Covering the long shadow: the moderating role of children's education on health disparity by social origin in Japan

This study investigates the moderating role of children's education on health disparity by social origin (origin health gap) in Japan. Previous studies have quantified origin health gap, but few studies have considered how origin health gap is reduced. Filling this lacuna, I focus on the education of children which also has a spillover effect on individuals' health. I examine how much the origin health gap is closed if I hypothetically intervene to equalize children's education. Results from Social Stratification and Mobility survey revealed that about 30.2 % of origin health gap is closed under the hypothetical intervention. The results are 19.4 % for male and 34.9 % for female. This study also has a policy implication in terms of generational equity; closing the educational inequality of children has a spillover effect to the health disparity of older adults by social origin.

The Genetic Architecture of Differentiating Behavioral and Emotional Problems in Early Life

BACKGROUND

Early in life, behavioral and cognitive traits associated with risk for developing a psychiatric condition are broad and undifferentiated. As children develop, these traits differentiate into characteristic clusters of symptoms and behaviors that ultimately form the basis of diagnostic categories. Understanding this differentiation process-in the context of genetic risk for psychiatric conditions, which is highly generalized-can improve early detection and intervention.

METHODS

We modeled the differentiation of behavioral and emotional problems from age 1.5 to 5 years (behavioral problems - emotional problems = differentiation score) in a preregistered study of ∼79,000 children from the population-based Norwegian Mother, Father, and Child Cohort Study. We used genomic structural equation modeling to identify genetic signal in differentiation and total problems, investigating their links with 11 psychiatric and neurodevelopmental conditions. We examined associations of polygenic scores (PGS) with both outcomes and assessed the relative contributions of direct and indirect genetic effects in ∼33,000 family trios.

RESULTS

Differentiation was primarily genetically correlated with psychiatric conditions via a neurodevelopmental factor. Total problems were primarily associated with the neurodevelopmental factor and p-factor. PGS analyses revealed an association between liability to attention-deficit/hyperactivity disorder and differentiation (β = 0.11; 95% CI, 0.10 to 0.12) and a weaker association with total problems (β = 0.06; 95% CI, 0.04 to 0.07). Trio-PGS analyses showed predominantly direct genetic effects on both outcomes.

CONCLUSIONS

We uncovered genomic signal in the differentiation process, mostly related to common variants associated with neurodevelopmental conditions. Investigating the differentiation of early-life behavioral and emotional problems may enhance our understanding of the developmental emergence of different psychiatric and neurodevelopmental conditions.

Research Review: A review of the past decade of family and genomic studies on adolescent mental health

BACKGROUND

Mental health problems and traits capturing psychopathology are common and often begin during adolescence. Decades of twin studies indicate that genetic factors explain around 50% of individual differences in adolescent psychopathology. In recent years, significant advances, particularly in genomics, have moved this work towards more translational findings.

METHODS

This review provides an overview of the past decade of genetically sensitive studies on adolescent development, covering both family and genomic studies in adolescents aged 10-24 years. We focus on five research themes: (1) co-occurrence or comorbidity between psychopathologies, (2) stability and change over time, (3) intergenerational transmission, (4) gene-environment interplay, and (5) psychological treatment outcomes.

RESULTS

First, research shows that much of the co-occurrence of psychopathologies in adolescence is explained by genetic factors, with widespread pleiotropic influences on many traits. Second, stability in psychopathology across adolescence is largely explained by persistent genetic influences, whereas change is explained by emerging genetic and environmental influences. Third, contemporary twin-family studies suggest that different co-occurring genetic and environmental mechanisms may account for the intergenerational transmission of psychopathology, with some differences across psychopathologies. Fourth, genetic influences on adolescent psychopathology are correlated with a wide range of environmental exposures. However, the extent to which genetic factors interact with the environment remains unclear, as findings from both twin and genomic studies are inconsistent. Finally, a few studies suggest that genetic factors may play a role in psychological treatment response, but these findings have not yet been replicated.

CONCLUSIONS

Genetically sensitive research on adolescent psychopathology has progressed significantly in the past decade, with family and twin findings starting to be replicated at the genomic level. However, important gaps remain in the literature, and we conclude by providing suggestions of research questions that still need to be addressed.

PIGEON: a statistical framework for estimating gene-environment interaction for polygenic traits

Understanding gene-environment interaction (GxE) is crucial for deciphering the genetic architecture of human complex traits. However, current statistical methods for GxE inference face challenges in both scalability and interpretability. Here we introduce PIGEON-a unified statistical framework for quantifying polygenic GxE using a variance component analytical approach. Based on this framework, we outline the main objectives in GxE studies and introduce an estimation procedure that requires only summary statistics data as input. We demonstrate the effectiveness of PIGEON through theoretical and empirical analyses, including a quasi-experimental gene-by-education study of health outcomes and gene-by-sex interaction for 530 traits using UK Biobank. We also identify genetic interactors that explain the treatment effect heterogeneity in a clinical trial on smoking cessation. PIGEON suggests a path towards polygenic, summary statistics-based inference in future GxE studies.

Raising the Floor? Genetic Influences on Educational Attainment Through the Lens of the Evolving Swedish Welfare State

Interest in the role of genetics in influencing key life outcomes such as educational attainment has grown quickly. However, the question of whether genetic influences on educational attainment, on average as well as in conjunction with socioeconomic circumstances, are moderated by macro-level factors has not yet received sufficient attention. This study combines polygenic indices for educational attainment (EA PGI) with high-quality register data in a large sample of Swedish twins of European ancestry born 1920-1999. Employing both conventional between-family and within-family models, the analyses suggest that the influences of education-related genetic propensities on educational attainment have increased in Sweden during the twentieth century, a period featuring major expansions of the Swedish educational system, and decreasing economic inequality. The analyses also suggest that the degree to which socioeconomic background enhances genetic influences on education has decreased across cohorts. Genetic influences on education do not appear to have translated into increased genetic influences on income. Additionally, there is some evidence of floor and ceiling effects in the analyses of dichotomous educational outcomes.

Socio-economic status is a social construct with heritable components and genetic consequences

In civilizations, individuals are born into or sorted into different levels of socio-economic status (SES). SES clusters in families and geographically, and is robustly associated with genetic effects. Here we first review the history of scientific research on the relationship between SES and heredity. We then discuss recent findings in genomics research in light of the hypothesis that SES is a dynamic social construct that involves genetically influenced traits that help in achieving or retaining a socio-economic position, and can affect the distribution of genes associated with such traits. Social stratification results in people with differing traits being sorted into strata with different environmental exposures, which can result in evolutionary selection pressures through differences in mortality, reproduction and non-random mating. Genomics research is revealing previously concealed genetic consequences of the way society is organized, yielding insights that should be approached with caution in pursuit of a fair and functional society.

Examining causal relationships between educational attainment and type 2 diabetes using genetic analysis: findings from the EPIC-InterAct study through Mendelian randomisation

INTRODUCTION

Observational studies have shown that more educated people are at lower risk of developing type 2 diabetes (T2D). However, robust study designs are needed to investigate the likelihood that such a relationship is causal. This study used genetic instruments for education to estimate the effect of education on T2D using the Mendelian randomisation (MR) approach.

