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

Enrichment of genetic markers of recent human evolution in educational and cognitive traits

Higher cognitive functions are regarded as one of the main distinctive traits of humans. Evidence for the cognitive evolution of human beings is mainly based on fossil records of an expanding cranium and an increasing complexity of material culture artefacts. However, the molecular genetic factors involved in the evolution are still relatively unexplored. Here, we investigated whether genomic regions that underwent positive selection in humans after divergence from Neanderthals are enriched for genetic association with phenotypes related to cognitive functions. We used genome wide association data from a study of college completion (N = 111,114), one of educational attainment (N = 293,623) and two different studies of general cognitive ability (N = 269,867 and 53,949). We found nominally significant polygenic enrichment of associations with college completion (p = 0.025), educational attainment (p = 0.043) and general cognitive ability (p = 0.015 and 0.025, respectively), suggesting that variants influencing these phenotypes are more prevalent in evolutionarily salient regions. The enrichment remained significant after controlling for other known genetic enrichment factors, and for affiliation to genes highly expressed in the brain. These findings support the notion that phenotypes related to higher order cognitive skills typical of humans have a recent genetic component that originated after the separation of the human and Neanderthal lineages.

Creating individual level air pollution exposures in an anonymised data safe haven: a platform for evaluating impact on educational attainment

Introduction

There is a lack of evidence on the adverse effects of air pollution on cognition for people with air quality-related health conditions. We propose that educational attainment, as a proxy for cognition, may increase with improved air quality. This study will explore whether asthma and seasonal allergic rhinitis, when exacerbated by acute exposure to air pollution, is associated with educational attainment.

Objective

To describe the preparation of individual and household-level linked environmental and health data for analysis within an anonymised safe haven. Also to introduce our statistical analysis plan for our study: COgnition, Respiratory Tract illness and Effects of eXposure (CORTEX).

Methods

We imported daily air pollution and aeroallergen data, and individual level education data into the SAIL databank, an anonymised safe haven for person-based records. We linked individual-level education, socioeconomic and health data to air quality data for home and school locations, creating tailored exposures for individuals across a city. We developed daily exposure data for all pupils in repeated cross sectional exam cohorts (2009-2015).

Conclusion

We have used the SAIL databank, an innovative, data safe haven to create individual-level exposures to air pollution and pollen for multiple daily home and school locations. The analysis platform will allow us to evaluate retrospectively the impact of air quality on attainment for multiple cross-sectional cohorts of pupils. Our methods will allow us to distinguish between the pollution impacts on educational attainment for pupils with and without respiratory health conditions. The results from this study will further our understanding of the effects of air quality and respiratory-related health conditions on cognition.

Highlights

Accounting for the shared environment in cognitive abilities and academic achievement with measured socioecological contexts

Behavioral and molecular genetic research has established that child cognitive ability and academic performance are substantially heritable, but genetic variation does not account for all of the stratification of cognitive and academic outcomes across families. Which specific contexts and experiences contribute to these shared environmental influences on cognitive ability and academic achievement? Using an ethnically and socioeconomically diverse sample of N = 1728 twins ages 7-20 from the Texas Twin Project, we identified specific measured family, school, and neighborhood socioecological contexts that statistically accounted for latent shared environmental variance in cognitive abilities and academic skills. Composite measures of parent socioeconomic status (SES), school demographic composition, and neighborhood SES accounted for moderate proportions of variation in IQ and achievement. Total variance explained by the multilevel contexts ranged from 15% to 22%. The influence of family SES on IQ and achievement overlapped substantially with the influence of school and neighborhood predictors. Together with race, the measured socioecological contexts explained 100% of shared environmental influences on IQ and approximately 79% of shared environmental influences on both verbal comprehension and reading ability. In contrast, nontrivial proportions of shared environmental variation in math performance were left unexplained. We highlight the potential utility of constructing "polyenvironmental risk scores" in an effort to better predict developmental outcomes and to quantify children's and adolescents' interrelated networks of experiences. A video abstract of this article can be viewed at: https://youtu.be/77E_DctFsr0.

Circulating vitamin E levels and Alzheimer's disease: a Mendelian randomization study

Alzheimer's disease (AD) is the leading cause of dementia in older adults. It is more than 50 years since vitamin E was recognized as critical for optimal neurological health. Clinical studies have yielded inconsistent findings on the effect of vitamin E on AD risk. Thus, it remains unclear whether vitamin E levels are genetically associated with AD risk. We performed a Mendelian randomization study to investigate association of circulating vitamin E levels with AD using large-scale vitamin E genome-wide association study data set (N = 7781 individuals of European descent) and AD genome-wide association study data set (N = 54,162 individuals [including 17,008 AD cases and 37,154 controls of European descent]). Mendelian randomization-Egger intercept test showed no significant pleiotropy (β = -0.113; p = 0.296). Inverse-variance weighted (odds ratio = 0.96, 95% confidence interval: 0.47-1.94, p = 0.936) and weighted median analyses (odds ratio = 1.13, 95% confidence interval: 0.35-3.69, p = 0.836) showed no significant association between vitamin E and AD. Together with previous literature, this suggests that vitamin E supplementation may not forestall AD in the general population.

Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia

Higher educational attainment (EA) is negatively associated with schizophrenia (SZ). However, recent studies found a positive genetic correlation between EA and SZ. We investigate possible causes of this counterintuitive finding using genome-wide association study results for EA and SZ (N = 443,581) and a replication cohort (1169 controls; 1067 cases) with deeply phenotyped SZ patients. We find strong genetic dependence between EA and SZ that cannot be explained by chance, linkage disequilibrium, or assortative mating. Instead, several genes seem to have pleiotropic effects on EA and SZ, but without a clear pattern of sign concordance. Using EA as a proxy phenotype, we isolate FOXO6 and SLITRK1 as novel candidate genes for SZ. Our results reveal that current SZ diagnoses aggregate over at least two disease subtypes: one part resembles high intelligence and bipolar disorder (BIP), while the other part is a cognitive disorder that is independent of BIP.

Genetically low vitamin D concentrations and myopic refractive error: a Mendelian randomization study

Background

Myopia prevalence has increased in the past 20 years, with many studies linking the increase to reduced time spent outdoors. A number of recent observational studies have shown an inverse association between vitamin D [25(OH)D] serum levels and myopia. However, in such studies it is difficult to separate the effects of time outdoors and vitamin D levels. In this work we use Mendelian randomization (MR) to assess if genetically determined 25(OH)D levels contribute to the degree of myopia.

Methods

We performed MR using results from a meta-analysis of refractive error (RE) genome-wide association study (GWAS) that included 37 382 and 8 376 adult participants of European and Asian ancestry, respectively, published by the Consortium for Refractive Error And Myopia (CREAM). We used single nucleotide polymorphisms (SNPs) in the DHCR7, CYP2R1, GC and CYP24A1 genes with known effects on 25(OH)D concentration as instrumental variables (IV). We estimated the effect of 25(OH)D on myopia level using a Wald-type ratio estimator based on the effect estimates from the CREAM GWAS.

