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An epigenetic clock controls aging


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We are accustomed to treating aging as a set of things that go wrong with the body. But for more than twenty years, there has been accumulating evidence that much of the process takes place under genetic control. We have seen that signaling chemistry can make dramatic differences in life span, and that single molecules can significantly affect longevity. We are frequently confronted with puzzling choices the body makes which benefit neither present health nor fertility nor long-term survival. If we permit ourselves a shift of reference frame and regard aging as a programmed biological function like growth and development, then these observations fall into place and make sense. This perspective suggests that aging proceeds under control of a master clock, or several redundant clocks. If this is so, we may learn to reset the clocks with biochemical interventions and make an old body behave like a young body, including repair of many of the modes of damage that we are accustomed to regard as independent symptoms of the senescent phenotype, and for which we have assumed that the body has no remedy.
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An epigenetic clock controls aging
Josh Mitteldorf
Received: 25 December 2014 / Accepted: 7 October 2015
Springer Science+Business Media Dordrecht 2015
Abstract We are accustomed to treating aging as a
set of things that go wrong with the body. But for more
than twenty years, there has been accumulating
evidence that much of the process takes place under
genetic control. We have seen that signaling chemistry
can make dramatic differences in life span, and that
single molecules can significantly affect longevity.
We are frequently confronted with puzzling choices
the body makes which benefit neither present health
nor fertility nor long-term survival. If we permit
ourselves a shift of reference frame and regard aging
as a programmed biological function like growth and
development, then these observations fall into place
and make sense. This perspective suggests that aging
proceeds under control of a master clock, or several
redundant clocks. If this is so, we may learn to reset the
clocks with biochemical interventions and make an
old body behave like a young body, including repair of
many of the modes of damage that we are accustomed
to regard as independent symptoms of the senescent
phenotype, and for which we have assumed that the
body has no remedy.
Keywords Senescence Programmed aging
Epigenetic Evolution Life history Gene expression
Reasons to believe that aging derives
from a genetic program
Since the pioneering work of Medawar (1952) and
Williams (1957), it has become customary to under-
stand the phenotypes of aging as failures of home-
ostasis in the body. Where the body has clearly made
metabolic choices that hasten its demise, we look for
tradeoffs and hidden benefits. Sometimes the tradeoffs
and benefits are obvious, but when we cannot find
them, we assume nevertheless that they must exist.
But a number of trends in recent decades suggest
that aging is an independent adaptation, and that
destruction of the body is proceeding under full
control of the genome.
The genetic basis for aging is conserved across
such great spans of evolutionary distance (Guar-
ente and Kenyon 2000; Kenyon 2001) as to render
pleiotropy an implausible explanation, and muta-
tional load an irrelevance.
Animals are able to extend life span under some
conditions of hardship and environmental chal-
lenge, including caloric restriction (Calabrese and
Baldwin 1998; Calabrese 2005; Masoro 2005,
2007). Frequently the life extension comes at
minimal cost in fertility (Flatt 2009), especially for
males (Weindruch and Walford 1988; Masoro
2003). The ability of the body to extend life span
J. Mitteldorf (&)
Department of EAPS, MIT, Cambridge, MA, USA
DOI 10.1007/s10522-015-9617-5
under stress hints that, in the absence of stress, the
body harbors a latent capacity for longer life that is
not activated because of genetic programming
(Mitteldorf 2001).
Evidence for pleiotropy of known aging genes is
weak (Kirkwood 2005; Blagosklonny 2010). In
fact, pleiotropic benefits have only been discov-
ered for a small proportion of genes that shorten
life span (Curtsinger et al. 1995; Stearns 2000),
and several examples are documented in which a
wild-type allele shortens life span and also lowers
fertility (Spitze 1991; Bronikowski and Promislow
2005; Hanson and Hakimi 2008).
The high fitness cost of aging in the wild (Ricklefs
1998; Bonduriansky and Brassil 2002; Nussey
et al. 2012; Jones et al. 2014) is inconsistent with
the once-dominant Mutation Accumulation the-
ory, and steepens the challenge to the pleiotropic
theories as well.
The existence of programmed aging in protists, in the
form of cellular senescence (Clark 1999,2004) defies
classical evolutionary theory. The association of
cellular senescence with increased mortality in
humans (Cawthon et al. 2003; Fitzpatrick et al.
2007; Kimura et al. 2008)isprima facie evidence for
a form of programmed death. The classical explana-
tion is that cellular senescence offers protection
against cancer (Sager 1991;Campisi2013;de
Magalhaes 2013). However, this has become increas-
ingly untenable as a clear association has emerged
between short telomeres and higher incidence of
cancer (Rode et al. 2015). Considering also that many
species not susceptible to cancer nevertheless are
subject to mortality increase from cellular senescence
(Mitteldorf 2013), we must regard cell senescence as
a form of programmed aging that has persisted since
the Cambrian explosion.
