Encyclopedia of Gerontology and Population Aging

Living Edition
| Editors: Danan Gu, Matthew E. Dupre

Aging Theories

  • Alexey M. OlovnikovEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-69892-2_32-1



Aging theories explain nature of aging as the age-related deterioration of structures and functions of a body owing to the passive accumulation of random errors (stochastic theories of aging) or as the active and nonrandom process (theories of programmed aging).


In spite of the current progress in deciphering various aspects of aging, including telomere shortening, epigenetic changes, mitochondrial dysfunction, stem cell exhaustion, etc., the central issue – why aging exists and what is its mechanism – remains the greatest unanswered problem of biology.

In the biology of aging, two terms describing age-related changes in animals are widely used: aging and senescence. Sometimes, they are used as synonyms, but here, they will be applied only in the following, fundamentally different meanings. Aging is a process of the age-related progressive decline of functions that begins after complete physiological maturation of the organism and leads to a growing hazard of death with increasing chronological age. Senescence is a state of a senescent cell that distinguishes it from cells of the same differentiation. Senescent cells are accumulated with the organismal aging, though they also appear and disappear as obligatory participants of normal development. Making this distinction is important because the driving forces of organismal aging and cellular senescence may not be identical.

There are many theories aimed to explain the nature of aging, and there are different systems of their classification (Medvedev 1990; Trindade et al. 2013; Libertini 2015a). However, all theories of aging can be subdivided into two principally distinct categories: stochastic theories of aging (passive accumulation of random errors or “wear and tear” of a body) and theories of programmed aging (aging as an active and nonrandom process).

Currently, after a century of research, the dispute still persists: whether aging is an active and possibly adaptive, at the supra-individual level, or it is passive and nonadaptive.

Key Findings

Aging theories can be subdivided into two groups – theories of stochastic aging and theories of programmed aging.

Theories of Stochastic Aging

The somatic mutation theories of aging belong to the group of stochastic theories, i.e., non-programmed aging theories since mutations are random damages (Medawar 1952; Szilard 1959). Gerontological ideas of Szilard’s mutation theory and Orgel’s model of protein error catastrophe were combined in a new catastrophe model of aging, in which proteins were replaced with DNA as an agent of the positive feedback loop (Milholland et al. 2017). The age-related exponential increase of mortality has been explained by an exponential accumulation of mutations supposedly appearing in genomes after spontaneous somatic mutations in genes of the DNA replication and repair systems.

Several overlapping stochastic theories of aging consider such processes as cross-linking of macromolecules, glycation, damage by free radicals, etc., and all postulate the accumulation of errors reducing the functionality of cells. The most known theory among them is the free radical theory by Harman (Harman 1956, 2009). Many works have come out with the support or criticism of this theory and its modifications (Pomatto and Davies 2018). Free radicals and related oxidants, mostly generated in mitochondria, are, according to this group of theories, the “usual suspects” in the aging process. However, high doses of antioxidants in experiments and clinic do not produce curable effects on aging and age-associated diseases (Viña et al. 2018). Instead, a role for mitochondrial reactive oxygen species (ROS) as intracellular regulatory messengers has been identified (Theurey and Pizzo 2018). The free radical theory has played an important role in the science of aging, but experiments aimed at its verifying did not bring explicit support. In any case, since mitochondria integrate cellular bioenergetics and homeostasis by quality control processes, age-related decline in activity of these organelles should be explained by any future theory of aging.

Cell damage can occur not only because of ROS but also owing to many metabolites that are intrinsically unstable and reactive and hence prone to cause various nonenzymatic damages. Recently, it was even suggested that the side reactions of reactive metabolites could impose a constraint on the biological evolution, due to spontaneous modifications of slowly renewable macromolecules (Golubev et al. 2018). Accumulation of spontaneously polymerized materials and the occasional modifications in the long-lasting structures are considered as a sufficient cause explaining the aging process (Golubev et al. 2017).