Results

Using the combined effect attributed to the four SNPs, the estimate for the effect of 25(OH)D on refractive error was -0.02 [95% confidence interval (CI) -0.09, 0.04] dioptres (D) per 10 nmol/l increase in 25(OH)D concentration in Caucasians and 0.01 (95% CI -0.17, 0.19) D per 10 nmol/l increase in Asians.

Conclusions

The tight confidence intervals on our estimates suggest the true contribution of vitamin D levels to degree of myopia is very small and indistinguishable from zero. Previous findings from observational studies linking vitamin D levels to myopia were likely attributable to the effects of confounding by time spent outdoors.

Trans-Ethnic Polygenic Analysis Supports Genetic Overlaps of Lumbar Disc Degeneration With Height, Body Mass Index, and Bone Mineral Density

Lumbar disc degeneration (LDD) is age-related break-down in the fibrocartilaginous joints between lumbar vertebrae. It is a major cause of low back pain and is conventionally assessed by magnetic resonance imaging (MRI). Like most other complex traits, LDD is likely polygenic and influenced by both genetic and environmental factors. However, genome-wide association studies (GWASs) of LDD have uncovered few susceptibility loci due to the limited sample size. Previous epidemiology studies of LDD also reported multiple heritable risk factors, including height, body mass index (BMI), bone mineral density (BMD), lipid levels, etc. Genetics can help elucidate causality between traits and suggest loci with pleiotropic effects. One such approach is polygenic score (PGS) which summarizes the effect of multiple variants by the summation of alleles weighted by estimated effects from GWAS. To investigate genetic overlaps of LDD and related heritable risk factors, we calculated the PGS of height, BMI, BMD and lipid levels in a Chinese population-based cohort with spine MRI examination and a Japanese case-control cohort of lumbar disc herniation (LDH) requiring surgery. Because most large-scale GWASs were done in European populations, PGS of corresponding traits were created using weights from European GWASs. We calibrated their prediction performance in independent Chinese samples, then tested associations with MRI-derived LDD scores and LDH affection status. The PGS of height, BMI, BMD and lipid levels were strongly associated with respective phenotypes in Chinese, but phenotype variances explained were lower than in Europeans which would reduce the power to detect genetic overlaps. Despite of this, the PGS of BMI and lumbar spine BMD were significantly associated with LDD scores; and the PGS of height was associated with the increased the liability of LDH. Furthermore, linkage disequilibrium score regression suggested that, osteoarthritis, another degenerative disorder that shares common features with LDD, also showed genetic correlations with height, BMI and BMD. The findings suggest a common key contribution of biomechanical stress to the pathogenesis of LDD and will direct the future search for pleiotropic genes.

Childhood Infections and Subsequent School Achievement Among 598,553 Danish Children

BACKGROUND

Hospitalizations for infections have been associated with subsequent decreased cognitive ability, but it is uncertain if childhood infections influence subsequent scholastic achievement (SA). We aimed to estimate the association between infections during childhood and SA.

METHODS

Nationwide prospective cohort study including 598,553 children born in Denmark between 1987 and 1997 and their parents. Exposures were hospitalization for infections and treatment with anti-infective agents. Outcomes were completion of ninth grade and ninth grade test scores. Data were analyzed with logistic and linear regression analysis techniques and adjusted for any mental disorder, birthweight, Apgar score, malformations at birth, chronic somatic diseases, first-born child, parental educational level and parental mental disorders.

RESULTS

Hospitalization with infections was linked to lower completion of ninth grade with an odds ratio of 0.82 (95% confidence interval: 0.79-0.85) compared with children without prior hospitalizations for infections. Dose-response relationships were observed with respect to number of hospital contacts for infections and a shorter time since last hospitalization (all P < 0.001). Among those who completed the ninth grade test score, we found a dose-response and time-since relationship between number of prior severe infections and subsequent lower grade scores (P < 0.001). Treatment of nonsevere infections with anti-infective agents did not predict lower completion of ninth grade but was associated with lower grade scores (P < 0.001).

CONCLUSIONS

Infections, particularly those requiring hospitalizations, were associated with subsequent affected cognitive ability as indicated by lower SA. These findings might also be explained by missed school days or socioeconomic factors associated with the susceptibility of acquiring infections.

Education, Smoking, and Cohort Change: Forwarding a Multidimensional Theory of the Environmental Moderation of Genetic Effects

We introduce a genetic correlation by environment interaction model [(rG)xE] which allows for social environmental moderation of the genetic relationship between two traits. To empirically demonstrate the significance of the (rG)xE perspective, we use genome wide information from respondents of the Health and Retirement Study (HRS; n = 8,181; birth years 1920-1959) and the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 4,347; birth years 1974-1983) to examine whether the genetic correlation (rG) between education and smoking has increased over historical time. Genetic correlation estimates (rG_HRS = -0.357; rG_{Add Health} = -0.729) support this hypothesis. Using polygenic scores for educational attainment, we show that this is not due to latent indicators of intellectual capacity, and we highlight the importance of education itself as an explanation of the increasing genetic correlation. Analyses based on contextual variation the milieus of the Add Health respondents corroborate key elements of the birth cohort analyses. We argue that the increasing overlap with respect to genes associated with educational attainment and smoking is a fundamentally social process involving complex process of selection based on observable behaviors that may be linked to genotype.

Associations of Combined Genetic and Lifestyle Risks With Incident Cardiovascular Disease and Diabetes in the UK Biobank Study

Importance

Genetic and lifestyle factors both contribute to the risk of developing cardiovascular disease, but whether poor health behaviors are associated with similar increases in risk among individuals with low, intermediate, or high genetic risk is unknown.

Objective

To investigate the association of combined health behaviors and factors within genetic risk groups with coronary artery disease, atrial fibrillation, stroke, hypertension, and type 2 diabetes as well as to investigate the interactions between genetic risk and lifestyle.

Design, Setting, and Participants

The UK Biobank cohort study includes more than 500 000 participants aged 40 to 70 years who were recruited from 22 assessment centers across the United Kingdom from 2006 to 2010. A total of 339 003 unrelated individuals of white British descent with available genotype and matching genetic data and reported sex were included in this study from the UK Biobank population-based sample. Individuals were included in the analyses of 1 or more new-onset diseases. Data were analyzed from April 2006 to March 2015.

Main Outcomes and Measures

Risks of new-onset cardiovascular disease and diabetes associated with genetic risk and combined health behaviors and factors. Genetic risk was categorized as low (quintile 1), intermediate (quintiles 2-4), or high (quintile 5). Within each genetic risk group, the risks of incident events associated with ideal, intermediate, or poor combined health behaviors and factors were investigated and compared with low genetic risk and ideal lifestyle.

