Felix C. Tropf

Human Fertility, Molecular Genetics, and Natural Selection in Modern Societies

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.

Does natural selection favour taller stature among the tallest people on earth

The Dutch are the tallest people on earth. Over the last 200 years, they have grown 20 cm in height: a rapid rate of increase that points to environmental causes. This secular trend in height is echoed across all Western populations, but came to an end, or at least levelled off, much earlier than in The Netherlands. One possibility, then, is that natural selection acted congruently with these environmentally induced changes to further promote tall stature among the people of the lowlands. Using data from the LifeLines study, which follows a large sample of the population of the north of The Netherlands (n = 94 516), we examined how height was related to measures of reproductive success (as a proxy for fitness). Across three decades (1935–1967), height was consistently related to reproductive output (number of children born and number of surviving children), favouring taller men and average height women. This was despite a later age at first birth for taller individuals. Furthermore, even in this low-mortality population, taller women experienced higher child survival, which contributed positively to their increased reproductive success. Thus, natural selection in addition to good environmental conditions may help explain why the Dutch are so tall.

Genetic influence on age at first birth of female twins born in the UK, 1919-68

Using a sample of monozygotic (945, 42 per cent) and dizygotic (1,329, 58 per cent) twin pairs born 1919–68 in the UK, we applied innovative tobit models to investigate genetic and environmental influences on age at first birth (AFB). We found that a substantial part (40 per cent) of the variation in AFB is caused by latent family characteristics. Genetic dispositions (26 per cent) play a more important role than the shared environment of siblings (14 per cent), with the non-shared environment/measurement error having the strongest influence (60 per cent). Like previous studies, this study reveals marked changes in estimates over time, and supports the idea that environmental constraints (war or economic crisis) suppress and normative freedom (sexual revolution) promotes the activation of genetic predispositions that affect fertility. We show that the exclusion of censored information (i.e., on the childless) by previous studies biased their results. Supplementary material for this article is available at: http://dx.doi.org/10.1080/00324728.2015.1056823

The Biodemography of Fertility: A Review and Future Research Frontiers

The social sciences have been reticent to integrate a biodemographic approach to the study of fertility choice and behaviour, resulting in theories and findings that are largely socially-deterministic. The aim of this paper is to first reflect on reasons for this lack of integration, provide a review of previous examinations, take stock of what we have learned until now and propose future research frontiers. We review the early foundations of proximate determinants followed by behavioural genetic (family and twin) studies that isolated the extent of genetic influence on fertility traits. We then discuss research that considers gene and environment interaction and the importance of cohort and country-specific estimates, followed by multivariate models that explore motivational precursors to fertility and education. The next section on molecular genetics reviews fertility-related candidate gene studies and their shortcomings and on-going work on genome wide association studies. Work in evolutionary anthropology and biology is then briefly examined, focusing on evidence for natural selection. Biological and genetic factors are relevant in explaining and predicting fertility traits, with socio-environmental factors and their interaction still key in understanding outcomes. Studying the interplay between genes and the environment, new data sources and integration of new methods will be central to understanding and predicting future fertility trends.ZusammenfassungIn sozialwissenschaftlichen Untersuchungen von Fertilitätsentscheidungen und –verhalten sind biodemographische Ansätze bislang kaum integriert worden, was zu überwiegend sozial-deterministischen Theorien und Befunden geführt hat. Der vorliegende Beitrag diskutiert zunächst die Gründe für diese weitgehend fehlende Integration, gibt dann einen Überblick über frühere Untersuchungen, fasst die bisher vorliegenden Erkenntnisse zusammen und zeigt schließlich Perspektiven zukünftiger Forschung auf. Ausgehend von grundlegenden Arbeiten zu den proximalen Determinanten der Fertilität werden verhaltensgenetische (Familien- und Zwillings-)Studien besprochen, die das Ausmaß genetischer Einflüsse auf Fertilitätsmerkmale isolieren konnten. Anschließend wird die Forschung zur Gen-Umwelt-Interaktion, zur Bedeutung von kohorten- und länderspezifischen Analysen sowie von Modellen, die Bildung und Fertilitätsentscheidungen vorausgehende Motivlagen berücksichtigen, betrachtet. Darüber hinaus werden Möglichkeiten und Grenzen molekulargenetischer Studien besprochen, bevor schließlich ein kurzer Überblick über Arbeiten aus der evolutionären Anthropologie und Biologie mit einem Fokus auf den Aspekt der natürlichen Auslese gegeben wird. Es zeigt sich, dass biologische und genetische Faktoren für das Verständnis und die Vorhersage von Fertilitätsmerkmalen relevant sind und dass ihre Interaktion mit sozialen Umweltfaktoren zentral für das Verständnis von Fertilitätsoutcomes ist. Für die Vorhersage zukünftiger Fertilitätstrends wird die Untersuchung des Zusammenspiels von Gen-Umwelt-Faktoren sowie die Nutzbarmachung neuer Datenquellen und die Integration neuer Methoden eine wesentliche Rolle spielen.