Among the non-programmed theories that seek to explain aging from an evolutionary perspective, two theories are central: antagonistic pleiotropy theory (Williams 1957) and disposable soma theory (Kirkwood 1977). These stochastic theories are based on Medawar’s mutation-accumulation theory, according to which expression of deleterious mutations is dangerous mostly after a certain age (Medawar 1952). Medawar suggested that the force of natural selection in the wild falls with the increasing chronological age because of unavoidable environmental risks. Over time, these risks eliminate from further breeding those individuals who successfully produced offspring when being young. As a result, natural selection loses the evolutionary ability to eliminate such an individually adverse trait as aging.

Age-related increasing mortality and aging in the wild are now firmly documented, in any case. This was described for a small tribal population of Paraguay, the Ache, living under natural conditions (Libertini 2013), and the same is true for many species in wild natural populations of animals (Libertini 1988; Nussey et al. 2013). It was admitted that such facts had lessened the force of one of the traditional arguments against programmed aging (Kowald and Kirkwood 2016).

Adherents of non-programmed aging meet with the difficulty in answering the following question: how it is possible to make, without a program, but instead with errors, to make fine tuning of the rate of aging in various species, from worms to whales.

In the development of Medawar’s idea that the evolutionary effect of aging is small, Williams put forward an evolutionary explanation for the origin of this process in the form of the antagonistic pleiotropy hypothesis of aging (Williams 1957). Pleiotropy means that a single gene can control more than one trait. The theory claims that pleiotropic alleles, which are good for the young body and therefore can spread over populations, can be bad to the old organisms, initiating their aging. Such genes are not eliminated from populations since the probability of reproduction decreases with age, and the selection becomes less effective. According to Williams’ theory, all attempts of gerontologists are fundamentally doomed to failure, since many potentially harmful pleiotropic genes cannot be replaced. However, an unanswered question still exists: why the beneficial effect, which is good for young, should be obligatorily linked to the adverse effects in later life? The antagonistic pleiotropy theory also does not explain why the symptoms of aging are very similar in different species having both very different lifespans and phenotypes.

The disposable soma theory of aging by Kirkwood states that adult organism reduces the anti-deterioration somatic processes in order to invest resources into increased reproductive efforts, while the accumulation of unrepaired damages leads to aging. Longevity is evolutionary regulated through the equilibrium between the repair functions and the rate at which damage accumulates (Kirkwood 1977, 2011; Kirkwood and Melov 2011; Kowald and Kirkwood 2016).

Like other theories of the metabolic trade-off, Kirkwood’s theory predicts an inverse correlation between lifespan and fertility, but such association was not observed either for humans or animals in captivity (Gavrilova et al. 2004; Ricklefs and Cadena 2007). This theory was competitive with other non-programmed aging theories in that time when programmed aging was seen as theoretically impossible as a trait which could not be approved by natural selection (Goldsmith 2017). Nevertheless, some researchers persist in the opinion that theories of non-programmed aging are still the best explanation for the evolution of aging (Flatt and Partridge 2018; Kowald and Kirkwood 2016).

According to Hayflick’s opinion, stochastic events determine the aging in both living and nonliving matter simply due to the second law of thermodynamics (Hayflick 2016). However, all considered arguments against stochastic theories of biological aging are equally applicable to the thermodynamic theory of aging, too.

It should be noted that some stochastic theories of aging could move from this class to the class of theories of programmed aging, if the following scenario would be in action: the programmed mechanism, for example, in a brain, is aimed at reducing, in an age-dependent manner, the fidelity of various systems in all cells of a body. In this case of programmed aging, the phenotypic changes in aging bodies would very much resemble the scenario of stochastic aging.

