The Sociogenomics of Polygenic Scores of Reproductive Behavior and Their Relationship to Other Fertility Traits melinda c. mills, nicola barban, and f elix c. tropf Human reproductive behavior until relatively recently has been explained exclusively via individual and social characteristics. This article applies results from a recent Genome- Wide Association Study that com- bined sixty- two data sources to isolate twelve genetic loci associated with reproductive behavior. We create polygenic scores that allow us to include a summary variable of genetic factors into our statistical models. We use four datasets: the U.S. Health and Retirement Study, Dutch LifeLines, TwinsUK and the Swedish Twin register. First, we provide a brief overview of the dominant explanations of reproductive behavior. Second, we test the predictive power of polygenic scores. Third, we interrogate the robustness of our models using a series of sensitivity analyses to take into account possible confounders due to population stratifica- tion and selection. Keywords: human reproduction, polygenic scores, genetics, educational attainment, age at first birth, number of children ever born, fertility Human reproductive behavior—measured by only related to biological fecundity, but also age at first birth (AFB) and number of children have a strong behavioral element in that they ever born (NEB)—is a central topic of study are driven by the reproductive choice of indi- within the social, medical, and biological sci- viduals and their partners. They are likewise ences. AFB and NEB are complex behaviors not influenced by the environment and social in- Melinda C. Mills is Nuffield Professor of Sociology at the University of Oxford and Nuffield College and leads the Sociogenome project. Nicola Barban is senior research associate in the Department of Sociology at the University of Oxford and Nuffield College.Felix C. Tropf is a postdoctoral researcher in the Department of So- ciology at the University of Oxford and Nuffield College. © 2018 Russell Sage Foundation. Mills, Melinda C., Nicola Barban, and Felix C. Tropf. 2018. “The Sociogenom- ics of Polygenic Scores of Reproductive Behavior and Their Relationship to Other Fertility Traits.” RSF: The Russell Sage Foundation Journal of the Social Sciences 4(4): 122–36. DOI: 10.7758/RSF.2018.4.4.07. The research leading to these results has received funding from the following awards to PI M.C. Mills, European Research Council (ERC) Consolidator Grant SOCIOGENOME (615603, www.sociogenome.com), and Economic and So- cial Research Council (ESRC) UK, National Centre for Research Methods (NCRM) grant SOCGEN, European Union’s FP7 FamiliesAndSocieties project (no.320116) and the Wellcome Trust ISSF and John Fell Fund. Direct correspondence to: Melinda C. Mills at [email protected], Department of Sociology, Nuffield Col- lege, University of Oxford, OX1 3UQ United Kingdom; Nicola Barban at [email protected]; and Felix C. Tropf at [email protected]. Open Access Policy: RSF: The Russell Sage Foundation Journal of the Social Sciences is an open access journal. This article is published under a Creative Commons Attribution- NonCommercial- NoDerivs 3.0 Unported Li- cense. the sociogenomics of polygenic scores 123 stitutions, including multiple factors such as to educational systems and the educational contraceptive legislation and availability, edu- level of individuals (particularly women) (Bhrol- cational expansion, and social norms (Balbo, cháin and Beaujouan 2012; Rindfuss, Morgan, Billari, and Mills 2013). The past four decades and Offutt 1996; Tropf and Mandemakers 2017), have brought a rapid postponement of AFB by gender equity (McDonald 2002; Mills et al. around four to five years in many advanced so- 2011), normative changes in preferences for cieties and a growth in childlessness (Mills et children (de Kaa 1987), effective contraception al. 2011). The biological ability to conceive (Murphy 1993), availability of childcare (Brew- starts to steeply decline for some women as ster and Rindfuss 2000), women’s employment early as age twenty- five, and almost 50 percent and occupation (Begall and Mills 2013; Brewster of women are sterile by the age of forty (Leri- and Rindfuss 2000), social interactions (Balbo don 2008). This delay has been linked to an and Barban 2014) and economic uncertainty unprecedented growth in infertility (involun- (Mills, Blossfeld, and Klijzing 2005). tary childlessness), which now affects around The genetic basis of human reproduction 10 to 15 percent of couples in Western societies, has often been ignored or even actively resisted and forty- eight million couples worldwide are by social scientists. As a recent review of the estimated as infertile (Boivin et al. 2007). biodemographic approach to fertility high- Relatively little is known about the specific lighted, the avoidance is largely attributed to genetic architecture of human reproductive be- the dark history related to eugenic policies, lack havior of AFB and NEB and the genetic relation- of proper interdisciplinary training, and appro- ship to other fertility