Apoptosis in yeast cells under stress has been
documented as an altruistic aging program (Fab-
rizio et al. 2004). Apoptosis continues to play a
role in senescence of multicelled organisms
including humans (Behl 2000; Marzetti and
Leeuwenburgh 2006).
An inverse association between fertility and life
span is predicted by the Disposable Soma (Kirk-
wood 1977) and other theories of metabolic trade-
off. But this correlation is observed neither in
animals (Ricklefs and Cadena 2007) nor in humans
(Gavrilova et al. 2004; Mitteldorf 2010a,b).
These and other arguments for aging as a genetic
program are reviewed in (Bredesen 2004; Mitteldorf
2004; de Magalha
˜es and Church 2005; Mitteldorf
2010a,b; de Magalha
˜es 2012; Goldsmith 2013;
Pepper et al. 2013; Mitteldorf 2016).
Programmed aging is inconsistent
with the standard model of evolutionary genetics
Historically, the idea that aging could be an evolu-
tionary adaptation has been a non-starter because
aging is the opposite of fitness, defined as individual
reproductive success. If we believe that natural
selection is in the business of maximizing some
measure of reproductive potential (e.g. ror R
), then
evolution must always be toward higher fertilities and
longer life spans, to the extent these are not in conflict.
The quantitative formulation on which this thinking
is founded is not Darwin’s, though it is called neo-
Darwinism. It was developed in the early twentieth
Century by Sharpe and Lotka (1911) and formalized
into a fully axiomatic mathematical system by Fisher
(1930). Most theoretical evolutionists take it as gospel,
but it is demonstrably false. There have been many
counter-examples, in which a variety that has shorter
life span, lower fertility, and worse survivability out-
competes a variety that is better in all these respects.
An example of guppies in the river pools of Trinidad
was documented by Reznick (Bryant and Reznick
2004). My favorite example is the Rocky Mountain
Locust, a super-competitor that swarmed to cover
hundreds of thousands of square kilometers of sky in
the American mid-west a hundred years ago, denuded
vast regions of every green leaf and blade of grass in its
heyday. Although individually a super-competed,
collectively, the Rocky Mountain Locust was a
circular firing squad that drove itself into extinction
within a few years. There are no surviving specimens
today (Yoon 2002).
My contribution to this field has been a theoretical
suggestion about why individual success in the
Darwinian competition inevitably leads to a tragedy
of the commons (Hardin 1968) that brings down the
entire ecosystem. Natural selection at the ecosystem
level is an efficient force in direct opposition to
individual selection for reproductive profligacy. This
changes everything we thought we knew about what
constitutes fitness. In particular, it opens a window for
selection of aging as an adaptation. What follows is a
line of reasoning adapted from (Mitteldorf 2006).
Intuitively, we know that populations are subject to
environmental feedback. If a population is lower than
the carrying capacity, births exceed deaths, and the
population grows. If a population is greater than the
carrying capacity, deaths exceed births, and the
population falls. We may expect a population out of
equilibrium to smoothly approach its carrying capacity
(Figs. 1,2).
But every species is dependent on an ecosystem.
The fox is dependent on the rabbit, and the rabbit
depends on the grass. Crucially, the rate at which the
grass grows is fixed by sunlight, and it cannot grow
faster. But other species, higher up the food chain,
evolve higher and higher growth rates according to
Lotka’s model. Increasing individual reproductive
success has the collective effect of increasing the
population growth rate, or exponential rate of increase.
Rabbits may evolve to grow their population faster
than the grass can keep up. For most species that are not
at the bottom trophic level, it is not difficult to evolve a
faster reproductive rate, because there is a reservoir of
food to be tapped. Tapping the food supply more
deeply permits a faster growth rate in the predator, but
the depleted prey population makes this a losing
proposition, not just in the long run but even in a single
generation. If collectively we abuse the ecosystem on
which we depend, our children will starve.
This dynamic is reflected in the mathematics of the
logistic equation. The plots in Figs. 1and 2were based
on an exponential growth rate for the rabbits that is small
compared to the grass. The ratio of the rabbits’ growth
rate to the growth rate of the grass is called the ‘‘chaos
parameter’’, for reasons we may see in Figs. 3,4,5.
When the rabbits grow at twice the rate of the grass, we
see some oscillation about the carrying capacity.
When the ratio increases to 2.5, this oscillation
becomes more severe.
For ratios greater than about 2.59, the pattern ceases
to be periodic, and fluctuations become increasingly
wide and irregular.
Fig. 1 Logistic solution for
population approaching
steady state from above
Fig. 2 Logistic solution for
population approaching
steady state from below
For values greater than 3, the population drops to
zero and, of course, cannot recover. The number 3 is a
line in the sand only for mathematics. But there’s no
physiologic reason why reproduction rates can’t get as
high as 3 or 4 or 10 or 20. In fact, the reason that
animals have evolved birth rates that are less than they
are physically capable of and death rates that are
higher than necessary is to avoid population chaos.
Demographic chaos is a fast track to extinction.
