Phenotypic Annotation: Using Polygenic Scores to Translate Discoveries From Genome-Wide Association Studies From the Top Down

Exploring the Fetal Origins Hypothesis Using Genetic Data

Birth weight is a robust predictor of valued life course outcomes, emphasizing the importance of prenatal development. But does birth weight act as a proxy for environmental conditions in utero, or do biological processes surrounding birth weight themselves play a role in healthy development? To answer this question, we leverage variation in birth weight that is, within families, orthogonal to prenatal environmental conditions: one's genes. We construct polygenic scores in two longitudinal studies (Born in Bradford, N = 2008; Wisconsin Longitudinal Study, N = 8488) to empirically explore the molecular genetic correlates of birth weight. A 1 standard deviation increase in the polygenic score is associated with an ~100-grams increase in birth weight and a 1.4 pp (22 percent) decrease in low birth weight probability. Sibling comparisons illustrate that this association largely represents a causal effect. The polygenic score-birth weight association is increased for children who spend longer in the womb and whose mothers have higher body mass index, though we find no differences across maternal socioeconomic status. Finally, the polygenic score affects social and cognitive outcomes, suggesting that birth weight is itself related to healthy prenatal development.

A disanalogy with RCTs and its implications for second-generation causal knowledge

We are less optimistic than Madole & Harden that family-based genome-wide association studies (GWASs) will lead to significant second-generation causal knowledge. Despite bearing some similarities, family-based GWASs and randomised controlled trials (RCTs) are not identical. Most RCTs assess a relatively homogenous causal stimulus as a treatment, whereas GWASs assess highly heterogeneous causal stimuli. Thus, GWAS results will not translate so easily into second-generation causal knowledge.

Interrogating the validity of cumulative indices of environmental and genetic risk for negative developmental outcomes

Indices of cumulative risk (CR) have long been used in developmental research to encode the number of risk factors a child or adolescent experiences that may impede optimal developmental outcomes. Initial contributions concentrated on indices of cumulative environmental risk; more recently, indices of cumulative genetic risk have been employed. In this article, regression analytic methods are proposed for interrogating strongly the validity of risk indices by testing optimality of compositing weights, enabling more informative modeling of effects of CR indices. Reanalyses of data from two studies are reported. One study involved 10 environmental risk factors predicting Verbal IQ in 215 four-year-old children. The second study included an index of genetic CR in a G×E interaction investigation of 281 target participants assessed at age 15 years and then again at age 31 years for observed hostility during videotaped interactions with close family relations. Principles to guide evaluation of results of statistical modeling are presented, and implications of results for research and theory are discussed. The ultimate goals of this paper are to develop stronger tests of conjectures involving CR indices and to promote methods for improving replicability of results across studies.

Overcoming attenuation bias in regressions using polygenic indices

Measurement error in polygenic indices (PGIs) attenuates the estimation of their effects in regression models. We analyze and compare two approaches addressing this attenuation bias: Obviously Related Instrumental Variables (ORIV) and the PGI Repository Correction (PGI-RC). Through simulations, we show that the PGI-RC performs slightly better than ORIV, unless the prediction sample is very small (N < 1000) or when there is considerable assortative mating. Within families, ORIV is the best choice since the PGI-RC correction factor is generally not available. We verify the empirical validity of the simulations by predicting educational attainment and height in a sample of siblings from the UK Biobank. We show that applying ORIV between families increases the standardized effect of the PGI by 12% (height) and by 22% (educational attainment) compared to a meta-analysis-based PGI, yet estimates remain slightly below the PGI-RC estimates. Furthermore, within-family ORIV regression provides the tightest lower bound for the direct genetic effect, increasing the lower bound for the standardized direct genetic effect on educational attainment from 0.14 to 0.18 (+29%), and for height from 0.54 to 0.61 (+13%) compared to a meta-analysis-based PGI.