traits that mark the re- priate genetic data that also contains social sci- productive window such as menarche and ence behavioral measures (Mills and Tropf menopause or behaviorally relevant traits such 2016). As noted by pioneers in this field (Kohler, as educational attainment (Okbay, Beauchamp, Rodgers, and Christensen 1999; Rodgers et al. et al. 2016). The current study uses polygenic 2001), another reason this connection has been scores constructed from a recent large meta- avoided is often attributed to an erroneously GWAS (Genome- Wide Association Study) of interpreted version of Ronald Fisher’s (1930) AFB and NEB, which used data from sixty- two Fundamental Theorem of Natural Selection. sources to isolate twelve loci linked to these Some interpreted Fisher’s theory to mean that traits (Barban et al. 2016). Some of the results since fertility is a fitness trait, this should the- reported here are briefly reported in the supple- oretically entail that a genetic basis (referred mentary material of this study, but without de- to as heritability1), should be zero. Fisher actu- tailed discussion, clarification or reflection. ally argued that fitness is moderately heritable in human populations. A naïve interpretation cenTral explanaTionS of has been that genes that reduce fitness should reproducTive Behavior have been less frequently passed on, leading to Reproductive behavior has been largely ex- the elimination of genetic variability in traits plained by social scientists by focusing on in- such as fertility (Courtiol, Tropf, and Mills dividual and couple characteristics and social 2016). Nevertheless, we find that fitness traits structural or institutional factors (Balbo, Bil- such as NEB and AFB have what is known as lari, and Mills 2013). Core explanations, bol- significant narrow- sense heritabilities.2 It may stered by a large body of empirical evidence, be that new mutations restore any genetic vari- has related the timing and number of children ance lost to selection, that there are sexual an- 1. Heritability (H2) is a statistical term used to denote the proportion of phenotypic (trait) variance due to variance in genotypes. It is important to note that it is specific to the population and environment of analysis and that it is a population and not an individual estimate. It is not a simple measure of the degree to which a trait or phe- notype is genetic but rather the proportion of phenotypic variance that is the result of genetic factors. 2. Both broad- and narrow- sense heritability can be estimated. Broad- sense heritability is the ratio of the total 2 genetic variance to total phenotypic (trait) variance or: H = VG/VP. Narrow- sense heritability refers to ratio of 2 the additive genetic component in contrast to the total (nonadditive) phenotypic variance or: h = VA/VP. rsf: the russell sage foundation journal of the social sciences 124 biosocial path Ways across the life course tagonistic genetic effects (genes have opposite one limited dataset, we test our results using effects for the fertility of men and women), four datasets: the Health and Retirement Study nonadditive genetic effects, environment and (HRS), LifeLines, TwinsUK, and Swedish Twin gene- environment interaction (Tropf et al. 2017; Registry (STR). Verweij et al. 2017). At least some genetic underpinnings of HRS fertility behavior are plausible. In fact, a grow- The Health and Retirement Study is an ongo- ing number of twin and family studies have ing cohort study of Americans, with interview shown a genetic component underlying AFB data collected biennially on demographics, and NEB (Briley, Tropf, and Mills 2017; Tropf, health behavior, health status, employment, Barban, et al. 2015; Zietsch et al. 2014). A recent income and wealth, and insurance status. The meta-analysis of all twin studies conducted un- first cohort was interviewed in 1992 and subse- til 2012 shows average heritability of 0.45 (SE = quently every two years; five additional cohorts 0.027, N = 50,265) among sixty- four reproduc- were added between 1994 and 2010. Between tive disease traits of women and of 0.36 (SE= 2006 and 2008, the HRS genotyped 12,507 re- 0.054, N = 9,376) among twenty- five reproduc- spondents who provided DNA samples and tive disease traits of men (Polderman et al. signed consent. DNA samples were genotyped 2015). The advent of molecular genetic data and using the Illumina Human Omni- 2.5 Quad complementary analytical tools means that we BeadChip, with coverage of approximately 2.5 are now able to go beyond twin models to ex- million single nucleotide polymorphisms amine for the first time the genetic relatedness (SNPs). The full details of the study are de- of unrelated individuals (Mills and Tropf 2016; scribed in (Juster and Suzman 1995). Yang et al. 2010). A recent study using whole- genome data of unrelated individuals shows LifeLines Cohort Study that 10 percent of the variance in NEB and 15 The LifeLines Cohort Study is a multidisci- percent in AFB are associated with common plinary prospective population- based cohort additive genetic variance (Tropf, Stulp, et al.