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

The Biosocial Approach to Human Development, Behavior, and Health Across the Life Course

Social and biological phenomena are widely recognized as determinants of human development, health, and socioeconomic attainments across the life course, but our understanding of the underlying pathways and processes remains limited. To address this gap, we define the "biosocial approach" as one that conceptualizes the biological and social as mutually constituting, and that draws on models and methods from the biomedical and social/behavioral sciences. By bringing biology into the social sciences, we can illuminate mechanisms through which socioeconomic, psychosocial, and other contextual factors shape human development and health. Human biology is a social biology, and biological measures can therefore identify aspects of social contexts that are harmful, as well as beneficial, with respect to well-being. By bringing social science concepts and study designs to biology and biomedicine, we encourage an epistemological shift that foregrounds social/contextual factors as important determinants of human biology and health. The biosocial approach also underscores the importance of the life course, as assessments of both biological and social features throughout human development over time, and across generations, are needed to achieve a full understanding of social and physical well-being. We conclude with a brief review of the papers in the volume, which showcase the value of a biosocial approach to understanding the pathways linking social stratification, biology, and health across the life course.

The Gene Encoding Protocadherin 9 (PCDH9), a Novel Risk Factor for Major Depressive Disorder

Genomic analyses have identified only a handful of robust risk loci for major depressive disorder (MDD). In addition to the published genome-wide significant genes, it is believed that there are undiscovered 'treasures' underlying the current MDD genome-wide association studies (GWASs) and gene expression data sets, and digging into these data will allow better understanding of the illness and development of new therapeutic approaches. For this purpose, we performed a meta-analytic study combining three MDD GWAS data sets (23andMe, CONVERGE, and PGC), and then conducted independent replications of significant loci in two additional samples. The genome-wide significant variants then underwent explorative analyses on MDD-related phenotypes, cognitive function alterations, and gene expression in brains. In the discovery meta-analysis, a previously unidentified single-nucleotide polymorphism (SNP) rs9540720 in the PCDH9 gene was genome-wide significantly associated with MDD (p=1.69 × 10^-8 in a total of 89 610 cases and 246 603 controls), and the association was further strengthened when additional replication samples were included (p=1.20 × 10^-8 in a total of 136 115 cases and 355 275 controls). The risk SNP was also associated with multiple MDD-related phenotypes and cognitive function impairment in diverse samples. Intriguingly, the risk allele of rs9540720 predicted lower PCDH9 expression, consistent with the diagnostic analysis results that PCDH9 mRNA expression levels in the brain and peripheral blood tissues were reduced in MDD patients compared with healthy controls. These convergent lines of evidence suggest that PCDH9 is likely a novel risk gene for MDD. Our study highlights the necessity and importance of excavating the public data sets to explore risk genes for MDD, and this approach is also applicable to other complex diseases.

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals.

Maternal iron status during pregnancy and respiratory and atopic outcomes in the offspring: a Mendelian randomisation study

Introduction

Limited evidence from birth cohort studies suggests that lower prenatal iron status may be a risk factor for childhood respiratory and atopic outcomes, but these observational findings may be confounded. Mendelian randomisation (MR) can potentially provide unconfounded estimates of causal effects by using common genetic variants as instrumental variables. We aimed to study the relationship between prenatal iron status and respiratory and atopic outcomes in the offspring using MR.

Methods

In the Avon Longitudinal Study of Parents and Children birth cohort, we constructed four maternal genotypic risk scores by summing the total number of risk alleles (associated with lower iron status) across single nucleotide polymorphisms known to be associated with at least one of four iron biomarkers (serum iron, ferritin, transferrin and transferrin saturation). We used MR to study their associations with respiratory and atopic outcomes in children aged 7-9 years (n=6002).

Results

When analyses were restricted to mothers without iron supplementation during late pregnancy, negative associations were found between the maternal transferrin saturation score and childhood forced expiratory volume in 1 s and forced vital capacity (difference in age, height and gender-adjusted SD units per SD increase in genotypic score: -0.05 (-0.09, -0.01) p=0.03, and -0.04 (-0.08, 0.00) p=0.04, respectively).

Conclusion

Using MR we have found weak evidence suggesting that low maternal iron status during pregnancy may cause impaired childhood lung function.

Collective effects of common single nucleotide polymorphisms and genetic risk prediction in type 1 diabetes

Type 1 diabetes (T1D) is a common autoimmune disease and may be related to multiple genetic and environmental risk factors. Previous genetic studies have focused on looking for individual polymorphic risk variants. Here, we studied the overall levels of genetic diversity in T1D patients by making use of a previously published study including 1865 cases and 2828 reference samples with genotyping data for 500 K common single nucleotide polymorphisms (SNPs). We determined the minor allele (MA) status of each SNP in the reference samples and calculated the total number of MAs or minor allele contents (MAC) of each individual. We found the average MAC of cases to be greater than that of the reference samples. By focusing on MAs with strong linkage to cases, we further identified a set of 112 SNPs that could predict 19.19% of cases. These results suggest that overall genetic variation over a threshold level may be a risk factor in T1D and provide a new genetic method for predicting the disorder.

