Dr Mercola Doesn’t Like Seed Oils

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.

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.



Saturated fat: 

Unsaturated fat:


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].


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]


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.

I’m not going to write about the British mortality data

It would be just like me to tease you with a clever, ironic headline like this introducing a long, detailed analysis of the British mortality data. But in this case, I’m being serious. This article is about why I think the data are unreliable and unworthy of our credence.

In August, the British Office of National Statistics (ONS) released data on all-cause mortality broken down by age and vaccination status. The ONS data covers months from April, 2021 through May, 2023.

This is exactly what we need to determine if the COVID vaccines have saved lives. Data by “cause of death” are tainted because hospitals have been incentivized to treat deaths “with COVID” differently from other deaths. But total death counts are harder to corrupt. I wish that more countries would release such data. (Are you listening, CDC?)

I’ve written about dangers of the COVID shots, including one analysis estimating deaths in the hundreds of thousands for the US alone. I should be eager to vindicate my prediction with new data, and the aggregated British data appear damning.

On its face, the straightforward, aggregate calculation says that vaccinated people are three times more likely to die than unvaccinated.

The British data is broken down into seven age categories. (Children are not included. The lowest age category is 18-39, and thereafter the age categories are by decade.) Let’s zoom in on the youngest age group:

A small number of subjects had bad reactions to the first shot, and discontinued from there. These people have elevated risk from the vaccine, but among those who went on to get the full sequence + boosters, the shots appear to be protective.

Other age groups show the same pattern. For example,

For every age group, multiple COVID shots appear to be protective against death from any cause.

A statistics lesson

Of course, it’s mathematically impossible that within every age group, the vaccinated are at lower risk of death but when you aggregate all the age groups together, it turns out that vaccinated people are at a higher risk of death.

That’s what I thought. I spent a whole evening checking and rechecking the calculation.

But I might have remembered Simpson’s Paradox.

The data are correct. The graphs are correct. The key to understanding the situation is that the lion’s share of the deaths (the numerator) are in the oldest age groups, but most of the head count (the denominator) is in the younger age groups.

Crucially, the vaccination rate among the young is much lower than among the old.

So what we are seeing in the aggregate chart is that the oldest people are more likely to be vaccinated, and they are also more likely to die. But that doesn’t mean that vaccination is causing the deaths.

So, does this vindicate the vaccines?

I have written and others have written that side effects from the COVID vaccines, including risk of death, are so much higher than vaccines of the past that it’s hard to see them on the same scale.

Furthermore, there is insurance data showing that death rates are up as much as 40% in working people, and anecdotes tell of people having sudden heart attacks and (widely “debunked”) turbo cancers.

How can this be reconciled with the idea that, in each age group, multiple COVID vaccinations are associated with lower rates of death from all causes?

In the 18-39 age group, almost no one is dying from COVID. The most significant causes of death are accidents, suicide, and overdoses. It is not reasonable to think that three COVID shots have the effect of lowering these risks by 20%.

The most plausible explanation is a strong “healthy user” effect. People who are unvaccinated are, on average, poorer and less educated than the rest of the population, and it is well-accepted that death rates are closely correlated with social class, especially at the lower end. More speculative is that the data has been tampered with, deliberately doctored to hide the vaccines’ dangers. See below, “Fraudulent manipulation…”

For these reasons, I think there is not much to be learned from the new British data.

A pattern too stark to ignore

There is one result embedded in the data that is highly significant (p<0.00002) and implies a role in the vaccines for excess mortality in 2021. During the months March – December, the all-cause death rate in the UK rose by 30%, and the rise was tightly correlated with the cumulative number of vaccinations (R=0.96).

This rise did not continue into 2022, but the overall death rate remained elevated. This pattern, again, cannot be explained as simply as a huge death toll from the vaccine. Thirty percent is enormous, and cannot be hidden by any government’s manipulation of the statistics.

I know… Ed Dowd has famously documented a 40% rise in insurance claims against corporate group life policies; but it was only possible to hide that 40% bump because the base rate among these young people employed by large corporations was so low that 40% of that was too small to show up in a graph of whole-population mortality, which is always dominated by the oldest segments.

