Education can reduce health differences related to genetic risk of obesity

Polygenic scores capture genetic modification of the adiposity-cardiometabolic risk factor relationship

Optimal use of genetics for precision medicine requires polygenic scores (PGS) that predict not just risk of disease, but also response to pharmaceutical or lifestyle interventions. These are detectable in observational datasets as PGS-by-exposure (PGS×E) interactions. Existing literature suggests that PGS based on interactions (iPGS) or variance effects (vPGS) may be more powerful than standard marginal PGS (mPGS) for the detection of PGS×E, but these have yet to be systematically compared. We describe a generalized pipeline for the development and comparison of different PGS types and apply it to detect genetic modification of the relationship between adiposity (measured by body mass index [BMI]) and a broad set of cardiometabolic risk factors (CRFs). Our applied analysis in the UK Biobank cohort identified significant PGS×BMI for at least one PGS type for 16/20 of these CRFs, many of which replicated in the All of Us cohort. Among PGS types, iPGS uncovered interactions with BMI most consistently across CRFs, with the strongest interactions impacting biomarkers of liver function (e.g., alanine aminotransferase [ALT]). Exploring the ALT iPGS more in-depth, we find a substantial effect modification of up to 72% larger BMI-ALT association in the top iPGS decile in All of Us, and further provide evidence that the iPGS prioritizes variants affecting hepatic lipid export. Taken together, our study provides a framework for the development and comparison of PGS×E strategies, quantifies genetic impacts on the adiposity-cardiometabolic risk relationship, and informs efforts to move toward clinically useful response-focused PGS.

Understanding genetic variants in context

Over the last three decades, human genetics has gone from dissecting high-penetrance Mendelian diseases to discovering the vast and complex genetic etiology of common human diseases. In tackling this complexity, scientists have discovered the importance of numerous genetic processes - most notably functional regulatory elements - in the development and progression of these diseases. Simultaneously, scientists have increasingly used multiplex assays of variant effect to systematically phenotype the cellular consequences of millions of genetic variants. In this article, we argue that the context of genetic variants - at all scales, from other genetic variants and gene regulation to cell biology to organismal environment - are critical components of how we can employ genomics to interpret these variants, and ultimately treat these diseases. We describe approaches to extend existing experimental assays and computational approaches to examine and quantify the importance of this context, including through causal analytic approaches. Having a unified understanding of the molecular, physiological, and environmental processes governing the interpretation of genetic variants is sorely needed for the field, and this perspective argues for feasible approaches by which the combined interpretation of cellular, animal, and epidemiological data can yield that knowledge.

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.

Exploring the importance of family socio-economic position on the association between parental BMI and offspring BMI trajectories

PURPOSE

We aimed to investigate the associations between parental BMI and offspring BMI trajectories and to explore whether the parent-offspring BMI growth trajectory association differed according to family SEP or social mobility.

METHODS

We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC). Children's weight and height were collected from 1 to 18 years. Parents' height and weight were reported pre-pregnancy. We assessed family SEP by measuring parents' and grandparents' educational attainment, social class, and social mobility by changes in education attainment across generations. Multilevel models were used to develop trajectories and assess patterns of change in offspring BMI, to associate parental BMI with these trajectories, and explore whether these associations differed by family SEP and social mobility.

RESULTS

13,612 children were included in the analyses. The average BMI of offspring whose parents were overweight or obese was higher throughout childhood and adolescence, compared to those with parents of normal BMI. Parental and grandparental low SEP were associated with higher child BMI, but there was little evidence of modification of parent-offspring associations. For example, at age 15 years the predicted mean BMI difference between children of overweight or obese mothers versus normal-weight mothers was 12.5 % (95 %CI: 10.1 % to 14.7 %) and 12.2 % (95 %CI: 10.3 % to 13.7 %) for high and low grandparental SEP, respectively.

DISCUSSION

These findings strengthen the evidence that higher parental BMI and lower family SEP were associated with higher offspring BMI, but we did not observe strong evidence that family SEP modifies the parental-offspring BMI association.

The role of gene-environment interaction in the formation of risk attitudes

Understanding the formation of risk preferences is crucial for elucidating the roots of economic, social, and health inequalities. However, this area remains inadequately explored. This study employs a risk preference measure directly linked to the labor market to examine whether previous experiences with high unemployment rates influence current risk decision-making among the elderly, and whether this impact varies by genotype. The findings indicate that individuals with low genetic predispositions for risk tolerance are more significantly influenced by historical fluctuations in unemployment rates than those with high genetic predispositions for risk tolerance. Consequently, this paper identifies genetic endowment as a crucial moderating factor that shapes how past experiences impact current decision-making processes. This disparity in how past experiences shape risk preferences based on genetic predisposition may further amplify inequalities in health, wealth, income, and other outcomes associated with risk preferences.

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.

Advantageous early-life environments cushion the genetic risk for ischemic heart disease

In one of the first papers on the impact of early-life conditions on individuals' health in older age, Barker and Osmond [Lancet, 327, 1077-1081 (1986)] show a strong positive relationship between infant mortality rates in the 1920s and ischemic heart disease in the 1970s. We merge historical data on infant mortality rates to 370,000 individual records in the UK Biobank using information on local area and year of birth. We replicate the association between the early-life infant mortality rate and later-life ischemic heart disease in our sample. We then go "beyond Barker," by showing considerable genetic heterogeneity in this association that is robust to within-area as well as within-family analyses. We find no association between the polygenic index and heart disease in areas with the lowest infant mortality rates, but a strong positive relationship in areas characterized by high infant mortality. These findings suggest that advantageous environments can cushion one's genetic disease risk.

