Telomeres: The Longer the Better

Mice have much longer telomeres than we do, long enough that telomeres never get critically short in a mouse lifetime. Yet, when designer mice were engineered to have even longer telomeres (hyper-long by any standard, longer than we can account for the use of them), these mice lived longer and were healthier in every way than mice with normal-long telomeres. Lab mice usually die of cancer, and these with the longer telomeres were protected from cancer, along with every other ailment that was looked at.

First, I ask your indulgence if I harp on the obvious: this result is not consistent with the prevailing theory of telomeres. In most vertebrates, telomerase is rationed so that telomeres are allowed gradually to shorten over a lifetime, and this is explained by most evolutionary biologists and geroscientists as an anti-cancer program. According to theory, in each species, telomere length has been optimized by natural selection as a compromise between longer telomeres (allowing stem cells to last longer without senescing) and shorter telomeres (which provide a firewall against cancer, a drop-dead signal when unchecked cell growth might be life-threatening). In contrast, experiments have frequently shown that longer telomeres lead to a lower cancer rate. Blasco’s new result is a clear case. We can’t explain telomere dynamics as a cancer prevention program.

(For background on what telomeres are and how they function, I refer you to my early blogs on the subject.)

But beyond this, there remain many mysteries. This study highlights the truth that we don’t understand the mechanisms. How exactly are hyper-long telomeres working on a biochemical level? What can a hyper-long telomere do that an extra-long (regular mouse) telomere can’t do?

Known mechanisms include:

  • Senescent cells. Much of the literature has focused on the importance not of average TL but on the shortest because a few cells run out of telomere and become senescent, and they poison the rest of the body. This is called SASP, for Senescent-Associated Secretory Phenotype.
  • Telomerase as an enzyme. Telomerase is best known for its ability to elongate telomeres, but there is evidence that it has other effects as well.
  • TPE – the telomoere position effect.  This is the only one that fits. Long telomeres wrap back around the end of the DNA, actually masking expression of the genes closet to the end of the chromosome.  The Blasco study raises the possibility that we’re better off when the genes near the ends of the telomeres are silenced.

In my story, genes that have legitimate uses are turned against the body in old age. But there are no pure “aging genes” because it’s hard for such genes to evolve uphill (against individual selection). Has Blasco discovered an exception? Are these genes near the end of the chromosometrue “aging genes”? Or is it an example of evolved pleiotropy [my blog; BioRxiv preprint].

From Munos-Lorente, 2019,


Maria Blasco’s Madrid telomere lab has been at the forefront of this field for more than a decade. The new experiment is right on the bleeding edge of biotech and genetic manipulation, where the Blasco lab has staked out territory.

I learned that you can’t make mouse egg cells with long telomeres because the body’s process of making the egg standardizes the telomere length as it wipes clean the epigenetic markers and rewrites a starting imprint. How to get around this? Blasco grew eggs just until the third cell division (8 cells), then injected embryonic stem cells that had been grown saturated with telomerase to give them the hyper-long telomeres. Yes, this tiny embryo, just 8 cells in size, was micro-injected by hand with many stem cells, cloned to be genetically identical, so they would not fight immunologically with the cells already in the embryo. The injected cells were marked with a gene for green fluorescent protein (GFP) so descendants of the long-telomere stem cells could be identified later. The article doesn’t indicate exactly how, but the original 8 cells were induced to bow out, so that 100% of the cells in the mice that grew from these embryos had the GFP marker, and presumably, they all had the hyper-long telomeres as well. Thus, the lab made “designer” mice out of cells, every one of which had telomeres that (AFAWK) were longer than nature has any use for.

The stated inspiration for the experiment was to determine whether the hyper-long telomeres led to any detrimental effects. What they found was that hyper-long telomeres were beneficial in every way. The effect seems to be related to caloric restriction, since the mice are noticeably leaner and their insulin sensitivity remains high at advanced ages when mice usually become insulin resistant. Perhaps independent of these changes, the hyper-long mice had less DNA damage with age and more efficient mitochondrial metabolism.

Telomeres are full of surprises, and this may signal a new telomere mechanism, probably epigenetic, that is undescribed previously. But if it is to be described with known biochemistry, the only candidate is TPE, the telomere position effect. Long telomeres fold back on the end of the chromosome, masking some genes that are located near the end. It is already known that unmasking those genes when telomeres become short has pro-aging effects. But the new result involves telomeres that are (presumably) longer than anything that is found in nature or in the mouse evolutionary history. It follows that the hyper-long telomeres are folding back so as to mask genes that just happen to be near (but not to near) the chromosome end. In this picture, these genes just happen to be pro-obesity, or insulin-blocking. The effect is not evolved, but just a chance occurrence. I don’t like such explanations from chance, so I’d bet on a new telomere mechanism that is yet to be characterized.