Since the British mortality increase is in the population as a whole, it must be concentrated in the older population. Part of the 30% rise was seasonal. Death rates increase 25% winter over summer. But part of the increase is likely due to a lingering effect of the vaccines on mortality and morbidity in the oldest group. Evidence for this is in the continuation of the graph into 2022 and 2023. Death rates are more variable, but we see that they reach new highs in the winter of 2023 and never return to baseline.

Fraudulent manipulation of the ONS data?

Last winter, Madhava Setty publicized research by Norman Fenton suggesting that ONS had tampered with their COVID data. The strongest evidence was for the early months, Jan-Mar of 2021, which are unaccountably absent from the latest edition of the ONS data. The current edition begins with April, 2021. The following graphs are derived from the ONS data release in July, 2022.

The charge that is easiest to verify is that deaths from the vaccine rollout have been shifted into the “unvaccinated” column. We can see this in the form of a spike in deaths of the unvaccinated just as the vaccines were being rolled out. This is most prominent in the death rate for the oldest groups.

This spike is hard to miss — three times as many deaths as expected in the small “unvaccinated” group in those first months when the much larger vaccinated group of elders was being given early priority for the vaccine. Nursing homes were first to be vaccinated.

In the spring, the vaccine was distributed to middle-aged citizens, and — remarkably — we see a similar bump in deaths of “unvaccinated” people in that age group. The bump started later and is more spread out, corresponding to the fact that middle-aged people signed up for the vaccine more gradually.

Starting in the summer, the vaccine was recommended for younger people, and we see a bump for mortality in “unvaccinated” adults under 40 begin in June.

The Jan-Mar data for 2021 has been censored in the new ONS release, and with it the evidence for the obvious spike in the older age groups. But what of the humps for younger age groups? Are they visible in the new data?

To answer this, I’ve plotted data from 2022 and 2023 on the same graph for each age range, so we can see where they match and where they don’t. At older ages, the data match nicely.

But for younger ages, the data have been revised upward, making the humps more prominent. I interpret this to mean that more post-vaccine deaths have been moved into the “unvaccinated” group.

For the youngest ages, it looks as though the data were adjusted more, proportionally, but the scale is much smaller because the death counts are very low for the young.

The bottom line

I’ll end where I began this entry. I’m not going to analyze the British ONS data because I don’t think the numbers are reliable.

News from Harold Katcher’s Lab

The big news: (1) the active ingredient in E5 is exosomes. (2) Young exosomes retain their ability to rejuvenate across mammalian species lines. Work that remains: (1) calibrate a new generation of methylation clocks. (2) Combine removal of old exosomes with addition of young exosomes. Optimize dosage and timing of treatments.

What is in E5, Katcher’s fountain of youth? From the beginning, it was described as a “plasma fraction”, leaving us guessing. Blood plasma contains thousands of chemical species in tiny quantities that nevertheless have powerful, systemic signaling effects. I thought once the patent was applied for, there would be no more need for secrecy, and the patent would reveal the formula; but the patent application was for a process, not a substance. Katcher and Sanghavi claimed rights for a broad array of substances extracted from the blood in different “embodiments” of the patented technique.

Then, in last month’s preprint posted on BioRxiv, the authors casually revealed the secret, almost parenthetically. “the exosome fraction of the plasma, which we term as E5”. So E5 is not large proteins or small proteins, it’s not non-coding RNAs — according to this document, E5 is made of exosomes and exosomes alone. Independently, a group from the Smidt Heart Institute published in July their finding that exosomes from embryonic plasma had a profound rejuvenating effect, while plasma without exosomes had no effect. (Akshay alerted me to that paper when it came out.)

This new preprint reports on experiments using E5 from piglets to rejuvenate a total of 14 rats. Epigenetic markers, cognitive, physical, and metabolic markers all improved impressively. Some of the limitations of Katcher’s experiments remain to be resolved. Because of small numbers and killing of test rats to obtain tissue samples, we still do not have a strong indication to what extent the restoration of all these markers of age translates into increased longevity.

