Dr. Josh Mitteldorf summarizes his research perspective published in Volume 17, Issue 5 of Aging (Aging-US), titled “Methylation clocks for evaluation of anti-aging interventions.”
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I am Josh Mitteldorf, and this is a summary of my article from Aging-US, called “Methylation clocks for evaluation of anti-aging interventions,” published in May of 2025.
The take-home message is that there are two kinds of methylation changes that take place with age: one beneficial and the other self-destructive. And our failure to distinguish between these two has resulted in the ambiguity in methylation clocks. Sometimes they work and sometimes they don’t. There are some ways to fix this distinguish between the two, and I believe better methylation clocks are on the horizon. Much of this is taken from my blog at agingmattersblog.org.
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.
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 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 changed consistently over a lifetime, Hannum and Horvath and others who came after them have created computer algorithms that can calculate a biological age. This idea of biological age doesn’t depend on your theory of aging, but the utility of epigenetic clocks and assessing the benefits of putative anti-aging measures certainly does depend on fundamental concepts about aging, about which experts are still divided.
So why does gene expression change in old age? Dobzhansky told us nothing in biology makes sense except in the light of evolution. One, 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 upregulated to the point where healthy muscle cells and brain cells are dying. Protective antioxidants, DNA repair and autophagy are downregulated. All this destruction is accomplished via turning genes on and off. If any intervention sets back the methylation clock, then there’s less self-destruction, more repair and maintenance. We expect that the body will live longer if the methylation clock reads a lower age.
But if you believe the neo-Darwinist theory that the body cannot be purposely destroying itself, then aging is an accumulation of incidental damage that 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’s less repair and maintenance. We expect that setting the aging clock back to a younger age will actually decrease life expectancy. This insight is counterintuitive, 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 counterproductive. Even if the clock is calibrated to markers of health like the pheno-age clock or calibrated to actual mortality like the GrimAge clock, it’s still based on the body’s responses to damage and not on the damage itself. Setting back the clock is counterproductive because it means dialing down the body’s repair and maintenance systems.
Since 2013, there’s been a kind of double-think in the world of anti-aging research. Most researchers, at least in public, continue to embrace perspective two even as they adopt methylation clocks to evaluate the interventions that they developed. All this is assuming perspective too, but I’m notorious for being a proponent of perspective one. From perspective one, 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’ve become convinced that the epigenetic changes of both type one and two 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 process. All the present clocks include a mixture of one and two, and this is why we do not yet have a reliable metric for the efficacy of anti-aging technologies.
What’s the evidence for this? Why do I think the changes of type one and two are both components of all extant aging clocks? Well, 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 show no significant benefit according to either the GrimAge or PhenoAge clocks. Conversely, Katcher’s intravenous infusion of exosomes called E5 has a dramatic effect on the Horvath rodent human clock reducing epigenetic age by half, but thus far it 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’re created. They report that clocks in common use do not respond as expected to known life-shortening conditions such as down syndrome, inflammation associated with arthritis and Parkinson’s disease.
Here’s what first clued me into the problem. The GrimAge clock of Liu 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 aspect of the GrimAge development alerted me to the issue concerning type two 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 they’re also valuable predictors of time until death. These were included in the GrimAge algorithm.
My assumption was that smoking decreases longevity by damaging tissues of the lungs and not by turning on the program of self-destruction. Therefore, if there are methylation changes associated with smoking, they’re probably of type two. 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 nonsmoker 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 for the purpose of evaluating anti-aging interventions. Methylation changes associated with smoking are statistically associated with shorter lifespan, but mechanistically with protection. These changes should have been included in an algorithmic clock 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’re statistically associated with a shorter life expectancy. In general, the methylation image of smokers is an example of type two. All type two changes should be counted with negative coefficients in methylation clocks, even though they’re statistically associated with older ages and shorter remaining lifespan. So it’s crucial to distinguish epigenetic changes of type one from type two.
The story of GrimAge carries a message that suggests ways that methylation changes of type one and two might be teased apart in algorithmic clocks. Present clocks don’t distinguish between one and two, so presumably the two types of methylation changes are combined in a way we might connote as one plus two. The goal would be to create a clock built on type one changes alone, or more speculatively penalize the clock for type two changes, so we might call the algorithm one minus two rather than one plus two. 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. But lacking this understanding in the interim, we might make progress toward distinguishing one and two by learning from the smoking example.
One way to acquire a database of type two changes is that animal models might be injected with pro-inflammatory cytokines, their epigenetic consequences mapped. Since the inflammation is imposed externally and not through methylation changes, we should presume that the response is all type two. Similarly, the animal’s immune system 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 two changes. These experiments could not ethically be performed on humans. However, there are humans whose is accelerated by non-epigenetic factors, including alcohol, drug abuse. Such people might be tested as part of the quest for type two changes. People healing from physical and emotional trauma might also be presumed to have epigenomes modified in the direction of type two.
Hormesis is the body’s overcompensation to challenge. 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. Calorie restriction, CR, is the best established example of hormesis. We might have most confidence in the epigenomes of people in 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 measures of biological age. These changes can be observed in humans as in CALERIE study mentioned above, or they can be observed in rodents which have enough commonality to human metabolisms that some of the same methylation sites have common functions in both. Our methylation clock 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 the clocks assuming that these changes must be beneficial and the clock algorithm should reward 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.
In the article, I have harsh criticism for several recent articles that purport to describe what they call stochastic methylation clocks. This is a response to the double-think that I mentioned at the beginning. People who believe that there is no such thing as programmed destruction, nevertheless want to use methylation clocks, so the meme of stochastic methylation change has gained popularity just in the last couple of years. The idea comes from recognizing that at least some of the methylation changes with age are harmful to the body. How can that account for this and still remain within the neo-Darwinian framework, which says that all programmed methylation changes must be pro-longevity?
The resolution that they hit upon is to propose that detrimental methylation changes with age are not programmed, but simply entropic or stochastic. They represent loss of information, their randomness creeping into the epigenetic program and not properly part of the evolved program itself. I argue that this is untenable. Random means that they should be different for every individual, and yet all clocks developed to date are based on commonalities among many individuals as they age. Several papers have been published that purport to present stochastic methylation clocks, but they use various tricks to put the rabbit in the hat. They all assume a programmed direction. For example, they take sites that are selected precisely because they change consistently with age from one individual to the next, and then they write a computer program that introduces epi-mutations at random intervals, but all along this predetermined path. So the clocks that claim to be stochastic are nothing of the sort.
To be clear, there certainly are stochastic methylation changes with age, changes that vary from one individual to the next. The Conboys hinted a clock built on such changes, but they don’t offer enough to reconstruct their worth entirely. For my Aging US publication, I created a methylation clock that is truly based on stochastic changes only. I show that it works sort of, but its correlation with age as much too low to be of practical use.
So in summary, methylation clocks to date have been of limited utility for the purpose of evaluating anti-aging interventions because they mix detrimental and beneficial epigenetic changes that take place with age, which I call type one and type respectively. There’s great potential if we can embark on a program that distinguishes between type one and type two.
Click here to read the full perspective published by Aging (Aging-US).
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