Unequal before death: The effect of paternal education on children's old-age mortality in the United States

A growing body of research documents the relevance of parental education as a marker of family socio-economic status for children's later-life health outcomes. A strand of this literature evaluates how the early-life environment shapes mortality outcomes during infancy and childhood. However, the evidence on mortality during the life course and old age is limited. This paper contributes to the literature by analysing the association between paternal education and children's old-age mortality. We use data from Social Security Administration death records over the years 1988-2005 linked to the United States 1940 Census. Applying a family(cousin)- fixed-effects model to account for shared environment, childhood exposures, and common endowments that may confound the long-term links, we find that having a father with a college or high-school education, compared with elementary/no education, is associated with a 4.6- or 2.6-month-higher age at death, respectively, for the child, conditional on them surviving to age 47.

Statistical methods for gene-environment interaction analysis

Most human complex phenotypes result from multiple genetic and environmental factors and their interactions. Understanding the mechanisms by which genetic and environmental factors interact offers valuable insights into the genetic architecture of complex traits and holds great potential for advancing precision medicine. The emergence of large population biobanks has led to the development of numerous statistical methods aiming at identifying gene-environment interactions (G × E). In this review, we present state-of-the-art statistical methodologies for G × E analysis. We will survey a spectrum of approaches for single-variant G × E mapping, followed by various techniques for polygenic G × E analysis. We conclude this review with a discussion on the future directions and challenges in G × E research.

The long-term effects of early-life pollution exposure: Evidence from the London smog

This paper uses a large UK cohort to investigate the impact of early-life pollution exposure on individuals' human capital and health outcomes in older age. We compare individuals who were exposed to the London smog in December 1952 whilst in utero or in infancy to those born after the smog and those born at the same time but in unaffected areas. We find that those exposed to the smog have substantially lower fluid intelligence and worse respiratory health, with some evidence of a reduction in years of schooling.

Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G)

The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment.

Causal interpretations of family GWAS in the presence of heterogeneous effects

Family-based genome-wide association studies (GWAS) have emerged as a gold standard for assessing causal effects of alleles and polygenic scores. Notably, family studies are often claimed to provide an unbiased estimate of the average causal effect (or average treatment effect; ATE) of an allele, on the basis of an analogy between the random transmission of alleles from parents to children and a randomized controlled trial. Here, we show that this interpretation 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. Consequently, 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 LD patterns, family studies provide a biased estimate of the average effect in the sample. At a single locus, family-based association studies 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, 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 for any subset or weighted average of families. Instead, family-based studies can be reinterpreted as enabling an unbiased estimate of the extent to which Mendelian segregation at loci in the PGS contributes to the population-level variance in the trait. Because this estimate does not include the between-family variance, however, this interpretation applies to only (roughly) half of the sample PGS variance. In practice, the potential biases of a family-based GWAS are likely smaller than those arising from confounding in a standard, population-based GWAS, and so family studies remain important for the dissection of genetic contributions to phenotypic variation. Nonetheless, the causal interpretation of family-based GWAS estimates is less straightforward than has been widely appreciated.

Heterogenous trajectories in physical, mental and cognitive health among older Americans: Roles of genetics and life course contextual factors

We investigate the roles of genetic predispositions, childhood SES and adult educational attainment in shaping trajectories for three important components of the overall health of older adults -- BMI, depressive symptoms and cognition. We use the Health & Retirement Study (HRS) and group-based trajectory modeling (GBTM) to identify subgroups of people who share the same underlying trajectories ages 51-94 years. After identifying common underlying health trajectories, we use fractional multinomial logit models to estimate associations of (1) polygenic scores for BMI, depression, ever-smoked, education, cognition and subjective wellbeing, (2) childhood SES and (3) educational attainment with the probabilities of trajectory group memberships. While genetic predispositions do play a part in predicting trajectory group memberships, our results highlight the long arm of socioeconomic factors. Educational attainment is the most robust predictor-it predicts increased probabilities of belonging to trajectories with BMI in the normal range, low depressive symptoms and very-high initial cognition. Childhood circumstances are manifested in trajectories to a lesser extent, with childhood SES predicting higher likelihood of being on the low depressive symptoms and very-high initial cognition trajectories. We also find suggestive evidence that associations of educational attainment on the probabilities of being on trajectories with BMI in the normal range, low depressive symptoms and very-high initial cognition vary with genetic predispositions. Our results suggest that policies to increase educational attainment may improve population health by increasing the likelihood of belonging to "good" aging trajectories.

Analysis of the Impact of Public Services on Residents' Health: A Spatial Econometric Analysis of Chinese Provinces

Objectives: The aim of this study was to explore the mechanism between public services and residents' health, focusing on the role of spatial geographical factors. Methods: Leveraging a comprehensive panel dataset encompassing 30 mainland Chinese provinces from 2007 to 2019, this study engineered a spatial Durbin model furnished with dual fixed effects through the application of the Lagrange multiplier, Hausman, and likelihood ratio tests. The primary objective was to delve into the repercussions of varying public service levels on residents' health outcomes. Results: The empirical findings reveal a palpable spatial autocorrelation between residents' health outcomes and the public services levels dispensed across Chinese provinces. Intriguingly, an elevation in the public service level in a given province not only ameliorates its residents' health outcomes but also triggers a spatial spillover effect, thereby positively influencing residents' health in neighboring provinces. The rigorous endogeneity and robustness checks affirm the reliability of the principal outcomes. Conclusion: Due to the increase in social uncertainty, all regions should break free of the administrative monopoly, enhance regional integration and development, and improve residents' health status by clustering public service supply.

