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

Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations

The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations

The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

Gene-obesogenic environment interactions in the UK Biobank study

Background

Previous studies have suggested that modern obesogenic environments accentuate the genetic risk of obesity. However, these studies have proven controversial as to which, if any, measures of the environment accentuate genetic susceptibility to high body mass index (BMI).

Methods

We used up to 120 000 adults from the UK Biobank study to test the hypothesis that high-risk obesogenic environments and behaviours accentuate genetic susceptibility to obesity. We used BMI as the outcome and a 69-variant genetic risk score (GRS) for obesity and 12 measures of the obesogenic environment as exposures. These measures included Townsend deprivation index (TDI) as a measure of socio-economic position, TV watching, a 'Westernized' diet and physical activity. We performed several negative control tests, including randomly selecting groups of different average BMIs, using a simulated environment and including sun-protection use as an environment.

Results

We found gene-environment interactions with TDI (Pinteraction = 3 × 10 -10 ), self-reported TV watching (Pinteraction = 7 × 10 -5 ) and self-reported physical activity (Pinteraction = 5 × 10 -6 ). Within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73 m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. The interactions were weaker, but present, with the negative controls, including sun-protection use, indicating that residual confounding is likely.

Conclusions

Our findings suggest that the obesogenic environment accentuates the risk of obesity in genetically susceptible adults. Of the factors we tested, relative social deprivation best captures the aspects of the obesogenic environment responsible.

Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits

Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10^-8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

Microsatellite polymorphisms associated with human behavioural and psychological phenotypes including a gene-environment interaction

Background

The genetic and environmental influences on human personality and behaviour are a complex matter of ongoing debate. Accumulating evidence indicates that short tandem repeats (STRs) in regulatory regions are good candidates to explain heritability not accessed by genome-wide association studies.

Methods

We tested for associations between the genotypes of four selected repeats and 18 traits relating to personality, behaviour, cognitive ability and mental health in a well-studied longitudinal birth cohort (n = 458-589) using one way analysis of variance. The repeats were a highly conserved poly-AC microsatellite in the upstream promoter region of the T-box brain 1 (TBR1) gene and three previously studied STRs in the activating enhancer-binding protein 2-beta (AP2-β) and androgen receptor (AR) genes. Where significance was found we used multiple regression to assess the influence of confounding factors.

Results

Carriers of the shorter, most common, allele of the AR gene’s GGN microsatellite polymorphism had fewer anxiety-related symptoms, which was consistent with previous studies, but in our study this was not significant following Bonferroni correction. No associations with two repeats in the AP2-β gene withstood this correction. A novel finding was that carriers of the minor allele of the TBR1 AC microsatellite were at higher risk of conduct problems in childhood at age 7-9 (p = 0.0007, which did pass Bonferroni correction). Including maternal smoking during pregnancy (MSDP) in models controlling for potentially confounding influences showed that an interaction between TBR1 genotype and MSDP was a significant predictor of conduct problems in childhood and adolescence (p < 0.001), and of self-reported criminal behaviour up to age 25 years (p ≤ 0.02). This interaction remained significant after controlling for possible confounders including maternal age at birth, socio-economic status and education, and offspring birth weight.

Conclusions

The potential functional importance of the TBR1 gene’s promoter microsatellite deserves further investigation. Our results suggest that it participates in a gene-environment interaction with MDSP and antisocial behaviour. However, previous evidence that mothers who smoke during pregnancy carry genes for antisocial behaviour suggests that epistasis may influence the interaction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-017-0374-y) contains supplementary material, which is available to authorized users.

Genetics and educational attainment

We explore how advances in our understanding of the genetics of complex traits such as educational attainment could constructively be leveraged to advance research on education and learning. We discuss concepts and misconceptions about genetic findings with regard to causes, consequences, and policy. Our main thesis is that educational attainment as a measure that varies between individuals in a population can be subject to exactly the same experimental biological designs as other outcomes, for example, those studied in epidemiology and medical sciences, and the same caveats about interpretation and implication apply.