METHODS

Analyses have been conducted in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study (more than 20 000 individuals), a case-cohort study of T2D nested in the EPIC cohort. Education was measured as Years of Education and Relative Index of Inequality. Prentice-weighted Cox models were performed to estimate the association between education and T2D. One-sample MR analyses investigated whether genetic predisposition towards longer education was associated with risk of T2D and investigated potential mediators of the association.

RESULTS

MR estimates indicated a risk reduction of about 15% for each year of longer education on the risk of developing T2D, confirming the protective role estimated by observational models (HR 0.96, 95% CI 0.95 to 0.96). MR analyses on putative mediators showed a significant role of education on body mass index, alcohol consumption, adherence to the Mediterranean diet and smoking habits.

CONCLUSION

The results supported the hypothesis that higher education is a protective factor for the risk of developing T2D. Based on its position in the causal chain, education may be antecedent of other known risk factors for T2D including unhealthy behaviours. These findings reinforce evidence obtained through observational study designs and bridge the gap between correlation and causation.

The Estonian Biobank's journey from biobanking to personalized medicine

Large biobanks have set a new standard for research and innovation in human genomics and implementation of personalized medicine. The Estonian Biobank was founded a quarter of a century ago, and its biological specimens, clinical, health, omics, and lifestyle data have been included in over 800 publications to date. What makes the biobank unique internationally is its translational focus, with active efforts to conduct clinical studies based on genetic findings, and to explore the effects of return of results on participants. In this review, we provide an overview of the Estonian Biobank, highlight its strengths for studying the effects of genetic variation and quantitative phenotypes on health-related traits, development of methods and frameworks for bringing genomics into the clinic, and its role as a driving force for implementing personalized medicine on a national level and beyond.

Parental kynurenine 3-monooxygenase genotype in mice directs sex-specific behavioral outcomes in offspring

BACKGROUND

Disruptions in brain development can impact behavioral traits and increase the risk of neurodevelopmental conditions such as autism spectrum disorder, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder, often in sex-specific ways. Dysregulation of the kynurenine pathway (KP) of tryptophan metabolism has been implicated in cognitive and neurodevelopmental disorders. Increased brain kynurenic acid (KYNA), a neuroactive metabolite implicated in cognition and sleep homeostasis, and variations in the Kmo gene, which encodes kynurenine 3-monooxygenase (KMO), have been identified in these patients. We hypothesize that parental Kmo genetics influence KP biochemistry, sleep behavior and brain energy demands, contributing to impairments in cognition and sleep in offspring through the influence of parental genotype and genetic nurture mechanisms.

METHODS

A mouse model of partial Kmo deficiency, Kmo heterozygous (HET-Kmo+/-), was used to examine brain KMO activity, KYNA levels, and sleep behavior in HET-Kmo+/- compared to wild-type control (WT-Control) mice. Brain mitochondrial respiration was assessed, and KP metabolites and corticosterone levels were measured in breast milk. Behavioral assessments were conducted on wild-type offspring from two parental groups: (i) WT-Control from WT-Control parents, (ii) wild-type Kmo (WT-Kmo+/+) from Kmo heterozygous parents (HET-Kmo+/-). All mice were C57Bl/6J background strain. Adult female and male offspring underwent behavioral testing for learning, memory, anxiety-like behavior and sleep-wake patterns.

RESULTS

HET-Kmo+/- mice exhibited reduced brain KMO activity, increased KYNA levels, and disrupted sleep architecture and electroencephalogram (EEG) power spectra. Mitochondrial respiration (Complex I and Complex II activity) and electron transport chain protein levels were impaired in the hippocampus of HET-Kmo+/- females. Breast milk from HET-Kmo+/- mothers increased kynurenine exposure during lactation but corticosterone levels were unchanged. Compared to WT-Control offspring, WT-Kmo+/+ females showed impaired spatial learning, heightened anxiety, reduced sleep and abnormal EEG spectral power. WT-Kmo+/+ males had deficits in reversal learning but no sleep disturbances or anxiety-like behaviors.

CONCLUSIONS

These findings suggest that Kmo deficiency impacts KP biochemistry, sleep behavior, and brain mitochondrial function. Even though WT-Kmo+/+ inherit identical genetic material as WT-Control, their development might be shaped by the parent's physiology, behavior, or metabolic state influenced by their Kmo genotype, leading to phenotypic sex-specific differences in offspring.

Associations between common genetic variants and income provide insights about the socio-economic health gradient

We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1-5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.

Parent-of-Origin Effects in Childhood Asthma at Seven Years of Age

Childhood asthma is more common among children whose mothers have asthma than among those whose fathers have asthma. The reasons for this are unknown, and we hypothesize that genomic imprinting may partly explain this observation. Our aim is to assess parent-of-origin (PoO) effects on childhood asthma by analyzing SNP array genotype data from a large population-based cohort. To estimate PoO effects in parent-reported childhood asthma at 7 years of age, we fit a log-linear model implemented in the HAPLIN R package to SNP array genotype data from 915 mother-father-child case triads, 603 mother-child case dyads, and 113 father-child case dyads participating in the Norwegian Mother, Father, and Child Cohort Study (MoBa). We found that alleles at two SNPs-rs3003214 and rs3003211-near the adenylosuccinate synthase 2 gene (ADSS2 on chromosome 1q44) showed significant PoO effects at a false positive rate ≤ 0.05. The ratio of the effect of the maternally and paternally inherited G-allele at rs3003214 was 1.68 (95% CI: 1.41-2.03, p value = 1.13E-08). Our results suggest PoO effects at the ADSS2 gene, particularly the maternally inherited G-allele at rs3003214, may contribute to the maternal effect in childhood asthma.

Family-based genome-wide association study designs for increased power and robustness

Family-based genome-wide association studies (FGWASs) use random, within-family genetic variation to remove confounding from estimates of direct genetic effects (DGEs). Here we introduce a 'unified estimator' that includes individuals without genotyped relatives, unifying standard and FGWAS while increasing power for DGE estimation. We also introduce a 'robust estimator' that is not biased in structured and/or admixed populations. In an analysis of 19 phenotypes in the UK Biobank, the unified estimator in the White British subsample and the robust estimator (applied without ancestry restrictions) increased the effective sample size for DGEs by 46.9% to 106.5% and 10.3% to 21.0%, respectively, compared to using genetic differences between siblings. Polygenic predictors derived from the unified estimator demonstrated superior out-of-sample prediction ability compared to other family-based methods. We implemented the methods in the software package snipar in an efficient linear mixed model that accounts for sample relatedness and sibling shared environment.