Evidence for Genetic Overlap Between Schizophrenia and Age at First Birth in Women

IMPORTANCE A recently published study of national data by McGrath et al in 2014 showed increased risk of schizophrenia (SCZ) in offspring associated with both early and delayed parental age, consistent with a U-shaped relationship. However, it remains unclear if the risk to the child is due to psychosocial factors associated with parental age or if those at higher risk for SCZ tend to have children at an earlier or later age. OBJECTIVE To determine if there is a genetic association between SCZ and age at first birth (AFB) using genetically informative but independently ascertained data sets. DESIGN, SETTING, AND PARTICIPANTS This investigation used multiple independent genome-wide association study data sets. The SCZ sample comprised 18 957 SCZ cases and 22 673 controls in a genome-wide association study from the second phase of the Psychiatric Genomics Consortium, and the AFB sample comprised 12 247 genotyped women measured for AFB from the following 4 community cohorts: Estonia (Estonian Genome Center Biobank, University of Tartu), the Netherlands (LifeLines Cohort Study), Sweden (Swedish Twin Registry), and the United Kingdom (TwinsUK). Schizophrenia genetic risk for each woman in the AFB community sample was estimated using genetic effects inferred from the SCZ genome-wide association study. MAIN OUTCOMES AND MEASURES We tested if SCZ genetic risk was a significant predictor of response variables based on published polynomial functions that described the relationship between maternal age and SCZ risk in offspring in Denmark. We substituted AFB for maternal age in these functions, one of which was corrected for the age of the father, and found that the fit was superior for the model without adjustment for the fathers age. RESULTS We observed a U-shaped relationship between SCZ risk and AFB in the community cohorts, consistent with the previously reported relationship between SCZ risk in offspring and maternal age when not adjusted for the age of the father. We confirmed that SCZ risk profile scores significantly predicted the response variables (coefficient of determination R2 = 1.1E-03, P = 4.1E-04), reflecting the published relationship between maternal age and SCZ risk in offspring by McGrath et al in 2014. CONCLUSIONS AND RELEVANCE This study provides evidence for a significant overlap between genetic factors associated with risk of SCZ and genetic factors associated with AFB. It has been reported that SCZ risk associated with increased maternal age is explained by the age of the father and that de novo mutations that occur more frequently in the germline of older men are the underlying causal mechanism. This explanation may need to be revised if, as suggested herein and if replicated in future studies, there is also increased genetic risk of SCZ in older mothers.

When genes and environment disagree: Making sense of trends in recent human evolution

In humans, for the first time, we are now able to observe ongoing natural selection at the molecular level. Natural selection operates when particular genetic variants render the individuals who bear them more likely to reproduce. As a consequence, those genetic variants increase in frequency in the next generation. In PNAS, Beauchamp (1) presents evidence of negative natural selection on genes implicated in higher educational attainment in a contemporary population in the United States. To understand his conclusion and avoid misinterpretation, we unpack the central concepts. The empirical study of natural selection in humans started with the examination of phenotypes: that is, individual traits, such as height or schizophrenia, measured without reference to genetics (Fig. 1). The simplest design establishes heritability of a phenotype by showing how much variation is attributed to genetic differences between relatives (using twins or other family members) (2). To claim evidence of natural selection, studies measure how much the number of children varies with the phenotype to produce a measure of the “magnitude” of natural selection. If the trait has some heritability and is associated with the number of children, researchers conclude that the traits are evolving as a result of natural selection (3). Height is highly heritable (4), so if taller individuals have more children, genes important for tall stature may become more frequent in future generations (5, 6). Fig. 1. The evolution of study designs used to document ongoing natural selection in contemporary human populations. The figure shows measurement and modeling approaches used to investigate ongoing natural selection. It differentiates between phenotypic and genotypic level and whether the level has been directly observed (gray box) or is inferred (red circles). The blue arrows mark the associations being used as evidence for natural selection. In classic study designs, the observed association between phenotype X … [↵][1]2To whom correspondence may be addressed. Email: courtiol{at}izw-berlin.de or melinda.mills{at}nuffield.ox.ac.uk. [1]: #xref-corresp-1-1

Mega-analysis of 31,396 individuals from 6 countries uncovers strong gene-environment interaction for human fertility

