Maarten Jan Wensink

The maintenance gap: a new theoretical perspective on the evolution of aging

One of the prevailing theories of aging, the disposable soma theory, views aging as the result of the accumulation of damage through imperfect maintenance. Aging, then, is explained from an evolutionary perspective by asserting that this lack of maintenance exists because the required resources are better invested in reproduction. However, the amount of maintenance necessary to prevent aging, ‘maintenance requirement’ has so far been largely neglected and has certainly not been considered from an evolutionary perspective. To our knowledge we are the first to do so, and arrive at the conclusion that all maintenance requirement needs an evolutionary explanation. Increases in maintenance requirement can only be selected for if these are linked with either higher fecundity or better capabilities to cope with environmental challenges to the integrity of the organism. Several observations are suggestive of the latter kind of trade-off, the existence of which leads to the inevitable conclusion that the level of maintenance requirement is in principle unbound. Even the allocation of all available resources to maintenance could be unable to stop aging in some organisms. This has major implications for our understanding of the aging process on both the evolutionary and the mechanistic level. It means that the expected effect of measures to reallocate resources to maintenance from reproduction may be small in some species. We need to have an idea of how much maintenance is necessary in the first place. Our explorations of how natural selection is expected to act on the maintenance requirement provides the first step in understanding this.

Age-specificity and the evolution of senescence: a discussion.

Senescence evolved because selection pressure declines with age. However, to explain senescence it does not suffice to demonstrate that selection pressure declines. It is also necessary to postulate biological mechanisms that lead to a deteriorated state of the organism at high ages, but not before. This has lead to the invocation of ‘age-specific’ genes or processes, a concept which is prone to be interpreted too freely. Events do not happen after a certain amount of time has passed. They need initiation, which means that senescence is required to be a continuous process. As a result, a change at a particular age cannot arise in isolation from changes at other ages, in particular not in isolation from changes at the ages nearby. These mechanistic constraints are not without consequence for the patterns of mortality and fecundity that can evolve. I conclude that from purely logical considerations, senescence is characterized as continuous rather than age-specific deterioration. These considerations guide (theoretical) research in the direction of investigating how continuous somatic change arises, rather than focusing at age-specific events.

The Rarity of Survival to Old Age Does Not Drive the Evolution of Senescence

The evolution of senescence is often explained by arguing that, in nature, few individuals survive to be old and hence it is evolutionarily unimportant what happens to organisms when they are old. A corollary to this idea is that extrinsically imposed mortality, because it reduces the chance of surviving to be old, favors the evolution of senescence. We show that these ideas, although widespread, are incorrect. Selection leading to senescence does not depend directly on survival to old age, but on the shape of the stable age distribution, and we discuss the implications of this important distinction. We show that the selection gradient on mortality declines with age even in the hypothetical case of zero mortality, when survivorship does not decline. Changing the survivorship function by imposing age independent mortality has no affect on the selection gradients. A similar result exists for optimization models: age independent mortality does not change the optimal result. We propose an alternative, brief explanation for the decline of selection gradients, and hence the evolution of senescence.

No senescence despite declining selection pressure: Hamilton's result in broader perspective

Theory predicts that senescence should inevitably evolve because selection pressure declines with age. Yet, data show that senescence is not a universal phenomenon. How can these observations peacefully coexist? Evolution of any trait hinges on its impact on fitness. A complete mathematical description of change in fitness, the total fitness differential, involves selection pressure along with a perturbation function that describes how the vital rates, mortality and fecundity, are affected across ages. We propose that the perturbation function can be used to model trade-offs when vital rates are perturbed in different directions and magnitude at different ages. We find that for every trade-off we can identify parameter values for which senescence does evolve and others for which it does not. We argue that this reconciles the apparent contradiction between data and theory. The total fitness differential is also instrumental in deriving mathematical relationships between alternative indicators of selection pressure. We show examples and highlight that any indicator combined with the right perturbation function can be used to parameterize a specific biological change. Biological considerations should motivate what perturbation functions are used. We interpret the relevance of Hamiltons finding that selection pressure declines for the evolution of senescence: declining selection pressure is a necessary but not a sufficient condition.