Results

Of 339 003 individuals, 181 702 (53.6%) were female, and the mean (SD) age was 56.86 (7.99) years. During follow-up, 9771 of 325 133 participants (3.0%) developed coronary artery disease, 7095 of 333 637 (2.1%) developed atrial fibrillation, 3145 of 332 971 (0.9%) developed stroke, 11 358 of 234 651 (4.8%) developed hypertension, and 4379 of 322 014 (1.4%) developed diabetes. Genetic risk and lifestyle were independent predictors of incident events, and there were no interactions for any outcome. Compared with ideal lifestyle in the low genetic risk group, poor lifestyle was associated with a hazard ratio of up to 4.54 (95% CI, 3.72-5.54) for coronary artery disease, 5.41 (95% CI, 4.29-6.81) for atrial fibrillation, 4.68 (95% CI, 3.85-5.69) for hypertension, 2.26 (95% CI, 1.63-3.14) for stroke, and 15.46 (95% CI, 10.82-22.08) for diabetes in the high genetic risk group.

Conclusions and Relevance

In this large contemporary population, genetic composition and combined health behaviors and factors had a log-additive effect on the risk of developing cardiovascular disease. The relative effects of poor lifestyle were comparable between genetic risk groups. Behavioral lifestyle changes should be encouraged for all through comprehensive, multifactorial approaches, although high-risk individuals may be selected based on the genetic risk.

Schools as Moderators of Genetic Associations with Life Course Attainments: Evidence from the WLS and Add Health

Genetic variants identified in genome-wide association studies of educational attainment have been linked with a range of positive life course development outcomes. However, it remains unclear whether school environments may moderate these genetic associations. We analyze data from two biosocial surveys that contain both genetic data and follow students from secondary school through mid- to late life. We test if the magnitudes of the associations with educational and occupational attainments varied across the secondary schools that participants attended or with characteristics of those schools. Although we find little evidence that genetic associations with educational and occupational attainment varied across schools or with school characteristics, genetic associations with any postsecondary education and college completion were moderated by school-level socioeconomic status. Along similar lines, we observe substantial between-school variation in the average level of educational attainment students achieved for a fixed genotype. These findings emphasize the importance of social context in the interpretation of genetic associations. Specifically, our results suggest that though existing measures of individual genetic endowment have a linear relationship with years of schooling that is relatively consistent across school environments, school context is crucial in connecting an individual's genotype to his or her likelihood of crossing meaningful educational thresholds.

Pleiotropy-robust Mendelian randomization

Background

The potential of Mendelian randomization studies is rapidly expanding due to: (i) the growing power of genome-wide association study (GWAS) meta-analyses to detect genetic variants associated with several exposures; and (ii) the increasing availability of these genetic variants in large-scale surveys. However, without a proper biological understanding of the pleiotropic working of genetic variants, a fundamental assumption of Mendelian randomization (the exclusion restriction) can always be contested.

Methods

We build upon and synthesize recent advances in the literature on instrumental variables (IVs) estimation that test and relax the exclusion restriction. Our pleiotropy-robust Mendelian randomization (PRMR) method first estimates the degree of pleiotropy, and in turn corrects for it. If (i) a subsample exists for which the genetic variants do not affect the exposure; (ii) the selection into this subsample is not a joint consequence of the IV and the outcome; (iii) pleiotropic effects are homogeneous, PRMR obtains unbiased estimates of causal effects.

Results

Simulations show that existing MR methods produce biased estimators for realistic forms of pleiotropy. Under the aforementioned assumptions, PRMR produces unbiased estimators. We illustrate the practical use of PRMR by estimating the causal effect of: (i) tobacco exposure on body mass index (BMI); (ii) prostate cancer on self-reported health; and (iii) educational attainment on BMI in the UK Biobank data.

Conclusions

PRMR allows for instrumental variables that violate the exclusion restriction due to pleiotropy, and it corrects for pleiotropy in the estimation of the causal effect. If the degree of pleiotropy is unknown, PRMR can still be used as a sensitivity analysis.

Exploring the association of genetic factors with participation in the Avon Longitudinal Study of Parents and Children

Background

It is often assumed that selection (including participation and dropout) does not represent an important source of bias in genetic studies. However, there is little evidence to date on the effect of genetic factors on participation.

Methods

Using data on mothers (N = 7486) and children (N = 7508) from the Avon Longitudinal Study of Parents and Children, we: (i) examined the association of polygenic risk scores for a range of sociodemographic and lifestyle characteristics and health conditions related to continued participation; (ii) investigated whether associations of polygenic scores with body mass index (BMI; derived from self-reported weight and height) and self-reported smoking differed in the largest sample with genetic data and a subsample who participated in a recent follow-up; and (iii) determined the proportion of variation in participation explained by common genetic variants, using genome-wide data.

Results

We found evidence that polygenic scores for higher education, agreeableness and openness were associated with higher participation; and polygenic scores for smoking initiation, higher BMI, neuroticism, schizophrenia, attention-deficit hyperactivity disorder (ADHD) and depression were associated with lower participation. Associations between the polygenic score for education and self-reported smoking differed between the largest sample with genetic data [odds ratio (OR) for ever smoking per standard deviation (SD) increase in polygenic score: 0.85, 95% confidence interval (CI): 0.81, 0.89} and subsample (OR: 0.96, 95% CI: 0.89, 1.03). In genome-wide analysis, single nucleotide polymorphism based heritability explained 18-32% of variability in participation.

Conclusions

Genetic association studies, including Mendelian randomization, can be biased by selection, including loss to follow-up. Genetic risk for dropout should be considered in all analyses of studies with selective participation.

Cell-specific histone modification maps in the human frontal lobe link schizophrenia risk to the neuronal epigenome

Risk variants for schizophrenia affect more than 100 genomic loci, yet cell- and tissue-specific roles underlying disease liability remain poorly characterized. We have generated for two cortical areas implicated in psychosis, the dorsolateral prefrontal cortex and anterior cingulate cortex, 157 reference maps from neuronal, neuron-depleted and bulk tissue chromatin for two histone marks associated with active promoters and enhancers, H3-trimethyl-Lys4 (H3K4me3) and H3-acetyl-Lys27 (H3K27ac). Differences between neuronal and neuron-depleted chromatin states were the major axis of variation in histone modification profiles, followed by substantial variability across subjects and cortical areas. Thousands of significant histone quantitative trait loci were identified in neuronal and neuron-depleted samples. Risk variants for schizophrenia, depressive symptoms and neuroticism were significantly over-represented in neuronal H3K4me3 and H3K27ac landscapes. Our Resource, sponsored by PsychENCODE and CommonMind, highlights the critical role of cell-type-specific signatures at regulatory and disease-associated noncoding sequences in the human frontal lobe.

Investigating causality in associations between education and smoking: a two-sample Mendelian randomization study

Background

Lower educational attainment is associated with increased rates of smoking, but ascertaining causality is challenging. We used two-sample Mendelian randomization (MR) analyses of summary statistics to examine whether educational attainment is causally related to smoking.

