Predicting educational achievement from DNA

Gestational Age and Cognitive Development in Childhood

Importance

Preterm and early-term births are known risk factors for cognitive impairment, but studies that comprehensively include genetics, prenatal risk, and child-specific factors in high-risk populations are lacking.

Objective

To investigate the long-term cognitive outcomes of children born at various gestational ages, including very preterm (28-31 weeks), moderately preterm (32-33 weeks), late preterm (34-36 weeks), and early term (37-38 weeks), compared with full-term (≥39 weeks), accounting for genetics and other risk factors.

Design, Setting, and Participants

In this prospective, multicenter, longitudinal cross-sectional study, children aged 9 to 10 years were recruited from the Adolescent Brain and Cognitive Development Study between January 1, 2016, and December 31, 2018. Children underwent cognitive assessments using the National Institutes of Health Toolbox, Little Man Task, and Rey Auditory Verbal Learning Test. Polygenic scores for cognitive performance (cogPGS) were generated using results of a genome-wide association study from the genetic variants related to cognitive performance, educational attainment, and mathematical ability. Data analysis was performed from March to June 2024.

Exposure

Preterm (very preterm, moderately preterm, late preterm) and early-term birth status, with full-term birth status as the reference group.

Main Outcomes and Measures

The primary outcome of interest was the composite cognitive score, while secondary outcomes included individual cognitive domain scores. Hierarchical regression models were used to examine associations between gestational age and cognitive outcomes, adjusting for socioeconomic status (SES), cogPGS, prenatal risks, and child-specific factors.

Results

Among 5946 children included in the study (mean [SD] age, 9.9 [0.6] years; 3083 [51.8%] male), 55 (0.9%) were born very preterm, 110 (1.8%) were born moderately preterm, 454 (7.6%) were born late preterm, 261 (4.4%) were born early term, and 5066 (85.2%) were born full term. The cogPGS was positively associated with the composite cognitive score (β = 0.14; 95% CI, 0.12-0.17; P < .001) in the overall cohort. Compared with full-term children, those born moderately preterm had lower composite cognitive scores (β = -0.39; 95% CI, -0.55 to -0.22; P < .001) and lower scores in vocabulary (β = -0.36; 95% CI, -0.53 to -0.19; P < .001), working memory (β = -0.27; 95% CI, -0.45 to -0.09; P = .003), episodic memory (β = -0.32; 95% CI, -0.50 to -0.14; P < .001), and both short-delay recall (β = -0.36; 95% CI, -0.54 to -0.18; P < .001) and long-delay recall (β = -0.29; 95% CI, -0.48 to -0.11; P = .002). These associations were independent of SES, cogPGS, and other risk factors. Importantly, the lowest cognitive scores appeared among children born at 32 weeks or less. In contrast, late-preterm and early-term children performed similarly to full-term peers.

Conclusions and Relevance

In this cross-sectional study of children aged 9 to 10 years, moderately preterm birth was associated with long-term cognitive problems independent of SES, genetics, and other risk factors. These findings underscore the need for continued follow-up of all preterm children, with particular focus on those born before 34 weeks' gestational age, because they may face greater developmental challenges over time.

The Geneticization of Education and Its Bioethical Implications

The day has arrived that genetic tests for educational outcomes are available to the public. Today parents and students alike can send off a sample of blood or saliva and receive a 'genetic report' for a range of characteristics relevant to education, including intelligence, math ability, reading ability, and educational attainment. DTC availability is compounded by a growing "precision education" initiative, which proposes the application of DNA tests in schools to tailor educational curricula to children's genomic profiles. Here I argue that these happenings are a strong signal of the geneticization of education; the process by which educational abilities and outcomes come to be examined, understood, explained, and treated as primarily genetic characteristics. I clarify what it means to geneticize education, highlight the nature and limitations of the underlying science, explore both real and potential downstream bioethical implications, and make proposals for mitigating negative impacts.

Exploring the genetic prediction of academic underachievement and overachievement

Academic underachievement refers to school performance which falls below expectations. Focusing on the pivotal first stage of education, we explored a quantitative measure of underachievement using genomically predicted achievement delta (GPAΔ), which reflects the difference between observed and expected achievement predicted by genome-wide polygenic scores. We analyzed the relationship between GPAΔ at age 7 and achievement trajectories from ages 7 to 16, using longitudinal data from 4175 participants in the Twins Early Development Study to assess empirically the extent to which students regress to their genomically predicted levels by age 16. We found that the achievement of underachievers and overachievers who deviated from their genomic predictions at age 7 regressed on average by one-third towards their genomically predicted levels. We also found that GPAΔ at age 7 was as predictive of achievement trajectories as a traditional ability-based index of underachievement. Targeting GPAΔ underachievers might prove cost-effective because such interventions seem more likely to succeed by going with the genetic flow rather than swimming upstream, helping GPAΔ underachievers reach their genetic potential as predicted by their GPS. However, this is a hypothesis that needs to be tested in intervention research investigating whether GPAΔ underachievers respond better to the intervention than other underachievers. We discuss the practicality of genomic indices in assessing underachievement.

Changes in environmental exposures over decades may influence the genetic architecture of severe spermatogenic failure

STUDY QUESTION

Do the genetic determinants of idiopathic severe spermatogenic failure (SPGF) differ between generations?

SUMMARY ANSWER

Our data support that the genetic component of idiopathic SPGF is impacted by dynamic changes in environmental exposures over decades.

WHAT IS KNOWN ALREADY

The idiopathic form of SPGF has a multifactorial etiology wherein an interaction between genetic, epigenetic, and environmental factors leads to the disease onset and progression. At the genetic level, genome-wide association studies (GWASs) allow the analysis of millions of genetic variants across the genome in a hypothesis-free manner, as a valuable tool for identifying susceptibility risk loci. However, little is known about the specific role of non-genetic factors and their influence on the genetic determinants in this type of conditions.

STUDY DESIGN, SIZE, DURATION

Case-control genetic association analyses were performed including a total of 912 SPGF cases and 1360 unaffected controls.

PARTICIPANTS/MATERIALS, SETTING, METHODS

All participants had European ancestry (Iberian and German). SPGF cases were diagnosed during the last decade either with idiopathic non-obstructive azoospermia (n = 547) or with idiopathic non-obstructive oligozoospermia (n = 365). Case-control genetic association analyses were performed by logistic regression models considering the generation as a covariate and by in silico functional characterization of the susceptibility genomic regions.

MAIN RESULTS AND THE ROLE OF CHANCE

This analysis revealed 13 novel genetic association signals with SPGF, with eight of them being independent. The observed associations were mostly explained by the interaction between each lead variant and the age-group. Additionally, we established links between these loci and diverse non-genetic factors, such as toxic or dietary habits, respiratory disorders, and autoimmune diseases, which might potentially influence the genetic architecture of idiopathic SPGF.

