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Part II : A Survey of For-profit Research Centers

How much money is going into aging research? The information is not so easy to come by.  This interview estimated that companies working on medical solutions to aging have a market cap of $300 billion as of 2018.  I’m guessing this number is rather too optimistic. This Business Insider article counted $850 million in venture capital funding in 2018.  That’s million with an m–a lowball estimate, it seems.  It’s safe to say the answer lies somewhere in the vast ocean between these distant shores.

I have not found comprehensive data on startups in anti-aging medicine, so this survey is incomplete and biased according to my own familiarity with the companies and their programs.  And the more important disclaimer: I have strong ideas about what the end of aging will look like, and this has colored the view I present of each company below. If you know of companies that you think should be on this list, please make suggestions in the Comments below.

Partial List:

Mature drugs

Geron is ancient by present standards, founded in Silicon Valley in 1990 by Michael West, who was already an advocate of telomerase therapies.  They are long established, with market cap of $260 million but only 15 full-time employees. Clearly, their mission is research rather than production. Over the years, they have turned their telomerase expertise into drugs that block telomerase, useful as a cancer treatment, since most tumors cannot continue to grow without telomerase.GRN163L (Imetelstat), is a drug under development that targets telomerase.  They apparently made the decision years ago, when they sold the IP for their best telomerase promoter to Noel Patton that telomerase was too dangerous to let out of the cage.  I wonder if even now they realize that was a mistake.

Elysium Health is Len Guarente’s company selling a formula of NR and pterostilbene.  Pterostilbene is a “better resveratrol”. Interest in both resveratrol and the NADH pathway grew out of Guarente’s long-time study of sirtuins.  I believe that modest health benefits have been established from this approach, but NADH is so well studied that if there were dramatic results, we would have seen them by now.  And NR treatment is not without risks.

Telomere therapies

Sierra Sciences (Bill Andrews) is focused on small molecules that promote expression of telomerase, lengthening telomeres and preventing cell senescence.  Screening hundreds of thousands of chemicals in vitro for telomerase activity, they came up with TAM 818, which is now for sale in New Zealand as a skin cream.  In an unrelated approach, they are offering a clinical trial (in a South Pacific island where regulatory agencies permit) using gene therapy to add copies of telomerase.  My personal opinion: Several years ago, I believed that telomere shortening was an aging clock of primary importance, but then a large Danish study demonstrated that the scatter in telomere length is greater than the consistent drift toward shorter telomeres with age.  I still think elongation of the shortest telomeres is an anti-aging strategy, but no longer regard it as centrally important.

Telocyte (Michael Fossel) is experimenting with telomere elongation to prevent Alzheimer’s disease and even to restore neurological function.  Fossel understood aging and had the vision to appreciate the role of telomere erosion more than 20 years ago, and I have the highest respect for him, but from what I know, AD as a target seems to be mismatched to the biology of telomeres.  Telocyte has recently announced a strategic partnership with Maria Blasco, a Spanish researcher whose lab has produced most of the biggest milestones in telomerase therapy.

Gene therapy

Rejuvenate Bio The Harvard laboratory of George Church was early in recognizing the potential for CRISPR technology to bring gene therapy into mainstream medicine.  Rejuvenate Bio is offering a gene therapy program to dogs who are at genetic risk for mitral valve disease, a congenital heart disorder. It’s cheaper than human trials, with less liability when something goes wrong, and it’s a viable lab for gaining experience and honing technique. [Writeup at FightAging!]

Stem cell therapy

Stem cells are among the most promising technologies we have for regenerative  medicine.  I’m surprised not to find more companies doing basic research, but there are lots of companies bringing the present (hit-and-miss) state of the art to patients.  Advanced Cell Technologies, a leader in the field, is now a part of Astella Therapeutics. Apceth Biopharma delivers stem cell technologies in the health marketplace but doesn’t seem to do much research.  Pluristem Therapeutics and Brainstorm Cell claim to have active research programs.  I have found no companies focused on the potential of stem cell therapies for extending lifespan.

Clinics and personalized medicine

AHNP (Apollo) acquired MPI, which was Dale Bredesen’s vehicle for bringing his Alzheimer’s protocol to the medical public.  I give AHNP special mention because I believe that Bredesen’s program is not only the first credible treatment for bringing brains back from AD; further, I think that Bredesen’s Alzheimer’s preventative program doubles as a comprehensive program to slow aging.  With individualized programs based on a battery of diagnostic tools, it’s a new model for how to do preventive medicine. I believe the program has transformative potential, but translation to the clinic has led to growing pains at AHNP. They can’t train new staff fast enough, and they’ve fallen behind explosive demand from new patients. Their software interface is buggy and there’s a backlog of requests for personal support, but they’re aware of the problems and building capacity as fast as they can.

Leucadia Theraputics has a diagnostic and treatment model for Alzheimer’s Disease based on drainage of amyloids from the brain, and physical blockage of the drainage pathway.

L-Nutra is Valter Longo’s company, offering programmed, packaged meals that provide some of the benefits of fasting with less of the hunger and deprivation.

Data Mining

Human Longevity is mining hospital records and genomic data to look for correlations. They offer testing and counseling to customers, then base their study on their customer base.

ASDERA is Knut Wittkowski’s small but important New York think tank.  Like other math geek operationss, they are using computers to mine data for patterns that lead to new drugs.  But unlike the others, they are not relying on the black box approach of neural networks. Wittkowski is an old-school statistician, familiar with an arsenal of classical statistical tests, choosing with judgment and expertise applied to the caseat hand.  Both approaches are computationally intensive. The difference is whether computations are guided by expertise and experience or by an algorithm that directs its own search toward a human-defined goal. Think of it as Artificial Intelligence vs Human intelligence, if you like.  Supervised learning vs a purely algorithmic search. Time will tell which approach yields more leads to actual treatments. I’m rooting as usual for the underdog, the classical against the avant garde.  Neural networks may yield a prescription, but you don’t know if it’s a fragile artifact of the particular data you used or a robust new truth about biochemistry, and the computer can’t tell you what it’s thinking.  With more human participation in the process comes more understanding of where the result comes from and (at least) a guess as to what it probably means.

 Acturx is another data mining project, headed by Edouard Debonneuil.  Debonneuil’s background is in actuarial science for insurance companies, and he is mining insurance records of millions of patients.  By correlating prescription records with health outcomes, they look for unknown benefits from known drugs.

Senolytics

Everon Biosciences was founded in 2010 by Andre Gudkov, with awareness of programmed aging built into their strategy. Gudkov believes that endogenous DNA damage in somatic cells is a primary clock driving diverse aging phenotypes.  A prominent kind of DNA damage is the duplication of regions of DNA that contain no genes (retrotransposons, including LINEs and SINEs).  NRT1 is a drug in development that inhibits the enzyme that makes the copies.  Another locus of research is senescent cells as emitters of signals that drive inflammaging.   But while other companies are racing to find agents that selectively kill senescent cells (leaving normal cells undamaged), Everon has focused on the innate immune system, including neutrophils and macrophages.  Their hypothesis is that the innate immune system takes care of senescent cells when we are young, but the system has a fixed lifetime capacity, and once its limit is reached, senescent cells accumulate and the vicious cycle of increased inflammation begins.  EBS3899 is a molecule they are testing for its ability to sensitize macrophages to senescent cells, and it seems to work better in vitro than in vivo.

Unity Biotechnology works on one molecule at a time, exploring their potential to relieve arthritis or degeneration of the eye or age-related disease in lungs, liver, kidneys and the CNS.  UBX0101 is their arthritis drug, in trials.  Other drugs at earlier stages of development target senescent cells and cognitive decline.

Oisin Biotechnologies is searching senolytic drugs, joining a crowded race to minimize toxicity to normal cells while efficiently eliminating senescent cells.

Biomarkers and Age Clocks

Spring Discovery and InSilico Medicine. In order to study anti-aging interventions, we need to evaluate them, and the traditional measure — waiting for experimental subjects to die — is too slow. This is the reason the Horvath clocks are so important.  His algorithms based solely on methylation profiles are the best measures of human biological age we have so far. Spring and InSilico are both trying to improve on that, combining other measures along with methylation, and using neural network analysis — the black box of AI — to look for patterns that evade human brains. These two companies are unrelated and working on opposite coasts, but if there’s a difference between their goals or methods, I have yet to understand what it might be.  [ScienceBlog article on InSilico]

Signal Molecules in Blood Plasma

[Background in my blog from 2 years ago.]

Jesse Karmazin’s Ambrosia  was an ambitious start-up, turned to object lesson in hazards of the fast track.  The basic premise is sound — that blood factors from the young are able to set back the clock of the older animal (or person) in whom they are introduced.  But which blood factors? And how much is needed? And how many treatments would be needed before the body would set its own clock back, and start producing the youthful factors by itself?  Karmazin’s plan was to ask these questions with clinical trials funded by his subjects, people willing to pay thousands of dollars for two transfused pints of blood from a young person. This past winter, the FDA stopped him in his tracks.

