Methylation update, Part II
Imagine Horvath’s thought process last year, when the PhenoAge clock (described last week) was derived. In order to evaluate anti-aging interventions in humans, the most useful measure would be a clock that estimates not how many years since your birth but how many years until your death. The 2013 methylation clock and the (non-methylation) blood tests combined to create PhenoAge both did a good job, and there was little overlap between the two. So combining an epigenetic/methylation measure with non-methylation blood tests might be the basis for an even more accurate estimate of time-to-death. There are also life-style factors that could be factored in, e.g., smoking, diet, exercise, socio-economic status.
Last spring, Horvath set his insightful project scientist, Ake Lu, to work on their “GrimAge” clock (named after the grim reaper). But a funny thing happened on the way to the spreadsheet. They started with a large training set of 2400 blood samples from the Framingham Heart Study, which has been collecting data since 1948. They supplemented the methylation data with blood markers and the known smoking history of each patient to create a composite index. The next step was standard statistical procedure: quantifying the overlap between the methylation and non-methylation data to eliminate redundancy. For example, they asked: to what extent is smoking history already reflected in methylation status? The surprising result was that the methylome already knew all about the smoking history and the body’s response to it. In fact, the methylation sites associated with smoking history predicted how long the person would live more accurately than the smoking history itself.
Remember from last week that the PhenoAge methylation clock was derived from the PhenoAge blood markers, and that the methylation version did not do as good a job at predicting mortality as the blood markers from which it was derived. This is the expected situation.
But this time, Horvath and Lu were confronted with a case where the information they had hoped to use to supplement methylation data was actually reflected in (different) methylation data, and the reflection worked better than the original. The methylation changes–presumably a response to smoking–told more about each person’s health risk than did the smoking history itself. Even stranger, the methylation marks most closely associated with smoking were found to be a powerful indication of future health even when the sample was confined to non-smokers.
If they continued undeterred on their original plan to add smoking status as a health indicator alongside methylation status, then the coefficient for smoking would have to be positive; yes, the math was telling them that, after allowing for all the information in the methylation profile, the extra information that a person had been a heavy smoker would actually lengthen the estimate of life expectancy, after the methylation response to smoking had been taken fully into account.
What could this possibly mean? Lu and Horvath don’t speculate on this point, but here are the three possibilities I can think of:
- Smokers are not reporting their history accurately, perhaps from shame or from censored memory. The methylation response is actually a better indication of the number of pack-years smoked than the person’s memory of the number of pack-years.
- The lung damage by smoking is highly individual. Each person’s response to smoking depends both on the number of cigarettes smoked and also his susceptibility to damage, and these two factors are reflected in the methylation pattern, which is a response to smoking.
- Most radical of all is the possibility that smoking kills not directly by damaging the lungs and arteries, but indirectly by inducing the body to alter gene expression toward an older, less healthy state. Radical, yes, but the only one of these three ideas that might explain why the methylation patterns predict mortality in non-smokers.
Rather than continue with this perverse conclusion, Lu and Horvath pursued their analysis with redoubled respect for the power of methylation indicators to predict age and age-related health. They looked for other markers–blood levels of certain proteins that might supplement methylation data in their Grim Age clock. And they found the same phenomenon as with the smoking. Yes, the blood markers held information about the individual’s future health prospects, but each marker also had its image in the DNA methylation pattern, and in several other cases (e.g. PAI-1 and TIMP-1) the methylation based surrogate marker was a better predictor of lifespan than was the original plasma protein level from which it was derived.
Some of these proteins will sound familiar to aging researchers: GDF15=Growth differentiation factor 15 (which should not be confused with GDF11). CRP=C-Reactive Protein, is a well-recognized marker of inflammation, which contributes to all diseases of old age. Others are more obscure. Cystatin-C is a blood marker of kidney function that more recently has been found to be a robust predictor of cardiovascular outcomes. TIMP1 is a protein that displays an impressively tight correlation with age, but I couldn’t begin to describe its biochemical function.
The article calls attention to the gene PAI-1, which I had never heard of. Plasma Activator-Inhibitor 1, aka, SERPIN-E1, regulates blood clotting, which is an important contributor to heart attacks and stroke. Later in life, de-methylation of suppressor regions in a chromosome causes more PAI-1 to appear in the blood, leading to increased heart risk. For no apparent reason, PAI-1 turns out to be a powerful predictor of heart disease, diabetes, fatty liver, and of age-related disease in general.
I would have liked to see correlation coefficients for all these measures because p values get better with more data, even if the correlation is weak. r tells you how much scatter you can expect if you try to extract information from the methylation profile of an individual or group of individuals in the future, but p only reassures you that yes, the correlation is not the result of chance. Horvath responded to me that there are technical reasons that r values cannot be inferred directly using the kinds of data on which his calculations were based.
Direct vs Indirect
Here’s another paradox. The DNAm GrimAge clock was developed in two stages, a correlation of a correlation. How does it compare to a direct, single stage computation of the methylation pattern that best predicts mortality (in technical language: a linear regression of time to death on the methylation profile)? In the Supplemental Materials published online with GrimAge, Horvath and Lu compare their GrimAge clock to Zhang’s clock (see last week) and to their own single-stage computation, developed for this purpose. Curiously, the indirect computation yields the better result. Why? In an email message, Horvath said he is just as surprised and puzzled by the result as I am.