LARGE SCALE DATA

GWAS data are available from the authors upon reasonable request.

LIMITATIONS, REASONS FOR CAUTION

Additional independent studies involving large cohorts in ethnically diverse populations are warranted to confirm our findings.

WIDER IMPLICATIONS OF THE FINDINGS

Overall, this study proposes an innovative strategy to achieve a more precise understanding of conditions such as SPGF by considering the interactions between a variable exposome through different generations and genetic predisposition to complex diseases.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the "Plan Andaluz de Investigación, Desarrollo e Innovación (PAIDI 2020)" (ref. PY20_00212, P20_00583), the Spanish Ministry of Economy and Competitiveness through the Spanish National Plan for Scientific and Technical Research and Innovation (ref. PID2020-120157RB-I00 funded by MCIN/ AEI/10.13039/501100011033), and the 'Proyectos I+D+i del Programa Operativo FEDER 2020' (ref. B-CTS-584-UGR20). ToxOmics-Centre for Toxicogenomics and Human Health, Genetics, Oncology and Human Toxicology, is also partially supported by the Portuguese Foundation for Science and Technology (Projects: UIDB/00009/2020; UIDP/00009/2020). The authors declare no competing interests.

TRIAL REGISTRATION NUMBER

N/A.

Infrastructuring Educational Genomics: Associations, Architectures, and Apparatuses

Technoscientific transformations in molecular genomics have begun to influence knowledge production in education. Interdisciplinary scientific consortia are seeking to identify 'genetic influences' on 'educationally relevant' traits, behaviors, and outcomes. This article examines the emerging 'knowledge infrastructure' of educational genomics, attending to the assembly and choreography of organizational associations, epistemic architecture, and technoscientific apparatuses implicated in the generation of genomic understandings from masses of bioinformation. As an infrastructure of datafied knowledge production, educational genomics is embedded in data-centered epistemologies and practices which recast educational problems in terms of molecular genetic associations-insights about which are deemed discoverable from digital bioinformation and potentially open to genetically informed interventions in policy and practice. While scientists claim to be 'opening the black box of the genome' and its association with educational outcomes, we open the black box of educational genomics itself as a source of emerging scientific authority. Data-intensive educational genomics does not straightforwardly 'discover' the biological bases of educationally relevant behaviors and outcomes. Rather, this knowledge infrastructure is also an experimental 'ontological infrastructure' supporting particular ways of knowing, understanding, explaining, and intervening in education, and recasting the human subjects of education as being surveyable and predictable through the algorithmic processing of bioinformation.

Attitudes towards genetic testing: The role of genetic literacy, motivated cognition, and socio-demographic characteristics

Understanding reasons for why people choose to have or not to have a genetic test is essential given the ever-increasing use of genetic technologies in everyday life. The present study explored the multiple drivers of people's attitudes towards genetic testing. Using the International Genetic Literacy and Attitudes Survey (iGLAS), we collected data on: (1) willingness to undergo testing; (2) genetic literacy; (3) motivated cognition; and (4) demographic and cultural characteristics. The 37 variables were explored in the largest to-date sample of 4311 participants from diverse demographic and cultural backgrounds. The results showed that 82% of participants were willing to undergo genetic testing for improved treatment; and over 73%-for research. The 35 predictor variables together explained only a small proportion of variance: 7%-in the willingness to test for Treatment; and 6%-for Research. The strongest predictors of willingness to undergo genetic testing were genetic knowledge and deterministic beliefs. Concerns about data misuse and about finding out unwanted health-related information were weakly negatively associated with willingness to undergo genetic testing. We also found some differences in factors linked to attitudes towards genetic testing across the countries included in this study. Our study demonstrates that decision-making regarding genetic testing is influenced by a large number of potentially interacting factors. Further research into these factors may help consumers to make decisions regarding genetic testing that are right for their specific circumstances.

School performance and genetic propensities for educational attainment and depression in the etiology of self-harm: a Danish population-based study

BACKGROUND

Poor school performance is linked to higher risks of self-harm. The association might be explained through genetic liabilities for depression or educational attainment. We investigated the association between school performance and self-harm in a population-based sample while assessing the potential influence of polygenic risk scores (PRSs) for depression (PRSMDD) and for educational attainment (PRSEDU).

METHOD

We conducted a follow-up study of individuals born 1987-98 and followed from age 18 until 2016. The total sample consisted of a case group (23,779 diagnosed with mental disorders; schizophrenia, bipolar disorder, depression, autism, and attention deficit hyperactivity disorder (ADHD) and a randomly sampled comparison group (n = 10,925). Genome-wide data were obtained from the Neonatal Screening Biobank and information on school performance, family psychiatric history, and socioeconomic status from national administrative registers.

RESULTS

Individuals in the top PRSMDD decile were at higher self-harm risk in the case group (IRR: 1.30; 95% CI 1.15-1.46), whereas individuals in the top PRSEDU decile were at lower self-harm risk (IRR: 0.63; 95% CI: 0.55-0.74). Poorer school performance was associated with higher self-harm risk in persons diagnosed with any mental disorder (IRR: 1.69; 95% CI: 1.44-1.99) and among the comparison group (IRR: 7.93; 95% CI: 4.47-15.18). Observed effects of PRSMDD and PRSEDU on self-harm risk were strongest for individuals with poor school performance.

CONCLUSION

Associations between PRSMDD and self-harm risk and between PRSEDU and self-harm risk were found. Nevertheless, these polygenic scores seem currently of limited clinical utility for identifying individuals at high self-harm risk.

Genome-wide association study of school grades identifies genetic overlap between language ability, psychopathology and creativity

Cognitive functions of individuals with psychiatric disorders differ from that of the general population. Such cognitive differences often manifest early in life as differential school performance and have a strong genetic basis. Here we measured genetic predictors of school performance in 30,982 individuals in English, Danish and mathematics via a genome-wide association study (GWAS) and studied their relationship with risk for six major psychiatric disorders. When decomposing the school performance into math and language-specific performances, we observed phenotypically and genetically a strong negative correlation between math performance and risk for most psychiatric disorders. But language performance correlated positively with risk for certain disorders, especially schizophrenia, which we replicate in an independent sample (n = 4547). We also found that the genetic variants relating to increased risk for schizophrenia and better language performance are overrepresented in individuals involved in creative professions (n = 2953) compared to the general population (n = 164,622). The findings together suggest that language ability, creativity and psychopathology might stem from overlapping genetic roots.

Statistical Methods for Disease Risk Prediction with Genotype Data

Single-nucleotide polymorphism (SNP) is the basic unit to understand the heritability of complex traits. One attractive application of the susceptible SNPs is to construct prediction models for assessing disease risk. Here, we introduce prediction methods for human traits using SNPs data, including the polygenic risk score (PRS), linear mixed models (LMMs), penalized regressions, and methods for controlling population stratification.

