Senescence is defined as a decrease in physiological function with age, manifested in population statistics as an increasing probability of mortality and decreasing reproductive success. Organisms wear out, just like machines. Macromolecules, including proteins, lipids and DNA, sustain damage from oxidation and other biochemical changes. Cells die and are not replaced. Tissues accumulate deposits of metabolites that impair function. Eventually, these changes can cause a breakdown of the life system and bring life to an end. Humans are acutely aware of their own mortality and are obsessed with finding ways to extend both the length of life and its quality. These goals have profound implications for the structure and economy of human society. Thus, it is understandable that so much effort has been devoted to understanding the process of ageing and devising interventions to reduce its consequences. Although considerable research has focused on ageing in humans, this effort also depends to a large extent on experimental investigations of other species, particularly so-called ‘animal models’, under the assumption that the causes of ageing can be generalized across very different kinds of organisms.
Animal models, which include the roundworm Caenorhabdites elegans, the fruit fly Drosophila melanogaster, and the laboratory mouse, are easy to maintain in the laboratory and have well-known genetics, development, physiology and biochemistry. Recently, however, many biologists have come to understand that variation in potential life span among species in nature might also hold clues to the regulation of ageing. This variation presumably reflects the influence of biological mechanisms that are subject to selection and that evolve in response to variations in the environment. Evolutionary changes in biological controls on ageing might suggest potential therapeutic interventions to extend the quality and length of human life.
In this article, I comment on how research on animal models and species in nature has elucidated changes that occur in the ageing organism, discuss some limitations of animal models, and show how comparative analyses of the demography of ageing in natural populations provide insight into the nature of senescence.
the causes of ageing
Senescence and ageing, which I shall use more or less interchangeably, have a long history in biological research (see Monaghan et al. 2008). Evolutionary biologists and ecologists have been interested primarily in why organisms age. Accepted wisdom maintains that the strength of selection on deleterious effects of alleles decreases with age in most populations, as fewer individuals remain alive to express these genes (Hamilton 1966; Baudisch 2008). This allows deleterious mutations with late expression to accumulate in a population, and also maintains pleiotropic genes whose positive effects at young ages outweigh negative effects later in life (Williams 1957; Rose 1991; Kirkwood 2002). Given the general and pervasive nature of the selective influences that mould patterns of ageing, we should expect a variety of underlying causes of ageing to have evolved. Variation at any gene locus that influences expected longevity potentially could affect age-related changes in organism function.
That the rate of ageing has a genetic basis was well established by quantitative genetic analyses and selection experiments (Rose 1984, 1991; Partridge & Barton 1993) before studies on animal models began to reveal numerous effects on life span of single gene mutations (Kenyon et al. 1993). Many of these mutations affect the insulin/insulin-like growth factor-1 (IGF-1) pathway that occurs in all animals, indicating a potential common basis for patterns of ageing (Clancy et al. 2001; Kenyon 2005; Selman et al. 2008). Moreover, it should not be surprising, and indeed it is reassuring, that many life-extending mutations appear to improve health at older age, as well, as shown in mice, for example, by Selman et al. (2008). However, the kinds of genes that are responsible for differences in life span between species are not known, although many populations have been shown to hold substantial genetic variation for length of life.
Twin studies and quantitative genetic analyses suggest that about one-quarter of the variance in the human life span in developed countries is due to genetic factors (Cournil & Kirkwood 2001). Studies on the heritability of life span in natural populations have yielded conflicting results, but reveal generally lower estimates owing to the larger environmental component of variance in life span in nature. Quantitative genetic analyses and quantitative trait locus (QTL) mapping might eventually provide details concerning the number of genes involved and identify their specific actions (Wilson et al. 2008). Potentially many genetic factors are important and they might affect life span through a number of pathways. Analyses of life-history trade-offs suggest that mechanisms that improve resistance to stress, such as the expression of heat shock proteins and detoxification systems, might have life-extending effects (Ogburn et al. 1998, 2001; Kapahi, Boulton & Kirkwood 1999; Fabrizio et al. 2001; Zera & Harshman 2001; Lithgow & Walker 2002; McElwee et al. 2004; Amador-Noguez et al. 2007; Gems & Partridge 2008).
experimental studies on ageing
Because humans are so concerned with length of life, much of our attention has focused on factors that extend life span. Genetic factors and interventions that push back senescent decline and death, irrespective of their consequences for the individual during its life, have been prominent in ageing research. Increasingly, however, the goal of research is to extend healthy life span, and it is becoming clear that prolonged life and good health might go together (Selman et al. 2008).