Related study from the Blasco Lab

Another study (last summer) from the Blasco lab looked across species for relationships between telomere dynamics and species life span. This follows on the work of Seluanov and Gorbunova a few years ago. The previous work concluded that telomere length is most closely related to the body mass but not lifespan across rodent species. The authors tried to relate this to Peto’s Paradox, which is the observation that large, long-lived animals ought to have much higher cancer rates than observed, assuming that cancer results from a random transformation event in a single cell. In the new work, Blasco finds the closest correlation between lifespan and the rate of telomere loss.

We observed that mean telomere length at birth does not correlate with species life span since many short-lived species had very long telomeres, and longlived species had very short telomeres.

In short-lived species, telomere erosion happens much more rapidly: 7,000 base pairs per year are lost in mice, compared with less than 100 in humans.

In the old story [as I have reported it], telomeres shorten over a lifetime because stem cells lose a little telomere length with each cell replication. But this huge difference in telomere attrition rates can’t be accounted for in this way. Stem cells in mice don’t replicate 100 times faster than in humans. So something else is going on. Probably, there is partial expression of telomerase in a way that is programmed under control of natural selection. Telomere shortening with age has evolved in a way that contributes to aging via TPE. But (probably, by my account) telomere shortening is not the principal means of programmed aging, because the correlation between telomere length and age is too weak. Mike Fossel continues to promote the idea that relative but not absolute telomere length is a good indicator, and indeed a driver of aging. That sounds like it accords in the abstract with the new results, but details remain elusive.

The Bottom Line

It’s clear that telomere shortening plays a role in aging, though not a dominant role. It’s clear that telomere shortening is completely under the body’s control, therefore an evolved adaptation. Beyond this, the subject seems complicated, and there is good evidence that there are mechanisms involved beyond what we know about.

At a given age, telomere length in humans does not correlate with health risks. On this basis, I have argued that various methylation clocks are far better measures of biological age, and perhaps the GrimAge clock is best.

Interview with Josh Mitteldorf

Transcript of interview 10/14/19.
IP = Ira Pastor, Health and Longevity Ambassador for IdeaXme, founder of BioQuark JJM = Josh Mitteldorf, author of Cracking the Aging Code, and the AgingMatters ScienceBlog

IP: We’ve been spending time on hierarchical levels of the aging process: the genome, the microbiome, systems biology. There is an extensive catalog of hallmarks of aging. This lengthy list includes inflammation, oxidation, microbial burden, somatic mutations, epigenetic modifications, stem cell exhaustion, senescent cell accumulation, damaged mitochondria, telomere erosion, and on and on. All very interesting topics, and good topics for intervention. But we have not found a unified picture of why we age. We have not touched the paradoxes that challenge the prevailing theories. Why do some damaged organisms live a long time? Why do pristine animals drop dead after reproduction in some species? Why do some of these hallmarks of aging appear, sometimes, in the earliest stages of life, when we’re first developing? So we have an incomplete picture of aging. Joining us today is Dr Josh Mitteldorf. Dr Mitteldorf earned a PhD in astrophysics here in Philadelphia at UPenn, and spent a decade or so in that field, “wandering in the plasma physics of extragalactic radio sources.” (This is after earlier careers working in optical design and energy conservation.) Then Dr Mitteldorf made a move into evolutionary biology, where he currently studies evolutionary biology of aging using computer simulations. He spent a lot of times correcting what he feels are errors in the foundations of evolutionary theory. Maybe the theory has focused too much on selfish genes, as opposed to the ecological context that determines a relative notion of “fitness”. In his paradigms, this has a lot to do with why we age in the first place, and, by extension, what we can do about it with medical interventions. Dr Mitteldorf has lectured extensively at Harvard, Berkeley, MIT, her in Philly at LaSalle and Temple Universities. He is the author of two books:

Cracking the Aging Code: The new science of growing old and what it means for staying young.
Aging is a Group-Selected Adaptation: Theory, evidence and medical implications

He is also responsible for the Aging Matters ScienceBlog, and he is organizing a new study called DataBETA, in cooperation with the UCLA lab of Steve Horvath, evaluating combinations of anti-aging supplements and interventions, looking for possible synergies which so many studies focusing on single interventions may have missed.