Methods and Findings

We used summary statistics from genome-wide association studies (GWAS) of educational attainment and a range of smoking phenotypes (smoking initiation, cigarettes per day, cotinine levels and smoking cessation). Of 74 single nucleotide polymorphisms (SNPs) that predict educational attainment, 57 (or their highly correlated proxies) were present in the smoking initiation, cigarettes per day and smoking cessation GWAS, and 72 in the cotinine GWAS. Various complementary MR techniques (inverse variance weighted regression, MR Egger, weighted median regression) were used to test the robustness of our results. We found broadly consistent evidence across these techniques that higher educational attainment leads to reduced likelihood of smoking initiation, reduced heaviness of smoking among smokers (as measured via self-report [e.g. inverse variance weighted beta -2.25, 95% confidence interval (CI) -3.81, -0.70, P = 0.005] and cotinine levels [e.g. inverse variance weighted beta -0.34, 95% CI -0.67, -0.01, P = 0.057]), and greater likelihood of smoking cessation among smokers (inverse variance weighted beta 0.65, 95% CI 0.35, 0.95, P = 5.54 × 10-5). Less consistent across the different techniques were associations between educational attainment and smoking initiation.

Conclusions

Our findings indicate a causal association between low educational attainment and increased risk of smoking, and may explain the observational associations between educational attainment and adverse health outcomes such as risk of coronary heart disease.

Genetic analysis of social-class mobility in five longitudinal studies

A summary genetic measure, called a "polygenic score," derived from a genome-wide association study (GWAS) of education can modestly predict a person's educational and economic success. This prediction could signal a biological mechanism: Education-linked genetics could encode characteristics that help people get ahead in life. Alternatively, prediction could reflect social history: People from well-off families might stay well-off for social reasons, and these families might also look alike genetically. A key test to distinguish biological mechanism from social history is if people with higher education polygenic scores tend to climb the social ladder beyond their parents' position. Upward mobility would indicate education-linked genetics encodes characteristics that foster success. We tested if education-linked polygenic scores predicted social mobility in >20,000 individuals in five longitudinal studies in the United States, Britain, and New Zealand. Participants with higher polygenic scores achieved more education and career success and accumulated more wealth. However, they also tended to come from better-off families. In the key test, participants with higher polygenic scores tended to be upwardly mobile compared with their parents. Moreover, in sibling-difference analysis, the sibling with the higher polygenic score was more upwardly mobile. Thus, education GWAS discoveries are not mere correlates of privilege; they influence social mobility within a life. Additional analyses revealed that a mother's polygenic score predicted her child's attainment over and above the child's own polygenic score, suggesting parents' genetics can also affect their children's attainment through environmental pathways. Education GWAS discoveries affect socioeconomic attainment through influence on individuals' family-of-origin environments and their social mobility.

Relationships between estimated autozygosity and complex traits in the UK Biobank

Inbreeding increases the risk of certain Mendelian disorders in humans but may also reduce fitness through its effects on complex traits and diseases. Such inbreeding depression is thought to occur due to increased homozygosity at causal variants that are recessive with respect to fitness. Until recently it has been difficult to amass large enough sample sizes to investigate the effects of inbreeding depression on complex traits using genome-wide single nucleotide polymorphism (SNP) data in population-based samples. Further, it is difficult to infer causation in analyses that relate degree of inbreeding to complex traits because confounding variables (e.g., education) may influence both the likelihood for parents to outbreed and offspring trait values. The present study used runs of homozygosity in genome-wide SNP data in up to 400,000 individuals in the UK Biobank to estimate the proportion of the autosome that exists in autozygous tracts—stretches of the genome which are identical due to a shared common ancestor. After multiple testing corrections and controlling for possible sociodemographic confounders, we found significant relationships in the predicted direction between estimated autozygosity and three of the 26 traits we investigated: age at first sexual intercourse, fluid intelligence, and forced expiratory volume in 1 second. Our findings corroborate those of several published studies. These results may imply that these traits have been associated with Darwinian fitness over evolutionary time. However, some of the autozygosity-trait relationships were attenuated after controlling for background sociodemographic characteristics, suggesting that alternative explanations for these associations have not been eliminated. Care needs to be taken in the design and interpretation of ROH studies in order to glean reliable information about the genetic architecture and evolutionary history of complex traits.

Inbreeding is well known to increase the risk of rare, monogenic diseases, and there has been some evidence that it also affects complex traits, such as cognition and educational attainment. However, difficulties can arise when inferring causation in these types of analyses because of the potential for confounding variables (e.g., socioeconomic status) to bias the observed relationships between distant inbreeding and complex traits. In this investigation, we used single-nucleotide polymorphism data in a very large (N > 400,000) sample of seemingly outbred individuals to quantify the degree to which distant inbreeding is associated with 26 complex traits. We found robust evidence that distant inbreeding is inversely associated with fluid intelligence and a measure of lung function, and is positively associated with age at first sex, while other trait associations with inbreeding were attenuated after controlling for background sociodemographic characteristics. Our findings are consistent with evolutionary predictions that fluid intelligence, lung function, and age at first sex have been under selection pressures over time; however, they also suggest that confounding variables must be accounted for in order to reliably interpret results from these types of analyses.

Genes regulated by SATB2 during neurodevelopment contribute to schizophrenia and educational attainment

SATB2 is associated with schizophrenia and is an important transcription factor regulating neocortical organization and circuitry. Rare mutations in SATB2 cause a syndrome that includes developmental delay, and mouse studies identify an important role for SATB2 in learning and memory. Interacting partners BCL11B and GATAD2A are also schizophrenia risk genes indicating that other genes interacting with or are regulated by SATB2 are making a contribution to schizophrenia and cognition. We used data from Satb2 mouse models to generate three gene-sets that contain genes either functionally related to SATB2 or targeted by SATB2 at different stages of development. Each was tested for enrichment using the largest available genome-wide association studies (GWAS) datasets for schizophrenia and educational attainment (EA) and enrichment analysis was also performed for schizophrenia and other neurodevelopmental disorders using data from rare variant sequencing studies. These SATB2 gene-sets were enriched for genes containing common variants associated with schizophrenia and EA, and were enriched for genes containing rare variants reported in studies of schizophrenia, autism and intellectual disability. In the developing cortex, genes targeted by SATB2 based on ChIP-seq data, and functionally affected when SATB2 is not expressed based on differential expression analysis using RNA-seq data, show strong enrichment for genes associated with EA. For genes expressed in the hippocampus or at the synapse, those targeted by SATB2 are more strongly enriched for genes associated EA than gene-sets not targeted by SATB2. This study demonstrates that single gene findings from GWAS can provide important insights to pathobiological processes. In this case we find evidence that genes influenced by SATB2 and involved in synaptic transmission, axon guidance and formation of the corpus callosum are contributing to schizophrenia and cognition.

Schizophrenia is a complex disorder caused by many genes. Using new gene discoveries to understand pathobiology is a foundation for development of new treatments. Current drugs for schizophrenia are only partially effective and do not treat cognitive deficits, which are key factors for explaining disability, leading to unemployment, homelessness and social isolation. Genome-wide association studies (GWAS) of schizophrenia have been effective at identifying individual SNPs and genes that contribute to risk but have struggled to immediately uncover the bigger picture of the underlying biology of the disorder. Here we take an individual gene identified in a schizophrenia GWAS called SATB2, which on its own is a very important regulator of brain development. We use functional genomics data from mouse studies to identify sets of others genes that are influenced by SATB2 during development. We show that these gene sets are enriched for common variants associated with schizophrenia and educational attainment (used as a proxy for cognition), and for rare variants that increase risk of various neurodevelopmental disorders. This study provides evidence that the molecular mechanisms that underpin schizophrenia and cognitive function include disruption of biological processes influenced by SATB2 as the brain is being organized and wired during development.