Associating broad and clinically defined polygenic scores for depression with depression-related phenotypes

Twin studies indicate that 30-40% of the disease liability for depression can be attributed to genetic differences. Here, we assess the explanatory ability of polygenic scores (PGS) based on broad- (PGS_BD) and clinical- (PGS_MDD) depression summary statistics from the UK Biobank in an independent sample of adults (N = 210; 100% European Ancestry) who were extensively phenotyped for depression and related neurocognitive traits (e.g., rumination, emotion regulation, anhedonia, and resting frontal alpha asymmetry). The UK Biobank-derived PGS_BD had small associations with MDD, depression severity, anhedonia, cognitive reappraisal, brooding, and suicidal ideation but only the association with suicidal ideation remained statistically significant after correcting for multiple comparisons. Similarly small associations were observed for the PGS_MDD but none remained significant after correcting for multiple comparisons. These findings provide important initial guidance about the expected effect sizes between current UKB PGSs for depression and depression-related neurocognitive phenotypes.

General v. specific vulnerabilities: polygenic risk scores and higher-order psychopathology dimensions in the Adolescent Brain Cognitive Development (ABCD) Study

BACKGROUND

Polygenic risk scores (PRSs) capture genetic vulnerability to psychiatric conditions. However, PRSs are often associated with multiple mental health problems in children, complicating their use in research and clinical practice. The current study is the first to systematically test which PRSs associate broadly with all forms of childhood psychopathology, and which PRSs are more specific to one or a handful of forms of psychopathology.

METHODS

The sample consisted of 4717 unrelated children (mean age = 9.92, s.d. = 0.62; 47.1% female; all European ancestry). Psychopathology was conceptualized hierarchically as empirically derived general factor (p-factor) and five specific factors: externalizing, internalizing, neurodevelopmental, somatoform, and detachment. Partial correlations explored associations between psychopathology factors and 22 psychopathology-related PRSs. Regressions tested which level of the psychopathology hierarchy was most strongly associated with each PRS.

RESULTS

Thirteen PRSs were significantly associated with the general factor, most prominently Chronic Multisite Pain-PRS (r = 0.098), ADHD-PRS (r = 0.079), and Depression-PRS (r = 0.078). After adjusting for the general factor, Depression-PRS, Neuroticism-PRS, PTSD-PRS, Insomnia-PRS, Chronic Back Pain-PRS, and Autism-PRS were not associated with lower order factors. Conversely, several externalizing PRSs, including Adventurousness-PRS and Disinhibition-PRS, remained associated with the externalizing factor (|r| = 0.040-0.058). The ADHD-PRS remained uniquely associated with the neurodevelopmental factor (r = 062).

CONCLUSIONS

PRSs developed to predict vulnerability to emotional difficulties and chronic pain generally captured genetic risk for all forms of childhood psychopathology. PRSs developed to predict vulnerability to externalizing difficulties, e.g. disinhibition, tended to be more specific in predicting behavioral problems. The results may inform translation of existing PRSs to pediatric research and future clinical practice.

Polygenic indices for cognition in healthy aging; the role of brain measures

Background

Genome-wide association studies (GWAS) have identified large numbers of genetic variants associated with cognition. However, little is known about how these genetic discoveries impact cognitive aging.

Methods

We conducted polygenic-index (PGI) analysis of cognitive performance in n = 168 European-ancestry adults aged 20-80. We computed PGIs based on GWAS of cognitive performance in young/middle-aged and older adults. We tested associations of the PGI with cognitive performance, as measured through neuropsychological evaluation. We explored whether these associations were accounted for by magnetic resonance imaging (MRI) measures of brain-aging phenotypes: total gray matter volume (GM), cortical thickness (CT), and white matter hyperintensities burden (WMH).

Results

Participants with higher PGI values performed better on cognitive tests (B = 0.627, SE = 0.196, p = 0.002) (age, sex, and principal components as covariates). Associations remained significant with inclusion of covariates for MRI measures of brain aging; B = 0.439, SE: 0.198, p = 0.028). PGI associations were stronger in young and middle-aged (age<65) as compared to older adults. For further validation, linear regression for Cog PGI and cognition in the fully adjusted model and adding the interaction between age group and Cog PGI, showed significant results (B = 0.892, SE: 0.325, p = 0.007) driven by young and middle-aged adults (B = -0.403, SE: 0.193, p = 0.039). In ancillary analysis, the Cognitive PGI was not associated with any of the brain measures.

Conclusions

Genetics discovered in GWAS of cognition are associated with cognitive performance in healthy adults across age, but most strongly in young and middle-aged adults. Associations were not explained by brain-structural markers of brain aging. Genetics uncovered in GWAS of cognitive performance may contribute to individual differences established relatively early in life and may not reflect genetic mechanisms of cognitive aging.