Tony Wyss-Coray’s Alkahest has taken the same promising premise and followed with more care toward a promising future.  In the early 2000s, Wyss-Coray was one of the Stanford pioneers of parabiosis. Originally, Alkahest seemed to be headed in the same direction as Ambrosia, offering small quantities of young blood to wealthy clients afflicted with Alzheimer’s.  But now they’ve made some important discoveries about the active ingredients that give young blood its rejuvenating power. They are well aware that it’s all about dosage–that some plasma components need to be downregulated and some upregulated to turn old blood to young (and perhaps turn old bodies to young…).  They’ve coined the term “chronokines”, key proteins that increase or decrease with age, and they’ve identified a few of these and launched clinical trials for macular degeneration and, Parkinson’s, and dementia. I’m impressed. My only suggestion is that they should be alert to the possibility that the interaction among these chronokines might be non-linear and, perhaps, surprisingly complex.

Other approaches

Google CALICO is well funded, but their relevance to progress in the field is hard to assess.  We might guess that their research direction follows the intersts of Cynthia Kenyon and David Botstein, i.e., understanding the genetic contributors to aging in worms and yeast cells.  They are partnering with Harvard’s Broad Institute and California’s Buck Institute in basic research.  They are in it for the long haul, building biochemical knowledge from the ground up. If someone doesn’t get there first, we may be very glad for their industry in another 10 years.

Google has also invested in shorter-term drug development through Verily Life Sciences, with partnerships that include GlaxoSmithKline. Personal note: I see a danger here, in which the company that we trust to direct us to the best information sources is allied with an industry that has done so much to promote its products with disinformation about health.

Lyceum is Michael Rose’s effort to commercialize research he’s done on the genetics of aging in fruitflies.  The web site claims a systems approach, which sounds right to me, but no details are offered at this early stage.

resTORbio is developing variants of rapamycin, which is perhaps the most credible anti-aging drug commercially available.  Rapamycin is not patentable, the main reason we see more research on variants and less on rapamycin itself.

CHAI = California Healthy Aging Initiative
Game-changer on the horizon

Activists in California are gathering support for a ballot initiative to provide $12B in state funding for anti-aging research over the next 12 years.  CA is one of the states in which the people can create legislation directly with their votes; and in 2004, this process was used to appropriate $4B for stem cell research.  Promoters of CHAI are trying to build on this precedent. But they face a dilemma. Gathering signatures and educating the public is an expensive proposition. They will need a broad coalition of research interests in the field to get their measure off the ground.  But of course, these organizations will want to write the text in such a way as to direct future funding to themselves. The grass-roots activists who are energizing this initiative believe that adding incrementally to institutions that are already well-funded is less likely to generate disruptive technologies than many small grants to individuals and start-ups with idiosyncratic theories of aging.  I like the idea of supporting small people with big ideas, perhaps because I are one.  This is a science still in its exploratory phase, where we do not have a definite idea what will work, and there are competing theoretical frameworks to guide us.  Once the proof-of-concept is complete, it’s appropriate to pursue the “D” part of “R&D”, and for that, industrial-scale research is the most efficient course.

My perspective on the state of research

I believe that aging is regulated under epigenetic control, but that the biochemical language of epigenetics is complicated, and it will be a slow road indeed if we persist in studying one intervention at a time.  The time is right for open science, open communications, interdiciplinary collaboration, and the testing of treatments in sets of 2 and 3 and 4. (If we study only treatments in isolation, we miss the boat; but if we try to study 5-way and 12-way interactions, the number of combinations will overwhelm our neural networks–both silicon and wetware.)

I continue to promote DataBETA because I think that it is a methodology for exploring the landscape from a perspective of radical empiricism, and point us in new directions.  DataBETA is looking for a university partner with experience in large-scale trials and otherwise is funded and ready to launch.

Our knowledge of biochemistry comes mostly from a reductionist framework.  We understand cellular systems better than we understand organs and tissues. We understand least of all the global signaling and interactions by which the body coordinates its growth, its homeostasis and (I believe) its aging.  The primitive state of systems biology counsels an empirical approach.

I‘m glad to see money and talent pouring into aging research, and it’s refreshing to see how much of it comes from people without theoretical preconceptions.  But many of the engineers and computer geeks coming into aging science are experienced in a world where problems can be split into manageable parts—divide and conquer.  My guess is that aging will be refractory to this approach, and will yield in the end to a multi-pronged but holistic therapy.

I gave up on the stock market years ago, the pride of the mathematician laid low by the surprises of the real world; but if I were a gambling man, I’d bet on Bredesen/Apollo.  There’s a solid core of biochemistry under a mountain of clinical data, and sparked to life with a bit of inspired guesswork.  They are modest (or prudent) enough to claim ‘only’ to have cured Alzheimer’s, but I would be eager to see methylation tests that relate their protocol to the best aging clock we’ve got.

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Part I : The Business Culture of Science

Since 2000, there has been a 20-fold increase* in research funding for anti-aging medicine.  Wow! That’s a good thing. But let’s keep our eyes on the ball. There is danger that this welcome infusion of capital may be biasing research priorities toward those that are most likely to be profitable, and maybe even diverting the best researchers from the radical thinking that will change our understanding of biology.

Whoever discovers an effective age-reversal treatment is destined to become a multi-billionaire!

At first blush, this statement seems obvious, but that doesn’t mean it’s true.  There are many historical examples of people who gave enormous gifts to the world, but struggled in their lifetimes for recognition and even for a livelihood.  Schubert, Poe, and van Gogh are artists who died poor, while people after them reaped billions from their work. Inventors who never profited from their inventions include Johannes Gutenberg and Nikola Tesla, Jagadish Chandra Bose, and Antonio Meucci (who?).  Reginald Fessenden invented radio a generation before Marconi.  Rosalind Franklin got no credit for being the person whose diffraction data and analysis was stolen by Watson and Crick for their Nobel research on the double helix.  

More to the point, there have been great discoveries that had no commercial value, or even negative commercial value.  Linus Pauling spent the last years of his life documenting the anti-cancer action of intravenous vitamin C. To this day, vitamin C is under-utilized and under-studied precisely because it is so cheap that no one can get rich from it.  I believe that aspirin and metformin may be two of the most potent life extention drugs that we currently know about, but we can’t be sure, because they are both long out of patent, and no private company can justify the investment to study them.

Rumors abound about cancer cures and energy technologies that are being suppressed because they would derail two of the most profitable businesses in the history of capitalism.  I don’t dismiss such claims out of hand.

If there were a drug that could increase average human lifespan by 15 years (with side-effects that were wholly salutary), there would be a dozen companies tinkering with it, adding a methyl group here or a double bond there, looking for a variant that might boost lifespan by 18 or 23 years.  In fact, there is about a 15-year advantage for people who are in a loving relationship, have deep community ties, assume responsibility for leadership, make lots of money, enjoy frequent sex, and remain close to young family members; in comparison, the typical middle-aged American is lonely, alienated, struggling financially, and sub-clinically depressed, with a life expectancy 15 years shorter than it could be.  The most effective things you can do to increase your statistical life expectancy are psycho-social, but who is conducting research into optimizing the life-extending benefits of community and relationship?

Diet, exercise, saunas, and fasting are life extension strategies that are promising and under-researched because there is no clear path to mega-profits.

What I believe

I am convinced that the primary basis of aging is an epigenetic program.  Systems that repair and protect our cells and tissues are gradually shut down, and destructive systems including inflammation and apoptosis are ramped up at late ages. Gene expression changes, modified systemically by transcription factors that circulate in the blood.  I believe that these blood factors are the holy grail of aging research. Control over aging will come when we learn enough about the basic language of epigenetics to reprogram gene expression with our interventions.

The difficulty is that there are dozens of known epigenetic mechanisms, of which only a few have been studied in detail.  A few years ago, it was understood that modifying non-coding regions of DNA could affect the transcription of nearby genes (cis epigenetic signals), but now we know that transcription of genes far away from the modification can also be affected (trans signals).

There is yet more complexity: most hormones and regulatory molecules have secondary roles that affect transcription.  Imagine an ecosystem of signal molecules that maintains itself homeostatically, but also changes with age. Sixty years ago, we learned that the genetic code is as simple as it can logically be; every codon three base pairs on a DNA strand is uniquely transcribed to one amino acid, and a protein is built by chaining these together in order.  Today we are learning that epigenetics is about as complex as it can be. So in my paradigm, basic research in epigenetics is an essential foundation for anti-aging medicine. If we are lucky, a dozen synergizing interventions will do enough reprogramming to re-set the aging clock. Perhaps there is even a region of the brain that is a common source for the molecules that induce age-related change.  If we are unlucky, it may require re-balancing blood levels of hundreds of different substances.

I am optimistic that this can be done, but it will require collaboration on a broad scale.  The process is unlikely to end with a single patent-holder who can rake in $ billions. The secrecy and the balkanization of corporate research is slowing progress.

Biases in Corporate Aging Research

For the last five years, Google CALICO has been the 800-pound gorilla in the room.  Of course, we welcome their funding, the legitimacy they lend, and their collective brainpower to our field.  But they don’t play by academic rules. They are not following the open-source / free-to-the-public model that has been so successful for Google in software.  They trend secretive and are not collaborating with university experts outside their walls.

