Assortative Mating and Differential Fertility by Phenotype and Genotype Across the 20Th Century

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Assortative Mating and Differential Fertility by Phenotype and Genotype Across the 20Th Century Assortative mating and differential fertility by phenotype and genotype across the 20th century Dalton Conleya,b,1, Thomas Laidleya, Daniel W. Belskyc,d, Jason M. Fletchere, Jason D. Boardmanf, and Benjamin W. Domingueg,1 aDepartment of Sociology, New York University, New York, NY 10003; bSchool of Medicine, New York University, New York, NY 10003; cDuke University School of Medicine, Durham, NC 27708; dSocial Science Research Institute, Durham, NC 27708; eLaFollette School of Public Affairs, University of Wisconsin, Madison, WI 53706; fInstitute of Behavioral Science, University of Colorado, Boulder, CO 80309; and gGraduate School of Education, Stanford University, Stanford, CA 94305 Edited by Sara S. McLanahan, Princeton University, Princeton, NJ, and approved April 28, 2016 (received for review November 30, 2015) This study asks two related questions about the shifting landscape marriage (13, 14). The presence of such “assortative mating” on of marriage and reproduction in US society over the course of the genotypes has implications for the statistical models used in genetic last century with respect to a range of health and behavioral research because genotype distributions will change across genera- phenotypes and their associated genetic architecture: (i) Has as- tions (15), causing, by extension, changes in phenotypic trait sortment on measured genetic factors influencing reproductive distributions. Here, we evaluate the implications of genotypic and social fitness traits changed over the course of the 20th cen- assortative mating for traits of interest in population and health tury? (ii) Has the genetic covariance between fitness (as measured sciences. by total fertility) and other traits changed over time? The answers To investigate trait-related genotypic assortative mating, we to these questions inform our understanding of how the genetic studied polygenic scores (PGSs) derived from genome-wide as- landscape of American society has changed over the past century sociation studies (GWAS) of educational attainment, height, and have implications for population trends. We show that hus- body mass index (BMI), and major depressive disorder (16–19). bands and wives carry similar loadings for genetic factors related PGSs are genome-wide summaries of genetic variation associ- to education and height. However, the magnitude of this similarity ated with a phenotype (20). They are continuous and typically is modest and has been fairly consistent over the course of the normally distributed, consistent with biometrical estimates of the 20th century. This consistency is particularly notable in the case of genetic architecture of complex traits (21). They are also robust education, for which phenotypic similarity among spouses has in- predictors of small amounts of phenotypic variance (22). creased in recent years. Likewise, changing patterns of the number Assortative genetic mating tells only part of the story with of children ever born by phenotype are not matched by shifts in respect to changes in the genetic variance of a population. Dif- genotype–fertility relationships over time. Taken together, these ferential fertility by genotype also influences the mean levels of a trends provide no evidence that social sorting is becoming increas- genotype and, consequently, the phenotype. Just as observations ingly genetic in nature or that dysgenic dynamics have accelerated. have been made regarding the changing patterns of spousal as- sortment, demographers have documented declines in fertility SOCIAL SCIENCES assortative mating | fertility | polygenic scores | cohort trends rates during the 20th century (23). Economic models suggest that the most powerful social (distal) correlates of fertility are child he traditional view of evolutionary dynamics in humans was survival and female education, both of which are negatively re- Tthat the history of modern humans was too short for the lated to fertility in developed countries (24–28). Meanwhile, twin species to have experienced substantive change in its genetic and molecular genetics studies find that fertility is also influ- makeup (1, 2). However, findings from recent population genetics enced by genetic factors (29), although somewhat less so than studies suggest the possibility that selective fertility, nonrandom mating, drift, and other violations of the Hardy–Weinberg equilib- Significance rium accelerated genetic divergence between modern human pop- ulations, particularly since humans began farming and civilization We describe dynamics in assortative mating and fertility pat- developed (3–6). Extending this logic, rapid economic development terns by polygenic