Theories of Programmed Aging

The advances of biology in understanding the genetic and cytological foundations of development that were achieved on the verge of the nineteenth and twentieth centuries undoubtedly influenced the researchers of aging (Comfort 1979; Medvedev 1990; Libertini 2015b). As the organism develops according to the program, it seemed natural to suppose that aging also has a program. Hence, Wallace, the co-discoverer of evolution by natural selection, suggested that aging is programmed, and Minot searched a cause of aging in the cessation of growth and differentiation (Comfort 1979). Weismann proposed that such a program could have an evolutionary goal: to free resources for progeny carrying new useful traits (Weismann 1882, 1891). Weismann also proposed the cytological cause that would restrict a lifespan, namely, the existence of cell division limits. If to use current terms and knowledge, this Weismann’s proposition assumed that aging is a consequence of the Hayflick limit, which is known to couple with telomere shortening. It should be noted that telomerase-treated mice, both at 1-year and at 2-year of age, had an increase in median lifespan of 24 and 13%, respectively (Bernardes de Jesus et al. 2012). In other words, these mice did not become immortal, although the possibility of telomerase-dependent immortalization of mitotic cells in vitro is experimentally proved (Bodnar et al. 1998; Vaziri and Benchimol 1998). Hence, organismal aging is hardly explainable only through the replicative senescence of cells of a body.

The idea of programmability of aging received further elaboration in recent years, although this possibility was considered earlier as theoretically inadmissible because it directly conflicts with the traditional version of Darwin’s survival-of-the-fittest concept (Goldsmith 2017). A current revisiting of the group and kin selection theories suggest that traits such as aging, if benefit a population, can evolve, even being bad for each individual. If such approaches are correct, then old objections disappear (Libertini 1988; Mitteldorf 2016).

In the theory of phenoptosis, which develops Weismann’s theory, Skulachev supposed that the biological cause of death is the launch of the program of organismal self-destruction (phenoptosis) (Skulachev 2012). This theory requires the existence of a timer. Interestingly, the stochastic events (e.g., the action of ROS, mitochondrial death, advanced glycation) were suggested as a fuel for the functioning of the timer that controls programmed aging (Severin et al. 2013). Koltover suggested another variant of a timer, the free radical redox timer, which also controls a lifespan (Koltover 2017).

In aging, an essential role is played by hormones, which are no less important for the development itself (Dilman and Dean 1992). Hertoghe considered aging as the syndrome of “multiple hormone deficiencies,” since (i) many diseases of aging (including cardiovascular diseases, obesity, osteoporosis, dementia, etc.) are similar to physical consequences of hormone deficiencies and (ii) most signs of aging (excessive free radical formation, glycation, cross-linking of proteins, accumulation of waste products, deficient immune system, etc.) may be caused in deficiencies of many hormones (Hertoghe 2005).

In the Dilman neuroendocrine theory (Dilman 1971; Dilman and Dean 1992), aging is seen as a continuation of the developmental program. Dilman postulated that aging is based on the gradual elevation of the hypothalamic threshold. Hence, the aging process is caused by a decrease of hypothalamus’ sensitivity to the inhibiting feedback signals (from the side of peripheral hormones). The gradual decrease of hypothalamus’ sensitivity is necessary for development, and the same process then leads to the hyperfunction of the hypothalamus, provoking both the aging and diseases of old age. However, what is the driving force that initiates over time the gradual changes of the sensitivity in postmitotic cells of a hypothalamus? This key question remained unanswered.

According to Blagosklonny, aging is not programmed, being a continuation of the developmental program, which persists later in life and becomes hyperfunctional and purposeless pseudo-program (Blagosklonny 2013). Reducing mTOR signaling (mTOR is a part of the developmental program) extends the lifespan of rodents by pushing back the onset of aging. However, this does not alter the shape of the mortality curve once aging starts. The stability of the shape of survival curves is interpreted better as a manifestation of the program rather than as a result of stochastic events (Garratt et al. 2016).

The immune system is often seen as part of the neuroendocrine-immune axis. According to the inflammaging theory proposed by Franceschi, the imbalance between pro- and anti-inflammatory pathways in the immune system is a driving force of frailty and age-related diseases, especially in very old patients (Fulop et al. 2018). Since imbalance has features of the system process, the theory can be attributed to the camp of programmed theories of aging.

Among the theories of programmed aging, there are also models that take into account the role of telomeres (Libertini and Ferrara 2016a).