Intergenerational transmission of polygenic predisposition for neuropsychiatric traits on emotional and behavioural difficulties in childhood

Childhood emotional and behavioural difficulties tend to co-occur and often precede diagnosed neuropsychiatric conditions. Identifying shared and specific risk factors for early-life mental health difficulties is therefore essential for prevention strategies. Here, we examine how parental risk factors shape their offspring's emotional and behavioural symptoms (e.g. feelings of anxiety, and restlessness) using data from 14,959 genotyped family trios from the Norwegian Mother, Father and Child Cohort Study (MoBa). We model maternal reports of emotional and behavioural symptoms, organizing them into general and specific domains. We then investigate the direct (genetically transmitted) and indirect (environmentally mediated) contributions of parental polygenic risk for neuropsychiatric-related traits and whether these are shared across symptoms. We observe evidence consistent with an environmental route to general symptomatology beyond genetic transmission, while also demonstrating domain-specific direct and indirect genetic contributions. These findings improve our understanding of early risk pathways that can be targeted in preventive interventions aiming to interrupt the intergenerational cycle of risk transmission.

A robust and powerful GWAS method for family trios supporting within-family Mendelian randomization analysis

Effect size estimates in genome-wide association studies (GWAS) and Mendelian randomization (MR) studies for independent individuals may be biased due to dynastic effect (DE) and residual population stratification (RPS). Existing GWAS methods for family trios effectively controlled such biases, while only using parental and offspring's genotypes and offspring's phenotype, and not incorporating parental phenotypes, which causes loss in estimation accuracy and test power. Therefore, we proposed a novel GWAS method based on structural equation modelling for family trios, denoted by FT-SEM. FT-SEM simultaneously uses parental and offspring's genotypes and phenotypes. Simulation results demonstrate that FT-SEM substantially improves estimation accuracy and test power while controlling bias and type I error rate. Using family trios from Minnesota Center for Twin and Family Research (MCTFR), we found that DE and RPS greatly distort the results only based on independent individuals, and FT-SEM effectively corrects such biases. Combining the GWAS results from MCTFR with existing summary data, we performed several two-sample MR analyses. We observed that the effects of BMI on nicotine, alcohol consumption and behavior disorder were due to bias rather than causality. Our findings underscore the necessity of using families to validate the results of GWAS and MR, and highlight FT-SEM's advantages.

Cognitive ability in offspring conscripts and cardiovascular disease risk in extended family members: assessing the impact of modifiable risk factors on familial risk

BACKGROUND

Previous studies have demonstrated an inverse association between cognitive ability (CA) and risk of cardiovascular diseases (CVDs). This study aims to investigate the associations between CA in offspring and CVD mortality in relatives of the parental generation (ie, parents, aunts/uncles (A/U) and the partners of A/U) and assesses the role of modifiable risk factors on these associations.

METHODS

This longitudinal study included nearly 3 million adults who were followed up from age 45 until death. Data for participants were obtained through the linkage of various Norwegian surveys and registries. HRs for CVD mortality among the parental generation in relation to offspring CA were estimated using Cox proportional hazards regression.

RESULTS

One standard deviation increase in CA was associated with a 23%, 17%, 9% and 9% CVD mortality reduction in mothers (HR: 0.77, 95% CI (0.74, 0.81)), fathers (0.83, (0.81, 0.86)), A/U (0.91, (0.87, 0.94)) and A/U partners (0.91, (0.89, 0.94)), respectively. Accounting for modifiable risk factors in the parental generation attenuated the association in mothers from 23% to 9% (0.91, (0.87, 0.96)), fathers from 17% to 7% (0.93, (0.91, 0.96)), A/U from 9% to 1% (0.99, (0.96, 1.03)) and A/U partners from 9% to 2% (0.98, (0.95, 1.01)).

CONCLUSIONS

We observed an inverse CA-CVD association in all familial relationships including non-genetically related duos (offspring-A/U partners). CA and CVD probably have shared causes such as genetic and environmental components common to the family members. These associations were largely accounted for by modifiable risk factors.

Gene-environment correlation: the role of family environment in academic development

Academic achievement is partly heritable and highly polygenic. However, genetic effects on academic achievement are not independent of environmental processes. We investigated whether aspects of the family environment mediated genetic effects on academic achievement across development. Our sample included 5151 children who participated in the Twins Early Development Study, as well as their parents and teachers. Data on academic achievement and family environments (parenting, home environments, and geocoded indices of neighbourhood characteristics) were available at ages 7, 9, 12 and 16. We computed educational attainment polygenic scores (PGS) and further separated genetic effects into cognitive and noncognitive PGS. Three core findings emerged. First, aspects of the family environment, but not the wider neighbourhood context, consistently mediated the PGS effects on achievement across development-accounting for up to 34.3% of the total effect. Family characteristics mattered beyond socio-economic status. Second, family environments were more robustly linked to noncognitive PGS effects on academic achievement than cognitive PGS effects. Third, when we investigated whether environmental mediation effects could also be observed when considering differences between siblings, adjusting for family fixed effects, we found that environmental mediation was nearly exclusively observed between families. This is consistent with the proposition that family environmental contexts contribute to academic development via passive gene-environment correlation processes or genetic nurture. Our results show how parents tend to shape environments that foster their children's academic development partly based on their own genetic disposition, particularly towards noncognitive skills, rather than responding to each child's genetic disposition.

Neuropsychiatric polygenic scores are weak predictors of professional categories

Polygenic scores (PGS) enable the exploration of pleiotropic effects and genomic dissection of complex traits. Here, in 421,889 individuals with European ancestry from the Million Veteran Program and UK Biobank, we examine how PGS of 17 neuropsychiatric traits are related to membership in 22 broad professional categories. Overall, we find statistically significant but weak (the highest odds ratio is 1.1 per PGS standard deviation) associations between most professional categories and genetic predisposition for at least one neuropsychiatric trait. Secondary analyses in UK Biobank revealed independence of these associations from observed fluid intelligence and sex-specific effects. By leveraging aggregate population trends, we identified patterns in the public interest, such as the mediating effect of education attainment on the association of attention-deficit/hyperactivity disorder PGS with multiple professional categories. However, at the individual level, PGS explained less than 0.5% of the variance of professional membership, and almost none after we adjusted for education and socio-economic status.

Do polygenic indices capture "direct" effects on child externalizing behavior problems? Within-family analyses in two longitudinal birth cohorts

Failures of self-control can manifest as externalizing behaviors (e.g., aggression, rule-breaking) that have far-reaching negative consequences. Researchers have long been interested in measuring children's genetic risk for externalizing behaviors to inform efforts at early identification and intervention. Drawing on data from the Environmental Risk Longitudinal Twin Study (N = 862 twins) and the Millennium Cohort Study (N = 2,824 parent-child trios), two longitudinal cohorts from the UK, we leveraged molecular genetic data and within-family designs to test for genetic associations with externalizing behavior that are not affected by common sources of environmental influence. We found that a polygenic index (PGI) calculated from genetic variants discovered in previous studies of self-controlled behavior in adults captures direct genetic effects on externalizing problems in children and adolescents when evaluated with rigorous within-family designs (β's = 0.13-0.19 across development). The externalizing behavior PGI can usefully augment psychological studies of the development of self-control.