Differences in exam performance between pupils attending selective and non-selective schools mirror the genetic differences between them

On average, students attending selective schools outperform their non-selective counterparts in national exams. These differences are often attributed to value added by the school, as well as factors schools use to select pupils, including ability, achievement and, in cases where schools charge tuition fees or are located in affluent areas, socioeconomic status. However, the possible role of DNA differences between students of different schools types has not yet been considered. We used a UK-representative sample of 4814 genotyped students to investigate exam performance at age 16 and genetic differences between students in three school types: state-funded, non-selective schools ('non-selective'), state-funded, selective schools ('grammar') and private schools, which are selective ('private'). We created a genome-wide polygenic score (GPS) derived from a genome-wide association study of years of education (EduYears). We found substantial mean genetic differences between students of different school types: students in non-selective schools had lower EduYears GPS compared to those in grammar (d = 0.41) and private schools (d = 0.37). Three times as many students in the top EduYears GPS decile went to a selective school compared to the bottom decile. These results were mirrored in the exam differences between school types. However, once we controlled for factors involved in pupil selection, there were no significant genetic differences between school types, and the variance in exam scores at age 16 explained by school type dropped from 7% to <1%. These results show that genetic and exam differences between school types are primarily due to the heritable characteristics involved in pupil admission.

Comment on 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' by Lam et al

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as 'trait specific' to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

The Nature of Nurture: Using a Virtual-Parent Design to Test Parenting Effects on Children's Educational Attainment in Genotyped Families

Research on environmental and genetic pathways to complex traits such as educational attainment (EA) is confounded by uncertainty over whether correlations reflect effects of transmitted parental genes, causal family environments, or some, possibly interactive, mixture of both. Thus, an aggregate of thousands of alleles associated with EA (a polygenic risk score; PRS) may tap parental behaviors and home environments promoting EA in the offspring. New methods for unpicking and determining these causal pathways are required. Here, we utilize the fact that parents pass, at random, 50% of their genome to a given offspring to create independent scores for the transmitted alleles (conventional EA PRS) and a parental score based on allelesnot transmittedto the offspring (EA VP_PRS). The formal effect of non-transmitted alleles on offspring attainment was tested in 2,333 genotyped twins for whom high-quality measures of EA, assessed at age 17 years, were available, and whose parents were also genotyped. Four key findings were observed. First, the EA PRS and EA VP_PRS were empirically independent, validating the virtual-parent design. Second, in this family-based design, children's own EA PRS significantly predicted their EA (β = 0.15), ruling out stratification confounds as a cause of the association of attainment with the EA PRS. Third, parental EA PRS predicted the SES environment parents provided to offspring (β = 0.20), and parental SES and offspring EA were significantly associated (β = 0.33). This would suggest that the EA PRS is at least as strongly linked to social competence as it is to EA, leading to higher attained SES in parents and, therefore, a higher experienced SES for children. In a full structural equation model taking account of family genetic relatedness across multiple siblings the non-transmitted allele effects were estimated at similar values; but, in this more complex model, confidence intervals included zero. A test using the forthcoming EA3 PRS may clarify this outcome. The virtual-parent method may be applied to clarify causality in other phenotypes where observational evidence suggests parenting may moderate expression of other outcomes, for instance in psychiatry.

Genetics and Crime: Integrating New Genomic Discoveries Into Psychological Research About Antisocial Behavior

Drawing on psychological and sociological theories of crime causation, we tested the hypothesis that genetic risk for low educational attainment (assessed via a genome-wide polygenic score) is associated with criminal offending. We further tested hypotheses of how polygenic risk relates to the development of antisocial behavior from childhood through adulthood. Across the Dunedin and Environmental Risk (E-Risk) birth cohorts of individuals growing up 20 years and 20,000 kilometers apart, education polygenic scores predicted risk of a criminal record with modest effects. Polygenic risk manifested during primary schooling in lower cognitive abilities, lower self-control, academic difficulties, and truancy, and it was associated with a life-course-persistent pattern of antisocial behavior that onsets in childhood and persists into adulthood. Crime is central in the nature-nurture debate, and findings reported here demonstrate how molecular-genetic discoveries can be incorporated into established theories of antisocial behavior. They also suggest that improving school experiences might prevent genetic influences on crime from unfolding.

The importance of cohort studies in the post-GWAS era

The past decade has seen enormous success of wide-scale genetic studies in identifying genetic variants that modify individuals' predisposition to common diseases. However, the interpretation and functional understanding of these variants lag far behind. In this Perspective, we discuss opportunities for using large-scale cohort studies to investigate the downstream molecular effects of SNPs at different 'omics' data levels. We point to the pivotal role of population cohorts in establishing causality and advancing drug discovery. In particular, we focus on the breadth-versus-depth concepts of population studies, on data harmonization, and on the challenges, ethical aspects and future perspectives of cohort studies.

