Reproduction and Aging

Background

Tradeoffs are believed to occur between biological function at all scales - from the molecular to the organismal. The three major categories in life history theory are growth, reproduction, and maintenance. Some scholars further partition maintenance between ‘survival’ and ‘defense’, because some physiological and immunological functions that favor survival now can come at the expense of health and survival over the long-term, potentially contributing to chronic and degenerative illness.

Organisms are limited in their capacity to acquire and allocate energy and other resources, resulting in tradeoffs between competing biological demands. These tradeoffs constrain evolution and influence phenotypic variation and health. For example, the number of children borne by a woman during her reproductive lifespan affects her disease risks and post-reproductive life expectancy. While consistent with evolutionary theory and research in other species, the mechanistic processes linking these ‘costs of reproduction’ to women’s health are unclear. Furthermore, women’s reproductive choices and obligations are situated within – and shaped by – broader social and physical contexts that affect health through other pathways.

Research: Past and current

A major branch of my research is centered on an assessment of the epigenetic processes underlying costs of reproduction in a cohort of young men and women in the Philippines. This work is conducted in collaboration with researchers in the US, Canada, and the Philippines as part of the Cebu Longitudinal Health and Nutrition Survey (CLHNS). The CLHNS is a large, longitudinal, multigenerational study based in metropolitan Cebu City, comprising more than 20 waves of data collected over the past 35 years. In addition to repeated measurements of participant growth, development, health, and reproduction, this study has generated extensive endocrine, immunological, genetic, and epigenetic data.

To test for costs of reproduction among women in Cebu, I used a measure of molecular aging referred to as ‘epigenetic age’. Epigenetic age is a biomarker of biological aging that is based on predictable changes in DNA methylation (DNAm) – a measure related to gene activity – at a subset of loci located across the genome. Epigenetic age unfolds predictably and is believed to reflect the degradation of molecular processes involved in maintaining epigenomic stability. The epigenetic ‘clock’ is the most accurate and robust predictor of chronological age currently available and has been validated in thousands of individuals across dozens of populations. More importantly, accelerated epigenetic age (relative to chronological age) is a strong predictor of all-cause mortality, making it a powerful tool to gauge the long-term health impacts of experiences earlier in the lifecycle (Ryan 2020).

Using epigenetic age (along with telomere length, a second measure of biological aging) as measures of cellular aging and predicted lifespan, we showed that women’s cells ‘aged’ with each additional pregnancy, supporting the theorized tradeoff between reproduction and bodily maintenance at the cellular level (Ryan et al. 2018). This effect was not attributable to genetic variation or to a range of social factors, such as urbanicity, parental education, household assets, or income. Despite evidence for cumulative costs of gravidity on cellular aging, women in our study appeared epigenetically ‘younger’ during pregnancy itself. To explore this paradox, I used genome-wide DNAm to characterize the epigenetic differences between women differing in reproductive status. These differences were used to construct ‘networks’ based on the functional properties of differentially-methylated genes. These findings, which are currently in preparation for publication, point to changes in immune function during pregnancy as potentially contributing to the lower risk for some cancers among parous women compared to nullipara. Furthermore, evidence for altered DNAm related to neurogenesis among parous women could shed light on previously reported effect of grand multiparity (>5 children) on Alzheimer’s Disease risk. Our finding that reproduction may carry not only cumulative costs (see also Sharazi, Hastings, Rosinger, and Ryan 2020) but also targeted protection, highlights the complex effects that reproduction likely confers on women’s health.

Graphical representation of our work, led by Talia Shirazi and Waylon Hastings at Penn State, showing how composite measures of biological aging derived from clinical measures are related to number of children among post-menopausal women. For more, see Shirazi, T. N., Hastings, W. J., Rosinger, A. Y. & Ryan, C. P. Parity predicts biological age acceleration in post-menopausal, but not pre-menopausal, women. Scientific Reports 10, 20522 (2020).

Research: Present and Future

I am following up on this research as part of the Cebu Longitudinal Health and Nutrition Survey and through other independent projects. Below is a brief description of some of these projects:

1. Longitudinal study of reproduction and women’s health.

While my work on the costs of reproduction at Cebu controls for a range of social, environmental, and genetic factors, the cross-sectional nature of this work makes it difficult to rule out the possibility that some of the effects are secondary to socioeconomic or other factors that might also affect DNAm and epigenetic age. To address this possibility, my current NSF funded work is updating reproductive histories and adding a second measure of DNAm as part of a 10-year follow-up. DNAm has been measured using DNA from dried blood spots (DBS) on the new ‘EPIC’ array (Illumina), which I have validated using replicate samples run on the legacy platform using whole blood. Expanding this work to include a second time point will minimize confounding tied to individual variation in health and access to resources. It will also produce DNAm data for an additional 800,000+ loci per individual, which will allow future investigations covering a range of questions about the relationship between the environment and the methylome in Cebu. This figure shows some of the longitudinal data I’m currently working on. Each line represents a woman at time 1 (left hand side) and time 2 (right hand side). The y-axis is gravidity (number of pregnancies) each woman reported in ongoing surveys between 2005 and 2009-2014. The slope is therefore the change in gravidity for each woman over time. This will be related to the change in epigenetic age over time, providing stronger indication of a causal role for gravidity and reproduction in accelerated epigenetic aging.

1. Funded NIH R01! Lifecourse determinants and outcomes of epigenetic age acceleration.

The sample sizes used for my work testing costs of reproduction in women (n = 400) are modest for human population epigenomics studies which can involve hundreds of thousands of tests. My dissertation was also not able to explicitly link epigenetic age with health and age-related decline. We are addressing these limitations through the addition of hundreds of DNAm samples for young men and women as part of a funded NIH R01 titled ‘Lifecourse determinants and outcomes of epigenetic age acceleration across two generations’. This grant – which I was instrumental in the conceptualization and writing of and for which I will lead bioinformatics moving forward – dovetails with and builds on the work laid out in my dissertation. It also expands our sample to the mothers of the original cohort, who are now between 56-83 years old. We will combine DNAm and epigenetic age in these older women with a study of health and aging completed in 2014. These data will allow us to explicitly test the relationships between epigenetic age and health and mortality in these women, which has yet to be done in a non-WEIRD population. This new funding for the Cebu study also will open up opportunities for involvement of students in the future, including in the data analysis, publication write up, and dissertation projects.

1. Fetal microchimerism and aging.

What might explain the cellular ‘youthfulness’ in epigenetic age that we observed among pregnant women? One possibility is fetal microchimerism – the ‘contamination’ of the maternal bloodstream by cells from her gestating child. If both maternal and fetal cells contribute to the DNA in a mother’s blood sample, our estimates of epigenetic age will be correspondingly skewed. Furthermore, the impact of fetal microchimerism on maternal aging is unknown. To test for fetal microchimerism on maternal epigenetic age, Dr. Meaghan Jones at the University of Manitoba and I are carrying out simulations using publicly-available datasets. If fetal microchimerism contributes significantly to maternal epigenetic age, this work will result in a correction factor for studies of epigenetic age that include pregnant women. It may also shed light on the interaction between maternal/fetal recognition, immunosenescence, and aging. Graphical depiction of microchimerism in its many guises. For an outstanding review of the topic, see Boddy, A. M., Fortunato, A., Sayres, M. W. & Aktipis, A. Fetal microchimerism and maternal health: A review and evolutionary analysis of cooperation and conflict beyond the womb. BioEssays 37, 1106–1118 (2015).