Methylation clocks have found their way into the community of aging research as a way to test anti-aging interventions without having to wait for mortality statistics. But methylation clocks are only useful for this purpose if aging is an epigenetic program, and most aging researchers still resist this paradigm. Just this year, some researchers have noticed this tension, and they have proposed that the methylation changes measured by epigenetic clocks are random drift, not under the body’s control. Below, I show why they are wrong about this, and why it may not even be possible to build an epigenetic clock based on unprogrammed drift.

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Beginning in 2013, I took an early interest in methylation clocks because of the intrinsic link to programmed aging. It had became clear that gene expression was a powerful way to understand growth, development, and metabolism. Every cell in the body has the same genes, and these do not change over a lifetime. It is switching genes on and off in particular places and particular times that is responsible for all the essential processes of life.

Thus the default assumption is that gene expression = epigenetics is a tightly-controlled process. Genes are turned on when and where they are needed, and turned off otherwise. It was natural to think that the timing of gene expression to implement growth and development continued to implement an aging program later in life.

So, when Steve Horvath taught us that genes are turned on and off over a lifetime with the regularity of clockwork, I was enthusiastic about potential of the technology to evaluate anti-aging interventions. Not only that, I interpreted the regularity of gene expression changes with age as evidence for an aging program, and I said so.

The Horvath clocks were useful, and have been adopted. Some people were aware that the technology itself was a contradiction to their theoretical belief that aging is not (“cannot be”) under the body’s control. This tension between theory and practice has been simmering for 10 years, and just this year a proposed reconciliation has emerged: Three papers on stochastic methylation changes have been published in 2024. Their thesis is that methylation clocks are measuring loss of focus in the methylation pattern, rather than a directed process. “Dysregulation”, “stochastic change”, and “epigenetic entropy” are other names for the same idea.

My view is that these articles are ideologically motivated, and unconvincing. Yes, some of the changes in methylation that occur with age seem to be random and undirected. But the Horvath clocks were built on methylation sites that change most reliably and consistently over a lifetime. Sites that change randomly are less useful, and are left out of the algorithms. We have every reason to believe that their directed change with age is under the body’s control. 

I have written previously that there are two possibilities for the purpose of directed methylation changes over time. Type 1 changes are destroying the body, tending gradually toward programmed death. Inflammation, autoimmunity, and apoptosis are dialed up, while repair and quenching of ROS are dialed down. Type 2 changes are the opposite: the body perceives that it is in trouble and turns on repair programs. Type 2 changes are part of an ancient defense program, not explicitly timed to age, but reliably timed to the extent that the accumulation of damage (to which they respond) is reliably timed. 

Distinguishing Type 1 from Type 2 methylation changes remains a major challenge. Both are occurring simultaneously, and they are difficult to disentangle. But if we wish to use methylation clocks to measure the anti-aging benefits of an intervention, Type 1 and Type 2 should be counted in opposite directions. “Younger” according to Type 1 means less self-destruction, and this is good. “Younger” according to Type 2 means less repair, and this is bad. There is the danger that an intervention might interfere with the body’s repair, probably shortening life expectancy, but if our methylation clock includes Type 2 sites, the intervention might be scored as beneficial.

 

Stochastic clocks

Three research articles have been published this year promoting the idea that epigenetic clocks are based on methylation changes with age that are primarily stochastic. In other words, they are dysregulation, loss of information. My purpose in this column is to expose the fallacies in their methods. I believe that the way sites are selected for the clocks strongly selects for directed, non-random changes.

Entropic theories of aging have been discredited since the 19th century

Len Hayflick was a reigning sage of the aging biology community, and the most prominent proponent today of the theory that aging reflects an inevitable accumulation of entropy. Entropic theories of aging have never been coherent, but they are nevertheless experiencing a resurgence in recent years, primarily because neo-Darwinist theories of aging are all failing. I find this ironic, because the neo-Darwinist theories arose precisely because scientists realized that the Second Law of Thermodynamics does not apply to living systems. 

There is no necessity for entropy of living things to increase, because living things are constantly taking in low-entropy food and dumping high-entropy waste products into the environment. In fact, living things accumulate information as they grow. All of life is an end run around the Second Law of Thermodynamics. Therefore, aging needs an explanation from evolution, not from physics.

The first neo-Darwinst theory to be proposed (Medawar, 1952) was the idea of a “selection shadow”. The natural world is highly competitive, and no animals in the wild live long enough for their fitness to decline from age. This was a plausible idea when it was proposed, but field studies in the 1990s demonstrated that it is incorrect; indeed, many animals in the wild live long enough to die of old age. Half a century after Medawar, Ricklefs, Promislow, Bonduriansky, and Jones et al independently compiled evidence that, in the natural world, there is no selection shadow. 

The second neo-Darwinst theory (Williams, 1957) was that aging is a side-effect of genes for fertility. Fertility is so important to natural selection that fertility genes are selected even at the expense of deterioration and early death. There are many observed contradictions to this theory

• “Aging genes” have been discovered that have no fertility benefit. (For example)
• David Reznick and others have demonstrated natural genetic variants that increase fertility and longevity simultaneously
• Williams didn’t know about epigenetics in 1957. The idea that genes are routinely turned on when needed and off when they are not undermines Williams’s thesis that the body is “stuck with” genes when they are no longer useful.

The third neo-Darwinist theory was published by Tom Kirkwood (1977). He theorized that both bodily maintenance and reproduction require a lot of food energy; Aging results from the body’s need to compromise and short-change the repair budget. This is the most insupportable of the 3 theories. Kirkwood was probably unaware in 1977 that animals live longest when they are starved; but he certainly knew that females spend a lot more energy on reproduction than males, and they generally live longer. I don’t blame Kirkwood for publishing this idea as a young student, but I think it’s hard to explain why he has clung so fast to a failed theory 37 years on. 

The only solution to this dilemma is to abandon neo-Darwinism and adopt a perspective of multi-level selection (MLS). Neo-Darwinism asserts that all natural selection is individual selection, and that fitness of a community or a population is not a relevant concept. MLS asserts that fit individuals need cooperative communities and stable ecosystems, and all these levels can experience evolutionary selection. This is what I have argued since I entered the field 25 years ago. 

To avoid this deep re-thinking of evolutionary dynamics, many aging researchers re-cast the old entropic theory in terms of biological information. “Information” in general is the opposite of entropy, and it may be acquired freely in the form of food energy (animals) or sunlight (plants). But biological information is specific to the organism. Its source repository is in the DNA. Genetic information can be lost to somatic mutations. Epigenetic information can be lost when methylation and de-methylation enzymes experience occasional failures. This appears to be a one-way street — information lost cannot be recovered.

My view: This is true in theory, but in reality the body is well adapted to assure that its function does not suffer significantly from somatic mutations. [See Hayashi and Chapter 3 from my academic book]. DNA repair is robust. There are two copies of every chromosome, and there are molecular mechanisms that can not only repair breaks in DNA, but can respond to damaged DNA in consultation with the homologous area of the sister chromosome. Unlike genetic information, loss of epigenetic information need not be irreversible; the information remains rooted in the methylation dynamics that can recreate patterns lost to epigenetic drift. 

This is the context for the three papers this year which have proposed that the epigenetic changes underlying methylation clocks are stochastic.

The three papers

One

The first of these was [Meyer & Schumacher 2024]. It is a data-free proof-of-concept. The study uses simulated (computer-generated) methylation data to demonstrate how one would go about constructing a methylation clock based not on directed methylation changes but on loss of methylation information.

The reproducibility of accurate aging clocks has reinvigorated the debate on whether a programmed process underlies aging. Here we show that accumulating stochastic variation in purely simulated data is sufficient to build aging clocks.

So far, I have no problem with this. I agree that creating a clock from stochastic loss of information in the epigenome is feasible. See below, where I try to do it.,,,

Although our simulations may not explicitly rule out a programmed aging process, our results suggest that stochastically accumulating changes in any set of data that have a ground state at age zero are sufficient for generating aging clocks.

Yes, they have not ruled out programmed aging, and yes it is possible to create a clock algorithm from stochastic variation. But what is missing is the acknowledgement that all the most popular clocks were created by explicitly looking for sites that change methylation status consistently over a lifetime in a directed way. There is no reason to believe that the demonstration of feasibility has anything to do with the Horvath clocks, and the Horvath clocks, because of the way they were created, are evidence that methylation changes are directed, i.e., that aging is programmed. 

The authors proceed to build a clock around DNA sites that begin life either 100% methylated or unmethylated. In either case, random change can only occur in one direction. In these cases, it is difficult to distinguish random change from directed change. However, this is not what Horvath has done. Most of the sites in the original (2013) Horvath clock and subsequent clocks do not start out at 0 or 100%, so directed change looks far more likely than random change that happens to go in one direction only.

Under the kind of model that Meyer assumes, random methylation and random demethylation are equally likely, so over time the sites all trend toward 50% methylation. In real life, there is no reason to assume that methylation and demethylation are equally likely. In any case, the Horvath clocks contain partially methylated sites that trend toward the extremes with age as well as sites that trend toward 50%.

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Second is from the Harvard lab of Vadim Gladyshev. (Tarkhov et al 2024) is intricate in detail, and, IMO, difficult to follow. It is premised on the explicit assumption that aging is not programmed, and that any changes in methylation with age are either random drift or a response to damage (what I have called Type 2).  They cite Hayflick as a source for their understanding of where aging comes from, blithely ignoring the fact that entropic views of aging were discredited in the 19th century for sound reasons. 

Tarkhov’s thesis is that most epigenetic change with age is stochastic, while the residue is “co-regulated”. How does he define “co-regulated”, and how does he distinguish co-regulated from stochastic CpG’s?

As I read it, “co-regulated” sites are sites within a CpG island that turn on and off together. If the β of a given site is not well-correlated with βs of nearby sites, then change in this site are assumed to be stochastic.

My comment: To the extent that we understand methylation and epigenetics, a fully methylated CpG island turns off an adjacent gene, while a fully unmethylated CpG island turns it on. If this is the whole truth and nothing but the truth, then it would be irrational for the body to turn on some CpGs and not others, so we might regard CpG changes that are not “co-regulated” to be “stochastic”. But I wouldn’t assume that we understand the ways of biology well enough to build a theory around this premise. The cell may well have its reasons for methylating a particular site while leaving adjacent sites unmethylated.

I don’t understand the claim that “…clocks built on the co-regulated cluster of CpG sites may perform worse in the context of chronological age prediction but may be able to better capture the effects of longevity interventions.” If by “co-regulated” he means “Type 2”, then I have argued that Type 2 sites are a confounder for predicting benefits of longevity interventions.

“A more mechanistic understanding of epigenetic aging based on co-regulation may improve performance of epigenetic clocks in evaluating anti-aging interventions.” 

Three

The third and most deceptive of these is [Tong et al 2024]. They ask the question: how much of the computation in the most popular Horvath methylation clocks is attributable to directed methylation changes, and how much of it is stochastic? They conclude that most of it is stochastic. How do they arrive at this conclusion?

• They start with the sites that have already been chosen by Horvath because they change most consistently with age.
• For each of these, they note what direction the site changes with age, and how much methylation of that site changes with each passing year.
• They feed that information into an algorithm that “randomly” adds or subtracts methylation to each particular site at the appropriate rate. The process is “random” only in that the exact timing of each methylation addition or subtraction is random. But the probability has been pre-adjusted so that the average rate will match the measured rate according to the Horvath clock.
• Wonder of wonders! Somehow their “random” simulation manages to match the Horvath clock pretty well.

Am I dismissing this model too lightly? My point is only that the model is far from a random process. The title of the article and its stated conclusions are not warranted. 

A truly stochastic aging clock

The genome really does lose epigenetic focus with age, and it should be possible in theory to develop a clock algorithm on this basis. The way to do this would be to choose methylation sites that do not change, on average, from birth to death. There are many such sites. The clock would be based on the RMS average deviation (in either direction) of an individual’s methylation from “where it is supposed to be”.

I tried to do this last month. I have a small, older database in my computer, with methylation profiles of 278 individuals with an age range from 2 to 92. I spent just two days on the exercise, and the results suggested to me that the implementation of a stochastic methylation clock is not useful in practice. Here are the details, for those who are interested.