JJM: Wow! You’ve said it all. I think we’re done.

IP: We can do a lot more. Can you introduce yourself, your background, how you got in astrophysics, then evolutionary biology, and where you find yourself today in terms of these innovative theories of aging.

JJM: In 25 words or less?
I grew up in New York and New Jersey. I was a wunderkind and went to Harvard early, and then I just dropped back, became a hippy for awhile, went to Taiwan, learned to speak Chinese, started a skills coop, became a yoga teacher, wandered back into science a few years later with a commitment, not just to solving equations but trying to figure out how the world works. My generation grew up with a disdain for the Military-Industrial Complex and all things capitalist. I have just enough money in the family that I don’t have to depend on a salary from industry or academia, and I have the privilege to investigate what I want to investigate. If I have anything to offer this field, it’s that I have a broad perspective and sometimes I can tie things together.

IP: I find your background in astrophysics fascinating. I come from the pharmaceutical industry, a very siloed place. One of my critiques of anti-aging biotech is the belief that if you’re not a specialist in cell biology you can’t contribute to the discussion. On this show, we’ve talked to people about the very small (quantum biology) to the very large (chronobiology). Before we get into your theories, talk about what it’s like for you as an astrophysicist coming into the field of aging biology as an outsider.

JJM: Not so much the outsider. Actually, the field was already dominated by mathematicians when I came aboard. Evolutionary biology during the first half of the 20th Century was two different fields. There were the mathematicians who knew precious little biology. These were brilliant people, including R.A. Fisher who invented the whole idea of correlation coefficients, analysis of variance–the foundations of how we evaluate significance in all fields of science today. But Fisher was also a passionate eugenicist. He felt the world was going to hell in a handbasket because the poor were having too many children. The rich people, who are intellectually superior to the poor, were not reproducing themselves, and he developed the whole theory now called “the selfish gene” based on fitness as a property of individual genes. [These ideas are uber-politically incorrect at present, but in the early 20th Century, before the Third Reich, they were mainstream among British intellectuals.] He recast Darwinian evolution as a 20th Century theory, making it quantitative, he modeled exclusively the competition which was part of Darwin’s thinking, and de-emphasized cooperation, which Darwin was very aware of. Darwin was a naturalist, who traveled the world describing different life forms and their relations.

So, back to the 20th Century, we have the naturalists, continuing in Darwin’s tradition: “This is what we see, and this is the explanation in terms of natural selection.” These people were observers of nature, using qualitative reasoning. On the other side, we had the mathematicians, who were developing selfish gene theory as a mathematical abstraction. This came to a head in 1964, with a book by George Williams, who had training in biology, but also deep respect for the mathematicians. He said, “You observational biologists, you naturalists will have to get your act together. You have not been rigorous in your idea of what fitness is and how evolution works. You have to embrace this mathematical theory and use it in every evolutionary explanation. Along with John Maynard Smith, he engineered a hostile takeover of the naturalists by the mathematicians, and the naturalists didn’t have the mathematical chops to challenge them. The idea of the selfish gene became dominant; cooperation was swept aside. “We know by theory that the only kind of cooperation that can possibly evolve is in lineages that share genes. For example, I share half my genes with my brother. I share one eight of my genes with first cousins. There’s a quip attributed to the mid-century theorist J.B.S. Haldane, asked whether he would ever sacrifice his own life for his brother’s sake. He replied, “No, but I would lay down my life for 2 brothers or 8 cousins.” This idea of “inclusive fitness” became the narrow lens through which all examples of cooperation in nature had to be explained.

Back to your question, What was it like for me to come into evolutionary biology as an outsider from mathematical physics? Well, the field was already dominated by mathematicians. I saw my role as taking the field back for the observational biologists. In science, observation is the highest authority whenever there is conflict with theory. I hoped that I might give the observational biologists the rigorous mathematics they needed to take back the field from theorists who had imposed a paradigm that didn’t fit the facts.

What facts in particular? If you think just about selfish genes, then what is aging? Aging has to be a mistake. Aging only detracts from individual fitness, and you’re not allowed to think about the fitness of the community because there’s no such thing as cooperation. Well, over the long haul, evolution doesn’t make mistakes, so there must be constraints, physical limitations or parts of fitness space that were unavailable. There were tradeoffs imposed, and therefore evolution is not able to make animals and plants that live and grow stronger for an indefinite period of time. This “wearing out” that we observe is an inevitable consequence of physical constraints that are imposed on evolution.