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 GWAS and Biological Insights Into Cognition: A Response to Hill (2018)

Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'.

Effects of autozygosity and schizophrenia polygenic risk on cognitive and brain developmental trajectories

Cognitive and brain development are determined by dynamic interactions between genes and environment across the lifespan. Aside from marker-by-marker analyses of polymorphisms, biologically meaningful features of the whole genome (derived from the combined effect of individual markers) have been postulated to inform on human phenotypes including cognitive traits and their underlying biological substrate. Here, estimates of inbreeding and genetic susceptibility for schizophrenia calculated from genome-wide data-runs of homozygosity (ROH) and schizophrenia polygenic risk score (PGRS)-are analyzed in relation to cognitive abilities (n = 4183) and brain structure (n = 516) in a general-population sample of European-ancestry participants aged 8-22, from the Philadelphia Neurodevelopmental Cohort. The findings suggest that a higher ROH burden and higher schizophrenia PGRS are associated with higher intelligence. Cognition-ROH and cognition-PGRS associations obtained in this cohort may, respectively, evidence that assortative mating influences intelligence, and that individuals with high schizophrenia genetic risk who do not transition to disease status are cognitively resilient. Neuroanatomical data showed that the effects of schizophrenia PGRS on cognition could be modulated by brain structure, although larger imaging datasets are needed to accurately disentangle the underlying neural mechanisms linking IQ with both inbreeding and the genetic burden for schizophrenia.

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

Parental Educational Attainment and Offspring Subjective Well-being and Self-Beliefs in Older Adulthood

This research examines whether parental educational attainment and subjective childhood socioeconomic status (SES) is associated with adult offspring well-being and self-beliefs (broadly defined). Participants from the Health and Retirement Study were included if they completed the leave-behind questionnaire in 2006 or 2008 (N=10,827; M_age=68.38; SD=9.81; range=50-101). Participants reported on their own and both parents educational attainment, subjective childhood financial situation, and financial difficulties in childhood at study entry and on well-being in 2006/2008. Linear regression was used to examine the association between offspring education, parental education, childhood SES and three aspects of well-being and self-beliefs: positive affect (e.g., positive emotions, optimism), negative affect (e.g., loneliness, hostility), and cognitive evaluation (e.g., life satisfaction). Participants with more education reported higher well-being (median β=.12). Parental educational attainment, subjective childhood SES, and a significant financial event during childhood were associated with more positive affect, less negative affect, and higher life satisfaction (median β=.05); these associations held controlling for offspring education. The educational and financial environment of childhood may hamper well-being into older adulthood; the offspring's own experiences and achievements do not completely attenuate the association with these aspects of the childhood environment.

Genome-wide association study of cognitive flexibility assessed by the Wisconsin Card Sorting Test

Cognitive flexibility is a critical component of executive function and is strongly influenced by genetic factors. We conducted a genome-wide association study of cognitive flexibility (as measured by perseverative errors on the Wisconsin Card Sorting Test) in two sets of African American (AA) and European American (EA) subjects (Yale-Penn-1: 1,411 AAs/949 EAs; Yale-Penn-2: 1,178 AAs/1,335 EAs). We examined the association of cognitive flexibility with genotyped or imputed SNPs across the genome. In AAs, two correlated common single nucleotide polymorphisms (SNPs) (rs7165213/rs35633795) in the downstream region of the noncoding gene LOC101927286 on chromosome 15 showed genome-wide significant (GWS) associations with cognitive flexibility (Yale-Penn-1: p = 6.0 × 10^-9 /1.3 × 10^-8 ; Yale-Penn-2: p = .029/.010; meta-analysis: p = 4.2 × 10^-7 /1.0 × 10^-7 ) in the same effect direction. In EAs, no GWS associations were observed. Enriched gene sets identified by Data-driven Expression-Prioritized Integration for Complex Traits (DEPICT) analysis of the top SNPs (p_{meta-analysis}  < 10^-5 ) included the signalosome and ubiquitin-specific peptidase 9, X-linked (USP9X) subnetwork in AAs, and abnormal frontal and occipital bone morphology in EAs. We also performed polygenic risk score (PRS) analysis to examine the genetic correlation of cognition-proxy phenotypes (general cognitive function, education attainment, childhood intelligence, and infant head circumference) and cognitive flexibility in EAs. The PRS derived from general cognitive function-associated SNPs was significantly associated with cognitive flexibility. Nongenetic factors (age, education, sex, and tobacco recency) also exerted significant effects on cognitive flexibility. Our study demonstrates that both genetic and nongenetic factors impact cognitive flexibility, and variants in genes involved in protein degradation and brain development may contribute to population variation in cognitive function.

Genetics of co-developing conduct and emotional problems during childhood and adolescence

Common genetic influences offer a partial explanation for comorbidity between different psychiatric disorders1-3. However, the genetics underlying co-development-the cross-domain co-occurrence of patterns of change over time-of psychiatric symptoms during childhood and adolescence has not been well explored. Here, we show genetic influence on joint symptom trajectories of parent-reported conduct and emotional problems (overall N = 15,082) across development (4-16 years) using both twin- and genome-wide polygenic score analyses (genotyped N = 2,610). Specifically, we found seven joint symptom trajectories, including two characterized by jointly stable and jointly increasing symptoms of conduct and emotional problems, respectively (7.3% of the sample, collectively). Twin modelling analyses revealed substantial genetic influence on trajectories (heritability estimates range of 0.41-0.78). Furthermore, individuals' risk of being classified in the most symptomatic trajectory classes was significantly predicted by polygenic scores for years-of-education-associated alleles and depressive symptoms-associated alleles. Complementary analyses of child self-reported symptoms across late childhood and early adolescence yielded broadly similar results. Taken together, our results indicate that genetic factors are involved in the co-development of conduct and emotional problems across childhood and adolescence, and that individuals with co-developing symptoms across multiple domains may represent a clinical subgroup characterized by increased levels of genetic risk.

Leveraging molecular quantitative trait loci to understand the genetic architecture of diseases and complex traits

There is increasing evidence that many risk loci found using genome-wide association studies are molecular quantitative trait loci (QTLs). Here we introduce a new set of functional annotations based on causal posterior probabilities of fine-mapped molecular cis-QTLs, using data from the Genotype-Tissue Expression (GTEx) and BLUEPRINT consortia. We show that these annotations are more strongly enriched for heritability (5.84× for eQTLs; P = 1.19 × 10-31) across 41 diseases and complex traits than annotations containing all significant molecular QTLs (1.80× for expression (e)QTLs). eQTL annotations obtained by meta-analyzing all GTEx tissues generally performed best, whereas tissue-specific eQTL annotations produced stronger enrichments for blood- and brain-related diseases and traits. eQTL annotations restricted to loss-of-function intolerant genes were even more enriched for heritability (17.06×; P = 1.20 × 10-35). All molecular QTLs except splicing QTLs remained significantly enriched in joint analysis, indicating that each of these annotations is uniquely informative for disease and complex trait architectures.