Cognitive genomics: Linking genes to behavior in the human brain

Correlations of genetic variation in DNA with functional brain activity have already provided a starting point for delving into human cognitive mechanisms. However, these analyses do not provide the specific genes driving the associations, which are complicated by intergenic localization as well as tissue-specific epigenetics and expression. The use of brain-derived expression datasets could build upon the foundation of these initial genetic insights and yield genes and molecular pathways for testing new hypotheses regarding the molecular bases of human brain development, cognition, and disease. Thus, coupling these human brain gene expression data with measurements of brain activity may provide genes with critical roles in brain function. However, these brain gene expression datasets have their own set of caveats, most notably a reliance on postmortem tissue. In this perspective, I summarize and examine the progress that has been made in this realm to date, and discuss the various frontiers remaining, such as the inclusion of cell-type-specific information, additional physiological measurements, and genomic data from patient cohorts.

Osteoarthritis year in review 2016: genetics, genomics and epigenetics

The purpose of this narrative review is to provide an overview of last year's publications in the field of genetics, genomics and epigenetics in the osteoarthritis (OA) field. Major themes arising from a Pubmed search on (epi)genetics in OA were identified. In addition, general developments in the fast evolving field of (epi)genetics are reviewed and relevance for the OA field is summarized. In the last 5 years, a number of genome-wide association studies have identified a modest number of genetic loci associated to OA. Continued functional research into these DNA variants is showing putative biological mechanisms underlying these associations. Over the last year, no additional large genome-wide association studies were published, but there clearly remains much to be discovered in the OA genetic field. A lot of research has been done into the epigenetics of OA over the last year. Several genome-wide screens examining the methylome of osteoarthritic cartilage were done. Pathway analysis confirmed deregulation of developmental and extracellular pathways in OA cartilage. Over the last year many microRNAs (miRNAs) have been identified that potentially play important roles in cartilage homeostasis and/or OA process. Continued research will learn whether these identified miRNAs are truly causal and can be used in clinical applications. Many of the epigenetic findings need further confirmation, but they highlight potential novel pathways involved in cartilage biology and OA.

Predicting educational achievement from DNA

A genome-wide polygenic score (GPS), derived from a 2013 genome-wide association study (N=127,000), explained 2% of the variance in total years of education (EduYears). In a follow-up study (N=329,000), a new EduYears GPS explains up to 4%. Here, we tested the association between this latest EduYears GPS and educational achievement scores at ages 7, 12 and 16 in an independent sample of 5825 UK individuals. We found that EduYears GPS explained greater amounts of variance in educational achievement over time, up to 9% at age 16, accounting for 15% of the heritable variance. This is the strongest GPS prediction to date for quantitative behavioral traits. Individuals in the highest and lowest GPS septiles differed by a whole school grade at age 16. Furthermore, EduYears GPS was associated with general cognitive ability (~3.5%) and family socioeconomic status (~7%). There was no evidence of an interaction between EduYears GPS and family socioeconomic status on educational achievement or on general cognitive ability. These results are a harbinger of future widespread use of GPS to predict genetic risk and resilience in the social and behavioral sciences.

Fine mapping genetic associations between the HLA region and extremely high intelligence

General cognitive ability (intelligence) is one of the most heritable behavioural traits and most predictive of socially important outcomes and health. We hypothesized that some of the missing heritability of IQ might lie hidden in the human leukocyte antigen (HLA) region, which plays a critical role in many diseases and traits but is not well tagged in conventional GWAS. Using a uniquely powered design, we investigated whether fine-mapping of the HLA region could narrow the missing heritability gap. Our case-control design included 1,393 cases with extremely high intelligence scores (top 0.0003 of the population equivalent to IQ > 147) and 3,253 unselected population controls. We imputed variants in 200 genes across the HLA region, one SNP (rs444921) reached our criterion for study-wide significance. SNP-based heritability of the HLA variants was small and not significant (h2 = 0.3%, SE = 0.2%). A polygenic score from the case-control genetic association analysis of SNPs in the HLA region did not significantly predict individual differences in intelligence in an independent unselected sample. We conclude that although genetic variation in the HLA region is important to the aetiology of many disorders, it does not appear to be hiding much of the missing heritability of intelligence.

Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies

Large-scale genome-wide association results are typically obtained from a fixed-effects meta-analysis of GWAS summary statistics from multiple studies spanning different regions and/or time periods. This approach averages the estimated effects of genetic variants across studies. In case genetic effects are heterogeneous across studies, the statistical power of a GWAS and the predictive accuracy of polygenic scores are attenuated, contributing to the so-called ‘missing heritability’. Here, we describe the online Meta-GWAS Accuracy and Power (MetaGAP) calculator (available at www.devlaming.eu) which quantifies this attenuation based on a novel multi-study framework. By means of simulation studies, we show that under a wide range of genetic architectures, the statistical power and predictive accuracy provided by this calculator are accurate. We compare the predictions from the MetaGAP calculator with actual results obtained in the GWAS literature. Specifically, we use genomic-relatedness-matrix restricted maximum likelihood to estimate the SNP heritability and cross-study genetic correlation of height, BMI, years of education, and self-rated health in three large samples. These estimates are used as input parameters for the MetaGAP calculator. Results from the calculator suggest that cross-study heterogeneity has led to attenuation of statistical power and predictive accuracy in recent large-scale GWAS efforts on these traits (e.g., for years of education, we estimate a relative loss of 51–62% in the number of genome-wide significant loci and a relative loss in polygenic score R² of 36–38%). Hence, cross-study heterogeneity contributes to the missing heritability.

Large-scale genome-wide association studies are uncovering the genetic architecture of traits which are affected by many genetic variants. In such efforts, one typically meta-analyzes association results from multiple studies spanning different regions and/or time periods. Results from such efforts do not yet capture a large share of the heritability. The origins of this so-called ‘missing heritability’ have been strongly debated. One factor exacerbating the missing heritability is heterogeneity in the effects of genetic variants across studies. The effect of this type of heterogeneity on statistical power to detect associated genetic variants and the accuracy of polygenic predictions is poorly understood. In the current study, we derive the precise effects of heterogeneity in genetic effects across studies on both the statistical power to detect associated genetic variants as well as the accuracy of polygenic predictions. We present an online calculator, available at www.devlaming.eu, which accounts for these effects. By means of this calculator, we show that imperfect genetic correlations between studies substantially decrease statistical power and predictive accuracy and, thereby, contribute to the missing heritability. The MetaGAP calculator helps researchers to gauge how sensitive their results will be to heterogeneity in genetic effects across studies. If strong heterogeneity is expected, random-effects meta-analysis methods should be used instead of fixed-effects methods.

Selection against variants in the genome associated with educational attainment

Epidemiological and genetic association studies show that genetics play an important role in the attainment of education. Here, we investigate the effect of this genetic component on the reproductive history of 109,120 Icelanders and the consequent impact on the gene pool over time. We show that an educational attainment polygenic score, POLY_EDU, constructed from results of a recent study is associated with delayed reproduction (P < 10^-100) and fewer children overall. The effect is stronger for women and remains highly significant after adjusting for educational attainment. Based on 129,808 Icelanders born between 1910 and 1990, we find that the average POLY_EDU has been declining at a rate of ∼0.010 standard units per decade, which is substantial on an evolutionary timescale. Most importantly, because POLY_EDU only captures a fraction of the overall underlying genetic component the latter could be declining at a rate that is two to three times faster.