A major finding is that exosomes from a young pig can rejuvenate an old rat. It is remarkable, very lucky, and certainly not to be taken for granted that such specific signals can cross species lines. What a horrible situation we would have been in if it turned out that the best anti-aging treatment available depended on harvesting the blood of babies.


There were only 14 treated rats in this round of experimentation. 6 males in round 1 were sacrificed so that methylation of their organs could be tested. 6 female and 2 male rats in round 2 were kept alive long enough for their blood to be drawn for methylation testing, but not long enough to determine their lifespans.

Methylation clocks: For 6 treated rats, age 109 weeks, these were the average epigenetic ages by tissue:

Tissue Epigenetic age
liver 28 weeks
blood 39
heart 58
hypothalamus 82

The preprint does not provide error bars for these average epigenetic ages, but I expect (based on the published minimum and maximum, and the small sample size) that the 95% confidence intervals are broad, corresponding to rejuvenation by anything between 30% and 70%.

The fact that various tissues are rejuvenated by exosomes indicates that exosomes are a medium for transmission of age information through the body, and that young exosomes in the blood are able to induce system-wide changes in gene expression.

It’s common for medical gerontologists to frame their work in terms of their favorite evolutionary theory of aging, which is always the 70-year-old, conservative theory that won’t raise any hackles. I’m grateful that Dr Katcher is unabashed about framing his medical research in evolutionary terms, and that his evolutionary theory agrees with mine. Aging is a timed program of self-destruction, coordinated through the body by chemical signals, and evolved because ecological communities are more stable when individuals have predictable lifespans.

The hypothalamus is a neuroendocrine region of the the brain that has been associated with circadian timekeeping (day-night) and also with tracking biological age. The fact that gene expression in the hypothalamus was rejuvenated to a far lesser extent than the other three tissues suggests that hypothalamus plays a special time-keeping role, and that perhaps the hypothalamus is a source for these exosomes in vivo. It may be that the hypothalamus gradually erases half the epigenetic gains from the E5 treatment over time. From this and previous tests, we still have limited data on long-term benefits of E5 treatment.

Blood markers:

“we measured the levels of the following biomarkers on 30, 60, 90, 120 and 155 days from the start of the experiment: bilirubin, serum glutamic-pyruvic transaminase (SGPT) and serum glutamic-oxaloacetic transaminase (SGOT) to monitor liver function; triglycerides (TG), HDL and cholesterol to monitor risk of atherosclerosis and heart disease, and liver function as well; glucose to monitor the pancreas and diabetes; and creatinine and blood urea nitrogen for kidney function. The levels of all these biomarkers in the treated old rats were altered towards the values of young rats, without exception.”

(Note: Blood sugar and triglycerides in treated old rats was reduced to levels indistinguishable from untreated young rats. In humans, Type 2 Diabetes is a primary means by which the body destroys itself. — JJM)

Cognitive recovery: Treated rats learned to escape from a Barnes maze faster than old rats.

Oxidative stress: ROS markers were restored close to a young state. Antioxidant enzymes GSH, SOD, and catalase were increased close to youthful levels.

Inflammation: TNF-α and IL-6 were reduced close to the levels of young rats. Nrf-2 was increased close to the level of young rats.

Sarcopenia and muscular fitness: Grip strength of treated rats rose within a week to levels comparable to young controls, and remained strong for at least 30 days.

A new/old biological clock based on glycation of antibodies

IgG is a blood component, another name for “antibodies”. These bind specifically to viruses and bacteria and tag the cells for attack by phagocytes, another immune component.  Antibodies are not cells or globules but individual Y-shaped protein molecules with both arms of the Y able to bind to the (same) antigen, and the stem of the Y modified to attract a phagocyte only when the other end signals that it’s “got one”.

Immune aging is a big deal, as it was identified as a prime cause of aging by Roy Walford already in the 1960s. Greg Fahy pushed the theory into a therapeutic concept four years ago with his TRIIM program. With TRIIM, the idea was validated that a rejuvenated immune system can signal rejuvenation to epigenetic age and, presumably, other aspects of aging.

Dr Fahy also subscribes to a programmed theory of aging, and he personally offered me my first opportunity for a wide audience in the anti-aging community in 2010.   Mitteldorf_Evolutionary-Origins-of-Aging.pdf

Hence, “immune age” is a promising target for measuring success of anti-aging interventions, independent of methylation age. This idea has been realized with a Glycan-Age clock. Antibodies in the blood are coated in complex carbohydrate (sugar) molecules, or glycans, and the structure of the glycans carry information, analogously to the way that DNA or proteins carry information via their sequencing. The particular sugars attached to antibodies change with age, and they become important signals promoting inflammation later in life. Clocks based on glycation of antibodies are as old as methylation clocks, though they have been developed to a lesser extent.

It is surprising, perhaps, that glycan age was never measured in the TRIIM study, but Katcher’s group added glycan age to the tests on his treated rats.

“a significant (p < 0.05) reduction in the relative abundance of the pro-inflammatory agalactosylated IgG2a glycoform (G0) was recorded. This was accompanied by a simultaneous upsurge in the antiinflammatory digalactosylated glycoform (G2)”

Is there such a thing as “biological age”?

The preprint includes the statement,

“However, in the context of aging and rejuvenation, it is crucial to differentiate between improved health or organ function, which could be achieved via medication or surgery, and genuine molecular age reversal.”

Intuitively, we all feel that this must be a legitimate concept. In our experience, we can look at most people and form a pretty good idea how old they are, and this translates into reliable expectations about their stamina, resistance to disease, and ability to cope with a fundamentally new environment.

But this is because we’ve mostly encountered natural humans. We know, for example, that movie stars can have expensive surgeries and skin treatments that make them look decades younger. We don’t expect that people who have had a face lift will live longer or have more youthful vitality.

It is perfectly possible to imagine anti-aging treatments that rejuvenate the liver but not the nervous system, or that slash the risk of heart disease but increase the risk of cancer. Hence, it is advisable to report a variety of functional and metabolic tests rather than relying on any one measure of “biological age”.

What is measured by the methylation clocks?

For more than a decade, I have been committed to the paradigm that the body’s gene expression changes with age, and that changing gene expression is a driver of aging. Methylation, as a convenient surrogate for gene expression, would then seem to be a reliable measure of biological age.

But in the last four years, I’ve entertained questions about this paradigm, and I am no longer absolutely committed. The crucial question is: Does gene expression change as a driver of aging, the body destroying itself with inflammation and by scaling back autophagy and repair? Or does gene expression change in response to damage accumulated with age, scaling up repair functions to mitigate damage?

As recently as four years ago, I wrote confidently that the former greatly predominated. Epigenetic changes drive aging. On this basis, I was confident that if you change the methylation clock, you must be changing the driver of aging, and this was bound to lead to longer lifespan.

I have since become convinced that both kinds of changes in gene expression accrue with age, and that there is no easy way to tell the drivers from the responses. I first blogged about this in response to the GrimAge clock. GrimAge is the best predictor we have of remaining life expectancy, but it is based not just on drivers of aging but also on the body’s distressed response to toxins and cell-level damage.

The bottom line is that epigenetic clocks are the best measure of life expectancy that we have, and that they are improving every year, but while uncertainty remains, it is well to supplement methylation clocks with specific tests of metabolic function, stamina, inflammation, and cognitive performance.

Six new methylation clocks

Prof Horvath (presumably it was Horvath) trained four new clocks on rat tissues plus two new clocks that were cross-trained on humans and rats. Since rats have a maximum lifespan of 3.8 years and humans 122.5 years, one logical way to train a clock that works for both species would be to scale the rat ages and human ages so that one rat year is about 32 human years. This is just what Horvath did.

But in addition, he trained a second combination clock (rat and human) to read in absolute years. This presumes there are changes in epigenetics of a very old rat (say, 3 years) that are parallel to epigenetic changes taking place in a very young human (also 3 years). A strange concept, indeed! What kinds of changes would we expect to take place in a 3-year-old rat and simultaneously in a 3-year-young human? My guess is that the training program is selecting those sites that behave very differently in rat and human, and that results derived for rats with this clock will not translate.

