Benjamin W. Domingue

Genetic and educational assortative mating among US adults

Significance It is well established that individuals are more similar to their spouses than other individuals on important traits, such as education level. The genetic similarity, or lack thereof, between spouses is less well understood. We estimate the genome-wide genetic similarity of spouses and compare the magnitude of this value to a comparable measure of educational similarity. We find that spouses are more genetically similar than two individuals chosen at random but this similarity is at most one-third the magnitude of educational similarity. Furthermore, social sorting processes in the marriage market are largely independent of genetic dynamics of sexual selection. Understanding the social and biological mechanisms that lead to homogamy (similar individuals marrying one another) has been a long-standing issue across many fields of scientific inquiry. Using a nationally representative sample of non-Hispanic white US adults from the Health and Retirement Study and information from 1.7 million single-nucleotide polymorphisms, we compare genetic similarity among married couples to noncoupled pairs in the population. We provide evidence for genetic assortative mating in this population but the strength of this association is substantially smaller than the strength of educational assortative mating in the same sample. Furthermore, genetic similarity explains at most 10% of the assortative mating by education levels. Results are replicated using comparable data from the Framingham Heart Study.

Polygenic Influence on Educational Attainment

Recent studies have begun to uncover the genetic architecture of educational attainment. We build on this work using genome-wide data from siblings in the National Longitudinal Study of Adolescent to Adult Health (Add Health). We measure the genetic predisposition of siblings to educational attainment using polygenic scores. We then test how polygenic scores are related to social environments and educational outcomes. In Add Health, genetic predisposition to educational attainment is patterned across the social environment. Participants with higher polygenic scores were more likely to grow up in socially advantaged families. Even so, the previously published genetic associations appear to be causal. Among pairs of siblings, the sibling with the higher polygenic score typically went on to complete more years of schooling as compared to their lower-scored co-sibling. We found subtle differences between sibling fixed-effect estimates of the genetic effect versus those based on unrelated individuals.

The Genetics of Success How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and environments were correlated: Children with higher polygenic scores were born into better-off homes. Third, children’s polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores. Fourth, polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development.

How social and genetic factors predict friendship networks

Recent research suggests that the genotype of one individual in a friendship pair is predictive of the genotype of his/her friend. These results provide tentative support for the genetic homophily perspective, which has important implications for social and genetic epidemiology because it substantiates a particular form of gene–environment correlation. This process may also have important implications for social scientists who study the social factors related to health and health-related behaviors. We extend this work by considering the ways in which school context shapes genetically similar friendships. Using the network, school, and genetic information from the National Longitudinal Study of Adolescent Health, we show that genetic homophily for the TaqI A polymorphism within the DRD2 gene is stronger in schools with greater levels of inequality. Our results suggest that individuals with similar genotypes may not actively select into friendships; rather, they may be placed into these contexts by institutional mechanisms outside of their control. Our work highlights the fundamental role played by broad social structures in the extent to which genetic factors explain complex behaviors, such as friendships.

Gene-environment interactions related to body mass: School policies and social context as environmental moderators

This paper highlights the role of institutional resources and policies, whose origins lie in political processes, in shaping the genetic etiology of body mass among a national sample of adolescents. Using data from Waves I and II of the National Longitudinal Study of Adolescent Health, we decompose the variance of body mass into environmental and genetic components. We then examine the extent to which the genetic influences on body mass are different across the 134 schools in the study. Taking advantage of school differences in both health-related policies and social norms regarding body size, we examine how institutional resources and policies alter the relative impact of genetic influences on body mass. For the entire sample, we estimate a heritability of .82, with the remaining .18 due to unique environmental factors. However, we also show variation about this estimate and provide evidence suggesting that social norms and institutional policies often mask genetic vulnerabilities to increased weight. Empirically, we demonstrate that more restrictive school policies and policies designed to curb weight gain are also associated with decreases in the proportion of variance in body mass that is due to additive genetic influences.

Is the Gene-Environment Interaction Paradigm Relevant to Genome-Wide Studies? The Case of Education and Body Mass Index

This study uses data from the Framingham Heart Study to examine the relevance of the gene-environment interaction paradigm for genome-wide association studies (GWAS). We use completed college education as our environmental measure and estimate the interactive effect of genotype and education on body mass index (BMI) using 260,402 single-nucleotide polymorphisms (SNPs). Our results highlight the sensitivity of parameter estimates obtained from GWAS models and the difficulty of framing genome-wide results using the existing gene-environment interaction typology. We argue that SNP-environment interactions across the human genome are not likely to provide consistent evidence regarding genetic influences on health that differ by environment. Nevertheless, genome-wide data contain rich information about individual respondents, and we demonstrate the utility of this type of data. We highlight the fact that GWAS is just one use of genome-wide data, and we encourage demographers to develop methods that incorporate this vast amount of information from respondents into their analyses.