Family and twin studies suggest that up to 50% of individual differences in human fertility within a population might be heritable. However, it remains unclear whether the genes associated with fertility outcomes such as number of children ever born (NEB) or age at first birth (AFB) are the same across geographical and historical environments. By not taking this into account, previous genetic studies implicitly assumed that the genetic effects are constant across time and space. We conduct a mega-analysis applying whole genome methods on 31,396 unrelated men and women from six Western countries. Across all individuals and environments, common single-nucleotide polymorphisms (SNPs) explained only ~4% of the variance in NEB and AFB. We then extend these models to test whether genetic effects are shared across different environments or unique to them. For individuals belonging to the same population and demographic cohort (born before or after the 20th century fertility decline), SNP-based heritability was almost five times higher at 22% for NEB and 19% for AFB. We also found no evidence suggesting that genetic effects on fertility are shared across time and space. Our findings imply that the environment strongly modifies genetic effects on the tempo and quantum of fertility, that currently ongoing natural selection is heterogeneous across environments, and that gene-environment interactions may partly account for missing heritability in fertility. Future research needs to combine efforts from genetic research and from the social sciences to better understand human fertility. Authors Summary Fertility behavior – such as age at first birth and number of children – varies strongly across historical time and geographical space. Yet, family and twin studies, which suggest that up to 50% of individual differences in fertility are heritable, implicitly assume that the genes important for fertility are the same across both time and space. Using molecular genetic data (SNPs) from over 30,000 unrelated individuals from six different countries, we show that different genes influence fertility in different time periods and different countries, and that the genetic effects consistently related to fertility are presumably small. The fact that genetic effects on fertility appear not to be universal could have tremendous implications for research in the area of reproductive medicine, social science and evolutionary biology alike.

Is the Association Between Education and Fertility Postponement Causal? The Role of Family Background Factors

A large body of literature has demonstrated a positive relationship between education and age at first birth. However, this relationship may be partly spurious because of family background factors that cannot be controlled for in most research designs. We investigate the extent to which education is causally related to later age at first birth in a large sample of female twins from the United Kingdom (N = 2,752). We present novel estimates using within–identical twin and biometric models. Our findings show that one year of additional schooling is associated with about one-half year later age at first birth in ordinary least squares (OLS) models. This estimate reduced to only a 1.5-month later age at first birth for the within–identical twin model controlling for all shared family background factors (genetic and family environmental). Biometric analyses reveal that it is mainly influences of the family environment—not genetic factors—that cause spurious associations between education and age at first birth. Last, using data from the Office for National Statistics, we demonstrate that only 1.9 months of the 2.74 years of fertility postponement for birth cohorts 1944–1967 could be attributed to educational expansion based on these estimates. We conclude that the rise in educational attainment alone cannot explain differences in fertility timing between cohorts.

What Explains the Heritability of Completed Fertility? Evidence from Two Large Twin Studies

In modern societies, individual differences in completed fertility are linked with genotypic differences between individuals. Explaining the heritability of completed fertility has been inconclusive, with alternative explanations centering on family formation timing, pursuit of education, or other psychological traits. We use the twin subsample from the Midlife Development in the United States study and the TwinsUK study to examine these issues. In total, 2606 adult twin pairs reported on their completed fertility, age at first birth and marriage, level of education, Big Five personality traits, and cognitive ability. Quantitative genetic Cholesky models were used to partition the variance in completed fertility into genetic and environmental variance that is shared with other phenotypes and residual variance. Genetic influences on completed fertility are strongly related to family formation timing and less strongly, but significantly, with psychological traits. Multivariate models indicate that family formation, demographic, and psychological phenotypes leave no residual genetic variance in completed fertility in either dataset. Results are largely consistent across U.S. and U.K. sociocultural contexts.

SNP-Based Heritability Estimates of Common and Specific Variance in Self- and Informant-Reported Neuroticism Scales.

OBJECTIVE Our study aims to estimate the proportion of the phenotypic variance of Neuroticism and its facet scales that can be attributed to common single-nucleotide polymorphisms (SNPs) in two adult populations from Estonia (EGCUT; N = 3,292) and the Netherlands (Lifelines; N = 13,383). METHOD Genomic-relatedness-matrix restricted maximum likelihood (GREML) using genome-wide complex trait analysis (GCTA) software was employed. To build upon previous research, we used self- and informant reports of the 30-facet NEO personality inventories and analyzed both the usual sum scores and the residual facet scores of Neuroticism. RESULTS In the EGCUT cohort, the proportion of phenotypic variance explained by the additive effects of common genetic variants in self- and informant-reported Neuroticism domain scores was 15.2% (p = .070, SE = .11) and 6.2% (p = .293, SE = .12), respectively. The SNP-based heritability estimates at the level of Neuroticism facet scales differed greatly across cohorts and modes of measurement but were generally higher (a) for self- than for informant reports, and (b) for sum than for residual scores. CONCLUSIONS Our findings indicate that a large proportion of the heritability of Neuroticism is not captured by additive genetic effects of common SNPs, with some evidence for Gene × Environment interaction across cohorts.