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PLoS One. 2015 Jun 3;10(6):e0126821. doi: 10.1371/journal.pone.0126821. eCollection 2015.

Human fertility, molecular genetics, and natural selection in modern societies.

Author information

1
Department of Sociology/ ICS, University of Groningen, Groningen, Netherlands.
2
Department of Population Health, London School of Hygiene and Tropical Medicine, London, England.
3
Department of Sociology/Nuffield College, University of Oxford, Oxford, England.
4
The Queensland Brain Institute, University of Queensland, Brisbane, Australia; The University of Queensland Diamantina Institute, The Translational Research Institute, Brisbane, Australia.
5
Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.

Abstract

Research on genetic influences on human fertility outcomes such as number of children ever born (NEB) or the age at first childbirth (AFB) has been solely based on twin and family-designs that suffer from problematic assumptions and practical limitations. The current study exploits recent advances in the field of molecular genetics by applying the genomic-relationship-matrix based restricted maximum likelihood (GREML) methods to quantify for the first time the extent to which common genetic variants influence the NEB and the AFB of women. Using data from the UK and the Netherlands (N = 6,758), results show significant additive genetic effects on both traits explaining 10% (SE = 5) of the variance in the NEB and 15% (SE = 4) in the AFB. We further find a significant negative genetic correlation between AFB and NEB in the pooled sample of -0.62 (SE = 0.27, p-value = 0.02). This finding implies that individuals with genetic predispositions for an earlier AFB had a reproductive advantage and that natural selection operated not only in historical, but also in contemporary populations. The observed postponement in the AFB across the past century in Europe contrasts with these findings, suggesting an evolutionary override by environmental effects and underscoring that evolutionary predictions in modern human societies are not straight forward. It emphasizes the necessity for an integrative research design from the fields of genetics and social sciences in order to understand and predict fertility outcomes. Finally, our results suggest that we may be able to find genetic variants associated with human fertility when conducting GWAS-meta analyses with sufficient sample size.

PMID:
26039877
PMCID:
PMC4454512
DOI:
10.1371/journal.pone.0126821
[Indexed for MEDLINE]
Free PMC Article

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