Overcoming attenuation bias in regressions using polygenic indices

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

The impact of entrepreneurship research on other academic fields

The remarkable ascent of entrepreneurship witnessed as a scientific field over the last 4 decades has been made possible by entrepreneurship's ability to absorb theories, paradigms, and methods from other fields such as economics, psychology, sociology, geography, and even biology. The respectability of entrepreneurship as an academic discipline is now evidenced by many other fields starting to borrow from the entrepreneurship view. In the present paper, seven examples are given from this "pay back" development. These examples were first presented during a seminar at the Erasmus Entrepreneurship Event called what has the entrepreneurship view to offer to other academic fields? This article elaborates on the core ideas of these presentations and focuses on the overarching question of how entrepreneurship research impacts the development of other academic fields. We found that entrepreneurship research questions the core assumptions of other academic fields and provides new insights into the antecedents, mechanisms, and consequences of their respective core phenomena. Moreover, entrepreneurship research helps to legitimize other academic fields both practically and academically.

Rank concordance of polygenic indices

Polygenic indices (PGIs) are increasingly used to identify individuals at risk of developing disease and are advocated as screening tools for personalized medicine and education. Here we empirically assess rank concordance between PGIs created with different construction methods and discovery samples, focusing on cardiovascular disease and educational attainment. We find Spearman rank correlations between 0.17 and 0.93 for cardiovascular disease, and 0.40 and 0.83 for educational attainment, indicating highly unstable rankings across different PGIs for the same trait. Potential consequences for personalized medicine and gene-environment (G × E) interplay are illustrated using data from the UK Biobank. Simulations show how rank discordance mainly derives from a limited discovery sample size and reveal a tight link between the explained variance of a PGI and its ranking precision. We conclude that PGI-based ranking is highly dependent on PGI choice, such that current PGIs do not have the desired precision to be used routinely for personalized intervention.

Low and differential polygenic score generalizability among African populations due largely to genetic diversity

African populations are vastly underrepresented in genetic studies but have the most genetic variation and face wide-ranging environmental exposures globally. Because systematic evaluations of genetic prediction had not yet been conducted in ancestries that span African diversity, we calculated polygenic risk scores (PRSs) in simulations across Africa and in empirical data from South Africa, Uganda, and the United Kingdom to better understand the generalizability of genetic studies. PRS accuracy improves with ancestry-matched discovery cohorts more than from ancestry-mismatched studies. Within ancestrally and ethnically diverse South African individuals, we find that PRS accuracy is low for all traits but varies across groups. Differences in African ancestries contribute more to variability in PRS accuracy than other large cohort differences considered between individuals in the United Kingdom versus Uganda. We computed PRS in African ancestry populations using existing European-only versus ancestrally diverse genetic studies; the increased diversity produced the largest accuracy gains for hemoglobin concentration and white blood cell count, reflecting large-effect ancestry-enriched variants in genes known to influence sickle cell anemia and the allergic response, respectively. Differences in PRS accuracy across African ancestries originating from diverse regions are as large as across out-of-Africa continental ancestries, requiring commensurate nuance.

The production of within-family inequality: Insights and implications of integrating genetic data

The integration of genetic data within large-scale social and health surveys provides new opportunities to test long-standing theories of parental investments in children and within-family inequality. Genetic predictors, called polygenic scores, allow novel assessments of young children's abilities that are uncontaminated by parental investments, and family-based samples allow indirect tests of whether children's abilities are reinforced or compensated. We use over 16,000 sibling pairs from the UK Biobank to test whether the relative ranking of siblings' polygenic scores for educational attainment is consequential for actual attainments. We find evidence consistent with compensatory processes, on average, where the association between genotype and phenotype of educational attainment is reduced by over 20% for the higher-ranked sibling compared to the lower-ranked sibling. These effects are most pronounced in high socioeconomic status areas. We find no evidence that similar processes hold in the case of height or for relatives who are not full biological siblings (e.g. cousins). Our results provide a new use of polygenic scores to understand processes that generate within-family inequalities and also suggest important caveats to causal interpretations the effects of polygenic scores using sibling difference designs. Future work should seek to replicate these findings in other data and contexts.

Wrestling with Social and Behavioral Genomics: Risks, Potential Benefits, and Ethical Responsibility

In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often-ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science-including genomewide association studies and polygenic indexes-can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. SBG research that compares individuals within a group according to a "sensitive" phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk-benefit profile.

Interpreting population and family-based genome-wide association studies in the presence of confounding

A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding, and can also absorb the 'indirect' genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of Mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect size estimates are used in polygenic scores. We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. In addition to known biases that can arise in family-based GWASs when interactions between family members are ignored, we show that biases can also arise from gene-by-environment (G×E) interactions when parental genotypes are not distributed identically across interacting environmental and genetic backgrounds. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding and interactions.

The social origins of obesity within and across generations

We propose a model for obesity development that traces a considerable part of its origins to the social domain (mainly different forms of prolonged social adversity), both within and across generations, working in tandem with a genetic predisposition. To facilitate overview of social pathways, we place particular focus on three areas that form a cascading sequence: (A) social adversity within the family (parents having a low education, a low social position, poverty and financial insecurity; offspring being exposed to gestational stress, unmet social and emotional needs, abuse, maltreatment and other negative life events, social deprivation and relationship discord); (B) increasing levels of insecurity, negative emotions, chronic stress, and a disruption of energy homeostasis; and (C) weight gain and obesity, eliciting further social stress and weight stigma in both generations. Social adversity, when combined with genetic predisposition, thereby substantially contributes to highly effective transmission of obesity from parents to offspring, as well as to obesity development within current generations. Prevention efforts may benefit from mitigating multiple types of social adversity in individuals, families, and communities, notably poverty and financial strain, and by improving education levels.

Can genomic research make a useful contribution to social policy?