CALICO isn’t announcing its philosophy or paradigm, but we might guess from its lineage that their methodology is rooted in data mining and artificial intelligence.  Other companies that have announced publicly that they are taking this approach include Unity Biotech, InSilico Medicine and Spring Discovery.  They have in common a data-intensive approach founded in theoretical agnosticism.

Machine learning has been used successfully to create algorithms that translate languages, that drive cars, and that recognize faces.  The best thing you can say about this approach to anti-aging medicine is that it is free of the theoretical biases that have plagued aging research through the decades.  The worst thing you can say about it is that it misses a fundamental difference between organisms and machines.

Machines are designed by human logical minds, and each part is engineered to perform a single function and do it optimally.  Organisms are evolved by a process that depends on results only and involves no logical thought. We have found empirically that in biology, parts tend to serve multiple purposes.  Causes and effects are entwined in tangled feedback loops. Hormones and other proteins are likely to serve multiple, overlapping functions, some of which are metabolic and some of which are regulatory.

With a homeostatic physical system, you can tweak it to the right and it will bounce back to the left some fraction of the distance, so that the net effect is to move to the right but with less than your original amplitude.  With a homeostatic biological system, you can tweak it to the right and it may bounce back and end up further to the left. The canonical example of this is hormesis, which is so counter-intuitive that it took experimental scientists two decades to establish its legitimacy among biological theorists.

The Challenge of Using AI to Modify Aging

Machine learning algorithms work by finding optimal paths toward a well-defined goal.  The machine learning paradigm needs a clearly-defined goal as a prerequisite. In the previous triumphs of machine learning listed above, the goal was well-defined before the process was begun.

Application of machine learning to anti-aging will require a quantified measure of biological age.  This is what has held up the field in the past. We can measure lifespans in worms in a few weeks, but to measure lifespans in humans takes decades.  Aging research needs feedback that is faster than this.

Just in the last year, there are epigenetic clocks based on methylation that predict future mortality and morbidity far better than any other metabolic test.  The bottleneck now is the availability of methylation data that is correlated to anti-aging interventions. That is why I have promoted the DataBETA project to collect methylation data from a diverse set of early-adopters of anti-aging interventions.

Using theory-free computer algorithms to search for anti-aging interventions is better than going about it with the wrong theory, but it’s not as effective as starting with the right theory.

This is larger than aging medicine

The culture of business has had a profound impact on science in general, not just aging science.  A hundred years ago, people who pursued science were motivated by pure curiosity and intellectual ambition, because there was little reward to be had.  Today, science is a career for something approching 10 million people worldwide.  Then, science was pursued by dogged individuals.  Now, science is managed by bureaucracies.

More patents have been issued since 2000 than all of history before. It’s often said that the number of working scientists is 10 times greater than all the scientists who have ever performed research in the past, but the actual figure is more than 100 times.

Credit: Future of Life https://futureoflife.org/2015/11/05/90-of-all-the-scientists-that-ever-lived-are-alive-today/

The advance in scientific data reflects this increase, and more.  To the extent that scientific productivity can be quantified, the productivity per scientist has increased as the number of scientists has advanced exponentially.

What we don’t have is exponentially more understanding.  It’s enlightening to compare the first half of the Twentieth Century with the second.  The first half** brought us revolutions in understanding:

  • Milliken made the electron real as Rutherford pointed to the structure of the atom
  • Planck told us the world is quantized
  • Einstein taught us to think in terms of a fabric of space-time, molded by matter-energy
  • Heisenberg and Schrodinger taught us that the quantum world is fundamentally interconnected and indeterminate
  • Godel surprised us with a demonstration that there are limits to mathematical certainty
  • Hubble discovered that there are hundreds of billions of galaxies beyond our own, and that they’re flying away from us, the further the faster
  • Lewis, Born, and Pauling gave us a science of chemical bonds based in quantum physics
  • Alpher and Gamow proposed the hot Big Bang universe
  • Franklin, Crick and Watson discovered the biochemical basis of genetics

What do we have in the second half of the century to compare? I’d put three things in the same league as the above list, and they are all observations for which a theoretical framework remains elusive:

  • Penzias and Wilson stumbled on the 3 degree microwave background, promoting Big Bang cosmology to the status of a quantitative science (1965)
  • Observations of distant galaxies proved that the expansion of the universe is accelerating; dark matter and dark energy were introduced as the least radical modification to established cosmology (1997)
  • Epigenetics came into its own in the 21st century, as it was discovered that big variations in gene expression are more important for the direction of life than small variations in gene sequence.

With so many more scientists, why aen’t we seeing new and powerfully synthetic theories?  It’s just not plausible that no one as smart as Newton or Euler or Darwin or Planck is alive today.  Then, are the “easy” problems all solved, and the remaining problems in science so much harder? Certainly that’s true to some extent.  But there is a larger part of the story, and it is the canalization of scientific thought. Scientists today are paid to be efficient. There is a model of productivity borrowed from industry that is completely inappropriate to science.

We are all agreed that your theory is crazy. The question that divides us is whether it is crazy enough to have a chance of being correct.                       — Niels Bohr (to Wolfgang Pauli)

Through the culture of business, science has become conservative, which is to say dogmatic.  It is more difficult than it used to be to throw out a theory that doesn’t work. Almost everyone is working to push outward in the directions that science has already advanced, but almost no one is digging at the roots, or exploring fundamentally new directions.  Almost everyone is engaged in the safe science of incremental advance and almost no one is taking the big risks.  Tenure is granted to fewer science faculty members, and they are getting tenure at later ages.  Career uncertainty makes scientists risk-averse.

With so much at stake, science is being managed by committees and bureaucracies.  They judge on the basis of conventional wisdom and measurable results.  Business by nature is risk-averse.  But in the long run, science can only advance when we scrap the idea of predictable returns on investment and accept a very high failure rate.

Part II next week: survey of biotech companies doing research in anti-aging medicine.

———————
* 20-fold increase is my estimate, a soft number.  I’ve been unable to identify hard statistics, and of course the very definition of “anti-aging” is changing as the idea that all diseases of old age can be delayed has come into general acceptance.

** I’ve taken the license to include two discoveries from 1952 in the first half of the century.

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Part I : The Business Culture of Science

Since 2000, there has been a 20-fold increase* in research funding for anti-aging medicine.  Wow! That’s a good thing. But let’s keep our eyes on the ball. There is danger that this welcome infusion of capital may be biasing research priorities toward those that are most likely to be profitable, and maybe even diverting the best researchers from the radical thinking that will change our understanding of biology.

Whoever discovers an effective age-reversal treatment is destined to become a multi-billionaire!

At first blush, this statement seems obvious, but that doesn’t mean it’s true.  There are many historical examples of people who gave enormous gifts to the world, but struggled in their lifetimes for recognition and even for a livelihood.  Schubert, Poe, and van Gogh are artists who died poor, while people after them reaped billions from their work. Inventors who never profited from their inventions include Johannes Gutenberg and Nikola Tesla, Jagadish Chandra Bose, and Antonio Meucci (who?).  Reginald Fessenden invented radio a generation before Marconi.  Rosalind Franklin got no credit for being the person whose diffraction data and analysis was stolen by Watson and Crick for their Nobel research on the double helix.  

More to the point, there have been great discoveries that had no commercial value, or even negative commercial value.  Linus Pauling spent the last years of his life documenting the anti-cancer action of intravenous vitamin C. To this day, vitamin C is under-utilized and under-studied precisely because it is so cheap that no one can get rich from it.  I believe that aspirin and metformin may be two of the most potent life extention drugs that we currently know about, but we can’t be sure, because they are both long out of patent, and no private company can justify the investment to study them.

Rumors abound about cancer cures and energy technologies that are being suppressed because they would derail two of the most profitable businesses in the history of capitalism.  I don’t dismiss such claims out of hand.

If there were a drug that could increase average human lifespan by 15 years (with side-effects that were wholly salutary), there would be a dozen companies tinkering with it, adding a methyl group here or a double bond there, looking for a variant that might boost lifespan by 18 or 23 years.  In fact, there is about a 15-year advantage for people who are in a loving relationship, have deep community ties, assume responsibility for leadership, make lots of money, enjoy frequent sex, and remain close to young family members; in comparison, the typical middle-aged American is lonely, alienated, struggling financially, and sub-clinically depressed, with a life expectancy 15 years shorter than it could be.  The most effective things you can do to increase your statistical life expectancy are psycho-social, but who is conducting research into optimizing the life-extending benefits of community and relationship?

Diet, exercise, saunas, and fasting are life extension strategies that are promising and under-researched because there is no clear path to mega-profits.

What I believe

I am convinced that the primary basis of aging is an epigenetic program.  Systems that repair and protect our cells and tissues are gradually shut down, and destructive systems including inflammation and apoptosis are ramped up at late ages. Gene expression changes, modified systemically by transcription factors that circulate in the blood.  I believe that these blood factors are the holy grail of aging research. Control over aging will come when we learn enough about the basic language of epigenetics to reprogram gene expression with our interventions.

The difficulty is that there are dozens of known epigenetic mechanisms, of which only a few have been studied in detail.  A few years ago, it was understood that modifying non-coding regions of DNA could affect the transcription of nearby genes (cis epigenetic signals), but now we know that transcription of genes far away from the modification can also be affected (trans signals).