Haplotype-based analysis distinguishes maternal-fetal genetic contribution to pregnancy-related outcomes

Genotype-based approaches for the estimation of SNP-based narrow-sense heritability ([Formula: see text]) have limited utility in pregnancy-related outcomes due to confounding by the shared alleles between mother and child. Here, we propose a haplotype-based approach to estimate the genetic variance attributable to three haplotypes - maternal transmitted ([Formula: see text]), maternal non-transmitted ([Formula: see text]) and paternal transmitted ([Formula: see text]) in mother-child pairs. We show through extensive simulations that our haplotype-based approach outperforms the conventional and contemporary approaches for resolving the contribution of maternal and fetal effects, particularly when m1 and p1 have different effects in the offspring. We apply this approach to estimate the explicit and relative maternal-fetal genetic contribution to the phenotypic variance of gestational duration and gestational duration-adjusted fetal size measurements at birth in 10,375 mother-child pairs. The results reveal that variance of gestational duration is mainly attributable to m1 and m2 ([Formula: see text]). In contrast, variance of fetal size measurements at birth are mainly attributable to m1 and p1 ([Formula: see text]). Our results suggest that gestational duration and fetal size measurements are primarily genetically determined by the maternal and fetal genomes, respectively. In addition, a greater contribution of m1 as compared to m2 and p1 ([Formula: see text]) to birth length and head circumference suggests a substantial influence of correlated maternal-fetal genetic effects on these traits. Our newly developed approach provides a direct and robust alternative for resolving explicit maternal and fetal genetic contributions to the phenotypic variance of pregnancy-related outcomes.

From genetic disposition to academic achievement: The mediating role of non-cognitive skills across development

Genetic effects on academic achievement are likely to capture environmental, developmental, and psychological processes. How these processes contribute to translating genetic dispositions into observed academic achievement remains critically under-investigated. Here, we examined the role of non-cognitive skills-e.g., motivation, attitudes and self-regulation-in mediating education-associated genetic effects on academic achievement across development. Data were collected from 5,016 children enrolled in the Twins Early Development Study at ages 7, 9, 12, and 16, as well as their parents and teachers. We found that non-cognitive skills mediated polygenic score effects on academic achievement across development, and longitudinally, accounting for up to 64% of the total effects. Within-family analyses highlighted the contribution of non-cognitive skills beyond genetic, environmental and demographic factors that are shared between siblings, accounting for up to 83% of the total mediation effect, likely reflecting evocative/active gene-environment correlation. Our results underscore the role of non-cognitive skills in academic development in how children evoke and select experiences that align with their genetic propensity.

Using twin-pairs to assess potential bias in polygenic prediction of externalising behaviours across development

Prediction from polygenic scores may be confounded by sources of passive gene-environment correlation (rGE; e.g. population stratification, assortative mating, and environmentally mediated effects of parental genotype on child phenotype). Using genomic data from 10 000 twin pairs, we asked whether polygenic scores from the most recent externalising genome-wide association study predict conduct problems, ADHD symptomology and callous-unemotional traits, and whether these predictions are biased by rGE. We ran regression models including within-family and between-family polygenic scores, to separate the direct genetic influence on a trait from environmental influences that correlate with genes (indirect genetic effects). Findings suggested that this externalising polygenic score is a good index of direct genetic influence on conduct and ADHD-related symptoms across development, with minimal bias from rGE, although the polygenic score predicted less variance in CU traits. Post-hoc analyses showed some indirect genetic effects acting on a common factor indexing stability of conduct problems across time and contexts.

Examining Differences in the Predictive Capacity of Educational Polygenic Scores on Physical Limitations Among Older Adults With European or African Ancestry

This research examined whether educational polygenic scores were associated with physical limitations among older adults with European or African ancestry. In the European ancestry sample, we found that education polygenic scores were significantly associated with physical limitations, net of age, sex, and current socioeconomic status. In the African ancestry sample, education polygenic scores were not associated with physical limitations in any of the models. Observed educational attainment was a robust predictor of physical limitations in both samples. This research demonstrates the inequalities in the predictive capacity of educational polygenic scores for physical health. We hypothesize that this disparity is a result of structural barriers to educational attainment by race, selection bias, and/or racial inequities in data collection. All of these explanations stem from structural racism and highlight the limited usefulness of polygenic scores for clinical decision-making.

A Litmus Test for Confounding in Polygenic Scores

Polygenic scores (PGSs) are being rapidly adopted for trait prediction in the clinic and beyond. PGSs are often thought of as capturing the direct genetic effect of one's genotype on their phenotype. However, because PGSs are constructed from population-level associations, they are influenced by factors other than direct genetic effects, including stratification, assortative mating, and dynastic effects ("SAD effects"). Our interpretation and application of PGSs may hinge on the relative impact of SAD effects, since they may often be environmentally or culturally mediated. We developed a method that estimates the proportion of variance in a PGS (in a given sample) that is driven by direct effects, SAD effects, and their covariance. We leverage a comparison of a PGS of interest based on a standard GWAS with a PGS based on a sibling GWAS-which is largely immune to SAD effects-to quantify the relative contribution of each type of effect to variance in the PGS of interest. Our method, Partitioning Genetic Scores Using Siblings (PGSUS, pron. "Pegasus"), breaks down variance components further by axes of genetic ancestry, allowing for a nuanced interpretation of SAD effects. In particular, PGSUS can detect stratification along major axes of ancestry as well as SAD variance that is "isotropic" with respect to axes of ancestry. Applying PGSUS, we found evidence of stratification in PGSs constructed using large meta-analyses of height and educational attainment as well as in a range of PGSs constructed using the UK Biobank. In some instances, a given PGS appears to be stratified along a major axis of ancestry in one prediction sample but not in another (for example, in comparisons of prediction in samples from different countries, or in ancient DNA vs. contemporary samples). Finally, we show that different approaches for adjustment for population structure in GWASs have distinct advantages with respect to mitigation of ancestry-axis-specific and isotropic SAD variance in PGS. Our study illustrates how family-based designs can be combined with standard population-based designs to guide the interpretation and application of genomic predictors.

Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank

Socioeconomic status (SES) impacts health and life-course outcomes. This genome-wide association study (GWAS) of sociologically informed occupational status measures (ISEI, SIOPS, CAMSIS) using the UK Biobank (N = 273,157) identified 106 independent single-nucleotide polymorphisms of which 8 are novel to the study of SES. Genetic correlations with educational attainment (rg = 0.96-0.97) and income (rg = 0.81-0.91) point to a common genetic factor for SES. We observed a 54-57% reduction in within-family predictions compared with population-based predictions, attributed to indirect parental effects (22-27% attenuation) and assortative mating (21-27%) following our calculations. Using polygenic scores from population predictions of 5-10% (incremental R2 = 0.023-0.097 across different approaches and occupational status measures), we showed that (1) cognitive and non-cognitive traits, including scholastic and occupational motivation and aspiration, link polygenic scores to occupational status and (2) 62% of the intergenerational transmission of occupational status cannot be ascribed to genetic inheritance of common variants but other factors such as family environments. Finally, links between genetics, occupation, career trajectory and health are interrelated with parental occupational status.