I searched a universe of 480,000 sites for those that met the following conditions:

• They had βs that stayed the same, on average, over the adult lifespan.
• Those average values were not close to 0 or to 1.
• The variance of the logistically-transformed βs among the oldest quarter of subjects was at least 100 times as large as the variance among the youngest quarter of subjects. There were 2300 such sites. (Logistic transform is defined as logit(β)=ln(β/(1-β)).)

From these 2300 sites, I constructed a clock. I reasoned that for each of the sites there was an average logit(β) where they “belonged”, and the the squared difference from this average represented drift which, by hypothesis, should increase with age. So my clock was based on the sum of squared differences of logit(β) from the average value.

I was surprised and disappointed that the correlation between this sum and chronological age was only 0.51, not high enough to be useful as a predictive clock. The RMS difference between predicted age and actual age was 17 years. 

Before discarding the idea, I gave the method an extra benefit which was likely not to be sustainable when generalized. I redefined “ideal” for each logit(β) as the average of children. I calculated a squared departure from that average for each age, and calculated a correlation (for each CpG) of the squared departure with chronological age. The best correlation was only 0.25. I calculated, for each age, the sum of squared departures, now restricted to just the best 1,000 out of 23,000 sites. Since these 1,000 were chosen explicitly for their high performance, it is likely that some or most of them performed well just by chance; hence it is likely this methodology would not be sustainable when translated to a different data set. Nevertheless, the average of the “best 1,000” did not perform any better than the average over the full 23,000.

I concluded that this methodology does not appear to be promising.

The bottom line

Gene expression is among the most tightly controlled biochemical processes in any organism. It is natural to assume that changes in gene expression are under the body’s control, absent powerful evidence to the contrary.

Methylation clocks have always been designed around the CpG sites that change most reliably and consistently over time. While there is stochastic variation as well as directed change over a lifetime, the extant clocks are all based on the latter. 

The recent publications claiming that methylation clocks are based on stochastic change are ideologically driven. They have had to redefine “stochastic” to implement their models. The clocks that they construct and call “stochastic” have directed change built into their assumptions. 

I have done a preliminary exploration for a clock algorithm that is truly based on stochastic changes in methylation. I find that the results are far less accurate than clocks based on directed methylation changes.

My title is taken from a well-known but less-well-authenticated quote from Max Planck: “Science progresses funeral by funeral.” 

Planck discovered the quantum principle in 1899, before the the physics world was ready for it. Eventually he was hailed as a visionary; but we can imagine his frustration when the smartest physicists in the world were refusing to consider his ideas because they were an unthinkable departure from the way they thought the world worked. Planck waited more than 20 years for his vindication.

Last week, we lost Len Hayflick (1928 – 2024), a giant in the field of biology of aging. As a young researcher in the 1960s, Hayflick discovered that cells in culture had a finite lifetime. They would replicate for a few hundred generations, then stop replicating. This contradicted a dogma (attributed to Alexis Carrel) that had been prevalent for more than forty years, which said that even though animals and plants have finite lifespans, their cells were, in principle, immortal. 

At the time of Hayflick’s discovery, DNA was relatively new, and the fact that chromosomes had protective DNA tails, called telomeres, was not yet known. Within 15 years, the full story came out: When DNA is copied during cell replication, a piece of each end is left uncopied. Related to this, the DNA includes a buffer of meaningless, repetitive DNA at each end so that no information is lost when the cell replicates. However, eventually the telomere is exhausted and if the cell were to replicate further, information in the coding DNA would indeed be lost.

This could, in principle, be an existential threat to all life. But never fear! Nature has provided a solution, in the form of an enzyme called telomerase.

The curious thing is that telomerase is turned off by default, allowing the telomere to shorten, with life-threatening consequences. You remember from basic biology that there are two modes of cell replication, called mitosis and meiosis. Mitosis is just the cell splitting in half, each half growing anew Meiosis begins with the merger of two cells, followed by an unnecessarily complex sequence of divisions and recombinations. Another word for meiosis is “sex”. 

It is a fact of biology going back to the single-celled eukaryotes (ciliates) that telomerase is switched on only during sex, but not during mitosis. What is this about? A few years ago, I created a computer model to demonstrate how this withholding of telomerase might have evolved as a way to prevent cells from the danger of unrestrained reproduction without sharing genes. Yes, evolution had to coerce cells, compelling them to have sex. Coercion seems to be less necessary for bonobos.

The evolutionary significance of telomere dynamics

My point is that telomerase has very low metabolic cost and withholding it has very steep consequences for what is usually called “fitness”. Withholding telomerase, allowing cell senescence to happen after a few hundred generation, is the earliest example of programmed death, and to this day, telomere shortening is a factor in the aging and death of higher animals, including ourselves.

Thus, telomere attrition is the clearest evidence that aging is not a failure of evolution but an active biological function. Aging has been part of evolution’s plan for life since before there were multi-celled plants and animals.

This conclusion is rightfully an important part of Hayflick’s legacy, a clear implication of his signature discovery. Young Hayflick had the temerity to defy the academic establishment and to pronounce what was at the time a radical reversal of scientific dogma. But he never embraced the obvious implication — 

• Cells die of telomere attrition
• Telomere attrition is readily avoidable, using an enzyme that is encoded in every eukaryotic cell
• Therefore, the cells do not want to avoid their date with the Grim Reaper. Death on a schedule a programmed biological function.

Hayflick espoused an entropic theory of aging

Programmed aging was part of Hayflick’s legacy, but it was not part of his professed beliefs. In the last 20 years of his life, he was an active proponent of entropic theories of aging.

This was not a radical but a reactionary position. Entropic theories of aging had been propounded and rejected in the 19th century. It was clear to Darwin and later to August Weismann that physical theories could not explain aging, and that an evolutionary understanding was necessary. 

The Second Law of Thermodynamics states that entropy must always increase in a closed system. But living things are not closed systems. They take in free energy from food or sunlight and use it for growth, development, and repair. They dump waste entropy into the environment, and thus they can accumulate order without defying any physical law. Machines must wear out, but not so living organisms.

In the period 1952-1977, three evolutionary theories were proposed to explain aging. First was Peter Medawar’s theory of a selection shadow — animals don’t live long enough to die of old age, so natural selection has no chance to act on old animals. Second was George Williams’s theory of antagonistic pleiotropy — genes selected for their enhancement of fertility early life have a corrosive effect on the metabolism over time. Third was Thomas Kirkwood‘s theory of the disposable soma — animals must budget limited food energy between fertility functions and repair functions, and the repair is performed imperfectly. 

Hayflick eschewed the accepted evolutionary theories, reverting to a discredited theory from the past. Entropic theories are inherently related to information since, in physics, information is the opposite of entropy. But biological information encoded in the DNA provides a new twist. This is not generic information such as can be provided by negentropy from the environment. Biology depends on DNA information that is specific to each individual and its species. If DNA information is lost, it cannot be replenished no matter how much free energy comes in in the form of food.

Abstract: The belief that aging is still an unsolved problem in biology is no longer true. Of the two major classes of theories, the one class that is tenable is derivative of a single common denominator that results in only one fundamental theory of aging. In order to address this complex subject, it is necessary to first define the four phenomena that characterize the finitude of life. These phenomena are aging, the determinants of longevity, age-associated diseases, and death. There are only two fundamental ways in which age changes can occur. Aging occurs either as the result of a purposeful program driven by genes or by events that are not guided by a program but are stochastic or random, accidental events. The weight of evidence indicates that genes do not drive the aging process but the general loss of molecular fidelity does. Potential longevity is determined by the energetics of all molecules present at and after the time of reproductive maturation. Thus, every molecule, including those that compose the machinery involved in turnover, replacement, and repair, becomes the substrate that experiences the thermodynamic instability characteristic of the aging process. However, the determinants of the fidelity of all molecules produced before and after reproductive maturity are the determinants of longevity. This process is governed by the genome. Aging does not happen in a vacuum. Aging must be the result of changes that occur in molecules that have existed at one time with no age changes. It is the state of these pre-existing molecules that governs longevity determination. The distinction between the aging process and age-associated disease is not only based on the molecular definition of aging described above but it is also rooted in several practical observations. Unlike any disease, age changes (a) occur in every multicellular animal that reaches a fixed size at reproductive maturity, (b) cross virtually all species barriers, (c) occur in all members of a species only after the age of reproductive maturation, (d) occur in all animals removed from the wild and protected by humans even when that species probably has not experienced aging for thousands or even millions of years, (e) occur in virtually all animate and inanimate matter, and (f) have the same universal molecular etiology, that is, thermodynamic instability. Unlike aging, there is no disease or pathology that shares these six qualities. Because this critical distinction is poorly understood, there is a continuing belief that the resolution of age-associated diseases will advance our understanding of the fundamental aging process. It will not. The distinction between disease and aging is also critical for establishing science policy because although policy makers understand that the funding of research on age-associated diseases is an unquestioned good, they also must understand that the resolution of age-associated diseases will not provide insights into understanding the fundamental biology of age changes. They often believe that it will and base decisions on that misunderstanding. The impact has been to fund research on age-associated diseases at several orders of magnitude greater than what is available for research on the biology of aging. There is an almost universal belief by geriatricians and others that the greatest risk factor for all of the leading causes of death is old age. Why then are we not devoting significantly greater resources to understanding more about the greatest risk factor for every age-associated pathology by attempting to answer this fundamental question—“What changes occur in biomolecules that lead to the manifestations of aging at higher orders of complexity and then increase vulnerability to all age-associated pathology?” [Ref]

We read from Len’s tone that, even late in life, he perceived himself as a radical. He was perceptive enough not to fall for the flawed tradeoff theories of Williams or Kirkwood. But right here in the abstract, he re-asserts Medawar’s reasonable but discredited idea that animals do not age in the wild (“probably has not experienced aging for thousands or even millions of years”). Evidence against this idea had been accumulated (independently) by Promislow, Ricklefs, and Bonduriansky. 

Also in this abstract is the self-contradictory idea that the body is perfectly capable of retaining biomolecules with perfect fidelity up to the age of sexual maturity, but these same molecules in the same body inevitably degrade beginning immediately thereafter. This is not logical and it is also not true. Humans and other animals begin their exponential (Gompertz) increase in mortality risk before puberty, defying the theoretical prediction of Williams as cited above.)

Len was a great, lifelong presence in the aging community, but he was wrong about programmed aging. In addition to the Hayflick Limit, there are other reasons we know that aging is programmed, among them:

• Aging in single-celled ciliates cannot be accounted for in any other way.
• The caloric restriction effect and other hormetic adaptations attest that the body is capable of attenuating aging when stressed, so certainly the body would have the same capability when unstressed.
• Semelparity offers obvious examples of programmed death.
• Genes that cause aging have been identified in all lab animals where we have looked for them. Disable the gene and the worm lives longer.

Len got the most important thing right: Medical research has been inexcusably focused on etiology of individual diseases — cancer, cardiovascular, and dementia — even as it is clear that all of these have a common underlying cause in the potentially preventable changes that our bodies undergo with age.

 

Do populations in nature self-regulate? I believe so, and have adduced evidence from field studies and from computer simulations. Indigenous human societies, too, effectively kept our numbers in check for our first million years during which people were part of nature. Now people have moved on from nature, and we’ve lost the intuitions that helped us to regulate our numbers. Do we need a global government that surveils our bedrooms and mandates selective abortions? No — this is a cure worse than the disease. What we need is a return to the attitudes and sensitivities that enables us to live in harmony with Gaia.

In the 21st century, I have written that ecosystems are self-regulating— not via some invisible hand that creates homeostasis out of selfishness, but by evolved individual behaviors that dampen population explosions and prevent population crashes.

Sixty years ago, a British naturalist with far more cred than I’ll ever have said the same thing, and he was canceled by an academic establishment that brooks no dissent. They theorize that selfish genes are the be-all and end-all of evolution, and they ruled the province of evolutionary science with an iron fist through the second half of the 20th century. From their perspective, fitness consists in leaving more offspring than your neighbors. The idea that natural selection could lead to voluntary limits on reproduction is (for them) a non-starter.

And yet, population control is an essential feature of ecology. The truth is that birth control and “death control” in the form of lifespans limited by aging are crucial to the very survival of ecosystems. (The origin of aging as a mechanism of population stabilization has been the subject of my principal contribution to the literature of evolutionary ecology. My book)

The mechanisms of population control in animal species are widely studied and discussed — though it is taboo to point out that they obviously violate the “selfish gene” paradigm. The most common mechanism is territoriality. A bird family or a pack of wolves will hold its territory and prevent others from encroaching, thus preserving a generous food supply for itself and its kin, while keeping out the competition.