Intrinsic and extrinsic mortality reunited.

Intrinsic and extrinsic mortality are often separated in order to understand and measure aging. Intrinsic mortality is assumed to be a result of aging and to increase over age, whereas extrinsic mortality is assumed to be a result of environmental hazards and be constant over age. However, allegedly intrinsic and extrinsic mortality have an exponentially increasing age pattern in common. Theories of aging assert that a combination of intrinsic and extrinsic stressors underlies the increasing risk of death. Epidemiological and biological data support that the control of intrinsic as well as extrinsic stressors can alleviate the aging process. We argue that aging and death can be better explained by the interaction of intrinsic and extrinsic stressors than by classifying mortality itself as being either intrinsic or extrinsic. Recognition of the tight interaction between intrinsic and extrinsic stressors in the causation of aging leads to the recognition that aging is not inevitable, but malleable through the environment.

Interaction mortality: senescence may have evolved because it increases lifespan.

Given an extrinsic challenge, an organism may die or not depending on how the threat interacts with the organisms physiological state. To date, such interaction mortality has been only a minor factor in theoretical modeling of senescence. We describe a model of interaction mortality that does not involve specific functions, making only modest assumptions. Our model distinguishes explicitly between the physiological state of an organism and potential extrinsic, age-independent threats. The resulting mortality may change with age, depending on whether the organisms state changes with age. We find that depending on the physiological constraints, any outcome, be it ‘no senescence’ or ‘high rate of senescence’, can be found in any environment; that the highest optimal rate of senescence emerges for an intermediate physiological constraint, i.e. intermediate strength of trade-off; and that the optimal rate of senescence as a function of the environment is driven by the way the environment changes the effect of the organisms state on mortality. We conclude that knowledge about the environment, physiology and their interaction is necessary before reasonable predictions about the evolution of senescence can be made.

The causal pie model: an epidemiological method applied to evolutionary biology and ecology.

A general concept for thinking about causality facilitates swift comprehension of results, and the vocabulary that belongs to the concept is instrumental in cross-disciplinary communication. The causal pie model has fulfilled this role in epidemiology and could be of similar value in evolutionary biology and ecology. In the causal pie model, outcomes result from sufficient causes. Each sufficient cause is made up of a “causal pie” of “component causes”. Several different causal pies may exist for the same outcome. If and only if all component causes of a sufficient cause are present, that is, a causal pie is complete, does the outcome occur. The effect of a component cause hence depends on the presence of the other component causes that constitute some causal pie. Because all component causes are equally and fully causative for the outcome, the sum of causes for some outcome exceeds 100%. The causal pie model provides a way of thinking that maps into a number of recurrent themes in evolutionary biology and ecology: It charts when component causes have an effect and are subject to natural selection, and how component causes affect selection on other component causes; which partitions of outcomes with respect to causes are feasible and useful; and how to view the composition of a(n apparently homogeneous) population. The diversity of specific results that is directly understood from the causal pie model is a test for both the validity and the applicability of the model. The causal pie model provides a common language in which results across disciplines can be communicated and serves as a template along which future causal analyses can be made.

Size, longevity and cancer: age structure

There is significant recent interest in Petos paradox and the related problem of the evolution of large, long-lived organisms in terms of cancer robustness. Petos paradox refers to the expectation that large, long-lived organisms have a higher lifetime cancer risk, which is not the case: a paradox. This paradox, however, is circular: large, long-lived organisms are large and long-lived because they are cancer robust. Lifetime risk, meanwhile, depends on the age distributions of both cancer and competing risks: if cancer strikes before competing risks, then lifetime risk is high; if not, not. Because no set of competing risks is generally prevalent, it is instructive to temporarily dispose of competing risks and investigate the pure age dynamics of cancer under the multistage model of carcinogenesis. In addition to augmenting earlier results, I show that in terms of cancer-free lifespan large organisms reap greater benefits from an increase in cellular cancer robustness than smaller organisms. Conversely, a higher cellular cancer robustness renders cancer-free lifespan more resilient to an increase in size. This interaction may be an important driver of the evolution of large, cancer-robust organisms.