Verweij Renske M, Mills Melinda C, Stulp Gert, Nolte Ilja M, Barban Nicola, Tropf Felix C, Carrell Douglas T, Aston Kenneth I, Zondervan Krina T, Rahmioglu Nilufer, Dalgaard Marlene, Skaarup Carina, Hayes M Geoffrey, Dunaif Andrea, Guo Guang, Snieder Harold
Department of Sociology and ICS, University of Groningen, Groningen, Netherlands.
Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, Netherlands.
Front Sociol. 2019 Nov 22;4:74. doi: 10.3389/fsoc.2019.00074. eCollection 2019.
Biological, genetic, and socio-demographic factors are all important in explaining reproductive behavior, yet these factors are typically studied in isolation. In this study, we explore an innovative sociogenomic approach, which entails including key socio-demographic (marriage, education, occupation, religion, cohort) and genetic factors related to both behavioral [age at first birth (AFB), number of children ever born (NEB)] and biological fecundity-related outcomes (endometriosis, age at menopause and menarche, polycystic ovary syndrome, azoospermia, testicular dysgenesis syndrome) to explain childlessness. We examine the association of all sets of factors with childlessness as well as the interplay between them. We derive polygenic scores (PGS) from recent genome-wide association studies (GWAS) and apply these in the Health and Retirement Study ( = 10,686) and Wisconsin Longitudinal Study ( = 8,284). Both socio-demographic and genetic factors were associated with childlessness. Whilst socio-demographic factors explain 19-46% in childlessness, the current PGS explains <1% of the variance, and only PGSs from large GWASs are related to childlessness. Our findings also indicate that genetic and socio-demographic factors are not independent, with PGSs for AFB and NEB related to education and age at marriage. The explained variance by polygenic scores on childlessness is limited since it is largely a behavioral trait, with genetic explanations expected to increase somewhat in the future with better-powered GWASs. As genotyping of individuals in social science surveys becomes more prevalent, the method described in this study can be applied to other outcomes.
生物学、遗传学和社会人口学因素在解释生育行为方面都很重要，但这些因素通常是单独进行研究的。在本研究中，我们探索了一种创新的社会基因组学方法，该方法需要纳入与行为（初育年龄、曾生育子女数）和生物学生育相关结果（子宫内膜异位症、绝经和初潮年龄、多囊卵巢综合征、无精子症、睾丸发育不全综合征）相关的关键社会人口学（婚姻、教育、职业、宗教、队列）和遗传因素来解释无子女现象。我们研究了所有因素集与无子女现象的关联以及它们之间的相互作用。我们从最近的全基因组关联研究（GWAS）中得出多基因评分（PGS），并将其应用于健康与退休研究（n = 10686）和威斯康星纵向研究（n = 8284）。社会人口学和遗传因素均与无子女现象有关。虽然社会人口学因素在无子女现象中可解释19 - 46%的情况，但当前的多基因评分仅解释了不到1%的变异，且只有来自大型GWAS的多基因评分与无子女现象相关。我们的研究结果还表明，遗传因素和社会人口学因素并非相互独立，初育年龄和曾生育子女数的多基因评分与教育和结婚年龄有关。多基因评分对无子女现象的解释变异有限，因为它在很大程度上是一种行为特征，随着GWAS功效的提高，未来遗传解释预计会有所增加。随着社会科学调查中个体基因分型变得更加普遍，本研究中描述的方法可应用于其他结果。