As genetic research into outcomes beyond health gathers pace, largely through the use of genome-wide association studies, interest from policy-makers has grown. In the last year, two UK reports have explored the policy implications of genomic research, one from the UK Government Office for Science and one from the Early Intervention Foundation. In this article, we explore areas of consensus between these two reports and use them to propose priorities for policy-makers as we prepare for what some have termed a 'genetic revolution'. Both reports agree on two clear recommendations for science and policy communities. One of these relates to public education and engagement, and the other to ensuring that genomic databases are ancestrally diverse. Both reports agree that-even if it is found to be a viable and ethical idea in the medium-term future-DNA data should not be incorporated into social policy before these two issues have been comprehensively addressed. In the article, we argue that scientists are taking the lead on tackling the diversity deficit but that there is a clear role for policy-makers to play in addressing low genetic literacy in society, and that this is a matter of urgency.

How interactions between ADHD and schools affect educational achievement: a family-based genetically sensitive study

BACKGROUND

Children with ADHD tend to achieve less than their peers in school. It is unknown whether schools moderate this association. Nonrandom selection of children into schools related to variations in their ADHD risk poses a methodological problem.

METHODS

We linked data on ADHD symptoms of inattention and hyperactivity and parent-child ADHD polygenic scores (PGS) from the Norwegian Mother, Father, and Child Cohort Study (MoBa) to achievement in standardised tests and school identifiers. We estimated interactions of schools with individual differences between students in inattention, hyperactivity, and ADHD-PGS using multilevel models with random slopes for ADHD effects on achievement over schools. In our PGS analyses, we adjust for parental selection of schools by adjusting for parental ADHD-PGS (a within-family PGS design). We then tested whether five school sociodemographic measures explained any interactions.

RESULTS

Analysis of up to 23,598 students attending 2,579 schools revealed interactions between school and ADHD effects on achievement. The variability between schools in the effects of inattention, hyperactivity and within-family ADHD-PGS on achievement was 0.08, 0.07 and 0.05 SDs, respectively. For example, the average effect of inattention on achievement was β = -0.23 (SE = 0.009), but in 2.5% of schools with the weakest effects, the value was -0.07 or less. ADHD has a weaker effect on achievement in higher-performing schools. Schools make more of a difference to the achievements of students with higher levels of ADHD, explaining over four times as much variance in achievement for those with high versus average inattention symptoms. School sociodemographic measures could not explain the ADHD-by-school interactions.

CONCLUSIONS

Although ADHD symptoms and genetic risk tend to hinder achievement, schools where their effects are weaker do exist. Differences between schools in support for children with ADHD should be evened out.

An in-laboratory stressor reveals unique genetic variation in child cortisol output

Dysregulation of biological stress response, as measured by cortisol output, has been a primary candidate mechanism for how social experiences become biologically embedded. Cortisol is the primary output of the hypothalamic pituitary adrenal (HPA) axis. Cortisol levels vary systematically across the day and change in response to both sudden, acute stress experiences as well as prolonged exposure to environmental stress. Using data from 8- to 15-year-old twins in the Texas Twin Project, we investigate the extent to which genetic influences are shared across different measures of cortisol output: chronic cortisol accumulations in hair (n = 1,104), diurnal variation in salivary output (n = 488), and salivary response to a standardized, acute in-laboratory stressor (n = 537). Multivariate twin models indicate that genetic factors regulating cortisol response to the in-laboratory stressor are separable from those regulating baseline cortisol levels, naturally occurring diurnal variation in cortisol, and hair cortisol levels. These findings illustrate that novel environments can reveal unique genetic variation, reordering people in terms of their observed phenotype rather than only magnifying or mitigating preexisting differences. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A quantile integral linear model to quantify genetic effects on phenotypic variability

Detecting genetic variants associated with the variance of complex traits, that is, variance quantitative trait loci (vQTLs), can provide crucial insights into the interplay between genes and environments and how they jointly shape human phenotypes in the population. We propose a quantile integral linear model (QUAIL) to estimate genetic effects on trait variability. Through extensive simulations and analyses of real data, we demonstrate that QUAIL provides computationally efficient and statistically powerful vQTL mapping that is robust to non-Gaussian phenotypes and confounding effects on phenotypic variability. Applied to UK Biobank (n = 375,791), QUAIL identified 11 vQTLs for body mass index (BMI) that have not been previously reported. Top vQTL findings showed substantial enrichment for interactions with physical activities and sedentary behavior. Furthermore, variance polygenic scores (vPGSs) based on QUAIL effect estimates showed superior predictive performance on both population-level and within-individual BMI variability compared to existing approaches. Overall, QUAIL is a unified framework to quantify genetic effects on the phenotypic variability at both single-variant and vPGS levels. It addresses critical limitations in existing approaches and may have broad applications in future gene-environment interaction studies.

Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores

Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and diseases by aggregating information across multiple genetic variants identified from genome-wide association studies. PRS can predict a broad spectrum of diseases and have therefore been widely used in research settings. Some work has investigated their potential applications as biomarkers in preventative medicine, but significant work is still needed to definitively establish and communicate absolute risk to patients for genetic and modifiable risk factors across demographic groups. However, the biggest limitation of PRS currently is that they show poor generalizability across diverse ancestries and cohorts. Major efforts are underway through methodological development and data generation initiatives to improve their generalizability. This review aims to comprehensively discuss current progress on the development of PRS, the factors that affect their generalizability, and promising areas for improving their accuracy, portability, and implementation.

The consequences of a year of the COVID-19 pandemic for the mental health of young adult twins in England and Wales

BACKGROUND

The COVID-19 pandemic has affected all our lives, not only through the infection itself but also through the measures taken to control the spread of the virus (e.g. lockdown).

AIMS

Here, we investigated how the COVID-19 pandemic and unprecedented lockdown affected the mental health of young adults in England and Wales.