Population dynamics is a very rapid and powerful
force of Darwinian selection. For insect species, it can
destroy a population in one season. With growth rates
Fig. 3 Logistic growth for
chaos parameter = 2
Fig. 4 Logistic growth for
chaos parameter = 2.5
Fig. 5 Logistic growth for
chaos parameter = 2.9
typical of mammals, it can wipe out an entire
population in a single individual’s lifetime. Such an
event was documented in recent history, when rein-
deer were introduced to St Matthews Island in the
Bering Sea in 1944. The reindeer were evolved for an
environment where they were hunted by wolves, but St
Matthews had no natural predators. The reindeer
population grew exponentially for 18 years, then died
off in a single winter (Klein 1968).
Population dynamics is a powerful evolutionary
force at the group level, and it is working in direct
opposition to individual selection for faster reproduc-
tion. This is why the 100-year old idea that natural
selection maximizes individual reproductive success
is wrong.
A window for evolution of aging
With the evolutionary imperative to maximize repro-
duction effective blunted, there is an opportunity for
aging to evolve as an adaptation. Aging may evolve
‘opportunistically’’ for reasons that have nothing to do
with population dynamics. Aging offers a selective
advantage for population turnover (Martins 2011),
contributes to evolvability (Mitteldorf and Martins
2014), and helps diversify the population to protect
against infectious epidemics (Mitteldorf and Pepper
In addition to these ‘‘opportunistic’’ pathways,
aging may evolve because of its direct benefit for
preventing demographic extinctions. Aging stabilizes
population dynamics by leveling out the death rate
when the grass is thick and when the grass is sparse.
Without aging, the entire adult population is uniformly
strong, and deaths tend to be highly clustered in times
of crowding, epidemics, and famine. Aging substitutes
a steady stream of individual deaths, and protects
against the overcrowding that leads to population
collapse (Mitteldorf and Goodnight 2012).
Biological clocks for aging
Once the theoretical objections to programmed aging
are answered and the empirical evidence is considered,
the programmed aspects of aging come into focus. If
aging proceeds under genetic control, it is probable
that the body keeps a reference clock, or perhaps
several redundant clocks to insure the body does not
escape destruction, and to protect against evolutionary
reversion to a non-aging phenotype.
Two biological clocks have been studied and
documented in humans, the first based on telomere
shortening and cell senescence; the second based on
involution of the thymus. Telomere attrition has an
ancient history as the only mode of senescence in one-
celled ciliates (Clark 1999,2004). In humans, telom-
ere length of leukocytes is now a commercially
available lab test. Since stem cells are replicating
through a lifetime and very little telomeraseis exp
ressed after the embryo stage, telomere length declines
over a lifetime. For decades, this was known, but there
was no indication whether telomere shortening had
implications for aging mortality. Then in 2003,
(Cawthon et al. 2003) used historic blood samples
from a Salt Lake City hospital to demonstrate that
telomere length is a strong predictor of age-adjusted
mortality. The finding has been replicated in humans
(Bischoff et al. 2005; Harris et al. 2006; Brouilette
et al. 2007; Fitzpatrick et al. 2007; Kimura et al. 2008;
Fyhrquist et al. 2011; Ma et al. 2011; Strandberg et al.
2011; Willeit et al. 2011) and also in mammals
¨mmendorf et al. 2002; McKevitt et al. 2002) and
birds (Pauliny et al. 2006). There are two plausible
mechanisms by which cellular senescence contributes
to aging. First, the population of stem cells that
replenish muscle, skin and immune cells is depleted by
senescence, contributing to aging of these tissues.
Second, cells with short telomeres are a source of
inflammatory cytokines, with system-wide conse-
quences far out of proportion to the number of affected
cells (Baker et al. 2011).
The thymus is a gland in which T-cells are trained
to distinguish self from invader. With age the thymus
shrinks in size and becomes less functional, with
consequences for the competence of the immune
system as a whole. At advanced ages, T cells are prone
to errors of Type 1 and Type 2. Type 1 errors allow
invading microbes to escape undetected, with the
result that the elderly have a heavier burden of
infectious disease. In type 2 errors, healthy indigenous
tissues are attacked in an autoimmune response,
typical of arthritis and other diseases of old age.
Reasons to believe there is a third clock
Williams (1957) first articulated theoretical reasons to
believe that aging should have evolved to be
controlled by multiple independent factors, and his
reasoning remains valid today.
Some animals suffer senescence even though their
telomeres don’t shorten with age. And some modes of
aging in humans seem unlikely to be related to
telomeres and immune function. For example, the
brain ages though neuronal growth is not directly
limited by short telomere or the state of the thymus.