Direct and indirect genetic effects on early neurodevelopmental traits

BACKGROUND

Neurodevelopmental conditions are highly heritable. Recent studies have shown that genomic heritability estimates can be confounded by genetic effects mediated via the environment (indirect genetic effects). However, the relative importance of direct versus indirect genetic effects on early variability in traits related to neurodevelopmental conditions is unknown.

METHODS

The sample included up to 24,692 parent-offspring trios from the Norwegian MoBa cohort. We use Trio-GCTA to estimate latent direct and indirect genetic effects on mother-reported neurodevelopmental traits at age of 3 years (restricted and repetitive behaviors and interests, inattention, hyperactivity, language, social, and motor development). Further, we investigate to what extent direct and indirect effects are attributable to common genetic variants associated with autism, ADHD, developmental dyslexia, educational attainment, and cognitive ability using polygenic scores (PGS) in regression modeling.

RESULTS

We find evidence for contributions of direct and indirect latent common genetic effects to inattention (direct: explaining 4.8% of variance, indirect: 6.7%) hyperactivity (direct: 1.3%, indirect: 9.6%), and restricted and repetitive behaviors (direct: 0.8%, indirect: 7.3%). Direct effects best explained variation in social and communication, language, and motor development (5.1%-5.7%). Direct genetic effects on inattention were captured by PGS for ADHD, educational attainment, and cognitive ability, whereas direct genetic effects on language development were captured by cognitive ability, educational attainment, and autism PGS. Indirect genetic effects on neurodevelopmental traits were primarily captured by educational attainment and/or cognitive ability PGS.

CONCLUSIONS

Results were consistent with differential contributions to neurodevelopmental traits in early childhood from direct and indirect genetic effects. Indirect effects were particularly important for hyperactivity and restricted and repetitive behaviors and interests and may be linked to genetic variation associated with cognition and educational attainment. Our findings illustrate the importance of within-family methods for disentangling genetic processes that influence early neurodevelopmental traits, even when identifiable associations are small.

The Genetics of Intelligence

BACKGROUND

Intelligence is defined as general mental capacity, which includes the abilities to reason, solve new problems, think abstractly, and learn quickly. Genetic factors explain a considerable fraction of inter-individual differences in intelligence. For many years, research on intelligence was limited to estimating the relative importance of genetic and environmental factors, without identifying any individual causal factors.

METHODS

This review of the literature is based on pertinent original publications and reviews.

RESULTS

Genome-wide association studies (GWAS) have shown that certain gene loci are associated with intelligence, as well as with educational attainment, which is known to be correlated with intelligence. As each individual gene locus accounts for only a very small part of the variance in intelligence ( < 0.02%), so-called "polygenic scores" (PGS) have been calculated in which thousands of genetic variants are summarized together. On the basis of the largest GWAS performed to date, it is estimated that 7-15% of inter-individual differences in educational attainment and 7-10% in intelligence among persons of European descent can be explained by genetic factors. These genetic effects are partly indirect. At the same time, the relative importance of genetic factors in determining complex features such as intelligence and educational attainment must always be seen against the background of individual environmental conditions. In the presence of difficult social conditions, for example, the influence of genetic factors is typically lower.

CONCLUSION

At present, the polygenic scores generated from genome-wide association studies are primarily of scientific interest, yet they are becoming increasingly informative and valid for individual prediction. There is, therefore, a need for broad social discussion about their future use.

Exome sequencing identifies genes for socioeconomic status in 350,770 individuals

Socioeconomic status (SES) is a critical factor in determining health outcomes and is influenced by genetic and environmental factors. However, our understanding of the genetic structure of SES remains incomplete. Here, we conducted a large-scale exome study of SES markers (household income, occupational status, educational attainment, and social deprivation) in 350,770 individuals. For rare coding variants, we identified 56 significant associations by gene-based collapsing tests, unveiling 7 additional SES-associated genes (NRN1, CCDC36, RHOB, EP400, NCAM1, TPTEP2-CSNK1E, and LINC02881). Exome-wide single common variant analysis revealed nine lead single-nucleotide polymorphisms (SNPs) associated with household income and 34 lead SNPs associated with EduYears, replicating previous GWAS findings. The gene-environment correlations had a substantial impact on the genetic associations with SES, as indicated by the significantly increased P values in several associations after controlling for geographic regions. Furthermore, we observed the pleiotropic effects of SES-associated genetic factors on a wide range of health outcomes, such as cognitive function, psychosocial status, and diabetes. This study highlights the contribution of coding variants to SES and their associations with health phenotypes.

Genetic Nurture Effects on Type 2 Diabetes Among Chinese Han Adults: A Family-Based Design

Background/Objectives: Genes and environments were transmitted across generations. Parents' genetics influence the environments of their offspring; these two modes of inheritance can produce a genetic nurture effect, also known as indirect genetic effects. Such indirect effects may partly account for estimated genetic variance in T2D. However, the well-established specific genetic risk factors about genetic nurture effect for T2D are not fully understood. This study aimed to investigate the genetic nurture effect on type 2 diabetes and reveal the potential underlying mechanism using publicly available data. Methods: Whole-genome genotyping data of 881 offspring and/or their parents were collected. We assessed SNP-level, gene-based, and pathway-based associations for different types of genetic effects. Results: Rs3805116 (β: 0.54, p = 4.39 × 10-8) was significant for paternal genetic nurture effects. MRPS33 (p = 1.58 × 10-6), PIH1D2 (p = 6.76 × 10-7), and SD1HD (p = 2.67 × 10-6) revealed significantly positive paternal genetic nurture effects. Five ontologies were identified as enrichment in both direct and indirect genetic effects, including flavonoid metabolic process and antigen processing and presentation via the MHC class Ib pathway. Two pathways were only enriched in paternal genetic nurture effects, including the transforming growth factor beta pathway. Tissue enrichment of type 2 diabetes-associated genes on different genetic effect types was performed using publicly available gene expression data from the Human Protein Atlas database. We observed significant gene enrichment in paternal genetic nurture effects in the gallbladder, smooth muscle, and adrenal gland tissues. Conclusions: MRPS33, PIH1D2, and SD1HD are associated with increased T2D risk through the environment influenced by paternal genotype, suggesting a novel perspective on paternal contributions to the T2D predisposition.