It is easy for Darwinian fundamentalists to understand the motivation of the selfish, hoarding behavior. What they can’t explain is why other birds or wolves go along with it. Why aren’t there more fights to the death, considering that 100% of a challenger’s Darwinian fitness hangs in the balance?

But birds and even tigers seldom fight. There is a legendary study by Stewart and Aldrich [1951], who found that for every mating pair of songbirds in a nest, there are a dozen or more birds cruising the periphery, waiting in the wings, so to speak, for a vacancy so they can build a nest. Somehow, the birds have all agreed to keep the breeding population constant, generation after generation, even as the non-breeding population waxes and wanes and even crashes. It’s a marvelously effective system for ecosystem homeostasis, but the mystery is how and why the birds agree to be bound by the rules. In particular, the majority of birds submit without protest to a convention that has zeroed out their Darwinian fitness.

Lori Stevens [1989] described beetles that cannibalizing their young under conditions of overcrowding.

In a famous experiment with Mouse Utopia, John Calhoun provided everything that his rats (later mice) needed to live — plenty of water and food, exercise wheels and playgrounds, in an environment free of disease and predators. Only living space was limited. Time after time, he watched the population expand exponentially, until these highly social animals became highly anti-social. They fought, bit and scratched, failed to protect their young, and eventually the entire colony collapsed to zero — all while the experimenters continued to provide an abundance of food for everyone.

Animals understand ecology

Back in 1968, just before it became taboo to write such a paper, Stonybrook ecologist Larry Slobodkin wrote “How to be a Predator”. The title was ironic, because his conclusion — backed by both mathematical models and common sense — is that the most important thing for a predator is to keep the population of prey near its maximum. It is tempting for any individual to take more than his share of prey, to use the extra energy to create more offspring, and thus to advance the interest of his “selfish genes”. But what if he succeeds? Then his offspring increase exponentially, and they come to dominate the predator population in just a few short generations. Then they find themselves competing with their own greedy cousins for a dwindling prey population. Mass starvation is unavoidable.

Can we be surprised that evolution learned this lesson early and often? Any population of animals that shares a common food source is forced to cooperate in order to keep their numbers under control. Failure to obey is punished by extinction, and extinction is the ne plus ultra of natural selection. This is a language that even neo-Darwinist dogmatists should understand. But many of them consider every evolved altruistic behavior to be a deep mystery.

Early humans

Curiously, the means by which human groups maintained population homeostasis for our first million years on the planet are less well understood. If you ask an anthropologist how indigenous cultures kept their populations in check, he will probably answer, “war”. No doubt, there is plenty of carnage in human history as we know it, but the history we know is less than 1% of man’s tenure on the planet. We know precious little about earlier human cultures, and in the absence of specific knowledge my guess would be that humans, like animals, had instincts that told them when reproduction would be counterproductive for the community. Various tribal cultures all had unwritten rules about who could reproduce, when, and how much. Human groups are imaginative beyond our imaginings, and it is likely (IMHO) that each tribe had its unique traditions and covenants that contributed to population stability without excessive violence.

I’m personally attracted to the idea that before Columbus, indigenous Americans had learned to be stewards of nature, to manage prolific ecosystems that provided their needs without the monoculture and livestock technologies that predominated in Eurasia. [Charles C. Mann]

Whatever it was that enabled tribal populations to thrive in harmonious relationship to diverse ecosystems, this knowledge has been lost, along with the motivation and the will to maintain harmony with nature as a condition of human existence. Human population is out of control these last several hundred years. Combined with an exploitative mentality and industrial means of destruction, exponential population growth is an existential threat to humanity. But there is no way out of this dilemma that does not violate our deeply held convictions about human rights and autonomy over our own bodies. Or so it seemed…

Eugenics

In Britain and America in the early 20th century, liberal intellectuals all received Darwin’s memo about the necessary pruning of the weak, and they realized that that was no longer morally acceptable to our civilized sensibilities. How then to preserve and even improve the human gene pool? Eugenics was part of the credo of the time: the state must take control, and apply meritocratic principles to determine who is allowed to have children. Then Hitler came along and gave eugenics a bad name.

In the 1970s, Paul Ehrlich and the Club of Rome warned us of an impending “population bomb”, timed to destroy humanity via starvation before the century was out. Population control again became thinkable. Then Mao tried it, with results that were wildly unpopular, even in the context of a docile Chinese culture that was conditioned to obey central authority. China is living today with the legacy of the one child policy. There are not enough women for the men who wish to marry, and it is projected that there will be not enough working people to support the generation coming to retirement age. But the results of the one-child experiment were not all bad. A generation of Chinese had excess income, in part because they did not have large families to support, and this contributed to an unparalleled wave of prosperity that lifted a billion people out of poverty. Freed from having to grow rice for a burgeoning population, peasants migrated to the cities to build an industrial powerhouse.

Some of us trust government more than others, but almost everyone is horrified at the prospect of a technocratic committee deciding who is allowed to have children, and when, and how many.

I like to tell the story of Sir Ronald Fisher (1890-1962). He was a brilliant man who integrated Mendel’s genetics with Darwin’s selection to create a mathematical theory of evolution that stands to this day. And along the way, he contributed most of the statistical methodology that is widely used in biology today, and also in medicine, astronomy, paleontology, etc.

What motivated Fisher more than anything was a passion for eugenics. He was convinced that his own peers of the British aristocracy were not having enough children, while the hoi-polloi were having too many, and that British culture would not survive the dilution of the gene pool. He fathered eight children. Fisher wrote just one book; the first half has served as text for a quantitative theory of evolution, and the second half is an embarrassing, racist screed.

Fisher’s evolutionary theory was the selfish gene. The term was not coined until Richard Dawkins wrote a popular book 40 years later, but the ideas were all Fisher’s. Fisher’s evolution is sometimes called “population genetics” or “neo-Darwinism”. It is a paradigm that turned evolution into a testable, quantitative theory; but it also became a rigid dogma that still holds the field back today. The Chinese translation of my book is called 无私的基因, The Unselfish Gene.

Tragedy of the Commons

In 1968, ecology professor Garrett Hardin captured the spirit of his time in a Science Magazine essay called The Tragedy of the Commons. In a mythic village where everyone’s sheep graze together on an ample acreage of lush grass, each farmer is motivated to increase his own herd size. And when the grass becomes thin and the sheep grow leaner, the motivation to increase each farmer’s individual share only grows stronger. The situation quickly escalates to the point where all the sheep starve.

Therefore (Hardin concluded), all it takes is for everyone to be pursuing his own enlightened self-interest in an enlightened and peaceful manner, and the human experiment will proceed to a suicidal end.

How many people can the Earth support?

I don’t pretend to know the answer, and I’m suspicious of anyone who tries to calculate a number. I have written about the possibility that transformative energy technologies are already known to some subset of the human population. Even without free energy, we might cram our apartment buildings ever higher and denser and grow hydroponic soy protein in our photovoltaic deserts. You might agree with me that this isn’t the world we want to bequeath our grandchildren.

Laws restricting abortion have inflamed some of the most divisive passions in American politics. Can you imagine if the Federal government tried to mandate abortion? You would have the entire Woke establishment and a feminist army lining up alongside the Pope and the Christian Right to say NO!

But we live on a finite planet.

Optimism

With clear, logical reasoning, it’s easy to convince ourselves that overpopulation is a hopeless problem. So, let me offer some fuzzy, illogical reasoning…

Urgency — It’s long past time to prevent damage to global ecosystems — we must begin ASAP to pick up our garbage and allow them to recover. We can do this much more quickly than we can reduce the world’s population. For example, Amory Lovins has showed us how to do this in the energy sector. We need to rein in the excesses of capitalism in externalizing the costs of doing business. The principal obstacle is the extent to which “democratic” governments have been captured by corporate influence. Our failure to prevent toxic waste and wasteful consumption is a failure of democracy, not a problem of overpopulation.

The Malthusian death spiral — 200 years after Malthus, world population has grown eightfold, but we are better able to feed the world than we were in 1800. We have inexcusable starvation in large regions of the world, but this is a tragic result of inequitable distribution and imperial exploitation, not a technical problem of food production. Counting just the grains that are stored in mega-silos and sold on world markets, we produce almost twice as many calories as 8 billion people need.

There is a myth that the “green revolution” has saved humanity from starvation. But mechanized agriculture, chemical pesticides, and factory farms are efficient only when accounted in dollars. Agribusiness has optimized for yield per man-hour, not yield per acre. Small farmers using traditional and sustainable methods could further increase yields. [Vandana Shiva]

The win-win path to population control — In Russia, Japan, and Italy, fertility is below replacement, and that is concerning to people who cherish the rich cultural traditions of these nations. Some of the reason is despair for the future. But the most promising reason for declining fertility is that people feel secure in their future and fulfilled in their lives outside the family.

Fertility explodes in controlled, exploited populations. Fertility declines when people have a social safety net to care for them in their old age. Fertility declines in stable, prosperous economies. Fertility declines when women have fulfilling careers outside the home. Bill Ryerson has devoted his career to slowing population growth by educating and empowering women.

Let’s continue to work toward more livable communities, especially for women, and the “population problem” just might take care of itself.

Vaccines are all designed to immunize against a specific disease. But vaccines also have important non-specific effects. Danish epidemiologist Christine Stabell Benn, MD has devoted her career to studying these effects.

Link to TED talk

Last week, Dr Stabell Benn was interviewed for DrJay Bhattacharya’s podcast.

Everything below (except where signed by my initials) is sourced from this interview.

Innate and adaptive immune system

The innate immune system works via inflammation in response to invasion, and also uses natural killer cells and phagocytes that engulf and dissolve invading organisms.

The adaptive immune system works by producing memory B cells that respond to a specific protein from a specific pathogen. These cells stick around for decades and are ready to multiply exponentially when a new exposure is detected. T cells then come along to attack the pathogens previously tagged by B cells.

Invertebrates have only innate immune systems. Vertebrates (fish, reptiles, mammals, birds, amphibians) all adaptive immune systems in addition.

Vaccines have been designed and tested based on their effect on the adaptive immune system because the adaptive immune system has antibodies that we can measure.

We used to think that the innate immune system was dumb and primitive, while the adaptive immune system was called “adaptive” precisely because it can learn from early exposures to better combat a later exposure to the same disease.

But we now know that the innate immune system is more important and smarter than the adaptive immune system. The innate immune system is capable of learning from exposure, but the “lessons” it learns are less literal, less specific. The innate immune system can learn from one disease to become smarter about fending off other, very different diseases.

Dead and live vaccines

Vaccines based on live, attenuated (artificially weakened) pathogens tend to make the innate immune system smarter and more capable. Their “side effects” tend to be positive, and people inoculated with live, attenuated pathogens are healthier overall, including lower all-cause mortality.

The opposite is true of vaccines based on dead pathogens or based on a single protein from a pathogen (called the “epitope”). They are designed to produce a response in the adaptive immune system, but they teach the innate immune system the wrong lesson. They teach that this invading protein is not associated with a disease, so don’t waste your efforts attacking it. Hence dead virus vaccines tend to make the innate immune system less vigilant.

Live vaccines have a public health benefit. They protect against transmission of the disease. By and large, dead vaccines increase transmission, even if they reduce the risk that a vaccinated person develops symptomatic disease.

Order of vaccines turns out to be important in ways that no one but Dr Stabell Benn noticed. If your most recent vaccine is a live virus vaccine, you are far less susceptible to disease generally than if your most recent vaccine was a dead or protein-epitope vaccine. This has life-saving implications for the childhood vaccine schedule.

Male and female

Girls have different immune systems from boys because they are prepared, someday, to carry a baby with a different genotype from their own. The immune system has to be able to tolerate the presence of a “foreign body” in the womb, and so girls’ immune systems are optimized more for learning, less for a broad, immediate response.

The differential effects of live and dead vaccines are stronger in girls than in boys. For girls, it matters much more that they should receive only live, attenuated vaccines. For boys, this is also a good idea, but less crucial.