Item-level analyses reveal genetic heterogeneity in neuroticism

Genome-wide association studies (GWAS) of psychological traits are generally conducted on (dichotomized) sums of items or symptoms (e.g., case-control status), and not on the individual items or symptoms themselves. We conduct large-scale GWAS on 12 neuroticism items and observe notable and replicable variation in genetic signal between items. Within samples, genetic correlations among the items range between 0.38 and 0.91 (mean rg = .63), indicating genetic heterogeneity in the full item set. Meta-analyzing the two samples, we identify 255 genome-wide significant independent genomic regions, of which 138 are item-specific. Genetic analyses and genetic correlations with 33 external traits support genetic differences between the items. Hierarchical clustering analysis identifies two genetically homogeneous item clusters denoted depressed affect and worry. We conclude that the items used to measure neuroticism are genetically heterogeneous, and that biological understanding can be gained by studying them in genetically more homogeneous clusters.

Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits

The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7858 DNAm sites and 2733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm.

Perceived Racial Discrimination and DNA Methylation Among African American Women in the InterGEN Study

INTRODUCTION

Experiences of racial discrimination have been associated with poor health outcomes. Little is known, however, about how perceived racial discrimination influences DNA methylation (DNAm) among African Americans (AAs). We examined the association of experiences of discrimination with DNAm among AA women in the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure (InterGEN) study.

METHODS

The InterGEN study examines the effects of genetic and psychological factors on blood pressure among AA women and their children. Measures include the Major Life Discrimination (MLD) and the Race-Related Events (RES) scales. In the present analysis, we examined discrimination and DNAm at baseline in the InterGEN study. The 850K EPIC Illumina BeadChip was used for evaluating DNAm in this epigenome-wide association study (EWAS).

RESULTS

One hundred and fifty-two women contributed data for the RES-EWAS analysis and 147 for the MLD-EWAS analysis. Most were 30-39 years old, nonsmokers, had some college education, and had incomes

CONCLUSION

We observed significant epigenetic associations between disease-associated genes (e.g., schizophrenia, bipolar disorder, and asthma) and perceived discrimination as measured by the MLD Scale. Future health disparities research should include epigenetics in high-risk populations to elucidate functional consequences induced by the psychosocial environment.

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Key Words

• African Americans
• DNA methylation
• epigenomics
• racism
• women

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MESH Headings

• Adult
• Black or African American/genetics
• Asthma/genetics
• Blood Pressure/genetics
• Child
• DNA/analysis
• DNA Methylation/genetics
• Epigenesis, Genetic
• Epigenomics
• Female
• Humans
• Racism
• Risk Factors
• United States

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Grants

• R01 NR013520 NINR NIH HHS
• UL1 TR001863 NCATS NIH HHS
• National Institute of Nursing Research

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Affiliation(s)

Veronica Barcelona de Mendoza 1 Yale School of Nursing, Orange, CT, USA
Yunfeng Huang 2 Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
Cindy A Crusto 3 Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
Yan V Sun 2 Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
Jacquelyn Y Taylor 1 Yale School of Nursing, Orange, CT, USA

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Collaborators Collapse

The new genetics of intelligence

Intelligence - the ability to learn, reason and solve problems - is at the forefront of behavioural genetic research. Intelligence is highly heritable and predicts important educational, occupational and health outcomes better than any other trait. Recent genome-wide association studies have successfully identified inherited genome sequence differences that account for 20% of the 50% heritability of intelligence. These findings open new avenues for research into the causes and consequences of intelligence using genome-wide polygenic scores that aggregate the effects of thousands of genetic variants.

The Developmental Nature of the Victim-Offender Overlap

PURPOSE

It is well-established that victims and offenders are often the same people, a phenomenon known as the victim-offender overlap, but the developmental nature of this overlap remains uncertain. In this study, we drew from a developmental theoretical framework to test effects of genetics, individual characteristics, and routine-activity-based risks. Drawing from developmental literature, we additionally tested the effect of an accumulation of adverse childhood experiences (ACEs).

METHODS

Data came from the Environmental Risk (E-Risk) Study, a representative UK birth cohort of 2232 twins born in 1994-1995 and followed to age 18 (with 93% retention). Crime victimization and offending were assessed through self-reports at age 18 (but findings replicated using crime records). We used the classical twin study method to decompose variance in the victim-offender overlap into genetic and environmental components. We used logistic regression to test the effects of childhood risk factors.

RESULTS

In contrast to past twin studies, we found that environment (as well as genes) contributed to the victim-offender overlap. Our logistic regression results showed that childhood low self-control and childhood antisocial behavior nearly doubled the odds of becoming a victim-offender, compared to a victim-only or an offender-only. Each additional ACE increased the odds of becoming a victim-offender, compared to a victim-only or an offender-only, by approximately 12%, pointing to the importance of cumulative childhood adversity.

CONCLUSIONS

This study showed that the victim-offender overlap is, at least partially, developmental in nature and predictable from personal childhood characteristics and an accumulation of many adverse childhood experiences.

Informed Consent in Translational Genomics: Insufficient Without Trustworthy Governance

Neither the range of potential results from genomic research that might be returned to participants nor future uses of stored data and biospecimens can be fully predicted at the outset of a study. Informed consent procedures require clear explanations about how and by whom decisions are made and what principles and criteria apply. To ensure trustworthy research governance, there is also a need for empirical studies incorporating public input to evaluate and strengthen these processes.