scores associated with anthropometric traits, and the corresponding demographic transition over the past two depression, and educational attainment across birth cohorts from centuries may have led to a further shift in the dynamics of re- 1920 to 1955. We find that, for example, increases in assortative production and selection. The present paper uses genetic and mating at the phenotypic level for education are not matched at phenotypic data from a nationally representative sample of US the genotypic level. We also show that genes related to height older adults to test whether the societal changes in the United are positively associated with fertility and that, despite a wid- States during the 20th century were reflected in (i) changes in ening gap between the more and less educated with respect to patterns of genetic assortment in marriage, and (ii) changes in fertility, there is no evidence that this trend is associated with genetic influences on fertility. genes. These findings are important to our understanding of Understanding trends with respect to specific deviations from the roots of shifting distributions of health and behavior across random mating and differential fertility is critical to both social generations in US society. and evolutionary scientists. For example, recent research in so- Author contributions: D.C. and B.W.D. designed research; D.C. and B.W.D. performed ciology has suggested that taking a prospective view on social research; D.C. and B.W.D. analyzed data; and T.L., D.W.B., J.M.F., J.D.B., and B.W.D. wrote stratification that incorporates differential fertility yields dispa- the paper. rate results for estimands such as levels of intergenerational edu- The authors declare no conflict of interest. cational mobility (7). Likewise, genetic research on human This article is a PNAS Direct Submission. populations often assumes that mating in a population is random Freely available online through the PNAS open access option. with respect to genotypes (8, 9). Recent empirical evidence suggests 1To whom correspondence may be addressed. Email: [email protected] or bdomingue@ otherwise; married couples tend to be more genotypically similar stanford.edu. – than would be expected by chance (10 12), although questions re- This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. main as to how much of this similarity arises from intraethnic 1073/pnas.1523592113/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1523592113 PNAS | June 14, 2016 | vol. 113 | no. 24 | 6647–6652 Downloaded by guest on September 28, 2021 A B C Fig. 1. Spousal associations for both standardized phenotypes and standardized polygenic risk scores among spousal pairs in the HRS, 2012 (n = 4,686; restricted to respondents in their first marriage who have genotypic data and valid phenotypic responses). (A) All birth cohorts pooled. (B and C) Trends in spousal correspondence across birth cohorts. The horizontal axis depicts birth cohort, whereas the vertical axis is the predicted value for the spouse of a focal individual conditional on the focal individual’s birth year and either phenotype or PGS (Eq. 1). The lines show fitted values for those at 1 SD above (gray) and below (black) the mean. Points are based on binned means for two groups of respondents (standardized value below −1, black; standardized value above 1, dark gray). For each group, the distribution of birth years is divided into 20 subgroups with approximately equal numbers. Plotted points are the mean birth year and response for these subgroups. B considers standardized phenotypes. Education demonstrates a change in spousal correlation across birth cohorts. Consider education in B: an individual with relatively low education is predicted to have a spouse of consistently low education across all birth cohorts. In contrast, a high-education individual will have, on average, a spouse with higher education in later birth cohorts compared with earlier birth cohorts. For height, the fact that relatively short individuals are predicted to marry relatively tall individuals is a consequence of the fact that we are looking at opposite sex pairs. C considers standardized PGSs. In contrast to results for phenotypes, spousal correlations in education PGS display reductions across 20th century birth cohorts as do those for height, although these results do not appear significant at conventional α levels. 6648 | www.pnas.org/cgi/doi/10.1073/pnas.1523592113 Conley et al. Downloaded by guest on September 28, 2021 most complex traits (30, 31). The combination of changes in parallel to previous genotypic assortative mating analyses (12). phenotypic associations with number of children (specifically We found no evidence for such a change. Thus, our results from with respect to years of schooling) along with the documented the PGS analysis are not likely to be
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