Girls have more auto-immune diseases. Boys have more respiratory infections. These differences begin in childhood and persist throughout our lives. [90% of lupus patients are female. — JJM]

COVID is a special case

The mRNA COVID vaccines have been in a class by themselves, producing roughly 100 times more side effects, including death, than the worst vaccines in the past. The mRNA vaccines are not only far more dangerous but also far less effective than vaccines in the past at preventing the illness they were designed to prevent. The vaccines’ protection against COVID fades after just two months, and by 5 months the effectiveness becomes negative, in the sense that vaccinated people are more likely to get the disease than unvaccinated.

As for preventing transmission, the COVID vaccines were never designed to do this, nor were they tested for their effect on transmission before they were mandated for employment, school, military service, etc based on “public health” considerations. One study by me and one study from Harvard School of Public Health have found that vaccination is associated with a higher rate of spread of COVID. — JJM

The reliance on new vaccine technologies as the sole defense against COVID violated everything that we knew about public health. It was a mistake on every front. Repurposed drugs, proven safe in the past, were suppressed while waiting for a vaccine. Then vaccine testing was insufficient and hasty, and was conducted by companies with a financial interest in the outcome. Scientific debate was censored during a time when we needed it most urgently. Natural immunity was ignored, when we know that natural immunity is always superior to vaccine immunity. In fact, the definition of “herd immunity” was changed to exclude immunity of people who had recovered from the disease itself — despite the fact that this had been the basis of herd immunity for hundreds of years of history. Not only did the mRNA vaccines contain no live viruses, they were based on a technology that had previously been shown to be too dangerous for human use. Risk was not stratified by age or sex, even for pregnant women. Vaccines were promoted and even mandated for billions of people at a time when the limited evidence was that they actually increased risk of mortality from any cause. Public health authorities previously had high esteem and a high level of trust, and they have thrown away public trust by their behavior.

Using data published by Pfizer and Moderna from their own studies of the mRNA vaccines, Dr Stabell Benn concluded early that more people were dying in the vaccinated group compared to the unvaccinated group. Taking all effects of the vaccines into account — not just effect on COVID antibodies — the net result of mRNA vaccination was to increase all-cause mortality. (The effect was not large enough to be statistically significant in the trials, where only a handful of people died, but now that billions of people have received the mRNA shots and we have several years’ data in which to look for all-cause mortality, there is no doubt that mRNA vaccines are increasing all-cause mortality. — JJM)

For the adenovirus vaccines developed by J&J and Astra-Zeneca, she found the opposite. All-cause mortality was lower among the vaccinated.  (These were not traditional live attenuated virus vaccines, but they were genetically engineered live viruses, with an artificially-inserted spike protein from the COVID virus. These adenovirus vaccines have been pulled from circulation and are no longer available.)

In another study of the mRNA vaccines, Dr Stabell Benn followed up vaccinated and unvaccinated children, and found that vaccinated children were three times more likely to get colds and flus compared to unvaccinated. Vaccinated children were also more likely to get RSV — a rare disease which is now the object of a new childhood vaccination campaign.

DTaP

The WHO was notified by Stabell Benn of problems with studies affirming the safety of DTaP vaccines (Diphtheria, Tetanus, acellular Pertussis). Ten years ago, WHO commissioned a study to correct these errors, and ten years later no report has yet been issued. Meanwhile, Dr Stabell Benn estimates that hundreds of thousands of girls have died from side effects of DTaP vaccination in Africa alone. (Where is Black Lives Matter when we need them? — JJM)

Personal cost of doing honest studies of costs and benefits

Dr Stabell Benn has had trouble getting her studies published. Sometimes a journal will refuse to send out her studies for peer review, saying only “this study should never have been undertaken.”

She has been the target of attacks, because her findings threaten a very profitable industry. On the other hand, her findings point the way to better, more effective (also more expensive) vaccine programs. “I’ve been attacked equally from both sides. I’m the only person who has been called ‘anti-vaxxer’ and ‘pharma bitch’.”

I became aware during COVID that analysis of vaccine trials was rigged by counting people who died promptly after vaccination as “unvaccinated deaths”, because they had not had the full 6-week interval which their immune systems needed to build immunity. Dr Stabell Benn reported that this is an old trick and it had been used by pharma companies for decades to cook the books on safety of vaccines long before COVID. — JJM

Polio vaccine

What does she think of polio vaccines? The oral polio vaccine is a live attenuated virus, and it has had broad knock-on effects improving public health generally. However, a small percentage of children get polio and are paralyzed after vaccination. This is a trade-off that should be studied so that public health officials can make general recommendations, and doctors can help parents to decide in specific cases whether the risks outweigh the benefits for an individual child.

Which other vaccines are based on live, attenuated viruses?

In addition to the oral polio vaccine, MMR, chickenpox, flu vaccines derive from live attenuated viruses.

Hepatitis B, shingles, HPV, pneumonia, and DTaP vaccines are based on single epitopes, with no live component. — JJM

Of course, generalizations are no substitute for full, independent trials of safety and efficacy for each separate vaccine. Inert placebos are appropriate for efficacy trials, but no placebo should be used in safety trials. Placebos in safety trials are a scam.

The field is full of surprises, and the current trend toward FDA approval of new mRNA vaccines with no human testing, based only on the record of past mRNA vaccines, is criminal. — JJM

A study out of Nanjing University last month brings exosome rejuvenation to the mainstream of researchers with broad new evidence and some speculations on mechanisms. The prominent publication in Nature Aging corroborates and greatly expands results from Harold Katcher’s Mumbai lab. Massive infusions of exosomes from young mice into old improve cognition, endurance, fertility, energy metabolism, heart function, immune function, bone density, cell senescence, and maximum lifespan.

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This current research grew from the Stanford lab of Tom Rando 20 years ago. An old mouse and a young mouse were sewed together so they shared a common blood supply. The old mouse showed signs of rejuvenation and the young mouse showed signs of accelerated aging. Irina and Mike Conboy graduated and set up their own lab at Berkeley, where they demonstrated that it was not blood cells but something in the plasma that was responsible for the effect.

Aging is not something that “happens” to cells. It is centrally orchestrated and information about age is transmitted through the bloodstream. Aging at the cell level responds to signals in the blood, even to the extent that old cells can become young in a “young environment”.

The Conboys worked on removing old signaling from the blood. In cooperation with Dobri Kiprov, there is an ongoing human trial, simply removing blood plasma (but not the red or white blood cells) as a therapy.

Twelve years ago, James P Watson whispered to me, “exosomes”, but I was too distracted to listen.

Seven years ago, Harold Katcher made an inspired guess and quietly conducted research in Mumbai, infusing rats with a blood plasma fraction he would only identify as “elixir” or “E5”. In 2020, his team announced that they had turned two-year-old rats to one-year-old rats according to the Horvath multi-species clock. I wrote about it as a “breakthrough”.

From 2020-23, research proceeded slowly because Harold’s business partner, Akshay Sanghavi, had trouble raising funds for industrial scale extraction of “E5”, and no one else knew what was in it.

Then, last summer, a research group at Smidt Heart Inst in Los Angeles announced promising results rejuvenating rat hearts with exosomes from young rats. Akshay consented to reveal the secret that E5 was exosomes.

What is an exosome? All cells release tiny information packages, wrapped in fats like a lipid nanoparticle. They contain DNA, RNA, proteins, as well as lipids, that communicate both within the body and through the air to other living things.

Would the phenotypic and epigenomic rejuvenation that Harold and Akshay observed lead to dramatically longer lifespans? We had data from only eight rats (all female), and results are not as consistent as we might hope. Median lifespan increased ~20%, depending what you use for a baseline, but curiously the maximum lifespan seems to be extended by 60% or more.

The current paper adds lifespan data from only eight more rats (all male), but the range of metabolic and performance tests is greatly expanded.

Introduction

I predict that this new paper will bring exosome therapy into the mainstream. It begins inauspiciously.

“Aging is an inevitable, time-dependent process that eventually limits the capacity of cells to maintain efficient homeostasis and repair mechanisms…”

“Inevitable”? If they really thought so, then they wouldn’t be doing this research. My guess is that journal editors demanded this kind of language, both because I’ve experienced such editor arrogance myself, and because Chinese researchers are less hypnotized by the Selfish Gene ideology than biologists in the West.

They continue, “Mechanistically, the aging process is predominantly attributed to the progressive accumulation of stochastic damages in cells, organelles and macromolecules.” This is pure dogma. Despite this disclaimer, the method of their experiment is not to address stochastic damage in cells, but to adjust signaling in the organism as a whole.

The fact that aging can be reversed with system-level signaling is a sign that it isn’t just “entropy”, that the body is in control, and, of course, that aging is not “cell autonomous” but centrally coordinated. Harold understands this, and it has been central to his key insights. But the mainstream theorists can’t believe that natural selection would be so perverse, and they remain stuck in older paradigms. Perhaps these Chinese authors were compelled to make obeisance to old British dogmas as a price for being published in Nature. The paper was held up in peer review for an inexcusable 27 months.

Results

Old mice, starting in late middle age = 20 months, were given weekly intravenous infusions of exosomes from young mice for as long as they continued to live.

Median lifespan was increased 12%, and maximum lifespan increased 20%. This reminds us of Harold’s exosome-treated rats, one of which lived much longer than the other seven. Usually we think that median lifespan is more malleable than maximum lifespan. For example, exercise increases median and mean lifespan, but not maximum lifespan. Here we find the opposite. More about this further down this column.

• Exosome-treated mice scored much lower on a frailty scale than untreated mice, but were not fully restored to their young, “zero frailty” state.
• Sperm counts and sperm motility were restored to young values, testosterone levels increased, and treated mice were as fertile as young mice. (all specimens were male)
• Metabolic rate (oxygen consumption) was restored about halfway to youthful values. This reflected activity rates, which were improved but not as active as young mice.
• Ejection fraction and other measures of heart performance were improved, but not to the level of young mice.
• Parts of the brain that atrophy in old mice regrew toward youthful volume.
• Memory, measured by a water maze test, was restored to youthful levels in exosome treated mice.
• Treadmill endurance came back almost to youthful levels.
• Treated mice had lower markers for cell senescence.
• Glycation is a kind of molecular damage that increases in old mice and old humans. Glycation was observed to decrease in treated mice.
• Treated mice restored bone density lost to osteoporosis.
• The Nanjing group did not report results from the Horvath epigenetic clock for rodents, however they did their own analysis of protein expression in various tissues, and showed that the proteomes of treated mice reverted toward younger profiles.
• As a control, young mice were infused with exosomes from old mice. Both their endurance and their memories were impaired. Exosomes from young mice have a rejuvenating effect and exosomes from old mice accelerate aging.

Mitochondria are electrochemical energy sources, and cells typically have hundreds to thousands of mitochondria. Mitochondria can reproduce and renew inside a single cell, but populations of mitochondria decline with age. We literally have less energy as we age. The Nanjing group documented restoration of mitochondrial populations in treated mice, and they assigned special significance to this, speculating that this could be a primary source of other rejuvenation effects. The title of the paper singles out mitochondria as a mechanism. Reading through the rationale, I don’t understand why the authors consider mitochondria to be the root of the exosomes’ anti-aging benefits.

My personal belief is that 20% increase in maximum lifespan — impressive as it is — is just the beginning. Exosome technology has not even begun to be optimized.

Dosage

What is the dosage of infused exosomes compared to the innate exosomes resident in the blood of the mice? The article does not offer this information directly; neither do we have specifications from Harold’s experiments. The best I was able to do was to make an estimate from the size of mice and from the provided information “200 microlitres in a weekly dose” and “1.8 micrograms total protein per microlitre”. From this, I guestimated that the infused exosomes are sufficient in quantity to overwhelm the innate exosomes, perhaps 10x the quantity. From some of Harold’s offhanded comments, I had roughly the same impression.

This large quantity underscores the difficulty of sourcing if this technology is to become widely available to humans. We might need 100 piglets per year per human patient, overwhelming the existing market for pork. Or we might need to develop in vitro technologies for growing stem cells that secrete young exosomes. Or we might be able to target a much smaller dose of exosomes to a part of the body that keeps track of time — my candidate is the hypothalamus.

Or, if it turns out that the activity is due to specific RNAs, we might synthesize them. See below.

Mechanism

“Given the above-observed phenotypes, it remains unclear which component is responsible for the rejuvenating effects of young plasma sEVs.” [sEVs are “small extracellular vessicles”, another name for exosomes.]