A broader reason for suspecting the existence of a
third, epigenetic aging clock comes from thinking
about developmental biology. In growth, development
and puberty, timing is exquisitely sensitive. It is
widely believed that development is under control of
gene expression, i.e., epigenetic programming. What
clock tells the body when to secrete growth factors and
when to stop, or when to initiate puberty with
gonadotropic hormones? This remains an unanswered
question in developmental biology. Ebling (2005)In
recent years, it has become clear that gene expression
is a strong function of age (de Magalha
˜es et al. 2009;
Zykovich et al. 2014). The fact that a separate clock
has never been identified suggests that gene expression
itself might be a clock. Time can be measured using a
feedback loop, and gene expression provides such a
Epigenetic state of cells controls gene expression
(including circulating hormones).
Circulating hormones feed back to continually
reprogram the epigenetic state of cells.
The existence of an epigenetic aging clock was
independently suggested by Rando and Chang (2012),
de Magalha
˜es (2012), and Johnson et al. (2012).
Parabiosis and factors in the blood
Parabiosis is the surgical joining of two bodies so that
they share a common circulatory flow. Heterochronic
parabiosis is the joining of a young and old animal.
Experiments were done with mice beginning in the
nineteenth century, and in the 1950s, the field was
renewed by the same Clive McCay et al. (1957) who
discovered the life extension potential of caloric
restriction in the 1930s.
The current wave of parabiosis experiments with
mice grew from Rando’s Stanford University
laboratory, and several of his students in the early
2000s. The Conboys, Villeda, Wagers, and Wyss-
Coray today conduct parabiosis experiments in their
own labs. The first promising experiment in this
new wave was published in 2005 (Conboy et al.
2005), in which it was reported that impaired
muscle and skin healing in an old mouse was
rescued by exposure to blood from a young mouse.
It was not the red or white blood cells that offered
the benefit, but protein and RNA factors dissolved
in the plasma. Intriguingly, gene expression was
found to be broadly impacted, reverting to a more
youthful profile.
These experiments established the possibility that
old tissue could be rejuvenated by a young signaling
environment. The next steps were to transfuse blood
plasma from young to old mice, and to identify
specific factors in the blood that are responsible for
rejuvenation. Mayack et al. (2010) found that
haematopoietic stem cells could be rejuvenated by a
youthful profile of blood factors.
This work is very much in progress. Recently, a
number of results have been published that make
the epigenetic clock model look more plausible.
Villeda (Bouchard and Villeda 2014) reports that
infusion of young blood plasma reverses nerve
damage, improves cognitive function in mouse
model of alzheimer’s disease. It has already
become clear that there are both anti-aging factors
that are under expressed and also pro-aging factors
that are overexpressed in old mice. Among the
anti-aging factors identified are GDF11, which
promotes nerve and muscle growth (Katsimpardi
et al. 2014) and oxytocin, which is necessary for
muscle maintenance (Elabd et al. 2014). Among the
pro-aging factors identified are TGFband NfjB,
which promote inflammation (Conboy et al. 2005),
and FSH which is associated with weight gain,
osteoporosis, and some cancers (Merry and Hole-
han 1981; Bowles 1998).
Using algorithmic searches based on statistics
alone, Horvath (Horvath 2013) has found combi-
nations of DNA methylation sites that change so
consistently with age that an accurate measure of
functional age can be constructed. There is a great
deal of consistency among different tissues and
different donors. (Jones et al. 2015) makes a first
pass at partitioning the difference in methylation
patterns between stochastic change, which may be
regarded as dysregulation, and consistent patterns,
which may be regarded as programmed aging.
Future directions
It is a fact that gene expression changes with age, and a
reasonable hypothesis that gene expression controls
some aging phenotypes. There is reason to hope that
restoring the body to a youthful state of gene
expression will rejuvenate the repair and growth
faculties, stimulating the body to repair years of
accumulated damage. We have seen that a few
powerful transcription factors are capable of repro-
gramming the epigenetic state of chromatin, and this
suggests a promising path for aging research.
For future medical applications, the existence of an
epigenetic aging clock will do us little good if it is
essentially complex, and must be re-programmed, one
site at a time, with the epigenetic markers character-
istic of youth.
But if we are fortunate, then some manageable
number of circulating hormones and other blood
factors will be discovered that can signal the body to
return epigenetic programming to a more youthful
state. If only because the prize is potentially so large,
this possibility is a worthy focus for intensive research
in the near future.