There is yet more complexity: most hormones and regulatory molecules have secondary roles that affect transcription.  Imagine an ecosystem of signal molecules that maintains itself homeostatically, but also changes with age. Sixty years ago, we learned that the genetic code is as simple as it can logically be; every codon three base pairs on a DNA strand is uniquely transcribed to one amino acid, and a protein is built by chaining these together in order.  Today we are learning that epigenetics is about as complex as it can be. So in my paradigm, basic research in epigenetics is an essential foundation for anti-aging medicine. If we are lucky, a dozen synergizing interventions will do enough reprogramming to re-set the aging clock. Perhaps there is even a region of the brain that is a common source for the molecules that induce age-related change.  If we are unlucky, it may require re-balancing blood levels of hundreds of different substances.

I am optimistic that this can be done, but it will require collaboration on a broad scale.  The process is unlikely to end with a single patent-holder who can rake in $ billions. The secrecy and the balkanization of corporate research is slowing progress.

Biases in Corporate Aging Research

For the last five years, Google CALICO has been the 800-pound gorilla in the room.  Of course, we welcome their funding, the legitimacy they lend, and their collective brainpower to our field.  But they don’t play by academic rules. They are not following the open-source / free-to-the-public model that has been so successful for Google in software.  They trend secretive and are not collaborating with university experts outside their walls.

CALICO isn’t announcing its philosophy or paradigm, but we might guess from its lineage that their methodology is rooted in data mining and artificial intelligence.  Other companies that have announced publicly that they are taking this approach include Unity Biotech, InSilico Medicine and Spring Discovery.  They have in common a data-intensive approach founded in theoretical agnosticism.

Machine learning has been used successfully to create algorithms that translate languages, that drive cars, and that recognize faces.  The best thing you can say about this approach to anti-aging medicine is that it is free of the theoretical biases that have plagued aging research through the decades.  The worst thing you can say about it is that it misses a fundamental difference between organisms and machines.

Machines are designed by human logical minds, and each part is engineered to perform a single function and do it optimally.  Organisms are evolved by a process that depends on results only and involves no logical thought. We have found empirically that in biology, parts tend to serve multiple purposes.  Causes and effects are entwined in tangled feedback loops. Hormones and other proteins are likely to serve multiple, overlapping functions, some of which are metabolic and some of which are regulatory.

With a homeostatic physical system, you can tweak it to the right and it will bounce back to the left some fraction of the distance, so that the net effect is to move to the right but with less than your original amplitude.  With a homeostatic biological system, you can tweak it to the right and it may bounce back and end up further to the left. The canonical example of this is hormesis, which is so counter-intuitive that it took experimental scientists two decades to establish its legitimacy among biological theorists.

The Challenge of Using AI to Modify Aging

Machine learning algorithms work by finding optimal paths toward a well-defined goal.  The machine learning paradigm needs a clearly-defined goal as a prerequisite. In the previous triumphs of machine learning listed above, the goal was well-defined before the process was begun.

Application of machine learning to anti-aging will require a quantified measure of biological age.  This is what has held up the field in the past. We can measure lifespans in worms in a few weeks, but to measure lifespans in humans takes decades.  Aging research needs feedback that is faster than this.

Just in the last year, there are epigenetic clocks based on methylation that predict future mortality and morbidity far better than any other metabolic test.  The bottleneck now is the availability of methylation data that is correlated to anti-aging interventions. That is why I have promoted the DataBETA project to collect methylation data from a diverse set of early-adopters of anti-aging interventions.

Using theory-free computer algorithms to search for anti-aging interventions is better than going about it with the wrong theory, but it’s not as effective as starting with the right theory.

This is larger than aging medicine

The culture of business has had a profound impact on science in general, not just aging science.  A hundred years ago, people who pursued science were motivated by pure curiosity and intellectual ambition, because there was little reward to be had.  Today, science is a career for something approching 10 million people worldwide.  Then, science was pursued by dogged individuals.  Now, science is managed by bureaucracies.

More patents have been issued since 2000 than all of history before. It’s often said that the number of working scientists is 10 times greater than all the scientists who have ever performed research in the past, but the actual figure is more than 100 times.

Credit: Future of Life https://futureoflife.org/2015/11/05/90-of-all-the-scientists-that-ever-lived-are-alive-today/

The advance in scientific data reflects this increase, and more.  To the extent that scientific productivity can be quantified, the productivity per scientist has increased as the number of scientists has advanced exponentially.

What we don’t have is exponentially more understanding.  It’s enlightening to compare the first half of the Twentieth Century with the second.  The first half** brought us revolutions in understanding:

  • Milliken made the electron real as Rutherford pointed to the structure of the atom
  • Planck told us the world is quantized
  • Einstein taught us to think in terms of a fabric of space-time, molded by matter-energy
  • Heisenberg and Schrodinger taught us that the quantum world is fundamentally interconnected and indeterminate
  • Godel surprised us with a demonstration that there are limits to mathematical certainty
  • Hubble discovered that there are hundreds of billions of galaxies beyond our own, and that they’re
  • Lewis, Born, and Pauling gave us a science of chemical bonds based in quantum physics
  • Alpher and Gamow proposed the hot Big Bang universe
  • Franklin, Crick and Watson discovered the biochemical basis of genetics

What do we have in the second half of the century to compare? I’d put three things in the same league as the above list, and they are all observations for which a theoretical framework remains elusive:

  • Penzias and Wilson stumbled on the 3 degree microwave background, promoting Big Bang cosmology to the status of a quantitative science (1965)
  • Observations of distant galaxies proved that the expansion of the universe is accelerating; dark matter and dark energy were introduced as the least radical modification to established cosmology (1997)
  • Epigenetics came into its own in the 21st century, as it was discovered that big variations in gene expression are more important for the direction of life than small variations in gene sequence.

With so many more scientists, why aen’t we seeing new and powerfully synthetic theories?  It’s just not plausible that no one as smart as Newton or Euler or Darwin or Planck is alive today.  Then, are the “easy” problems all solved, and the remaining problems in science so much harder? Certainly that’s true to some extent.  But there is a larger part of the story, and it is the canalization of scientific thought. Scientists today are paid to be efficient. There is a model of productivity borrowed from industry that is completely inappropriate to science.

We are all agreed that your theory is crazy. The question that divides us is whether it is crazy enough to have a chance of being correct.                       — Niels Bohr (to Wolfgang Pauli)

Through the culture of business, science has become conservative, which is to say dogmatic.  It is more difficult than it used to be to throw out a theory that doesn’t work. Almost everyone is working to push outward in the directions that science has already advanced, but almost no one is digging at the roots, or exploring fundamentally new directions.  Almost everyone is engaged in the safe science of incremental advance and almost no one is taking the big risks.  Tenure is granted to fewer science faculty members, and they are getting tenure at later ages.  Career uncertainty makes scientists risk-averse.

With so much at stake, science is being managed by committees and bureaucracies.  They judge on the basis of conventional wisdom and measurable results.  Business by nature is risk-averse.  But in the long run, science can only advance when we scrap the idea of predictable returns on investment and accept a very high failure rate.

Part II next week: survey of biotech companies doing research in anti-aging medicine.

———————
* 20-fold increase is my estimate, a soft number.  I’ve been unable to identify hard statistics, and of course the very definition of “anti-aging” is changing as the idea that all diseases of old age can be delayed has come into general acceptance.

** I’ve taken the license to include two discoveries from 1952 in the first half of the century.

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Josh Mitteldorf - Aging Matters by Josh Mitteldorf - 3w ago

Every supplement has its downside.  Metformin and rapamycin are the best candidates among fully-developed products, and metformin can dissipate the benefits of exercise, while rapamycin can suppress immune response and raise insulin resistance.  NAD enhancers can affect epigenetic methylation and damage the liver.  I’ve written about the adverse effects of anti-oxidants, which are the most highly publicized treatments for aging.  But glutathione (GSH) is one anti-oxidant for which I’ve read multiple benefits, and I’ve never seen a negative word. As far as I know, the more glutathione you have, the healthier you can expect to be.  

Glutathione is akin to a miniature protein with just 3 amino acids (glutamate, cysteine, and glycine).  Our bodies manufacture glutathione regularly from the three constituent amino acids, but we make less of it when we are older, and need it more.  (In my book, this is an example of programmed aging, the body deliberately turning to self-destruction, but you don’t have to believe in programmed aging.

Glutathione

It was originally discovered as a recyclable anti-oxidant.  The most active and toxic ROS are reduced to the less toxic form, hydrogen peroxide, H2O2, and it is the job of glutathione to take care of the H2O2. The active (reduced) form is abbreviated GSH, and the ‘second-hand’ form, ready to be recharged, is GSSG.  Glutothione reductase is the enzyme that does the honors of restoring GSSG to GSH. Glutathione antioxidant activity depends on an enzyme containing the trace element selenium, which is available in a quirky variety of foods (brazil nuts, mushrooms) and in trace mineral supplements.

As the number of supplements I take has multiplied over the years, I have begun to randomize my intake, selecting from a shelf full of pills each morning based on whim as much as anything.  Through this transition, N-Acetyl Cysteine (NAC) is the one supplement that I keep handy and continue to take several times each day. NAC is a precursor and recharger of glutathione. After researching the present article, I’ve added raw glutathione to my pill shelf, for reasons you’ll read below.