The assumption implicit in this statement is that there is just one chemical species in young-derived exosomes that is responsible for all the benefits. When will we absorb the message that living organisms are not like human-designed machines? The association of one protein with one function is vanishingly rare. Almost always, individual functions are not performed by individual chemicals. Rather, there are overlapping complexes of chemicals responsible for what we regard as a single function. Every chemical has multiple functions, and every function is accomplished by multiple chemicals in concert.

Thus, I think it likely that no reduction of the exosome’s complexity will be discovered, and hence there will be no patented single-bullet solutions to aging forthcoming from these experiments. But again, read on…

Exosomes include proteins, RNAs, DNAs, and lipids. All these molecules carry information, and it may be that they all work together to whisper “young” when they are taken up by an aged cell.

The Nanjing authors nevertheless guessed that there might be a few RNA species that did all the heavy lifting and went looking for them with the tools of data mining that have become fashionable among molecular biologists.

They report limited success in identifying crucial RNA species. “Thus, miR-144-3p, miR-149-5p and miR-455-3p encapsulated in young plasma sEVs are the key rejuvenating miRNAs and have the potential to stimulate PGC-1α expression and improve mitochondrial energetic metabolism.” This claim is in fact an overstatement. What they succeeded in proving was that blocking all three of these RNAs with RNA interference was sufficient to negate the benefits of the therapy.

So, yes, the benefit seems to require at least one of these three RNAs, but it also may require a great many more RNAs that are “essential”. And it may be that if any one RNA is missing, others can substitute. After all, the reason that biology is evolved to use these complex, multipronged chemical mechanisms is that they are robust to disruption, much more so than human-designed machines which, typically, can fail catastrophically if a single part is broken.

The study also includes investigation of the role of RNAs in the age-accelerating effect of old-derived exosomes. They report several RNAs from old-derived exosomes that are potential culprits: “Therefore, miR-29a-3p, miR-29c-3p and miR-34a-5p in aged plasma sEVs are the key pro-aging miRNAs with an entirely opposite function to miR-144-3p, miR-149-5p and miR-455-3p encapsulated in young plasma sEVs.” They use RNA interference to block these specific RNAs, and find that the old exosomes lose their detrimental effect.

Questions for research

This work with specific RNAs that are pro-aging and anti-aging suggests that RNA therapies might be devised that bypass the need for animal-derived exosomes. These would be patentable, manufactured products which might attract capital investment. Creating a viable therapy from a combination of RNA and RNA interference products, presumably packaged in lipid nanoparticles, could be an attractive research direction for pharma companies.

As a first step, it would be useful to analyze RNAs of exosomes derived from young and old human donors and to quantify the differences.

Determining the natural source of the exosomes could be crucial. Are exosomes that carry age information generated from a “clock region” in the body, perhaps in the hypothalamus? Or are the most relevant exosomes created by many tissues, all over the body, so that we can think of the whole body keeping track of age and coordinating age information system-wide with exosomes in the blood plasma?

Can the treatment be made more effective if “old” exosomes are removed at the same time that “young” exosomes are added?

Certainly exosomes carry a variety of information unrelated to age. Are there specialized exosomes that carry age information? Or is age information one component of the information in all exosomes?

The authors suggest that a useful step would be labeling donor exosomes with radioisotopes so that they can be traced in the mouse who receives them, and tissues can be identified where they are absorbed preferentially. I would add to this the suggestion that different mice might absorb the exosomes in different tissues, and this might be correlated to the variable effect.

Is it feasible to tag different source organs, so we can determine where the age-relevant exosomes are produced?

Response to exosome therapy as currently conceived seems to be highly variable. Animals who respond best live a lot longer, while others die within the expected time frame. The limited data from Harold and from Nanjing both support this.

This makes me think of the mRNA vaccine technology introduced for COVID. Exosomes are lipid nanoparticles, and lipid nanoparticles are the delivery mechanism of the mRNA products. The present article presents evidence that RNAs are at least part of the mechanism of action.

Some people who took the mRNA shots got protection from COVID, while others got heart disease and still others suffered neurological damage. I think that LNPs and exosomes go everywhere in the body, and their effect depends on where they are taken up.

There is speculation that in response to certain exosomes, cells can sometimes decide, “this is an important message that I want to pass on”. Cells can create similar exosomes and amplify the message, like a virus or a “tweet that goes viral”. This is speculation, but not far from the edge of exosome behavior that has been established. Cells undergoing apoptosis emit exosomes that can signal other cells into apoptosis. [Apoptosis is cell suicide.] It is reasonable to regard viruses as exosomes that have gone rogue and evolved to maximize their own reproduction — to hell with intercellular messaging. It is likely that exosomes are an essential vehicle of cancer metastasis.

Exosomes for the Hypothalamus?

I have written about suggestions by Dongsheng Cai and Claudia Cavadas that there is an aging clock in the hypothalamus. We know that exosomes can sometimes cross the blood brain barrier. I wonder if the rejuvenating effect of exosomes is strongest if they reset an age clock in the hypothalamus. It is within current experimental technique to target exosomes to the brain and ask this question experimentally.

Whether or not the hypothalamus plays a central role, it will be interesting to discover whether animals rejuvenated with exosomes can transition toward producing younger exosomes, so that the rejuvenation becomes self-sustaining.

Directions for translational medicine

One of the (many) promising features of exosome intervention is that it seems to compress morbidity. In other words, healthspan is extended more than lifespan. Whatever our feelings about lifespan, we are all looking to remain healthier, longer.

There remains much to be done before exosome therapy can be widely distributed to humans. First on my list would be a factory scale source of young exosomes. Harold and Akshay have suggested that blood from the millions of young pigs slaughtered each year for meat could be a feedstock. Before this can be realized,

• We need to confirm that exosomes from pigs are able to rejuvenate humans.
• We should check that factory-farmed pigs are not impaired in the quality of their exosomes.
• We need industrial scale separation and refinement techniques for extracting exosomes efficiently from blood.

Summary

These results corroborate a theoretical framework in which the age state of the body is communicated to somatic cells, which obediently can become old or young in response. Exosomes seem to be a prime candidate for the communication mechanism. Their lipid coatings enable them to slip easily through cell membranes, and their cargoes include a diverse array of active signal molecules.

It is my hope that with this new paper, the concept of exosome rejuvenation explodes into the mainstream of anti-aging medicine. There is much work to be done before we have treatments for humans available at scale.

It is extra-promising that healthspan seems to be universally improved, even in animals where lifespan does not change. Another auspicious sign is that maximum lifespan is augmented more than median lifespan in this study as well as Harold’s experiment.

Rejuvenation via exosomes appears to be quite variable across individual mice, despite the fact that these mice are inbred to be genetically identical. This suggests that a lot can be learned from studies comparing mice that respond well to mice that don’t respond at all.

If specific RNAs can be identified that do the heavy lifting, then these might be synthesized artificially. If, on the other hand, the whole package of DNA, RNA, protein, and lipid molecules in an exosome is found to work together, then we will need industrial-scale extraction from animal sources.

If we are really lucky, then targeting exosome therapy to the hypothalamus could greatly reduce the quantity per treatment and the cost of the treatment.

Of the many species that outlive their fertility, lab worms (C elegans) take the cake.  They stop laying eggs after two days, but they can go on to live for two more weeks. Did they miss school the day that the teacher was lecturing on Darwinian fitness? Or perhaps do the elders of their community have a message for their grandchildren?

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In the paper that launched the modern evolutionary theory of aging, George Williams [1957] predicted:

“(6) There should be little or no post-reproductive period in the normal life cycle of any species.” 

Not so long ago, evolutionary scientists thought that human menopause was unique in the biosphere. A whole industry arose explaining the “grandmother effect”: Playing the game they like best, population geneticists would try to concoct circumstances under which a woman’s “selfish genes” could leave more copies of themselves by not reproducing, but instead freeing their bearer to raise her grandchildren, while their mother went out hunting and gathering. 

Then a literature began to appear in which other animals were discovered to outlive their fertility. But this didn’t stop them. Seldom do facts on the ground discourage an enterprising evolutionary theorist.

In several whale species, the female undergoes menopause and continues to live for several decades thereafter [McAuliffe]. Elephants, lions, and baboons experience menopause [Packer], and all these animals might plausibly be argued to relate to their grandchildren.

But some other animals, not so much. As early as 2004, menopause was recognized as a “generalized mammalian trait”. Beyond mammals, hens and guppies both stop laying eggs. Yeast cells stop budding. 

James Vaupel’s research group published a comprehensive survey of animal “life histories” [2013], in which they charted fertility and mortality over a lifetime for dozens of species of plants and animals. The blue lines map fertility, and the grey background curves show survival.

In these 48 plots, C elegans worms, the common lab roundworm, stands out as living most of its life with no fertility at all. Why would that be?

My principal contribution to the evolutionary theory of aging has been to cite demographic stability. Population homeostasis doesn’t come for free; in fact all ecosystems would blow up if their constituent species were evolved to live and reproduce as copiously as possible. In general, aging has evolved as nature’s way to prevent population overshoot, to avoid extinctions that come when populations crash, and thus to keep ecosystems stable and productive in the long term. This is my theory paper, with Charles Goodnight, on post-reproductive lifespan as a demographic adaptation. 

The life cycle of C elegans in nature

C elegans worms are hermaphrodites. For the first day of their lives, they are male, and generate a few hundred sperm cells. Then they become female, and start laying eggs, one by one, fertilized by their own stored sperm. But after two days, they run out of sperm and can’t fertilize their own eggs. They become infertile, unless…

One worm in a thousand is not a hermaphrodite but a male. It lays no eggs, but produces oodles of sperm, which can fertilize the eggs of a hermaphrodite worm. But she has to be very lucky to find a male, because males are so rare. So this is an interesting footnote, but probably irrelevant to the reason worms are programmed to run out of sperm and discontinue fertility. The vast majority of hermaphrodite worms just live out their lackluster lives. Without sex, is life worth living?

When they are not growing in a Petri dish, C elegans worms live on rotting fruit in the wild. One piece of fruit on the ground can feed millions of worms over a period of several weeks. But how are they to get to the next piece of fruit?

If the worm is fat and happy, it lives 2 to 3 weeks. But if the worm is starved, it has a special adaptation. When food is scarce, it can go into a diapause stage called dauer, in which it doesn’t eat and its metabolic rate is very low. As a dauer, the worm can live for many months. The dauer can be ingested by a bird and survive digestion.

Carried by the wind or hitching a ride in a bird’s intestine, dauers are the worm’s plan for getting from one piece of fruit to the next. The “fitness” of a worm is probably better measured by its probability of finding a new piece of fruit than by the number of offspring it produces. Fitness is a property of a worm colony, not of a single worm. The fitness of a colony is related to the number of dauers that are sent out to explore the environment for the next piece of fruit.

Do the math — at several hundred worms per generation, the first three generations will do fine. They will be able to gorge themselves on fruit. But the fourth generation would be hundreds of times larger. The worms would start to grow, only to find that there are so many of them competing for the fruit that none have a chance to grow to maturity. 

This is why the ability to dauer is not just useful but essential to the worms’ collective survival. Larval worms detect food scarcity, and they flip a switch into dauer mode. They cast their future to the wind, or commit themselves to the gut of a hungry bird. 

There is a danger, though, that they might miss their timing. If they are starved right out of the egg, the worm is not yet large enough to form a dauer. But one day out of the egg, the worm is already committed to maturity, and it is too late to dauer. The dauering window is just a few hours long. It is easy to miss.

Here is where grandma can help. In a worm colony that is in its fourth generation, there are already hundreds of thousands of elder worms, post-reproductive but still squirming. These worms saturate the nest with dauer pheromone. The pheromone signals the hatchlings of the fourth generation that, even though it may seem that there’s plenty of food for now, the generation size is so high that the food supply is in danger of being exhausted before they can grow to maturity. The pheromone encourages the young larvae to go into dauer rather than take their chances on maturity and reproduction in present conditions. Dauer pheromone from the oldest worms is a signal both of crowding and of colony age. Exponential mathematics is what is threatening the worm population, and exponential mathematics is what potentiates the enormous increase in dauer pheromone that inform the larvae that their best prospects are to leave home and seek their fortune in the countryside.

This last paragraph is my personal theory, not yet fully confirmed. For a decade, I have been looking for someone to actually measure dauer pheromone from elder worm populations, and no one has taken up the challenge in this form. But from two labs where I have worked, there is partial confirmation. These are in the Beijing National Institute of Biological Sciences (Meng-qiu Dong and Wu Gang) and at Washington University of St Louis (Kerry Kornfeld and Andrea Scharf). 