The Moderating Influence of School Achievement on Intelligence: A Cross-National Comparison

Education-related variables are positively associated with intelligence in both causal directions, but little is known about the associations' underlying genetically and environmentally intertwined processes and many 'third variables' are probably involved too. In this study, we investigated how school achievement, measured by grade point average (GPA), moderated intelligence test score variation in young adulthood in broadly representative samples from the U.S. state of Minnesota, Denmark, and Germany, attempting to improve both understanding of the importance of environmental contexts and the limitations of currently available modelling techniques to help remedy them. School achievement was positively associated with intelligence test scores in all three contexts, but it moderated variances differently, even within the two cohorts comprising the Minnesota sample. One Minnesota cohort and the German sample suggested that shared environmental variance was larger among individuals with extreme GPAs, while the Danish sample suggested that this was only true among individuals with low GPAs. In contrast to these observations, the other Minnesota cohort suggested that genetic and non-shared environmental variances were greater among individuals with high GPAs. These observations indicated that underlying individual developmental processes and population-level impacts differed. However, our statistical models did not capture these differences clearly. The ways in which they failed all suggested the model limitations involve an inability to address degrees to which environmental constraints restrain social movements that are confounded with individual variations in capacities to move within society.

The Mechanisms Underlying the Intergenerational Transmission of Substance Use and Misuse: An Integrated Research Approach

Substance use and substance use disorders run in families. While it has long been recognized that the etiology of substance use behaviors and disorders involves a combination of genetic and environmental factors, two key questions remain largely unanswered: (1) the intergenerational transmission through which these genetic predispositions are passed from parents to children, and (2) the molecular mechanisms linking genetic variants to substance use behaviors and disorders. This article aims to provide a comprehensive conceptual framework and methodological approach for investigating the intergenerational transmission of substance use behaviors and disorders, by integrating genetic nurture analysis, gene expression imputation, and weighted gene co-expression network analysis. We also additionally describe two longitudinal cohorts - the Brisbane Longitudinal Twin Study in Australia and the Lifelines Cohort Study in the Netherlands. By applying the methodological framework to these two unique datasets, our future research will explore the complex interplay between genetic factors, gene expression, and environmental influences on substance use behaviors and disorders across different life stages and populations.

Migraine and cognitive dysfunction: a narrative review

The association between migraine and cognitive function has been studied during the last decade, however, this relationship is not well established. As migraine prevalence is highest between the ages of 30-40, aligning with some of our most productive years, we must understand cognitive changes within this disorder. Cognitive impairment potentially limits social and professional interactions, thus negatively impacting quality of life. Therefore, we will review the relationship between prevalent migraine and cognition. Cognitive dysfunction has been reported to be the second largest cause of disability, after pain, in migraine patients. While subjective patient reports on cognition consistently describe impairment, findings for objective neuropsychological assessments vary. Many studies report worse cognitive performance in the ictal phase compared to controls, which can persist into the postictal period, although whether this continues in the interictal period has been understudied. There is limited consensus as to whether cognition differs in migraine with aura versus migraine without aura, and while many studies do support cognitive impairment in chronic migraine, it remains uncertain as to whether this is more debilitating than the cognitive difficulties experienced by those with episodic migraine. To date, objective assessment of neurological abnormalities that may underlie cognitive impairment through neuroimaging has been underutilized. There is limited consensus as to whether cognitive impairment is a characteristic specific to migraine, whether it is driven by a combination of factors including co-morbidities such as anxiety, depression, or vascular dysfunction, treatment, or whether it is a more general characteristic of pain disorders. Overall, increasing numbers of studies support cognitive impairment in migraine patients. Future studies should consider longitudinal study designs to assess cognition across different migraine phases and subtypes of the disorder, including migraine with aura and chronic migraine, as well as controlling for important confounders such as treatment use.

Using the phenotype differences model to identify genetic effects in samples of partially genotyped sibling pairs

The identification of causal relationships between specific genes and social, behavioral, and health outcomes is challenging due to environmental confounding from population stratification and dynastic genetic effects. Existing methods to eliminate environmental confounding leverage random genetic variation resulting from recombination and require within-family dyadic genetic data (i.e., parent-child and/or sibling pairs), meaning they can only be applied in relatively small and selected samples. We introduce the phenotype differences model and provide derivations showing that it-under plausible assumptions-provides consistent (and, in certain cases, unbiased) estimates of genetic effects using just a single individual's genotype. Then, leveraging distinct samples of fully and partially genotyped sibling pairs in the Wisconsin Longitudinal Study, we use polygenic indices and phenotypic data for 24 different traits to empirically validate the phenotype differences model. Finally, we utilize the model to test the effects of 40 polygenic indices on lifespan. After a 10% false discovery rate correction, we find that polygenic indices for three traits-body mass index, self-rated health, chronic obstructive pulmonary disease-have a statistically significant effect on an individual's lifespan.

Examining the role of common variants in rare neurodevelopmental conditions

Although rare neurodevelopmental conditions have a large Mendelian component1, common genetic variants also contribute to risk2,3. However, little is known about how this polygenic risk is distributed among patients with these conditions and their parents nor its interplay with rare variants. It is also unclear whether polygenic background affects risk directly through alleles transmitted from parents to children, or whether indirect genetic effects mediated through the family environment4 also play a role. Here we addressed these questions using genetic data from 11,573 patients with rare neurodevelopmental conditions, 9,128 of their parents and 26,869 controls. Common variants explained around 10% of variance in risk. Patients with a monogenic diagnosis had significantly less polygenic risk than those without, supporting a liability threshold model5. A polygenic score for neurodevelopmental conditions showed only a direct genetic effect. By contrast, polygenic scores for educational attainment and cognitive performance showed no direct genetic effect, but the non-transmitted alleles in the parents were correlated with the child's risk, potentially due to indirect genetic effects and/or parental assortment for these traits4. Indeed, as expected under parental assortment, we show that common variant predisposition for neurodevelopmental conditions is correlated with the rare variant component of risk. These findings indicate that future studies should investigate the possible role and nature of indirect genetic effects on rare neurodevelopmental conditions, and consider the contribution of common and rare variants simultaneously when studying cognition-related phenotypes.

Biospecimens in the HEALthy Brain and Child Development (HBCD) Study: Rationale and protocol

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The longitudinal collection of biological samples from over 7000 birthing parents and their children within the HBCD study enables research on pre- and postnatal exposures (e.g., substance use, toxicants, nutrition), and biological processes (e.g., genetics, epigenetic signatures, proteins, metabolites) on neurobehavioral developmental outcomes. The following biosamples are collected from the birthing parent: 1) blood (i.e., whole blood, serum, plasma, buffy coat, and dried blood spots) during pregnancy, 2) nail clippings during pregnancy and one month postpartum, 3) urine during pregnancy, and 4) saliva during pregnancy and at in-person postnatal assessments. The following samples are collected from the child at in-person study assessments: 1) saliva, 2) stool, and 3) urine. Additionally, placenta tissue, cord blood, and cord tissue are collected by a subset of HBCD sites. Here, we describe the rationale for the collection of these biospecimens, their current and potential future uses, the collection protocol, and collection success rates during piloting. This information will assist research teams in the planning of future studies utilizing this collection of biological samples.

