Genetic analysis of selection bias in a natural experiment: Investigating in-utero famine effects on elevated body mass index in the Dutch Hunger Winter Families Study.

Natural-experiment designs that compare survivors of in-utero famine exposure to unaffected controls suggest that in-utero undernutrition predisposes to development of obesity. However, birth rates drop dramatically during famines. Selection bias could arise if factors that contribute to obesity also protect fertility and/or fetal survival under famine conditions. We investigated this hypothesis using genetic analysis of a famine-exposed birth cohort. We genotyped participants in the Dutch Hunger Winter Families Study (DHWFS, N=950; 45% male), of whom 51% were exposed to the 1944-1945 Dutch Famine during gestation and 49% were their unexposed same-sex siblings or "time controls" born before or after the famine in the same hospitals. We computed body-mass index (BMI) polygenic indices (PGIs) in DHWFS participants and compared BMI PGIs between famine-exposed and control groups. Participants with higher polygenic risk had higher BMIs (Pearson r=0.42, p<0.001). However, differences between BMI PGIs of famine-exposed participants and controls were small and not statistically different from zero across specifications (Cohen's d=0.10, p>0.092). Our findings did not indicate selection bias, supporting the validity of the natural-experiment design within DHWFS. In summary, our study outlines a novel approach to explore the presence of selection bias in famine and other natural experiment studies.

Accelerated biological aging six decades after prenatal famine exposure.

To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N=951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944-5, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.

Incentivizing free riders improves collective intelligence in social dilemmas.

Collective intelligence challenges are often entangled with collective action problems. For example, voting, rating, and social innovation are collective intelligence tasks that require costly individual contributions. As a result, members of a group often free ride on the information contributed by intrinsically motivated people. Are intrinsically motivated agents the best participants in collective decisions? We embedded a collective intelligence task in a large-scale, virtual world public good game and found that participants who joined the information system but were reluctant to contribute to the public good (free riders) provided more accurate evaluations, whereas participants who rated frequently underperformed. Testing the underlying mechanism revealed that a negative rating bias in free riders is associated with higher accuracy. Importantly, incentivizing evaluations amplifies the relative influence of participants who tend to free ride without altering the (higher) quality of their evaluations, thereby improving collective intelligence. These results suggest that many of the currently available information systems, which strongly select for intrinsically motivated participants, underperform and that collective intelligence can benefit from incentivizing free riding members to engage. More generally, enhancing the diversity of contributor motivations can improve collective intelligence in settings that are entangled with collective action problems.

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.

Social and genetic associations with educational performance in a Scandinavian welfare state.

Recent research has suggested that across Western developed societies, the influence of genetics on educational outcomes is relatively constant. However, the degree to which family environment matters varies, such that countries with high levels of intergenerational mobility have weaker associations of family background. Research in this vein has relied on twin-based estimates, which involve variance decomposition, so direct assessment of the association of genes and environments is not possible. In the present study, we approach the question by directly measuring the impact of child genotype, parental genetic nurture, and parental realized education on educational achievement in primary and secondary school. We deploy data from a social democratic context (Norway) and contrast our findings with those derived from more liberal welfare state contexts. Results point to genetics only confounding the relationship between parent status and offspring achievement to a small degree. Genetic nurture associations are similar to those in other societies. We find no, or very small, gene-environment interactions and parent-child genotype interactions with respect to test scores. In sum, in a Scandinavian welfare state context, both genetic and environmental associations are of similar magnitude as in societies with less-robust efforts to mitigate the influence of family background.

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.

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals.

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.

Genome-Wide Heritability Estimates for Family Life Course Complexity.

Sequence analysis is an established method used to study the complexity of family life courses. Although individual and societal characteristics have been linked with the complexity of family trajectories, social scientists have neglected the potential role of genetic factors in explaining variation in family transitions and events across the life course. We estimate the genetic contribution to sequence complexity and a wide range of family demographic behaviors using genomic relatedness-based, restricted maximum likelihood models with data from the U.S. Health and Retirement Study. This innovative methodological approach allows us to provide the first estimates of the heritability of composite life course outcomes-that is, sequence complexity. We demonstrate that a number of family demographic indicators (e.g., the age at first birth and first marriage) are heritable and provide evidence that composite metrics can be influenced by genetic factors. For example, our results show that 11% of the total variation in the complexity of differentiated family sequences is attributable to genetic influences. Moreover, we test whether this genetic contribution varies by social environment as indexed by birth cohort over a period of rapid changes in family norms during the twentieth century. Interestingly, we find evidence that the complexity of fertility and differentiated family trajectories decreased across cohorts, but we find no evidence that the heritability of the complexity of partnership trajectories changed across cohorts. Therefore, our results do not substantiate claims that lower normative constraints on family demographic behavior increase the role of genes.