In the telomere theory of cellular senescence (Olovnikov 1971, 1973), the following was proposed: (1) the DNA end underreplication problem, or marginotomy, was first formulated; (2) the telomere shortening in cell replication was predicted, and an interpretation of the limit of cell doublings, or the Hayflick limit, was given as the consequence of telomere shortening; (3) it was predicted that germline cells and cancer cells should express a special form of DNA polymerase compensating for telomere shortening; and (4) the circular form of bacterial genome was first explained as a way to protect a genome from the DNA end underreplication. This telomere theory was inspired by the groundbreaking discovery of Hayflick’s limit (a limited potential of normal cells to replicate) (Hayflick 1965). The existence of this limit required the explanation. The early history of telomere biology and the significance of telomeres for gerontology are considered in (Hayashi 2018; Blackburn and Epel 2017; Fossel 2015; Olovnikov 1996).

Some options for interventions into cellular senescence and aging, using the subtelomere-telomere-telomerase system as a target are considered in (Libertini 2015a; Libertini and Ferrara 2016b).

Accounting for some data concerning the organismal aging and the replicative senescence, which did not fit into the telomere theory, had led to the formulation of new ideas summarized in the chronographic theory (Olovnikov 2015). This theory presupposes the existence of relatively small perichromosomal DNA amplificates, namely, the small DNA molecules covered by proteins and appearing in development as intranuclear (perichromosomal) organelles. There are two classes of these organelles: printomeres (in mitotic cells) and chronomeres (in neurons specialized for time control of development). Each specific DNA molecule in each organelle is the copy of the strictly defined regulatory segment of chromosomal DNA. Using its own transcripts, each of these specific regulatory organelles is able to control and optimize the expression of the strictly defined set of chromosomal genes.

The chronographic theory states that the regulation of development and aging of multicellular animals are organized in time according to the principle “consecutive abolition of inhibition.” In the course of development, the consecutive programmed losses of the stage-specific chronomeres consecutively abolish the prohibition on the fulfillment of the next developmental stage. Namely, after the loss of chronomeres, which controlled the developmental stage 1, chronomeres of the stage 2 are activated. Then, after the loss of chronomeres of stage 2, the chronomeres of the stage 3 are activated, and so on, up to activation of the “adult” chronomeres that are responsible for the complete physiological maturation of an adult organism. Reduction of the stock of the “adult” chronomeres, due to their programmed gradual losses, causes aging of a body because of the growing deficiency of the regulatory transcripts of chronomeres. At the individual level, the programmed expenditure of chronomeres firstly ensures the establishment and maturation of a body and then forces it to grow old. At the population level, this effect is responsible for increasing adult mortality with increasing chronological age.

As to the replicative senescence of dividing cells, it occurs owing to the critical shortening of printomeres. Their ends are gradually shortening like telomeres. The process of DNA end underreplication of printomeres, rather than telomeres shortening, is the leading cause of the replicative senescence (Olovnikov 2015). Some indications on the possible existence of putative DNA amplificates were reported in (Shubernetskaya et al. 2017). The chronographic theory also belongs to the class of theories of programmed aging.

To this class of theories also belongs to the demographic theory of aging, which aims to explain the origin of aging in evolution as a programmed process of the demographic homeostasis (Mitteldorf 2016). Proceeding from the notion that population dynamics can be a key to understanding the evolution of aging, this theory implies the existence of the programmed ability of organisms to level the death rate, avoiding overpopulation and, hence, extinction. The demographic theory of aging states that aging is a group-selected adaptation. The appeal to the idea of group selection is caused by an attempt to understand how aging might have developed as a trait that negatively contributes to individual fitness. It is pertinent, however, to note that the conception of group selection contrasts with the traditional view which holds that Darwinian selection, the driving force of biological evolution usually occurs at the individual level.