Male antisocial behaviour in adolescence and beyond

Male antisocial behavior is concentrated in the adolescent period of the life course, as documented by the curve of crime over age. This article reviews recent evidence regarding the hypothesis that the age-crime curve conceals two groups with different causes. Life-course persistent males show extreme, pervasive, persistent antisocial behavior from early childhood to adulthood. They are hypothesized to be rare, with pathological risk factors and poor life outcomes. In contrast, adolescence-limited males show similar levels of antisocial behavior but primarily during the adolescent stage of development. They are hypothesized to be common and normative, whereas abstainers from offending are rare. This article recaps the taxonomy's 25-year history, concluding that it is standing the test of time in research, and making an impact on policy in early-years prevention and juvenile justice. Research is needed into how the taxonomy relates to neuroscience, health, genetics, and changes in modern crime, including digital crime.

Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap

The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders-autism, schizophrenia, bipolar disorder, depression, and alcoholism-compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism-based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity.

Genome-wide analysis of self-reported risk-taking behaviour and cross-disorder genetic correlations in the UK Biobank cohort

Risk-taking behaviour is a key component of several psychiatric disorders and could influence lifestyle choices such as smoking, alcohol use, and diet. As a phenotype, risk-taking behaviour therefore fits within a Research Domain Criteria (RDoC) approach, whereby identifying genetic determinants of this trait has the potential to improve our understanding across different psychiatric disorders. Here we report a genome-wide association study in 116,255 UK Biobank participants who responded yes/no to the question "Would you consider yourself a risk taker?" Risk takers (compared with controls) were more likely to be men, smokers, and have a history of psychiatric disorder. Genetic loci associated with risk-taking behaviour were identified on chromosomes 3 (rs13084531) and 6 (rs9379971). The effects of both lead SNPs were comparable between men and women. The chromosome 3 locus highlights CADM2, previously implicated in cognitive and executive functions, but the chromosome 6 locus is challenging to interpret due to the complexity of the HLA region. Risk-taking behaviour shared significant genetic risk with schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, and post-traumatic stress disorder, as well as with smoking and total obesity. Despite being based on only a single question, this study furthers our understanding of the biology of risk-taking behaviour, a trait that has a major impact on a range of common physical and mental health disorders.

Novel Loci Associated With Attention-Deficit/Hyperactivity Disorder Are Revealed by Leveraging Polygenic Overlap With Educational Attainment

OBJECTIVE

Attention-deficit/hyperactivity disorder (ADHD) is a common and highly heritable psychiatric condition. By exploiting the reported relationship between ADHD and educational attainment (EA), we aimed to improve discovery of ADHD-associated genetic variants and to investigate genetic overlap between these phenotypes.

METHOD

A conditional/conjunctional false discovery rate (condFDR/conjFDR) method was applied to genome-wide association study (GWAS) data on ADHD (2,064 trios, 896 cases, and 2,455 controls) and EA (n=328,917) to identify ADHD-associated loci and loci overlapping between ADHD and EA. Identified single nucleotide polymorphisms (SNPs) were tested for association in an independent population-based study of ADHD symptoms (n=17,666). Genetic correlation between ADHD and EA was estimated using LD score regression and Pearson correlation.

RESULTS

At levels of condFDR<0.01 and conjFDR<0.05, we identified 5 ADHD-associated loci, 3 of these being shared between ADHD and EA. None of these loci had been identified in the primary ADHD GWAS, demonstrating the increased power provided by the condFDR/conjFDR analysis. Leading SNPs for 4 of 5 identified regions are in introns of protein coding genes (KDM4A, MEF2C, PINK1, RUNX1T1), whereas the remaining one is an intergenic SNP on chromosome 2 at 2p24. Consistent direction of effects in the independent study of ADHD symptoms was shown for 4 of 5 identified loci. A polygenic overlap between ADHD and EA was supported by significant genetic correlation (rg=-0.403, p=7.90×10-8) and >10-fold mutual enrichment of SNPs associated with both traits.

CONCLUSION

We identified 5 novel loci associated with ADHD and provided evidence for a shared genetic basis between ADHD and EA. These findings could aid understanding of the genetic risk architecture of ADHD and its relation to EA.

GENES AND GINI: WHAT INEQUALITY MEANS FOR HERITABILITY

Research has established that genetic differences among people explain a greater or smaller proportion of the variation in life outcomes in different environmental conditions. This review evaluates the results of recent educationally relevant behavioural genetic studies and meta-analyses in the context of recent trends in income and wealth distribution. The pattern of results suggests that inequality and social policies can have profound effects on the heritability of educational attainment and achievement in a population (Gene–Gini interplay). For example, heritability is generally higher at greater equality levels, suggesting that inequality stifles the expression of educationally relevant genetic propensities. The review concludes with a discussion of the mechanisms of Gene–Gini interplay and what the findings mean for efforts to optimize education for all people.

