Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-16T07:27:20.258Z Has data issue: false hasContentIssue false

Chapter 13 - Causal Crypticity

from Section 3 - Key Concepts for Biosocial Research

Published online by Cambridge University Press:  20 June 2024

Michelle Pentecost
Affiliation:
King's College London
Jaya Keaney
Affiliation:
University of Melbourne
Tessa Moll
Affiliation:
University of the Witwatersrand
Michael Penkler
Affiliation:
University of Applied Sciences, Wiener Neustadt

Summary

The concept of ’causal crypticity’ was introduced by Richardson (2021) to describe the DOHaD field’s high tolerance for both causes and effects that are challenging to observe in nature, show small effect sizes, and are unstable across study populations and contexts. Causal crypticity can be understood in three ways: as an epistemic norm; as a boundary-delimiting signature of field culture or epistemic style; and as a promissory mode. Increasingly, causal crypticity characterises many fields of the big data-rich, postgenomic life sciences, making DOHaD science a useful index case for scholars of the history, philosophy, and social studies of science interested in the epistemic terrain and social implications of postgenomic sciences. The chapter concludes with a discussion of ethical and accountable claimsmaking in DOHaD science under conditions of causal crypticity.

Type
Chapter
Information
The Handbook of DOHaD and Society
Past, Present, and Future Directions of Biosocial Collaboration
, pp. 155 - 165
Publisher: Cambridge University Press
Print publication year: 2024
Creative Commons
Creative Common License - CCCreative Common License - BY
This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY 4.0 https://creativecommons.org/cclicenses/

Causal crypticity is an epistemic norm in the field of maternal–fetal effects science. That is, fetal origins researchers assert causal hypotheses about links between small permutations in the gestational environment and later life outcomes. The causes and effects of these permutations are typically not directly observed but are inferred from variations in developmental outcomes or health risks that occur later in life, often along a decades-long chain of other exposures and experiences. To advance these hypotheses requires field-wide epistemic norms that accept, in most cases, an ineliminable crypticity – meaning both subtlety and elusiveness – in the causes and effects under study.

This feature of Developmental Origins of Health and Disease (DOHaD) science is not the perception of hard-nosed sceptics. Many DOHaD researchers are frank about its causal dilemmas [Reference Heijmans and Mill1Reference Richmond, Relton and Davey Smith3]. DOHaD scientists have faced fierce criticisms of their theories and findings by scientists who doubt the plausibility of their causal claims [Reference Paneth and Susser4Reference Wilcox7], and scientists in the varied research streams that comprise fetal origins/maternal effects science have been openly debating the question of causality for decades. The search for causal mechanisms propelled the entry of epigenetic methodologies into the field and contributed to the pioneering of new inference causal testing models such as Mendelian randomisation to attempt to examine the plausibility and strength of hypothesised causal relations [Reference Birney, Smith and Greally8Reference Richmond, Timpson, Felix, Palmer, Gaillard and McMahon12].

The crypticity of causality in DOHaD is no standard-issue causality conundrum. As I argued in The Maternal Imprint: The Contested Science of Maternal-Foetal Effects (2021), from the field’s inception, causal crypticity has been deeply carved into the historical development of the field and will likely continue to be a persistent feature of any research in maternal–fetal effects science, regardless of the amount of data acquired or the sophistication of computational methods employed [Reference Richardson13]. Nods to the context-specificity and complexity of causal attributions in DOHaD science do not sufficiently acknowledge the persistent, intransigent crypticity of causality in maternal–fetal effects science, nor do they capture the social dimension of its function as an epistemic style in DOHaD discourse.

High tolerance for causal crypticity can be defined as a field-defining epistemic norm that accepts a persistent state of indeterminacy about the empirical reality, strength, and magnitude of hypothesised causal phenomena that are the object of study. Causal crypticity distinguishes approaches to causal reasoning within DOHaD from certain ideals of scientific inference prising replicable experiments, intervenability demonstrating causal invariability across conditions, and identification of a physiological mechanism [Reference Woodward14]. But this does not imply that causal crypticity is particularly epistemically suspect compared to other causality-seeking knowledge projects. Causal crypticity is not a term intended to pinion the scientific merit or rigour of DOHaD science but to characterise its epistemic norms to better understand the field’s theories, its evidential base, and the judgements that undergird its inferences. My claim is descriptive, not evaluative: causal crypticity operates as an epistemic norm in DOHaD science.