Analysis of shared heritability in common disorders of the brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top-associated cis-expression or -DNA methylation (DNAm) quantitative trait loci (cis-eQTLs or cis-mQTLs) between brain and blood (r _b ). Using publicly available data, we find that genetic effects at the top cis-eQTLs or mQTLs are highly correlated between independent brain and blood samples ([Formula: see text] for cis-eQTLs and [Formula: see text] for cis-mQTLs). Using meta-analyzed brain cis-eQTL/mQTL data (n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL/mQTL data with large sample sizes.

Education and myopia: assessing the direction of causality by mendelian randomisation

OBJECTIVES

To determine whether more years spent in education is a causal risk factor for myopia, or whether myopia is a causal risk factor for more years in education.

DESIGN

Bidirectional, two sample mendelian randomisation study.

SETTING

Publically available genetic data from two consortiums applied to a large, independent population cohort. Genetic variants used as proxies for myopia and years of education were derived from two large genome wide association studies: 23andMe and Social Science Genetic Association Consortium (SSGAC), respectively.

PARTICIPANTS

67 798 men and women from England, Scotland, and Wales in the UK Biobank cohort with available information for years of completed education and refractive error.

MAIN OUTCOME MEASURES

Mendelian randomisation analyses were performed in two directions: the first exposure was the genetic predisposition to myopia, measured with 44 genetic variants strongly associated with myopia in 23andMe, and the outcome was years in education; and the second exposure was the genetic predisposition to higher levels of education, measured with 69 genetic variants from SSGAC, and the outcome was refractive error.

RESULTS

Conventional regression analyses of the observational data suggested that every additional year of education was associated with a more myopic refractive error of -0.18 dioptres/y (95% confidence interval -0.19 to -0.17; P<2e-16). Mendelian randomisation analyses suggested the true causal effect was even stronger: -0.27 dioptres/y (-0.37 to -0.17; P=4e-8). By contrast, there was little evidence to suggest myopia affected education (years in education per dioptre of refractive error -0.008 y/dioptre, 95% confidence interval -0.041 to 0.025, P=0.6). Thus, the cumulative effect of more years in education on refractive error means that a university graduate from the United Kingdom with 17 years of education would, on average, be at least -1 dioptre more myopic than someone who left school at age 16 (with 12 years of education). Myopia of this magnitude would be sufficient to necessitate the use of glasses for driving. Sensitivity analyses showed minimal evidence for genetic confounding that could have biased the causal effect estimates.

CONCLUSIONS

This study shows that exposure to more years in education contributes to the rising prevalence of myopia. Increasing the length of time spent in education may inadvertently increase the prevalence of myopia and potential future visual disability.

The role of genetic variation of human metabolism for BMI, mental traits and mental disorders

OBJECTIVE

The aim was to assess whether loci associated with metabolic traits also have a significant role in BMI and mental traits/disorders METHODS: We first assessed the number of single nucleotide polymorphisms (SNPs) with genome-wide significance for human metabolism (NHGRI-EBI Catalog). These 516 SNPs (216 independent loci) were looked-up in genome-wide association studies for association with body mass index (BMI) and the mental traits/disorders educational attainment, neuroticism, schizophrenia, well-being, anxiety, depressive symptoms, major depressive disorder, autism-spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer's disease, bipolar disorder, aggressive behavior, and internalizing problems. A strict significance threshold of p < 6.92 × 10-6 was based on the correction for 516 SNPs and all 14 phenotypes, a second less conservative threshold (p < 9.69 × 10-5) on the correction for the 516 SNPs only.

RESULTS

19 SNPs located in nine independent loci revealed p-values < 6.92 × 10-6; the less strict criterion was met by 41 SNPs in 24 independent loci. BMI and schizophrenia showed the most pronounced genetic overlap with human metabolism with three loci each meeting the strict significance threshold. Overall, genetic variation associated with estimated glomerular filtration rate showed up frequently; single metabolite SNPs were associated with more than one phenotype. Replications in independent samples were obtained for BMI and educational attainment.

CONCLUSIONS

Approximately 5-10% of the regions involved in the regulation of blood/urine metabolite levels seem to also play a role in BMI and mental traits/disorders and related phenotypes. If validated in metabolomic studies of the respective phenotypes, the associated blood/urine metabolites may enable novel preventive and therapeutic strategies.

Genome-wide meta-analysis of cognitive empathy: heritability, and correlates with sex, neuropsychiatric conditions and cognition

We conducted a genome-wide meta-analysis of cognitive empathy using the 'Reading the Mind in the Eyes' Test (Eyes Test) in 88,056 research volunteers of European Ancestry (44,574 females and 43,482 males) from 23andMe Inc., and an additional 1497 research volunteers of European Ancestry (891 females and 606 males) from the Brisbane Longitudinal Twin Study. We confirmed a female advantage on the Eyes Test (Cohen's d=0.21, P<2.2 × 10^-16), and identified a locus in 3p26.1 that is associated with scores on the Eyes Test in females (rs7641347, P_meta=1.58 × 10^-8). Common single nucleotide polymorphisms explained 5.8% (95% CI: 4.5%-7.2%; P=1.00 × 10^-17) of the total trait variance in both sexes, and we identified a twin heritability of 28% (95% CI: 13%-42%). Finally, we identified significant genetic correlation between the Eyes Test and anorexia nervosa, openness (NEO-Five Factor Inventory), and different measures of educational attainment and cognitive aptitude.

Cntn6 deficiency impairs allocentric navigation in mice

INTRODUCTION

CNTN6 is an immunoglobulin domain-containing cell adhesion molecule that belongs to the contactin family. It is involved in the development of the nervous system. We aim to determine the effect of Cntn6 deficiency on the allocentric navigation in mice.

METHODS

We recorded the travel distance and escape time of wild-type and Cntn6 mutant male and female mice in the Morris water maze task according to the protocol.

RESULTS

There was hardly any Cntn6 expression in the hippocampus of postnatal day 0 (P0) mice, while obvious Cntn6 expression was present in the hippocampal CA1 region of the P7 mice. During the acquisition period of Morris water maze task (Day 1 to 4), Cntn6-/- male mice failed to shorten the escape time to reach platform on the third day, while the travel distance to platform was not significantly different. There was no significant difference in both escape time and travel distance to the platform among all female subjects. In the probe trial test (Day 5), spatial memory of the female mutant mice was mildly affected, while Cntn6-/- male mice were normal. In the spatial relearning test (Day 7 to 10), Cntn6-/- male mice showed no difference in escape time to the platform compared to the wild-type male mice, while Cntn6 deficient female mice required shorter escape time to travel to the platform on day 7, day 8, and day 10.

CONCLUSIONS

Cntn6 is expressed in the developing hippocampus in mice. Cntn6 deficiency affects spatial learning and memory, indicating that Cntn6 plays a role in the development of hippocampus and affects allocentric navigation of the animals.

Genetic identification of brain cell types underlying schizophrenia

With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs) and certain interneurons, but far less consistently to embryonic, progenitor or glial cells. These enrichments were due to sets of genes that were specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (genes involved in synaptic function, those encoding mRNAs that interact with FMRP, antipsychotic targets, etc.) generally implicated the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with MSNs did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.