GABRA2, alcohol, and illicit drug use: An event-level model of genetic risk for polysubstance use

GABRA2, the gene encoding the α2 subunit of the GABAA receptor, potentially plays a role in the etiology of problematic drinking, as GABRA2 genotype has been associated with subjective response to alcohol and other alcohol-related reward processes. The GABRA2 gene has also been associated with illicit drug use, but the extent to which associations with drug use are independent of associations with alcohol use remains unclear, partly because most previous research has used a cross-sectional design that cannot discriminate comorbidity at the between-person level and co-occurrence within-persons. The present study used a daily monitoring method that assessed the effects of GABRA2 variation on substance use as it occurred in the natural environment during emerging adulthood. Non-Hispanic European participants provided DNA samples and completed daily reports of alcohol and drug use for 1 month per year across 4 years (N = 28,263 unique observations of N = 318 participants). GABRA2 variants were associated with illicit drug use in both sober and intoxicated conditions. Moreover, the effect of GABRA2 variation on drug use was moderated by an individual's degree of intoxication. These findings are consistent with recent genetic and neuroscience research, and they suggest GABRA2 variation influences drug-seeking behavior through both alcohol-related and alcohol-independent pathways. (PsycINFO Database Record

The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders

Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes.

The social genome of friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health

Humans tend to form social relationships with others who resemble them. Whether this sorting of like with like arises from historical patterns of migration, meso-level social structures in modern society, or individual-level selection of similar peers remains unsettled. Recent research has evaluated the possibility that unobserved genotypes may play an important role in the creation of homophilous relationships. We extend this work by using data from 5,500 adolescents from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine genetic similarities among pairs of friends. Although there is some evidence that friends have correlated genotypes, both at the whole-genome level as well as at trait-associated loci (via polygenic scores), further analysis suggests that meso-level forces, such as school assignment, are a principal source of genetic similarity between friends. We also observe apparent social-genetic effects in which polygenic scores of an individual's friends and schoolmates predict the individual's own educational attainment. In contrast, an individual's height is unassociated with the height genetics of peers.

Genomic data can illuminate the architecture and evolution of cognitive abilities

Does general intelligence exist across species, and has it been a target of natural selection? These questions can be addressed with genomic data, which can rule out artifacts by demonstrating that distinct cognitive abilities are genetically correlated and thus share a biological substrate. This work has begun with data from humans and can be extended to other species; it should focus not only on general intelligence but also specific capacities like language and spatial ability.

Causal associations between risk factors and common diseases inferred from GWAS summary data

Health risk factors such as body mass index (BMI) and serum cholesterol are associated with many common diseases. It often remains unclear whether the risk factors are cause or consequence of disease, or whether the associations are the result of confounding. We develop and apply a method (called GSMR) that performs a multi-SNP Mendelian randomization analysis using summary-level data from genome-wide association studies to test the causal associations of BMI, waist-to-hip ratio, serum cholesterols, blood pressures, height, and years of schooling (EduYears) with common diseases (sample sizes of up to 405,072). We identify a number of causal associations including a protective effect of LDL-cholesterol against type-2 diabetes (T2D) that might explain the side effects of statins on T2D, a protective effect of EduYears against Alzheimer’s disease, and bidirectional associations with opposite effects (e.g., higher BMI increases the risk of T2D but the effect of T2D on BMI is negative).

Genetic methods are useful to test whether risk factors are causal for or consequence of disease. Here, Zhu et al. develop a generalized summary-based Mendelian Randomization (GSMR) method which uses summary-level data from GWAS to test for causal associations of health risk factors with common diseases.

The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis

Non-coding regions comprise most of the human genome and harbor a significant fraction of risk alleles for neuropsychiatric diseases, yet their functions remain poorly defined. We created a high-resolution map of non-coding elements involved in human cortical neurogenesis by contrasting chromatin accessibility and gene expression in the germinal zone and cortical plate of the developing cerebral cortex. We link distal regulatory elements (DREs) to their cognate gene(s) together with chromatin interaction data and show that target genes of human-gained enhancers (HGEs) regulate cortical neurogenesis and are enriched in outer radial glia, a cell type linked to human cortical evolution. We experimentally validate the regulatory effects of predicted enhancers for FGFR2 and EOMES. We observe that common genetic variants associated with educational attainment, risk for neuropsychiatric disease, and intracranial volume are enriched within regulatory elements involved in cortical neurogenesis, demonstrating the importance of this early developmental process for adult human cognitive function.

Genetic variation interacts with experience to determine interindividual differences in learned song

Learning reflects the influence of experience on genetically determined circuitry, but little is known about how experience and genetics interact to determine complex learned phenotypes. Here, we used vocal learning in songbirds to study how experience and genetics contribute to interindividual differences in learned song. Previous work has established that such differences in song within a species depend on learning, but in principle some of these differences could also depend on genetic variation. We focused on song tempo, a learned and quantifiable feature that is controlled by central neural circuitry. To identify genetic contributions to tempo we computer-tutored juvenile Bengalese finches (Lonchura striata domestica) from different genetic backgrounds with synthetic songs in which tempo was systematically varied. Computer-tutored birds exhibited unexpectedly strong heritability for song tempo and comparatively weak influence of experience. We then tested whether heritability was fixed and independent of experience by providing a second group of birds with enriched instruction via live social tutoring. Live tutoring resulted in not only a significant increase in the influence of experience on tempo but also a dramatic decrease in the influence of genetics, indicating that enriched instruction could overcome genetic biases evident under computer tutoring. Our results reveal strong heritable genetic contributions to interindividual variation in song tempo but that the degree of heritability depends profoundly on the quality of instruction. They suggest that for more complex learned phenotypes, where it can be difficult to identify and control relevant experiential variables, heritability may similarly be contingent on the specifics of experience.