A current view on contactin-4, -5, and -6: Implications in neurodevelopmental disorders

Contactins (Cntns) are a six-member subgroup of the immunoglobulin cell adhesion molecule superfamily (IgCAMs) with pronounced brain expression and function. Recent genetic studies of neuropsychiatric disorders have pinpointed contactin-4 (CNTN4), contactin-5 (CNTN5) and contactin-6 (CNTN6) as candidate genes in neurodevelopmental disorders, particularly in autism spectrum disorders (ASDs), but also in intellectual disability, schizophrenia (SCZ), attention-deficit hyperactivity disorder (ADHD), bipolar disorder (BD), alcohol use disorder (AUD) and anorexia nervosa (AN). This suggests that they have important functions during neurodevelopment. This suggestion is supported by data showing that neurite outgrowth, cell survival and neural circuit formation can be affected by disruption of these genes. Here, we review the current genetic data about their involvement in neuropsychiatric disorders and explore studies on how null mutations affect mouse behavior. Finally, we highlight to role of protein-protein interactions in the potential mechanism of action of Cntn4, -5 and -6 and emphasize that complexes with other membrane proteins may play a role in neuronal developmental functions.

A method for integrating neuroimaging into genetic models of learning performance

Specific learning disorders (SLD) are an archetypal example of how clinical neuropsychological (NP) traits can differ from underlying genetic and neurobiological risk factors. Disparate environmental influences and pathologies impact learning performance assessed through cognitive examinations and clinical evaluations, the primary diagnostic tools for SLD. We propose a neurobiological risk for SLD with neuroimaging biomarkers, which is integrated into a genome-wide association study (GWAS) of learning performance in a cohort of 479 European individuals between 8 and 21 years of age. We first identified six regions of interest (ROIs) in temporal and anterior cingulate regions where the group diagnosed with learning disability has the least overall variation, relative to the other group, in thickness, area, and volume measurements. Although we used the three imaging measures, the thickness was the leading contributor. Hence, we calculated the Euclidean distances between any two individuals based on their thickness measures in the six ROIs. Then, we defined the relative similarity of one individual according to the averaged ranking of pairwise distances from the individuals to those in the SLD group. The inverse of this relative similarity is called the neurobiological risk for the individual. Single nucleotide polymorphisms in the AGBL1 gene on chromosome 15 had a significant association with learning performance at a genome-wide level. This finding was supported in an independent cohort of 2,327 individuals of the same demographic profile. Our statistical approach for integrating genetic and neuroimaging biomarkers can be extended into studying the biological basis of other NP traits.

Endophenotype best practices

This review examines the current state of electrophysiological endophenotype research and recommends best practices that are based on knowledge gleaned from the last decade of molecular genetic research with complex traits. Endophenotype research is being oversold for its potential to help discover psychopathology relevant genes using the types of small samples feasible for electrophysiological research. This is largely because the genetic architecture of endophenotypes appears to be very much like that of behavioral traits and disorders: they are complex, influenced by many variants (e.g., tens of thousands) within many genes, each contributing a very small effect. Out of over 40 electrophysiological endophenotypes covered by our review, only resting heart, a measure that has received scant advocacy as an endophenotype, emerges as an electrophysiological variable with verified associations with molecular genetic variants. To move the field forward, investigations designed to discover novel variants associated with endophenotypes will need extremely large samples best obtained by forming consortia and sharing data obtained from genome wide arrays. In addition, endophenotype research can benefit from successful molecular genetic studies of psychopathology by examining the degree to which these verified psychopathology-relevant variants are also associated with an endophenotype, and by using knowledge about the functional significance of these variants to generate new endophenotypes. Even without molecular genetic associations, endophenotypes still have value in studying the development of disorders in unaffected individuals at high genetic risk, constructing animal models, and gaining insight into neural mechanisms that are relevant to clinical disorder.

Age is no barrier: predictors of academic success in older learners

Although predictors of academic success have been identified in young adults, such predictors are unlikely to translate directly to an older student population, where such information is scarce. The current study aimed to examine cognitive, psychosocial, lifetime, and genetic predictors of university-level academic performance in older adults (50-79 years old). Participants were mostly female (71%) and had a greater than high school education level (M = 14.06 years, SD = 2.76), on average. Two multiple linear regression analyses were conducted. The first examined all potential predictors of grade point average (GPA) in the subset of participants who had volunteered samples for genetic analysis (N = 181). Significant predictors of GPA were then re-examined in a second multiple linear regression using the full sample (N = 329). Our data show that the cognitive domains of episodic memory and language processing, in conjunction with midlife engagement in cognitively stimulating activities, have a role in predicting academic performance as measured by GPA in the first year of study. In contrast, it was determined that age, IQ, gender, working memory, psychosocial factors, and common brain gene polymorphisms linked to brain function, plasticity and degeneration (APOE, BDNF, COMT, KIBRA, SERT) did not influence academic performance. These findings demonstrate that ageing does not impede academic achievement, and that discrete cognitive skills as well as lifetime engagement in cognitively stimulating activities can promote academic success in older adults.