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... Lithgow, 2006 Most researchers studying the evolution of aging consider aging to be non-adaptive in the sense that it appears to be a by-product or side e ect of other biological and evolutionary processes rather than an end in itself (e.g., Austad 2004;Kirkwood & Melov 2011;Cohen 2015). Increasingly, however, the ETAs have been questioned and various authors advocated aging as being evolutionarily adaptive and programmed (Libertini 1988(Libertini , 2006(Libertini , 2008Nusbaum 1996;Skulachev 1997Skulachev , 1999Skulachev , 2002Skulachev , 2011Bowles 1998Bowles , 2000Lewis 1999;Mitteldorf 2001Mitteldorf , 2004Mitteldorf , 2006Mitteldorf , 2010aMitteldorf , 2010bMitteldorf , 2014Mitteldorf , 2015Mitteldorf , 2016Mitteldorf , 2018Heininger 2002Heininger , 2012Goldsmith 2003Goldsmith , 2008Goldsmith , 2010Goldsmith , 2012Goldsmith , 2013Bredesen 2004aBredesen , 2004bTravis 2004;Longo et al. 2005;Prinzinger 2005;Mele et al. 2010;Milewski 2010;Martins 2011;Gavrilova et al. 2012;Khalyavkin 2013;Yang 2013;Mitteldorf & Martins 2014;Skulachev & Skulachev 2014;Werfel et al. 2015Werfel et al. , 2017Shilovsky et al. 2016Shilovsky et al. , 2017Shilovsky et al. , 2021Singer 2016;Lenart & Bienertová-Vašků 2017;Muller 2018;Van Raamsdonk 2018;Veenstra et al. 2018Veenstra et al. , 2020Galimov & Gems 2020Poljsak et al. 2020;Winterhalter & Simm 2022). And even staunch proponents of the ETAs (de Grey 2015; Cohen 2018) concede that there are a small number of exceptions where aging is clearly programmed. ...
... DNA methylation (DNAm) profiles of CpGs allow one to develop accurate estimators of chronological age which are referred to as "DNAm age", "epigenetic age", or "epigenetic clock" (Marttila et al. 2015;Mitteldorf 2015Mitteldorf , 2016Declerck & Vanden Berghe 2018;Field et al. 2018;Lu et al. 2018;Raj 2018;He et al. 2021). A small fraction (~2%) of the CpG sites show age-related changes, either hypermethylation or hypomethylation. ...
... These theories are in line with the insufficiency of maintenance and repair processes that leads to stochastic damage accumulation with aging thus causing the functional decline of the organism 7 . Recent progress on aging clocks, however, has revived the idea of a potential program involved in aging 8,9 . Currently, it is controversially discussed whether aging is purely a stochastic entropy-driven event in line with the evolutionary theory of aging or whether the existence of aging clocks could show a causal relationship to aging 10,11 . ...
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Aging clocks have provided one of the most significant recent breakthroughs in the biology of aging. Such clocks allow the determination of chronological and increasingly also biological age, which is prerequisite for assessing the effectiveness of interventions in the aging process and preventive treatments of age-related diseases. The most advanced aging clocks are based on age-dependent changes in DNA methylation pattern. The reproducibility of such changes over the life course has reinvigorated the debate whether a programmed process underlies aging. A programmed aging process, however, is incompatibly with the evolutionary theory of aging. Aging occurs as a consequence of a vanishing force of selective pressure post-reproduction as no fitness benefit is provided by immortality of the soma. In fact, stochastic events have been observed to increasingly occur during the aging process. Here, we test whether aging clocks could be built with entirely stochastic variation. We find that accumulating stochastic variation is sufficient to accurately predict chronological and biological age. Moreover, current aging clocks are entirely compatible with random alterations in the methylation or transcriptomic patterns. Our analysis unifies the clock measure of aging with the evolutionary theory of aging and predicts that any set of data that have a ground state at the age zero with accumulating stochastic variation could be used for building accurate aging clocks.
... Distress-induced epigenetic changes are associated with accelerated biological aging as shown through various epigenetic clocks (Hunter & McEwen, 2013;Jones, et al., 2015;Mitteldorf, 2013aMitteldorf, , 2016. These clocks are typically based on measuring methylation levels at CpG sites in the promoter regions of genes associated with aging (Mc Auley, 2021). ...
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High levels of stress are known to accelerate biological aging in susceptible individuals, often leading to a downward course of ill health and early death. This book-length review explores how and why. It is too long to expect anyone to read the whole thing, but it serves to keep track of my understandings and syntheses (as of May 2022) while delving into literatures on toxic stress, aging, life history, and evolutionary theory. A common theme in these literatures is the connection between early life adversity (ELA) and later ill health and early death. Just about the only evolutionary explanation to be found is that ELA signals infants and children to develop a “live fast, die young” strategy to beat the odds against reproduction in their harsh environments, but this siphons energy from bodily maintenance leading to ill health later in life. However, the “live fast, die young” model has been increasingly questioned based on both theory and research. Even if it is valid in some cases, it must be incomplete because it is based on individual level theoretical reasoning. But humans and most primates live in social groupings that can only exist because individuals give up some degree of autonomy as they cooperate and support each other, especially their close relatives. This review takes the very rare approach of asking what happens if we assess the mass of ELA research through the lenses of inclusive fitness and multilevel selection, which were both developed to explain the puzzle of altruism. Is it possible there’s an altruistic aspect to accelerated biological aging? We arrive at an answer of “yes” in a multilevel model of stress and aging which appears to be particularly unique in simultaneously accounting for (1) inclusive fitness as a universal design principle; (2) the existential imperative to control free-riders (a concept virtually absent in the aging and stress literatures); (3) allometric scaling with body size determining baseline species-specific metabolic rates and lifespans (as reflected in the same lifetime limit in number of heartbeats across all mammal species); (4) social status hierarchies as venues of social selection which imposes distresses and eustresses based on relative current social and prospective fitness values of individuals; and (5) the tendency of high social distress to accelerate biological aging while eustress can maintain or even decelerate it, thereby (6) channeling individuals along diverging reproductive arcs which advantage higher status individuals, but disadvantage and speed the altruistic exit-by-aging of lower status individuals along with identified predatory free-riders.