Genetic determinism, essentialism and reductionism: semantic clarity for contested science

Research linking genetic differences with human social and behavioural phenotypes has long been controversial. Frequently, debates about the ethical, social and legal implications of this area of research centre on questions about whether studies overtly or covertly perpetuate genetic determinism, genetic essentialism and/or genetic reductionism. Given the prominent role of the '-isms' in scientific discourse and criticism, it is important for there to be consensus and clarity about the meaning of these terms. Here, the author integrates scholarship from psychology, genetics and philosophy of science to provide accessible definitions of genetic determinism, genetic reductionism and genetic essentialism. The author provides linguistic and visual examples of determinism, reductionism and essentialism in science and popular culture, discusses common misconceptions and concludes with recommendations for science communication.

Polygenic Liability to Depression Is Associated With Multiple Medical Conditions in the Electronic Health Record: Phenome-wide Association Study of 46,782 Individuals

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disease-associated disability, with much of the increased burden due to psychiatric and medical comorbidity. This comorbidity partly reflects common genetic influences across conditions. Integrating molecular-genetic tools with health records enables tests of association with the broad range of physiological and clinical phenotypes. However, standard phenome-wide association studies analyze associations with individual genetic variants. For polygenic traits such as MDD, aggregate measures of genetic risk may yield greater insight into associations across the clinical phenome.

METHODS

We tested for associations between a genome-wide polygenic risk score for MDD and medical and psychiatric traits in a phenome-wide association study of 46,782 unrelated, European-ancestry participants from the Michigan Genomics Initiative.

RESULTS

The MDD polygenic risk score was associated with 211 traits from 15 medical and psychiatric disease categories at the phenome-wide significance threshold. After excluding patients with depression, continued associations were observed with respiratory, digestive, neurological, and genitourinary conditions; neoplasms; and mental disorders. Associations with tobacco use disorder, respiratory conditions, and genitourinary conditions persisted after accounting for genetic overlap between depression and other psychiatric traits. Temporal analyses of time-at-first-diagnosis indicated that depression disproportionately preceded chronic pain and substance-related disorders, while asthma disproportionately preceded depression.

CONCLUSIONS

The present results can inform the biological links between depression and both mental and systemic diseases. Although MDD polygenic risk scores cannot currently forecast health outcomes with precision at the individual level, as molecular-genetic discoveries for depression increase, these tools may augment risk prediction for medical and psychiatric conditions.

Using a polygenic score in a family design to understand genetic influences on musicality

To further our understanding of the genetics of musicality, we explored associations between a polygenic score for self-reported beat synchronization ability (PGS_rhythm) and objectively measured rhythm discrimination, as well as other validated music skills and music-related traits. Using family data, we were able to further explore potential pathways of direct genetic, indirect genetic (through passive gene–environment correlation) and confounding effects (such as population structure and assortative mating). In 5648 Swedish twins, we found PGS_rhythm to predict not only rhythm discrimination, but also melody and pitch discrimination (betas between 0.11 and 0.16, p < 0.001), as well as other music-related outcomes (p < 0.05). In contrast, PGS_rhythm was not associated with control phenotypes not directly related to music. Associations did not deteriorate within families (N = 243), implying that indirect genetic or confounding effects did not inflate PGS_rhythm effects. A correlation (r = 0.05, p < 0.001) between musical enrichment of the family childhood environment and individuals' PGS_rhythm, suggests gene–environment correlation. We conclude that the PGS_rhythm captures individuals' general genetic musical propensity, affecting musical behavior more likely direct than through indirect or confounding effects.

Challenging the utility of polygenic scores for social science: Environmental confounding, downward causation, and unknown biology