Sibling Similarity in Education Across and Within Societies.

The extent to which siblings resemble each other measures the omnibus impact of family background on life chances. We study sibling similarity in cognitive skills, school grades, and educational attainment in Finland, Germany, Norway, Sweden, the United Kingdom, and the United States. We also compare sibling similarity by parental education and occupation within these societies. The comparison of sibling correlations across and within societies allows us to characterize the omnibus impact of family background on education across social landscapes. Across countries, we find larger population-level differences in sibling similarity in educational attainment than in cognitive skills and school grades. In general, sibling similarity in education varies less across countries than sibling similarity in earnings. Compared with Scandinavian countries, the United States shows more sibling similarity in cognitive skills and educational attainment but less sibling similarity in school grades. We find that socioeconomic differences in sibling similarity vary across parental resources, countries, and measures of educational success. Sweden and the United States show greater sibling similarity in educational attainment in families with a highly educated father, and Finland and Norway show greater sibling similarity in educational attainment in families with a low-educated father. We discuss the implications of our results for theories about the impact of institutions and income inequality on educational inequality and the mechanisms that underlie such inequality.

The impact of late-career job loss and genetic risk on body mass index: Evidence from variance polygenic scores.

Unemployment shocks from the COVID-19 pandemic have reignited concerns over the long-term effects of job loss on population health. Past research has highlighted the corrosive effects of unemployment on health and health behaviors. This study examines whether the effects of job loss on changes in body mass index (BMI) are moderated by genetic predisposition using data from the U.S. Health and Retirement Study (HRS). To improve detection of gene-by-environment (G × E) interplay, we interacted layoffs from business closures-a plausibly exogenous environmental exposure-with whole-genome polygenic scores (PGSs) that capture genetic contributions to both the population mean (mPGS) and variance (vPGS) of BMI. Results show evidence of genetic moderation using a vPGS (as opposed to an mPGS) and indicate genome-wide summary measures of phenotypic plasticity may further our understanding of how environmental stimuli modify the distribution of complex traits in a population.

Public attitudes toward genetic risk scoring in medicine and beyond.

Advances in genomics research have led to the development of polygenic risk scores, which numerically summarize genetic predispositions for a wide array of human outcomes. Initially developed to characterize disease risk, polygenic risk scores can now be calculated for many non-disease traits and social outcomes, with the potential to be used not only in health care but also other institutional domains. In this study, we draw on a nationally-representative survey of U.S. adults to examine three sets of lay attitudes toward the deployment of genetic risk scores in a variety of medical and non-medical domains: 1. abstract belief about whether people should be judged on the basis of genetic predispositions; 2. concrete attitudes about whether various institutions should be permitted to use genetic information; and 3. personal willingness to provide genetic information to various institutions. Results demonstrate two striking differences across these three sets of attitudes. First, despite almost universal agreement that people should not be judged based on genetics, there is support, albeit varied, for institutions being permitted to use genetic information, with support highest for disease outcomes and in reproductive decision-making. We further find significant variation in personal willingness to provide such information, with a majority of respondents expressing willingness to provide information to health care providers and relative finder services, but less than a quarter expressing willingness to do so for an array of other institutions and services. Second, while there are no demographic differences in respondents' abstract beliefs about judging based on genetics, demographic differences emerge in permissibility ratings and personal willingness. Our results should inform debates about the deployment of polygenic scores in domains within and beyond medicine.

Gene-environment Interactions and School Tracking during Secondary Education: Evidence from the U.S.

