Using Polygenic Scores in Social Science Research: Unraveling Childlessness

Renske M. Verweij*, Melinda C. Mills, Gert Stulp, Ilja M. Nolte, Nicola Barban, Felix C. Tropf, Douglas T. Carrell, Kenneth I. Aston, Krina T. Zondervan, Nilufer Rahmioglu, Marlene Dalgaard, Carina Skaarup, M. Geoffrey Hayes, Andrea Dunaif, Guang Guo, Harold Snieder

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

45 Downloads (Pure)


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
Original languageEnglish
Article number74
JournalFrontiers in Sociology
Number of pages14
Publication statusPublished - 2019


  • Fertility
  • Childlessness
  • Polygenic risk scores
  • Sociogenomics
  • Infertility


Dive into the research topics of 'Using Polygenic Scores in Social Science Research: Unraveling Childlessness'. Together they form a unique fingerprint.

Cite this