Evidence for the grandmother worm theory

NIBS Beijing

In 2017, while I was a visiting scholar at the National Institute for Biological Sciences in Beijing, my host, Meng-qiu Dong, was kind enough to design two experiments with grad students Wu Gang and Peng Lei. 

First they raised infertile worms synchronized by age, so they could extract liquid from their growth medium when all the worms were a fixed age. They confirmed that dauer pheromone could be extracted from the medium, and that the quantity peaked for 5-day-old worms. Larvae grown in the medium where 5-day-old worms had lived were more likely to dauer than larvae in a control medium. 5-day-old worms are grandparents, but not yet great grandparents.

Second, they grew worms to old age on half a Petri dish, and then grew a fresh generation of worms on the same Petri dish. As the young worms moved around, they tended to avoid the half of the plate where the old worms had lived (compared to a control dish where no worms had previously grown).This suggests the worms are instinctively avoiding crowding.

Results written up informally here were never published because they are highly preliminary. I think the hypothesis warrants further experimentation.

Wash U St Louis

In the WashU lab of Kerry Kornfeld, my job was to model the worm’s physiology and life cycle based on individual measurements of their growth, food consumption, maturation, dauering, egg-laying, and death. My computer model aggregates the worms’ individual behavior to predict population growth and population crash in a test tube where food (bacteria) is added on any given schedule. In our first published paper, we reported good agreement between the model and population curves as measured with worm counting software. 

But there was one persistent disparity between the predicted population curve and the lab results. With daily feeding, the computer model predicts that population should reach a peak on the 10th day, before declining precipitously and then leveling off with smaller oscillations. But in the lab, the worm population peaked on the 13th day, a lower peak followed by a less calamitous decline.

Secretly, I was delighted. We had been working on this project since 2014, and I had predicted at the beginning that our most significant discovery would be finding that we could not accurately model the worm population without including pheromone communication in the model. I created and refined a computer model for the WashU team that had only individual worm behaviors. But on the side, for my own curiosity, I was adding a parameter that controlled worm communication mediated via pheromones. 

I tested the bare model (no pheromones) by varying parameters within the experimental range and beyond, but the time to the first population peak was very insensitive to all my parameters. This is because the population is increasing exponentially, so between the 10th and the 13th day, the population explodes by almost 100x. 

But one change in the model that is capable of reproducing lab results is to increase the probability of dauering as the population matures. This is indirect but tantalizing evidence that the old worms really are sending a chemical signal that warns the young larvae not to try to grow to maturity, but to dauer instead.

My theory and why it is significant

Chemical signals from the grandmother worms alert a late generation of larvae that they should not try to grow up, but go into suspended animation. This softens the incipient population crash and assures a bumper harvest of dauers that spread through the neighborhood in search of a new home.

My hypothesis is that populations are evolved for homeostasis, to avoid population overshoot and crashes that can lead to extinction. Roundworms in nature are subject to highly variable food availability, and they are highly adapted to protect against population crashes. 

The “selfish gene” model is still the prevailing paradigm in academic evolution. It is difficult to understand post-reproductive lifespan within this paradigm. If confirmed, this would be an example of an adaptation at the population level in which individuals cooperate to guard against extinction of the community. There is an established communication system, even in this primitive animal, explicitly for this collective purpose. 

Spermidine is found naturally in many foods. Blood levels decline with age. Supplementation extends lifespan and healthspan in various species, and lowers mortality in human trials. I have been unable to find toxicity data or any downside to spermidine supplementation, except that the effective dosage may be impractical.

“Consistently across species, extra supply of spermidine prolongs the life span in an autophagy-dependent manner and counteracts age-associated pathologies such as cardiovascular disease, neurodegeneration, and cancer.”
— Guido Kroemer in Science [2018] 

If you haven’t followed Guido Kroemer, you’ll find he’s a wellspring of deep biochemical knowledge. 

Many life extension strategies involve hacking the body’s signaling systems, binding to specific proteins like SIRT or TOR. But spermidine is a small molecule, too simple to have specific signaling properties. Compared to even smaller molecules like H2O2 and NO, it persists in the metabolism long enough to be transported and affect multiple tissues. 

Autophagy is the recycling of damaged organelles (cell parts) and damaged biomolecules, a renewing process that has long been recognized as a necessary process for keeping the body young. Mitochondria are the organelles that generate energy, and ROS are their toxic byproduct. One of the most essential functions of autophagy is the recycling of mitochondria.

Fasting triggers autophagy, and this is part of the reason it is good for us. Longo’s Fasting-Mimicking Diet was designed to promote autophagy. The life extension and other benefits from spermidine are found to result principally from enhanced autophagy. (The way this is determined is to repeat life extension experiments with an autophagy gene disabled, and it is found that spermidine has no benefit [2016].) Spermidine was found to extend lifespan in yeast, worms, flies, and human cell cultures [2009].

Apoptosis=programmed cell death is an essential function for removing senescent and cancerous cells. We need apoptosis, and would be more vulnerable without it, but as we get older, apoptosis develops a “hair trigger”, and cells begin to commit suicide when they’re still healthy and useful. Overactive apoptosis is to blame for sarcopenia – the loss of muscle mass with age. Apoptosis is also implicated in the loss of brain cells that leads to Alzheimer’s Disease. Spermidine dials down apoptosis. 

Spermidine is an anti-inflammatory, and there is suggestion from animal models that it could relieve arthritis [2016]. This study found a stronger benefit for spermine, which is a metabolic product downstream of spermidine.

Foods with the highest concentrations of spermidine include wheat germ, natto and other soy products, mushrooms, some cheeses, and apples. An ounce of wheat germ or 8 oz of cheese contains 10 mg spermidine. Some of our spermidine comes from the gut microbiome. The probiotic Bifidobacterium LKM512 increased blood levels of spermidine in mice.

Spermidine dosage is curiously missing from some of the most important studies. 

In the mouse lifespan study that produced the best results [2017], mean lifespan was extended by 24%. Spermidine was added to the drinking water of test mice at a concentration of 3mM. Translating to humans is not straightforward, but here’s a rough estimate: If you drank 2 quarts a day of water or other fluids with this concentration of spermidine, you would be getting about 1 gram. To get this from food you would eat 6 pounds of wheat germ daily. The highest-dosage supplement pills I can find have 5 mg, so 1 gram per day = 200 pills. For some other supplements, pills of ½ g or a full g are not hard to find. I don’t know if spermidine is intrinsically expensive or if there is another reason that supplement companies gauge the dosage levels so low.

There are no human studies based on supplementation, but some authors have tried to correlate mortality with estimates of spermidine intake from (self-reported) food surveys. Again, they report results by dividing the test subjects into three groups, comparing highest and lowest (estimated) spermidine intake without specifying quantities [2018]. Mortality was reduced by about 25% in the tercile with highest spermidine intake, corresponding to about 3 years of extra life. Because the correlation is computed based on foods, this result may include confounding errors, as the foods highest in spermidine have other health benefits. 

This Japanese study from 2012 looks for factors that affect longevity across 48 Western countries. Because there are so many variables, the uncertainty is great, but dietary polyamines (including spermidine) stood out as a factor decreasing cardiovascular disease burden (r = -0.355, p = 0.007). 

In elders with mild cognitive impairment, there was an indication of possible memory benefits [2018, 2021]. Two studies suggest benefits for immunosenescence as well [2014, 2015]. 

Here’s an excellent short review, also by Kroemer [2019] as senior author. 

The bottom line

I don’t know why it has taken me so long to discover spermidine, or why it is not more frequently discussed by health gurus and biohackers. This month’s Life Extension magazine calls for trials of multiple combined interventions — an idea which I have advocated since 2018. Spermidine is on top of their list of substances to try in combinations.

I plan to self-experiment with high dosages, based on the very limited data from rodents.

Methylation clocks promise to revolutionize testing of anti-aging interventions in humans, by measuring their effectiveness in a few months instead of having to wait years to see if they affect mortality statistics. But there are signs that the clocks we have can be deceptive. I think this is because the clocks capture aspects of aging that are defensive and aspects that are programmed, and there has been no effort to tease them apart. To the extent that the body is defending itself against perceived damage, the clocks are measuring the wrong thing. (This summary probably won’t make sense until you read the details below — please be patient.) 

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I recently submitted an academic study on this subject.

We have a lot of life extension treatments that work in lab animals. Do any of these work in humans? In practice, we need aging clocks to test them, because testing them directly requires tens of thousands of people to be followed over decades for each intervention. I’ve been enthusiastic about aging clocks since Steve Horvath published his groundbreaking analysis in 2013. But recently I’ve realized that the field needs a course correction.

Epigenetic clocks are based on patterns of methylation in our DNA. Genes are turned on and off at different places in the body, at different times of day, and, crucially, at different stages of life. Methylation is the most accessible and easiest to measure of many methods by which the body turns genes on and off. By focusing on the methylation patterns that change consistently over a lifetime, Hannum, Horvath and others who came after them have created computer algorithms that can calculate a “biological age”.  

The idea of “biological age” doesn’t depend on your theory of aging. But the utility of epigenetic clocks in assessing the benefits of putative anti-aging measures certainly does depend on fundamental concepts about aging, about which experts are still divided.

Why does gene expression change in old age?

“Nothing in biology makes sense except in the light of evolution.”
— T. Dobzhansky

1)    If you believe in programmed aging, then the directed changes in gene expression are means of self-destruction. Genes are turned on that increase inflammation, destroying arteries and neurons. Apoptosis is up-regulated to the point where healthy muscle and brain cells are dying. Protective anti-oxidants, DNA repair, and autophagy are down-regulated. All this destruction is accomplished via turning genes on and off. If any intervention sets back the methylation clock, then there is less self-destruction, more repair and maintenance. We expect that the body will live longer if the methylation clock reads a lower age.

2)    If you believe the neo-Darwinist theory that the body cannot be purposely destroying itself, then aging is an accumulation of incidental damage at the cellular and molecular levels. If there are associated epigenetic changes, these cannot be causing the destruction, so they must be a response to the damage. Changes in gene expression as captured in the methylation clocks must be the body’s effort to protect itself with increased immune function, increased autophagy, increased antioxidants, increased DNA repair. If any intervention sets back the methylation clock, then there is less repair and maintenance. We expect that setting the aging clock back to a younger age will actually decrease life expectancy. This insight is counter-intuitive, but, if correct, it changes the logic of methylation clocks. 

For people who don’t believe that aging is an evolved program, the whole idea of a methylation clock is a non-starter. No matter how accurate the clock is, setting it back is counter-productive. Even if the clock is calibrated to markers of health (like the PhenoAge clock) or calibrated to actual mortality (GrimAge), it is still based on the body’s response to damage, and not on the damage itself. Setting back the clock is counter-productive, because it means dialing down the body’s repair and maintenance system. 

Since 2013, there has been a kind of double-think in the world of anti-aging research. Most researchers, at least in public, continue to embrace perspective (2), even as they adopt methylation clocks to evaluate the interventions they develop.

All this is assuming perspective (2). But I’m notorious for being a proponent of perspective (1). From perspective (1), turning back the methylation clock is a good thing. It means that the body’s program of self-destruction is dialed back. So where’s the problem?

In recent years, I have become convinced that epigenetic changes of both types (1) and (2) are taking place simultaneously as the body ages. The body is at war with itself. The self-destructive adaptations listed above are real: dialing down repair and maintenance, promoting systemic inflammation, apoptosis of healthy cells, derangement of the immune system. But the body retains its protective responses, and there are also changes in gene expression that ramp up the repair processes. All the present clocks include a mixture of (1) and (2); this is why we do not yet have a reliable metric for the efficacy of anti-aging technologies. 

What is the evidence that changes of types (1) and (2) are both components of all extant aging clocks?

Some of the best-established interventions for extending lifespan do not affect the major algorithmic clocks, or do so modestly compared to what might be expected from their observed effects on lifespan. Rapamycin extends lifespan of male mice without affecting their methylation age in the Horvath rodent clock. Participants in the CALERIE study who have adopted extreme CR diets showed no significant benefit according to either the GrimAge or PhenoAge clocks.