... However, some animal species suffer deterioration with age although their telomeres do not become shorter with advanced age and human neurons suffer aging although being post-mitotic. Aging could be explained as a process of adaptation to endogenous and/or exogenous factors, as a population turnover, evolution, prevention of demographic influences, and to stabilize the population 20,[35][36][37][38] . ...
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Aging interventions will be ineffective if we do not understand the basic principles of aging. Currently, there is no consensus on the issue whether aging is programmed or not. The hypothesis presented in this article indicates that aging (at least graying of male hairs) is programmed. This hypothesis is supported by the symmetry of the graying of male beard hairs. According to stochastic theories of aging, aging is a passive non-programmed process where random dispersion of graying hairs should result. On the contrary, programmed theories of aging would predict that there should be symmetry on the left and right parts of the face showing the same proportion, pattern and time of appearance of graying hairs.
... The molecular mechanisms underlying these constraints remain poorly understood 2,3 , despite prior studies correlating maximum lifespan with specific molecular processes and life history strategies [4][5][6] . Many authors have suggested that epigenetic mechanisms may play a role in controlling lifespan and aging [7][8][9][10][11][12][13][14][15] . The role of epigenetics in mammalian aging is underscored by recent studies demonstrating age reversal through (transient) epigenetic reprogramming with Yamanaka factors [16][17][18][19][20][21] . ...
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Maximum lifespan of a species is the oldest that individuals can survive, reflecting the genetic limit of longevity in an ideal environment. Here we report methylation-based models that accurately predict maximum lifespan (r=0.89), gestational time (r=0.96), and age at sexual maturity (r=0.87), using cytosine methylation patterns collected from over 12,000 samples derived from 192 mammalian species. Our epigenetic maximum lifespan predictor corroborated the extended lifespan in growth hormone receptor knockout mice and rapamycin treated mice. Across dog breeds, epigenetic maximum lifespan correlates positively with breed lifespan but negatively with breed size. Lifespan-related cytosines are located in transcriptional regulatory regions, such as bivalent chromatin promoters and polycomb-repressed regions, which were hypomethylated in long-lived species. The epigenetic estimators of maximum lifespan and other life history traits will be useful for characterizing understudied species and for identifying interventions that extend lifespan.
... The idea that aging is a programmed process has been previously proposed based on experimental data mainly from yeasts (Saccharomyces cerevisiae), worms (Caenorhabditis elegans) and mice [16]. The hypothesis that aging is a programmed process under the control of an epigenetic clock has also been proposed [17]. Another model of programmed aging proposes that organismal aging is the result of the combined action of many clocks, like DNA damage, telomere attrition, mitochondrial production of reactive oxygen and nitrogen species (ROS and RNS) at the cellular/ molecular level, as well as higher level clocks located in the central nervous system [18]. ...
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The view of aging has evolved in parallel with the advances in biomedical sciences. Long considered as an irreversible process where interventions were only aimed at slowing down its progression, breakthrough discoveries like animal cloning and cell reprogramming have deeply changed our understanding of postnatal development, giving rise to the emerging view that the epigenome is the driver of aging. The idea was significantly strengthened by the converging discovery that DNA methylation (DNAm) at specific CpG sites could be used as a highly accurate biomarker of age defined by an algorithm known as the Horvath clock. It was at this point where epigenetic rejuvenation came into play as a strategy to reveal to what extent biological age can be set back by making the clock tick backwards. Initial evidence suggests that when the clock is forced to tick backwards in vivo, it is only able to drag the phenotype to a partially rejuvenated condition. In order to explain the results, a bimodular epigenome is proposed, where module A represents the DNAm clock component and module B the remainder of the epigenome. Epigenetic rejuvenation seems to hold the key to arresting or even reversing organismal aging.
... Epigenetic marks establish changes in gene expression during cellular differentiation, and in response to environmental stimuli like DRs and rapamycin (D'Aquila et al., 2013). Some authors even support the existence of an "epigenetic clock" (Jones et al., 2015;Mitteldorf, 2016b;Horvath and Raj, 2018). This would be essentially different from the "epigenetic drift" during aging which corresponds to stochastic changes of small or not interest for the control of longevity (Jones et al., 2015). ...
