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Using Polygenic Scores in Social Science Research: Unraveling Childlessness

Verweij, Renske M and Mills, Melinda C and Stulp, Gert and Nolte, Ilja M and Barban, Nicola and Tropf, Felix C and Carrell, Douglas T and Aston, Kenneth I and Zondervan, Krina T and Rahmioglu, Nilufer and Dalgaard, Marlene and Skaarup, Carina and Hayes, M Geoffrey and Dunaif, Andrea and Guo, Guang and Snieder, Harold (2019) 'Using Polygenic Scores in Social Science Research: Unraveling Childlessness.' Frontiers in Sociology, 4. ISSN 2297-7775

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Abstract

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 (N = 10,686) and Wisconsin Longitudinal Study (N = 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.

Item Type: Article
Uncontrolled Keywords: fertility, childlessness, polygenic risk scores, sociogenomics, infertility
Divisions: Faculty of Social Sciences > Institute for Social and Economic Research
Depositing User: Elements
Date Deposited: 08 Jan 2021 14:12
Last Modified: 08 Jan 2021 14:12
URI: http://repository.essex.ac.uk/id/eprint/26035

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