Cultural Genomics: Promises and Challenges

In this article, we attempt to integrate recent advances in our understanding of the relations between culture and genes into an emerging field—cultural genomics—and discuss its promises and theoretical and methodological challenges. We first provide a brief review of previous conceptualizations about the relations between culture and genes and then argue that recent advances in molecular evolution research has allowed us to reframe the discussion away from parallel genetic and cultural evolution to focus on the interactions between the two. After outlining the key issues involved in cultural genomics (unit of analysis, timescale, mechanisms, and direction of influence), we provide examples of research for the different levels of interactions between culture and genes. We then discuss ideological, theoretical, and methodological challenges in cultural genomics and propose tentative solutions.

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10-8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

Polygenic pleiotropy and potential causal relationships between educational attainment, neurobiological profile, and positive psychotic symptoms

Event-related potential (ERP) components have been used to assess cognitive functions in patients with psychotic illness. Evidence suggests that among patients with psychosis there is a distinct heritable neurophysiologic phenotypic subtype captured by impairments across a range of ERP measures. In this study, we investigated the genetic basis of this "globally impaired" ERP cluster and its relationship to psychosis and cognitive abilities. We applied K-means clustering to six ERP measures to re-derive the globally impaired (n = 60) and the non-globally impaired ERP clusters (n = 323) in a sample of cases with schizophrenia (SCZ = 136) or bipolar disorder (BPD = 121) and healthy controls (n = 126). We used genome-wide association study (GWAS) results for SCZ, BPD, college completion, and childhood intelligence as the discovery datasets to derive polygenic risk scores (PRS) in our study sample and tested their associations with globally impaired ERP. We conducted mediation analyses to estimate the proportion of each PRS effect on severity of psychotic symptoms that is mediated through membership in the globally impaired ERP. Individuals with globally impaired ERP had significantly higher PANSS-positive scores (β = 3.95, P = 0.005). The SCZ-PRS was nominally associated with globally impaired ERP (unadjusted P = 0.01; R² = 3.07%). We also found a significant positive association between the college-PRS and globally impaired ERP (FDR-corrected P = 0.004; R² = 6.15%). The effect of college-PRS on PANSS positivity was almost entirely (97.1%) mediated through globally impaired ERP. These results suggest that the globally impaired ERP phenotype may represent some aspects of brain physiology on the path between genetic influences on educational attainment and psychotic symptoms.

Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences

Genomewide association studies (GWASs) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (odds ratio < 1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWASs can be used to generate polygenic risk scores (PRS) in independent, target data sets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition?). The intuitive appeal and generalizability of PRS have led to their widespread use and new insights into mechanisms of polygenic liability. However, when currently applied across traits they account for small amounts of variance (<3%), are relatively uninformative for clinical treatment, and, in isolation, provide no insight into molecular mechanisms. Larger GWASs are needed to increase the precision of PRS, and novel approaches integrating various data sources (e.g., multitrait analysis of GWASs) may improve the utility of current PRS.

Genome-wide association study for risk taking propensity indicates shared pathways with body mass index

Risk-taking propensity is a trait of significant public health relevance but few specific genetic factors are known. Here we perform a genome-wide association study of self-reported risk-taking propensity among 436,236 white European UK Biobank study participants. We identify genome-wide associations at 26 loci (P < 5 × 10-8), 24 of which are novel, implicating genes enriched in the GABA and GABA receptor pathways. Modelling the relationship between risk-taking propensity and body mass index (BMI) using Mendelian randomisation shows a positive association (0.25 approximate SDs of BMI (SE: 0.06); P = 6.7 × 10-5). The impact of individual SNPs is heterogeneous, indicating a complex relationship arising from multiple shared pathways. We identify positive genetic correlations between risk-taking and waist-hip ratio, childhood obesity, ever smoking, attention-deficit hyperactivity disorder, bipolar disorder and schizophrenia, alongside a negative correlation with women's age at first birth. These findings highlight that behavioural pathways involved in risk-taking propensity may play a role in obesity, smoking and psychiatric disorders.

A genome-wide association study for extremely high intelligence

We used a case-control genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (~170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and significant genome-wide genetic correlations of 0.78 were observed with educational attainment and 0.86 with population IQ. Three variants in locus ADAM12 achieved genome-wide significance, although they did not replicate with published GWA analyses of normal-range IQ or educational attainment. A genome-wide polygenic score constructed from the GWA results accounted for 1.6% of the variance of intelligence in the normal range in an unselected sample of 3414 individuals, which is comparable to the variance explained by GWA studies of intelligence with substantially larger sample sizes. The gene family plexins, members of which are mutated in several monogenic neurodevelopmental disorders, was significantly enriched for associations with high IQ. This study shows the utility of extreme trait selection for genetic study of intelligence and suggests that extremely high intelligence is continuous genetically with normal-range intelligence in the population.

Genetic risk scores and family history as predictors of schizophrenia in Nordic registers

BACKGROUND

Family history is a long-standing and readily obtainable risk factor for schizophrenia (SCZ). Low-cost genotyping technologies have enabled large genetic studies of SCZ, and the results suggest the utility of genetic risk scores (GRS, direct assessments of inherited common variant risk). Few studies have evaluated family history and GRS simultaneously to ask whether one can explain away the other.

METHODS

We studied 5959 SCZ cases and 8717 controls from four Nordic countries. All subjects had family history data from national registers and genome-wide genotypes that were processed through the quality control procedures used by the Psychiatric Genomics Consortium. Using external training data, GRS were estimated for SCZ, bipolar disorder (BIP), major depression, autism, educational attainment, and body mass index. Multivariable modeling was used to estimate effect sizes.

RESULTS

Using harmonized genomic and national register data from Denmark, Estonia, Norway, and Sweden, we confirmed that family history of SCZ and GRS for SCZ and BIP were risk factors for SCZ. In a joint model, the effects of GRS for SCZ and BIP were essentially unchanged, and the effect of family history was attenuated but remained significant. The predictive capacity of a model including GRS and family history neared the minimum for clinical utility.

CONCLUSIONS

Combining national register data with measured genetic risk factors represents an important investigative approach for psychotic disorders. Our findings suggest the potential clinical utility of combining GRS and family history for early prediction and diagnostic improvements.

Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data

We propose genetic instrumental variable (GIV) regression—a method that controls for pleiotropic effects of genes on two variables. GIV regression is broadly applicable to study outcomes for which polygenic scores from large-scale genome-wide association studies are available. We explore the performance of GIV regression in the presence of pleiotropy across a range of scenarios and find that it yields more accurate estimates than alternative approaches such as ordinary least-squares regression or Mendelian randomization. When GIV regression is combined with proper controls for purely environmental sources of bias (e.g., using control variables and sibling fixed effects), it improves our understanding of the causal relationships between genetically correlated variables.

Identifying causal effects in nonexperimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables [i.e., Mendelian randomization (MR)]. However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in nonexperimental data that would also undermine the ability of MR to correct for endogeneity bias from nongenetic sources. Here, we propose an alternative approach, genetic instrumental variable (GIV) regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGSs) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into nonoverlapping subsamples, we obtain multiple indicators of the outcome PGSs that can be used as instruments for each other and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA.