N-Acetyl Cysteine

Cancer is a counter-indication (?)

H2O2 is not just a toxic byproduct; it is also a signaling molecule with multiple functions, including self-destruction of the cell.  GSH can lessen the propensity for apoptosis (cell suicide). This is generally a good thing in anyone over 50, but you might think twice about it if you’re actively battling cancer.

Not just an ordinary anti-oxidant

In addition to anti-oxidant activity, GSH is now known to have many other roles, including DNA repair, protein synthesis, and chemical signaling.  It is not obvious that the health benefits of GSH come from its role as anti-oxidant.

In the liver and kidneys, GSH binds to a broad variety of toxins and carcinogens, helping to neutralize them while they are being eliminated.  There are several common genetic variants that affect the hormones that assist in this process, glutathione S-transferases, or GSTs. People with GSTM-1 variants are more susceptible to most cancers, asbestos, lead and mercury poisoning, etc. The herb silymarin (milk thistle) increases the presence of glutathione selectively boosts glutathioneIn the liver. Hospital ERs use NAC for emergency detox, and in my personal experience a relative’s life was recently saved and liver damage avoided with intravenous NAC.

Animal evidence

Supplementation with NAC has been found to increase lifespan in several animal models, most important in male mice

(Female mice in this study with or without NAC live as long as male mice with supplementation.)

Human evidence

To my knowledge, there is no direct evidence in humans regarding lifespan or mortality benefits of NAC or glutathione.

Glutathione is produced within each cell, and cells produce less of it in older humans.   This is the reason glutathione levels decline as we age, about 40% between ages 30 and 70.  Not only do older people have less glutathione, but levels tend to be lowest in people with chronic disease of any sort [ref].

NAC can extend the capacity of muscles to resist fatigue, both in rodents and in humans [ref].  This is probably related to recharging glutathione in and around mitochondria as they expend energy.  Glutathione is especially useful in the energy metabolism, and there is evidence it is continually pumped into mitochondria.

Eating glutathione?

I have believed for a long while that GSH doesn’t survive stomach acid, and it’s worthless to take it orally.  This was based on the idea that GSH is a miniature protein, and the peptide bonds that hold proteins together are efficiently broken in the stomach.  Hence the time-honored way to get more GSH is to take NAC, which is a precursor which the body uses to make GSH.

I’ve learned there are several things wrong with this story.

  • Oral GSH is more bioavailable than I had thought.
  • NAC only can lead to more glutathione if the body is flush with the other two amino acids, glutamate and glycine.  For people who take NAC, glycine commonly becomes the bottleneck, so it helps to supplement with glycine as well.
  • NAC often doesn’t increase total glutathione, but “recharges” the GSSG form back to GSH.  So NAC can increase available glutathione up to a limit, but may not be sufficient to restore youthful levels in those of us who are past our youth.  Alpha lipoic acid also helps to regenerate GSH, and so supplementing with ALA also tends to increase GSH levels.
  • Liposomal and sub-lingual versions of glutathione are supposed to be more bio-available, but there’s not much data to support this, and the data seems to show only marginal improvement in bioavailability–not enough to justify the big difference in price.

Raw and Liposomal

Oral glutathione (raw) 250mg/day increased levels in red blood cells by about 30% over 6 months.   Increasing to 1000mg/day didn’t do significantly better [ref].  

Liposomal delivery is the encapsulation of the payload (glutathione) in microscopic droplets of vegetable oil, which protects the glutathione through digestion, and helps it pass through cell membranes.

I could only find a shorter-term study of liposomal glutathione [ref], and results were only marginally better than with raw glutathione.

In this study, a genetic defect that impairs glutathione efficiency is associated with low HDL and high trigycerides in the blood, which are two of the most telling indicators of cardiovascular disease.  In this study, people who come into the ER with heart attacks tend to have much lower glutathione than a control population that doesn’t have heart attacks.

The Bottom Line

Glutathione serves multiple protective functions.  The body manufactures less of it as we age.  There is good indirect evidence from several angles that glutathione is an anti-aging supplement.  In recent years, it has become clear that it can be taken orally with good effect.

Glutathione GSH is constantly being used as an antioxidant, after which it becomes GSSG, which needs to be recycled to GSH.  NAC helps in the recycling, so more glutathione is available in its active form. The action is short-term and doesn’t increase the total amount of glutathione.  Taking glutathione orally has a long-term benefit, increasing the total amount of glutathione in blood and in cells. Liposomal glutathione may be more readily absorbed than the simple glutathione pills, but it is so much more expensive that it’s hard to justify.  There is independent evidence for NAC as an anti-aging supplement in rodents. 

Chris Masterjohn has posted a review which seems to ask all the right questions, and I have taken much of my analysis from him.   

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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.

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As I wrote last spring, we can efficiently test treatments for aging once we have an objective measure for the rate of aging.  Without it, we’re left with the standard epidemiological: treating thousands of people and waiting for a few of them to die.  I have predicted that methylation-based aging clocks will turn a page in the history of epidemiology.

Six years ago, UCLA biostatistician Steve Horvath realized the potential value of an aging clock and set out to measure human age using methylation markers in DNA from across the body.  He used statistical pattern-recognition software to look for relationships between a person’s age and the methylation state of his DNA. Methylation is the best-studied of the epigenetic markers that control which genes are turned on and off, and different sets of genes are active at different stages of life.

thanks to the Horvath lab for this image

Age is an important predictor because the diseases that kill most of us all occur in a highly age-dependent way.  In fact, the risks for cancer, heart disease, and Alzheimer’s disease all rise exponentially with age.

One statistical result from the original Horvath clock has a profound implication which aging researchers have been slow to take to heart:  The Horvath clock was derived with statistical methods that looked only at chronological age. The algorithm was optimized to produce the best estimate of a person’s calendar age.  Of course, age by the calendar is a good predictor of a person’s risk of death. In Americans over 40, the probability of death doubles every 8 years.

We should expect that since the Horvath clock is well-correlated to age and age is well-correlated to mortality, the Horvath clock should be correlated to mortality.  (This isn’t guaranteed mathematically except when the two separate correlations are strong.) The interesting twist is this: The Horvath clock is more tightly correlated with mortality than age itself.  The clock algorithm was derived from chronological age, so the math knows only about calendar years. But the clock algorithm predicts mortality better than age itself.

We can conclude that this extra accuracy of the methylation clock derives not from math but from biology.  The message is that methylation is linked to the biological process of aging. Methylation changes don’t just happen over time; they are coupled to whatever it is that causes the risk of death to rise, linked, in other words, to aging itself.

With more recent developments in the clock, this conclusion gets stronger, and also stranger.

2017  The Zhang Clock

Yan Zhang of the German National Cancer Inst in Heidelberg has developed a methylation-based computation of mortality risk which is based on historic samples of blood from 406 people who died over a 15-year period and from 1,000 demographically-matched control.

They identify 58 sites that were tightly coupled to mortality.  In 49 out of 58, less methylation was associated with a higher risk of death, and in the other 9, more methylation led to higher risk of death.  (More methylation corresponds to less gene expression. The message is that increase in age-related mortality is due more to turning on genes that destroy us than to silencing genes that protect us.)

None (count ’em–zero!) of the 58 were incorporated in any of the previously published aging clocks (by Horvath and Hannum).  What do we make of this? Age is associated with mortality more closely than any other biological indicator, and in fact mortality risk rises exponentially with age.  And yet Zhang et al set out to look for methylation sites most closely associated with mortality risk, Horvath et al set out to look for methylation sites most closely associated with chronological age, and there was zero overlap between the sites they identified!  In fact, less than half the sites they identified (23/58) had statistically significant correlations with age at all.

The recently established epigenetic clock (DNAm age) has received growing attention as an increasing number of studies have uncovered it to be a proxy of biological ageing and thus potentially providing a measure for assessing health and mortality. Intriguingly, we targeted mortality-related DNAm changes and did not find any overlap with previously established CpGs that are used to determine the DNAm age. [Zhang]

Part of the explanation may be that Zhang’s study was conducted in an older population (median age=62) at higher risk of death, and that the Horvath clock to which he compared it was designed to generally reflect age, from womb to tomb.  Zhang says, “Methylation levels were measured on average 8.2 years before dying.”

Zhang’s mortality risk estimator is a count of how many of the 10 most telling methylation sites are in the “worst” quartile of his test population.  (The “worst” quartile is the highest quartile for some and the lowest quartile for other sites.) A score of 5 corresponds to a 7-fold increase in mortality risk.  This qualifies the Zhang score as one of the most powerful risk indicators that we have (don’t tell Aetna). For comparison, a BMI of 35 qualifies as “obese” and corresponds to a mortality risk ratio of only 1.36.  Hemoglobin A1C, and HDL are common indicators of health status in older adults, and all of these have marginal associations with age-adjusted mortality.  C-reactive protein and IL6 are blood markers of inflammation, and they were associated with risk ratios of 1.6 and 1.9, respectively [ref].  By this standard, the Zhang score is a big step forward.