METHOD

We compared the mental health symptoms of up to 4773 twins in their mid-20s in 2018 prior to the COVID-19 pandemic (T1) and during four-wave longitudinal data collection during the pandemic in April, July and October 2020, and in March 2021 (T2-T5) using phenotypic and genetic longitudinal designs.

RESULTS

The average changes in mental health were small to medium and mainly occurred from T1 to T2 (average Cohen d = 0.14). Despite the expectation of catastrophic effects of the pandemic on mental health, we did not observe trends in worsening mental health during the pandemic (T3-T5). Young people with pre-existing mental health problems were disproportionately affected at the beginning of the pandemic, but their increased problems largely subsided as the pandemic persisted. Twin analyses indicated that the aetiology of individual differences in mental health symptoms did not change during the lockdown (average heritability 33%); the average genetic correlation between T1 and T2-T5 was 0.95, indicating that genetic effects before the pandemic were substantially correlated with genetic effects up to a year later.

CONCLUSIONS

We conclude that on average the mental health of young adults in England and Wales has been remarkably resilient to the effects of the pandemic and associated lockdown.

Polygenic and socioeconomic risk for high body mass index: 69 years of follow-up across life

Genetic influences on body mass index (BMI) appear to markedly differ across life, yet existing research is equivocal and limited by a paucity of life course data. We thus used a birth cohort study to investigate differences in association and explained variance in polygenic risk for high BMI across infancy to old age (2-69 years). A secondary aim was to investigate how the association between BMI and a key purported environmental determinant (childhood socioeconomic position) differed across life, and whether this operated independently and/or multiplicatively of genetic influences. Data were from up to 2677 participants in the MRC National Survey of Health and Development, with measured BMI at 12 timepoints from 2-69 years. We used multiple polygenic indices from GWAS of adult and childhood BMI, and investigated their associations with BMI at each age. For polygenic liability to higher adult BMI, the trajectories of effect size (β) and explained variance (R2) diverged: explained variance peaked in early adulthood and plateaued thereafter, while absolute effect sizes increased throughout adulthood. For polygenic liability to higher childhood BMI, explained variance was largest in adolescence and early adulthood; effect sizes were marginally smaller in absolute terms from adolescence to adulthood. All polygenic indices were related to higher variation in BMI; quantile regression analyses showed that effect sizes were sizably larger at the upper end of the BMI distribution. Socioeconomic and polygenic risk for higher BMI across life appear to operate additively; we found little evidence of interaction. Our findings highlight the likely independent influences of polygenic and socioeconomic factors on BMI across life. Despite sizable associations, the BMI variance explained by each plateaued or declined across adulthood while BMI variance itself increased. This is suggestive of the increasing importance of chance ('non-shared') environmental influences on BMI across life.

Polygenic Scores for Plasticity: A New Tool for Studying Gene-Environment Interplay

Fertility, health, education, and other outcomes of interest to demographers are the product of an individual's genetic makeup and their social environment. Yet, gene × environment (G×E) research deploys a limited toolkit on the genetic side to study the gene-environment interplay, relying on polygenic scores (PGSs) that reflect the influence of genetics on levels of an outcome. In this article, we develop a genetic summary measure better suited for G×E research: variance polygenic scores (vPGSs), which are PGSs that reflect genetic contributions to plasticity in outcomes. First, we use the UK Biobank (N ∼ 408,000 in the analytic sample) and the Health and Retirement Study (N ∼ 5,700 in the analytic sample) to compare four approaches to constructing PGSs for plasticity. The results show that widely used methods for discovering which genetic variants affect outcome variability fail to serve as distinctive new tools for G×E. Second, using the PGSs that do capture distinctive genetic contributions to plasticity, we analyze heterogeneous effects of a UK education reform on health and educational attainment. The results show the properties of a useful new tool for population scientists studying the interplay of nature and nurture and for population-based studies that are releasing PGSs to applied researchers.

Lottery, luck, or legacy. A review of "The Genetic Lottery: Why DNA matters for social equality"

A book review of "The genetic lottery: why DNA matters for social equality." (Princeton University Press, 2021) by Kathryn Paige Harden.

Genetic and environmental influences on quality of life: The COVID-19 pandemic as a natural experiment

By treating the coronavirus disease 2019 (COVID-19) pandemic as a natural experiment, we examine the influence of substantial environmental change (i.e., lockdown measures) on individual differences in quality of life (QoL) in the Netherlands. We compare QoL scores before the pandemic (N = 25,772) to QoL scores during the pandemic (N = 17,222) in a sample of twins and their family members. On a 10-point scale, we find a significant decrease in mean QoL from 7.73 (SD = 1.06) before the pandemic to 7.02 (SD = 1.36) during the pandemic (Cohen's d = 0.49). Additionally, variance decomposition shows an increase in unique environmental variance during the pandemic (0.30-1.08), and a decrease in the heritability estimate from 30.9% to 15.5%. We hypothesize that the increased environmental variance is the result of lockdown measures not impacting everybody equally. Whether these effects persist over longer periods and how they impact health inequalities remain topics for future investigation.

Pathways of Parental Education on Children's and Adolescent's Body Mass Index: The Mediating Roles of Behavioral and Psychological Factors

Aim

The increasing body mass index (BMI) often followed by overweight and obesity is a global health problem of the 21st century. Children and adolescents with lower socioeconomic status are more affected than their counterparts. The mechanisms behind these differences must be well understood to develop effective prevention strategies. This analysis aims at examining the association of parental education as an indicator of the socioeconomic status on children's and adolescent's body mass index and the role of behavioral and psychological risk factors for a higher BMI longitudinally.