The sociogenomics revolution is upon us, we are told. Whether revolutionary or not, sociogenomics is poised to flourish given the ease of incorporating polygenic scores (or PGSs) as "genetic propensities" for complex traits into social science research. Pointing to evidence of ubiquitous heritability and the accessibility of genetic data, scholars have argued that social scientists not only have an opportunity but a duty to add PGSs to social science research. Social science research that ignores genetics is, some proponents argue, at best partial and likely scientifically flawed, misleading, and wasteful. Here, I challenge arguments about the value of genetics for social science and with it the claimed necessity of incorporating PGSs into social science models as measures of genetic influences. In so doing, I discuss the impracticability of distinguishing genetic influences from environmental influences because of non-causal gene-environment correlations, especially population stratification, familial confounding, and downward causation. I explain how environmental effects masquerade as genetic influences in PGSs, which undermines their raison d'être as measures of genetic propensity, especially for complex socially contingent behaviors that are the subject of sociogenomics. Additionally, I draw attention to the partial, unknown biology, while highlighting the persistence of an implicit, unavoidable reductionist genes versus environments approach. Leaving sociopolitical and ethical concerns aside, I argue that the potential scientific rewards of adding PGSs to social science are few and greatly overstated and the scientific costs, which include obscuring structural disadvantages and cultural influences, outweigh these meager benefits for most social science applications.

Building causal knowledge in behavior genetics

Behavior genetics is a controversial science. For decades, scholars have sought to understand the role of heredity in human behavior and life-course outcomes. Recently, technological advances and the rapid expansion of genomic databases have facilitated the discovery of genes associated with human phenotypes such as educational attainment and substance use disorders. To maximize the potential of this flourishing science, and to minimize potential harms, careful analysis of what it would mean for genes to be causes of human behavior is needed. In this paper, we advance a framework for identifying instances of genetic causes, interpreting those causal relationships, and applying them to advance causal knowledge more generally in the social sciences. Central to thinking about genes as causes is counterfactual reasoning, the cornerstone of causal thinking in statistics, medicine, and philosophy. We argue that within-family genetic effects represent the product of a counterfactual comparison in the same way as average treatment effects (ATEs) from randomized controlled trials (RCTs). Both ATEs from RCTs and within-family genetic effects are shallow causes: They operate within intricate causal systems (non-unitary), produce heterogeneous effects across individuals (non-uniform), and are not mechanistically informative (non-explanatory). Despite these limitations, shallow causal knowledge can be used to improve understanding of the etiology of human behavior and to explore sources of heterogeneity and fade-out in treatment effects.

Incarceration, polygenic risk, and depressive symptoms among males in late adulthood

This study demonstrates how social and genetic factors jointly influence depression in late adulthood. We focus on the effect of incarceration, a major life event consistently found to be associated with mental health problems. Drawing on data from males in the Wisconsin Longitudinal Study and the Health and Retirement Study, we conduct a polygenic score analysis based on a genome-wide association study on depressive symptoms. Our analysis produces two important findings. First, incarceration experience mediates the association between the depression polygenic score and depressive symptoms in late adulthood (i.e., greater polygenic scores are associated with elevated incarceration risk, which increases depressive symptoms in late adulthood). Second, about one-fifth of the association between incarceration experience and late-adulthood depressive symptoms is accounted for by the depression polygenic score and childhood depression. These findings reveal complex biological and social mechanisms in the development of depression and, more broadly, provide important insights for causal inference in social science research.

Resource profile and user guide of the Polygenic Index Repository

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

Educational attainment polygenic score predicts inhibitory control and academic skills in early and middle childhood

Inhibitory control skills are important for academic outcomes across childhood, but it is unknown whether inhibitory control is implicated in the association between genetic variation and academic performance. This study examined the relationship between a GWAS-based (EduYears) polygenic score indexing educational attainment (EA PGS) and inhibitory control in early (Mage  = 3.80 years) and middle childhood (Mage  = 9.18 years), and whether inhibitory control in early childhood mediated the relation between EA PGS and academic skills. The sample comprised 731 low-income and racially/ethnically diverse children and their families from the longitudinal early steps multisite study. EA PGS predicted middle childhood inhibitory control (estimate = 0.09, SE = 0.05, p < 0.05) and academic skills (estimate = 0.18, SE = 0.05, p < 0.01) but did not predict early childhood inhibitory control (estimate = 0.08, SE = 0.05, p = 0.11); thus, mediation was not tested. Sensitivity analyses showed that effect sizes were similar across European and African American groups. This study suggests that inhibitory control could serve as a potential mechanism linking genetic differences to educational outcomes.