What is driving the relationship between height and cognition? Evidence from the Twins Early Development Study

Taller children tend to have better cognitive ability, and the relationship between height and cognition has been proposed as an explanation for the height-wage labor market premium. Height-cognition associations may arise due to social factors that favor taller individuals or be driven by "common factors" that are correlated with height and cognition. Indeed, there is now evidence of a genetic correlation between height and cognition that provides specific evidence for this concern. We examine whether genetic factors explain the relationship by estimating associations between childhood height and cognition in the Twins Early Development Study. We find that height is associated with better cognition even after controlling for genetic and environmental factors shared by twins. The association between height and cognition within fraternal twin pairs is also robust to controlling for individual genetic predictors of height and cognition. These results suggest that genetic factors are not solely responsible for driving the relationship between height and cognition.

A population-wide gene-environment interaction study on how genes, schools, and residential areas shape achievement

A child's environment is thought to be composed of different levels that interact with their individual genetic propensities. However, studies have not tested this theory comprehensively across multiple environmental levels. Here, we quantify the contributions of child, parent, school, neighbourhood, district, and municipality factors to achievement, and investigate interactions between polygenic indices for educational attainment (EA-PGI) and environmental levels. We link population-wide administrative data on children's standardised test results, schools and residential identifiers to the Norwegian Mother, Father, and Child Cohort Study (MoBa), which includes >23,000 genotyped parent-child trios. We test for gene-environment interactions using multilevel models with interactions between EA-PGI and random effects for school and residential environments (thus remaining agnostic to specific features of environments). We use parent EA-PGI to control for gene-environment correlation. We found an interaction between students' EA-PGI and schools suggesting compensation: higher-performing schools can raise overall achievement without leaving children with lower EA-PGI behind. Differences between schools matter more for students with lower EA-PGI, explaining 4 versus 2% of the variance in achievement for students 2 SD below versus 2 SD above the mean EA-PGI. Neighbourhood, district, and municipality variation contribute little to achievement (<2% of the variance collectively), and do not interact with children's individual EA-PGI. Policy to reduce social inequality in achievement in Norway should focus on tackling unequal support across schools for children with difficulties.

Educational attainment polygenic scores, socioeconomic factors, and cortical structure in children and adolescents

Genome‐wide polygenic scores for educational attainment (PGS‐EA) and socioeconomic factors, which are correlated with each other, have been consistently associated with academic achievement and general cognitive ability in children and adolescents. Yet, the independent associations of PGS‐EA and socioeconomic factors with specific underlying factors at the neural and neurocognitive levels are not well understood. The main goals of this study were to examine the unique contributions of PGS‐EA and parental education to cortical structure and neurocognitive skills in children and adolescents, and the associations among PGS‐EA, cortical structure, and neurocognitive skills. Participants were typically developing 3‐ to 21‐year‐olds (53% male; N = 391). High‐resolution, T1‐weighted magnetic resonance imaging data were acquired, and cortical thickness (CT) and surface area (SA) were measured. PGS‐EA were computed based on the EA3 genome‐wide association study of educational attainment. Participants completed executive function, vocabulary, and episodic memory tasks. Higher PGS‐EA and parental education were independently and significantly associated with greater total SA and vocabulary. Higher PGS‐EA was significantly associated with greater SA in the left medial orbitofrontal gyrus and inferior frontal gyrus, which was associated with higher executive function. Higher parental education was significantly associated with greater SA in the left parahippocampal gyrus after accounting for PGS‐EA and total brain volume. These findings suggest that education‐linked genetics may influence SA in frontal regions, leading to variability in executive function. Associations of parental education with cortical structure in children and adolescents remained significant after controlling for PGS‐EA, a source of genetic confounding.

Three legs of the missing heritability problem

The so-called 'missing heritability problem' is often characterized by behavior geneticists as a numerical discrepancy between alternative kinds of heritability. For example, while 'traditional heritability' derived from twin and family studies indicates that approximately ∼50% of variation in intelligence is attributable to genetics, 'SNP heritability' derived from genome-wide association studies indicates that only ∼10% of variation in intelligence is attributable to genetics. This 40% gap in variance accounted for by alternative kinds of heritability is frequently referred to as what's "missing." Philosophers have picked up on this reading, suggesting that "dissolving" the missing heritability problem is merely a matter of closing the numerical gap between traditional and molecular kinds of heritability. We argue that this framing of the problem undervalues the severity of the many challenges to scientific understanding of the "heritability" of human behavior. On our view, resolving the numerical discrepancies between alternative kinds of heritability will do little to advance scientific explanation and understanding of behavior genetics. Thus, we propose a new conceptual framework of the missing heritability problem that comprises three independent methodological and explanatory challenges: the numerical gap, the prediction gap, and the mechanism gap.

Polygenic Risk Scores for Blood Pressure to Assess the Risk of Severe Bevacizumab-Induced Hypertension in Cancer Patients (Alliance)

Hypertension is a common bevacizumab-induced toxicity. No markers are available to predict patients at risk of developing hypertension. We hypothesized that genetic risk of essential hypertension, as measured by a blood pressure polygenic risk score (PRS), would be associated with risk of severe bevacizumab-induced hypertension. PRSs were calculated for 1,027 bevacizumab-treated patients of European descent with cancer from four clinical trials (Alliance for Clinical Trials in Oncology (Alliance) / Cancer and Leukemia Group B (CALGB) 80303, 40503, 90401, 40502) using summary systolic blood pressure (SBP) and diastolic blood pressure (DBP) genome-wide association results obtained from 757,601 individuals of European descent. The association between PRS and grade 3 bevacizumab-induced hypertension (Common Toxicity Criteria for Adverse Events version 3) in each trial was performed by multivariable logistic regression. Fixed-effect meta-analyses odds ratios (ORs) per standard deviation (SD) of the association of PRS (quantitative) and hypertension across trials were estimated by inverse-variance weighting. PRSs were additionally stratified into quintiles, with the bottom quintile as the referent group. The OR of the association between hypertension and each quintile vs. the referent group was determined by logistic regression. The most significant PRS (quantitative)-hypertension association included up to 67 single-nucleotide variants (SNPs) associated with SBP (P = 0.0077, OR per SD = 1.31, 95% confidence interval (CI), 1.07-1.60), and up to 53 SNPs associated with DBP (P = 0.0209, OR per SD = 1.27, 95% CI, 1.04-1.56). Patients in the top quintile had a higher risk of developing bevacizumab-induced hypertension compared with patients in the bottom quintile using SNPs associated with SBP (P = 4.75 × 10^-4 , OR = 3.72, 95% CI, 1.84-8.16) and DBP (P = 0.076, OR = 1.83, 95% CI, 0.95-3.64). Genetic variants associated with essential hypertension, mainly SBP, increase the risk of severe bevacizumab-induced hypertension.