Circulating metabolites and general cognitive ability and dementia: Evidence from 11 cohort studies

INTRODUCTION

Identifying circulating metabolites that are associated with cognition and dementia may improve our understanding of the pathogenesis of dementia and provide crucial readouts for preventive and therapeutic interventions.

METHODS

We studied 299 metabolites in relation to cognition (general cognitive ability) in two discovery cohorts (N total = 5658). Metabolites significantly associated with cognition after adjusting for multiple testing were replicated in four independent cohorts (N total = 6652), and the associations with dementia and Alzheimer's disease (N = 25,872) and lifestyle factors (N = 5168) were examined.

RESULTS

We discovered and replicated 15 metabolites associated with cognition including subfractions of high-density lipoprotein, docosahexaenoic acid, ornithine, glutamine, and glycoprotein acetyls. These associations were independent of classical risk factors including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, glucose, and apolipoprotein E (APOE) genotypes. Six of the cognition-associated metabolites were related to the risk of dementia and lifestyle factors.

DISCUSSION

Circulating metabolites were consistently associated with cognition, dementia, and lifestyle factors, opening new avenues for prevention of cognitive decline and dementia.

Polygenic scores for schizophrenia and educational attainment are associated with behavioural problems in early childhood in the general population

BACKGROUND

Genome-wide association studies in adults have identified numerous genetic variants related to psychiatric disorders and related traits, such as schizophrenia and educational attainment. However, the effects of these genetic variants on behaviour in the general population remain to be fully understood, particularly in younger populations. We investigated whether polygenic scores of five psychiatric disorders and educational attainment are related to emotional and behaviour problems during early childhood.

METHODS

From the Generation R Study, we included participants with available genotype data and behavioural problems measured with the Child Behavior Checklist (CBCL) at the age of 3 (n = 1,902), 6 (n = 2,202) and 10 years old (n = 1,843). Polygenic scores were calculated for five psychiatric disorders and educational attainment. These polygenic scores were tested for an association with the broadband internalizing and externalizing problem scales and the specific CBCL syndrome scale scores.

RESULTS

Analysis of the CBCL broadband scales showed that the schizophrenia polygenic score was associated with significantly higher internalizing scores at 3, 6 and 10 years and higher externalizing scores at age 3 and 6. The educational attainment polygenic score was associated with lower externalizing scores at all time points and lower internalizing scores at age 3. No associations were observed for the polygenic scores of bipolar disorder, major depressive disorder and autism spectrum disorder. Secondary analyses of specific syndrome scores showed that the schizophrenia polygenic score was strongly related to the Thought Problems scores. A negative association was observed between the educational attainment polygenic score and Attention Problems scores across all age groups.

CONCLUSIONS

Polygenic scores for adult psychiatric disorders and educational attainment are associated with variation in emotional and behavioural problems already at a very early age.

C.7van MeursJoyce8IsaacsAaron9JansenRick10FrankeLude11BoomsmaDorret I.12PoolRené12van DongenJenny12HottengaJouke J.12van GreevenbroekMarleen MJ13StehouwerCoen D. A.13van der KallenCarla J. H.13SchalkwijkCasper G.13WijmengaCisca11FrankeLude11ZhernakovaSasha11TigchelaarEttje F.11SlagboomP. Eline6BeekmanMarian6DeelenJoris6van HeemstDiana14VeldinkJan H.15van den BergLeonard H.15van DuijnCornelia M.9HofmanBert A.16IsaacsAaron9UitterlindenAndré G.8van MeursJoyce8JhamaiP. Mila8VerbiestMichael8SuchimanH. Eka D.6VerkerkMarijn8van der BreggenRuud6van RooijJeroen8LakenbergNico6MeiHailiang17van ItersonMaarten6van GalenMichiel7BotJan18ZhernakovaDasha V.11JansenRick10van’t HofPeter17DeelenPatrick11NoorenIrene18’t HoenPeter A. C.7HeijmansBastiaan T.6MoedMatthijs6FrankeLude11VermaatMartijn7ZhernakovaDasha V.11LuijkRené6BonderMarc Jan11van ItersonMaarten6DeelenPatrick11van DijkFreerk19van GalenMichiel7ArindrartoWibowo17KielbasaSzymon M.20SwertzMorris A.19van ZwetErik W.20JansenRick10HoenPeter-Bram’t7HeijmansBastiaan T.6. DNA methylation signatures of educational attainment

Educational attainment is a key behavioural measure in studies of cognitive and physical health, and socioeconomic status. We measured DNA methylation at 410,746 CpGs (N = 4152) and identified 58 CpGs associated with educational attainment at loci characterized by pleiotropic functions shared with neuronal, immune and developmental processes. Associations overlapped with those for smoking behaviour, but remained after accounting for smoking at many CpGs: Effect sizes were on average 28% smaller and genome-wide significant at 11 CpGs after adjusting for smoking and were 62% smaller in never smokers. We examined sources and biological implications of education-related methylation differences, demonstrating correlations with maternal prenatal folate, smoking and air pollution signatures, and associations with gene expression in cis, dynamic methylation in foetal brain, and correlations between blood and brain. Our findings show that the methylome of lower-educated people resembles that of smokers beyond effects of their own smoking behaviour and shows traces of various other exposures.