The practical utility of genetic screening in school settings

Can genetic screening be used to personalize education for students? Genome-wide association studies (GWAS) screen an individual's DNA for specific variations in their genome, and how said variations relate to specific traits. The variations can then be assigned a corresponding weight and summed to produce polygenic scores (PGS) for given traits. Though first developed for disease risk, PGS is now used to predict educational achievement. Using a novel simulation method, this paper examines if PGS could advance screening in schools, a goal of personalized education. Results show limited potential benefits for using PGS to personalize education for individual students. However, further analysis shows PGS can be effectively used alongside progress monitoring measures to screen for learning disability risk. Altogether, PGS is not useful in personalizing education for every child but has potential utility when used simultaneously with additional screening tools to help determine which children may struggle academically.

Duration of Untreated Psychosis in First-Episode Psychosis is not Associated With Common Genetic Variants for Major Psychiatric Conditions: Results From the Multi-Center EU-GEI Study

Duration of untreated psychosis (DUP) is associated with clinical outcomes in people with a diagnosis of first-episode psychosis (FEP), but factors associated with length of DUP are still poorly understood. Aiming to obtain insights into the possible biological impact on DUP, we report genetic analyses of a large multi-center phenotypically well-defined sample encompassing individuals with a diagnosis of FEP recruited from 6 countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study. Genetic propensity was measured using polygenic scores for schizophrenia (SZ-PGS), bipolar disorder (BD-PGS), major depressive disorder (MDD-PGS), and intelligence (IQ-PGS), which were calculated based on the results from the most recent genome-wide association meta-analyses. Following imputation for missing data and log transformation of DUP to handle skewedness, the association between DUP and polygenic scores (PGS), adjusting for important confounders, was investigated with multivariable linear regression models. The sample comprised 619 individuals with a diagnosis of FEP disorders with a median age at first contact of 29.0 years (interquartile range [IQR] = 22.0-38.0). The median length of DUP in the sample was 10.1 weeks (IQR = 3.8-30.8). One SD increases in SZ-PGS, BD-PGS, MDD-PGS or IQ-PGS were not significantly associated with the length of DUP. Our results suggest that genetic variation does not contribute to the DUP in patients with a diagnosis of FEP disorders.

From Genome-Wide to Environment-Wide: Capturing the Environome

Genome-wide association (GWA) studies have shown that genetic influences on individual differences in affect, behavior, and cognition are driven by thousands of DNA variants, each with very small effect sizes. Here, we propose taking inspiration from GWA studies for understanding and modeling the influence of the environment on complex phenotypes. We argue that the availability of DNA microarrays in genetic research is comparable with the advent of digital technologies in psychological science that enable collecting rich, naturalistic observations in real time of the environome, akin to the genome. These data can capture many thousand environmental elements, which we speculate each influence individual differences in affect, behavior, and cognition with very small effect sizes, akin to findings from GWA studies about DNA variants. We outline how the principles and mechanisms of genetic influences on psychological traits can be applied to improve the understanding and models of the environome.

Nurture might be nature: cautionary tales and proposed solutions

Across a wide range of studies, researchers often conclude that the home environment and children's outcomes are causally linked. In contrast, behavioral genetic studies show that parents influence their children by providing them with both environment and genes, meaning the environment that parents provide should not be considered in the absence of genetic influences, because that can lead to erroneous conclusions on causation. This article seeks to provide behavioral scientists with a synopsis of numerous methods to estimate the direct effect of the environment, controlling for the potential of genetic confounding. Ideally, using genetically sensitive designs can fully disentangle this genetic confound, but these require specialized samples. In the near future, researchers will likely have access to measured DNA variants (summarized in a polygenic scores), which could serve as a partial genetic control, but that is currently not an option that is ideal or widely available. We also propose a work around for when genetically sensitive data are not readily available: the Familial Control Method. In this method, one measures the same trait in the parents as the child, and the parents' trait is then used as a covariate (e.g., a genetic proxy). When these options are all not possible, we plead with our colleagues to clearly mention genetic confound as a limitation, and to be cautious with any environmental causal statements which could lead to unnecessary parent blaming.

Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction

Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used genomic structural equation modeling and prior genome-wide association studies (GWASs) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability. We identified 157 genome-wide-significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Noncognitive genetics were enriched in the same brain tissues and cell types as cognitive performance, but showed different associations with gray-matter brain volumes. Noncognitive genetics were further distinguished by associations with personality traits, less risky behavior and increased risk for certain psychiatric disorders. For socioeconomic success and longevity, noncognitive and cognitive-performance genetics demonstrated associations of similar magnitude. By conducting a GWAS of a phenotype that was not directly measured, we offer a view of genetic architecture of noncognitive skills influencing educational success.