Predicting loneliness with polygenic scores of social, psychological and psychiatric traits

Loneliness is a heritable trait that accompanies multiple disorders. The association between loneliness and mental health indices may partly be due to inherited biological factors. We constructed polygenic scores for 27 traits related to behavior, cognition and mental health and tested their prediction for self-reported loneliness in a population-based sample of 8798 Dutch individuals. Polygenic scores for major depressive disorder (MDD), schizophrenia and bipolar disorder were significantly associated with loneliness. Of the Big Five personality dimensions, polygenic scores for neuroticism and conscientiousness also significantly predicted loneliness, as did the polygenic scores for subjective well-being, tiredness and self-rated health. When including all polygenic scores simultaneously into one model, only 2 major depression polygenic scores remained as significant predictors of loneliness. When controlling only for these 2 MDD polygenic scores, only neuroticism and schizophrenia remain significant. The total variation explained by all polygenic scores collectively was 1.7%. The association between the propensity to feel lonely and the susceptibility to psychiatric disorders thus pointed to a shared genetic etiology. The predictive power of polygenic scores will increase as the power of the genome-wide association studies on which they are based increases and may lead to clinically useful polygenic scores that can inform on the genetic predisposition to loneliness and mental health.

Polygenic risk for schizophrenia and measured domains of cognition in individuals with psychosis and controls

Psychotic disorders including schizophrenia are commonly accompanied by cognitive deficits. Recent studies have reported negative genetic correlations between schizophrenia and indicators of cognitive ability such as general intelligence and processing speed. Here we compare the effect of polygenetic risk for schizophrenia (PRS_SCZ) on measures that differ in their relationships with psychosis onset: a measure of current cognitive abilities (the Brief Assessment of Cognition in Schizophrenia, BACS) that is greatly reduced in psychotic disorder patients, a measure of premorbid intelligence that is minimally affected by psychosis onset (the Wide-Range Achievement Test, WRAT); and educational attainment (EY), which covaries with both BACS and WRAT. Using genome-wide single nucleotide polymorphism (SNP) data from 314 psychotic and 423 healthy research participants in the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) Consortium, we investigated the association of PRS_SCZ with BACS, WRAT, and EY. Among apparently healthy individuals, greater genetic risk for schizophrenia (PRS_SCZ) was significantly associated with lower BACS scores (r = -0.17, p = 6.6 × 10^-4 at P_T = 1 × 10^-4), but not with WRAT or EY. Among individuals with psychosis, PRS_SCZ did not associate with variations in any of these three phenotypes. We further investigated the association between PRS_SCZ and WRAT in more than 4500 healthy subjects from the Philadelphia Neurodevelopmental Cohort. The association was again null (p > 0.3, N = 4511), suggesting that different cognitive phenotypes vary in their etiologic relationship with schizophrenia.

Genetically-Predicted Adult Height and Alzheimer's Disease

BACKGROUND

Observational studies have linked increased adult height with better cognitive performance and reduced risk of Alzheimer's disease (AD). It is unclear whether the associations are due to shared biological processes that influence height and AD or due to confounding by early life exposures or environmental factors.

OBJECTIVE

To use a genetic approach to investigate the association between adult height and AD.

METHODS

We selected 682 single nucleotide polymorphisms (SNPs) associated with height at genome-wide significance (p < 5×10-8) in the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Summary statistics for each of these SNPs on AD were obtained from the International Genomics of Alzheimer's Project (IGAP) of 17,008 individuals with AD and 37,154 controls. The estimate of the association between genetically predicted height and AD was calculated using the inverse-variance weighted method.

RESULTS

The odds ratio of AD was 0.91 (95% confidence interval, 0.86-0.95; p = 9.8×10-5) per one standard deviation increase (about 6.5 cm) in genetically predicted height based on 682 SNPs, which were clustered in 419 loci. In an analysis restricted to one SNP from each height-associated locus (n = 419 SNPs), the corresponding OR was 0.92 (95% confidence interval, 0.86-0.97; p = 4.8×10-3).

CONCLUSIONS

This finding suggests that biological processes that influence adult height may have a role in the etiology of AD.

Genetic influence on social outcomes during and after the Soviet era in Estonia

The etiology of individual differences in educational attainment and occupational status includes genetic as well as environmental factors1-5 and can change as societies change3,6,7. The extent of genetic influence on these social outcomes can be viewed as an index of success in achieving meritocratic values of equality of opportunity by rewarding talent and hard work, which are to a large extent influenced by genetic factors, rather than rewarding environmentally driven privilege. To the extent that the end of the Soviet Union and the independence of Estonia led to an increase in meritocratic selection of individuals in education and occupation, genetic influence should be higher in the post-Soviet era than in the Soviet era. Here we confirmed this hypothesis: DNA differences (single-nucleotide polymorphisms, SNPs) explained twice as much variance in educational attainment and occupational status in the post-Soviet era compared to the Soviet era in both polygenic score analyses and SNP heritability analyses of 12 500 Estonians. This is the first demonstration of a change in the extent of genetic influence in the same population following a massive and abrupt social change - in this case, the shift from a communist to a capitalist society.

Geographic Clustering of Polygenic Scores at Different Stages of the Life Course

We interrogate state-level clustering of polygenic scores at different points in the life course and variation in the association of mean polygenic scores in a respondent's state of birth with corresponding phenotypes. The polygenic scores for height and smoking show the most state-level clustering (2 to 4 percent) with relatively little clustering observed for the other scores. However, even the small amounts of observed clustering are potentially meaningful. The state-mean polygenic score for educational attainment is strongly associated with an individual's educational attainment net of that person's polygenic score. The ecological clustering of polygenic scores may denote a new environmental factor in gene-environment research. We conclude by discussing possible mechanisms that underlie this association and the implications of our findings for social and genetic research.

Detecting Polygenic Adaptation in Admixture Graphs

An open question in human evolution is the importance of polygenic adaptation: adaptive changes in the mean of a multifactorial trait due to shifts in allele frequencies across many loci. In recent years, several methods have been developed to detect polygenic adaptation using loci identified in genome-wide association studies (GWAS). Though powerful, these methods suffer from limited interpretability: they can detect which sets of populations have evidence for polygenic adaptation, but are unable to reveal where in the history of multiple populations these processes occurred. To address this, we created a method to detect polygenic adaptation in an admixture graph, which is a representation of the historical divergences and admixture events relating different populations through time. We developed a Markov chain Monte Carlo (MCMC) algorithm to infer branch-specific parameters reflecting the strength of selection in each branch of a graph. Additionally, we developed a set of summary statistics that are fast to compute and can indicate which branches are most likely to have experienced polygenic adaptation. We show via simulations that this method-which we call PolyGraph-has good power to detect polygenic adaptation, and applied it to human population genomic data from around the world. We also provide evidence that variants associated with several traits, including height, educational attainment, and self-reported unibrow, have been influenced by polygenic adaptation in different populations during human evolution.