Analysis of the joint effect of SNPs to identify independent loci and allelic heterogeneity in schizophrenia GWAS data

We have tested published methods for capturing allelic heterogeneity and identifying loci of joint effects to uncover more of the "hidden heritability" of schizophrenia (SCZ). We used two tools, cojo-GCTA and multi-SNP, to analyze meta-statistics from the latest genome-wide association study (GWAS) on SCZ by the Psychiatric Genomics Consortium (PGC). Stepwise regression on markers with p values <10^-7 in cojo-GCTA identified 96 independent signals. Eighty-five passed the genome-wide significance threshold. Cross-validation of cojo-GCTA by CLUMP was 76%, i.e., 26 of the loci identified by the PGC using CLUMP were found to be dependent on another locus by cojo-GCTA. The overlap between cojo-GCTA and multi-SNP was better (up to 92%). Three markers reached genome-wide significance (5 × 10^-8) in a joint effect model. In addition, two loci showed possible allelic heterogeneity within 1-Mb genomic regions, while CLUMP analysis had identified 16 such regions. Cojo-GCTA identified fewer independent loci than CLUMP and seems to be more conservative, probably because it accounts for long-range LD and interaction effects between markers. These findings also explain why fewer loci with possible allelic heterogeneity remained significant after cojo-GCTA analysis. With multi-SNP, 86 markers were selected at the threshold 10^-7. Multi-SNP identifies fewer independent signals, due to splitting of the data and use of smaller samples. We recommend that cojo-GCTA and multi-SNP are used for post-GWAS analysis of all traits to call independent loci. We conclude that only a few loci in SCZ show joint effects or allelic heterogeneity, but this could be due to lack of power for that data set.

A Recurrent De Novo Nonsense Variant in ZSWIM6 Results in Severe Intellectual Disability without Frontonasal or Limb Malformations

A recurrent de novo missense variant within the C-terminal Sin3-like domain of ZSWIM6 was previously reported to cause acromelic frontonasal dysostosis (AFND), an autosomal-dominant severe frontonasal and limb malformation syndrome, associated with neurocognitive and motor delay, via a proposed gain-of-function effect. We present detailed phenotypic information on seven unrelated individuals with a recurrent de novo nonsense variant (c.2737C>T [p.Arg913Ter]) in the penultimate exon of ZSWIM6 who have severe-profound intellectual disability and additional central and peripheral nervous system symptoms but an absence of frontonasal or limb malformations. We show that the c.2737C>T variant does not trigger nonsense-mediated decay of the ZSWIM6 mRNA in affected individual-derived cells. This finding supports the existence of a truncated ZSWIM6 protein lacking the Sin3-like domain, which could have a dominant-negative effect. This study builds support for a key role for ZSWIM6 in neuronal development and function, in addition to its putative roles in limb and craniofacial development, and provides a striking example of different variants in the same gene leading to distinct phenotypes.

Modifiable pathways in Alzheimer's disease: Mendelian randomisation analysis

OBJECTIVE

To determine which potentially modifiable risk factors, including socioeconomic, lifestyle/dietary, cardiometabolic, and inflammatory factors, are associated with Alzheimer's disease.

DESIGN

Mendelian randomisation study using genetic variants associated with the modifiable risk factors as instrumental variables.

SETTING

International Genomics of Alzheimer's Project.

PARTICIPANTS

17 008 cases of Alzheimer's disease and 37 154 controls.

MAIN OUTCOME MEASURES

Odds ratio of Alzheimer's per genetically predicted increase in each modifiable risk factor estimated with Mendelian randomisation analysis.

RESULTS

This study included analyses of 24 potentially modifiable risk factors. A Bonferroni corrected threshold of P=0.002 was considered to be significant, and P<0.05 was considered suggestive of evidence for a potential association. Genetically predicted educational attainment was significantly associated with Alzheimer's. The odds ratios were 0.89 (95% confidence interval 0.84 to 0.93; P=2.4×10-6) per year of education completed and 0.74 (0.63 to 0.86; P=8.0×10-5) per unit increase in log odds of having completed college/university. The correlated trait intelligence had a suggestive association with Alzheimer's (per genetically predicted 1 SD higher intelligence: 0.73, 0.57 to 0.93; P=0.01). There was suggestive evidence for potential associations between genetically predicted higher quantity of smoking (per 10 cigarettes a day: 0.69, 0.49 to 0.99; P=0.04) and 25-hydroxyvitamin D concentrations (per 20% higher levels: 0.92, 0.85 to 0.98; P=0.01) and lower odds of Alzheimer's and between higher coffee consumption (per one cup a day: 1.26, 1.05 to 1.51; P=0.01) and higher odds of Alzheimer's. Genetically predicted alcohol consumption, serum folate, serum vitamin B12, homocysteine, cardiometabolic factors, and C reactive protein were not associated with Alzheimer's disease.