Genome-wide analysis identifies 12 loci influencing human reproductive behavior

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

'Mr Cummings clearly does not understand the science of genetics and should maybe go back to school on the subject': an exploratory content analysis of the online comments beneath a controversial news story

An article published in the UK Guardian on 11/10/2013 with the headline 'Genetics outweighs teaching, Gove advisor tells his boss' reported a leaked document written by special advisor Dominic Cummings to the then UK Secretary of State for Education, Michael Gove. The article generated 3008 on-line reader comments from the public. These reader comments offer a naturalistic opportunity to understand public opinion regarding Cummings' controversial suggestions and ideas. We conducted a content analysis of n = 800 reader comments, coding them on the basis of level of agreement with the ideas and opinions expressed in the article. Of all aspects of education mentioned, Cummings' reported views on genetics were commented upon most frequently and were subject to the most opposition from commenters, but also the most support. Findings offer some insight into the challenges involved in conducting public discourse about the relevance of genes in education. We discuss the accuracy with which Cummings' views were presented and the effect this may have had on reader responses to the points being raised.

Genes, behavior, and behavior genetics

According to the 'first law' of behavior genetics, 'All human behavioral traits are heritable.' Accepting the validity of this first law and employing statistical methods, researchers within psychology, sociology, political science, economics, and business claim to have demonstrated that all the behaviors studied by their disciplines are heritable-no matter how culturally specific these behaviors appear to be. Further, in many cases they claim to have identified specific genes that play a role in those behaviors. The validity of behavior genetics as a discipline depends upon the validity of the research methods used to justify such claims. It also depends, foundationally, upon certain key assumptions concerning the relationship between genotype (one's specific DNA sequences) and phenotype (any and all observable traits or characteristics). In this article, I examine-and find serious flaws with-both the methodologies of behavior genetics and the underlying assumptions concerning the genotype-phenotype relationship. WIREs Cogn Sci 2017, 8:e1405. doi: 10.1002/wcs.1405 For further resources related to this article, please visit the WIREs website.

A current snapshot of common genomic variants contribution in psychiatric disorders

In the past decade, numerous advances were achieved in psychiatric genetics. Particularly, the genome wide association studies (GWAS) have contributed to uncovering new genes and pathways associated to psychiatric disorders (PDs). At the same time, with increasing sample sizes in the GWAS, the polygenic risk score (PRS) promoted an additional tool for identification and evaluation the genetic risk quantitatively in PDs. This concept review presents the state of the art GWAS analysis and PRS focusing on the genetic underpinnings of PDs. © 2016 Wiley Periodicals, Inc.

Molecular genetic aetiology of general cognitive function is enriched in evolutionarily conserved regions

Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions.

Ultra-rare disruptive and damaging mutations influence educational attainment in the general population

Disruptive, damaging ultra-rare variants in highly constrained genes are enriched in individuals with neurodevelopmental disorders. In the general population, this class of variants was associated with a decrease in years of education (YOE). This effect was stronger among highly brain-expressed genes and explained more YOE variance than pathogenic copy number variation but less than common variants. Disruptive, damaging ultra-rare variants in highly constrained genes influence the determinants of YOE in the general population.

Genetic variants linked to education predict longevity

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.