In this chapter, I explicate and develop the concept of causal crypticity, first introduced in Richardson (2021). Causal crypticity can be understood in three ways: as an epistemic norm; as a boundary-delimiting signature of field culture or epistemic style; and as a promissory mode. Contending with causal crypticity as a norm-shaping feature of the knowledge landscape of maternal–fetal effects science, I conclude, demands reflection on strategies for ethical and accountable practices of claimsmaking in DOHaD science, in a world where its findings are received as carrying social implications in arenas ranging from reproductive autonomy to efforts to redress the health implications of racism and intergenerational trauma.

13.1 Crypticity

The term ‘cryptic’ has multiple connotations, which I embrace. Something that is cryptic may be real but difficult to decode or retrieve. Equally, something that is cryptic can be unclear, and whether it is real or not can be impossible to discern. Phenomena that are cryptic are elusive, shape-shifting, and impermanent in form. DOHaD science connects cryptic effects with cryptic causes. Cryptic effects are findings of health outcomes in exposed compared to unexposed populations that are small in effect size and that present inconsistently across different study cohorts; moreover, such crypticity in reported outcomes is persistent and unresolved despite expanding volumes of data. Cryptic effects are typified by DOHaD studies reporting small absolute changes in risk factors for common diseases among populations of healthy, average births exposed to a hypothesised intrauterine variable.

The field’s tolerance for causal crypticity is in clear evidence, for instance, in the Dutch famine studies, a touchstone in DOHaD research. The Dutch famine studies are often presented as definitively demonstrating a causal link between nutrition in the womb and obesity and related metabolic conditions, including high blood pressure, diabetes and insulin resistance, and cardiovascular disease. These metabolic outcomes are based on measures taken from a small sample of 422 survivors, in their fifties, who were gestationally exposed to the famine (and matched siblings) during the four months of the acute famine of 1944–1945 in the Netherlands [Reference Lumey, Stein, Kahn, van der Pal-de Bruin, Blauw and Zybert15]. As researchers will readily agree when queried, the findings from these studies are much less generalisable, and much more contingent and uncertain, than portrayed in the standard textbook narrative. Famine survivors have been found to have, on average, modestly elevated blood pressure compared to non-survivors [Reference Stein, Zybert, van der Pal-de and Lumey16]. Women gestated during the Dutch famine have, on average, an extra few centimetres around the waist, at age 59, than their non-exposed sisters [Reference Rundle, Stein, Kahn, van der Pal–de Bruin, Zybert and Lumey17]. However, the effect sizes in such findings are small. They are also unstable, appearing and disappearing across different age cohorts and genders/sexes within the study populations. Critical reviews demonstrate that the Dutch famine studies have shown a few, if any, stable metabolic outcomes of significant effect size specifically correlated with in utero exposure to famine [Reference Lumey, Stein and Susser18].

Other statements frequently reiterated in the literature, such as that early exposure to famine doubles the risk of obesity, are, upon examination, not supported by current evidence but are statistical relics of dated metrics of what constitutes abnormally overweight body composition from the 1970s [Reference Ravelli, Stein and Susser19]. Furthermore, researchers have struggled to identify biological mechanisms that could account for the purported specific causal effects of famine exposure during gestation. A much-celebrated early finding of epigenetic changes in the insulin-like growth factor 2 (IGF2) gene among famine survivors has never been replicated [Reference Heijmans, Tobi, Stein, Putter, Blauw and Susser20, Reference Tobi, Slieker, Luijk, Dekkers, Stein and Xu21]. Subsequent studies attempting to find epigenetic mediators of triglyceride levels among survivors have not withstood causality inference testing [Reference Richmond, Relton and Davey Smith3]. Yet even as effects are causally cryptic – effect sizes remain small, findings are contested and conflicting, and mechanisms are elusive – the Dutch famine studies are presented in the literature as a foundation and model for future work [Reference Roseboom22], and scientific publications, textbooks, and popular media frequently feature studies of health outcomes among ageing members of the cohort of infants gestated during the Dutch famine as a gold-standard example of the promise of developmental origins science [Reference Zimmer23].