Experiment Findings
The strong interest shown in the study of the causes of aging in recent decades has uncovered many mechanisms that could contribute to the rate of aging. These include mitochondrial ROS production, DNA modification and repair, lipid peroxidation-induced membrane fatty acid unsaturation, autophagy, telomere shortening rate, apoptosis, proteostasis, senescent cells, and most likely there are many others waiting to be discovered. However, all these well-known mechanisms work only or mainly at the cellular level. Although it is known that organs within a single individual do not age at exactly the same rate, there is a well-defined species longevity. Therefore, loose coordination of aging rate among the different cells and tissues is needed to ensure species lifespan. In this article we focus on less known extracellular, systemic, and whole organism level mechanisms that could loosely coordinate aging of the whole individual to keep it within the margins of its species longevity. We discuss heterochronic parabiosis experiments, systemic factors distributed through the vascular system like DAMPs, mitochondrial DNA and its fragments, TF-like vascular proteins, and inflammaging, as well as epigenetic and proposed aging clocks situated at different levels of organization from individual cells to the brain. These interorgan systems can help to determine species longevity as a further adaptation to the ecosystem.
Tooth enamel and dentin are the most studied hard tissues used to explore hominin evolution, life history, diet, health, and culture. Surprisingly, cementum (the interface between the alveolar bone and the root dentin) remains the least studied dental tissue even though its unique growth, which is continuous throughout life, has been acknowledged since the 1950s. This interdisciplinary volume presents state-of-the-art studies in cementum analysis and its broad interpretative potential in anthropology. The first section focuses on cementum biology; the second section presents optimized multi-species and standardized protocols to estimate age and season at death precisely. The final section highlights innovative applications in zooarchaeology, paleodemography, bioarchaeology, paleoanthropology, and forensic anthropology, demonstrating how cementochronology can profoundly affect anthropological theories. With a wealth of illustrations of cementum histology and accompanying online resources, this book provides the perfect toolkit for scholars interested in studying past and current human and animal populations.
Ageing is characterised by a physical decline in biological functioning which results in a progressive risk of mortality with time. As a biological phenomenon, it is underpinned by the dysregulation of a myriad of complex processes. Recently, however, ever-increasing evidence has associated epigenetic mechanisms, such as DNA methylation (DNAm) with age-onset pathologies, including cancer, cardiovascular disease, and Alzheimer’s disease. These diseases compromise healthspan. Consequently, there is a medical imperative to understand the link between epigenetic ageing, and healthspan. Evolutionary theory provides a unique way to gain new insights into epigenetic ageing and health. This review will: (1) provide a brief overview of the main evolutionary theories of ageing; (2) discuss recent genetic evidence which has revealed alleles that have pleiotropic effects on fitness at different ages in humans; (3) consider the effects of DNAm on pleiotropic alleles, which are associated with age related disease; (4) discuss how age related DNAm changes resonate with the mutation accumulation, disposable soma and programmed theories of ageing; (5) discuss how DNAm changes associated with caloric restriction intersect with the evolution of ageing; and (6) conclude by discussing how evolutionary theory can be used to inform investigations which quantify age-related DNAm changes which are linked to age onset pathology.
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Recent field studies suggest that it is common in nature for animals to outlive their reproductive viability. Post-reproductive life span has been observed in a broad range of vertebrate and invertebrate species. But post-reproductive life span poses a paradox for traditional theories of life history evolution. The only commonly-cited explanation is the 'grandmother hypothesis', which is limited to higher, social mammals. We propose that post-reproductive life span evolves to stabilize population dynamics, avoiding local extinctions. Predator-prey and other ecosystem interactions tend to produce volatility that can create population crashes and local extinctions. Total fertility rates that exceed the ecosystem's recovery rate contribute to population overshoot, followed by collapse. These local extinctions may constitute a potent group selection mechanism, driving evolution toward controlled rates of population growth, even when there is a significant individual cost. In this paper, we consider the question: what life history characteristics support demographic homeostasis at the least cost to individual fitness? In individual-based evolutionary simulations, we find that reduction in fertility is sufficient to avoid population instabilities leading to extinction, but that life histories that include senescence can accomplish the same thing at a lower cost to individual fitness. Furthermore, life histories that include the potential for a post-reproductive period are yet more efficient at stabilizing population dynamics, while minimizing the impact on individual fitness.
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Why do we age? This question has baffled scientists for 150 years and remains unresolved. Scientists disagree over even the general nature of aging. Is aging the result of fundamental limitations that apply to all living things, do we age because our bodies do not try harder not to age, or are organisms designed by nature or “programmed” to age because a limited lifespan conveys some evolutionary advantage? Amazingly, in the 21st century, there is still scientific disagreement regarding this question. This issue has potentially enormous implications for medicine. If aging is the result of fundamental and unalterable forces of nature, then anti-aging medicine is impossible and anti-aging research is futile and foolish. If aging is dictated by a species-specific design, then research may well reveal means for altering the operation of the aging mechanism and thereby improve the treatment of many age-related diseases and conditions. This book provides a review of theories of biological aging including underlying evolution and genetics issues and describes recent discoveries and theories that overwhelmingly favor programmed aging and therefore suggest that increased research on aging mechanisms would be highly beneficial to public health.