Genetic associations with learning over 100 days of practice

Cognitive performance is both heritable and sensitive to environmental inputs and sustained practice over time. However, it is currently unclear how genetic effects on cognitive performance change over the course of learning. We examine how polygenic scores (PGS) created from genome-wide association studies of educational attainment and cognitive performance are related to improvements in performance across nine cognitive tests (measuring perceptual speed, working memory, and episodic memory) administered to 131 adults (N = 51, ages = 20-31, and N = 80, ages = 65-80 years) repeatedly across 100 days. We observe that PGS associations with performance on a given task can change over the course of learning, with the specific pattern of change in associations differing across tasks. PGS correlations with pre-test to post-test scores may mask variability in how soon learning occurs over the course of practice. The associations between PGS and learning do not appear to simply reconstitute patterns of association between baseline performance and subsequent learning. Associations involving PGSs, however, were small with large confidence intervals. Intensive longitudinal research such as that described here may be of substantial value for clarifying the genetics of learning when implemented as far larger scale.

Education and Income Show Heterogeneous Relationships to Lifespan Brain and Cognitive Differences Across European and US Cohorts

Higher socio-economic status (SES) has been proposed to have facilitating and protective effects on brain and cognition. We ask whether relationships between SES, brain volumes and cognitive ability differ across cohorts, by age and national origin. European and US cohorts covering the lifespan were studied (4-97 years, N = 500 000; 54 000 w/brain imaging). There was substantial heterogeneity across cohorts for all associations. Education was positively related to intracranial (ICV) and total gray matter (GM) volume. Income was related to ICV, but not GM. We did not observe reliable differences in associations as a function of age. SES was more strongly related to brain and cognition in US than European cohorts. Sample representativity varies, and this study cannot identify mechanisms underlying differences in associations across cohorts. Differences in neuroanatomical volumes partially explained SES-cognition relationships. SES was more strongly related to ICV than to GM, implying that SES-cognition relations in adulthood are less likely grounded in neuroprotective effects on GM volume in aging. The relatively stronger SES-ICV associations rather are compatible with SES-brain volume relationships being established early in life, as ICV stabilizes in childhood. The findings underscore that SES has no uniform association with, or impact on, brain and cognition.

Genetic effects on educational attainment in Hungary

INTRODUCTION

Educational attainment is a substantially heritable trait, and it has recently been linked to specific genetic variants by genome-wide association studies (GWASs). However, the effects of such genetic variants are expected to vary across environments, including countries and historical eras.

METHODS

We used polygenic scores (PGSs) to assess molecular genetic effects on educational attainment in Hungary, a country in the Central Eastern European region where behavioral genetic studies are in general scarce and molecular genetic studies of educational attainment have not been previously published.

RESULTS

We found that the PGS is significantly associated with the attainment of a college degree as well as the number of years in education in a sample of Hungarian study participants (N = 829). PGS effect sizes were not significantly different when compared to an English (N = 976) comparison sample with identical measurement protocols. In line with previous Estonian findings, we found higher PGS effect sizes in Hungarian, but not in English participants who attended higher education after the fall of Communism, although we lacked statistical power for this effect to reach significance.

DISCUSSION

Our results provide evidence that polygenic scores for educational attainment have predictive value in culturally diverse European populations.

Socioeconomic origin, future expectations, and educational achievement: A longitudinal three-generation study of the persistence of family advantage

Expectations about the future direct effort in goal-oriented action and may influence a range of life course outcomes, including educational attainment. Here we investigate whether such expectations are implicated in the dynamics underlying the persistence of educational advantage across family generations, and whether such dynamics have changed in recent decades in view of historical change. Focusing on the role of domain-specific (educational) and general (optimism and control) expectations, we examine parallels across parent-child cohorts in (a) the relationships between parental socioeconomic status (SES) and children's future expectations and (b) the associations between children's future expectations and their academic achievement. We estimate structural equation models using data from the prospective multigenerational Youth Development Study (N = 422 three-generation triads [G1-G2-G3]; G1 Mage in 1988 = 41.0 years, G2 Mage in 1989 = 14.7 years, G3 Mage in 2011 = 15.8 years; G2 White in 1989 = 66.4%, G3 White in 2011 = 64.4%; G1 mean annual household income, converted to 2008 equivalents = $41,687, G2 mean annual household income in 2008 dollars = $42,962; G1 mode of educational attainment = high school, G2 mode of educational attainment = some college). We find intergenerational similarity in the relationships between parental educational attainment and children's future expectations. Children's educational expectations strongly predicted their academic achievement in the second generation, but not in the third generation. With educational expansion, the more recent cohort had higher educational expectations that were less strongly related to achievement. Overall, the findings reveal dynamics underlying the persistence of educational success across generations. The role of future expectations in this intergenerational process varies across historical time, confirming a central conclusion of life span developmental psychology and life course sociological research that individual functioning is influenced by sociocultural contexts. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Genetic and environmental contributions to IQ in adoptive and biological families with 30-year-old offspring

While adoption studies have provided key insights into the influence of the familial environment on IQ scores of adolescents and children, few have followed adopted offspring long past the time spent living in the family home. To improve confidence about the extent to which shared environment exerts enduring effects on IQ, we estimated genetic and environmental effects on adulthood IQ in a unique sample of 486 biological and adoptive families. These families, tested previously on measures of IQ when offspring averaged age 15, were assessed a second time nearly two decades later ( M offspring age = 32 years). We estimated the proportions of the variance in IQ attributable to environmentally mediated effects of parental IQs, sibling-specific shared environment, and gene-environment covariance to be .01 [95% CI .00, .02], .04 [95% CI .00, .15], and .03 [95% CI .00, .07] respectively; these components jointly accounted for 8 percent of the IQ variance in adulthood. The heritability was estimated to be .42 [95% CI .21, .64]. Together, these findings provide further evidence for the predominance of genetic influences on adult intelligence over any other systematic source of variation.

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.

Three genetic-environmental networks for human personality

Phylogenetic, developmental, and brain-imaging studies suggest that human personality is the integrated expression of three major systems of learning and memory that regulate (1) associative conditioning, (2) intentionality, and (3) self-awareness. We have uncovered largely disjoint sets of genes regulating these dissociable learning processes in different clusters of people with (1) unregulated temperament profiles (i.e., associatively conditioned habits and emotional reactivity), (2) organized character profiles (i.e., intentional self-control of emotional conflicts and goals), and (3) creative character profiles (i.e., self-aware appraisal of values and theories), respectively. However, little is known about how these temperament and character components of personality are jointly organized and develop in an integrated manner. In three large independent genome-wide association studies from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phenotypic networks of temperament and character and also the genetic networks with which they are associated. We found three clusters of similar numbers of people with distinct combinations of temperament and character profiles. Their associated genetic and environmental networks were largely disjoint, and differentially related to distinct forms of learning and memory. Of the 972 genes that mapped to the three phenotypic networks, 72% were unique to a single network. The findings in the Finnish discovery sample were blindly and independently replicated in samples of Germans and Koreans. We conclude that temperament and character are integrated within three disjoint networks that regulate healthy longevity and dissociable systems of learning and memory by nearly disjoint sets of genetic and environmental influences.