Conversely, Katcher’s intravenous infusion of exosomes (E5) has a dramatic effect on the Horvath rodent/human clock, reducing epigenetic age by half, but thus far seems to extend lifespan less than the clock setback would imply. The Conboys recently published a withering criticism of the utility of current methylation clocks, and of the machine learning algorithms from which they are created. They report that clocks in common use do not respond as expected to known life-shortening conditions, such as Down Syndrome, inflammaging associated with arthritis, and Parkinson Disease.

Here’s what first clued me in

The GrimAge clock of Lu and Horvath was trained on actual mortality data, using historic blood samples for which the future history of the donors was known. This was a major advance from previous clocks. But one element of the GrimAge development alerted me to the issue concerning type (2) changes, as described above.

Part of the training of GrimAge involved a methylation image of the subject’s smoking history. Smoking is known to accelerate aging and shorten life expectancy. Certain patterns of methylation are associated with smoking, and are also valuable predictors of time until death. These were included in the GrimAge algorithm.

My assumption was that smoking decreases longevity by damaging tissue of the lungs, not by turning on the program of self-destruction. Therefore, if there are methylation changes associated with smoking, they are probably of type (2). In other words, the methylation signature of a smoker who scores as “older” in GrimAge is likely to include activation of more protective pathways than a non-smoker who scores “younger”.

This is an important clue. The methylation profile of a smoker is useful in constructing a GrimAge clock, but it should be counted in reverse. Methylation changes associated with smoking are statistically associated with shorter lifespan, but mechanistically with protection. These changes should have been included in algorithmic clocks with negative coefficients, signaling a younger biological age. This was not how the GrimAge clock was constructed in fact. Methylation changes associated with smoking were included in the GrimAge clock with positive coefficients (simply because they are statistically associated with a shorter life expectancy).

In general, the methylation image of smokers is an example of type (2). All type (2) changes should be counted with negative coefficients in methylation clocks, even though they are statistically associated with older ages and shorter remaining life expectancy.

So it is crucial to distinguish epigenetic changes of type (1) from type (2)

 The story of GrimAge carries a message that suggests ways that methylation changes of types (1) and (2) might be teased apart in algorithmic clocks. Present clocks don’t distinguish between (1) and (2) so presumably the two types of methylation changes are combined in a way we might connote as (1) + (2). The goal would be to create a clock built on type (1) changes alone, or, more speculatively, penalize the clock for type (2) changes, so with the result that the algorithm measures (1) – (2) rather than (1) + (2).

The long-term goal would be to understand the metabolic consequences of each CpG change, separately and in combination, so that a clock could be constructed with full confidence that it scores beneficial and detrimental methylation changes appropriately.

Lacking this understanding in the interim, we might make progress toward distinguishing (1) and (2), by learning from the smoking example. One way to acquire a database of type (2) changes is that animal models might be injected with pro-inflammatory cytokines, and their epigenetic consequences mapped. Since the inflammation is imposed externally, we should presume that the response is all type (2). 

Similarly, the animals’ immune systems might be challenged, or they might be subjected to laceration or small doses of radiation, again to chart the epigenetic response to compile a list of candidates for type (2) changes. These experiments could not ethically be performed on humans, however there are humans whose aging is accelerated by non-epigenetic factors, including alcohol and drug abuse. Such people might be tested as part of the quest for type (2) changes. People healing from physical and emotional trauma might also be presumed to have epigenomes modified in the direction of type (2).

Hormesis is the body’s overcompensation to challenges. The body is damaged by something we do or we eat or suffer from, but the body overcompensates to the damage such that we live longer. 

Caloric restriction (CR) is the best-established example of hormesis. We might have most confidence in the epigenomes of people and animals subjected to caloric restriction]. Across the animal kingdom, CR is the most robust anti-aging strategy known at present, and we can be confident in subtracting CR-associated epigenetic changes from any algorithmic measure of biological age. These changes can be observed in humans, as in the CALERIE study mentioned above; or they can be observed in rodents, which have enough commonality to human metabolism that some of the same methylation sites have common functions in both. Our methylation clocks should be calibrated to be sure that the changes associated with CR are scored toward a younger biological age. 

In addition to CR, there are dozens of interventions known experimentally to extend lifespan in rodents, including juvenile exosomes, rapamycin, certain peptides, vitamin D, NAC, certain anti-inflammatories and angiotensin inhibitors. Recently, some of these have been tested for their effect on algorithmic clocks; and this has been interpreted as evidence for or against the intervention. We might reverse the logic and interpret the same data as training to calibrate clocks, assuming that these changes must be beneficial, and the clock algorithm should reward them with a younger age. If an intervention is known to increase lifespan, then we may presume that epigenetic changes observed in response to that intervention are beneficial.

Before 2013, biological age was estimated with measures of performance and appearance: grip strength, gait speed, athletic endurance, memory, exhalation volume (FEV), skin wrinkles, arterial inflammation, cartilage integrity. In the age of epigenetics, these physical characteristics retain their value as predictors of mortality, and a hybrid clock might be devised, combining physical and epigenetic factors. 

For the future

I know of projects at Stanford (the Biomarkers of Aging Consortium), at Tally Health, and at Tru Diagnostic to develop the next generation of clocks to evaluate anti-aging interventions. There are probably other, parallel efforts that I don’t know about, but I will hear about them in your comments. I hope that the theory and suggestions in this blog may be useful to them.

The Levin laboratory has found the developmental blueprint that tells the embryo how it must grow. The language of morphology is not genetic or epigenetic, not biochemical at all, but bioelectric. If, as I and others have speculated, aging is an extension of development into a program of self-destruction, then maybe aging follows a bioelectric blueprint. Maybe electrical interventions have a role in anti-aging therapies, supplementing or replacing the biochemical interventions that have dominated research in gerontology. Below I review a prospective analysis from the Levin lab.

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Background — Levin’s laboratory has put bioelectricity on the map

Michael Levin is my favorite living scientist. He is firmly rooted in laboratory biology, yet he has devised and interpreted his experiments so as to cast new theoretical light on biological mechanisms, again and again.

Levin studies morphology first. Why do bodies take the form that they do? How does the developing body know which organ to grow in which location? How does a hand know to generate exactly five fingers? How does the limb know when it is the right size, and it’s time to stop growing?

His signature thesis is that embryonic development is guided by electrical patterns, rather than gene expression. There are patterns of electrical potential that are maintained by cell walls that selectively allow the passage of some ions but not others. Voltage patterns imprinted across embryos contain detailed information about the shape and form of the adult, and how the embryo is to develop toward that goal.

At this point, you are wondering where the electrical patterns come from. The egg and sperm didn’t have these imprinted patterns, and the only information they carried was genetic and epigenetic. This is a crucial question, as Levin acknowledges, but he doesn’t yet have an answer.

Levin’s favorite model animal is the flatworm, Planaria. These worms rarely go through the trouble of sexual reproduction (which is essential in the long term for preserving the integrity of the genome). Commonly they reproduce clonally. Any small piece of a worm can regenerate a full body. As a result of long periods of asexual reproduction, the genomes of these worms are a mess, with different chromosomes — even different numbers of chromosomes — in a mosaic through the body. But no matter! The worms seem to develop their adult shape and function fully independent of what selection of genes happen to be available.

In one of Levin’s signature experiments, he is able to modify the electrical pattern in a piece of a worm, not touching any of the biochemistry, and the result is a worm with two heads and no tail. Or two tails and no head. Both seem to be perfectly viable, and survive well, at least in the lab environment. The two-headed worm breeds true, in that pieces of a two-headed worm will regenerate another two-headed worm, and pieces of a two-tailed worm will regenerate another two-tailed worm. But if the experimenter artificially induces a change in the electrical pattern, he can cause the progeny of either of these to revert to the boring phenotype with one tail and one head. The two-headed worms and the no-head worms do not differ genetically from the normal type.

I’m in danger of getting carried away with these results before I even get to Levin’s paper on aging. I’ll just mention two more.

Learning. You can train a worm in simple behaviors. Then cut off its head, and the tail grows a new head that remembers the behavior you taught to the old head. This is one of several counter-examples to the universally accepted common sense that memory lives in the brain. (The experiment was repeated in Levin’s lab, but originated decades ago.)

Adaptation. Barium salts poison the ion channels that cells use to maintain their electric potentials, and in planaria they cause a worm’s head to shrivel up. The worm grows a new head, and it is resistant to barium salts. Levin notes how unexpected this is. Worms in nature never encounter high enough concentrations of barium to cause a problem, so this is not an evolved adaptation to barium. And yet it is immediate. The worms know to turn on a handful of genes that are otherwise silenced and it solves their problem.

the cells detect (and act on) highly processed state information several steps removed from the proximal events at the membrane. In this case, the many ways to depolarize tissue could be naturally coarse-grained to represent a single problem: a change in membrane voltage addressable by a single set of transcriptional actions… Acting on such coarse-grained information is a simple form of meta-processing (i.e., “higher-level” information processing that controls some lower-level process). [ref]

Connections

Most of the paper is reviewing relationships between electricity and aging. The list is impressive, but perhaps this is because electricity is the unsung hero of many biological processes. The last 50 years of bioscience have been focused so intensively on the chemistry of DNA and proteins that we have a distorted idea of their importance. Life depends on electric forces within and between cells. Nerves operate via pumping Ca and Mg ions across membranes to create electrical signals. Exchange between Na and K ions causes muscle cells to contract. Mitochondria provide energy to all our cells by converting chemical energy to electric energy, The zeta potential is a charge on blood cells moving through our arteries, while preventing clotting.

Some of the relationships of bioelectricity to aging, all of which were new to me:

• Rejuvenation via exosomes was shown to work (among other mechanisms) via modification of K+ and Ca++ ion channels
• Oxytocin, identified by the Conboys as a key anti-aging blood factor, works by regulating depolarization and firing of neurons.
• Rapamycin and resveratrol both inhibit voltage-gated K+ channels
• Quercetin and other senolytics regulate ion channels
• Unsurprisingly, brain aging is intimately linked to Ca++  ion pumps, which form the basis of neuronal signaling. Calcium channel blockers can protect against Parkinson’s.
• The heart is dependent on bioelectric function both to run its clock and to fire the pump muscles. Levin lists some ways that CV aging is connected to bioelectricity.
• Cancer is a special case…

Cancer

Levin’s lab has rediscovered a new property of cancer cells that came to light only late in the game, and still occupies a backwater of cancer research.

“It has been known for decades that tumorigenesis begins with the bioelectric decoupling of cells from the somatic morphogenetic network (2003; 2010; 2006).”

Normal cells are in electrical communication with all their neighbors. But cancer cells cut off all communication, and each cell is isolated from information about its surroundings. Levin was able to revert cancer cells to well-behaved growth simply by restoring their electrical contact with neighbors.

The old theory about the etiology of cancer is that it starts in the nucleus, with a series of compounding mutations. Schaefer and Israel disproved this, to my mind, by transplanting mutated nuclei of cancer cells into normal cells (they remained normal cells) and transplanting healthy nuclei into cancer cells (they remained cancer cells). Despite this clear demonstration almost 30 years ago, most oncologists still believe that cancer is caused by mutations, rather than that mutations are caused by something outside the cell nucleus. Schaefer and Israel seemed to show that the the real source of cancer is in the cytoplasm. But their work is also consistent with Levin’s hypothesis — cancer is all about electrical communication networks.

How are adjacent cells connected?

Cells are enclosed by their individual cell membranes, and within these membranes are embedded proteins called connexins that can hook into connexins from an adjacent cell, forming a bridge. The bridge conducts charged ions and small molecules across the gap junction, leaving large molecules on either side.

(This sounds like synapses connecting nerve cells. Synapses have gap junctions, but their gap junction channels do not involve connexins. Levin reminds us frequently that the electrical networks formed by neurons are just one manifestation of a ubiquitous and much older phenomenon of electrical communication between animal cells.)

How is this useful for cancer therapies? Levin has experience using drugs to open and close ion channels between cells and create a desired pattern of electric potential in a group of cells. He has done it successfully for years in planaria. Can the same technique be used to recreate healthy relationships among tumor cells, redirecting the transformed cells to become functioning team players in the body? The part that has already been accomplished (using voltage reporter dyes) is to measure electrical patterns. The challenge, as Levin reports, is to create computer models which will predict the effect on these patterns from various combinations of ionophores.