An implication for Anti-Aging Lifestyle
Aside from the corroboration that we shouldn’t smoke cigarettes (duh), there is just one other direct implication for lifestyle in the GrimAge paper. They report longer life expectancies for people taking omega 3 supplements. The effect was on the edge of statistical significance, and more pronounced in men than in women. But it corroborates results from human epidemiology. A word to the wise.
Why the methylation clock is able to detect omega 3 supplements is again puzzling. We imagine that omega 3 in the diet acts directly on the lipids in the bloodstream, and that is where the health benefits come from. But it seems that dietary omega 3 affects the methylome as well. If this were just a response to the blood lipids, we would not expect it to correlate so well with the aging clock. Once again, the methylation clock is proving more robust than even its proponents would have guessed.
Methylation clocks to evaluate life extension technology
I have been enthusiastic about the potential of methylation clocks to screen life extension interventions and tell us what works. In fact, I’m organizing a trial in humans to test many common interventions and their interactions. If we think of the methylation clock as a faster, cheaper replacement for lifespan statistics, then the DNAm GrimAge clock is the latest and greatest tool we have. It is thus important to ask, what is the evidence for a close correspondence between interventions that slow the methylation clock and interventions that lengthen life expectancy? In short, there is evidence of a close but not perfect correspondence. I reviewed the evidence last year,
Eating red meat shortens life expectancy, and indeed it increases GrimAge. Conversely, vegetables, nuts, and fruits in the diet increase life expectancy and they lower GrimAge. HDL levels in the blood are good for longevity and lower GrimAge. Markers of inflammation are associated with faster aging, and also with higher GrimAge. Blood sugar control is important for longevity, and it appears to be reflected in GrimAge. Perhaps less expected, higher levels of education and income are associated with longer life expectancy, and both seem to be robustly mirrored in methylation, as measured by GrimAge. Age acceleration from smoking is well-reflected in GrimAge. Early menopause forbodes an early death, and this, too, has fingerprints in GrimAge.
On the other hand, we think rapamycin is the best candidate yet for an anti-aging drug, and no significant effect of rapamycin on methylation age has yet been detected. Obesity is associated with life shortening, but only weakly accelerates GrimAge. Aspirin, metformin, and vitamin D are supplements that are thought to have a small but significant benefit for lifespan. Do the methylation clocks pick up these effects? I have not seen data that they do. The fact that telomerase expression seems to accelerate methylation clocks gives pause.
And this study provides grounds for caution. Blood stem cells from the bone marrow were transplanted for medical reasons, and years later, the blood cells derived from the donor stem cells were collected and analyzed for methylation age. The result was that the blood cells remembered the age of the donor. They were not re-programmed by the new environment to match the age of the recipient’s body. While this result can’t detract from the accuracy of aging clocks based on methylation, it raises a theoretical and a practical issue. The result weighs against a theory (which has been a favorite of mine) that aging is programmed centrally, and that information about the body’s age is transmitted throughout the body by signals in the blood plasma. And it also calls into question the assumption (at the root of my Data-BETA study) that methylation clocks based on the blood will respond with the body if an anti-aging intervention is effective.
Other applications—other clocks
GrimAge takes the prize as the best candidate to replace the lifespan study, which is our current gold standard for evaluating anti-aging interventions.But there remain other uses for methylation clocks, and there is every reason to develop other clocks which predict other aspects of aging:
- Brain aging–perhaps a composite of reaction time and ability to form new memories
- Fast twitch muscles for sprinting
- Mitochondrial efficiency and aerobic capacity
- Cardiovascular age, from loss of elasticity in artery walls and stiffening of the heart muscle with glycation
- Aging of the immune system
The Bottom Line
Horvath and Lu have given us the most accurate epigenetic predictor yet of future mortality and morbidity, and, surprisingly, it is based in methylation alone, and not the other blood markers and lifestyle factors that they had originally thought would supplement methylation. Horvath’s finding that secondary methylation indicators are more accurate than the underlying primary indicator from which they were derived is provocative, and calls out for a new understanding. It suggests that methylation clocks might be even more robust than we thought. On the other hand, the recent finding that blood stem cells transplanted from one body into another retain a memory of the donor’s age suggests just the opposite.
As always a great new article. One thing I would consider that was not mentioned with respect to the fact that some anti-aging candidates seem to have no effect on methylation status-like rapamycin for example.,
is that there are likely many more aging systems than DNA methylation. So maybe rapamycin might be working on them.
In addition to DNA methylation covering various stretches of DNA we also have lamin A proteins (which are defective in progeria),
chromatin proteins,DNA helicase subunits that attach to and differnetiate stem cell DNA (defective in Werner’s Syndrome)
telomeric DNA which folds over on coding DNA
So I would bet we need a lot more than a DNA methylation clock to get a more accurate predictor of lifepsan.
We need to get a glimpse of the laminA-ome the WS DNA HELICASE-ome, the chromatin-ome, etc etc…..
So that’s just a thought…
“Horvath is quick to emphasize, DNAm GrimAge’s results are, at present, “not very accurate.” A given GrimAge might be off by four or five years in either direction, meaning a given GrimAge might only reveal the decade you’ll die”.
“Still, the only living person to get a GrimAge reading so far is Horvath himself. He had fared pretty poorly on his pan-tissue clock — “I want to say I was four or five years older than expected; I didn’t like that” — but according to GrimAge, he’s on track to die more or less when he expected”
All very confusing but fascinating. .
The smoking results are less surprising if you see the methylation as damage (whether it’s in a causal chain to ill health, which seems likely, or is only a side indicator). Smoking causes that damage, but other things may cause it too. And smoking may cause different amounts of that damage in different individuals.
So even though this methylation indicator was derived from smoking history data, the indicator could predict better than the original data itself, in part because smoking could be more efficient in causing damage in some people or some situations than others, and smoking history data ignores that. And the indicator might be expected to work for non-smokers as well.
An indicator that works better than the data from which it was derived is more than a shortcut. It could offer insights into basic biological mechanisms involved.
John S James @AgeTreatment
Luke Perry had a high standard of living and died young. Over here in Indochina, out following the wartime network of Ho Chi Minh Trails that run through the mountainous Laos/Vietnam border areas of Laos the past few months by way of dirt motorcycle, I came across so many very poor old hilltribe ladies- aged 60s to late 80s- that were hauling heavy loads of firewood (strapped to their heads and back), walking up steep terrain, all the while puffing on their own local homemade variety of cigar. And they do it every day of their lives, with their daily intake of red meat not seeming to matter at all either. (BTW, I am a vegetarian so I am not trying to convince anyone that diet risk factors are meaningless). But who really knows? I would wager a guess, though, that an intense daily workout overides a lot of other negative health habits.
The red meat finding is probably confounded with sugar intake, like in all the epidemiological studies – eating more saturated fats on top of a carb based (western) diet will obviously make things worse (more energy directed to fat storage), but eating a heavy meat diet with low carbs is clearly very healthy (i.e. keto).
Wow, excellent article with surprising mixed results. Truly a conundrum!
First thing that came to my mind is comments from Jan Gruber around his study using drug synergies
“There has been much interest in the potential for MET and possibly RAP to delay age dependent decline and disease in humans. Given this translational interest, the limited benefit of combining MET with RAP in both C. elegans and mice is somewhat disappointing. However, as our results illustrate, lifespan is determined through complex and interactive biochemical and gene regulatory networks. Intervening simultaneously at multiple points of these networks can result in significant and sometimes surprising benefits (28,62). Our proof-of principle study suggests that beneficial synergistic and additive interactions affecting key longevity pathways are unexpectedly common and evolutionarily conserved. These data support the feasibility of targeting multiple conserved ageing pathways using existing drugs to slow down biological ageing rate, an approach that, if translatable to humans, would result in dramatic medical and economic benefits (63)”
Link to full study is here https://www.biorxiv.org/content/biorxiv/early/2017/06/21/153205.full.pdf
Great follow up Josh.
I wonder if they controlled for life style differences in the bone marrow transplantation studies. The DNAm age of the transplanted tissue may differ from the host’s, but it could be accelerated due to life style changes. Otherwise findings such as smoking affecting DNAm do not make a lot of sense.
Also slightly related to this, if I recalled correctly Horvath’s newer ‘blood and skin’ clock did correlate with cell passage and I imagine with telomere length. Although this could just be due to higher levels of proliferation in these tissues.
Ultimately, this brings us to the main question of what makes the clock ‘tick’. I personally do not believe it can be put down to ‘drift’, otherwise it would not be highly correlated to chron. age, to biological age and even between species. Whether this is a cause of a result of ageing, we are not looking at a random process.
Circadian rhythms have been proposed. And that sounds like the only plausible system for an ‘intrinsic’ cell clock, which does not require cell duplication nor it converges with the hosts body in transplants, but it continues to reliable ‘tick’ nonetheless. But I have a hard time visualizing how a daily clock can drive a system of only a few hundreds locus.
circadian clock could be easy to mess with I guess. you could synchronize mice with multi day dark/light cycles, maybe even with medication or surgery. would they live teiwce as long then?
actually the drift can be stochastic, but just think about it:
A, some of the drift is meaningless, so its random.
some of the drift is lethal, so its either
B countermeasured by the body (apoptosis, SASP, immune system) or the result is
C cancer or CV death.
Horvaths clock maybe measures B or the result of B, which is deterministic but can be thought of as a defense mechanism to a stochastic change
but it can just as well be drift alone
I’d advise caution interpreting the blood stem cells study – this was done with DNAm age not PhenoAge or GrimAge, and the methylation sites barely overlap. The study would need to be repeated with the newer methylation clocks before we can say with more certainty the blood stem cells have not been affected by their younger/older environment.
Ditto with the telomerase DNAm Age acceleration – this is not the case for Pheno or Grim Age clocks.
“…Remember from last week that the PhenoAge methylation clock was derived from the PhenoAge blood markers…”
Thank you Josh. Do I understand correctly that, when comparing with your last week post and Levine’s paper, you are meaning here “DNAm PhenoAge” and “Phenotypic Age” respectively ?
The notion that a person has a “physiological age” exhibits a methodological shortcoming. This is that the numerical value that is assigned by a model to this physiological age is insusceptible to being cross validated.
Like any model, this one makes an argument. This argument is either a statistical inference or what I like to call a “unit-measure-equivocation.” The latter is an equivocation, that is, an argument in which a term changes meaning in the midst of the argument. The term that changes meaning is “unit measure,” a proposition and axiom of probability theory. Under a statistical inference, “unit measure” is true but under a unit-measure-equivocation, “unit measure” is false.
As a unit measure equivocation looks exactly like a statistical inference, to mistake a unit-measure-equivocation for a statistical inference is a mistake to which model builders are prone. but there is a test that is capable of determination of whether the argument that is made by a model is a statistical argument or unit-measure-equivocation. Under this test one determines whether a “concrete” statistical population underlies the model. A concrete statistical population does not underlie Horvath’s model. Thus, the argument that is made by this model is a unit-measure-equivocation rather than being a statistical inference. It follows that Horvath’s model provides a user of this model with no “mutual information” as this term is defined in information theory. It follows that Horvath’s model is incapable of supporting regulation of a person’s age at death.
Could you explain a bit more simply the logical fallacy of the work? If valid I would expect your objection invalidates also many more works which might suffer the same fallacy. I likely miss the point but isn’t the model validated on several populations? Thank you.
Thank you for your insightful response! How could one establish that there is such a thing as a Horvath Clock? This could be established by determination of the statistical significance of the “time” on the Horvath Clock for the life-span (or related biomarker) of an organism such as a human being.
The notion of the “statistical significance” is dependent upon the existence of the statistical population underlying the model of a physical system. Theorists prove prone to assuming the existence of this statistical population without actually identifying what this statistical population is!
In the case of Horvath’s clock, theorists fail to identify the partition of the time-coordinate of spacetime that is an element of the definition of this statistical population. This statistical population identifies a really existing human being with each element of this partition. For theorists to identify this partition is required for the theory of the existence of Horvath’s clock to become testable.
Neither derivatives of group statistics, nor correlations of correlations, seem to be the techniques needed to understand biological causes of effects.
your theory that aging is programmed centrally, and that information about the body’s age is transmitted throughout the body by signals in the blood plasma and the recent study that blood stem cells transplanted from one body into another retain a memory of the donor’s age can be explained in the following way, the methylation of the stem cells which is what the epigenetic clock is, happens at a constant rate from signals in the blood i.e the number and secretome of methylated cells do not affect the rate of methylation and therefore the gap in the donor and receiver age is maintained. there is no buildup of signals in the blood which cause methylation to happen
In this model, aging can never be reversed. Maybe that’s true. I hope not.
No there is an explanation, the stem cells have an intrinsic replicative clock, but that clock is overridden in presence of factors in young blood. So in effect there are are two clocks
This makes perfect sense if the rate of methylation changes is proportional to metabolic rate: basically a rate that varies only slightly between individuals, and can be altered slightly by some interventions like CR.
Metformin should be put to the test:
Metformin alters DNA methylation genome-wide via the H19/SAHH axis (2017) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5415944/
Significantly altered peripheral blood cell DNA methylation profile as a result of immediate effect of metformin use in healthy individuals (2018)
Metformin rapamycin CR and certain type of exercise all do result in wide changes including methylation changes but the key is to what degree. Josh is quoting from data that shows that rapamycin did not show significant effect on methylation age. What Issa shows is that these system wide hormetic benefits are successful in slowing the rate of age related methylation drift but not stopping it or reversing it https://www.nature.com/articles/s41467-017-00607-3 MN
Metformin induces low level stress which induces mitohormesis:
Another interesting paper:
Josh your posts are always interesting. I am not surprised that rapamycin and metformin do not show significant effect on methylation. I have said this here and in my posts that their benefit is derived due to evolutionarily conserved survival mechanism of hormesis which works like a tonic to help overcome low level stressful events. I also believe that aging program is implemented by progressively dampening repair efficiencies. Some of key repair pathways like Nrf2 are inversely related to mTOR. So when rapamycin inhibits mTOR it indirectly upregulates repair pathways as part of the overall hormetic package of benefits.
Regarding bone marrow stem cells retaining ‘memory’ of donor and not being influenced by current environment is something that needs to be examined in detail may be by some of the readers here. The evidence of aging being programmed is has emerged in hundreds of studies and can not refuted by one anomaly. There is some type of biological clock. Forget aging even if we see falling of teeth replaced by adult teeth, puberty, menopause all dictated by a time in our life cycle. All the above are outward events that we can observe but this clock also triggers at certain time points internal aging related events. This is executed by various tools – methylation is one – that effectively reorient gene expression to progressively inhibit repair pathways. There are three ways one can counter that. a) By using bioavailable supplements that activate repair pathways directly or indirectly. b) By using molecules and compounds that change the gene expression beneficially. 3. By what Harold and I did: hacking the signalling system to a youthful state thereby reversing the bio clock back to another point and reversing at one stroke all the gene expression changes done by the aging program.
This can be verified by testing with Horvath’s clocks.
Akshay, The above is an excellent summary of the current situation. As you note, aging is due to the suspension of repair mechanisms. This can be addressed in a number of ways, though the approach you are taking with Harold would seem to be the most holistic.
Have you done this yet Akshay? I mean test the sacrificed rat tissues with one of the methylation clocks?
Mark, Steve Horvath is building a rat methylation bioage clock as we speak for which our lab has supplied samples. Once it’s done we will be sending quite a lot of samples from our current mega trial to check if methylation age has been reversed.
Have you already started more trials Akshay, or are you referring to the trial Josh wrote about recently?
Mark yes we are approaching ethical committee for our next 96 old rat trial to replicate results and discover optimum dosage and frequency and some more answers we want. We will extrapolate that to prepare for our next trial on old dogs in the USA.
Interesting paper from 2003
Telomerase expression in culture stops the demethylation drift.
Telomerase Expression in Normal Human Fibroblasts StabilizesDNA 5-Methylcytosine Transferase I
That’s interesting GaborB. I’ve only read the abstract. But i’m not surprised telomeres have some control over gene expression (telomere position effect), I just didn’t know it would be exerted through methylation.
Its interesting and it is contradicting one recent article, which is about telomerase dependent age acceleration in vitro.
Epigenetic ageing is distinct from senescence-mediated ageing and is not prevented by telomerase expression
Sylwia Kabacik,corresponding author1 Steve Horvath,2 Howard Cohen,3 and Kenneth Raj1
Another interesting article (10 years old), according to which telomere elongation is not required for cell immortalization, but telomerase is!
Separation of telomerase functions by reverse genetics
Shibani Mukherjee, Eduardo J. Firpo, Yang Wang, and James M. Roberts
Mutant telomerase causes cell to overcome the hayflick limit with very short telomeres and without genetic damage.
I think this is another overlooked gem.
Yes, in fact telomerase expression seems to accelerate methylation aging, according to an article cited in the main text above.
I’ll have a read. I know you can maintain telomeres at a short but viable length. However if they’re too short DNA damage will go up, as in cancer cells that do this intentionally (as a mutational driver).
Youthful length telomeres should yield a youthful pattern of gene expression, so maybe this would equate with faster methylation changes.
Interesting what you say down thread about methylation changes not being repairable. You might be on to something, as you can only reverse these changes through dramatically pushing back to a progenitor cell phenotype – epigenetic memory of cell state is not fine enough to do small changes.
If I remember right, short telomeres fail to loop back into the chromosome and are sensed as DNA damage by the cell, triggering apoptosis or senescence as if it was an irrerapable DNA break.
I imagine expression of telomerase may still allow these loops to form, or prevent the cellular senescence response somehow. This has been shown with other proteins like TRF2.
Ultimately, we have to ask, to which degree is the SASP responsible for what we experience as ageing? To what degree is telomere position effect on gene expression?. And even how much stem cell exhaustion may play a role, and be affected by cell lineage senescence.
Yes there is a critical length at which telomere length no longer allows looping. There is also the possibility that the loop ‘tucks in’ at different points on the chromosomal DNA depending on length, and this is one mechanism by which gene expression is changed, in combination with chromatin.
there are various facts to consider
1 Replicative Senescence of Stem Cells in vitro
2 young blood rejuvenates old tissues
3 dnam age is basically stem cell age
4 blood stem cells transplanted from young person into an older one retain a memory of the donor’s age
5 the dnam curve shows that during growth dnam is steep and tapers off to a constant rate i.e dnam clock is not clicking at a constant rate during growth
if the dnam clock had a constant rate growth would not occur, the stem cells have an intrinsic replicative clock, but that clock is overridden in presence of factors in young blood. So in effect there are are two clocks
and the anomaly
whether blood stem cells transplanted from old person into an younger one retain a memory of the donor’s age or results in GVHD
Well the replicative clock is basically telomere length and the restriction on telomerase, which even stem cells have to some extent. But yes, this can be overcome and the more de-differentiated the cell is, the easier it is to do.
The methylation clock is a different animal. You’re right it advances more during growth and development and then slows down. We haven’t yet discovered what factors are causing the ticking of this clock. It’s possible it’s stochastic (based on ROS, for example). But it might be signalling too. After all OSKM can reverse it. The key will be looking at what in young blood makes it tick FASTER. (The opposite to what we are looking for in factors in young blood causing rejuvenation). I expect it’s something simple, like a signal for cells to differentiate, which after all is what is required in a child. Another way of studying it would be to take samples at the site of an injury. I’d expect an influx of stem cells, plus maybe some de-differentiation via inflammation to cause a temporary drop in methylation age, followed by more cell differentiation and proliferation causing an increase in methylation age, which overall leaves the body sightly older than it was before. If this is true it shows methylation age is a proxy for the exhaustion of the body’s regenerative powers.
blood stem cells transplanted from old person into an younger one retain a memory of the donor’s age
blood stem cells transplanted from young person into an older one retain a memory of the donor’s age
could it be growth is a seperate case of signalling/dnam changes in the body apart from dnam aging clock
could it be what we are measuring as a dnam aging clock is just replicative senescence, which appears to be happening at a high rate during growth, but the growth is so fast that the constant rate of replicative senescence appears accelerated.
could it be growth is a separate dnam clock which tapers off at maturity, which is not being captured by current dnam clocks
DNAm changes are universal across non dividing tissues such as brain, muscles. I think this is basically damage accumulated over the state of the chromatin. This is the only thing the cell cannot repair.
because chromatin state is time variant, It depends on its former state.
Protein, mitochondria, DNA is time invariant, so damage to them can be readily fixed.
In the study cited by josh, blood stem cells transplanted from old person into an younger one retain a memory of the donor’s age 17 years after HSCT, where the young recipients are 1 and 3 years old.
dnam clock as i understand is a ratio of methylated to unmethylated stem cells. In a young person 1 to 3 years old,dnam age of the blood stem cells is of the older donor and still the population of cells expands as the person matures starting with the ratio of methylated to unmethylated stem cells/dnam age from age of the donor at the time of donation, with the ratio/dnam age increasing each year and the population of cells increasing each year. The young environment fails to reset the dnam age of stem cells to that of the recipient even as the overall population of cells expand.
if this is true then young blood plasma will not lower the dnam age even as it will rejuvenate the body, where i suspect the young environment encourages rapid stem cell division, but the overall composition of the population of stem cells reflect changing ratio of methylated to unmethylated/dnam age. To reverse the dnam age the methylated cells have to be removed
it is entirely possible that a snapshot of the young plasma, wherein the composition of the various factors is maintained constantly in the body as in the experiment done by Dr Harold Katcher the dnam age would halt and not worsen.
the young plasma snapshot might hold the rate of renewal of the stem cells at a fixed rate thus stopping the advance of the dnam age
Here is something that Dr. Sinclair is working on that implies cell ageing program reversal:
GAZETTE: What excites you most about the state of anti-aging and longevity research?
SINCLAIR: Well, I hate to pick favorite children. Someone will always be upset. I have my hands in a few pies, but the most recent one that I’m excited about is cellular reprogramming.
GAZETTE: And how does that occur?
SINCLAIR: We introduce a combination of genes into the animal, or the cell, and we see that the tissue is rejuvenated as though it was young again. So it can heal, it can start new growth, like it was young. And if we can figure out how to deliver that to patients in a safe way, then it’s quite possible that aging is a reversible disease.
GAZETTE: What genes are we changing?
SINCLAIR: We’re using a combination of Yamanaka factors [used to reprogram differentiated adult cells into induced pluripotent stem cells] that are used to make stem cells currently in a dish, but what we’re finding is that you can introduce them into the animal as well. They tolerate it well and tissues rejuvenate.
I haven’t published it yet, so I can’t say too much, but we’re writing up the paper now that shows that parts of the mouse’s body that we thought would not ever improve are able to be regenerated. So we’re licensing that technology and hoping that it will be tested in the clinic in the next two years.
Glad someone is pushing this towards the clinic. Very ambitious to be only a few years away though.
I wonder what disease they are targeting (assuming aging have not been recognised as one at that time)?
I am happy that people finally picking up this method
However there is always a paper that contradicts the encouraging results:
Interrupted reprogramming into induced pluripotent stem cells does not rejuvenate human mesenchymal stromal cells
Carolin Göbel, Roman Goetzke, Thomas Eggermann & Wolfgang Wagner
Though in this paper 2D cell culture is used. I believe for such an intricate signal as epigenetic aging, the 2D cell cultures with hyperdoses of growth factors and 10-20% fetal bovine serum probably just not appropriate. However Nature does not hesitate to publish it.
Yeah, and while we’re at it, cell culture has to be done at physiological O2 (1-2%) to mean anything.
Most “cell culture” is only relevant to the HeLa species and its artificial ecological niche, parasitizing grad students 😉
Agreed, but wouldn’t that mean a really slow growing cell culture? (which would defeat the purpose of many in vitro studies)
nice article on longevity
The dnam age clock curve actually shows that methylation increases at a rapid pace during growth. the factors in the young blood fail to reverse the dnam age, instead dnam age advances rapidly. it could be
1- the body fails to neutralize the methylated cells and hence the accumulate, but then had they been harmful, evolution would have led to them being neutralized.
2- the methylated cells actually aid in growth and they become deleterious only after the body matures and the growth impulse dies down gradually.
In the study where the recipient blood cells retain the donor age even in 1 and 3 year old, the methylation does not increase steeply during growth and the dnam age advances gradually from a high base.
could it be the body senses it has enough methylated cells for the needed growth and therefore the gradual dnam changes.
All the growth factors in the young after being born fail to reverse dnam age as evidenced by the dnam curve, so it is quite possible to reverse dnam age will require factors which are not present in the young plasma.
I believe that the epigenetic rate of aging is set by the mitochondria, possibly by their rate of ROS, but possibly also related to antioxidant systems and the stability of the mtDNA.
This would explain why transplanted cells continue to accumulate more epigenetic nuclear changes over time in a stochastic manner but at a predictable rate. It is likely (without cellular reprogramming factors) an irreversible process.
One way of testing this would be to put human cells in a mouse. If I am right then the epigenetic clock should tick much faster in the transplanted cells than those remaining in a human.
This also explains why epigenetic changes occur in both dividing and quiescent cells – it is a consequence of faulty remethylation after DNA repair, which is constantly happening in all cells due to damage from ROS.
Things we know that lead to a longer, healthier life across the world, like coffee drinking or eating oily fish, are known to activate NRF2, which decreases the rate of DNA damage. Likewise things like smoking or eating excess sugar do the reverse – they increase DNA damage. But it was never the DNA damage itself that mattered – but the necessity during repair to remove and then reappply epigenetic marks – which is a highly imperfect process (compared to DNA repair, which is incredibly successful).
We need a study on the effect of boosting NAD+ on methylation and other epigenetics.
There is a new study showing that Nicotinamide Riboside can help treat chemotherapy-induced cytopenias:
Transient non-integrative nuclear reprogramming promotes multifaceted reversal of aging in human cells
T Rando, S Horvath among the authors
Unfortunatelly only abstract is available but requested full text.
Aging is characterized by a gradual loss of function occurring at the molecular, cellular, tissue and organismal levels. At the chromatin level, aging is associated with the progressive accumulation of epigenetic errors that eventually lead to aberrant gene regulation, stem cell exhaustion, senescence, and deregulated cell/tissue homeostasis. The technology of nuclear reprogramming to pluripotency, through over-expression of a small number of transcription factors, can revert both the age and the identity of any cell to that of an embryonic cell by driving epigenetic reprogramming. Recent evidence has shown that transient transgenic reprogramming can ameliorate age-associated hallmarks and extend lifespan in progeroid mice. However, it is unknown how this form of epigenetic rejuvenation would apply to physiologically aged cells and, importantly, how it might translate to human cells. Here we show that transient reprogramming, mediated by transient expression of mRNAs, promotes a rapid reversal of both cellular aging and of epigenetic clock in human fibroblasts and endothelial cells, reduces the inflammatory profile in human chondrocytes, and restores youthful regenerative response to aged, human muscle stem cells, in each case without abolishing cellular identity. Our method, that we named Epigenetic Reprogramming of Aging (ERA), paves the way to a novel, potentially translatable strategy for ex vivo cell rejuvenation treatment. In addition, ERA holds promise for in vivo tissue rejuvenation therapies to reverse the physiological manifestations of aging and the risk for the development of age-related diseases.
The full text is available.
These are the guys from Turn.bio (you can look up the company on google).
Interestingly they use mRNAs to express OSKM plus LIN28 and NANOG to reverse epigenetic age without inducing pluripotency. They also claim (not in paper) that they are now doing this in vivo (!) using lipid nanoparticles to deliver the mRNA.
This getting exciting now.
Thanks. Finally, anti aging research is receiving professional VC funding. I hope there will be an explosion of financing and hype in this sector soon. I expected this happened 10 years earlier right after the housing bubble.
Finally someone has looked at telomere length in different tissues, and even in mice with active telomerase, lengths declined with age in all tissues studied.
There will be an anti aging conference in Berlin next week organized by de Grey. Anyone going there?
This paper just came out two weeks ago. Its not even peer reviewed I guess, but huge if true
Human Aging DNA Methylation Signatures are Conserved but Accelerated in Cultured Fibroblasts
It was known earlier that cell cultures age much faster than in vivo cells, now they examined it and were able to relate cell culture aging to in vivo aging. They found that cell culture aging looks epigenetically very much like normal aging but was accelerated 60 times. So in a few months time 20 years of adult aging was simulated. I think this is a wonderful assay, because it is fast, cheap, human cells versus rodent
So what factors account for the x60 acceleration? Greater oxygen, forced replication, other factors in the culture?
Maybe its just replication load, or growth factor overload?
Sad that noone seems to do reseach on such fundamental questions.
There is a very nice paper from Berenice Benayoun
“Remodeling of epigenome and transcriptome landscapes with aging in mice reveals widespread induction of inflammatory responses”
My take from this paper is that a major culprit is the stochastic DNA demethylation across the genome.
I think so because the major differential expression signal is the upregulation of viral protection pathways probably as a response to TE activation. The cell struggles to maintain its expression profile but its getting more and more expensive energetically as the youthful DNA methylation mask is lost.
I think one key research area should be, how the cell remethylates the DNA during blastocyte stage and during IPSC induction, so that all the garbage DNA is suppressed from expression and a sharp expression signal is obtained.
I found a paper from a Thailand based group that supports my idea
Alu siRNA to increase Alu element methylation and prevent DNA damage
They introduced siRNA into human fibroblasts that bound to TE sequences and increased the DNA methlyation at such sites. They found the proliferation rate of fibroblasts increased and the fibroblast became more resistant to DNA damage.
