. No polymorphisms reached genome-wide significance in the meta-analysis. The combined evidence suggests that political ideology constitutes a fundamental aspect of one's genetically informed psychological disposition, but as Fisher proposed long ago, genetic influences on complex traits will be composed of thousands of markers of very small effects and it will require extremely large samples to have enough power in order to identify specific polymorphisms related to complex social traits.

Genetics of environmental sensitivity to psychiatric and neurodevelopmental phenotypes: evidence from GWAS of monozygotic twins.

Individual sensitivity to environmental exposures may be genetically influenced. This genotype-by-environment interplay implies differences in phenotypic variance across genotypes. However, environmental sensitivity genetic variants have proven challenging to detect. GWAS of monozygotic twin differences is a family-based variance analysis method, which is more robust to systemic biases that impact population-based methods. We combined data from up to 21,792 monozygotic twins (10,896 pairs) from 11 studies to conduct the largest GWAS meta-analysis of monozygotic phenotypic differences in children and adolescents/adults for seven psychiatric and neurodevelopmental phenotypes: attention deficit hyperactivity disorder (ADHD) symptoms, autistic traits, anxiety and depression symptoms, psychotic-like experiences, neuroticism, and wellbeing. The SNP-heritability of variance in these phenotypes were estimated (h2: 0% to 18%), but were imprecise. We identified a total of 13 genome-wide significant associations (SNP, gene, and gene-set), including genes related to stress-reactivity for depression, growth factor-related genes for autistic traits and catecholamine uptake-related genes for psychotic-like experiences. Monozygotic twins are an important new source of evidence about the genetics of environmental sensitivity.

The genetic origins of the relationship between psychological traits and social trust.

Recent studies have shown that trusting attitudes and behavior are biologically influenced. Focusing on the classic trust game, it has been demonstrated that oxytocin increases trust and that humans are endowed with genetic variation that influences their behavior in the game. Moreover, several studies have shown that a large share of the variation in survey responses to trust items is accounted for by an additive genetic component. Against this backdrop, this article makes two important contributions. First, utilizing a unique sample of more than 2,000 complete Swedish twin pairs, we provide further evidence of the heritability of social trust. Our estimates of the additive genetic component in social trust were consistent across the sexes -- .33 for males and .39 for females -- and are similar to the results reported in earlier studies. Secondly, we show that social trust is phenotypically related to three psychological traits -- extraversion, personal control, and intelligence - and that genetic factors account for most of these correlations. Jointly, these psychological factors share around 30% of the genetic influence on social trust both for males and females. Future studies should further explore the possible causal pathways between genes and trust using panel data on both psychological traits and social trust.

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals.

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.

Resource profile and user guide of the Polygenic Index Repository.

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the 'additive SNP factor'. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.

Author Correction: Multi-trait analysis of genome-wide association summary statistics using MTAG.

In the version of the paper initially published, no competing interests were declared. The 'Competing interests' statement should have stated that B.M.N. is on the Scientific Advisory Board of Deep Genomics. The error has been corrected in the HTML and PDF versions of the article.

Publisher Correction: Multi-trait analysis of genome-wide association summary statistics using MTAG.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

It Runs in the Family: A Study of Political Candidacy Among Swedish Adoptees.

What motivates citizens to run for office? Recent work has shown that early life parental socialization is strongly associated with a desire to run for office. However, parents not only shape their children's political environment, they also pass along their genes to those same children. A growing area of research has shown that individual differences in a wide range of political behaviors and attitudes are linked to genetic differences. As a result, genetic factors may confound the observed political similarities among parents and their children. This study analyzes Swedish register data containing information on all nominated and elected candidates in the ten parliamentary, county council, and municipal elections from 1982 to 2014 for a large sample of adoptees and their adoptive and biological parents. By studying the similarity in political ambition within both adoptive and biological families, our research design allows us to disentangle so-called "pre-birth" factors, such as genes and pre-natal environment, and "post-birth" factors like parental socialization. We find that the likelihood of standing as a political candidate is twice as high if one's parent has been a candidate. We also find that the effects of pre-birth and post-birth factors are approximately equal in size. In addition, we test a number of potential pre- and post-birth transmission mechanisms. First, disconfirming our expectations, the pre-birth effects do not seem to be mediated by cognitive ability or leadership skills. Second, consistent with a role modeling mechanism, we find evidence of a strong transmission in candidacy status between rearing mothers and their daughters.

Multi-trait analysis of genome-wide association summary statistics using MTAG.

We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.