Methods

The analysis was based on a nationwide sample of N = 460 children and adolescents, aged 11 to 17 at baseline (2009-2012), who took part in the representative BELLA study, the mental health module of the German National Health Interview and Examination Survey among Children and Adolescents (KiGGS). A follow-up was conducted 5 years later. Using mediation analyses, the mediating effects of breakfast consumption, consumption of sugar-sweetened beverages, screen time, physical activity, mental health problems (Strengths and Difficulties Questionnaire), and health-related quality of life (KIDSCREEN-10) on the association of parent's years of education on their children's BMI were investigated.

Results

A lower level of parental education was significantly associated with a higher BMI in children and adolescents 5 years later. The association was partially mediated by breakfast consumption and total screen time, with breakfast consumption mediating 16.7% and total screen time 27.8% of the association. After controlling for age, gender, and migration status, only breakfast consumption remained a partial mediator (8.5%). Other included variables had no mediating effects.

Conclusions

Preventive measures should be mainly targeted at children and adolescents of parents with lower educational levels. Tailored strategies to prevent the development of overweight and obesity in this population among children and adolescents should promote daily breakfast consumption at home and reducing screen time.

EDUCATION AND INCOME GRADIENTS IN LONGEVITY: THE ROLE OF POLICY

Education and income are strong predictors of health and longevity. In the last 20 years many efforts have been made to understand if these relationships are causal and what the possible role of policy should be as a result. The evidence from various studies is ambiguous: the effects of education and income policies on health are heterogeneous and vary over time, and across places and populations. I discuss explanations for these disparate results and suggest directions for future research.

The Interaction Between Genetic Variant ZNF804A rs1344706 and Alcohol Withdrawal on Impulsivity: Evidence for the Diathesis-Stress Model

Objective: Alcohol use disorder (AUD) is the most common substance use disorder, which may relate to increased impulsivity. A more detailed understanding of the potential moderating factor on association between AUD and impulsivity is likely to have far-reaching effects. This study aims to examine whether the interaction between a genetic variant ZNF804A rs1344706 and alcohol use is related to impulsivity in Chinese Han adult males diagnosed with AUD. Methods: A total of 455 Chinese Han adult males diagnosed with AUD were included in this study. Impulsivity was assessed using Barratt Impulsiveness Scale. Alcohol dependence was measured by Michigan Alcoholism Screening Test. Genomic DNA was extracted from peripheral blood of participants and genotyped. Results: Hierarchical multiple regression yielded a significant interaction between ZNF804A rs1344706 and alcohol use (β = 0.20, p = 0.0237). Then, A region of significance (RoS) test was performed to interpret the interaction effect. Re-parameterized regression models revealed that the interaction between ZNF804A rs1344706 and alcohol problem severity fit to the weak diathesis-stress model (R 2 = 0.15, p < 0.0010), indicating that the T allele carriers are more susceptible to alcohol problem severity, jointly contributing to impulsivity. Conclusions: This study, which analyzed a specific gene-environment interaction, demonstrated that carriers of the T allele of ZNF804A rs1344706 may be more susceptible to alcohol problem severity, correlated with higher levels of impulsivity during withdrawal.

Health endowments, schooling allocation in the family, and longevity: Evidence from US twins

We analyze data from the Minnesota Twin Registry (MTR), combined with the Socioeconomic Survey of Twins (SST), and new mortality data, and contribute to two bodies of literature. First, we demonstrate a beneficial causal effect of education on health and longevity in contrast to other twin-based studies of the US population, which show little or no effect of education on health. Second, we present evidence that is consistent with parental compensation through education for differences in their children's endowments that predict health, but find no evidence that parents reinforce differences in endowments that predict earnings. We argue that there is a bias towards detecting reinforcement both in this paper and in the literature. Despite this bias, we still find statistical evidence of compensating behavior. We account for observed and unobserved confounding factors, sample selection bias, and measurement error in education.

Socioeconomic Vulnerability Index and Obesity among Korean Adults

Examining the socioeconomic vulnerability–obesity relationship is a different approach than comparing obesity rates according to the socioeconomic level. This study explored the socioeconomic vulnerability–obesity relationship among Korean adults. This secondary analysis used data from the Korea National Health and Nutrition Examination Survey, which were collected nationwide from participants aged 30–64 years. Seven socioeconomic indicators (education level, residential area, personal income level, household income level, food insecurity, house ownership, and national basic livelihood security beneficiary status) were used to create the socioeconomic vulnerability index. The prevalence of obesity was higher in the lowest socioeconomic vulnerability index quartile than in the highest socioeconomic vulnerability index quartile (odds ratio = 1.31; 95% confidence interval = 1.13–1.52) after adjusting for gender. When developing future interventions for the prevention and management of obesity, health care providers and researchers need to consider the differences in socioeconomic vulnerability index in adults.

Genetic predispositions moderate the effectiveness of tobacco excise taxes

BACKGROUND

Tobacco consumption is one of the leading causes of preventable death. In this study, we analyze whether someone's genetic predisposition to smoking moderates the response to tobacco excise taxes.

METHODS

We interact polygenic scores for smoking behavior with state-level tobacco excise taxes in longitudinal data (1992-2016) from the US Health and Retirement Study (N = 12,058).

RESULTS

Someone's genetic propensity to smoking moderates the effect of tobacco excise taxes on smoking behavior along the extensive margin (smoking vs. not smoking) and the intensive margin (the amount of tobacco consumed). In our analysis sample, we do not find a significant gene-environment interaction effect on smoking cessation.

CONCLUSIONS

When tobacco excise taxes are relatively high, those with a high genetic predisposition to smoking are less likely (i) to smoke, and (ii) to smoke heavily. While tobacco excise taxes have been effective in reducing smoking, the gene-environment interaction effects we observe in our sample suggest that policy makers could benefit from taking into account the moderating role of genes in the design of future tobacco control policies.

