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.

Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

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.

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.

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.

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.

Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

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.

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.

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.

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.

Atlantic cod cDNA encoding a psychrophilic chymotrypsinogen

A cDNA clone encoding a psychrophilic cod chymotrypsinogen has been isolated and characterized. The predicted amino acid sequence reveals a preproenzyme of 263 amino acids containing a unique 18 residue signal sequence. Amino acid sequence identity between the cod and mammalian chymotrypsinogens is 64-68%. Two highly conserved proline residues are substituted in cod chymotrypsin.

Isolation and characterization of cDNAs from Atlantic cod encoding two different forms of trypsinogen

The cDNAs encoding two different anionic forms of Atlantic cod trypsinogen have been isolated and sequenced. The nucleotide sequences include the 5'-noncoding and 3'-noncoding regions in addition to preproenzymes of 241 amino acids. These consist of hydrophobic signal peptides, activation hexapeptides and trypsins of 222 amino acid residues. The cod trypsins contain all the major structural features common to trypsins such as the catalytic triad His57, Asp102 and Ser195. Furthermore, the obligatory Asp189 and the six disulphide bonds are conserved. Eight amino acid residues are different between the isozymes, leading to a difference of four charges. Both cod trypsins are one-amino-acid-residue shorter than most mammalian trypsins as a result of deletion of proline at position 152, and have a high methionine content. In addition, the cod preproenzyme signal and activation peptides differ markedly from their mammalian analogues. The amino acid identity between the cod and bovine trypsins is approximately 60%.