Polygenic Scores in Developmental Psychology: Invite Genetics In, Leave Biodeterminism Behind

Polygenic scores offer developmental psychologists new methods for integrating genetic information into research on how people change and develop across the life span. Indeed, polygenic scores have correlations with developmental outcomes that rival correlations with traditional developmental psychology variables, such as family income. Yet linking people's genetics with differences between them in socially valued developmental outcomes, such as educational attainment, has historically been used to justify acts of state-sponsored violence. In this review, we emphasize that an interdisciplinary understanding of the environmental and structural determinants of social inequality, in conjunction with a transactional developmental perspective on how people interact with their environments, is critical to interpreting associations between polygenic measures and phenotypes. While there is a risk of misuse, early applications of polygenic scores to developmental psychology have already provided novel findings that identify environmental mechanisms of life course processes that can be used to diagnose inequalities in social opportunity.

The ego dampening influence of religion: evidence from behavioral genetics and psychology

Religion is a product of evolutionary and biological processes. Thus, understanding why some people are religious and how it impacts their everyday lives requires an integrated perspective. This review presents a theoretical framework incorporating recent findings on religious influences on the behavioral expression of genetic and psychological predispositions. We propose that religion may facilitate ego dampening, or weakening of the impact of one's internal drive, for the service of sociality. Evidence from gene-environment interaction and behavioral studies suggests that religious beliefs and practices may dampen more prepotent, self-focused motives that can be at odds with cooperation and social cohesion. The review underscores the importance of taking an interdisciplinary perspective to understand complex and fundamental questions about religion.

Using DNA From Mothers and Children to Study Parental Investment in Children's Educational Attainment

This study tested implications of new genetic discoveries for understanding the association between parental investment and children's educational attainment. A novel design matched genetic data from 860 British mothers and their children with home-visit measures of parenting: the E-Risk Study. Three findings emerged. First, both mothers' and children's education-associated genetics, summarized in a genome-wide polygenic score, were associated with parenting-a gene-environment correlation. Second, accounting for genetic influences slightly reduced associations between parenting and children's attainment-indicating some genetic confounding. Third, mothers' genetics were associated with children's attainment over and above children's own genetics, via cognitively stimulating parenting-an environmentally mediated effect. Findings imply that, when interpreting parents' effects on children, environmentalists must consider genetic transmission, but geneticists must also consider environmental transmission.

Interactions between Polygenic Scores and Environments: Methodological and Conceptual Challenges

Interest in the study of gene-environment interaction has recently grown due to the sudden availability of molecular genetic data-in particular, polygenic scores-in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened when used to integrate observational genomic and social science data. We articulate some of these key challenges, provide new perspectives on the study of gene-environment interactions, and end by offering some practical guidance for conducting research in this area. Given the sudden availability of well-powered polygenic scores, we anticipate a substantial increase in research testing for interaction between such scores and environments. The issues we discuss, if not properly addressed, may impact the enduring scientific value of gene-environment interaction studies.

Appropriate Use of Bifactor Analysis in Psychopathology Research: Appreciating Benefits and Limitations

Co-occurrence of psychiatric disorders is well documented. Recent quantitative efforts have moved toward an understanding of this phenomenon, with the general psychopathology or p-factor model emerging as the most prominent characterization. Over the past decade, bifactor model analysis has become increasingly popular as a statistical approach to describe common/shared and unique elements in psychopathology. However, recent work has highlighted potential problems with common approaches to evaluating and interpreting bifactor models. Here, we argue that bifactor models, when properly applied and interpreted, can be useful for answering some important questions in psychology and psychiatry research. We review problems with evaluating bifactor models based on global model fit statistics. We then describe more valid approaches to evaluating bifactor models and highlight 3 types of research questions for which bifactor models are well suited to answer. We also discuss the utility and limits of bifactor applications in genetic and neurobiological research. We close by comparing advantages and disadvantages of bifactor models with other analytic approaches and note that no statistical model is a panacea to rectify limitations of the research design used to gather data.