Genetic Contribution to Concern for Nature and Proenvironmental Behavior

Earth is undergoing a devastating extinction crisis caused by human impacts on nature, but only a fraction of society is strongly concerned and acting on the crisis. Understanding what determines people's concern for nature, environmental movement activism, and personal conservation behavior is fundamental if sustainability is to be achieved. Despite its potential importance, the study of the genetic contribution to concern for nature and proenvironmental behaviors has been neglected. Using a twin data set (N = 2312), we show moderate heritability (30%–40%) for concern for nature, environmental movement activism, and personal conservation behavior and high genetic correlations between them (.6–.7), suggesting a partially shared genetic basis. Our results shed light on the individual variation in sustainable behaviors, highlighting the importance of understanding both the environmental and genetic components in the pursuit of sustainability.

Genetic propensity for obesity, socioeconomic position, and trajectories of body mass index in older adults

Identifying how socioeconomic positioning and genetic factors interact in the development of obesity is imperative for population-level obesity prevention strategies. The current study investigated whether social positioning, either independently or through interaction with a polygenic score for Body Mass Index (BMI-PGS), influences BMI trajectories across older adulthood. Data were analysed from 7,183 individuals from the English Longitudinal Study of Aging (ELSA). Interactions between the BMI-PGS and; lower educational attainment, self-perceived social status (SSS), and income, on BMI trajectories over 12 years across older adulthood were investigated through linear mixed effects models. Lower educational attainment, SSS and income were each associated with a higher baseline BMI for women, but not for men. There were interaction effects between BMI-PGS and social positioning such that men aged > 65 with a lower educational attainment (β = 0.62; 95%CI 0.00 – 1.24, p < 0.05), men aged ≤ 65 of a lower income (β = − 0.72, 95%CI − 1.21 - − 0.23, p < 0.01) and women aged ≤ 65 of lower SSS (β = − 1.41; 95%CI − 2.46 – 0.36, p < 0.01) showed stronger associations between the BMI-PGS and baseline BMI. There were few associations between markers of socioeconomic position and rate of change in BMI over the follow-up period. In sum, lower socioeconomic positioning showed adverse associations with women’s BMI in older adulthood. Moreover, the expression of the BMI-PGS, or extent to which it translates to a higher BMI, was subtly influenced by socioeconomic standing in both women and in men.

Social mobility by parent education and childhood overweight and obesity: a prospective cohort study

BACKGROUND

The association of social mobility, measured by parent education and childhood overweight and obesity (OWOB) has been scarcely reported on. This study evaluated the associations between social mobility measured by parent education and childhood OWOB at child age 6 and 10 years.

METHODS

We analyzed data of 4030 children and parents participating in the Generation R study. We used generalized linear models controlling for potential confounders to determine if social mobility (upward mobility, static-low and static-high based on the change of parent education) was associated with age- and sex-specific standard deviation scores of body mass index (BMI-SDS) or OWOB (the cut-offs of International Obesity Task Force).

RESULTS

Mean BMI-SDS of the children was 0.23 ± 0.89 and 0.26 ± 1.03 at child age 6 and 10 years, respectively; the prevalence of OWOB increased from 15.2 to 17.4%. Compared with children from mothers in the upward mobility group, children from mothers in the static-high group had lower BMI-SDS and lower odds of OWOB at both ages (all P < 0.001). Compared with children from fathers in the upward mobility group, children from fathers in static-low group had higher BMI-SDS and higher odds of OWOB at both ages (all P < 0.05).

CONCLUSIONS

Our study contributes to the literature by showing that the behaviors of parents' obtaining a higher level of education after the child was born may be beneficial to attenuate the odds of the child developing overweight in late childhood.

The consequences of a year of the COVID-19 pandemic for the mental health of young adult twins in England and Wales

The COVID-19 pandemic has impacted all our lives, not only through the infection itself, but also through the measures taken to control the virus’s spread (e.g., lockdown). Here we investigated how the COVID-19 pandemic and unprecedented lockdown affected the mental health of young adults in England and Wales. We compared the mental health symptoms of up to 4,000 twins in their mid-twenties in 2018 prior to the COVID-19 pandemic (T1) to those in a four-wave longitudinal data collection during the pandemic in April, July, and October 2020, and in March 2021 (T2-T5). The average changes in mental health were small-to-medium and mainly occurred from 2018 (T1) to March 2020 (T2, one month following the start of lockdown; average Cohen d=0.14). Despite the expectation of catastrophic effects on the pandemic on mental health of our young adults, we did not observe trends in worsening mental health during the pandemic (T3-T5). Young people with pre-existing mental health problems were adversely affected at the beginning of the pandemic, but their increased problems largely subsided as the pandemic persisted. Twin analyses indicated that the aetiology of individual differences did not change during the lockdown. The average heritability of mental health symptoms was 33% across 5 waves of assessment, and the average genetic correlation between T1 and T2-T5 was .95, indicating that genetic effects before the pandemic (T1) are substantially correlated with genetic effects up to a year later (T2-T5). We conclude that on average the mental health of young adults in England and Wales has been remarkably resilient to the effects of the pandemic and associated lockdown.

Reconstructing Sociogenomics Research: Dismantling Biological Race and Genetic Essentialism Narratives

We detail the implications of sociogenomics for social determinants research. We focus on education and race because of how early twentieth-century scientific eugenic thinking facilitated a range of racist and eugenic policies, most of which helped justify and pattern racial and educational morbidity and mortality disparities that remain today, and are central to sociological research. Consequently, we detail the implications of sociogenomics research by unpacking key controversies and opportunities in sociogenomics as they pertain to the understanding of racial and educational inequalities. We clarify why race is not a valid biological or genetic construct, the ways that environments powerfully shape genetic influence, and risks linked to this field of research. We argue that sociologists can usefully engage in genetics research, a domain dominated by psychologists and behaviorists who, given their focus on individuals, have mostly not examined the role of history and social structure in shaping genetic influence.