Causal crypticity characterises the explanations for cryptic effects because such cryptic effects are unstable and variable, such that they make non-ideal observations for substantiating a link to a specific cause. In the case of maternal intrauterine effects, in which the direct effects of perturbations during gestation are already challenging to observe, measure, or quantify, causal crypticity is particularly amplified. This is because, due to the many environmental and genetic confounders of early human development, in nearly every case the cryptic maternal effect is an endpoint of complex, multiply confounded causal chains, frequently occurring at a significant temporal distance from the hypothesised initial exposure, which itself is sometimes a confounded, variably defined, difficult-to-measure ‘cryptic cause’ such as ‘stress’ or ‘metabolic dysregulation’.

Such crypticity is apparent even within maternal–fetal programming science that is often presented as most foundational, most settled, and as presenting the most extreme exposures, the largest effects, and the most incontrovertible findings, as in the Dutch Hunger Winter studies. The field’s high tolerance for causally cryptic findings as constituting knowledge helps us understand how such findings, which at best offer support for what may be model-theoretically plausible or physiologically possible, become concretised as a textbook, settled science, and as known or proven facts within the field of DOHaD.

13.2 Causal Crypticity as an Epistemic Style and Promissory Mode

Tolerance for causal crypticity, as a feature of the DOHaD field’s culture, norms, standards, or epistemic style, is apparent in the forms of evidence accepted within the DOHaD field as contributions to scientific knowledge and reflected in its shared assumptions about the questions and objects of interest. For example, the quality of crypticity is arguably constitutive of what makes something a developmental or maternal effect rather than, for instance, a birth defect or anomaly. Causal crypticity is, furthermore, integral to the central questions and problems that the DOHaD field addresses and to how it goes about addressing them. As Gemma Sharp, Debbie Lawler, and I have argued, the question of whether maternal–fetal programming effects are real is in many senses not a question for researchers in the DOHaD field. For DOHaD researchers, it is indisputable that programmable maternal–fetal effects are real [Reference Sharp, Lawlor and Richardson24]; the question is only whether we can see and prove them, given that the biology involved must be very complex and that the pragmatics of studying maternal–fetal effects in human populations is challenging.

Scientific fields are social formations. Sociologists and historians of science posit that scientific fields function most efficiently to advance empirical understanding of phenomena when there is a shared culture of sorts and when the field agrees on its core questions. As a part of this boundary-defining work, fields typically close down or defer certain questions as well as certain epistemological considerations [Reference Bourdieu25Reference Knorr-Cetina28]. Causal crypticity can be tolerated, one might hypothesise, when it serves other important functions for the field as a social formation. Following scholars of scientific hype [Reference Fortun29, Reference Caulfield30], one speculation is that causal crypticity may function to keep fetal origins science at the centre of controversy, with findings persistently described as emergent, yet to be validated, still being tested, and even essentially contested. In part because of this, causal crypticity could work cathectically to draw intrigue and to construct a continually self-replicating arc of future speculation and possibility. In this way, causal crypticity may function as an electric current that both makes the field of maternal–fetal effects a flashpoint and draws curious researchers to it.

In this sense, causal crypticity can be understood as a promissory discourse that conveys causal-ish claims that generate excitement and interest [Reference Fortun29]. Thus, although the field is now more than three decades old, its claims are frequently presented as offering a new, emergent, and provocative resource for science. It is commonplace to read in publications, to hear at an academic conference on DOHaD, or to find in a media presentation of DOHaD research a statement such as: ‘In recent years, research from the field of the Developmental Origins of Health and Disease (DOHaD) has suggested that events before birth can have life-long consequences’ [Reference Jacob and Hanson31]. Such broad statements suggesting a powerful causal relation between intrauterine environment and later life health are, technically speaking, perfectly consistent with a collection of unreplicated findings that intrauterine exposure X is associated with small effects on offspring outcome Y in study population Z, yet it also implies stronger and more widely validated causal effects actionable for public health and in the clinic than present evidence can support.

Specifically, causal crypticity may function socially and discursively to generate excitement and interest in the scientific field by pointing towards a future in which knowledge of such cryptic patterns could be harnessed to optimise health outcomes [Reference Heeney32]. Notably, cryptic patterns of perturbations linked to outcomes do not promise control or prediction for any particular individual, but at best speak to patterns and trends and to risk categories and potential problems at the level of population groups [Reference Penkler33]. These patterns and risk categories generate uncertainty and require concern and ongoing monitoring.

In a world rife with crises, risk, and uncertainty, the potential for cryptic sources of fetal developmental perturbation requiring ongoing tracking is everywhere. We thus see speculation about the relevance of developmental origins theories to nearly every area of social anxiety and uncertainty, including natural disasters and political or economic crises, from the 9/11 attacks [Reference Berkowitz, Wolff, Janevic, Holzman, Yehuda and Landrigan34Reference Ohlsson and Shah36] to climate change [Reference Wesselink and Wellenius37Reference Derfel39], to most recently, the COVID-19 pandemic [Reference Forestieri, Pintus, Marcialis, Pintus and Fanos40Reference Schoenmakers, Verweij, Beijers, Bijma, Been and Steegers-Theunissen42]. Writing in 2021, Tessa Roseboom and colleagues warned in the Journal of the Developmental Origins of Health and Disease that ‘the legacy of this pandemic looms large for unborn babies … These individuals, being unseen and unheard, are likely to go unprotected’. The implications of experiencing the pandemic while in the womb, these authors assert, will affect an entire generation and ‘all of our future societies’: ‘Today’s (unborn) children will drive growth and development in our future societies. […] We must now act to prevent further scarring of the life chances of a generation’ [Reference Roseboom, Ozanne, Godfrey, Isasi, Itoh and Simmons41]. The potential for harm to the ‘unborn’ is pervasive, as in Figure 13.1, which conceptualises the mother’s work, daily hassle, and even the condition of pregnancy itself, as health-imperilling stressors transmuted to the fetus through the mother [Reference Schoenmakers, Verweij, Beijers, Bijma, Been and Steegers-Theunissen42].

Figure 13.1 ‘Overview of potential maternal prenatal stressors during the current COVID-19 pandemic as part of the early life course medicine’.

DOHaD science on maternal–fetal effects promises to inform public policy to improve future outcomes, but causal crypticity entails that DOHaD research is not, by and large, likely to produce interventions driven by the reversal of biochemical mechanisms at the moment or site of programming [Reference Penkler33]. In a field of inquiry characterised by the epistemic style and promissory mode of causal crypticity, interventions, while hoped-for, are ultimately less the order of the day than demonstrating the possibility or plausibility of harm. In the case of DOHaD, this harm is conceptualised as a limitation on future potential. That is, DOHaD findings of cryptic effects deliver evidence of limitations or lesions in the potential for life flourishing, from early mortality to educational achievement. Powerful ableist, Western norms and pressures to optimise birth outcomes, complemented by globalist, development economics frameworks for measuring human capital in the metrics of health and at the level of the body, help sustain this promissory mode in maternal–fetal effects science [Reference Valdez43Reference Reiches46]. The range of possible future adverse outcomes is so wide that the full implications of the developmental harm can never be fully grasped, only proxied by limited quantitative physiological measures such as adiposity or blood pressure. Moreover, it is argued that these harms are set so early in development that compensating for or redressing the harms will be challenging. DOHaD researchers frequently suggest that early developmental harms might only be redressed in future generations by removing or waiting out the scourge of trauma, poverty, or metabolic deprivation.

13.3 Causal Crypticity in the Context of Big Data and Postgenomic Science

While DOHaD science has long operated with a high tolerance for causal crypticity, the epistemic norm of causal crypticity, as I have characterised it here, increasingly might be said to characterise the knowledge claims and knowledge practices endemic to data-rich, twenty-first-century postgenomic biomedical life sciences, particularly those endeavours operating in complex biosocial causal spaces. Indeed, as commentators have pointed out [Reference Richardson and Stevens47], in many areas of postgenomic biomedicine, causal claims are not expected to result from investigations. It is expected that the strength of findings will vary depending on contextual factors and that findings will not replicate across all datasets. Even as researchers strive to validate causal connections, a tolerance for a certain permissiveness with implying the likely causality of observed correlations is increasingly integrated into the norms and culture of postgenomic biomedicine.

There is a broader social context for these shifts in knowledge paradigms in the postgenomic life sciences. The epistemic style of causal crypticity is primed to flourish in a knowledge culture defined by massive information. The epistemology of massive information is defined by constructs such as ‘search’, trending ideas, chatter, pattern recognition, the notion of ‘data mining’, network, and systems-like ideas about the connectivity of all things, total information, emergence, and surveillance [Reference Stevens, Richardson and Stevens48]. This epistemology contrasts sharply with ‘magic bullet’ or ‘master molecule’ approaches to knowledge that are oriented towards control, intervention, and cure [Reference Keller49]. In a knowledge culture embracing causal crypticity, grievance or evidence of harm is not expected to surface as a gaping wound – acute, localisable, and repairable – but as a population-level signal – subtle, elusive, and with harms and benefits of uncertain interpretation.

Similarly in postgenomic science, signals are not expected to be single-gene lesions [Reference Boyle, Li and Pritchard50], but polygenic scores or risk calculi that must be carefully contextualised against a backdrop of population genetic structure, developmental context, and social conditions. These sciences, underpinned by genome-wide association studies, multidimensional forms of social data, and AI-informed analytics, are made up of statistically sophisticated evidence of correlations between biological and social outcomes. While these correlations themselves do not support causal inference, causal crypticity enables a presumption of the likelihood of causality. Findings are narrated within a larger frame that implies a strong assumption that such correlations, summed in their entirety, are evidence supporting an intuition of causality. This shift in epistemic norms is collapsing the twentieth-century oppositional distinction between the complexity-affirming ‘dissident’ anti-genetic determinist sciences and the reductionist and determinist gene-centric biological sciences [Reference Richardson, Richardson and Stevens51].

In sum, causal crypticity is an epistemic norm that aligns with the speculative and promissory mode of today’s transnational, big data-crunching science, which proposes to mine previously undetected patterns across populations, unlocking a key to who we are and where we are going in our uncertain era of demographic transformation in lifespans and family size, technological change, and environmental crisis. Like these fields, DOHaD pleads for a deferral of judgement and for more space for free investigation, by implicitly suggesting that cryptic patterns long postulated or hypothesised, and for which current evidence is trace-like at best, will soon be detectable as meaningful sources of human variation in health – once we have the data and the proper data mining tools to retrieve those patterns. In this way, within the postgenomic life sciences, DOHaD science offers an index case of the leading edge of a broadening trend of embracing the bold pursuit of cryptic causes.

13.4 Ethical and Accountable Claimsmaking in DOHaD Science under Conditions of Causal Crypticity

In The Maternal Imprint, I traced the history of attempts to empirically confirm speculations about the long-term or permanent effects of experiences or exposures in the womb [Reference Richardson13]. The book followed three intertwining threads within this history: First, discourses about maternal agency and responsibility for reproductive outcomes. Second, progressive, anti-genetic determinist constructs of the biosocial body position the maternal–fetal relation as a particularly heightened space for the inscription of social and environmental context on the body. Third persistent and unresolved questions about the limits of empirical science in confirming the causal effects of intrauterine perturbations on disease distribution in human populations.

This third, seemingly epistemic dimension, I argued, cannot be fully pulled apart from the other two. This is because bold causal claims in the absence of consistent and convincing evidence of predictive, intervenable effects can only persist if there is a powerful social and scientific imaginary carrying them forward. The churning, resilient, charged space of maternal responsibility for optimising reproductive outcomes and the subversive, hopeful, riveting, intuitive, and narratively compelling picture of bodies embedded in environments and social systems are two such imaginaries.

The subtle effect sizes and complex confounding typical of causal claims in DOHaD science are not simply an everyday causal challenge but rather function as both a defining epistemic norm of the field and a future-oriented social discourse. The concept of ‘causal crypticity’ directs attention to the links between causal crypticity as an epistemic norm, the production of risk categories, and the promissory hype cycle of science.

Fields such as DOHaD are defining the epistemic terrain of postgenomic inquiry, particularly at the interface of the genetic and social sciences [Reference Richardson, Richardson and Stevens51]. For some DOHaD scientists, the concept of causal crypticity as I have motivated it here may at first provoke defensiveness. Most scientists understand themselves instead to be seeking – even if not always finding – causal relations grounded only on rigorous empirical inference. However, embracing this feature of DOHaD research could make DOHaD a laboratory for grappling with causal crypticity in a reflective and forthcoming manner. This surely includes strengthening frameworks for making causal inferences in the face of causal crypticity, as some already are [Reference Lawlor, Relton, Sattar and Nelson2, Reference Gage, Munafo and Davey52]. But it also includes practices such as rigorously placing risk claims emerging from such sciences in context, in particular through collaboration with social scientists exploring the socio-structural dimensions of health and lifecourse development [Reference Müller, Hanson, Hanson, Penkler, Samaras and Chiapperino53], accurately characterising the degree of uncertainty in scientific findings in this area [Reference Richardson, Daniels, Gillman, Golden, Kukla and Kuzawa54], and educating the consumers of such science in the features of reasoning in a field defined by causal crypticity.

References

Heijmans, BT, Mill, J. The seven plagues of epigenetic epidemiology. International Journal of Epidemiology. 2012;41(1):74–8.CrossRefGoogle ScholarPubMed
Lawlor, DA, Relton, C, Sattar, N, Nelson, SM. Maternal adiposity – A determinant of perinatal and offspring outcomes? Nature Reviews Endocrinology. 2012;8(11):679–88.CrossRefGoogle ScholarPubMed
Richmond, R, Relton, C, Davey Smith, G. What evidence is required to suggest that DNA methylation mediates the association between prenatal famine exposure and adulthood disease. Scientific Advances. 2018;eLetter to eaao4364.Google Scholar
Paneth, N, Susser, M. Early origin of coronary heart disease (the ‘Barker hypothesis’). British Medical Journal. 1995;310(6977):411–12.CrossRefGoogle ScholarPubMed
Lancet. An overstretched hypothesis? Lancet. 2001;357(9254):405.CrossRefGoogle Scholar
Geronimus, AT. Deep integration: Letting the epigenome out of the bottle without losing sight of the structural origins of population health. American Journal of Public Health. 2013;103:S56.CrossRefGoogle ScholarPubMed
Wilcox, AJ. On the importance – and the unimportance – of birthweight. International Journal of Epidemiology. 2001;30(6):1233–41.CrossRefGoogle ScholarPubMed
Birney, E, Smith, GD, Greally, JM. Epigenome-wide association studies and the interpretation of disease -omics. PLOS Genetics. 2016;12(6):e1006105.CrossRefGoogle ScholarPubMed
Davey Smith, G, Hemani, G. Mendelian randomization: Genetic anchors for causal inference in epidemiological studies. Human Molecular Genetics. 2014;23(R1):R89R98.CrossRefGoogle ScholarPubMed
Langley, K, Heron, J, Smith, GD, Thapar, A. Maternal and paternal smoking during pregnancy and risk of ADHD symptoms in offspring: Testing for intrauterine effects. Am Journal of Epidemiology. 2012;176(3):261–8.CrossRefGoogle ScholarPubMed
Lawlor, DA, Timpson, NJ, Harbord, RM, Leary, S, Ness, A, McCarthy, MI, et al. Exploring the developmental overnutrition hypothesis using parental-offspring associations and FTO as an instrumental variable. PLoS Medicine. 2008;5(3):e33.CrossRefGoogle ScholarPubMed
Richmond, RC, Timpson, NJ, Felix, JF, Palmer, T, Gaillard, R, McMahon, G, et al. Using genetic variation to explore the causal effect of maternal pregnancy adiposity on future offspring adiposity: A Mendelian Randomisation Study. PLoS Medicine. 2017;14(1):e1002221.CrossRefGoogle ScholarPubMed
Richardson, SS. The Maternal Imprint: The Contested Science of Maternal-fetal Effects. Chicago: University of Chicago Press; 2021. 310 p.CrossRefGoogle Scholar
Woodward, JF. Making Things Happen: A Theory of Causal Explanation. New York: Oxford University Press; 2003. vi, 410 p.Google Scholar
Lumey, LH, Stein, AD, Kahn, HS, van der Pal-de Bruin, KM, Blauw, GJ, Zybert, PA, et al. Cohort profile: The Dutch Hunger Winter families study. International Journal of Epidemiology. 2007;36(6):1196–204.CrossRefGoogle ScholarPubMed
Stein, AD, Zybert, PA, van der Pal-de, Bruin K, Lumey, LH. Exposure to famine during gestation, size at birth, and blood pressure at age 59 y: Evidence from the Dutch famine. European Journal of Epidemiology. 2006;21(10):759–65.CrossRefGoogle ScholarPubMed
Rundle, A, Stein, AD, Kahn, HS, van der Pal–de Bruin, K, Zybert, PA, Lumey, L. Anthropometric measures in middle age after exposure to famine during gestation: Evidence from the Dutch famine. The American Journal of Clinical Nutrition. 2007;85(3):869–76.Google Scholar
Lumey, LH, Stein, AD, Susser, E. Prenatal famine and adult health. Annual Review of Public Health. 2011;32(1):237–62.CrossRefGoogle ScholarPubMed