Another, simpler idea is immediately available. Animal cells almost always carry a negative charge, maintained by assorted ion pumps in the cell membrane. Cancer cells tend to collect positive Na+ ions and lose their negative charge. The simple remedy is to deliver an ionophore drug that tends to pump positive ions out of the cell. Preliminary experiments suggest this has both a preventive effect and could be a treatment for cancers that have already developed [ref]. Bioelectric drugs were shown to have anti-cancer effects in cell cultures of human glioblastoma [ref].

 

“Regeneration and longevity are intrinsically linked”

This idea is the underlying motivation for Levin’s foray into the science of aging. Evolutionary theory would suggest that animals that have long gestation times, slow development, and gradual reproduction have greater investments in each individual and a greater need for a capacity to regenerate; but this does not imply that loss of regenerative potential is related to the root of aging. Salamanders are the best example of the correlation; they have extraordinary ability to regenerate, and they have extraordinary lifetimes for their size, up to 30 years. Planaria don’t age at all, and their capacity to regenerate is even more impressive than salamanders. Sea stars also have remarkable regenerative capacity, and their lifetimes are long, but less impressive than salamanders. On the other hand, octopuses can regenerate entire legs, but their lifespans are short for their size. Giant octopuses over 100 pounds only live 5 years.

 

Regeneration sounds attractive — but does it address aging?

Here’s a factoid I remember reading more than two decades ago, but in all that time, I’ve never been able to rediscover the reference. Sea stars have regeneration ability comparable to planaria — you can cut them up in small pieces, and each piece generates a whole new sea star. But unlike planaria, sea stars reproduce sexually and they age gradually, with a fixed lifespan of about 8 years. If you cut off a sea star leg, it will regenerate the whole body, but the body will remember the age of the original animal and die on the same schedule. A weaker example of which I’m more certain is the octopus. Octopuses have limited regeneration ability, but they can grow back one or several severed tentacles. Octopuses are semelparous, and the fact that they grow back new tissue doesn’t change the fact that they will die following reproduction.

The relationship between regeneration and aging is largely unexplored. The Levin lab is way out in front studying regeneration. It will be interesting to see if aging can be addressed with the ionophores and other “morphogenetic” tools that they use to modify voltage patterns in animal tissues.

Programmed aging — where is the program?

Approaches to anti-aging medicine have been divided between those that work at the cellular level (bottom up) and those that work at the systemic level (top down). You probably know that I have been an advocate for top-down from the beginning. The body knows how to repair itself, and just needs the orders to do so.

I have imagined those orders to come from signal molecules in the blood — hormones and cytokines and ribozymes = active RNA. Levin’s lab has elucidated another level of centralized control using electrical signaling. Aging is programmed. To what extent is aging programmed chemically and to what extent electrically? It’s a question to be explored with new experimental paradigms.

You’ll forgive me, knowing who I am, if I point out that the weakest part of this paper is that it considers only the loss of electrical information, and never the possibility that electrical information could be purposefully modified in a manner that is destructive to the integrity of the organism. For example, the use of the word “corrupted” shows that the authors are thinking in terms of lost information rather than deliberate rewriting of the pattern.

A key question for the biomedical applications of morphoceuticals for aging is how the bioelectrical pattern is corrupted over time and if an enhancement/repair of it will lead to proper maintenance or rejuvenation.

The introduction pays lip service to “programmed aging” as one of the viable theoretical frameworks, but this idea is clearly not digested. References cited for “programmed aging” are all for authors who are hostile to the idea. My book is not cited, nor are cogent accounts of the experimental case for programmed aging by people with reputations far greater than mine [ref, ref, ref, ref].

I find it interesting that even though Levin is always thinking in terms of logic circuits and electric controls, the tools he uses are always chemical. Drugs are used to move ions around and modify electric patterns. No one, not even the Levin lab, has found ways to modify the patterns of electrical potential directly.

Programmed aging requires a reference time, localized or spread through the body, a repository of information about age. If we could find the clock and set it back, like rewinding the odometer of a car, the body would make the appropriate repairs and adjustments to recreate a young body.

I have speculated the clock is in the hypothalamus, where chemistry and electrical memories meet; or maybe it is distributed in the epigenetic state of cells throughout the body. But how does it keep time? Is it logically possible for the clock to be homeostatic without some external reference time? Are there multiple clocks that consult each other and find a consensus (what Aubrey calls ‘“crosstalk”)?

Is one of these age clocks, at the highest level of control, based on patterns of bioelectricity?

I’ve learned a great deal from Dr Mercola over the years. His orientation toward natural approaches to long-term health, using diet and lifestyle in preference to pharmaceuticals, aligns with my own. I agree with most of what he has to say.

So, when he launched a campaign vilifying seed oils in the diet, I stood up and paid attention. “Linoleic acid found in vegetables and seed oils may be the biggest contributor to chronic disease in the Western world.” [from Dr Mercola’s Censored Library]

Last spring, he published a review article on health hazards from Ω 6 fatty acids in general and linoleic acid (LA) in particular. He makes a multi-pronged theoretical case linking LA to defective cell membranes, leading to diabetes, cognitive impairment, heart disease, and cancer. At the end, he tries to tie these concerns to real life results with epidemiological studies. To me, it seems that the theoretical arguments are strong, but epidemiology doesn’t seem to support his fears. In particular, most nuts are abundant sources of LA, and yet nut consumption is robustly linked to good health and long life.

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Chemistry background

Petroleum oil consists of chains of carbon atoms surrounded by hydrogen. These have no biological presence. Saturated fats (biological oils) in biology are similar chains with COOH at one end — essentially petroleum-like molecules with vinegar at one end. Unsaturated fats have a double bond between carbons, which is a place where there are missing hydrogens, and an angle or kink in the chain.

Petroleum:

 

Saturated fat: 

Unsaturated fat:

Comparison:

For omega 3s, the kink is close to the end opposite the vinegar end. For omega 6s, the kink is closer to the vinegar end.

 

(The pictures are alpha linoleic acid, ALA, an omega 3 (left), and and gamma linoleic acid, GLA, an omega 6 (right).)

 

Petroleum oils are biologically inert because there are no enzymes that can attack the carbon-carbon and carbon-hydrogen bonds. But the vinegar end of a fatty acid is a biochemically active site, and each double bond in the fatty acid is another active site. 

Food Chemistry

Animal fats tend to be saturated (no double bonds). They are more viscous. Vegetable oils end to be unsaturated, less viscous, more chemically active.

The double bonds make it easier for the body to work with a fat and put it to use. But each double bond is also a place where oxygen can attack the molecule and turn it into a useless and harmful product. OXLAM means “oxidated linoleic acid metabolite”, and it is not a single chemical, but a class of chemical byproducts which, Mercola says, can cause disease.

Even before it enters the body, unsaturated fats are prone to being oxidized in high-temperature frying. Saturated fats are theoretically better for frying because the double bonds in unsaturated fats are target sites for oxidation. So, for home-fried foods, it is safer to use coconut oil, ghee, butter, or lard. Restaurant and commercially fried foods are often made with unsaturated seed oils, which are likely to be oxidized by the time we ingest them.

The benefits of maintaining the proper omega 3:6 ratio are well-established. Bodily tissues consist primarily of saturated and monounsaturated fats, which are a readily utilized source of nutrients that support the development and maintenance of cells. The primary PUFAs are omega-3 and omega-6 fats, which the body needs in relatively small quantities [ref].

It is important to consume sufficient amounts of omega 3 fatty acids to sustain optimal health, with the recommended daily serving being between 500 and 1000 milligrams of omega 3 [ref, ref]. Contrary to previous perceptions, however, consuming larger servings of omega 3 fatty acids does not support an ideal ratio. Instead, excessive quantities of omega 3s may cause additional metabolic damage—similar to that which occurs due to the conversion of elevated LA levels. [from Mercola & D’Adamo]

It is well accepted that omega 3 fatty acids have benefits for reducing inflammation. Mercola claims that animal-derived omega 3’s are better in this regard, on the authority of this review. DHA and EPA are long-chain omega 3s, and are converted by our bodies into resolvins that cool inflammation. They come from either fish or ocean algae sources. ALA is a short-chain omega 3 that comes from walnuts, chia seeds, flax seeds and other vegetarian sources. ALA can be converted to DHA in the body, but slowly and inefficiently.

Examine.com  agrees

Omega 3 fatty acids in flax seed (as well as in Hemp Protein) are found in the form of Alpha-Linolenic Acid (ALA). Not only is ALA not sufficient to supplement on its own[1], but ALA has to be converted by the body into a usable form, and the ratio of conversion from unusable form to usable is rather poor, somewhere in the range of 5-15%[2]. Omega 3 supplements in the form of EPA and DHA are what the body tends to use for many of the benefits associated with fish oil.

For vegetarians and vegans, supplementing with DHA from algae can “markedly enhance the DHA status (of serum and platelets)” and “provide for the formation of substantial EPA”[3]. Supplementation of ALA and/or GLA is not enough[4].

Theory

Mercola fingers inadvertent oxidation as the process that turns LA into toxic OXLAMs. LA becomes incorporated into cell membranes, where it can remain for years. The membranes are then more fragile, and oxidation of LA in the membranes makes them porous, not functioning as the cell needs them to function. A particular OXLAM called 4-hydroxynonenal (4-HNE) accumulates, and high levels can trigger programmed cell death in the same way that peroxide is designed to do. 

Cardiolipin, created from four fatty acids, is essential for the efficient operation of mitochondria. Mitochondria are particularly vulnerable to oxidative damage, and incorporation of LA into cardiolipin is problematic for the mitochondria. Misformed cardiolipin distorts the convoluted shape of mitochondria, impairing their function

Health statistics

The epidemiological evidence for Mercola’s worries is weak, and he admits as much. There are conflicting studies, associating LA level positively and negatively with CV risk. Mercola claims the same is true of LA and diabetes, but the beneficial effects are documented by epidemiology, while the paper he cites for detrimental effects is theoretical. The effect of LA on cancer is mixed, and too small to measure. 

In this study, higher levels of circulating LA were associated with slightly lower all-cause mortality. In this study, addition of safflower oil to the diet was associated with slightly higher all-cause mortality.

Nuts — a counter-example

Nuts generally have high fat content, with 80% or more of the total calories coming from fat. Most of that fat is unsaturated (87% in peanuts, 95% in almonds, 80% in cashews), so Dr Mercola recommends limiting nuts to a small part of the diet. But many epidemiological studies have associated nuts in the diet with modest but significant benefits for CV risk, insulin resistance, and all-cause mortality,. [meta-analysis, review]

Plasmalogen

This recent review highlighted the benefits of omega 3s for brain health. The focus is on long-chain omega 3s, derived from either fish or algae. Plasmalogens are singled out as a promising supplement for preventing and even reversing dementia. Plasmalogens are ether phospholipids constructed by the body out of ingested fatty acids including ALA. Plasmalogens are essential components of cell membranes, especially in the nervous system. Levels decline after age 40, and declining plasmalogen levels are associated with cognitive decline. 

Confusingly, the word plasmalogen in the singular is sometimes used to denote a particular short-chain polyunsaturated species, AKA plasmenyl-phosphatidylethanolamine. Dietary supplements of plasmalogen are derived from cow milk or soy, and have been applied successfully in dementia trials. 

Dietary implications

Though there are many things that Mercola gets right, he has never understood aging as internally signaled self-destruction, so he is more fearful of accumulated damage than I think is appropriate. Oxidized lipids fits well with his damage model of aging. I understand the theory, but I think the real-world evidence of epidemiology is more compelling, and epidemiology tells us that nuts and even olive oil are pro-longevity. 

I agree with Mercola that the story about saturated fats ⇒ cholesterol ⇒ cardiovascular risk is discredited. Nevertheless, I’m a vegetarian for 50 years now. There is some evidence that vegetarians live longer, but my personal motivation is more empathetic than scientific [newer ref].  

I continue to eat a lot of nuts in the context of a low-carb vegetarian diet. I make salad dressing from olive oil and avocados, and cook with coconut oil. In the past, I have gone out of my way to include chia seeds and flax seeds, both for fiber and for Ω3s. Having learned what I did in writing this piece, I will back off the chia and flax seeds because their short chain Ω3s do not offer significant value. I don’t eat fish, so I will continue to supplement generously with fish oil and krill oil. It’s possible to get Ω3s from vegetarian ocean sources, but it’s expensive.

I’ve followed this diet for decades and it works for me, but your metabolism is different from mine, and diets are individual by nature. There is no one optimal diet.