When I first learned this in the mid-1990s, I thought, “this has got to be wrong.” There is so much cooperation in nature that is not between close relatives. And not only this, aging has a deep heritage. There are genes that control aging in us that have been around for a billion years. They’re the same genes that control aging in worms and in yeast cells, separated from us by half a billion and a full billion years, respectively, since our last common ancestor. So maybe evolution has some constraints, but what constraints could conceivably apply equally to yeast cells and mammals? Any gene that’s been kept around for a billion years has to have a purpose. Of course, there are many genes that we share with these primitive eukaryotes, and these genes program the basics of cell chemistry, energy metabolism, and protein synthesis. These genes control functions that are so important that evolution does not want to mess with them. Well, genes for aging are in this same category. Evidently, the genes for aging must have a purpose that is just as central, just as important as genes for the metabolic machinery of the eukaryotic cell.

IP: When you talk about a billion years, I think of deep lineages with evolving purpose. For example, the amoeba dictyostelium, pond scum has genes that are used to swim around and hunt for food, but when food is scarce, these same genes are used to organize the cells into multicellular structures. We find that a billion years later, these same genes lead to tumor formation and metastasis. So there are these fascinating connections across time. Take us a little further now into your book. What are we missing when we look at aging from a cell perspective and not considering the organism or the ecological context?

JJM : Let me add one more hint that brought me into this field, the thing that lit the lightbulb in my head. It was 1996, and there was a cover story in Scientific American by Richard Weindruch about caloric restriction. We all know today that animals that eat less live longer, pretty much across the animal kingdom. But this was new to me at the time, and it got me thinking, what can an individual do when it’s starved that it couldn’t do when it was well-nourished? We’re not just talking about 10% less food. In a cohort where some of the animals are dropping dead from starvation, the ones that survive are living almost twice as long. What can an animal do in extremis of caloric deprivation that it couldn’t do when fully fed? This led me at the time to think that lifespan must be a choice the metabolism is making. The individual is programmed to live a shorter time when fully fed so that it can live a longer time when the community needs them most. The fully-fed animals are programmed by evolution for lower individual fitness. If this is true for so many species, there must be a deep and quite general explanation.

An aside here — I learned later that one well-accepted way to get around this conclusion is to posit that there’s an energy tradeoff, that food energy can be used either for longevity or for reproduction. When there’s plenty of energy, it all goes into reproduction and this somehow causes a shortage of the portion for repair. Then, when energy is in short supply–this makes no sense, but it’s part of the canon of what’s called Disposable theory–when food energy is severely restricted, there’s actually more of it available for keeping the body in repair long-term. I wrote a rebuttal at the time, pointing out some of the cheats that the author was using to reach this paradoxical result, which he needed for his theory. For one thing, his model only worked for pregnant females, not for females kept in lab conditions in cages with other females, and certainly not for males, which can maintain their fertility when calorically restricted.

This one example was enough to make me question the Fisher model. Fitness is not just about getting more of your genes into the next generation. It’s also about sustainability, about community, about ecological homeostasis. This has been my major contribution to the field. I callit the Demographic Theory of Aging. The reason there is aging is so we don’t all die at once. Imagine a world in which we did not suffer aging, in which we got bigger and stronger and less likely to die with each passing year. Well, we wouldn’t live forever, of course. Something would kill us eventually. The population would grow so high that our food sources would be pushed to extinction. We would die in a famine. Or maybe our population would grow so dense and so homogeneous that conditions are ripe for an epidemic to come in and decimate the population. Aging evolved so that we die continuously over time, rather than everyone dying at once. Without aging, populations would cycle severely, with exponential rise and sudden population crashes. Ecology can’t sustain this. It’s terribly unstable. Maybe the population can recover once or twice from such a crash, but we’re pushing our luck, and one such crash will lead to extinction. Well, natural selection is highly motivated to avoid extinction–isn’t this the core of Darwin’s theory? We die individually of old age, one at a time, so that we don’t all die at once.

This was the evolutionary explanation for aging that I came up with in the late 1990s. It took a long time to get it into print. It’s very gratifying for me to see, 20 years later, that much of the medical community, the research community has embraced the idea that aging is programmed. Even some people in the evolutionary community recognize this. Aging is on purpose. It’s not something that “happens to us”. It’s internally programmed. And fitness is not just about individuals, but also about communities.