Environment-by-PGS Interaction in the Classical Twin Design: An Application to Childhood Anxiety and Negative Affect

One type of genotype-environment interaction occurs when genetic effects on a phenotype are moderated by an environment; or when environmental effects on a phenotype are moderated by genes. Here we outline these types of genotype-environment interaction models, and propose a test of genotype-environment interaction based on the classical twin design, which includes observed genetic variables (polygenic scores: PGSs) that account for part of the genetic variance of the phenotype. We introduce environment-by-PGS interaction and the results of a simulation study to address statistical power and parameter recovery. Next, we apply the model to empirical data on anxiety and negative affect in children. The power to detect environment-by-PGS interaction depends on the heritability of the phenotype, and the strength of the PGS. The simulation results indicate that under realistic conditions of sample size, heritability and strength of the interaction, the environment-by-PGS model is a viable approach to detect genotype-environment interaction. In 7-year-old children, we defined two PGS based on the largest genetic association studies for 2 traits that are genetically correlated to childhood anxiety and negative affect, namely major depression (MDD) and intelligence (IQ). We find that common environmental influences on negative affect are amplified for children with a lower IQ-PGS.

Genetic architecture reconciles linkage and association studies of complex traits

Linkage studies have successfully mapped loci underlying monogenic disorders, but mostly failed when applied to common diseases. Conversely, genome-wide association studies (GWASs) have identified replicable associations between thousands of SNPs and complex traits, yet capture less than half of the total heritability. In the present study we reconcile these two approaches by showing that linkage signals of height and body mass index (BMI) from 119,000 sibling pairs colocalize with GWAS-identified loci. Concordant with polygenicity, we observed the following: a genome-wide inflation of linkage test statistics; that GWAS results predict linkage signals; and that adjusting phenotypes for polygenic scores reduces linkage signals. Finally, we developed a method using recombination rate-stratified, identity-by-descent sharing between siblings to unbiasedly estimate heritability of height (0.76 ± 0.05) and BMI (0.55 ± 0.07). Our results imply that substantial heritability remains unaccounted for by GWAS-identified loci and this residual genetic variation is polygenic and enriched near these loci.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Mediating pathways between attention deficit hyperactivity disorder and type 2 diabetes mellitus: evidence from a two-step and multivariable Mendelian randomization study

AIMS

Type 2 diabetes (T2D) is a global health burden, more prevalent among individuals with attention deficit hyperactivity disorder (ADHD) compared to the general population. To extend the knowledge base on how ADHD links to T2D, this study aimed to estimate causal effects of ADHD on T2D and to explore mediating pathways.

METHODS

We applied a two-step, two-sample Mendelian randomization (MR) design, using single nucleotide polymorphisms to genetically predict ADHD and a range of potential mediators. First, a wide range of univariable MR methods was used to investigate associations between genetically predicted ADHD and T2D, and between ADHD and the purported mediators: body mass index (BMI), childhood obesity, childhood BMI, sedentary behaviour (daily hours of TV watching), blood pressure (systolic blood pressure, diastolic blood pressure), C-reactive protein and educational attainment (EA). A mixture-of-experts method was then applied to select the MR method most likely to return a reliable estimate. We used estimates derived from multivariable MR to estimate indirect effects of ADHD on T2D through mediators.

RESULTS

Genetically predicted ADHD liability associated with 10% higher odds of T2D (OR: 1.10; 95% CI: 1.02, 1.18). From nine purported mediators studied, three showed significant individual mediation effects: EA (39.44% mediation; 95% CI: 29.00%, 49.73%), BMI (44.23% mediation; 95% CI: 34.34%, 52.03%) and TV watching (44.10% mediation; 95% CI: 30.76%, 57.80%). The combination of BMI and EA explained the largest mediating effect (53.31%, 95% CI: -1.99%, 110.38%) of the ADHD-T2D association.

CONCLUSIONS

These findings suggest a potentially causal, positive relationship between ADHD liability and T2D, with mediation through higher BMI, more TV watching and lower EA. Intervention on these factors may thus have beneficial effects on T2D risk in individuals with ADHD.

Mendelian randomization analysis of maternal coffee consumption during pregnancy on offspring neurodevelopmental difficulties in the Norwegian Mother, Father and Child Cohort Study (MoBa)

BACKGROUND

Previous observational epidemiological studies have suggested that coffee consumption during pregnancy may affect fetal neurodevelopment. However, results are inconsistent and may represent correlational rather than causal relationships. The present study investigated whether maternal coffee consumption was observationally associated and causally related to offspring childhood neurodevelopmental difficulties (NDs) in the Norwegian Mother, Father and Child Cohort Study.

METHODS

The observational relationships between maternal/paternal coffee consumption (before and during pregnancy) and offspring NDs were assessed using linear regression analyses (N = 58694 mother-child duos; N = 22 576 father-child duos). To investigate potential causal relationships, individual-level (N = 46 245 mother-child duos) and two-sample Mendelian randomization (MR) analyses were conducted using genetic variants previously associated with coffee consumption as instrumental variables.

RESULTS

We observed positive associations between maternal coffee consumption and offspring difficulties with social-communication/behavioral flexibility, and inattention/hyperactive-impulsive behavior (multiple testing corrected p < 0.005). Paternal coffee consumption (negative control) was not observationally associated with the outcomes. After adjusting for potential confounders (smoking, alcohol, education and income), the maternal associations attenuated to the null. MR analyses suggested that increased maternal coffee consumption was causally associated with social-communication difficulties (individual-level: beta = 0.128, se = 0.043, p = 0.003; two-sample: beta = 0.348, se = 0.141, p = 0.010). However, individual-level MR analyses that modelled potential pleiotropic pathways found the effect diminished (beta = 0.088, se = 0.049, p = 0.071). Individual-level MR analyses yielded similar estimates (heterogeneity p = 0.619) for the causal effect of coffee consumption on social communication difficulties in maternal coffee consumers (beta = 0.153, se = 0.071, p = 0.032) and non-consumers (beta = 0.107, se = 0.134, p = 0.424).

CONCLUSIONS

Together, our results provide little evidence for a causal effect of maternal coffee consumption on offspring NDs.

Estimation of Direct and Indirect Polygenic Effects and Gene-Environment Interactions using Polygenic Scores in Case-Parent Trio Studies

Family-based studies provide a unique opportunity to characterize genetic risks of diseases in the presence of population structure, assortative mating, and indirect genetic effects. We propose a novel framework, PGS-TRI, for the analysis of polygenic scores (PGS) in case-parent trio studies for estimation of the risk of an index condition associated with direct effects of inherited PGS, indirect effects of parental PGS, and gene-environment interactions. Extensive simulation studies demonstrate the robustness of PGS-TRI in the presence of complex population structure and assortative mating compared to alternative methods. We apply PGS-TRI to multi-ancestry trio studies of autism spectrum disorders (Ntrio = 1,517) and orofacial clefts (Ntrio = 1,904) to establish the first transmission-based estimates of risk associated with pre-defined PGS for these conditions and other related traits. For both conditions, we further explored offspring risk associated with polygenic gene-environment interactions, and direct and indirect effects of genetically predicted levels of gene expression and metabolite traits.