Polygenic Risk Predicts Obesity in Both White and Black Young Adults

Objective To test transethnic replication of a genetic risk score for obesity in white and black young adults using a national sample with longitudinal data. Design and Methods A prospective longitudinal study using the National Longitudinal Study of Adolescent Health Sibling Pairs (n = 1,303). Obesity phenotypes were measured from anthropometric assessments when study members were aged 18–26 and again when they were 24–32. Genetic risk scores were computed based on published genome-wide association study discoveries for obesity. Analyses tested genetic associations with body-mass index (BMI), waist-height ratio, obesity, and change in BMI over time. Results White and black young adults with higher genetic risk scores had higher BMI and waist-height ratio and were more likely to be obese compared to lower genetic risk age-peers. Sibling analyses revealed that the genetic risk score was predictive of BMI net of risk factors shared by siblings. In white young adults only, higher genetic risk predicted increased risk of becoming obese during the study period. In black young adults, genetic risk scores constructed using loci identified in European and African American samples had similar predictive power. Conclusion Cumulative information across the human genome can be used to characterize individual level risk for obesity. Measured genetic risk accounts for only a small amount of total variation in BMI among white and black young adults. Future research is needed to identify modifiable environmental exposures that amplify or mitigate genetic risk for elevated BMI.

Assortative mating and differential fertility by phenotype and genotype across the 20th century

Significance We describe dynamics in assortative mating and fertility patterns by polygenic scores associated with anthropometric traits, depression, and educational attainment across birth cohorts from 1920 to 1955. We find that, for example, increases in assortative mating at the phenotypic level for education are not matched at the genotypic level. We also show that genes related to height are positively associated with fertility and that, despite a widening gap between the more and less educated with respect to fertility, there is no evidence that this trend is associated with genes. These findings are important to our understanding of the roots of shifting distributions of health and behavior across generations in US society. This study asks two related questions about the shifting landscape of marriage and reproduction in US society over the course of the last century with respect to a range of health and behavioral phenotypes and their associated genetic architecture: (i) Has assortment on measured genetic factors influencing reproductive and social fitness traits changed over the course of the 20th century? (ii) Has the genetic covariance between fitness (as measured by total fertility) and other traits changed over time? The answers to these questions inform our understanding of how the genetic landscape of American society has changed over the past century and have implications for population trends. We show that husbands and wives carry similar loadings for genetic factors related to education and height. However, the magnitude of this similarity is modest and has been fairly consistent over the course of the 20th century. This consistency is particularly notable in the case of education, for which phenotypic similarity among spouses has increased in recent years. Likewise, changing patterns of the number of children ever born by phenotype are not matched by shifts in genotype–fertility relationships over time. Taken together, these trends provide no evidence that social sorting is becoming increasingly genetic in nature or that dysgenic dynamics have accelerated.

Is the effect of parental education on offspring biased or moderated by genotype

Parental education is the strongest measured predictor of offspring education, and thus many scholars see the parent–child correlation in educational attainment as an important measure of social mobility. But if social changes or policy interventions are going to have dynastic effects, we need to know what accounts for this intergenerational association, that is, whether it is primarily environmental or genetic in origin. Thus, to understand whether the estimated social influence of parental education on offspring education is biased owing to genetic inheritance (or moderated by it), we exploit the findings from a recent large genome-wide association study of educational attainment to construct a genetic score designed to predict educational attainment. Using data from two independent samples, we find that our genetic score significantly predicts years of schooling in both between-family and within-family analyses. We report three findings that should be of interest to scholars in the stratification and education fields. First, raw parent–child correlations in education may reflect one-sixth genetic transmission and five-sixths social inheritance. Second, conditional on a child’s genetic score, a parental genetic score has no statistically significant relationship to the child’s educational attainment. Third, the effects of offspring genotype do not seem to be moderated by measured sociodemographic variables at the parental level (but parent–child genetic interaction effects are significant). These results are consistent with the existence of two separate systems of ascription: genetic inheritance (a random lottery within families) and social inheritance (across-family ascription). We caution, however, that at the presently attainable levels of explanatory power, these results are preliminary and may change when better-powered genetic risk scores are developed.

Testing the key assumption of heritability estimates based on genome-wide genetic relatedness

Comparing genetic and phenotypic similarity among unrelated individuals seems a promising way to quantify the genetic component of traits while avoiding the problematic assumptions plaguing twin- and other kin-based estimates of heritability. One approach uses a Genetic Relatedness Estimation through Maximum Likelihood (GREML) model for individuals who are related at less than 0.025 to predict their phenotypic similarity by their genetic similarity. Here we test the key underlying assumption of this approach: that genetic relatedness is orthogonal to environmental similarity. Using data from the Health and Retirement Study (and two other surveys), we show two unrelated individuals may be more likely to have been reared in a similar environment (urban versus nonurban setting) if they are genetically similar. This effect is not eliminated by controls for population structure. However, when we include this environmental confound in GREML models, heritabilities do not change substantially and thus potential bias in estimates of most biological phenotypes is probably minimal.