But I would suggest that even the time-scaled clock (based on 32 years of human life = 1 year of rat life) is suboptimal. This is because different events in development and aging may occur at different points in the life cycle. A male rat reaches sexual maturity at about 8 weeks. Using a 32x multiplier, this would correspond to a 5-year-old boy. But in fact, boys don’t reach sexual maturity until well into their teens.

Prof Horvath has been developing methylation clocks for more than a decade, and his work has had a deep impact on the science of aging. To my knowledge, all his clocks are based on straight-line changes in methylation over a lifetime, and I have counseled that this is an unnecessary limitation on the clocks’ accuracy. More realistic clocks can be constructed based on parabolic curves, or even the simple expedient of grafting two straight lines together to create a “spline”. He has been creating cross-species clocks for the last few years, and to my knowledge these have all been based on a single scaling factor for each species. My recommendation is that here it is even more important to project the life cycle of one species onto another using a flexible mapping, pegged at several intermediate time points which are determined in a mathematical optimization process. Cross-species clocks will be of increasing importance as we translate mouse studies to develop experimental protocols for human medicine.

Unanswered questions

A few paragraphs up, I referred to a major issue in methylation clocks: A given intervention affects a set of methylation sites that are all associated with younger age. Which of these are actually beneficial, leading to life extension; and which represent reversion of the body to a younger state when it had less damage to deal with? For the latter, the younger state corresponds to repair mechanisms that are less active (presumably because they are less needed), and “rejuvenation” to this state could actually lead to shorter life expectancy.

To date, the best methylation clocks have been calibrated by how well they predict future life expectancy. This is, of course, very useful information, but it is all based on naturally-aged individuals. Our interventions that reduce methylation age may not increase lifespan.

In two previous rounds of Katcher’s experiments, males experienced more epigenetic rejuvenation, but they were killed before their lifespans could be measured; while females experienced less epigenetic rejuvenation, and their lifespans were measured to be only modestly extended relative to controls. Unexplained is the fact that the controls lived far longer than Sprague-Dawley rats are usually expected to live, and that a single treated rat lived far longer than 7 others that received the same treatment. These are all curious observations that warrant further investigation.

The failure of Katcher’s rats last year to live as long as their methylation age predicted should be a motivator for future research, studying not just the interventions but also the clocks.

We can try to classify different methylation sites based on theory; but if we want to address the question head-on, we need different experimental interventions that affect different CpG sites. Then we can see which CpG sites, when artificially methylated or demethylated, lead to longer lifespan. Hence, Katcher’s experiments provide a unique opportunity to determine in practice: which methylation sites, when reverted to a younger age state, actually extend lifespan? This is an experimental solution to the stickiest problem in aging clocks: which epigenetic changes correspond to drivers of aging and which correspond to responses to damage?

Do we have methylation for Sima, Katcher’s record-setting long-lived rat? If so, we might compare methylation profiles for Sima to his cage-mates that were treated the same way, yet died many months earlier. This is a start, but what we really need is an experiment in which about a hundred rats (M and F) are treated with different E5 protocols, their methylation profiles are monitored over time, and they are also permitted to live until their natural end. Manipulated methylation profiles can then be correlated with life expectancy, and from this a uniquely useful methylation clock can be constructed.

For me, the bottom line is the same thing I’ve been saying since the beginning: Katcher’s research is the most promising line of investigation in the field of anti-aging medicine, and it is a travesty that it is taking place under a single investigator’s direction, and with very limited resources. It will take extensive lab resources to optimize E5 dosage and timing, and to try combining addition of young exosomes with removal of old exosomes. This same research can be the basis for the first methylation clock that is known to predict lifespan for rejuvenated animals.

I would like to see the abundant money that is now in anti-aging research re-directed into rejuvenation via exosomes, and I would like to see Katcher sharing his techniques openly with the research community.