Could aging evolve as a pathogen control strategy?

Aging clocks based on accumulating stochastic variation

Aging clocks have provided one of the most important recent breakthroughs in the biology of aging, and may provide indicators for the effectiveness of interventions in the aging process and preventive treatments for age-related diseases. The reproducibility of accurate aging clocks has reinvigorated the debate on whether a programmed process underlies aging. Here we show that accumulating stochastic variation in purely simulated data is sufficient to build aging clocks, and that first-generation and second-generation aging clocks are compatible with the accumulation of stochastic variation in DNA methylation or transcriptomic data. We find that accumulating stochastic variation is sufficient to predict chronological and biological age, indicated by significant prediction differences in smoking, calorie restriction, heterochronic parabiosis and partial reprogramming. Although our simulations may not explicitly rule out a programmed aging process, our results suggest that stochastically accumulating changes in any set of data that have a ground state at age zero are sufficient for generating aging clocks.

A general framework for modelling trade-offs in adaptive behaviour

An animal's behaviour can influence many variables, such as its energy reserves, its risk of injury or mortality, and its rate of reproduction. To identify the optimal action in a given situation, these various effects can be compared in the common currency of reproductive value. While this idea has been widely used to study trade-offs between pairs of variables, e.g. between energy gain versus survival, here we present a unified framework that makes explicit how these various trade-offs fit together. This unification covers a wide range of biological phenomena, highlighting similarities in their logical structure and helping to identify knowledge gaps. To fill one such gap, we present a new model of foraging under the risk of predation and damage accumulation. We conclude by discussing the use and limitations of state-dependent optimisation theory in predicting biological observations.

Exploring Patterns of Human Mortality and Aging: A Reliability Theory Viewpoint

The most important manifestation of aging is an increased risk of death with advancing age, a mortality pattern characterized by empirical regularities known as mortality laws. We highlight three significant ones: the Gompertz law, compensation effect of mortality (CEM), and late-life mortality deceleration and describe new developments in this area. It is predicted that CEM should result in declining relative variability of mortality at older ages. The quiescent phase hypothesis of negligible actuarial aging at younger adult ages is tested and refuted by analyzing mortality of the most recent birth cohorts. To comprehend the aging mechanisms, it is crucial to explain the observed empirical mortality patterns. As an illustrative example of data-directed modeling and the insights it provides, we briefly describe two different reliability models applied to human mortality patterns. The explanation of aging using a reliability theory approach aligns with evolutionary theories of aging, including idea of chronic phenoptosis. This alignment stems from their focus on elucidating the process of organismal deterioration itself, rather than addressing the reasons why organisms are not designed for perpetual existence. This article is a part of a special issue of the journal that commemorates the legacy of the eminent Russian scientist Vladimir Petrovich Skulachev (1935-2023) and his bold ideas about evolution of biological aging and phenoptosis.

Putting zoo animal cancer into perspective

As part of a comparative research agenda that promises insights that help extend the human lifespan and combat cancer, cancer prevalence in zoo animals has received recent attention. Here, we want to draw attention to a principle of cancer research that was introduced into the zoo world as early on as 1933, but that seems to have gone somewhat forgotten: Cancer is mainly a disease of old age, and therefore studies aiming at identifying taxa that are particularly susceptible or resistant to cancer must control for whether the respective zoo populations are 'old.' In a comparative context, 'old age' cannot be measured in absolute terms (e.g., years), but only in relation to a species' maximum lifespan: Species that achieve, across zoos, a higher mean lifespan as a percent of their maximum lifespan are 'older.' When applying this metric to former as well as more recently published data on cancer prevalence, it appears that those species that become relatively old in zoos-in particular, the carnivores-have a relatively high cancer prevalence. Any improvement in animal husbandry-which reduces premature deaths-should, by default, lead to more cancer. Cancer in zoo animals, like any other old-age condition, might therefore be embraced as a proxy for good husbandry. Rather than following a sensationalist approach that dramatizes disease and death per se, zoos should be clear about what their husbandry goals are, what relative longevities they want to achieve for which species, and what old-age diseases they should therefore expect: in the end, one has to die of something.

Somatic mutation as an explanation for epigenetic aging

DNA methylation marks have recently been used to build models known as "epigenetic clocks" which predict calendar age. As methylation of cytosine promotes C-to-T mutations, we hypothesized that the methylation changes observed with age should reflect the accrual of somatic mutations, and the two should yield analogous aging estimates. In analysis of multimodal data from 9,331 human individuals, we find that CpG mutations indeed coincide with changes in methylation, not only at the mutated site but also with pervasive remodeling of the methylome out to ±10 kilobases. This one-to-many mapping enables mutation-based predictions of age that agree with epigenetic clocks, including which individuals are aging faster or slower than expected. Moreover, genomic loci where mutations accumulate with age also tend to have methylation patterns that are especially predictive of age. These results suggest a close coupling between the accumulation of sporadic somatic mutations and the widespread changes in methylation observed over the course of life.

Is Aging an Inevitable Characteristic of Organic Life or an Evolutionary Adaptation?

Aging is an evolutionary paradox. Several hypotheses have been proposed to explain it, but none fully explains all the biochemical and ecologic data accumulated over decades of research. We suggest that senescence is a primitive immune strategy which acts to protect an individual's kin from chronic infections. Older organisms are exposed to pathogens for a longer period of time and have a higher likelihood of acquiring infectious diseases. Accordingly, the parasitic load in aged individuals is higher than in younger ones. Given that the probability of pathogen transmission is higher within the kin, the inclusive fitness cost of infection might exceed the benefit of living longer. In this case, programmed lifespan termination might be an evolutionarily stable strategy. Here, we discuss the classical evolutionary hypotheses of aging and compare them with the pathogen control hypothesis, discuss the consistency of these hypotheses with existing empirical data, and present a revised conceptual framework to understand the evolution of aging.