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Natural selection acts primarily on organisms, and the existence of evolved, active, internal mechanisms that cause organismal death would seem paradoxical. However, there is substantial evidence that internal death promoting mechanisms exist and are taxonomically widespread. Where these are argued to be 'programmed organismal death' (POD), they require evolutionary explanations. Any such explanation must draw on our understanding of fitness trade-offs and multiple levels of selection in evolution. This review includes two main categories of putative POD: senescence in multicellular-organisms, and programmed cell death in unicellular organisms. The evidence for POD as a genetically controlled phenotype is strong for semelparous and significant but more controversial for iteroparous plants and animals. In multicellular organisms the program frequently (although not always) appears to be the result of fitness trade-offs. Here the death phenotype itself is not adaptive but the fitness related program most likely is. However, in some cases of behavioral suicide, particularly in insects, there are distinct advantages to kin and group level benefits may play a role. In unicells, programmed death is ubiquitous and POD often provides benefits to others. While benefits do not equate with adaptations, they are consistent with it. Here, death may be adaptive at a level other than the individual cell. In other instances of POD in unicells the phenotype (eg autophagy) can be explained as pleiotropy. The overall picture of POD as a natural phenomenon is still emerging, and continued work on diverse lines of evidence is necessary to complete our evolutionary understanding of this apparent paradox. While some questions remain, we conclude that POD is most likely, in some circumstances at least, adaptive.
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The process of aging results in a host of changes at the cellular and molecular levels, which include senescence, telomere shortening, and changes in gene expression. Epigenetic patterns also change over the lifespan, suggesting that epigenetic changes may constitute an important component of the aging process. The epigenetic mark that has been most highly studied is DNA methylation, the presence of methyl groups at CpG dinucleotides. These dinucleotides are often located near gene promoters and associate with gene expression levels. Early studies indicated that global levels of DNA methylation increase over the first few years of life and then decrease beginning in late adulthood. Recently, with the advent of microarray and next-generation sequencing technologies, increases in variability of DNA methylation with age have been observed, and a number of site-specific patterns have been identified. It has also been shown that certain CpG sites are highly associated with age, to the extent that prediction models using a small number of these sites can accurately predict the chronological age of the donor. Together, these observations point to the existence of two phenomena that both contribute to age-related DNA methylation changes: epigenetic drift and the epigenetic clock. In this review, we focus on healthy human aging throughout the lifetime and discuss the dynamics of DNA methylation as well as how interactions between the genome, environment, and the epigenome influence aging rates. We also discuss the impact of determining 'epigenetic age' for human health and outline some important caveats to existing and future studies. © 2015 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.
The effect of predation by the aquatic dipteran larva Chaoborus americanus on genetic diversity and life-history evolution in the cladoceran Daphnia pulex was investigated in large replicate laboratory populations. Instantaneous daily loss rates of clonal diversity and genetic variance for fitness indicate that 93-99% of initial genetic diversity can be removed from populations during the 8-12 generations of clonal reproduction that occur each year in natural populations. In the absence of predation, the principal evolved changes in mean population life history were smaller immature body size and increased and earlier fecundity. In the presence of size-selective Chaoborus predation, populations evolved toward larger body size and increased and earlier reproduction. The difference between these two trajectories is an estimate of the direct additive effect of Chaoborus predation. This effect was manifested as evolution toward larger body size with a trend toward earlier and increased reproduction.
Short telomeres in peripheral blood leukocytes are associated with older age and age-related diseases. We tested the hypotheses that short telomeres are associated with both increased cancer mortality and all-cause mortality. Individuals (n = 64637) were recruited from 1991 onwards from two Danish prospective cohort studies: the Copenhagen City Heart Study and the Copenhagen General Population Study. All had telomere length measured by quantitative polymerase chain reaction and the genotypes rs1317082 (TERC), rs7726159 (TERT), and rs2487999 (OBFC1) determined. The sum of telomere-shortening alleles from these three genotypes was calculated. We conducted Cox regression analyses and instrumental variable analyses using the allele sum as an instrument. All statistical tests were two-sided. Among 7607 individuals who died during follow-up (0-22 years, median = 7 years), 2420 had cancer and 2633 had cardiovascular disease as causes of death. Decreasing telomere length deciles were associated with increasing all-cause mortality (P trend = 2*10(-15)). The multivariable-adjusted hazard ratio of all-cause mortality was 1.40 (95% confidence interval [CI] = 1.25 to 1.57) for individuals in the shortest vs the longest decile. Results were similar for cancer mortality and cardiovascular mortality. Telomere length decreased 69 base pairs (95% CI = 61 to 76) per allele for the allele sum, and the per-allele hazard ratio for cancer mortality was 0.95 (95% CI = 0.91 to 0.99). Allele sum was not associated with cardiovascular, other, or all-cause mortality. Short telomeres in peripheral blood leukocytes were associated with high mortality in association analyses. In contrast, genetically determined short telomeres were associated with low cancer mortality but not with all-cause mortality. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: