Commentary: Developing the future: life course epidemiology, DOHaD and evolutionary medicine Free

In advancing new concepts in science, it is often wise to be one’s own harshest critic, and this is the position that Ben-Shlomo et al. have taken in their comprehensive review¹ of the recent history and the potential of life course epidemiology, a concept of which they were leading architects. In closing their review, they rehearse the criticism, apparently posed by an eminent colleague, that the data and analytical demands necessary to test the underlying concepts of life course epidemiology just may not be available: Ben-Shlomo et al.’s survey of the state of the art makes it clear that the detailed phenotyping of individuals in several ongoing large cohorts, and marrying epidemiology with other disciplines, may address this issue, providing as they say a ‘feast’ of data since the 1990s. We agree, although the necessity of starting the life course analysis for one generation with phenotypic data for the previous one demands that recruitment starts before conception and ideally extends to the next generation as well. It also needs to be supported by careful documentation of exposures and the molecular phenotype, as there is now overwhelming evidence that subtle environmental influences in early development can have long-lasting effects on both the epigenotype and the physiological phenotype that emerge.^2,3 Few current cohorts have adopted this approach, although it can be tackled if the current, more detailed birth cohorts are maintained into their reproductive years and beyond. The life course approach needs to encapsulate the human life cycle as well as taking the longer view that understanding ageing demands.

A focus of Ben-Shlomo et al.’s review is a discussion of the concordance between concepts in life course epidemiology and the emergent field of developmental origins of health and disease (DOHaD); this was known as fetal origins of adult disease until 2003, when it was apparent that the processes underlying risk of later disease can operate in the embryo and continue through child development and beyond, and that such processes influence long-term health as well as disease well before adulthood.

Importantly, the focus has shifted from looking solely at developmental factors predisposing to disease to those promoting health and resilience. This inevitably led to incorporation of evolutionary concepts into the public health and medical paradigms, in particular recognizing the significance of developmental plasticity. This led to the recognition that there are multiple pathways by which early developmental factors affect later disease risk, some being protective mechanisms evolved to increase likelihood of survival to reproduction (i.e. evolutionarily adaptive mechanisms which have been termed PARs⁴). These themselves need not induce a greater disease risk; indeed in some circumstances they can lead to greater resilience. In the context of the contemporary world, however, where a ‘mismatch’ between the predicted and actual post-infant environments is likely, many children are potentially at greater risk of ill health in later life.⁵ This developmental ‘mismatch’⁶ underlines the importance of ecological interactions across the life course—something also emphasized by Ben Shlomo et al. A challenge for life course epidemiology is the growing evidence that developmental environments need only change subtly to affect later biology. For example, variations in maternal diet and fetal growth within the normal range for a Western population can produce long-term effects on health.^5,7–9

In addition, fetuses and infants now face an increasing number of evolutionarily novel environments such as maternal obesity, environmental toxins, gestational diabetes and infant overfeeding, which impact during a critical window of plasticity and can have long-term consequences. These cannot be framed in an evolutionary sense but may co-opt evolved mechanisms, with adverse consequences.¹⁰ The science of both adaptive and maladaptive developmental plasticity has become central to understanding both life course biology and DOHaD. It is now clear that components of the epigenome can be influenced in early life with lifelong effects.^2,11–15 Further challenges to both biological and epidemiological investigation come from the evidence that components of the environmentally-sensitive paternal epigenome can pass meiosis, and for grand-maternal effects mediated via the oocyte when the mother herself is an embryo. Evolutionary biology concepts are increasingly applied to the life course, especially the relationship between life history traits, ecological factors and the life history itself. Life history theory¹⁶ may offer additional theoretical elements for explaining life course phenomena.

An important impetus mechanistically was derived from linking DOHaD to the interface between evolutionary and developmental biology.^17–19 One of the most important examples of this convergence in thinking is that developmental biology emphasizes that plasticity, in response to signals from the environment operating across the ecological range, contributes more substantially than do fixed genetic processes to the variation in phenotype. The contribution of developmental plasticity to the reaction norm which forms the substrate on which selection acts is thus very important. The mechanistic insights from the explosion of studies in developmental epigenetics have led to a new level of understanding. In concert with this, epidemiological studies now reveal how processes influencing life course health as well as disease risk operate across the entire normal range of development, not only with ‘sub-optimal development’. Along with Ben-Shlomo et al., we would celebrate a new era of human physiology arising from the alliance between life course epidemiology and DOHaD mechanistic investigations.

In addition to development, life history theory has also led to an increasingly robust set of evolutionary explanations regarding ageing.²⁰ It makes the important distinction between extrinsic and intrinsic causes of mortality. Greater consideration needs to be given to distinguishing between how developmental factors influence intrinsic mechanisms versus those factors that influence risk of extrinsic mortality induced through infectious or lifestyle and ecological factors. Life course epidemiological studies still do not distinguish between markers of pathophysiology, for example with ageing and associated with disease, and those of physiological function. Such thinking may allow for even greater convergence between these schools of thought.