IP : Moving from your book to your blog, where you discuss different interventions– pharmacological, nutritional, lifestyle–can you tell us what your targets are. At the same time, you’ve created the DataBETA project, a new kind of clinical trial. You’re working with Steve Horvath’s group which developed this epigenetic clock for aging. You’re measuring combinations, and not just individual treatments. Regulators have traditionally been down on this. If you want to develop a combination treatment A, B, and C, you first have to prove that A and B and C are individually safe and effective. Only then can you put them together. Perhaps this is beginning to change. Our FDA and the PMDA in Japan are starting to recognize the potential of combined treatments. Can you talk about going beyond the pharmacological model of one treatment at a time?

JJM : I’ve been an advocate for the idea that we need to test medicines and anti-aging interventions in combinations, not just one-at-a-time. That the interactions among these treatments are just as important as the individual effects. We’re not looking for the magic bullet but maybe the “magic shotgun”. I think in terms of the Yamanaka factors. What a genius it took to find this combination of four proteins that together are able to turn a fully-differentiated cell back into a pluripotent stem cell. No one of these has that effect. No three of them together will do the job. How did he discover this synergistic combination of four factors? My hope is that anti-aging research will also discover such combinations that have synergies.

Before we get into that, I want to go back and fill in the gaps: How did I get from an evolutionary theory to an attitude toward medical research? The big message from medicine in the 20th Century is that the body has robust healing power, and if we can harness that, to turn on the latent healing, remove obstacles so the body can do what it is designed to do–that is the essence of good medicine. Restoring the body’s natural healing. That’s taken us far, and it’s the right paradigm for infectious disease, for trauma, for everything that afflicts us when we’re young. But it’s not going to work for the diseases of old age. We’ve focused on seeing how the body has been derailed and helping it get back on track. But with aging, the body is already on track–it’s on track to destroy itself. This is why natural medicine, holistic medicine if you will, will not work for the diseases of old age. Once you realize that the body is programmed for a finite lifespan, for deliberate self-destruction, it changes the picture. Inflammation is a good example. Inflammation is a protective mechanism. That’s its original purpose. But late in life, inflammation turns on the body and destroys perfectly good cells. Autoimmunity is another example. The immune system is essential for our lives, but as we get older, autoimmunity becomes a problem. Arthritis is an autoimmune disease. We’ve learned that dementia and Parkinson’s are also deeply connected to autoimmunity. Apoptosis is a third example, programmed cell death. Again, we need it. When a cell is in the wrong place at the wrong time or when it is diseased, the cell is programmed to eliminate itself. But as we get older, perfectly good cells, nerve and muscle cells are committing suicide. These are the mechanisms of programmed death that collectively constitute aging. Getting the body back on track is the medicine we’re used to. It’s natural medicine, the medicine of the 20th Century, and it works great when we’re young. But for the diseases of old age, we will need to interfere with the program. We will want to thwart the body’s self-destruction. I’m knocking on doors, shaking people and telling them that this is what we need to realize. In the anti-aging community today, there is a deep divide between those who look at aging as damage that accumulates over time despite the body’s best efforts to protect itself. Our job, then, is to assess the damage at the cellular level and come up with ways to repair these damaged cells. The other half of the community–my half–says that aging is controlled at a systemic level by signal molecules in the blood. It’s true that cells suffer damage, but they’re damaged because they’re getting signals that tell the cells to shut off their repair mechanisms. Of course, we could figure out how to repair the damage. But this may take many decades of research to figure out all the different things that need repair and how to fix them. Once we realize that all this damage is happening under the regulation of signal molecules, a shortcut suggests itself. If we can understand the signaling system well enough to intervene there, we can tell the body in its own biochemical language to repair itself. Our job is to rebalance the signal molecules at their youthful state so the body thinks it’s young and takes up these repairs is it did so well in its prime. This is the royal road to anti-aging medicine, a great shortcut.

IP : I’m a big fan of the history of regenerative biology. There’s a fascinating body of work from the 1940s-60s, when they were transplanting cells from old bodies to young, taking off a right hand and sewing it on the left. We learned that putting young cells into an older environment doesn’t usually show any benefit. But when the old cells are exposed to a young environment, they move toward being youjng again. This concept of the higher-level signals controlling things at level of whole tissues is going to be extremely important. I completely agree with you on that. Talk a little about DataBETA. What stage is it at, and how can people get involved.