The role of parental genotype in predicting offspring years of education: evidence for genetic nurture

Similarities between parent and offspring are widespread in psychology; however, shared genetic variants often confound causal inference for offspring outcomes. A polygenic score (PGS) derived from genome-wide association studies (GWAS) can be used to test for the presence of parental influence that controls for genetic variants shared across generations. We use a PGS for educational attainment (EA3; N ≈ 750 thousand) to predict offspring years of education in a sample of 2517 twins and both parents. We find that within families, the dizygotic twin with the higher PGS is more likely to attain higher education (unstandardized β = 0.32; p < 0.001). Additionally, however, we find an effect of parental genotype on offspring outcome that is independent of the offspring's own genotype; this raises the variance explained in offspring years of education from 9.3 to 11.1% (∆R² = 0.018, p < 0.001). Controlling for parental IQ or socioeconomic status substantially attenuated or eliminated this effect of parental genotype. These findings suggest a role of environmental factors affected by heritable characteristics of the parents in fostering offspring years of education.

Genetic interactions with stressful environments in depression and addiction

Stress is the most important proximal precipitant of depression, yet most large genome-wide association studies (GWAS) do not include stress as a variable. Here, we review how gene × environment (G × E) interaction might impede the discovery of genetic factors, discuss two examples of G × E interaction in depression and addiction, studies incorporating high-stress environments, as well as upcoming waves of genome-wide environment interaction studies (GWEIS). We discuss recent studies which have shown that genetic distributions can be affected by social factors such as migrations and socioeconomic background. These distinctions are not just academic but have practical consequences. Owing to interaction with the environment, genetic predispositions to depression should not be viewed as unmodifiable destiny. Patients may genetically differ not just in their response to drugs, as in the now well-recognised field of pharmacogenetics, but also in how they react to stressful environments and how they are affected by behavioural therapies.

Phenotypically independent profiles relevant to mental health are genetically correlated

Genome-wide association studies (GWAS) and family-based studies have revealed partly overlapping genetic architectures between various psychiatric disorders. Given clinical overlap between disorders, our knowledge of the genetic architectures underlying specific symptom profiles and risk factors is limited. Here, we aimed to derive distinct profiles relevant to mental health in healthy individuals and to study how these genetically relate to each other and to common psychiatric disorders. Using independent component analysis, we decomposed self-report mental health questionnaires from 136,678 healthy individuals of the UK Biobank, excluding data from individuals with a diagnosed neurological or psychiatric disorder, into 13 distinct profiles relevant to mental health, capturing different symptoms as well as social and risk factors underlying reduced mental health. Utilizing genotypes from 117,611 of those individuals with White British ancestry, we performed GWAS for each mental health profile and assessed genetic correlations between these profiles, and between the profiles and common psychiatric disorders and cognitive traits. We found that mental health profiles were genetically correlated with a wide range of psychiatric disorders and cognitive traits, with strongest effects typically observed between a given mental health profile and a disorder for which the profile is common (e.g. depression symptoms and major depressive disorder, or psychosis and schizophrenia). Strikingly, although the profiles were phenotypically uncorrelated, many of them were genetically correlated with each other. This study provides evidence that statistically independent mental health profiles partly share genetic underpinnings and show genetic overlap with psychiatric disorders, suggesting that shared genetics across psychiatric disorders cannot be exclusively attributed to the known overlapping symptomatology between the disorders.

An examination of genetic and environmental factors related to negative personality traits, educational attainment, and economic success

Personality variables are associated with educational attainment and socioeconomic outcomes. In this study we incorporated a polygenic score derived from the largest genome-wide association study (GWAS) of educational attainment to date (Lee et al., 2018) into the Interactionist Model of R. D. Conger, Martin, and Masarik (2021) that describes the influence of socioeconomic factors on individual development. The inclusion of a polygenic score predictive of educational attainment (PS-Edu) into this model, and the use of the multigeneration, longitudinal Family Transitions Project (FTP) provide a unique opportunity to investigate genetic and environmental influences on the development of negative personality traits and educational and economic outcomes. The FTP is a three-generation sample. This study utilized data from the first generation (G1; mean age 40 at initiation of the FTP) and second generation (G2; assessed at mean ages 18 and 30). Participants are approximately 50% female, 99% of European ancestry, primarily from lower to middle class SES. PS-Edu was significantly correlated with educational attainment in both generations of the FTP, accounting for 4.1 to 6.7% of the variance. Findings confirm that PS-Edu is a complex genetic index that is correlated with all of the socioeconomic constructs in the model. Results suggest potential gene-environment correlation or common genetic influences underlie associations among parenting investments, negative personality traits, and educational attainment. Genetic variance captured by PS-Edu was mediated substantially through G1 parental investments. Although study limitations warrant cautious interpretation, we demonstrate the promise of including polygenic scores in developmental models to better understand genetic and environmental influences on human development. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Assessment of Posttraumatic Stress Disorder and Educational Achievement in Sweden

IMPORTANCE

Posttraumatic stress disorder (PTSD) has been associated with impaired educational performance. Previous studies on the disorder could not control for important measured and unmeasured confounders.

OBJECTIVE

To prospectively investigate the association between PTSD and objective indicators of educational attainment across the life span, controlling for familial factors shared by full siblings, psychiatric comorbidity, and general cognitive ability.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cohort study included 2 244 193 individuals born in Sweden between January 1, 1973, and December 31, 1997, who were followed-up until December 31, 2013. Clusters of full siblings were used to account for familial factors. Data analyses were conducted between December 2018 and May 2020.

EXPOSURE

International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses of PTSD in the Swedish National Patient Register.

MAIN OUTCOMES AND MEASURES

Eligibility to access upper secondary education after finishing compulsory education, finishing upper secondary education, starting a university degree, and finishing a university degree.