Oxidative damage is a strong candidate for ageing-related changes in individuals (Stadtman 1992; Hamilton et al. 2001; Kujoth et al. 2007), and it is not surprising that organisms have evolved mechanisms to counter these effects. Curbing the production of ROS in the mitochondria by decoupling oxidative phosphorylation (Balaban, Nemoto & Finkel 2005) results in reduced efficiency in producing ATP and increased overall metabolism (energy requirement) (Serra et al. 2003; Speakman et al. 2004; Selman et al. 2005). Other trade-offs apply to energy production. For example, higher cell metabolism is correlated with higher proportions of polyunsaturated phospholipids in membranes, which increase both membrane fluidity and susceptibility to oxidative damage (Pamplona et al. 2004).
Telomeres are regions of highly repetitive DNA that cap the ends of chromosomes (see Vleck, Haussmann & Vleck 2003, this issue). Because some DNA is lost at the ends of chromosomes with each replication cycle, having non-coding sequences (telomeres) at the ends enables cell lines to undergo repeated replication. When the length of a telomere declines to a certain point, the DNA can no longer replicate, and chromosomes sometimes break or join end to end (Capper et al. 2007), which impairs cell function. Such senescent cells might undergo apoptosis and be removed from the cell population (Finkel, Serrano & Blasco 2007). However, the end of cell division signals a decline in tissue repair and cell replacement that might contribute to the ageing process. The enzyme telomerase can extend telomere length and maintain the proliferation capacity of cell lines, as occurs in the germ line. Comparative studies have observed a correlation between the potential longevity of individuals and maintenance of telomere length (Haussmann, Vleck & Nisbet 2003), to the point that average telomere length in the red blood cells of some long-lived seabird populations remains unchanged with age, likely because telomeres are maintained by telomerase activity (Haussmann et al. 2007).
Telomere length is associated with length of life within populations of the roundworm C. elegans (Joeng et al. 2004), suggesting a potential therapeutic intervention, although experimental increase in telomerase activity in mice increases the rate of tumour formation, as well (Gonzalez-Suarez et al. 2001; Artandi et al. 2002). Indeed, several investigators have suggested a direct trade-off between the proliferation capacity of tissues, which tend to reduce ageing and tumour formation, which represents the uncontrolled proliferation of cells (Finkel et al. 2007). When telomeres decrease below a certain length, the genome tends to become unstable. Normally, such senescent cells die and are removed in the normal course of the ageing process. However, oncogenes appear to block autophagy (Finkel et al. 2007), which could lead to increasing populations of cells with unstable genomes. This mechanism provides the basis for an inverse relationship between rate of ageing and cancer formation – one of the trade-offs that presumably is optimized with respect to the evolution of potential life span.
Kirkwood's idea of the disposable soma (see Monaghan et al. 2008) suggests that delaying senescence has costs, and that the evolution of mechanisms that prevent damage to the organism, or repair it, must balance potential benefits against these costs. For example, the production of ROS, which play a role in cellular ageing, can be balanced to some extent by the maintenance of mechanisms to counteract ROS, such as antioxidants (Finkel & Holbrook 2000; Sohal et al. 2002). However, these mechanisms presumably require energy and nutrient allocation, and potentially interfere with the roles of ROS as signalling molecules and in defences against pathogens (Konjufca et al. 2004; McGraw & Ardia 2007).
ageing in model systems
In spite of the strong effects of certain gene loci on life span (Bartke et al. 2001), the mechanisms by which these genes influence ageing can be extremely complex. For example, daf-2 mutants impact a cascade of genetic interactions and gene products, some of which appear to promote longevity while others appear to reduce life span. For example, Dong et al. (2007) recently identified 47 proteins with higher abundance in daf-2 mutants of C. elegans and 39 proteins with reduced abundance. RNA interference (RNAi) in the activity of seven of the genes responsible for producing these proteins influenced life span in every case, but not in the expected directions. When individual proteins that increased in daf-2 mutants with longer life spans were blocked, life span increased slightly, and vice versa. Thus, these proteins could not individually have been responsible for life extension.
Most importantly, interpreting genetic effects on rate of ageing and life span requires an understanding of the evolutionary and environmental context of the experimental systems (Austad 1993a; Austad & Podlutsky 2006). Studies of the effects of individual gene loci on ageing and life span have been possible only in laboratory populations of animals with well-known genetics that are amenable to genetic and other manipulations. Typically, these organisms – yeast, C. elegans, D. melanogaster, laboratory mice – are easy to culture on defined media and foods, and they have short life spans and high fecundity. Their life histories also differ from humans and other large mammals and birds in a number of ways that bring into question the applicability of these model organisms to understanding ageing more generally.