Ben-Shlomo et al. are right, in our view, to question the use of the deterministic term ‘programming’ in relation to DOHaD, although the ballistic connotations of ‘trajectory’, which is widely used in life course studies, may suffer from similar limitations if it suggests a predetermined target which influences the direction of travel and the impetus imparted to an object. The importance of the early life environment, and the consequences of the developing individual’s responses to it, have been recognized since the time of Hippocrates. Seminal scientific studies were conducted in the early part of the past century upon which the work of Barker and many colleagues and other groups built.⁵ But one of the reasons why the investigation of fundamental biological mechanisms underlying these epidemiological observations has been slow was the excessive emphasis on birthweight as a measure of the nature of developmental environment, whereas it is now clear that very subtle developmental exposures that do not overtly influence the birth phenotype can have longer-term consequences. Whether or not ‘biomarkers’ such as birthweight lie on the causal pathway to later risk, there is always the problem that epidemiological or other observational studies will yield data on correlation rather than causation; the ‘omics revolution to which Ben-Shlomo et al. refer may deepen the level of observation but will not necessarily address the question of causation.

As physiologists, though, we insist on having accurate measures of the exposure as well as of the response of the individual. It is tempting to read Ben-Shlomo et al.’s review of the contribution to life course epidemiology to the generation of ‘trajectories of functional phenotypes’ in these terms, although it is not always clear that this is the case. Even if we focus on the ageing component of the life course, we cannot rule out the possibility that some forms of plasticity still operate⁸—for example, there is a growing interest in the role of stem cells in determining intrinsic rates of ageing.²¹

There is a danger of confusing the evolutionary and physiological meanings of adaptation.¹⁹ Phenotypic changes may be physiologically adaptive even if they cannot strictly be termed evolutionary adaptations (other than perhaps via a small component of ‘grandmother’ effect).²² Ben-Shlomo et al. refer to the complex interactions of many processes, on a homeostatic time- scale as well as across the life course. They would include cellular metabolic sensing, inflammation, endocrine factors such as IGF-1 and changes in body composition, to name only some of the mechanisms, many underpinned by a range of epigenetic processes. These interactions may be actively regulated differentially from the well-known markers of decline such as telomere length.²³ Ben-Shlomo et al. rightly point out that some markers of function, such as blood pressure, may be useful clinically but cannot elucidate changes in the balance of underlying processes, such as cardiac function, vascular structure or autonomic control, occurring across the life course.

Pursuing this theme, there are two concepts that arguably have now arisen from the growing congruence of current research in developmental plasticity, life course epidemiology and DOHaD. The first relates to the need to measure responses to brief, clearly defined challenges as an index of where an individual lies on the life course pathway for an organ or system. This is classical physiological thinking and, as Ben-Shlomo et al. point out, is demonstrated by the use of the glucose tolerance test or a measure of neurocognitive function such as a short-term memory challenge. As these are dynamic tests, they cannot be represented simply on a plot of level of risk for a particular condition such as diabetes or cognitive impairment versus age: rather, they have to be viewed as tangents to such a plot. This goes beyond the accumulation of risk/damage model of ageing, as Ben-Shlomo et al. indicate: but it is also a refinement of the path-dependency model, which is not usually appreciated, because the interaction between dynamic and static sensitivity to a change in stimulus is complicated and non-linear for many physiological systems.

The second concept relates to what Ben-Shlomo et al. call ‘compensatory reserve’, the ability to recover from adverse exposures. In their Figure 5, they visualize this in terms of physiological function building from zero at birth to a plateau in mid life and then declining during ageing. It is questionable whether any single quantity can capture the range of physiological responses to challenges across the life course: for example, neonates have an extraordinary ability to survive severe challenges, such as starvation or hypothermia, and thus have a high degree of physiological function and ‘compensatory reserve’. A further complication and limitation is that evolutionary arguments and empirical evidence both suggest that the response to any developmental challenge within a window of plasticity comprises an integrated phenotypic response involving multiple systems—this involves a number of developmental trade-offs to ensure a greater likelihood of survival and reproductive success.²⁴ Indeed, different cues can lead to very similar phenotypic consequences. Thus to study individual characteristics in isolation may be misleading.

In applying life course concepts to public health, we favour the term ‘good healthcare permit capital’^25,26 as this makes it easier to show how good health during the reproductive period passes a healthy start to life on to the next generation, and how healthy behaviours, living in a healthy environment and in a society with good health care permit capital to be accumulated over the life course, inevitably to be spent to an extent during ageing, with the caveat that we need to be clear about the distinction between effects on intrinsic ageing processes and extrinsic causes of mortality. We only have to note the poorly understood but enormous differences in life expectancy (∼ 15 years) associated with the season of birth in the Gambia, where there is seasonal famine, but which do not appear until the third decade of life,²⁷ to appreciate the need for sophisticated studies that link biomedical, evolutionary and epidemiological perspectives. The extension of these ideas to the reduction in the prevalence of non-communicable diseases globally, which is one of the prerequisites for attaining the Sustainable Development Goals²⁸ will be important. As Ben-Shlomo et al. conclude, interdisciplinary research involving life course epidemiology, mechanistic biomedical science and evolutionary and developmental biology should be a fertile field for future research, and one which needs to be pursued urgently.

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