Mental health and music engagement: review, framework, and guidelines for future studies

Is engaging with music good for your mental health? This question has long been the topic of empirical clinical and nonclinical investigations, with studies indicating positive associations between music engagement and quality of life, reduced depression or anxiety symptoms, and less frequent substance use. However, many earlier investigations were limited by small populations and methodological limitations, and it has also been suggested that aspects of music engagement may even be associated with worse mental health outcomes. The purpose of this scoping review is first to summarize the existing state of music engagement and mental health studies, identifying their strengths and weaknesses. We focus on broad domains of mental health diagnoses including internalizing psychopathology (e.g., depression and anxiety symptoms and diagnoses), externalizing psychopathology (e.g., substance use), and thought disorders (e.g., schizophrenia). Second, we propose a theoretical model to inform future work that describes the importance of simultaneously considering music-mental health associations at the levels of (1) correlated genetic and/or environmental influences vs. (bi)directional associations, (2) interactions with genetic risk factors, (3) treatment efficacy, and (4) mediation through brain structure and function. Finally, we describe how recent advances in large-scale data collection, including genetic, neuroimaging, and electronic health record studies, allow for a more rigorous examination of these associations that can also elucidate their neurobiological substrates.

Associations of Genetic Factors, Educational Attainment, and Their Interaction With Kidney Function Outcomes

Both genetic predisposition and low educational attainment (EA) are associated with higher risk of chronic kidney disease. We examined the interaction of EA and genetic risk in kidney function outcomes. We included 3,597 participants from the Prevention of Renal and Vascular End-Stage Disease Cohort Study, a longitudinal study in a community-based sample from Groningen, the Netherlands (median follow-up, 11 years; 1997–2012). Kidney function was approximated by obtaining estimated glomerular filtration rate (eGFR) from serum creatinine and cystatin C. Individual longitudinal linear eGFR trajectories were derived from linear mixed models. Genotype data on 63 single-nucleotide polymorphisms, with known associations with eGFR, were used to calculate an allele-weighted genetic score (WGS). EA was categorized into high, medium, and low. In ordinary least squares analysis, higher WGS and lower EA showed additive effects on reduced baseline eGFR; the interaction term was nonsignificant. In analysis of eGFR decline, the significant interaction term suggested amplification of genetic risk by low EA. Adjustment for known renal risk factors did not affect our results. This study presents the first evidence of gene-environment interaction between EA and a WGS for eGFR decline and provides population-level insights into the mechanisms underlying socioeconomic disparities in chronic kidney disease.

The epidemiology of cognitive development

The epidemiology of cognitive development is an approach essentially based on large observational studies, which examines individual differences in cognitive abilities throughout childhood and their determinants. Although different in terms of methodology and main interests from developmental psychology, cognitive epidemiology offers complementary viewpoints on cognitive development and addresses fundamental research questions of interest to developmental psychologists. The present paper depicts the contributions of the epidemiological approach to the field of cognitive development and highlights the methodological advances that have made such contributions possible. We discuss the stability and developmental trajectories of cognitive functions, their main predictors, the complex interplay between environmental and genetic predictors, and the relationships between the different domains of cognition from birth to adulthood.

Achieved educational attainment, inherited genetic endowment for education, and obesity

This study investigates two sources of education effects on obesity - achieved educational attainment and inherited genetic endowment for education. In doing so, we accomplish two goals. First, we assess the role of genetic confounding in the association between education and health. Second, we consider the heterogeneity in the extent to which genetic potential for education is realized, and we examine its impact on obesity. Data come from the National Longitudinal Study of Adolescent to Adult Health. Using a polygenic score approach, we find that, net of genetic confounding, holding a college degree is associated with a lower likelihood of obesity. Moreover, among individuals who hold a college degree, those with a high education polygenic score (a greater genetic propensity to succeed in education) are less likely to be obese than those with a relatively low education polygenic score. However, when individuals with a high education polygenic score do not have a college degree, their risk of obesity is similar to that of non-college-educated individuals with a low education polygenic score, suggesting that the effect of genetic endowment for education on obesity is conditional on college education.

Selection into shift work is influenced by educational attainment and body mass index: a Mendelian randomization study in the UK Biobank

BACKGROUND

Shift work is associated with increased cardiometabolic disease risk. This observation may be partly explained by cardiometabolic risk factors having a role in the selection of individuals into or out of shift work. We performed Mendelian randomization (MR) analyses in the UK Biobank (UKB) to test this hypothesis.

METHODS

We used genetic risk scores (GRS) to proxy nine cardiometabolic risk factors and diseases (including educational attainment, body mass index (BMI), smoking, and alcohol consumption), and tested associations of each GRS with self-reported frequency of current shift work among employed UKB participants of European ancestry (n = 190 573). We used summary-level MR sensitivity analyses to assess robustness of the identified effects, and we tested whether effects were mediated through sleep timing preference.

RESULTS

Genetically instrumented liability to lower educational attainment (odds ratio (OR) per 3.6 fewer years in educational attainment = 2.40, 95% confidence interval (CI) = 2.22-2.59, P = 4.84 × 10-20) and higher body mass index (OR per 4.7 kg/m2 higher BMI = 1.30, 95% CI = 1.14-1.47, P = 5.85 × 10-5) increased odds of reporting participation in frequent shift work. Results were unchanged in sensitivity analyses allowing for different assumptions regarding horizontal pleiotropy. No selection effects were evident for the remaining exposures, nor for any exposures on selection out of shift work. Sleep timing preference did not mediate the effects of BMI and educational attainment on selection into shift work.

CONCLUSIONS

Liability to lower educational attainment and higher BMI may influence selection into shift work. This phenomenon may bias epidemiological studies of shift work that are performed in the UKB.