RESULTS

Of the final cohort of 2 244 193 individuals (1 151 414 [51.3%] men) included in the analysis, 1 425 326 were assessed for finishing compulsory education (919 with PTSD), 2 001 944 for finishing upper secondary education (2013 with PTSD), and 1 796 407 and 1 356 741 for starting and finishing a university degree (2243 and 2254 with PTSD, respectively). Posttraumatic stress disorder was associated with lower odds of achieving each of the educational milestones during the study period, including 82% lower odds of finishing compulsory education (adjusted odds ratio [aOR], 0.18; 95% CI, 0.15-0.20), 87% lower odds of finishing upper secondary education (aOR, 0.13; 95% CI, 0.12-0.14), 68% lower odds of starting a university degree (aOR, 0.32; 95% CI, 0.28-0.35), and 73% lower odds of finishing a university degree (aOR, 0.27; 95% CI, 0.23-0.31). Estimates in the sibling comparison were attenuated (aOR range, 0.22-0.53) but remained statistically significant. Overall, excluding psychiatric comorbidities and adjusting for the successful completion of the previous milestone and general cognitive ability did not statistically significantly alter the magnitude of the associations.

CONCLUSIONS AND RELEVANCE

Posttraumatic stress disorder was associated with educational impairment across the life span, and the associations were not entirely explained by shared familial factors, psychiatric comorbidity, or general cognitive ability. This finding highlights the importance of implementing early trauma-informed interventions in schools and universities to minimize the long-term socioeconomic consequences of academic failure in individuals with PTSD.

Resurecting raciology? Genetic ethnology and pre-1945 anthropological race classification

This article places the current high-profile and controversial scientific project that I call 'genetic ethnology' within the same two-century tradition of biologically classifying modern peoples as pre-1945 race anthropology. Similarities in how these two biological projects have combined political and scientific agendas raise questions about the liberalism of genetics and stimulate concerns that genetic constructions of human difference might revive a politics of hate, division and hierarchy. The present article however goes beyond existing work that links modern genetics with race anthropology. It systematically compares their many similar practices and organisational features, showing that both projects were political-scientific syntheses. Studying how the origins, geography, filiations, 'travels and encounters of our ancestors' affect 'current genetic variation', both seem to have responded to a continuous public demand for biologists to explain the histories of politically significant peoples and give them a scientific basis. I challenge habitual contrasts between apolitical scientific genetics and racist pseudoscience and use race anthropology as a parable for how, in the era of Brexit and Trump, right-wing identity politics might infect genetic ethnology. I argue however that although biology-based identities carry risks of essentialism and determinism, the practices and organisation of classification pose greater political dangers.

Polygenic predictors of age-related decline in cognitive ability

Polygenic scores can be used to distil the knowledge gained in genome-wide association studies for prediction of health, lifestyle, and psychological factors in independent samples. In this preregistered study, we used fourteen polygenic scores to predict variation in cognitive ability level at age 70, and cognitive change from age 70 to age 79, in the longitudinal Lothian Birth Cohort 1936 study. The polygenic scores were created for phenotypes that have been suggested as risk or protective factors for cognitive ageing. Cognitive abilities within older age were indexed using a latent general factor estimated from thirteen varied cognitive tests taken at four waves, each three years apart (initial n = 1091 age 70; final n = 550 age 79). The general factor indexed over two-thirds of the variance in longitudinal cognitive change. We ran additional analyses using an age-11 intelligence test to index cognitive change from age 11 to age 70. Several polygenic scores were associated with the level of cognitive ability at age-70 baseline (range of standardized β-values = -0.178 to 0.302), and the polygenic score for education was associated with cognitive change from childhood to age 70 (standardized β = 0.100). No polygenic scores were statistically significantly associated with variation in cognitive change between ages 70 and 79, and effect sizes were small. However, APOE e4 status made a significant prediction of the rate of cognitive decline from age 70 to 79 (standardized β = -0.319 for carriers vs. non-carriers). The results suggest that the predictive validity for cognitive ageing of polygenic scores derived from genome-wide association study summary statistics is not yet on a par with APOE e4, a better-established predictor.

Separating Measured Genetic and Environmental Effects: Evidence Linking Parental Genotype and Adopted Child Outcomes

There has been widespread adoption of genome wide summary scores (polygenic scores) as tools for studying the importance of genetics and associated life course mechanisms across a range of demographic and socioeconomic outcomes. However, an often unacknowledged issue with these studies is that parental genetics impact both child environments and child genetics, leaving the effects of polygenic scores difficult to interpret. This paper uses multi-generational data containing polygenic scores for parents (n = 7193) and educational outcomes for adopted (n = 855) and biological (n = 20,939) children, many raised in the same families, which allows us to separate the influence of parental polygenic scores on children outcomes between environmental (adopted children) and environmental and genetic (biological children) effects. Our results complement recent work on "genetic nurture" by showing associations of parental polygenic scores with adopted children's schooling, providing additional evidence that polygenic scores combine genetic and environmental influences and that research designs are needed to separate these estimated impacts.

Separating Measured Genetic and Environmental Effects: Evidence Linking Parental Genotype and Adopted Child Outcomes

There has been widespread adoption of genome wide summary scores (polygenic scores) as tools for studying the importance of genetics and associated life course mechanisms across a range of demographic and socioeconomic outcomes. However, an often unacknowledged issue with these studies is that parental genetics impact both child environments and child genetics, leaving the effects of polygenic scores difficult to interpret. This paper uses multi-generational data containing polygenic scores for parents (n = 7193) and educational outcomes for adopted (n = 855) and biological (n = 20,939) children, many raised in the same families, which allows us to separate the influence of parental polygenic scores on children outcomes between environmental (adopted children) and environmental and genetic (biological children) effects. Our results complement recent work on "genetic nurture" by showing associations of parental polygenic scores with adopted children's schooling, providing additional evidence that polygenic scores combine genetic and environmental influences and that research designs are needed to separate these estimated impacts.

Tutorial: a guide to performing polygenic risk score analyses

A polygenic score (PGS) or polygenic risk score (PRS) is an estimate of an individual's genetic liability to a trait or disease, calculated according to their genotype profile and relevant genome-wide association study (GWAS) data. While present PRSs typically explain only a small fraction of trait variance, their correlation with the single largest contributor to phenotypic variation-genetic liability-has led to the routine application of PRSs across biomedical research. Among a range of applications, PRSs are exploited to assess shared etiology between phenotypes, to evaluate the clinical utility of genetic data for complex disease and as part of experimental studies in which, for example, experiments are performed that compare outcomes (e.g., gene expression and cellular response to treatment) between individuals with low and high PRS values. As GWAS sample sizes increase and PRSs become more powerful, PRSs are set to play a key role in research and stratified medicine. However, despite the importance and growing application of PRSs, there are limited guidelines for performing PRS analyses, which can lead to inconsistency between studies and misinterpretation of results. Here, we provide detailed guidelines for performing and interpreting PRS analyses. We outline standard quality control steps, discuss different methods for the calculation of PRSs, provide an introductory online tutorial, highlight common misconceptions relating to PRS results, offer recommendations for best practice and discuss future challenges.