Methylation is presumed to be under the body’s programmatic control.  There are two reasons that methylation might be powerfully associated with mortality.  First, some changes in methylation may be an indication of an acute response to some life-threatening stress; second, some changes in methylation may be part of an intrinsic death program associated with age.  My guess is that there is some of each going on, but probably more of the former, since (as I said) only 23 of the 58 sites are significantly correlated with age.

Another curious fact: the methylation sites associated with smoking provided a better indicator mortality risk than was smoking itself.  More about this below.

2018:  The Levine Clock

Morgan Levine, working with Horvath at UCLA, developed a second-generation clock last year based on mortality and morbidity data as well as chronological age.  The Levine clock was optimized with hindsight, factoring in age-related disease that occurred years after the blood was sampled.

Levine and her team worked in two stages.  First, they developed a measure they call “phenotypic age” which includes age itself plus 9 modifiers that contribute to mortality risk.

Albumin: dissolved proteins in the plasma, including hormones and other signal molecules.
Creatinine: this is a waste product cleared by the kidneys, thus a high value suggests kidney malfunction; but it can be confounded by exercise, which raises creatinine.
Glucose: blood sugar rises with Type 2 diabetes and loss of insulin sensitivity.
C-reactive protein: this is a measure of systemic inflammation.
Lymphocyte %: the most common types of white blood cells.
Mean red cell volume (MCV): the average size of red blood cells
Red cell distribution width (RDW): standard deviation of the above
Alkaline phosphatase (ALP): this is elevated in liver disease, including cancers and hepatitis.
White blood cell count: total white blood cells of all types

The list surprised me.  This was not a popularity contest; it was developed from statistical association with mortality, with no prejudices up front.  I was not surprised to see glucose and CRP in the list (though I would have thought they would substitute A1C for glucose, because A1C is more stable, while glucose varies from hour to hour).  I would have thought to find HDL and IL-6 in the list, and I was particularly surprised to see the strongest weighting was Red cell distribution width, which I had not heard of. RDW is measured as the standard deviation in volume of individual red blood cells (erythrocytes).  It turns out that small red blood cells are a symptom of diabetes, while high RDW scores are associated with cancer and heart disease.  There’s a modest association between RDW and Alzheimer’s Dementia.

Also curious: total white blood cell count is positively associated with aging diseases, while lymphocytes, a subset of white blood cells, has a negative association.  So, what are the white blood cells that are not lymphocytes? These comprise neutrophils, eosinophils, monocytes, and basophils. Large quantities of these are a warning of bad health to come.  Neutrophils are the largest category among these, and they are part of the body’s innate defense against cancer and infections.  Lymphocytes, on the other hand, comprise natural killer (NK) cells and T- and B-cells. NK cells are part of the innate immune system, while T-and B-cells are part of the adaptive immune system, but all of these are indicative of good health and long life.

All these components were put together by Levine et al to form their measure of phenotypic age.  The team then went on to stage two, looking for methylation sites that correlate best with their newly-defined measure of phenotypic age.  513 sites were incorporated in their computation (see below).  This can be confusing:  PhenoAge is the measure derived from the above 9 blood tests + chronological age.  DNAm PhenoAge is the methylation clock derived from the PhenoAge blood test.

The resulting PhenoAge methylation clock (DNAm PhenoAge) correlates only about 75% with chronological age (compared to 94% for the original Horvath clock).  But DNAm PhenoAge predicts mortality and morbidity far better than either chronological age or the original Horvath clock. As you might expect, the methylation clock which was derived from the newly-invented PhenoAge measure does not predict mortality rates as well as PhenoAge itself, from which it was derived.  This is expected because the DNAm PhenoAge clock is targeted directly to predict PhenoAge, and only indirectly to predict mortality. I am only making a point of this because the story is different and surprising in the case of the new GrimAge methylation clock–described next week.

Fifty sites vs Five Hundred

The first step in producing a clock is to produce a list of individual methylation sites in order of how tightly they correlate with age.  If you construct a clock out of the first few, you get the best correlation and the most accurate measure of age. But the measure is fragile, and the accuracy may be illusory.  When selecting a few items out of a list of hundreds of thousands, there will usually be accidents and outliers, statistical flukes. By including more sites assures that the overall age measure is not unduly affected by any one site, so if a few of the correlations turn out to be statistical errors, the overall average is still quite good.  Horvath has generally chosen to be conservative and sacrifice some accuracy for robustness.

Next week, the new GrimAge clock…

Methylation measurements have provided the most accurate measure of age and prediction of age-related disease, head and shoulders above other measures.  But can we do even better if we supplement methylation data with other things we know about a person–not just other blood tests, but life style factors.  When I visited Horvath last summer, he introduced me to his post-doc Ake Lu, who was working on a composite clock, based on this thinking: methylation plus.  That was the origin of the GrimAge clock.

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I say “rumors” because there is no publication and results from just 6 rats, all of which were sacrificed for the sake of tissue biopsies.  Worse, we have no announcement of what the active agent(s) were that rejuvenated the rats, so discussion of mechanisms will have to wait. I’m writing this largely from personal and scientific trust, while recognizing that even the most careful and honest scientists can deceive themselves.  “You are the easiest person to fool,” Feynman warned us.

Some of you may recognize the name of Dr Harold Katcher, who is one of the most prolific and best-informed among many well-informed readers commenting on this blog.  I’ve known Harold for about 10 years. We came together because we have the same idea about what aging is. The difference is that I have only the evolutionary reasoning, the logical shell.  Harold also has the background in biochemistry to fill in the details. Filling in the details is what he has been doing, and this week he convinced me that he has the most promising age-reversal intervention yet devised.  His treatment protocol is in preliminary stages of testing, and because the ideas that he and I share are out of the mainstream, it has not been easy for him to get funding. Now that he has preliminary results, perhaps that is about to change.  He is committed to bypassing the standard channel of Big Pharma, proceeding on his own with appropriate partners to assure that the the technology gets to a wide public at affordable prices–but it is early to think in these terms.

The heretical idea that unites Harold’s thinking and mine is this:  Aging is controlled through evolutionarily conserved mechanisms. Some of the same genes and proteins that control the rate of aging in yeast cells serve the same function in mammals, which may live a thousand times longer than yeast.  This implies that aging isn’t just random damage to individual cells; rather it is tightly regulated at the systemic level. Maybe there is a central clock, or maybe there is a consensus that is reached body-wide. But in any case, there is communication, assuring that different parts of the body keep to a common schedule.  The natural place to look for this communication of the age state of the body is through signal molecules in the blood.

Thus our hypothesis, Harold’s and mine, is that even an old body remembers how to be young, if only it gets the message in the appropriate biochemical language.  If an old mouse were to have the blood of a young mouse coursing through its veins, the old mouse would become a young mouse. Parabiosis experiments, sewing together mice of different ages so that they share a common blood supply, originated in the 19th century, but they took a leap into the 21st century beginning in the Stanford laboratory of Irv Weissman.  His students spread out to Berkeley and Harvard, and the successors to these programs are studying the rejuvenation potential of various blood plasma components.  (It’s not the red blood cells or the white blood cells. It’s not any cells at all, but the proteins and RNAs and short peptides that are dissolved in the blood’s clear liquid background, called plasma.)  Some of the best-known people working on this idea are Mike and Irina Conboy at Berkeley, Amy Wagers at Harvard, Tony Wyss-Coray at Stanford. Two companies (Ambrosia and Alkahest) have begun selling transfusions of young blood to wealthy old folks, brave or desperate enough to experiment on themselves with untried technology, and to pay for the privilege.  

Harold doesn’t have the funding or the university infrastructure that these people have, but by his report he has leapfrogged their research.  He claims to have isolated the crucial molecules in young blood plasma, and that it is feasible in the not-too-distant future to synthesize them, so we’re not all running like vampires after 20-something men and women, bidding up the price of their blood.

His experimental results are preliminary, but impressive.  On the one hand, there are big questions that remain; on the other hand, I’ve never seen success like this from any other intervention.  (The possible exception is the Mayo Clinic’s work with senolytics, extending the lives of older mice; but the two approaches are so very different and what we know about the two is so different that there is no basis for saying one is more successful or more promising than the other.)

So, what were the results that we find so impressive?  I’ve linked to his own chart of results, and I’ve asked Harold to tell us in his own words.

To tell you the truth, when I first was invited by my partner, Akshay Sanghvi to conduct research at a laboratory in Mumbai (India, formerly ‘Bombay’) I had a very definite idea of what I wanted to do.  I wanted to transfer the plasma of a young rat, to replace the plasma of an old rat, which I have called Heterochronic Plasma Exchange (HPE).  This idea was originally based on heterochronic parabiosis, which apparently resulted in rejuvenation at the cellular level in mice, but without  the bizarre and cruel aspects of sewing two animals together; and yet, it should have more profound effects as 100% of the old animal’s blood could be replaced–while in heterochronic parabiosis, a young rat is half the weight of an old rat, so that the combined plasma circulation in the parabiots is considerably less than 50% young plasma.   If it is assumed that there are ‘pro-aging’ factors in the blood plasma of old animals, those factors would remain. By using HPE however, sufficient rounds of plasma replacement should leave the old animal with nearly pure ‘young’ plasma. The greater concentration of youthful factors and the absence aging factors should push the cells and, eventually, the body to youthfulness.  

