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The ticking clock: how genetics may explain fertility traits

Dr Nicola Barban, Reader and Co-Director of the ESRC Research Centre on Micro-Social Change, is at the forefront of new research combining the study of genetics with social science.

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In many industrialised societies, first-time parents are considerably older than decades before, which in turn has consequences for the number of children they can have. Since the 1970s, there has been a rapid postponement by around 4-6 years in the mean age at first birth of women having their first child at around 24 years in 1970 to 29 years now in many industrialised societies. There has not only been postponement, but also significant increases in the levels in childlessness, with around 20-25% of women born in 1965-69 in Southern and Western European countries having no children.

The biological ability to conceive a child starts to decline steeply for some women as of age 25, with almost 50% of women being sterile by the age of 40. This means that a growing number of women start to have their first and subsequent children exactly at the time that their ability to conceive starts to decrease. Not surprisingly, this delay has led to an unprecedented growth in involuntary infertility, which affects between 10-15% of couples in Western countries. An estimated 48 million couples worldwide are infertile, with a large part of it, particularly in men, remaining unexplained.

Reproductive behaviour has been largely explained by social scientists by focusing on individual and couple characteristics and social structural or institutional factors. Birth postponement and a lower number of children has been largely attributed to social, economic and cultural environmental factors (i.e., individual and partner characteristics, socioeconomic status), with virtually no attention paid to the genetic or biological underpinnings of this behaviour. However, a growing number of studies based on twins have shown a genetic component underlying fertility traits such as number of children, age at first birth and age at first sexual intercourse.

Our recent study isolated twelve genetic variants associated with age at first birth and number of children (Barban et al. 2016) based on 300,000 individuals from 62 studies from all around the world. The study, published in Nature Genetics, allows for the first time to include a genetic variable or predictor of reproductive behaviour in our social science research. Given that human reproduction is a complex behavioural outcome, results show that it is not possible to use only one candidate gene to predict fertility outcomes. Rather, most genetic effects are too small and scattered all across the DNA. For this reason, the myriad of genetic variants is compiled into a comprehensive polygenic score that can be interpreted as a single quantitative measure of genetic predisposition. By looking at the genetics of an individual, it is possible to attribute to each person her/his predisposition for age at first birth or number of children.

The magnitude of the effect is not big. On average, one standard deviation (SD) variation on the polygenic score for age at first birth is associated with an increase of 175 days of age at first birth for women and 120 days for men, while the polygenic risk score for number of children is associated with an increase of 0.04 children on average. While these numbers seem ‘extremely small’, these results represent a first step in understanding the biological causes of involuntary infertility.

Importantly, by examining the function of the 12 DNA regions and the genes in these regions in detail, our research team has identified 24 genes that are likely to be responsible for variation in reproductive behaviour. Some of these genes were already known to influence infertility, while others have not yet been studied. An improved understanding of the function of these genes may provide new insights for infertility treatments.

Genetics play only a minor role in those traits that are mostly determined by personal choice and social factors, but these results may be very important at a population level to understand the interplay between biology and social sciences in explaining fertility outcomes and childlessness. For example, our results demonstrate a fascinating underlying genetic link with the shifting of the entire reproductive window for certain individuals. The polygenic score for age at first birth is clearly linked to development and the reproductive window. Those having a genetic propensity to later birth also have a later genetic propensity for the onset of menarche and menopause.

Also, polygenic scores can be used in conjunction with social factors to understand gene-environment interactions, meaning that the social environment may have different effects on people that are genetically different. This may affect the way we think about social policy, since social interventions may not have the same effect on all individuals.

It is moreover important to investigate the effect of genetics throughout the entire life course to understand at which age genetics play the most important role in shaping fertility outcomes. This can be done using surveys that collect information from the same individuals longitudinally such as Understanding Society, the UK Household Longitudinal Study, collecting genomic data from a subsample of the study.

We made all the results publicly available and we are collaborating with numerous studies to provide polygenic scores for researchers. For social scientists who study reproductive behaviour, we offer and provide an entirely new variable and way of theoretically thinking about and measuring human reproductive behaviour. These polygenic scores for age at first birth and number of children will also be easily usable in publicly available datasets, which will allow researchers to include these predictors in their biosocial research.

For further details see “The Sociogenomics of Polygenic Scores of Reproductive Behavior and Their Relationship to Other Fertility Traits” (M.C.Mills, N.Barban, F.C.Tropf), published in The Russell Sage Foundation Journal of the Social Science in April 2018.

Image credit: Photo credit: Brandi Redd