Ravelli, GP, Stein, ZA, Susser, MW. Obesity in young men after famine exposure in utero and early infancy. New England Journal of Medicine. 1976;295(7):349–53.CrossRefGoogle ScholarPubMed
Heijmans, BT, Tobi, EW, Stein, AD, Putter, H, Blauw, GJ, Susser, ES, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proceedings of the National Academy of Sciences. 2008;105(44):17046–9.CrossRefGoogle ScholarPubMed
Tobi, EW, Slieker, RC, Luijk, R, Dekkers, KF, Stein, AD, Xu, KM, et al. DNA methylation as a mediator of the association between prenatal adversity and risk factors for metabolic disease in adulthood. Science Advances. 2018;4(1):eaao4364.CrossRefGoogle ScholarPubMed
Roseboom, TJ. Epidemiological evidence for the developmental origins of health and disease: Effects of prenatal undernutrition in humans. Journal of Endocrinology. 2019;242(1):T135–T44.CrossRefGoogle ScholarPubMed
Zimmer, C. The famine ended 70 years ago, but Dutch genes still bear scars. The New York Times. 2018 31 Jan.Google Scholar
Sharp, GC, Lawlor, DA, Richardson, SS. It’s the mother!: How assumptions about the causal primacy of maternal effects influence research on the developmental origins of health and disease. Social Science & Medicine. 2018;213:20–7.CrossRefGoogle ScholarPubMed
Bourdieu, P. The specificity of the scientific field and the social conditions of the progress of reason. Social Science Information. 1975;14(6):1947.CrossRefGoogle Scholar
Panofsky, A. Misbehaving Science: Controversy and the Development of Behavior Genetics. Chicago: The University of Chicago Press; 2014.CrossRefGoogle Scholar
Kuhn, TS. The Structure of Scientific Revolutions. Chicago: University of Chicago Press; 1962. xv, 172 p.Google Scholar
Knorr-Cetina, K. Epistemic Cultures: How the Sciences Make Knowledge. Cambridge, MA: Harvard University Press; 1999. xiii, 329 p.CrossRefGoogle Scholar
Fortun, M. Promising Genomics: Iceland and deCODE Genetics in a World of Speculation. Berkeley: University of California Press; 2008.CrossRefGoogle Scholar
Caulfield, T. Spinning the genome: Why science hype matters. Perspectives in Biology and Medicine. 2018;61:560–71.CrossRefGoogle ScholarPubMed
Jacob, CM, Hanson, M. Implications of the Developmental Origins of Health and Disease concept for policy-making. Current Opinion in Endocrine and Metabolic Research. 2020;13:20–7.CrossRefGoogle Scholar
Heeney, C. Problems and promises: How to tell the story of a Genome Wide Association Study? Studies in History and Philosophy of Science Part A. 2021;89:110.CrossRefGoogle ScholarPubMed
Penkler, M. Caring for biosocial complexity. Articulations of the environment in research on the Developmental Origins of Health and Disease. Studies in History and Philosophy of Science. 2022;93:110.CrossRefGoogle ScholarPubMed
Berkowitz, GS, Wolff, MS, Janevic, TM, Holzman, IR, Yehuda, R, Landrigan, PJ. The world trade center disaster and intrauterine growth restriction. JAMA: Journal of the American Medical Association. 2003;290(5):595–6.CrossRefGoogle ScholarPubMed
Engel, SM, Berkowitz, GS, Wolff, MS, Yehuda, R. Psychological trauma associated with the World Trade Center attacks and its effect on pregnancy outcome. Paediatric and Perinatal Epidemiology. 2005;19(5):334–41.CrossRefGoogle ScholarPubMed
Ohlsson, A, Shah, PS, the Knowledge Synthesis Group of Determinants of Preterm LBWb. Effects of the September 11, 2001 disaster on pregnancy outcomes: A systematic review. Acta Obstetricia et Gynecologica Scandinavica. 2011;90(1):618.CrossRefGoogle ScholarPubMed
Wesselink, AK, Wellenius, GA. Impacts of climate change on reproductive, perinatal and paediatric health. Paediatric and Perinatal Epidemiology. 2022;36(1):13.CrossRefGoogle ScholarPubMed