Although transfusion technologies for humans are mature and quite safe, transfusing small animals requires state-of-the-art lab techniques. Try as we might, we could not perform plasma exchange in rats. Time was growing short (I was on a two-month visa) so what to do? I made the decision to completely change my approach: yes I believed HPE would work, but I decided to leap ahead, to see if we could make the process of HPE into a marketable product.

Our first pass was to try a combination of known herbal supplements that are known to bind with the targets we’d identified.  We gave them to rats, and at first nothing seemed to be happening. But after two months (about 4 years in human terms) the rats showed signs of rejuvenation.  We were encouraged. Rather than continue with the herbs, though, we formulated the elixir that we report on here. This is our first iteration, with dosage and timing determined theoretically, yet to be optimized in the lab.

We have addressed several different problems:

  1. Identification and purification of youth-inducing factors and a process for their large-scale production. Our processes are scalable from microliters to metric tonnes
  2. Raw material supply: we have gone beyond the need to obtain blood from young people, our sources are virtually limitless
  3. Removal of the effects of ‘pro-aging-factors’.  We have discovered a way to do that, one hidden in plain sight.

Here are our results.  Notice the striking and simultaneous occurrence of increases in mental speed and physical strength coupled with lower inflammatory markers and blood glucose levels.  Also encouraging is that these changes began days after the IV treatment, and the markers that were improved but not quite down to youthful levels continued to improve right up until the day of their sacrifice. It would appear that the changes induced are permanent, but it will take additional experimentation to confirm this.

Clearly, our next steps are

  • repeating and extending our rat results to include molecular and epigenetic signs of aging (Steve Horvath is developing a methylation clock for rats).
  • extending results to dogs (in collaboration with Dr Greg Fahy)
  • Looking for other molecular changes, including telomere length and various mitochondrial parameters
  • and, of course trying the elixir in humans.   

I am looking ahead to envision an elixir that brings you back to apparent youth in a week and a day with no side effects.  Time will tell, but I feel that the results we have at this point justify optimism.

— Harold Katcher

I’m full of questions, but Harold tells me these will have to wait until intellectual property is secured.

  • For some interventions, the body is made stronger and levels of tissue growth repair are restored to youthful states, but there is a cost in elevated cancer risk.  This is something that will take time to determine, and perhaps working with mice would be better, since they have higher cancer rates than rats.
  • I would guess that a fully youthful phenotype will require restoration of the thymus, which shrinks severely with age both in rats and humans.  The current report doesn’t mention thymic regrowth.
  • What would rejuvenation look like in humans?  Physical strength and mental acuity are a great start.  Would my eye lenses soften to youthful levels?  Would I grow new discs between my vertebrae (and regain the 2″ I’ve lost in the last decade)?  How about teeth and hair?
  • I’ve read that many blood factors are transient, with a half-life of seconds to minutes.  I can imagine long-term effects from epigenetic reprogramming through blood factors, but I’m surprised this could happen without a continuous IV feed.
  • And, of course, I’m curious about the content of the elixir.  Thousands of different compounds have been isolated from blood plasma, and hundreds that differ between young and old.  I think of the Conboys as leaders in this field, and when I spoke to them less than two years ago, they had been unable to identify a small subset of key factors that would induce changes in the rest.  Harold has said, “these factors are ‘bio-similar’ to factors already present in the blood, they work by natural means…”

The bottom line

I respect Harold’s caution in protecting his discovery out of the reach of Big Pharma.  On the other hand, so many questions are not being addressed because his resources are limited.  This is indeed a very promising start, and let’s hope that the appropriate connections come along so that further experiments can proceed without delay.

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At year end, I have a tradition of writing a column more speculative and personal than usual.  In this post, I consider critically the standard physicalist belief that our consciousness depends on a physical brain, and hence death is the end of all awareness. 

I was 46 years old when I first considered the question, what is aging and where does it come from?  Before that, I had been a physicist with diverse scientific interests pretty much all my life. What was I thinking?  Why had I never considered this topic before? I think the answer is: fear.

Ever since I can remember, I’ve been interested in preserving my health and extending my life.  But it was several years into a committed study of aging science that I thought to ask, why? Do I love life especially well, or am I afraid of death?

I’ve gradually come to realize that fear of death has cast a shadow over my thinking about aging, and possibly about many other other things as well.  I was a young child when I taught myself to avoid thinking about death because I couldn’t handle the abyss of terror into which my thoughts spun. As I developed the habit of tiptoeing around thoughts and discussions of death, what was I missing?  I’ve come to think that whole areas of my humanity became occluded, and have only begun to re-emerge in recent years.

In 1972, Ernest Becker wrote a book called The Denial of Death, which I knew even then that I ought to read.  I bought it, but years went by and it never made it remained unopened on my bookshelf.  Becker proposed that all of human civilization—art and literature, architecture, music, settlements and empires, stories of heroism, religious teachings, projects great and small—all of it stems from a drive to compensate for our mortality by creating something more permanent than our physical selves.  Even if this is only a little true, we have to wonder: Who would we be if we weren’t trying so hard to avoid death?

The Bhutanese people are reputed to be the happiest in the world.  Their mountains are majestic, their lifestyle modest and close to the land; but in this they are no different from many nations whose people seem to be pitiable.  So what is their secret? Eric Weiner tells us that their culture is steeped in death rituals, and that death is out in the open in Bhutan.  Bhutanese Buddhists contemplate their own death five times a day. Weiner goes on to cite studies that suggest thinking about death makes us more joyous.  These studies wouldn’t convince anyone, unless they wanted to be convinced. Maybe I want to be convinced

Of course, Buddhism is pervasive in Bhutan, with its belief that our souls cycle through birth and rebirth in karmic cycles.  Death is not a final end. The abyss that terrified me is not part of their belief system. I used to try consoling myself with such possibilities, but I got nowhere.  This is not science, it’s wishful thinking. Religions have manipulated people with promises about life after death since the dawn of human civilization. I’m too smart to be deceived with such fairy tales.  Even if it makes me afraid, even if it paralyzes me with terror, I prefer the realism of science.

But there came a point when it occurred to me maybe that the immortal soul was the reality and the fear was the delusion.  Did I believe in the Great Void just so I could feel smarter than people who believed in heaven? I peeked out from my fear just enough to question whether the abyss was a scientific deduction, or merely an artifact of scientific culture. Science or scientism?

But there came a point when I wondered whether the self-delusion was in the belief that it was all wishful thinking.  I peeked out from my fear just enough to question whether the abyss was a scientific deduction, or merely an artifact of scientific culture. Science or scientism?

Let’s backtrack to a different scientific myth.  We have been effective in reversing the scientific prejudice that says human lifespan is a fixed, unalterable fact of our biology. Given the intellectual bankruptcy of this thesis, why would so many people, scientists especially, have embraced it for so long?  One reason is the experience with being disappointed by charlatans, fooled by mountebanks, alchemists and snake-oil salesmen who have profited from their customers’ willingness to believe. Perhaps a larger reason is the fear of death that they have walled off with a kind of despair masquerading as science.  Hope is often more frightening than despair. As Milton wrote, “So farewell hope, and with hope farewell fear.”

They leave their hope behind so they don’t have to face the discomfort of their fears.  We have exposed their unreason.

Now, I wonder if we have been drawn into the same dynamic: that we have relinquished a hope that is too uncomfortable to carry.  The hope we have relinquished is that the “self” persists in some form and awareness continues after physical death. For most of my life, I believed that physical reality is the only reality there is, that anything I feel as a “self” depends on 100 billion neurons and a blood supply.

And yet, my primary experience, the only thing of which I am truly certain, is that I exist as a point of consciousness, a primal self-awareness that all our science (as Chalmers has pounded home to us all) is powerless to explain.  Many of us believe (with Dennett) that, since physical reality is the only reality, this primal self-awareness must be an epiphenomenon of neural activity in the physical brain—some would say an illusion created by computation. Maybe this is true, but there is no scientific support for this statement, nor does scientific evidence weigh against it.  The statement that our feeling of self derives from computation is an article of faith, or of Scientism, rather than anything for which we can adduce evidence.

And for me, this idea is counter-intuitive.  I have a meditation practice. I have studied astrophysics and quantum mechanics.  I go for long walks in the woods and I allow my mind to run all over such topics, and the result until now has been for me to trust this feeling of selfhood more than I trust any reasoning about an alleged physical basis.  The light of my awareness is a truth unto itself.

“Yeah, yeah,” says my scientific training, “where’s the evidence?”  Evidence there is aplenty, but it is ignored by the scientific mainstream.  Some of it is recognized as anomaly that we will understand someday, even though it seems strange now.  The more direct kinds of evidence are actively suppressed, banned from mainstream scientific journals and exiled to the Journal of Scientific Exploration and other publications of mixed quality, where it takes some patience to separate the wheat from the chaff.

In the former category are some of the anomalies cited at the beginning of the Michael Levin video that I reported on last week.  Caterpillars whose brains are literally dissolved in morphing into a butterfly, and yet memories survive.  Monarch butterflies that pass memories about the route to return home over half a dozen generations. Ciliated protozoa that are capable of learning and memory, though they have no nerve cells.  People who develop a musical ability or an interest in motorcycles or a vegetarian conviction when they receive a heart transplant.