Sometimes it seems the cell turns off the very genes it needs to survive. Going back to an old classic (https://www.nature.com/articles/srep10434), we see fibroblasts lose oxidative respiration with age. It was convincingly attributed to methylation of nuclear genes SHMT2 and GCAT.
These are important genes for production of one carbon units for , among other things, creation of mitochondrial DNA. SHMT2 also produces glycine from serine, which can also be cleaved by the glycine cleavage system to continue the production if SHMT2 fails.
Adding glycine to the aged fibroblasts cell culture for 10 days partially rescued oxidative respiration.
Interestingly despite glycine being one of the most common amino acids in the body, there is invariably a shortage of it in most large land mammals.
Crazy though that the cells would turn off these genes, when they are precisely what it needs to survive. Unless they need to turn down oxidative respiration for some reason. Could this be damage control? Or an attempt at apoptosis?
Thanks. It seems to me methylation is a double edged sword. For example there is SUV39.
I have read several articles about SUV39, for examples this one:
“Over-expression of the SUV39H1 histone methyltransferase induces altered proliferation and differentiation in transgenic mice”
It seems that this methyltransferase alone is able to immortalize fibroblasts, yet with a stable karyotype.
Stable chromatin seems to be really important. And interestingly, those SUV39 overexpressed mice were not embryonic lethal, they had some developmental defects but viable.
Seems to me SUV39 supresses TEs, which might play a minor role in embyonic development.
The down side of methyltransferases is that sometime they methlyate oncosupressors, e.g. p16 p21. Or they may repress genes required for metabolism as you linked in.
But I somehow feel methyltransferases are really important for producing long lived, durable , good quality cells. Those repetitive elements may be beneficial from an evolutionary aspect but toxic for the individual.
Methyltransferases are also implicated in telomere length control. After all telomeres are heterochromatin, too.
Maybe it is as simple as hypo methylated genes are more exposed to damage and genes that increase oxidative respiration doubly so. So higher respiration necessitates greater antioxidant defence, methylation control, sirtuins, etc.
On the subject of telomeres we now know even non-proliferating cells suffer telomere damage from ROS and this can lead to cellular senescence.
As telomere damage is not repaired, (unlike damage to the chromosome in general), their only protection is via being rolled up and inaccessible (and being relatively short).
This is a damn interesting hypothesis from the Thailand group I quoted above:
A Hypothesis to Explain How the DNA of Elderly People Is Prone to Damage: Genome- Wide Hypomethylation Drives Genomic Instability in the Elderly by Reducing Youth-Associated Gnome-Stabilizing DNA Gaps
They claim there are proteins for intentional DNA double strand breaks in order to relieve tension in DNA: These controlled breaks are more frequent in young cells. They claim global DNA methylation is a signal for this DNA preserving mechanism.
Amazing if true.
Another paper that links epigentic aging to DNA damage
Regulation of Cellular Senescence by Polycomb Chromatin Modifiers through Distinct DNA Damage- and Histone Methylation-Dependent Pathways
We report here that epigenetic ageing is not affected by replicative senescence, telomere length, somatic cell differentiation, cellular proliferation rate or frequency. It is instead retarded by rapamycin, the potent inhibitor of the mTOR complex which governs many pathways relating to cellular metabolism. Rapamycin, however, is also an effective inhibitor of cellular senescence
How many times have I said that methylation changes are driven by metabolism!?
I think that Horvath’s assertion methylation changes have nothing to do with cellular senescence (because rapamycin treated cells still senesce) may be wrong, or atleast missing a trick.
Rapamycin keeps cells smaller, which probably has an impact on methylation. This effect persists even to the point of telomere exhaustion, when the cell senesces anyway.
Cool but I guess even mice kept at highest non lethal dose of rapamycin only have up to 40% life extension.
Other than that please note that Horvath’s clock does not equal to age related chromatin degradation (a.ka epigenetic aging). It is only a machine learning proxy for the age related epigenetic changes. It just selects 300 good markers from a pool of potentially millions of markers.
If Horvath trained his clock with samples from people on rapamycin, than rapamycin probably would have very little effect on his clock.
I think the best they’ve achieved is 60% life extension on a male mice; a dose that killed females faster than their controls.
We don’t know if rapamycin can reverse methylation (or other epigenetic) changes, the experiment has not been done – it would be interesting to see Horvath expand his culture experiments to see what effect rapamycin would have on already old cells. We know that there is a beneficial effect on already old mice (or humans for that matter), but we don’t know how that would be reflected epigenetically.
I usually do not leave a bunch of responses, but i did a few searching and wound up here DNAm GrimAge—the
Newest Methylation Clock | Josh Mitteldorf. And I do have 2 questions for you if it’s allright.
Is it only me or does it seem like some of these comments look like
coming from brain dead visitors? 😛 And, if you are posting on additional online sites, I would like to keep up with anything new you
have to post. Would you make a list of every one of all your community sites like your linkedin profile, Facebook
page or twitter feed?