Cleft lip/palate and educational attainment: cause, consequence or correlation? A Mendelian randomization study

BACKGROUND

Previous studies have found that children born with a non-syndromic orofacial cleft have lower-than-average educational attainment. Differences could be due to a genetic predisposition to low intelligence and academic performance, factors arising due to the cleft phenotype (such as social stigmatization, impaired speech/language development) or confounding by the prenatal environment. A clearer understanding of this mechanism will inform interventions to improve educational attainment in individuals born with a cleft, which could substantially improve their quality of life. We assessed evidence for the hypothesis that common variant genetic liability to non-syndromic cleft lip with or without cleft palate (nsCL/P) influences educational attainment.

METHODS

We performed a genome-wide association study (GWAS) meta-analysis of nsCL/P with 1692 nsCL/P cases and 4259 parental and unrelated controls. Using GWAS summary statistics, we performed Linkage Disequilibrium (LD)-score regression to estimate the genetic correlation between nsCL/P, educational attainment (GWAS n = 766 345) and intelligence (GWAS n = 257 828). We used two-sample Mendelian randomization to evaluate the causal effects of genetic liability to nsCL/P on educational attainment and intelligence.

RESULTS

There was limited evidence for shared genetic aetiology or causal relationships between nsCL/P and educational attainment [genetic correlation (rg) -0.05, 95% confidence interval (CI) -0.12 to 0.01, P 0.13; MR estimate (βMR) -0.002, 95% CI -0.009 to 0.006, P 0.679) or intelligence (rg -0.04, 95% CI -0.13 to 0.04, P 0.34; βMR -0.009, 95% CI -0.02 to 0.002, P 0.11).

CONCLUSIONS

Common variants are unlikely to predispose individuals born with nsCL/P to low educational attainment or intelligence. This is an important first step towards understanding the aetiology of low educational attainment in this group.

The Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology

Individual differences in educational attainment are linked to differences in intelligence, and predict important social, economic, and health outcomes. Previous studies have found common genetic factors that influence educational achievement, cognitive performance and total brain volume (i.e., brain size). Here, in a large sample of participants from the UK Biobank, we investigate the shared genetic basis between educational attainment and fine-grained cerebral cortical morphological features, and associate this genetic variation with a related aspect of cognitive ability. Importantly, we execute novel statistical methods that enable high-dimensional genetic correlation analysis, and compute high-resolution surface maps for the genetic correlations between educational attainment and vertex-wise morphological measurements. We conduct secondary analyses, using the UK Biobank verbal-numerical reasoning score, to confirm that variation in educational attainment that is genetically correlated with cortical morphology is related to differences in cognitive performance. Our analyses relate the genetic overlap between cognitive ability and cortical thickness measurements to bilateral primary motor cortex as well as predominantly left superior temporal cortex and proximal regions. These findings extend our understanding of the neurobiology that connects genetic variation to individual differences in educational attainment and cognitive performance.

Population phenomena inflate genetic associations of complex social traits

Heritability, genetic correlation, and genetic associations estimated from samples of unrelated individuals are often perceived as confirmation that genotype causes the phenotype(s). However, these estimates can arise from indirect mechanisms due to population phenomena including population stratification, dynastic effects, and assortative mating. We introduce these, describe how they can bias or inflate genotype-phenotype associations, and demonstrate methods that can be used to assess their presence. Using data on educational achievement and parental socioeconomic position as an exemplar, we demonstrate that both heritability and genetic correlation may be biased estimates of the causal contribution of genotype. These results highlight the limitations of genotype-phenotype estimates obtained from samples of unrelated individuals. Use of these methods in combination with family-based designs may offer researchers greater opportunities to explore the mechanisms driving genotype-phenotype associations and identify factors underlying bias in estimates.

Cognitive ability and education: How behavioural genetic research has advanced our knowledge and understanding of their association

Cognitive ability and educational success predict positive outcomes across the lifespan, from higher earnings to better health and longevity. The shared positive outcomes associated with cognitive ability and education are emblematic of the strong interconnections between them. Part of the observed associations between cognitive ability and education, as well as their links with wealth, morbidity and mortality, are rooted in genetic variation. The current review evaluates the contribution of decades of behavioural genetic research to our knowledge and understanding of the biological and environmental basis of the association between cognitive ability and education. The evidence reviewed points to a strong genetic basis in their association, observed from middle childhood to old age, which is amplified by environmental experiences. In addition, the strong stability and heritability of educational success are not driven entirely by cognitive ability. This highlights the contribution of other educationally relevant noncognitive characteristics. Considering both cognitive and noncognitive skills as well as their biological and environmental underpinnings will be fundamental in moving towards a comprehensive, evidence-based model of education.

Sibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabis

BACKGROUND AND AIMS

The associations between low educational attainment and substance use disorders (SUDs) may be related to a common genetic vulnerability. We aimed to elucidate the associations between polygenic scores for educational attainment and clinical criterion counts for three SUDs (alcohol, nicotine and cannabis).

DESIGN

Polygenic association and sibling comparison methods. The latter strengthens inferences in observational research by controlling for confounding factors that differ between families.

SETTING

Six sites in the United States.

PARTICIPANTS

European ancestry participants aged 25 years and older from the Collaborative Study on the Genetics of Alcoholism (COGA). Polygenic association analyses included 5582 (54% female) participants. Sibling comparisons included 3098 (52% female) participants from 1226 sibling groups nested within the overall sample.

MEASUREMENTS

Outcomes included criterion counts for DSM-5 alcohol use disorder (AUDSX), Fagerström nicotine dependence (NDSX) and DSM-5 cannabis use disorder (CUDSX). We derived polygenic scores for educational attainment (EduYears-GPS) using summary statistics from a large (> 1 million) genome-wide association study of educational attainment.

FINDINGS

In polygenic association analyses, higher EduYears-GPS predicted lower AUDSX, NDSX and CUDSX [P < 0.01, effect sizes (R2 ) ranging from 0.30 to 1.84%]. These effects were robust in sibling comparisons, where sibling differences in EduYears-GPS predicted all three SUDs (P < 0.05, R2 0.13-0.20%).

CONCLUSIONS

Individuals who carry more alleles associated with educational attainment tend to meet fewer clinical criteria for alcohol, nicotine and cannabis use disorders, and these effects are robust to rigorous controls for potentially confounding factors that differ between families (e.g. socio-economic status, urban-rural residency and parental education).

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.