The Earliest Origins of Genetic Nurture: The Prenatal Environment Mediates the Association Between Maternal Genetics and Child Development

Observed genetic associations with educational attainment may be due to direct or indirect genetic influences. Recent work highlights genetic nurture, the potential effect of parents' genetics on their child's educational outcomes via rearing environments. To date, few mediating childhood environments have been tested. We used a large sample of genotyped mother-child dyads (N = 2,077) to investigate whether genetic nurture occurs via the prenatal environment. We found that mothers with more education-related genes are generally healthier and more financially stable during pregnancy. Further, measured prenatal conditions explain up to one third of the associations between maternal genetics and children's academic and developmental outcomes at the ages of 4 to 7 years. By providing the first evidence of prenatal genetic nurture and showing that genetic nurture is detectable in early childhood, this study broadens our understanding of how parental genetics may influence children and illustrates the challenges of within-person interpretation of existing genetic associations.

Using genetics for social science

Social science genetics is concerned with understanding whether, how and why genetic differences between human beings are linked to differences in behaviours and socioeconomic outcomes. Our review discusses the goals, methods, challenges and implications of this research endeavour. We survey how the recent developments in genetics are beginning to provide social scientists with a powerful new toolbox they can use to better understand environmental effects, and we illustrate this with several substantive examples. Furthermore, we examine how medical research can benefit from genetic insights into social-scientific outcomes and vice versa. Finally, we discuss the ethical challenges of this work and clarify several common misunderstandings and misinterpretations of genetic research on individual differences.

Genetic Associations Between Executive Functions and a General Factor of Psychopathology

OBJECTIVE

Symptoms of psychopathology covary across diagnostic boundaries, and a family history of elevated symptoms for a single psychiatric disorder places an individual at heightened risk for a broad range of other psychiatric disorders. Both twin-based and genome-wide molecular methods indicate a strong genetic basis for the familial aggregation of psychiatric disease. This has led researchers to prioritize the search for highly heritable childhood risk factors for transdiagnostic psychopathology. Cognitive abilities that involve the selective control and regulation of attention, known as executive functions (EFs), are a promising set of risk factors.

METHOD

In a population-based sample of child and adolescent twins (n = 1,913, mean age = 13.1 years), we examined genetic overlap between both EFs and general intelligence (g) and a transdiagnostic dimension of vulnerability to psychopathology, comprising symptoms of anxiety, depression, neuroticism, aggression, conduct disorder, oppositional defiant disorder, hyperactivity, and inattention. Psychopathology symptoms in children were rated by children and their parents.

RESULTS

Latent factors representing general EF and g were highly heritable (h2 = 86%-92%), and genetic influences on both sets of cognitive abilities were robustly correlated with transdiagnostic genetic influences on psychopathology symptoms (genetic r values ranged from -0.20 to -0.38).

CONCLUSION

General EF and g robustly index genetic risk for transdiagnostic symptoms of psychopathology in childhood. Delineating the developmental and neurobiological mechanisms underlying observed associations between cognitive abilities and psychopathology remains a priority for ongoing research.

Factors Moderating the Association Between Cannabis Use and Psychosis Risk: A Systematic Review

Increasing evidence indicates a relationship between cannabis use and psychosis risk. Specific factors, such as determinants of cannabis use or the genetic profile of cannabis users, appear to moderate this association. The present systematic review presents a detailed and up-to-date literature overview on factors that influence the relationship between cannabis use and psychosis risk. A systematic search was performed according to the PRISMA guidelines in MEDLINE and Embase, and 56 studies were included. The results show that, in particular, frequent cannabis use, especially daily use, and the consumption of high-potency cannabis are associated with a higher risk of developing psychosis. Moreover, several genotypes moderate the impact of cannabis use on psychosis risk, particularly those involved in the dopamine function, such as AKT1. Finally, cannabis use is associated with an earlier psychosis onset and increased risk of transition in individuals at a clinical high risk of psychosis. These findings indicate that changing cannabis use behavior could be a harm reduction strategy employed to lower the risk of developing psychosis. Future research should aim to further develop specific biomarkers and genetic profiles for psychosis, thereby contributing to the identification of individuals at the highest risk of developing a psychotic disorder.

