CRISPR update

I believe that all we have to do to make ourselves younger is to turn on the genes that were expressed when we were young, and turn off the genes that are expressed when we are old. This will require both knowledge and technique; (1) knowing which genes these are, and (2) having a targeted mechanism for turning specific genes on and off in vivo. At this time, our technique is advancing nicely, outpacing the knowledge, thanks to CRISPR / Cas9.

I wrote nearly two years ago that CRISPR was a third-generation technology for editing the genome, which could also be adapted to “edit the epigenome” by turning genes off.  Turning genes on was, and still is more difficult.  The work-around is to add extra copies of the gene, which can be a higher-risk operation, because the body has no evolved mechanisms for deciding when to turn the extra copy on and off.

The older technology of AAV (Adeno-Associated Virus) can be deployed within the living body, transfecting large numbers of cells and inserting a payload gene (of limited size); but there is no control over where in the genome the gene is inserted, and so there is no assurance that it is turned on or off at appropriate times and places.  The newer technology of CRISPR is precisely targeted, can remove or insert a gene, can turn a gene off (but not on).  But so far it is only possible in cell cultures in the lab, and not for large numbers of cells within a living organism.

There are thousands of clinical trials worldwide for AAV gene therapies, and last week the first clinical trial was announced for CRISPR as a cancer therapy.  The protocol is to extract the patient’s own T cells from a blood sample, then modify the cells in lab culture using CRISPR.

The researchers will remove T cells from 18 patients with several types of cancers and perform three CRISPR edits on them. One edit will insert a gene for a protein engineered to detect cancer cells and instruct the T cells to target them, and a second edit removes a natural T-cell protein that could interfere with this process. The third is defensive: it will remove the gene for a protein that identifies the T cells as immune cells and prevent the cancer cells from disabling them. The researchers will then infuse the edited cells back into the patient.

This is a modest first effort in many ways–not just that it is limited to 18 patients and nominally seeks only safety data.  There is great potential for sensitizing the T cells to the patient’s particular cancer.  It would also be logical to combine CRISPR with stem cell therapy.  A patient’s bone marrow stem cells could be harvested, modified with CRISPR, and re-injected, whereupon they would create an ongoing supply of sensitized T cells.  Neither of these ideas will be attempted in this first trial.

The Nature article goes on to recall the tragedy of the first gene therapy trial to kill an 18-year-old patient in 1999, and how gene therapy research lost a decade dealing with safety issues after that.

Hydrodynamic Gene Therapy

This is a kind of brute force method for delivering a genetic payload.  A large volume of dissolved DNA is injected directly into a vein, rapidly enough to raise blood pressure system-wide for a few seconds.  The pressure pushes some of the payload through capillary walls.  This system has been widely adapted for rodent experiments, with a tail vein used as the delivery point.  It has even been tried in humans.  But it is crude and untargeted.  Penetration rates remain low, and collateral damage is unavoidable.


Incorporating CRISPR into Gene Therapy

Of course, what we would really like is the specificity of CRISPR combined with the wide in vitro delivery provided by AAV gene therapy.  The complete machinery for Cas9 to break the DNA strand in a chosen location is too large a payload to fit within the AAV virus.  So marrying CRISPR to AAV has been the subject of some ingenious research just in the last two years.  The first successful experiment was announced this past winter in Nature Biotech.  An MIT-based research team reports that in a single treatment, they are able to make targeted modifications to 6% of white blood cells in a lab mouse.  I’m out of my depth reading about their technique, but from what I understand, there are separate delivery systems for the gene (via AAV virus) and for the targeting (via nano-particles of Cas9 enzyme dissolved in organic fats).  The former makes its way efficiently to the cell nucleus, because that it is what the virus was evolved to do.  The latter must be relied upon to diffuse into the nucleus at random, and the microencapsulation facilitates its transit.

Once inside the nucleus, the Cas9 breaks the chromosome in just the right place, and the virus seizes the opportunity to insert its payload conveniently.  The authors emphasize the importance of eliminating the Cas9 promptly.  If it were part incorporated in the virus, there would be a danger of ongoing, long-term DNA breaks; but the nano-particles containing Cas9 are short-lived.