There is much evidence to suggest that family background and the context of secondary education both contribute to the formation of educational inequalities. Meanwhile, our knowledge about the role of ability in generating class differences in educational outcomes is still limited. By deploying genetic data that allow us to measure at least part of "innate" ability inherited through biological mechanisms from parents, this study examines how such abilities are associated with educational tracking outcomes among U.S. high schoolers. This study also details our understanding of the role of nature and nurture in the educational attainment processes by testing for gene-environment interactions-that is, a joint, mutually moderating effect of one's genetic potential and one's environment (e.g., family background or school context) on phenotypic outcomes (educational tracking). Using the National Longitudinal Study of Adolescent to Adult Health that collects a unique set of demographic, educational, and genetic characteristics of students, we report the following results: First, a positive association between the genetic potential for educational attainment and taking advanced courses holds even after controlling for previous course tracking measures. Second, results provide suggestive evidence that parental SES amplifies the association between one's genetic potential for educational attainment and mathematics tracking. In contrast to the argument by some stratification scholars that places primary emphasis on the role of social background for the reproduction of educational stratification, the present findings imply that we need to fully consider the role of genetic inheritance for educational stratification in addition to social origin.

Variable prediction accuracy of polygenic scores within an ancestry group.

Fields as diverse as human genetics and sociology are increasingly using polygenic scores based on genome-wide association studies (GWAS) for phenotypic prediction. However, recent work has shown that polygenic scores have limited portability across groups of different genetic ancestries, restricting the contexts in which they can be used reliably and potentially creating serious inequities in future clinical applications. Using the UK Biobank data, we demonstrate that even within a single ancestry group (i.e., when there are negligible differences in linkage disequilibrium or in causal alleles frequencies), the prediction accuracy of polygenic scores can depend on characteristics such as the socio-economic status, age or sex of the individuals in which the GWAS and the prediction were conducted, as well as on the GWAS design. Our findings highlight both the complexities of interpreting polygenic scores and underappreciated obstacles to their broad use.

Complex diseases like cancer and heart disease are caused by the interplay of many factors: the variants of genes we inherit, the lifestyles we lead and the environments we inhabit, plus the interaction of all these factors. In fact, almost every trait, even how many years we will spend studying, is influenced both by our environment and our genes. To identify some of the genetic factors at play, scientists perform analyses known as genome-wide association studies, or GWAS for short. In these studies, the genomes from many different people are scanned to look for genetic differences associated with differences in traits. By summing up all the small genetic differences, so-called "polygenic scores" can be calculated. When there is a large genetic component to a trait, polygenic scores can be useful predictive tools. But there is a catch: polygenic scores make less accurate predictions for individuals of a different ancestry than those involved in the GWAS, which limits the use of these tools around the world. Mostafavi, Harpak et al. set out to understand if there are other factors in addition to ancestry that could influence the performance of polygenic scores. Using data from the UK Biobank, an international health resource that pairs genomic data and clinical information, Mostafavi, Harpak et al. examined polygenic scores among individuals that share a single, common ancestry. These polygenic scores were used to predict three traits (blood pressure, body mass index and educational attainment) in individuals and the predictions were then compared to the actual trait values to see how accurate they were. The analysis revealed that even within a group of people with similar ancestry, the accuracy of polygenic scores can vary, depending on characteristics such as the sex, age or socioeconomic status of the individuals. This analysis emphasises how variable GWAS and their predictive value can be even within seemingly similar population groups. It further highlights both the complexities of interpreting polygenic scores and underappreciated obstacles to their broad use in medical and social sciences.

Civilian public sector employment as a long-run outcome of military conscription.

Since at least T. H. Marshall, scholars have recognized military service as a form of sacrifice that warrants compensation from the state. War-widow pensions, expansion of the franchise, and subsidized higher education are all examples of rights and benefits "bestowed" in return for wartime mobilization. Similarly, in the United States, governments have hired veterans preferentially for civilian public jobs as recompense for active military service. Although oft overlooked, those policies seem influential: the percentage of job holders identifying as veterans in the civilian US executive branch exceeds the proportion in the wider population by several multiples. This century-old pattern suggests another way that wartime mobilization has influenced the state. Yet, efforts to understand it have struggled to rule out the possibility that those who serve in the armed forces are predisposed to work for the state in both military and civilian capacities. Here, we rule out this possibility by examining whether birthdates randomly called for induction in the Vietnam-Era Selective Service Lotteries (VSSL) appear disproportionately in the population of nonsensitive personnel records of the civilian US executive branch. We find that birthdates called for induction appear with unusually high frequency among employees who were draft eligible and at risk for induction but not among other employees. This finding suggests a treatment effect from military service, thus dovetailing with the hypothesis that wartime mobilization has substantially and continually influenced who works in the contemporary administrative state.