Predicting educational achievement from genomic measures and socioeconomic status

The two best predictors of children's educational achievement available from birth are parents’ socioeconomic status (SES) and, recently, children's inherited DNA differences that can be aggregated in genome‐wide polygenic scores (GPS). Here, we chart for the first time the developmental interplay between these two predictors of educational achievement at ages 7, 11, 14 and 16 in a sample of almost 5,000 UK school children. We show that the prediction of educational achievement from both GPS and SES increases steadily throughout the school years. Using latent growth curve models, we find that GPS and SES not only predict educational achievement in the first grade but they also account for systematic changes in achievement across the school years. At the end of compulsory education at age 16, GPS and SES, respectively, predict 14% and 23% of the variance of educational achievement. Analyses of the extremes of GPS and SES highlight their influence and interplay: In children who have high GPS and come from high SES families, 77% go to university, whereas 21% of children with low GPS and from low SES backgrounds attend university. We find that the associations of GPS and SES with educational achievement are primarily additive, suggesting that their joint influence is particularly dramatic for children at the extreme ends of the distribution.

International Society of Psychiatric Genetics Ethics Committee: Issues facing us

Psychiatric genetics research is improving our understanding of the biological underpinnings of neurodiversity and mental illness. Using psychiatric genetics in ways that maximize benefits and minimize harms to individuals and society depends largely on how the ethical, legal, and social implications (ELSI) of psychiatric genetics are managed. The International Society of Psychiatric Genetics (ISPG) is the largest international organization dedicated to psychiatric genetics. Given its history, membership, and international reach, we believe the ISPG is well-equipped to contribute to the resolution of these ELSI challenges. As such, we recently created the ISPG Ethics Committee, an interdisciplinary group comprised of psychiatric genetics researchers, clinical geneticists, genetic counselors, mental health professionals, patients, patient advocates, bioethicists, and lawyers. This article highlights key ELSI challenges identified by the ISPG Ethics Committee to be of paramount importance for the ethical translation of psychiatric research into society in three contexts: research settings, clinical settings, and legal proceedings. For each of these arenas, we identify and discuss pressing psychiatric genetics ELSI dilemmas that merit attention and require action. The goal is to increase awareness about psychiatric genetics ELSI issues and encourage dialogue and action among stakeholders.

Polygenic score for educational attainment captures DNA variants shared between personality traits and educational achievement

Genome-wide polygenic scores (GPS) can be used to predict individual genetic risk and resilience. For example, a GPS for years of education (EduYears) explains substantial variance in cognitive traits such as general cognitive ability and educational achievement. Personality traits are also known to contribute to individual differences in educational achievement. However, the association between EduYears GPS and personality traits remains largely unexplored. Here, we test the relation between GPS for EduYears, neuroticism, and well-being, and 6 personality and motivation domains: Academic Motivation, Extraversion, Openness, Conscientiousness, Neuroticism, and Agreeableness. The sample was drawn from a U.K.-representative sample of up to 8,322 individuals assessed at age 16. We find that EduYears GPS was positively associated with Openness, Conscientiousness, Agreeableness, and Academic Motivation, predicting between 0.6% and 3% of the variance. In addition, we find that EduYears GPS explains between 8% and 16% of the association between personality domains and educational achievement at the end of compulsory education. In contrast, both the neuroticism and well-being GPS significantly accounted for between 0.3% and 0.7% of the variance in a subset of personality domains. Furthermore, they did not significantly account for any of the covariance between the personality domains and achievement, with the exception of the neuroticism GPS explaining 5% of the covariance between Neuroticism and achievement. These results demonstrate that the genetic effects of educational attainment relate to personality traits, highlighting the multifaceted nature of EduYears GPS. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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.

Twins Early Development Study: A Genetically Sensitive Investigation into Behavioral and Cognitive Development from Infancy to Emerging Adulthood

The Twins Early Development Study (TEDS) is a longitudinal twin study that recruited over 16,000 twin-pairs born between 1994 and 1996 in England and Wales through national birth records. More than 10,000 of these families are still engaged in the study. TEDS was and still is a representative sample of the population in England and Wales. Rich cognitive and emotional/behavioral data have been collected from the twins from infancy to emerging adulthood, with data collection at first contact and at ages 2, 3, 4, 7, 8, 9, 10, 12, 14, 16, 18 and 21, enabling longitudinal genetically sensitive analyses. Data have been collected from the twins themselves, from their parents and teachers, and from the UK National Pupil Database. Genotyped DNA data are available for 10,346 individuals (who are unrelated except for 3320 dizygotic co-twins). TEDS data have contributed to over 400 scientific papers involving more than 140 researchers in 50 research institutions. TEDS offers an outstanding resource for investigating cognitive and behavioral development across childhood and early adulthood and actively fosters scientific collaborations.

The moderating role of SES on genetic differences in educational achievement in the Netherlands

Parental socioeconomic status (SES) is a strong predictor of children's educational achievement (EA), with an increasing effect throughout development. Inequality in educational outcomes between children from different SES backgrounds exists in all Western countries. It has been proposed that a cause of this inequality lies in the interplay between genetic effects and SES on EA, which might depend on society and the equality of the education system. This study adopted two approaches, a classical twin design and polygenic score (PGS) approach, to address the effect of parental SES on EA in a large sample of 12-year-old Dutch twin pairs (2479 MZ and 4450 DZ twin pairs with PGSs for educational attainment available in 2335 children) from the Netherlands Twin Register (NTR). The findings of this study indicated that average EA increased with increasing parental SES. The difference in EA between boys and girls became smaller in the higher SES groups. The classical twin design analyses based on genetic covariance structure modeling pointed to lower genetic, environmental, and thus phenotypic variation in EA at higher SES. Independent from a child's PGS, parental SES predicted EA. However, the strength of the association between PGS and EA did not depend on parental SES. In a within-family design, the twin with a higher PGS scored higher on EA than the co-twin, demonstrating that the effect of the PGS on EA was at least partly independent from parental SES. To conclude, EA depended on SES both directly and indirectly, and SES moderated the additive genetic and environmental components of EA. Adding information from PGS, in addition to parental SES, improved the prediction of children's EA.

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.

A Polygenic Score for Higher Educational Attainment is Associated with Larger Brains

People who score higher on intelligence tests tend to have larger brains. Twin studies suggest the same genetic factors influence both brain size and intelligence. This has led to the hypothesis that genetics influence intelligence partly by contributing to the development of larger brains. We tested this hypothesis using four large imaging genetics studies (combined N = 7965) with polygenic scores derived from a genome-wide association study (GWAS) of educational attainment, a correlate of intelligence. We conducted meta-analysis to test associations among participants' genetics, total brain volume (i.e., brain size), and cognitive test performance. Consistent with previous findings, participants with higher polygenic scores achieved higher scores on cognitive tests, as did participants with larger brains. Participants with higher polygenic scores also had larger brains. We found some evidence that brain size partly mediated associations between participants' education polygenic scores and their cognitive test performance. Effect sizes were larger in the population-based samples than in the convenience-based samples. Recruitment and retention of population-representative samples should be a priority for neuroscience research. Findings suggest promise for studies integrating GWAS discoveries with brain imaging to understand neurobiology linking genetics with cognitive performance.