JJM : DataBETA is the Database for Epigenetic Evaluation of Treatments for Aging. We have a natural experiment out there. Millions of people trying to extend their life expectancy using a variety of strategies–medications, diets, exercise, in different combinations. If this were ten years ago, we’d ask, How can we know what is working? We’ll have to wait decades for enough people to die that we can count them and know which groups are succeeding in lowering their mortality risk. All that is changed with the Horvath clock. The Horvath clock looks at gene expression, one particular mechanism of gene expression called methylation. It may not be the most important epigenetic mechanism, but is the one we have the best handle on. We know how to assess methylation, to map it quickly and cheaply. So Horvath developed a clock based on methylation patterns on DNA that change consistently with age. If you look at certain methylation markers, you can tell within a couple of years how old a person is. In some cases, the methylation clock turns out to be a better indication of how long a person is going to live than the chronological age–which was the original calibration for the methylation clock. You can make a strong case that these methylation clocks are a true measure of your body’s metabolic age, and if you succeed in setting back the methylation clock, it is a sign that you’ve actually made the body younger. If you slow the progression of the methylation markers, you’ve probably slowed down the aging process itself. This is an opportunity for a revolution in anti-aging research. At last we can know what works without having to wait decades, but maybe just a year or two to see changes in people’s epigenetic markers. The idea for DataBETA is to recruit 5,000 people with 5,000 different strategies, recruiting for great diversity. Measure methylation ages at the beginning, middle, and end of a two-year period. See which are aging faster, which are aging slower. Is there a sub-population that is aging backward, getting younger over the course of the study? Look for the people who are doing best, and then look for commonalities. What combination of strategies characterize the people who are most successful at slowing or turning back the clock? The easy part is going to be collecting data, and the hard part will be making sense of it. Maybe there will be a signal buried in the noise, and my hope is that we will be able to use statistical methods to disentangle all these interacting effects. If we can find a common theme among the people who are most successful in slowing or reversing aging, then we’ll have an idea what combination of strategies is likely to work.

IP : I don’t know how many biohackers and how many amateurs are out there trying to find what works, but it seems like an untapped population to gather data from.

JJM : News from just the last week: For several months, I’ve been looking for university partners to actually run the study. I need people with experience running a trial. I need an Institutional Review Board to make this kosher. Just last week I was up at McGill (in Montreal) and met Moshe Szyf, who was a pioneer in studying methylation markers on DNA, starting 30 years ago. He is a world-class expert in the statistics of methylation patterns. He loved my project, and he wants to take it under his wing at McGill. So I now have the partner I need to move forward. We will need another couple of months to get necessary permissions and to set up a secure online database, but I’m hoping that by the end of the year we will begin accepting people into the program.

IP : Excellent! You’ve got to have good partners and the right connections to get the job done in this increasingly connected world, and it sounds like you’re doing it.

I read your bio, and you’re involved in so many other things in the Philadelphia area where we both live. I mentioned that you teach yoga, you’re actively involved in meditation, you are an amateur musician on piano and French horn with Olney Symphony, you’re an environmentalist, you were president of the Coalition for a Tobacco-free Pennsylvania. Many other things that are extremely important in aging include our mental health, the environment around us. Talk a little about the importance of all these things in your personal anti-aging protocol.

JJM : There are so many people who know one aspect of me. They think of me as the neighborhood yoga teacher, where I’ve been teaching one class a week for 40 years. They don’t know that I’m an astrophysicist. There are people who know me from the amateur music community who have no idea of my work in evolution. I’m known in the election integrity community for using statistics to root out election theft. I’m grateful that you’ve looked up all these other parts of me. It’s a privilege to live the way I live. I don’t have a lot of money, but the thing it’s most important for me to buy with what I have is freedom to pursue the activities and ideas and the ways of giving back that mean the most to me. I live a life of service to the community where I live, service to the scientific community, service to a political community as well.

One activity you didn’t mention is that I am an editor at OpEdNews, which is a people’s forum on current affairs, debunking the lies that are routinely fed to us by the news media we trust most–the lies of the New York Times and CNN and National Public Radio. I try to call them out, and I rely on a broad knowledge of science to counter the political propaganda, not just of the Republicans but the Democrats, too. It’s a great privilege to live the way that I live, to be independent of a boss or of an institution. Sometimes people pay me for what I do, but often I’m doing it because it’s what I’m interested in, what I believe in. I would hope that we might all live this way. But I recognize that the economy is being controlled so that very few people have that option today. People have to think about paying the rent and keeping food on the table, and they have little energy for anything else. It doesn’t have to be that way.

IP : I agree with you in a major way.