Here is a recent review of progress in combining CRISPR with viral vectors for gene therapy, written at a technical level.  The Concluding Remarks section speculates on the possibility of combining three separate viruses for delivery of the CRISPR template, the Cas9 enzyme, and the genetic payload.  The obvious problem with such a system is going to be that each of these three viruses has a limited penetration, and it will only be in cells that all three viruses have transfected that the right thing happens (double-stranded break in just the right place, followed by insertion of the payload gene).  In the much larger number of cells that receive one or two of the viruses, there is the probability of damaging side-effects.


A Tangle of Signals

In the fable of the Sorcerer’s Apprentice (and a hundred myths from ancient Africa, Europe and the Orient), the protagonist is attracted to the quick acquisition of power, less interested in the slow acquisition of wisdom.  Exercise of power without wisdom is the classical gateway to tragedy.

And so we see our labs acquiring control over the genome and over gene expresssion proceeding apace, while understanding of the tangle of signaling pathways lags behind.  Many of us are now convinced that aging is controlled by epigenetic signals.  We are beginning to map difference in gene experesssion that occur with age.  But which genes are upstream and which are downstream?  Which are cause and which are effects?  Which are tissue-specific, and which are systemic signal molecules?

It now appears that the technology to modify gene expression will be ours before we know how to use it.

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Rapamycin Redux

Rapamycin is the best anti-aging treatment yet discovered.  Most treatments that work in flies and worms fail when they get to mammals, but rapamycin has consistently extended lifespan more than 20% in mice [review as or 2014].  It works even when administered late in life, and intermittent dosing works as well or sometimes better than daily dosing.

Too bad that rapamycin is too dangerous for general human use.  It is a powerful immune suppressor, used, in fact, to keep kidney transplant patients from rejecting the foreign tissue.  People who take rapamycin are it elevated risk from infectious disease, and who knows but that the immune suppression might inhibit the body’s ability to detect and eliminate incipient tumors.  So there’s a search on for safer “rapalogs” that work through the same TOR (“target of rapamycin”) pathway, but without the side effects, especially with respect to immune suppression.

But what if rapamycin isn’t dangerous?  What if people who take rapamycin don’t get sick any more often, and their cancer risk is actually significantly decreased?  Might rapamycin be a safe and effective anti-aging drug, available now?

Last month, two encouraging reports came out of the research on rapamycin.  One short-term test in marmoset monkeys seemed to show that “immune suppression” was a bogeyman.  There were no adverse effects, even from continuous, long-term administration.  Daily dosage in this test was 1mg/kg, which is the same as used in mice, and 50 times larger than typical human dosages, if calculated with strict scaling by body mass.  (For organ transplant patients, dosages range from 1 to 5 mg per day.)  Scaling of dosage is a not an exact science, and 1 mg per kg of body weight is certainly too large a dosage for our body size.

Marmosets live about 12 years, and there is not yet any data on whether lifespan is affected by rapamycin.

Marmoset monkeys weigh less than a pound.

Mice and some people on rapamycin tend to have high blood sugar, which in humans and mice is associated with risk of all age-related disease.  But the marmosets didn’t have high blood sugar.

Authors of the marmoset paper note that all studies of rapamycin in humans involve people who are sick enough to need an organ transplant, and are taking many other drugs.  We don’t know anything about the effect of rapamycin alone in healthy humans.  Maybe rapamycin enhances the suppression of tissue rejection from other drugs without in itself suppressing the immune system.   This study claims that everolimus actually enhances immune function in elderly humans. (Everolimus, a.k.a. RAD001, is a chemical cousin of rapamycin, a.k.a. Sirolimus, that is used similarly to prevent tissue rejection by organ transplant patients.  Both rapamycin and everolimus act by suppressing the mTOR signal.