Genetic associations between non-cognitive skills and academic achievement over development

Non-cognitive skills, such as motivation and self-regulation, are partly heritable and predict academic achievement beyond cognitive skills. However, how the relationship between non-cognitive skills and academic achievement changes over development is unclear. The current study examined how cognitive and non-cognitive skills are associated with academic achievement from ages 7 to 16 years in a sample of over 10,000 children from England and Wales. The results showed that the association between non-cognitive skills and academic achievement increased across development. Twin and polygenic scores analyses found that the links between non-cognitive genetics and academic achievement became stronger over the school years. The results from within-family analyses indicated that non-cognitive genetic effects on academic achievement could not simply be attributed to confounding by environmental differences between nuclear families, consistent with a possible role for evocative/active gene-environment correlations. By studying genetic associations through a developmental lens, we provide further insights into the role of non-cognitive skills in academic development.

The importance of family-based sampling for biobanks

Biobanks aim to improve our understanding of health and disease by collecting and analysing diverse biological and phenotypic information in large samples. So far, biobanks have largely pursued a population-based sampling strategy, where the individual is the unit of sampling, and familial relatedness occurs sporadically and by chance. This strategy has been remarkably efficient and successful, leading to thousands of scientific discoveries across multiple research domains, and plans for the next wave of biobanks are underway. In this Perspective, we discuss the strengths and limitations of a complementary sampling strategy for future biobanks based on oversampling of close genetic relatives. Such family-based samples facilitate research that clarifies causal relationships between putative risk factors and outcomes, particularly in estimates of genetic effects, because they enable analyses that reduce or eliminate confounding due to familial and demographic factors. Family-based biobank samples would also shed new light on fundamental questions across multiple fields that are often difficult to explore in population-based samples. Despite the potential for higher costs and greater analytical complexity, the many advantages of family-based samples should often outweigh their potential challenges.

The researcher's guide to selecting biomarkers in mental health studies

Clinical mental health researchers may understandably struggle with how to incorporate biological assessments in clinical research. The options are numerous and are described in a vast and complex body of literature. Here we provide guidelines to assist mental health researchers seeking to include biological measures in their studies. Apart from a focus on behavioral outcomes as measured via interviews or questionnaires, we advocate for a focus on biological pathways in clinical trials and epidemiological studies that may help clarify pathophysiology and mechanisms of action, delineate biological subgroups of participants, mediate treatment effects, and inform personalized treatment strategies. With this paper we aim to bridge the gap between clinical and biological mental health research by (1) discussing the clinical relevance, measurement reliability, and feasibility of relevant peripheral biomarkers; (2) addressing five types of biological tissues, namely blood, saliva, urine, stool and hair; and (3) providing information on how to control sources of measurement variability.

Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations

BACKGROUND

The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing.

OBJECTIVE AND RATIONALE

This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom.

SEARCH METHODS

We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant.

OUTCOMES

The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling.

WIDER IMPLICATIONS

The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.

Causal interpretations of family GWAS in the presence of heterogeneous effects

Family-based genome-wide association studies (GWASs) are often claimed to provide an unbiased estimate of the average causal effects (or average treatment effects; ATEs) of alleles, on the basis of an analogy between the random transmission of alleles from parents to children and a randomized controlled trial. We show that this claim does not hold in general. Because Mendelian segregation only randomizes alleles among children of heterozygotes, the effects of alleles in the children of homozygotes are not observable. This feature will matter if an allele has different average effects in the children of homozygotes and heterozygotes, as can arise in the presence of gene-by-environment interactions, gene-by-gene interactions, or differences in linkage disequilibrium patterns. At a single locus, family-based GWAS can be thought of as providing an unbiased estimate of the average effect in the children of heterozygotes (i.e., a local average treatment effect; LATE). This interpretation does not extend to polygenic scores (PGSs), however, because different sets of SNPs are heterozygous in each family. Therefore, other than under specific conditions, the within-family regression slope of a PGS cannot be assumed to provide an unbiased estimate of the LATE for any subset or weighted average of families. In practice, the potential biases of a family-based GWAS are likely smaller than those that can arise from confounding in a standard, population-based GWAS, and so family studies remain important for the dissection of genetic contributions to phenotypic variation. Nonetheless, their causal interpretation is less straightforward than has been widely appreciated.

Social Background Effects on Educational Outcomes-New Insights from Modern Genetic Science

Sociological theory and empirical research have found that parents' socioeconomic status and related resources affect their children's educational outcomes. Findings from behavior genetics reveal genetic underpinnings of the intergenerational transmission of education, thus altering previous conclusions about purely environmental transmission mechanisms. In recent years, studies in molecular genetics have led to new insights. Genomic data, polygenic scores, and other facets of sociogenomics are increasingly used to advance research in social stratification. Notably, the 2018 discovery of "genetic nurture" suggested that parents' genes influence children above and beyond the genes they directly transmitted to their children. Such indirect genetic effects can be interpreted as consequences of parental behavior, which is itself influenced by the parents' genetics and is essential for their children's environment. Indirect genetic effects fit hand in glove with the sociological literature because they represent environmental transmission mechanisms. For instance, parenting behaviors, which are partly influenced by parents' genes, shape children's home environments and possibly their later educational outcomes. However, current findings based on more sophisticated research designs demonstrate that "genetic nurture" effects are actually much smaller than initially assumed and hence call for a reevaluation of common narratives found in the social stratification literature. In this paper, we review recent developments and ongoing research integrating molecular genetics to study educational outcomes, and we discuss their implications for sociological stratification research.

Effect of polygenic scores of telomere length alleles on telomere length in newborns and parents

In adults, polygenic scores (PGSs) of telomere length (TL) alleles explain about 4.5% of the variance in TL, as measured by quantitative polymerase chain reaction (qPCR). Yet, these PGSs strongly infer a causal role of telomeres in aging-related diseases. To better understand the determinants of TL through the lifespan, it is essential to examine to what extent these PGSs explain TL in newborns. This study investigates the effect of PGSs on TL in both newborns and their parents, with TL measured by Southern blotting and expressed in base-pairs (bp). Additionally, the study explores the impact of PGSs related to transmitted or non-transmitted alleles on TL in newborns. For parents and newborns, the PGS effects on TL were 172 bp (p =  2.03 × 10-15) and 161 bp (p =  3.06 × 10-8), explaining 6.6% and 5.2% of the TL variance, respectively. The strongest PGS effect was shown for maternally transmitted alleles in newborn girls, amounting to 214 bp (p =  3.77 × 10-6) and explaining 7.8% of the TL variance. The PGS effect of non-transmitted alleles was 56 bp (p = 0.0593) and explained 0.6% of the TL variance. Our findings highlight the importance of TL genetics in understanding early-life determinants of TL. They point to the potential utility of PGSs composed of TL alleles in identifying susceptibility to aging-related diseases from birth and reveal the presence of sexual dimorphism in the effect of TL alleles on TL in newborns. Finally, we attribute the higher TL variance explained by PGSs in our study to TL measurement by Southern blotting.