Genetic characterization of physical activity behaviours in university students enrolled in kinesiology degree programs

Studies of physical activity behaviours have increasingly shown the importance of heritable factors such as genetic variation. Nonsynonymous polymorphisms of alpha-actinin 3 (ACTN3) and the β-adrenergic receptors 1 and 3 (ADRB1 and ADRB3) have been previously associated with exercise capacity and cardiometabolic health. We thus hypothesized that these polymorphisms are also related to physical activity behaviours in young adults. To test this hypothesis we examined relationships between ACTN3 (R577X), ARDB1 (Arg389Gly), ADRB3 (Trp64Arg), and physical activity behaviours in university students. We stratified for student enrollment in kinesiology degree programs compared with nonmajors as we previously found this to be a predictor of physical activity. We did not identify novel associations between physical activity and ACTN3. However, the minor alleles of ADRB1 and ADRB3 were significantly underrepresented in kinesiology students compared with nonmajors. Furthermore, carriers of the ADRB1 minor allele reported reduced participation in moderate physical activity and increased afternoon fatigue compared with ancestral allele homozygotes. Together, these findings suggest that the heritability of physical activity behaviours in young adults may be linked to nonsynonymous polymorphisms within β-adrenergic receptors.

A sequence variant associating with educational attainment also affects childhood cognition

Only a few common variants in the sequence of the genome have been shown to impact cognitive traits. Here we demonstrate that polygenic scores of educational attainment predict specific aspects of childhood cognition, as measured with IQ. Recently, three sequence variants were shown to associate with educational attainment, a confluence phenotype of genetic and environmental factors contributing to academic success. We show that one of these variants associating with educational attainment, rs4851266-T, also associates with Verbal IQ in dyslexic children (P = 4.3 × 10⁻⁴, β = 0.16 s.d.). The effect of 0.16 s.d. corresponds to 1.4 IQ points for heterozygotes and 2.8 IQ points for homozygotes. We verified this association in independent samples consisting of adults (P = 8.3 × 10⁻⁵, β = 0.12 s.d., combined P = 2.2 x 10⁻⁷, β = 0.14 s.d.). Childhood cognition is unlikely to be affected by education attained later in life, and the variant explains a greater fraction of the variance in verbal IQ than in educational attainment (0.7% vs 0.12%,. P = 1.0 × 10⁻⁵).

Molecular Genetic Contributions to Social Deprivation and Household Income in UK Biobank

Individuals with lower socio-economic status (SES) are at increased risk of physical and mental illnesses and tend to die at an earlier age [1, 2, 3]. Explanations for the association between SES and health typically focus on factors that are environmental in origin [4]. However, common SNPs have been found collectively to explain around 18% of the phenotypic variance of an area-based social deprivation measure of SES [5]. Molecular genetic studies have also shown that common physical and psychiatric diseases are partly heritable [6]. It is possible that phenotypic associations between SES and health arise partly due to a shared genetic etiology. We conducted a genome-wide association study (GWAS) on social deprivation and on household income using 112,151 participants of UK Biobank. We find that common SNPs explain 21% of the variation in social deprivation and 11% of household income. Two independent loci attained genome-wide significance for household income, with the most significant SNP in each of these loci being rs187848990 on chromosome 2 and rs8100891 on chromosome 19. Genes in the regions of these SNPs have been associated with intellectual disabilities, schizophrenia, and synaptic plasticity. Extensive genetic correlations were found between both measures of SES and illnesses, anthropometric variables, psychiatric disorders, and cognitive ability. These findings suggest that some SNPs associated with SES are involved in the brain and central nervous system. The genetic associations with SES obviously do not reflect direct causal effects and are probably mediated via other partly heritable variables, including cognitive ability, personality, and health.

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Common SNPs explain 21% of social deprivation and 11% of household income

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Two loci attained genome-wide significance for household income

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Genes in these loci have been linked to synaptic plasticity

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Genetic correlations were found between both measures of SES and many other traits

Maternal and Birth Characteristics and Childhood Embryonal Solid Tumors: A Population-Based Report from Brazil

BACKGROUND

Several maternal and birth characteristics have been reported to be associated with an increased risk of many childhood cancers. Our goal was to evaluate the risk of childhood embryonal solid tumors in relation to pre- and perinatal characteristics.