CONCLUSION

These results provide support that higher educational attainment is associated with a reduced risk of Alzheimer's disease.

Human longevity: 25 genetic loci associated in 389,166 UK biobank participants

We undertook a genome-wide association study (GWAS) of parental longevity in European descent UK Biobank participants. For combined mothers' and fathers' attained age, 10 loci were associated (p<5*10-8), including 8 previously identified for traits including survival, Alzheimer's and cardiovascular disease. Of these, 4 were also associated with longest 10% survival (mothers age ≥90 years, fathers ≥87 years), with 2 additional associations including MC2R intronic variants (coding for the adrenocorticotropic hormone receptor). Mother's age at death was associated with 3 additional loci (2 linked to autoimmune conditions), and 8 for fathers only. An attained age genetic risk score associated with parental survival in the US Health and Retirement Study and the Wisconsin Longitudinal Study and with having a centenarian parent (n=1,181) in UK Biobank. The results suggest that human longevity is highly polygenic with prominent roles for loci likely involved in cellular senescence and inflammation, plus lipid metabolism and cardiovascular conditions. There may also be gender specific routes to longevity.

An epigenome-wide association study meta-analysis of educational attainment

The epigenome is associated with biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here we provide evidence on the associations between epigenetic modifications-in our case, CpG methylation-and educational attainment (EA), a biologically distal environmental factor that is arguably among the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10 767 individuals. We find nine CpG probes significantly associated with EA. However, robustness analyses show that all nine probes have previously been found to be associated with smoking. Only two associations remain when we perform a sensitivity analysis in the subset of never-smokers, and these two probes are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, the effect sizes of the associations with EA are far smaller than the known associations with the biologically proximal environmental factors alcohol consumption, body mass index, smoking and maternal smoking during pregnancy. Follow-up analyses that combine the effects of many probes also point to small methylation associations with EA that are highly correlated with the combined effects of smoking. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.

Genetic Risk Variants Associated With Comorbid Alcohol Dependence and Major Depression

Importance

Alcohol dependence (AD) and major depression (MD) are leading causes of disability that often co-occur. Genetic epidemiologic data have shown that AD and MD share a common possible genetic cause. The molecular nature of this shared genetic basis is poorly understood.

Objectives

To detect genetic risk variants for comorbid AD and MD and to determine whether polygenic risk alleles are shared with neuropsychiatric traits or subcortical brain volumes.

Design, Setting, and Participants

This genome-wide association study analyzed criterion counts of comorbid AD and MD in African American and European American data sets collected as part of the Yale-Penn study of the genetics of drug and alcohol dependence from February 14, 1999, to January 13, 2015. After excluding participants never exposed to alcohol or with missing information for any diagnostic criterion, genome-wide association studies were performed on 2 samples (the Yale-Penn 1 and Yale-Penn 2 samples) totaling 4653 African American participants and 3169 European American participants (analyzed separately). Tests were performed to determine whether polygenic risk scores derived from potentially related traits in European American participants could be used to estimate comorbid AD and MD.

Main Outcomes and Measures

Comorbid criterion counts (ranging from 0 to 14) for AD (7 criteria) and MD (9 criteria, scaled to 7) as defined by the DSM-IV.

Results

Of the 7822 participants (3342 women and 4480 men; mean [SD] age, 40.1 [10.7] years), the median comorbid criterion count was 6.2 (interquartile range, 2.3-10.9). Under the linear regression model, rs139438618 at the semaphorin 3A (SEMA3A [OMIM 603961]) locus was significantly associated with AD and MD comorbidity in African American participants in the Yale-Penn 1 sample (β = 0.89; 95% CI, 0.57-1.20; P = 2.76 × 10-8). In the independent Yale-Penn 2 sample, the association was also significant (β = 0.83; 95% CI, 0.39-1.28; P = 2.06 × 10-4). Meta-analysis of the 2 samples yielded a more robust association (β = 0.87; 95% CI, 0.61-1.12; P = 2.41 × 10-11). There was no significant association identified in European American participants. Analyses of polygenic risk scores showed that individuals with a higher risk of neuroticism (β = 1.01; 95% CI, 0.50-1.52) or depressive symptoms (β = 0.87; 95% CI, 0.32-1.42) and a lower level of subjective well-being (β = -0.94; 95% CI, -1.46 to -0.42) and educational attainment (β = -1.00, 95% CI, -1.57 to -0.44) had a higher level of AD and MD comorbidity, while larger intracranial (β = 1.07; 95% CI, 0.50 to 1.64) and smaller putamen volumes (β = -1.16; 95% CI, -1.86 to -0.46) were associated with higher risks of AD and MD comorbidity.

Conclusions and Relevance

SEMA3A variation is significantly and replicably associated with comorbid AD and MD in African American participants. Analyses of polygenic risk scores identified pleiotropy with neuropsychiatric traits and brain volumes. Further studies are warranted to understand the biological and genetic mechanisms of this comorbidity, which could facilitate development of medications and other treatments for comorbid AD and MD.