Abstract
It is well established that individuals age differently. Yet the nature of these inter-individual differences is still largely unknown. For humans, two main hypotheses have been recently formulated: individuals may experience differences in aging rate or aging timing. This issue is central because it directly influences predictions for human lifespan and provides strong insights into the biological determinants of aging. In this article, we propose a model which lets population heterogeneity emerge from an evolutionary algorithm. We find that whether individuals differ in (i) aging rate or (ii) timing leads to different emerging population heterogeneity. Yet, in both cases, the same mortality patterns are observed at the population level. These patterns qualitatively reproduce those of yeasts, flies, worms and humans. Such findings, supported by an extensive parameter exploration, suggest that mortality patterns across species and their potential shapes belong to a limited and robust set of possible curves. In addition, we use our model to shed light on the notion of subpopulations, link population heterogeneity with the experimental results of stress induction experiments and provide predictions about the expected mortality patterns. As biology is moving towards the study of the distribution of individual-based measures, the model and framework we propose here paves the way for evolutionary interpretations of empirical and experimental data linking the individual level to the population level.
Highlights
Aging can be generally defined as age-related changes in a set of variables, from growth rate to reproductive effort, which influence the fitness of an organism
We study the evolution of mortality patterns to investigate the nature of inter-individual differences in aging
Biodemographic studies of aging have shown that specific population heterogeneity can reproduce the main features of qualitatively different mortality patterns, such as late-age mortality plateaus [18,19]. These studies make ad-hoc assumptions about (i) population heterogeneity, e.g., a Gamma distribution, and (ii) the nature of inter-individual differences in aging. We address these issues in the light of evolution, we do not assume a specific population heterogeneity and we explore different types of interindividual differences in aging
Summary
Aging can be generally defined as age-related changes in a set of variables, from growth rate to reproductive effort, which influence the fitness of an organism. Since Gompertz’ seminal work on human data [4], such mortality curves have been obtained for a large variety of species [7], in a broad range of environmental conditions (e.g., [8,9]) These curves play a central role in understanding aging processes and predicting the dynamics of population growth and human life expectancy [10,11]. Agespecific mortality curves allow the comparison of aging processes between species as the same measure can be applied from unicellular organisms to humans, as long as the death of the individual is clearly defined. All of these contribute to make changes in mortality over age a well-accepted definition of aging from the demographic perspective. We study the evolution of mortality patterns to investigate the nature of inter-individual differences in aging
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