Life span evolves in the context of the life history of the organism. Thus, different life histories might engage different mechanisms to influence life span, in which case results for one type of organism might not be generalizable. We should ask whether D. melanogaster and C. elegans, for example, are suitable models for understanding human ageing. Although these species share conserved longevity mechanisms with mice (McElwee et al. 2007), uncertainties about the genes responsible for differences in longevity between these species and differences in the life histories of model organisms make it difficult to draw general conclusions.
Humans, as well as most large mammals and birds, are characterized by growth to a characteristic size, repeated reproduction over many years, lack of resting stages, and continued proliferation of cells in the course of tissue function, maintenance, and repair. Other organisms have fundamentally different life histories, and therefore different contexts under which life span evolves. For example, plants exhibit continuous meristematic growth, in which case the distinction between the germ line and the soma is blurred and ageing-related damage to proliferating cells can be sorted out by clonal selection, as in single-celled organisms such as yeast (Petit & Hampe 2006). It is not surprising therefore that some plants can achieve ages of thousands of years (Lanner & Connor 2001; Larson 2001; Flanary & Kletetschka 2005). Other plants and many insects have annual life cycles in which the individual suffers an inevitable death at the end of the growing season, allowing the evolution of a programmed senescence in which resources are allocated preferentially to reproduction rather than continued life (Gan 2007).
Water fleas (Cladocera) alternate phases of parthenogenetic (asexual or clonal) and sexual reproduction (Dudycha 2001). Many vertebrates, including fish and turtles, increase in size with age. As a result of their increasing fecundity with age and size, selection to postpone senescence remains strong late into life (Baudisch 2005, 2008), and many long-lived species show little evidence of ageing-related decline in performance (Congdon et al. 2001, 2003; Coulson & Fairweather 2001; Nisbet, Apanius & Friar 2002). Flies (e.g. Drosophila) undergo complete metamorphosis, which separates aspects of larval and adult life, with unknown consequences for the evolution of ageing. The roundworm C. elegans, which is one of the workhorses of ageing research, is unusual in having a completely post-mitotic adult life – lacking tissue regeneration by cell proliferation – and a resting, or dauer, stage in which cell metabolism is reduced and the individual enters a state of ‘suspended animation’ (Kenyon 1988; Riddle 1988). Even the more typical mammals used in ageing research – laboratory mice and rats, for example – are unusual in having been selected for high fecundity, rapid development and short generation time (Miller et al. 2002). In addition, laboratory strains of mice typically are highly inbred and genetically uniform, which is advantageous for genetic analysis and experimentation, but presents a highly atypical background for life span manipulation.
How do these ‘complications’ colour evolutionary interpretations of variation in life span? Does life extension under laboratory conditions inform us about potential interventions under ‘natural’ conditions, or are responses specific to laboratory environments as well as to organisms? A couple of examples illustrate the potential difficulties of relating studies on animal models to evolution of life span more generally, particularly in mammals and birds. Linnen, Tatar & Promislow (2001) examined the age-specific patterns of mortality in wild and laboratory strains of D. melanogaster. Wild Drosophila brought into the laboratory showed a typical exponential increase in mortality rate with age. Experimental strains kept in culture for hundreds of generations showed the same pattern, only with elevated mortality at each age compared to the wild flies. That is, the laboratory strains had shorter life spans. However, while selection on life span in the laboratory strains registered impressive gains in the length of life, the age-specific mortality rates merely decreased to the levels observed in wild-caught flies, and no further. Thus, selection can improve life span, but might only be effective in removing genetic factors incorporated in laboratory strains selected for short development time and rapid early reproduction. It is not clear that life span can be extended beyond that in natural populations.
Van Voorhies, Fuchs & Vleck (2005) demonstrated that C. elegans likes agar, the typical laboratory medium, better than natural soil. Life span on agar was considerably longer than on a substrate of natural soil, pasteurized soil or acid-washed pasteurized sand when grown in the laboratory. As we have seen, daf-2 mutants live about twice as long as wild-type individuals on agar. However, on both soil and sand, the life span of daf-2 mutants was reduced rather than extended. Thus, the influence of daf-2 on ageing depends dramatically on the environment. It is unclear what generalized lessons about ageing in natural populations can be learned from gene effects in the C. elegans system.