Cao-Lei, L, de Rooij, SR, King, S, Matthews, SG, Metz, GAS, Roseboom, TJ, et al. Prenatal stress and epigenetics. Neuroscience and Biobehavioral Reviews. 2017;117:198210.CrossRefGoogle ScholarPubMed
Derfel, A. Prenatal stress from extreme weather is having negative effect on babies. The Montreal Gazette. 2009 31 Jan;Sect. News.Google Scholar
Forestieri, S, Pintus, R, Marcialis, MA, Pintus, MC, Fanos, V. COVID-19 and developmental origins of health and disease. Early Human Development. 2021;155:105322.CrossRefGoogle ScholarPubMed
Roseboom, TJ, Ozanne, SE, Godfrey, KM, Isasi, CR, Itoh, H, Simmons, R, et al. Unheard, unseen and unprotected: DOHaD council’s call for action to protect the younger generation from the long-term effects of COVID-19. Journal of Developmental Origins of Health and Disease. 2021;12(1):35.CrossRefGoogle ScholarPubMed
Schoenmakers, S, Verweij, EJ, Beijers, R, Bijma, HH, Been, JV, Steegers-Theunissen, RPM, et al. The impact of maternal prenatal stress related to the COVID-19 pandemic during the first 1000 days: A historical perspective. International Journal of Environmental Research and Public Health. 2022;19(8):4710.CrossRefGoogle Scholar
Valdez, N. Weighing the Future: Race, Science, and Pregnancy Trials in the Postgenomic Era. Oakland: University of California Press; 2022. pages cm p.Google Scholar
Murphy, M. The Economization of Life. Durham, NC; London: Duke University Press; 2017. ix, 220 p.Google Scholar
Baedke, J, Nieves Delgado, A. Race and nutrition in the New World: Colonial shadows in the age of epigenetics. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 2019;76:101175.CrossRefGoogle ScholarPubMed
Reiches, M. Reproductive justice and the history of prenatal supplementation: Ethics, birth spacing, and the ‘Priority Infant’ model in The Gambia. Signs: Journal of Women in Culture and Society. 2019;45(1):326.CrossRefGoogle Scholar
Richardson, SS, Stevens, H. Postgenomics: Perspectives on Biology after the Genome. Durham, NC: Duke University Press; 2015. ix, 294 p.Google Scholar
Stevens, H. Networks: Representations and tools in postgenomics. In: Richardson, SS, Stevens, H, editors. Postgenomics: Perspectives on Biology after the Genome. Durham: Duke University Press; 2015. p. 0.Google Scholar
Keller, EF. The Century of the Gene. Cambridge, MA: Harvard University Press; 2000. 186 p.CrossRefGoogle Scholar
Boyle, EA, Li, YI, Pritchard, JK. An expanded view of complex traits: From polygenic to omnigenic. Cell. 2017;169(7):1177–86.CrossRefGoogle ScholarPubMed
Richardson, SS. Maternal bodies in the postgenomic order: Gender and the explanatory landscape of epigenetics. In: Richardson, SS, Stevens, H, editors. Postgenomics: Perspectives on Biology after the Genome. Durham, NC: Duke University Press; 2015. pp. 210–31.Google Scholar
Gage, SH, Munafo, MR, Davey, Smith G. Causal inference in Developmental Origins of Health and Disease (DOHaD) Research. Annual Review Psychology. 2016;67:567–85.CrossRefGoogle ScholarPubMed
Müller, R, Hanson, C, Hanson, M, Penkler, M, Samaras, G, Chiapperino, L, et al. The biosocial genome? EMBO Reports. 2017;18(10):1677–82.CrossRefGoogle ScholarPubMed
Richardson, SS, Daniels, CR, Gillman, MW, Golden, J, Kukla, R, Kuzawa, C, et al. Society: Don’t blame the mothers. Nature. 2014;512(7513):131–2.CrossRefGoogle ScholarPubMed
Figure 0

Figure 13.1 ‘Overview of potential maternal prenatal stressors during the current COVID-19 pandemic as part of the early life course medicine’.

Source: Schoenmakers et al. [42]

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×