Pathways Between a Polygenic Score for Educational Attainment and Higher Educational Attainment in an African American Sample

We investigated the extent to which performance on standardized achievement tests, executive function (EF), and aggression in childhood and adolescence accounted for the relationship between a polygenic score for educational attainment (EA PGS) and years of education in a community sample of African Americans. Participants (N = 402; 49.9% female) were initially recruited for an elementary school-based prevention trial in a Mid-Atlantic city and followed into adulthood. In first and twelfth grade, participants completed math and reading standardized tests and teachers reported on participants' aggression and EF, specifically impulsivity and concentration problems. At age 20, participants reported on their years of education and post-secondary degrees attained and their genotype was assayed from blood or buccal swabs. An EA PGS was created using results from a large-scale GWAS on EA. A higher EA PGS was associated with higher education indirectly via adolescent achievement. No other mediating mechanisms were significant. Adolescent academic achievement is thus one mechanism through which polygenic propensity for EA influences post-secondary education among urban, African American youth.

The Genetic Links to Anxiety and Depression (GLAD) Study: Online recruitment into the largest recontactable study of depression and anxiety

BACKGROUND

Anxiety and depression are common, debilitating and costly. These disorders are influenced by multiple risk factors, from genes to psychological vulnerabilities and environmental stressors, but research is hampered by a lack of sufficiently large comprehensive studies. We are recruiting 40,000 individuals with lifetime depression or anxiety and broad assessment of risks to facilitate future research.

METHODS

The Genetic Links to Anxiety and Depression (GLAD) Study (www.gladstudy.org.uk) recruits individuals with depression or anxiety into the NIHR Mental Health BioResource. Participants invited to join the study (via media campaigns) provide demographic, environmental and genetic data, and consent for medical record linkage and recontact.

RESULTS

Online recruitment was effective; 42,531 participants consented and 27,776 completed the questionnaire by end of July 2019. Participants' questionnaire data identified very high rates of recurrent depression, severe anxiety, and comorbidity. Participants reported high rates of treatment receipt. The age profile of the sample is biased toward young adults, with higher recruitment of females and the more educated, especially at younger ages.

DISCUSSION

This paper describes the study methodology and descriptive data for GLAD, which represents a large, recontactable resource that will enable future research into risks, outcomes, and treatment for anxiety and depression.

Comparing Within- and Between-Family Polygenic Score Prediction

Polygenic scores are a popular tool for prediction of complex traits. However, prediction estimates in samples of unrelated participants can include effects of population stratification, assortative mating, and environmentally mediated parental genetic effects, a form of genotype-environment correlation (rGE). Comparing genome-wide polygenic score (GPS) predictions in unrelated individuals with predictions between siblings in a within-family design is a powerful approach to identify these different sources of prediction. Here, we compared within- to between-family GPS predictions of eight outcomes (anthropometric, cognitive, personality, and health) for eight corresponding GPSs. The outcomes were assessed in up to 2,366 dizygotic (DZ) twin pairs from the Twins Early Development Study from age 12 to age 21. To account for family clustering, we used mixed-effects modeling, simultaneously estimating within- and between-family effects for target- and cross-trait GPS prediction of the outcomes. There were three main findings: (1) DZ twin GPS differences predicted DZ differences in height, BMI, intelligence, educational achievement, and ADHD symptoms; (2) target and cross-trait analyses indicated that GPS prediction estimates for cognitive traits (intelligence and educational achievement) were on average 60% greater between families than within families, but this was not the case for non-cognitive traits; and (3) much of this within- and between-family difference for cognitive traits disappeared after controlling for family socio-economic status (SES), suggesting that SES is a major source of between-family prediction through rGE mechanisms. These results provide insights into the patterns by which rGE contributes to GPS prediction, while ruling out confounding due to population stratification and assortative mating.

The Genome-Wide Study of Human Social Behavior and Its Application in Sociology

Recent years have seen a push for the integration of modern genomic methodologies with sociological inquiry. The inclusion of genomic approaches promises to help address long-standing issues in sociology (e.g., selection effects), as well as open up new avenues for future research. This article reviews the substantive findings of behavior genetic/genomic research, both from the recent past (e.g., twin/adoption studies, candidate gene studies) and from contemporary genomic analyses. The article primarily focuses on modern genomic methods available to sociologists (e.g., polygenic score analysis) and their various applications for answering sociological questions. The article concludes by considering a number of areas to which genomic researchers and sociologists should pay close attention if a consilience between genomic methods and sociological research is to be fully realized.