METHODS

A case-cohort study was performed using two population-based datasets, which were linked through R software. Tumors were classified as central nervous system (CNS) or non-CNS-embryonal (retinoblastoma, neuroblastoma, renal tumors, germ cell tumors, hepatoblastoma and soft tissue sarcoma). Children aged <6 years were selected. Adjustments were made for potential confounders. Odds ratios (OR) with 95% confidence intervals (CI) were computed by unconditional logistic regression analysis using SPSS.

RESULTS

Males, high maternal education level, and birth anomalies were independent risk factors. Among children diagnosed older than 24 months of age, cesarean section (CS) was a significant risk factor. Five-minute Apgar ≤8 was an independent risk factor for renal tumors. A decreasing risk with increasing birth order was observed for all tumor types except for retinoblastoma. Among children with neuroblastoma, the risk decreased with increasing birth order (OR = 0.82 (95% CI 0.67-1.01)). Children delivered by CS had a marginally significantly increased OR for all tumors except retinoblastoma. High maternal education level showed a significant increase in the odds for all tumors together, CNS tumors, and neuroblastoma.

CONCLUSION

This evidence suggests that male gender, high maternal education level, and birth anomalies are risk factors for childhood tumors irrespective of the age at diagnosis. Cesarean section, birth order, and 5-minute Apgar score were risk factors for some tumor subtypes.

How Cognitive Genetic Factors Influence Fertility Outcomes: A Mediational SEM Analysis

Utilizing a newly released cognitive Polygenic Score (PGS) from Wave IV of Add Health (n = 1,886), structural equation models (SEMs) examining the relationship between PGS and fertility (which is approximately 50% complete in the present sample), employing measures of verbal IQ and educational attainment as potential mediators, were estimated. The results of indirect pathway models revealed that verbal IQ mediates the positive relationship between PGS and educational attainment, and educational attainment in turn mediates the negative relationship between verbal IQ and a latent fertility measure. The direct path from PGS to fertility was non-significant. The model was robust to controlling for age, sex, and race; furthermore, the results of a multigroup SEM revealed no significant differences in the estimated path coeficients across sex. These results indicate that those predisposed towards higher verbal IQ by virtue of higher PGS values are also predisposed towards trading fertility against time spent in education, which contributes to those with higher PGS values producing fewer offspring at this stage in their life course.

Gene set analysis for interpreting genetic studies

Interpretation of genome-wide association study (GWAS) results is lacking behind the discovery of new genetic associations. Consequently, there is an urgent need for data-driven methods for interpreting genetic association studies. Gene set analysis (GSA) can identify aetiologic pathways and functional annotations and may hence point towards novel biological insights. However, despite the growing availability of GSA tools, the sizeable amount of variants identified for a vast number of complex traits, and many irrefutably trait-associated gene sets, the gap between discovery and interpretation remains. More efficient interpretation requires more complete and consistent gene set representations of biological pathways, phenotypes and functional annotations. In this review, I examine different types of gene sets, discuss how inconsistencies in gene set definitions impact GSA, describe how GSA has helped to elucidate biology and outline potential future directions.

Gender and genetic contributions to weight identity among adolescents and young adults in the U.S

In this paper, we investigate the possibility that genetic variation contributes to self-perceived weight status among adolescents and young adults in the U.S. Using samples of identical and fraternal twins across four waves of the National Longitudinal Study of Adolescent to Adult Health (Add Health) study, we calculate heritability estimates for objective body mass index (BMI) that are in line with previous estimates. We also show that perceived weight status is heritable (h(2) ∼ 0.47) and most importantly that this trait continues to be heritable above and beyond objective BMI (h(2) ∼ 0.25). We then demonstrate significant sex differences in the heritability of weight identity across the four waves of the study, where h(2)women = 0.39, 0.35, 0.40, and 0.50 for each wave, respectively, and h(2)men = 0.10, 0.10, 0.23, and 0.03. These results call for a deeper consideration of both identity and gender in genetics research.