JJM : The other half of what you asked, what does this have to do with aging? When you think about anti-aging interventions, you imagine a pill or a medical treatment. Or maybe you think, if I really starve myself–if I’m willing to be hungry all the time, I can live a long time. Twenty years ago, the book came out The 120-Year Diet, which was about caloric restriction in humans. We now know that this works much better in short-lived species than in long-lived humans. We can double the worm’s lifespan with CR, and the mouse might live 40% longer. But in humans, we’ll be happy with an extra 5 years–maybe 10 years if you compare the strictest caloric restriction to the obesity brought on by the Standard American Diet. We’re not gong to live 120 years just by starving ourselves? What is the most powerful thing we can do to extend our life expectancies? It’s to live in a way that’s socially connected. To have loving relationships with our families. To be engaged in our communities. To have service relationships, and to be needed. To be a leader. People who have these things in their lives can expect to live 10 to 15 extra years, compared to the depressed and the lonely who are probably the predominant majority in this country. This is the largest increment in life expectancy that we know how to control, far larger than anything you can get from pills. And it’s good news because it says that the most fulfilling way to live is also the healthiest in the long haul.

IP : That’s an extremely wonderful message, especially in 2019 when, as connected as we may all be electronically, we experience a lot of distance from one another in a human sense. Josh, one final question that I like to ask my guests: Who is the person in history you most would have liked to have met. If you could ride my hypothetical time machine and visit for awhile, who would you sit down with? An astrophysicist? An evolutionary biologist? Who would be most rewarding for you to meet?

JJM : I had a bunch of people over just last Friday night reading the Tao Te Ching of Lao Tzu. This is the bible of Daoism, and I’ve been absorbing the message of the master Lao Tzu, about whom very little is known, where he lived and even if he was one person or a composite of several. The book dates from 2500 years ago, around the time of Confucius and Socrates and Zoroaster and the Buddha. This was an amazing age when all over the world, there was a simultaneous flourishing of wisdom among communities that had no contact with each other. The one that speaks to me the best is Lao Tzu. Tao Te Ching means literally, Moral Text, and you think, What are the rules for good living? What are the 10 Commandments of Daoism? But that’s not what the book is about. It say, Yes, there’s good and there’s evil in the world, but it’s not your place to take sides. Don’t try to fight for the good to defeat the evil. There’s no need for that. The Dao of the world is taking care of that. The Tao Te Ching counsels you to become a natural person, in touch with your instincts, with the part of you that is the Dao. Then you don’t worry about what to do, don’t struggle with decisions. You don’t look back and lament, “If I had only done such and so.”  But if you’re motivated in each moment by connection with the Dao that leads you into harmony with the way the world is unfolding. How different this is from a life of trying to figure out the difference between right and wrong.

When I was growing up, I was the smartest kid to come out of my high school in a generation. I thought, “I am my brain.” I had no idea there was anything valuable in me besides the extraordinary brain I’ve been given. It’s been a lifelong lesson for me that the brain is a great servant but a poor master. If I got to meet one person from the past, it would be Lao Tzu.

IP : Josh, it’s been a great pleasure to hear your story and the way your mind works. It’s completely fascinating. You truly bring together a convergent expertise in an area that requires synergy and combinatorial thinking.

Methylation Clocks and True Biological Age

The good news is that the DataBETA project has found a home.  After several months of seeking a university partner, I am thrilled to be working with Moshe Szyf’s lab at McGill School of Medicine.  DataBETA is a broad survey of things people do to try to extend life expectancy, combined with evaluation of these strategies (and their interactions!) using the latest epigenetic clocks.  Szyf was a true pioneer of epigenetic science, back in an era when epigenetics was not yet on any of our radar screens. No one has more experience extracting information from methylation data.

DataBETA is just the kind of study that is newly possible, now that methylation clocks have come of age. Studies of anti-aging interventions had been impractical in the past, because as long as the study depends on people dying of old age, it is going to take decades and cost $ tens of millions. Using methylation clocks to evaluate biological age shortcuts that process, potentially slashing the time by a factor of 10 and the cost by a factor of 100.  But it depends critically on the assumption that the methylation clocks remain true predictors of disease and death when unnatural interventions are imposed. Is methylation an indicator, a passive marker of age? Or do changing methylation patterns cause aging?

Two types of methylation changes with age

Everyone agrees that methylation changes with age are the most accurate measure we have, by far, of a person’s chronological age—and beyond this, the GrimAge clock and PhenoAge clock are actually better indications of a person’s life expectancy and future morbidity than his chronological age.

Everyone agrees that methylation is a program under the body’s control. Epigenetic signals control gene expression, and gene expression is central to every aspect of the body’s metabolism, every stage of life history. Sure, there is a loss of focus in methylation patterns with age, sometimes called “epigenetic drift”.  But there is also clearly directed change, and it is on the directed changes that methylation clocks are based.