In the latter category are a number of experiments for which the best source might be Dean Radin’s books, for example Entangled Minds and The Conscious Universe.  There are near-death experiences, in which people have memories, often blissful and love-filled, from the time when there was no neural activity in their brains.  Reflexively, the scientific rationalists dismiss these reports as fantasy creations of the oxygen-starved brain. But in many cases, the person recovering from an NDE reports things she would have no way of knowing if she had not been conscious during the time she was clinically dead.  My introduction to NDE science was by Pim van Lommel. His latest book is Infinite Awareness.  Similar stories have been collected by John Hagan, Chris Carter, Eben Alexander, and others.  Finally, there is the scientific study of reincarnation, pioneered in the West by the late Ian Stevenson, professor of psychiatry at University of Virginia.  His work has been continued by Jim Tucker at UVa and Raymond Moody (his book), Roy Stemman, and others elsewhere.  Carol Bowman researched and documented one spectacular case of a Louisiana couple, non-religious skeptics, whose 2-year-old son had persistent nightmares, then displayed uncanny knowledge about the crash of a World War II fighter plane in Iwo Jima.

Why does the mainstream scientific community persist in dismissing all this research without evaluating it?  Because it conflicts with a strictly-materialist, “scientific” world-view formed in the 19th Century, when the world of science was suffering under the delusion that every natural phenomenon might soon be explained by deterministic laws.  A few decades later, quantum physics put that aspiration to rest, and offered a mechanics at the foundation of science that has room for mind, for intention, for Cartesian dualism, for those who see fit to interpret quantum mechanics in that light.  Quantum mechanics may be 90 years old, but the scientific world has yet to absorb its message.  In particular, it has been shown in independent experiments by Radin, Jahn, and others that the events that are treated as “random” in QM can be influenced by conscious intent, without any recognized physical connection between the brain and the quantum system.  Furthermore, this connection is stronger when there is an emotional stake in the outcome, and its force increases non-linearly with the number of people whose attention is focused on a quantum target.

My tentative conclusion from this is that there is room within what quantum mechanics treats as “random” for (non-material) mind to influence material reality.  And there is evidence from experiment and anecdotes that this actually occurs.  Hence, the door remains open for a non-material locus of selfhood, or some aspect thereof.

“Despite the unrivaled empirical success of quantum theory, the very suggestion that it may be literally true as a description of nature is still greeted with cynicism, incomprehension, and even anger.”   — David Deutsch
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Josh Mitteldorf - Aging Matters by Josh Mitteldorf - 4M ago

Every supplement has its downside.  Metformin and rapamycin are the best candidates among fully-developed products, and metformin can dissipate the benefits of exercise, while rapamycin can suppress immune response and raise insulin resistance.  NAD enhancers can affect epigenetic methylation and damage the liver.  I’ve written about the adverse effects of anti-oxidants, which are the most highly publicized treatments for aging.  But glutathione (GSH) is one anti-oxidant for which I’ve read multiple benefits, and I’ve never seen a negative word. As far as I know, the more glutathione you have, the healthier you can expect to be.  

Gutathione is akin to a miniature protein with just 3 amino acids (glutamate, cysteine, and glycine).  Our bodies manufacture glutathione regularly from the three constituent amino acids, but we make less of it when we are older, and need it more.  (In my book, this is an example of programmed aging, the body deliberately turning to self-destruction, but you don’t have to believe in programmed aging.

Glutathione

It was originally discovered as a recyclable anti-oxidant.  The most active and toxic ROS are reduced to the less toxic form, hydrogen peroxide, H2O2, and it is the job of glutathione to take care of the H2O2. The active (reduced) form is abbreviated GSH, and the ‘second-hand’ form, ready to be recharged, is GSSG.  Glutothione reductase is the enzyme that does the honors of restoring GSSG to GSH. Glutathione antioxidant activity depends on an enzyme containing the trace element selenium, which is available in a quirky variety of foods (brazil nuts, mushrooms) and in trace mineral supplements.

As the number of supplements I take has multiplied over the years, I have begun to randomize my intake, selecting from a shelf full of pills each morning based on whim as much as anything.  Through this transition, N-Acetyl Cysteine (NAC) is the one supplement that I keep handy and continue to take several times each day. NAC is a precursor and recharger of glutathione. After researching the present article, I’ve added raw glutathione to my pill shelf, for reasons you’ll read below.

N-Acetyl Cysteine

Cancer is a counter-indication (?)

H2O2 is not just a toxic byproduct; it is also a signaling molecule with multiple functions, including self-destruction of the cell.  GSH can lessen the propensity for apoptosis (cell suicide). This is generally a good thing in anyone over 50, but you might think twice about it if you’re actively battling cancer.

Not just an ordinary anti-oxidant

In addition to anti-oxidant activity, GSH is now known to have many other roles, including DNA repair, protein synthesis, and chemical signaling.  It is not obvious that the health benefits of GSH come from its role as anti-oxidant.

In the liver and kidneys, GSH binds to a broad variety of toxins and carcinogens, helping to neutralize them while they are being eliminated.  There are several common genetic variants that affect the hormones that assist in this process, glutathione S-transferases, or GSTs. People with GSTM-1 variants are more susceptible to most cancers, asbestos, lead and mercury poisoning, etc. The herb silymarin (milk thistle) increases the presence of glutathione selectively boosts glutathioneIn the liver. Hospital ERs use NAC for emergency detox, and in my personal experience a relative’s life was recently saved and liver damage avoided with intravenous NAC.

Animal evidence

Supplementation with NAC has been found to increase lifespan in several animal models, most important in male mice

(Female mice in this study with or without NAC live as long as male mice with supplementation.)

Human evidence

To my knowledge, there is no direct evidence in humans regarding lifespan or mortality benefits of NAC or glutathione.

Glutathione is produced within each cell, and cells produce less of it in older humans.   This is the reason glutathione levels decline as we age, about 40% between ages 30 and 70.  Not only do older people have less glutathione, but levels tend to be lowest in people with chronic disease of any sort [ref].

NAC can extend the capacity of muscles to resist fatigue, both in rodents and in humans [ref].  This is probably related to recharging glutathione in and around mitochondria as they expend energy.  Glutathione is especially useful in the energy metabolism, and there is evidence it is continually pumped into mitochondria.

Eating glutathione?

I have believed for a long while that GSH doesn’t survive stomach acid, and it’s worthless to take it orally.  This was based on the idea that GSH is a miniature protein, and the peptide bonds that hold proteins together are efficiently broken in the stomach.  Hence the time-honored way to get more GSH is to take NAC, which is a precursor which the body uses to make GSH.

I’ve learned there are several things wrong with this story.

  • Oral GSH is more bioavailable than I had thought.
  • NAC only can lead to more glutathione if the body is flush with the other two amino acids, glutamate and glycine.  For people who take NAC, glycine commonly becomes the bottleneck, so it helps to supplement with glycine as well.
  • NAC often doesn’t increase total glutathione, but “recharges” the GSSG form back to GSH.  So NAC can increase available glutathione up to a limit, but may not be sufficient to restore youthful levels in those of us who are past our youth.  Alpha lipoic acid also helps to regenerate GSH, and so supplementing with ALA also tends to increase GSH levels.
  • Liposomal and sub-lingual versions of glutathione are supposed to be more bio-available, but there’s not much data to support this, and the data seems to show only marginal improvement in bioavailability–not enough to justify the big difference in price.

Raw and Liposomal

Oral glutathione (raw) 250mg/day increased levels in red blood cells by about 30% over 6 months.   Increasing to 1000mg/day didn’t do significantly better [ref].  

Liposomal delivery is the encapsulation of the payload (glutathione) in microscopic droplets of vegetable oil, which protects the

I could only find a shorter-term study of liposomal glutathione [ref], and results were only marginally better than with raw glutathione.

In this study, a genetic defect that impairs glutathione efficiency is associated with high low HDL and high trigycerides in the blood, which are two of the most telling indicators of cardiovascular disease.  In this study, people who come into the ER with heart attacks tend to have much lower glutathione than a control population that doesn’t have heart attacks.

The Bottom Line

Glutathione serves multiple protective functions.  The body manufactures less of it as we age.  There is good indirect evidence from several angles that glutathione is an anti-aging supplement.  In recent years, it has become clear that it can be taken orally with good effect.

Glutathione GSH is constantly being used as an antioxidant, after which it becomes GSSG, which needs to be recycled to GSH.  NAC helps in the recycling, so more glutathione is available in its active form. The action is short-term and doesn’t increase the total amount of glutathione.  Taking glutathione orally has a long-term benefit, increasing the total amount of glutathione in blood and in cells. Liposomal glutathione may be more readily absorbed than the simple glutathione pills, but it is so much more expensive that it’s hard to justify.  There is independent evidence for NAC as an anti-aging supplement in rodents. 

Christ Masterjohn has posted a review which seems to ask all the right questions, and I have taken much of my analysis from him.   

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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 and 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 methylation clocks correlate in the wrong direction with telomere clocks is puzzling.

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.

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