Mendelian randomization in (epi)genetic epidemiology: an effective tool to be handled with care

A study examining blood lipid traits takes epigenomics approaches to the next level by using carefully performed Mendelian randomization to assess causality rather than simply reporting associations.

See related research article: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1000-6

Genetic evidence for natural selection in humans in the contemporary United States

Recent findings from molecular genetics now make it possible to test directly for natural selection by analyzing whether genetic variants associated with various phenotypes have been under selection. I leverage these findings to construct polygenic scores that use individuals' genotypes to predict their body mass index, educational attainment (EA), glucose concentration, height, schizophrenia, total cholesterol, and (in females) age at menarche. I then examine associations between these scores and fitness to test whether natural selection has been occurring. My study sample includes individuals of European ancestry born between 1931 and 1953 who participated in the Health and Retirement Study, a representative study of the US population. My results imply that natural selection has been slowly favoring lower EA in both females and males, and are suggestive that natural selection may have favored a higher age at menarche in females. For EA, my estimates imply a rate of selection of about -1.5 mo of education per generation (which pales in comparison with the increases in EA observed in contemporary times). Although they cannot be projected over more than one generation, my results provide additional evidence that humans are still evolving-albeit slowly, especially compared with the rapid changes that have occurred over the past few generations due to cultural and environmental factors.

Detection and interpretation of shared genetic influences on 42 human traits

We performed a scan for genetic variants associated with multiple phenotypes by comparing large genome-wide association studies (GWAS) of 42 traits or diseases. We identified 341 loci (at a false discovery rate of 10%) associated with multiple traits. Several loci are associated with multiple phenotypes; for example, a nonsynonymous variant in the zinc transporter SLC39A8 influences seven of the traits, including risk of schizophrenia (rs13107325: log-transformed odds ratio (log OR) = 0.15, P = 2 × 10(-12)) and Parkinson disease (log OR = -0.15, P = 1.6 × 10(-7)), among others. Second, we used these loci to identify traits that have multiple genetic causes in common. For example, variants associated with increased risk of schizophrenia also tended to be associated with increased risk of inflammatory bowel disease. Finally, we developed a method to identify pairs of traits that show evidence of a causal relationship. For example, we show evidence that increased body mass index causally increases triglyceride levels.

Education and alcohol use: A study of gene-environment interaction in young adulthood

The consequences of heavy alcohol use remain a serious public health problem. Consistent evidence has demonstrated that both genetic and social influences contribute to alcohol use. Research on gene-environment interaction (GxE) has also demonstrated that these social and genetic influences do not act independently. Instead, certain environmental contexts may limit or exacerbate an underlying genetic predisposition. However, much of the work on GxE and alcohol use has focused on adolescence and less is known about the important environmental contexts in young adulthood. Using data from the young adult wave of the Finnish Twin Study, FinnTwin12 (N = 3402), we used biometric twin modeling to test whether education moderated genetic risk for alcohol use as assessed by drinking frequency and intoxication frequency. Education is important because it offers greater access to personal resources and helps determine one's position in the broader stratification system. Results from the twin models show that education did not moderate genetic variance components and that genetic risk was constant across levels of education. Instead, education moderated environmental variance so that under conditions of low education, environmental influences explained more of the variation in alcohol use outcomes. The implications and limitations of these results are discussed.

Genetics affects choice of academic subjects as well as achievement

We have previously shown that individual differences in educational achievement are highly heritable throughout compulsory education. After completing compulsory education at age 16, students in England can choose to continue to study for two years (A-levels) in preparation for applying to university and they can freely choose which subjects to study. Here, for the first time, we show that choosing to do A-levels and the choice of subjects show substantial genetic influence, as does performance after two years studying the chosen subjects. Using a UK-representative sample of 6584 twin pairs, heritability estimates were 44% for choosing to do A-levels and 52-80% for choice of subject. Achievement after two years was also highly heritable (35-76%). The findings that DNA differences substantially affect differences in appetites as well as aptitudes suggest a genetic way of thinking about education in which individuals actively create their own educational experiences in part based on their genetic propensities.