But there are two interpretations of what this means. (1) There is the theory that aging is fundamentally an epigenetic program. Senescence and death proceed on an evolutionarily-determined time schedule, just as growth and development unfold via epigenetic programming at an earlier stage in life. Several prominent articles were written even before the first Horvath clock proposing this ideas [ref, ref], and I have been a proponent of this view from early on [ref]. If you think this way, then methylation changes are a root cause of aging, and restoring the body to a younger epigenetic state is likely to make the body younger.

(2) The other view, based on an evolutionary paradigm of purely individual selection, denies that programmed self-destruciton is a biological possibility. Since there is a program in late-life epigenetic changes, it must be a response and not a cause of aging. Aging is damage to the body at the molecular and cellular level. In response to this threat, the body is ramping up its repair and defense mechanisms, and this accounts for consistency of the methylation clock. In this view, setting back the methylation pattern to a younger state would be counter-productive. To do so is to shut off the body’s repair mechanisms and to shorten life expectancy.

So, if you believe (1) then setting back the bodys methylation clock leads to longer life, but if you believe (2) then setting back the bodys methylation clock leads to shorter life.

I think there is good reason to support the first interpretation (1). Epigenetics is fundamentally about gene expression. If you drill down to specific changes in gene expression with age, you find that glutathione, CoQ10=ubiquinone, SOD and other antioxidant defenses are actually dialed down in late life when we need them more. You find that inflammatory cytokines like NFκB are ramped up, worsening the chronic inflammation that is our prominent enemy with age.  You find that protective hormones like pregnenolone are shut off, while damaging hormones like LH and FSH are sky high in women when, past menopause, they have no use for them. There is a method in this madness, and the method appears to be self-destruction.

Until this year, I have been very comfortable with this argument, and comfortable promoting the DataBETA study, which is founded in the premise that setting back the methylation clock is our best indicator of enhanced life expectancy. The thing that made me start to question was the story of Lu and Horvath’s GrimAge clock, which I blogged about back in March. 

The GrimAge clock is the best predictor of mortality and morbidity currently available, and it was built not directly on a purely statistical analysis of direct associations with m&m, but based on indirect associations with such things as inflammatory markers and smoking history. (This is a really interesting story, and I suggest you go back and read the March entry if you have not already. The story has been told in this way nowhere else.)

(Please be patient, I’m getting to the point.) Years of smoking leave an imprint on the body’s methylation patterns, and this imprint (but not the smoking history itself) is part of the GrimAge clock. I asked myself, How does smoking shorten life expectancy? I have always assumed that smoking damages the lungs, damages the arteries, damages the body’s chemistry. Smoking shortens lifespan not through instructions imprinted in the epigenetic program, but quite directly through damaging the body’s tissues. Therefore, the epigenetic shadow of smoker-years that contributes to the GrimAge clock is not likely to be programmed aging of type (1), but rather programmed protection, type (2).

For me, this realization marked a crisis. I have begun to worry that setting back the methylation clock does not always contribute positively to life expectancy. The canonical example is that if we erased the body’s protective response to the damage incurred by smoking, we would not expect the smoker to live longer.

The bottom line

I now believe there are two types of methylation changes with age. I remain convinced that type (1) predominates, and that setting these markers to a younger state is a healthy thing to do, and that it offers genuine rejuvenation. But there are also some type (2) changes with age—how common they are, I do not know—and we want to be careful not to set these back to a younger, less protected state. 

The methylation clocks promise a new era in medical research on aging, an era in which we can know what works without waiting decades to detect mortality differences between test and control groups. But it is only type (1) methylation changes that can be used in this way. So it is an urgent research priority to distinguish between these two types of directed changes.

This is a difficult problem, because the obvious research method would be to follow many people with many different methylation patterns for many decades—exactly the slow and costly process that the methylation clocks were going to help us avoid. My first hunch is that we might find a shortcut experimenting with cell cultures. Using CRISPR, we can induce methylation changes one-at-a-time in cell lines and then assess changes in the transcriptome, and with known metabolic chemistry, make an educated guess whether these changes are likely to be beneficial or the opposite. As stated, this probably will not work because methylation on CpGs tends to work not via individual sites but on islands that are typically ~1,000 base pairs in length. Perhaps changes in the transcriptome can be detected when we intervene to methylate or demethylate an entire CpG island.

Perhaps there is a better way. I invite suggestions from people who know more biology than I know for experimental ways to distinguish type (1) from type (2) methylation changes with age.