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Genes can predict a woman's first birth
Researchers analyzed the genes of thousands of women in the UK and the Netherlands and found the genes accurately predicted in about 15 per cent of women, when they will have their first baby.
University of Oxford researchers analysed the genomes of thousands of women in the United Kingdom and the Netherlands to measure the extent to which her genes play a role in when she has her first child — or how many children she will have.
Significantly, they found some women are genetically predisposed to have children earlier than others and conclude this time table was passed down as a reproductive advantage. However, they also found that although modern women (born in the 20th century) might be evolutionarily expected to have babies earlier than previous generations, they choose not to.
The study, published in the journal PLOS ONE, found women in modern societies are "over-riding" natural selection due to the strong influences of today's lifestyle.
The international team working on the Sociogenome Project, led by the University of Oxford and funded by the European Research Council, exploited the latest advances in molecular and quantitative genetics. They combined data from 4,300 unrelated women in the Netherlands in the Lifelines Cohort Study, with results from TwinsUK, another 2,400 women, the United Kingdom's largest adult twin registry — from which they randomly selected only one twin for analysis.
From all these women, they found that genes account for about 15 per cent of the differences between when modern women have their first baby, and 10 per cent difference between women in regards to the number of children they will have. They also discovered a genetic overlap that helps explain why women having earlier births also have more children.
Previous similar studies have relied on datasets related to twins — or within families. But, this is the first time research has used molecular genetic information of unrelated women including the population-based Lifelines study.
By combining the genetic results of both datasets, they found natural selection is not just an historic process. Modern societies are still evolving, with early fertility patterns being an inherited reproductive advantage.
Project leader Professor Melinda Mills, from the Department of Sociology at Nuffield College, University of Oxford adds: "In evolutionary and genetic terms, this suggests that younger generations today should be inclined to have children at an earlier age than women in the past. However, what we actually observe is that the reverse is happening. Social and environmental factors mean women in modern societies are delaying starting families, knowing there is a risk of becoming infertile if they leave it off too late.
"This research tells us there are genetic differences between women which could be significant for women making decisions about when to have their first baby."
"In the second half of the 20th century, women across many societies delay starting a family. Although genes play a significant part, it seems wider social changes, such as an increase of women going further in education and working, as well as available effective contraception, are having a stronger impact on determining when women in modern societies have children."
Felix Tropf PhD, lead author, the University of Groningen in the Netherlands
Finally, the results suggest scientists may be able to find genetic variations associated with human fertility in such meta data that can help in diagnosis and treatment of infertility.
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.
The paper was authored by a team from the University of Oxford, the University of Groningen; University Medical Center Groningen; London School of Hygiene and Tropical Medicine; and Queensland Brain Institute, Australia.
The paper, 'Human Fertility, molecular genetics, and natural selection in modern societies' by Felix C. Tropf, Gert Stulp, Nicola Barban, Peter M. Visscher , Jian Yang, Harold Snieder and Melinda C. Mills is published in the journal, PLOS ONE, on 3 June 2015, at http://dx.plos.org/10.1371/journal.pone.0126821
For the Netherlands sample, the data used was from the Lifelines Cohort Study, a population-based study examining the health and health-related behaviours of three generations of 167,000 people living in the north. It includes genotyped information from more than 13,000 unrelated individuals.
For the UK, the data was from TwinsUK, the largest adult twin registry in the country with more than 12,000 respondents. The research team randomly selected only one twin for analysis and controlled for dizygotic twinning as a genetically related process.
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