Future Prospects

Some pros and cons of various theories of aging are mentioned above. Current comparative studies provide additional facts. Expression of genes involved in DNA repair is higher in ant queens than in short-lived workers, though their brains do not differ in the expression of genes involved in the ubiquitin-proteasome system, which degrades misfolded or damaged proteins (Lucas et al. 2016). On termites, other social insects, it was shown that in workers, unlike long-lived reproductive queens and kings, activation of transposons occurs (Elsner et al. 2018); probably this is epigenetically programmed and shortens a lifespan of workers. Huge differences in lifespan (ranging from four to more than 100 years) are characteristic for various species of sea urchins; in addition, they have long-lasting cells and a low level of cell turnover (Bodnar and Coffman 2016). Making a likely assumption about the similarity of their metabolism, such differences in longevity are difficult to explain within the framework of stochastic aging. Within mammals, maximum lifespan differs more than 100 folds. Many birds, with their increased metabolic rate, live longer than similar-sized mammals. All these facts are hardly compatible with the supposed (Golubev et al. 2017) key role of metabolic by-products in the origin of aging.

Concerning the reasons for the appearance of senescent cells in a body, three cell senescence programs are considered: replicative, stress-induced, and developmentally programmed senescence (von Kobbe 2018). Is the appearance of senescent cells only a result of events inside these cells themselves? Or they can also appear as a secondary response to the programmed influences from an aging body? This still has no clear answer.

In the past, criticism of the idea of programmed aging used two main assumptions: (i) in the wild, animals die without waiting for aging, and therefore the selection does not “see” their aging; and (ii) mutations could sometimes eliminate aging (Kowald and Kirkwood 2016). The first argument contradicts the current data on the age-dependent decline in many functions long before old age. As for mutations, indeed, among genes that confer the increased lifespan, no mutations have been found, which would be able to abolish aging (Kirkwood 2011; Kirkwood and Melov 2011). Non-programmers advance this fact as the main objection to the theories of programmed aging.

Triploid Drosophila flies live no longer than diploid ones. Diploid and haploid males of wasps Habrobracon have the same lifespan (Comfort 1979). Such data are difficult to correlate with occasional damage to a genome and better correspond to the programmed cause of aging.

Another argument in discussions on the origin of aging is the existence of epigenetic clocks. Age-dependent changes in DNA methylation at nonrandom sites of the genome show linear increase across the lifespan and are used in epigenetic clocks that can indicate chronological age in different species (Horvath and Raj 2018; Ito et al. 2018). The strict order of changes in DNA methylation at the definite sites of the genome is most convincingly explained by the work of the program rather than by a blind play of stochastic factors. Thus, the supposition of non-programmers that aging is caused by the lifelong accumulation of occasional damages/errors is seemingly misleading. Another fundamental mistake of some critics of the idea of programmed aging is their belief that aging requires genes responsible for destruction processes. No genes that are unique to aging have been found. At least in the case of the chronographic theory of development and aging, such genes are unnecessary: if the same genetic factors are used for development and aging, mutations that eliminate aging cannot persist in evolution. Such mutations would abolish the development itself.

Proponents of stochastic aging are more pessimistic about the hope of a significant slowdown of aging compared to programmers since an avalanche of random errors is more difficult to curb than the program. However, both camps of gerontologists (Fig. 1) hope to help medicine, moving forward in understanding one of the major mysteries that occupies mankind from time immemorial.
Fig. 1

On the state of affairs in the world of theoretical gerontology


The nature of the pivotal mechanism of organismal aging remains a field of controversy. The existing theories of aging can be divided into two groups. The first group (theories of stochastic aging or otherwise damage theories) argues that aging is caused by the accumulation of accidental errors. According to the alternative viewpoint (theories of programmed aging), the course of aging is evolutionarily programmed. Currently, there is a trend toward the prevalence of programmed theories of aging.



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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Biochemical PhysicsRussian Academy of SciencesMoscowRussia
  2. 2.Research Center for ObstetricsGynecology and PerinatologyMoscowRussia

Section editors and affiliations

  • Giacinto Libertini
    • 1
  1. 1.ASL NA2 NordItalian National Health ServiceFrattamaggioreItaly