Coming down to earth, this study found that in cancer patients treated with everolimus, risk of infection was about double, and in this study, mice infected with influenza and treated with an anti-viral agent did a little worse when rapamycin was added to the cocktail.  But there are other indications that the relationship between TOR and immune response is complex and not yet understood.  Rapamycin seems to inhibit the age-related reactivation of dormant cyto-megalovirus, though it has no direct action against the virus itself..  Already in 2009, it was seen (in mice) that rapamycin can slow the loss of white blood cells that cripples the immune system with age.  In this study, rapamycin was used successfully to aid in treatment of  a mouse model of malaria.  It is the particular action of inflammation against healthy, native tissues that is arguably the greatest source of metabolic damage in aging, and rapamycin may offer a particular protection against this destruction.

Remarkably, animals were protected against ECM [experimental cerebral malaria] even though rapamycin treatment significantly increased the inflammatory response induced by infection in both the brain and spleen and elevated the levels of peripheral parasitemia.



Last month, 40 aging dogs in a limited trial of rapamycin seemed to show improved health without troubling side-effects.  Some dog owners reported a resurgence of puppy-like activity in older dogs.

Cautions from the dog study paper:

The doses used clinically to prevent organ transplant rejection are associated with side effects, such as impaired wound healing, edema, elevated circulating triglycerides, impaired glucose homeostasis, gastrointestinal discomfort, and mouth ulcers (Augustine et al. 2007; de Oliveira et al. 2011).

Triglycerides in the blood spike upward when people first take rapamycin.  Triglyceride levels are associated with increased risk of CV disease, and in fact a better predictor than any of the many measures of cholesterol [ref, ref].  “Impaired glucose homeostasis” means type 2 diabetes, which is tightly correlated with aging, and probably has a causal relationship to many of the losses and risks associated with age.  It’s a big warning sign, and also a paradox.  At minimum, it suggests that anyone self-experimenting with rapamycin should be taking metformin as well.  Or, maybe the insulin challenge is part of what makes rapamycin work–it wouldn’t be the first time that throwing a challenge at the body had the paradoxical effect of extending lifespan.


The Russian-American biochemist Mikhail Blagosklonny is our foremost enthusiast for rapamycin in humans.  (Read about him in this Bloomsburg article from last year.)

“Some people ask me, is it dangerous to take rapamycin?” Blagosklonny says. “It’s more dangerous to not take rapamycin than to overeat, smoke, and drive without belt, taken together.”  Many colleagues have regarded his advocacy as a bit over-the-top.

It’s rumored that Blagosklonny takes rapamycin himself, but I couldn’t get him to talk about it.  (Actually, I agree with him that it’s one thing for him to experiment on himself, another for him to publicly encourage others to do so.) Blagosklonny writes

  1. Rapamycin suppresses geroconversion: conversion from cellular quiescence to senescence. Geroconversion is cellular basis of organismal aging.
  2. Genetic manipulations that inhibit the TOR pathway extend life-span in diverse species from yeast to mammals
  3. Rapamycin extends lifespan in all species tested
  4. Calorie restriction, which inhibits MTOR, extends lifespan
  5. MTOR is involved in diseases of aging and rapamycin prevents these diseases in animal models

Caveats and Obstacles

Rapamycin is presently the best candidate we have for a drug to extend life in humans.  It is expected to extend “health span” as well as lifespan, lowering incidence of cancer, heart disease and stroke.  But is it “safe and effective” for use in people?  We may never know, because its patent has run out, and there is no company motivated to invest the cost of a human trial.

Proper dosing for human anti-aging purposes is hard to guess.

A short course of Sirolimus (a name brand for rapamycin) can cost thousands of dollars and requires a prescription.  You can buy rapamycin more cheaply from a number of lab supply houses, but only if you provide a delivery address for a university lab, and certify that the purchase is for research purposes only.  It is less pure and quality control is unregulated.


In this recent paper, D. W. Lamming of UWisconsin suggests that the effects of rapamycin can be divided into inhibition of two complexes, mTORC1 and mTORC2.  C1, he says, is good for longevity, while C2 is responsible for the side-effects.  C1 responds quickly, while C2 responds more slowly.  Hence, he suggests that intermittent dosing might be effective at safely increasing life span.  The definition of “intermittent” remains undefined until a variety of schedules can be tested.

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Lamarck Update

I wrote a few weeks ago about newly-discovered dynamics of DNA that make Lamarckian genetic inheritance more plausible than ever.  I wrote that there was now just one step missing from a fully-documented Lamarckian mechanism.  In a comment on that page, a reader pointed me to a paper that fills in that final step.

Almost everyone looking at the process of evolution that has created the vast biosphere is struck initially by how surprisingly efficient the whole process has been.  But quantitative estimates that might tell us whether this intuition is valid are frustratingly elusive.  No one has been able to model or to estimate or even to place a reasonable lower bound on the pace of evolutionary change in a biosphere with the stats of our own Gaia.  The question we would like to be able to ask is whether blind mutation and natural selection constitute a sufficient mechanism to explain all that we see in biology, and the answer is, “no one knows”.  I hasten to add that it is not just religious fundamentalists who are skeptical.  My favorite example is an essay by Carl Woese, but I might have cited a dozen others.

One key to the question (how evolution manages to be as efficient as it is) is the realization that the process of evolution is subject to evolution.  This is “evolution of evolvability” or, as I like to call it, Evolution Squared.  The idea is that in the beginning, evolution may have depended on blind mutation and natural selection, but the process has become vastly more sophisticated and efficient since then, because as nature selects (directly) for increasing fitness, she also selects (indirectly) for those communities that are advancing in fitness more rapidly.  I use the word “communities” advisedly, because evolution isn’t something that happens to an individual; the smallest unit that can evolve is a deme, meaning a local set of animals or plants, all of the same species, that interbreed with one another.

Evolution of evolution has led to many innovations that we see and document, the greatest of which is sexual sharing and mixing of genes.  There is no doubt that the ability to adapt to the environment within an individual’s lifetime and transmmit that adaptation to offspring would be a tremendously useful innovation. This is Lamarckian inheritance, and if it were ever to arise, it would have been copiously rewarded by natural selection for ever increasing fitness.  Is Lamarckian inheritance a reality?

Fifty years after Lamarck, Darwin believed that Lamarck’s mechanism played a role in evolution.  But Darwin’s heirs in the 20th Century decided that Lamarckian inheritance was implausible.  If, for example, a muscle is conditioned and strengthed by constant exercise, how could the information about that muscle ever be communicated to the germ cells, the sperm or egg cells in the gonads that would be the progenitors of the next generation?  Then, in the 1920s, Lysenko’s wild claims about Lamarckian inheritance pulled all credibility out from under the idea, and the scientific community firmly rejected the possibility.

Then, toward the end of the twentieth century, a strange thing happened.  A new kind of semi-permanent inheritance was discovered, and it was fully Lamarckian in its implementation.  This is epigenetic inheritance, the inheritance not of different versions of genes, but of patterns of gene expression.  The choice of which genes are turned on or off is erased from the DNA and reprogrammed with each new embryo.  But through the reprogramming, a selective memory remains; an afterimage of what was found to be useful in the previous lifetime is transmitted to the next generation.

Epigenetic memory lasts a few generations, but it is not as permanent as changes in the DNA sequence (= genetic inheritance).  Could it be that genetic changes are not completely random but, like epigenetic changes, they are subject to Lamarckian influence?  The prevailing skepticism of this idea is rooted in theory, and our understanding of biochemistry.  Remarkably, there has been no thorough experimental exploration, not even a well-designed single trial looking for evidence of Lamarckian inheritance.

But we now know that information about gene expression does get fed back to the germline in the form of epigenetic markers.  From here, it does not seem so implausible that the epigenetic markers may be translated into more permanent changes in the genome.  In this paper from Washington State biologists last year, the last link in the chain is closed.  The authors expose rats to a toxic fungicide, and confirm the previously-observed epigenetic changes in the rats, changes that are transmitted to their offspring.  They then go on to breed the rats for three more generations, and note that there are extra copies of hundreds of genes, some of which are useful in the detox of the fungicide.  These genetic changes appeared in the third generation after exposure, but they were absent in the first generation.  They can’t be written off as mutagenic effects in the fungicide, because they were three generations removed from exposure.

This report does not claim creation of new genes or even new alleles, but it does include permanent changes to the germline DNA.  The emerging view is that gene expression is more important in determining an organism’s structure and function (and fitness) than the precise form of the alleles themselves.  98% of our DNA is not genes but introns, the segments of DNA between genes that collectively determine the timing and circumstance of gene expression.  A curious finding stressed by the authors of this study is that there is zero overlap between the areas of the genome that were epigenetically modified in Generation One after exposure and the areas of the genome that later produced extra copies in Generation Three.  This suggests that the mechanism for this first example of Lamarckian genetic inheritance remains a complete mystery.


Far-reaching implications

I now believe that the remaining pieces of a fully Lamarckian evolutionary mechanism will fall into place.  Books on evolution will have to be rewritten starting from Chapter 1.  Everything that was learned about evolution in the 20th Century will be subject to reinterpretation, and much of it will be deemed irrelevant or naive.  If Lamarckian inheritance pans out, it will turn the science of evolution on its head, and give it a good shake.

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A Germ Theory of Aging?

Can microbial infections make you age faster? Last week, Alzheimer’s experts cited several lines of indirect evidence linking infections to dementia. There have been other reports, going back decades, suggesting that infections early in life are associated with shorter life expectancy far down the road. “Makes sense” was the comment quoted from medical scientists.

It “makes sense” in that most biologists still want to believe that the body is doing its best to live as long as possible, and that every challenge to the body ought to have a negative impact on longevity, as the body’s resources are diverted from the task of constant repairing and rebuilding. [Science Times article based on article in Science Translational Medicine]

But we know, or should know by now, that the biology of aging doesn’t “make sense” in this way. The word hormesis describes the startlingly unexpected phenomenon that, if the body survives a challenge, it tends to age more slowly and live longer.

Science is driven by hunches and intuitions as much as by observations and theories. And in the area of aging medicine, scientific intuitions are stuck in a discredited paradigm that is holding us back. We look ever more creatively, ever less credibly, for something that is forcing the body to tolerate a deterioration that we know is not a necessary byproduct of life. We have been slow to face up to the fact that the body is choosing to be old, because we believe that “nature is beneficent” or because we can’t stomach the idea that our bodies are mutineers and we its victims, or because at some subconscious level we have been influenced by a narrow version of Darwin’s evolution.

The germ theory of AD is “logical” within this discredited paradigm. If the body is asked to fight off infection, then maybe it’s “distracted” from doing the repair work. To its credit, the new Harvard Med paper is a step above this delusion, however. Maybe the body is countering infection by mounting an inflammatory response that would be a healthy, useful adaptation in other tissues, under different circumstances; but in the brain it happens to wreak havoc, because there is no local mechanism for cleaning up the detritus from this war. We need only hypothesize that the body has evolved a general response that happens to be counter-productive in this one instance, and that evolution hasn’t had time as yet to create an exception to the rules about what threats to respond to, where, and how to respond.

The weak link, of course, is that we must assume that evolution made a mistake.  A response that is generally appropriate is applied in a circumstance where it’s not just inappropriate, it’s deadly.

The evidence

(from the article in Science Translational Medicine)

  • Researchers injected nasty bacteria into mouse brains. Plaques appeared quickly, similar to those associated with AD.
  • When this experiment was repeated with mice that were immune-suppressed so as not to respond to the bacteria, the bacteria killed them quickly. (Clearly this was a worse result than AD.)
  • In humans, infection with herpes is statistically associated with AD.
  • The blood-brain barrier weakens with age. First area of leakage is the hippocampus, which is often where amyloid plaques are known to begin. (This is the “mistake”.)


My take

This is new to me, and I would not have predicted that the association with infection is as strong as it seems to be. But we have known for a long time that inflammation is powerfully associated with AD, and that infection promotes inflammation. I would ask what the new data suggests that adds to those important and well-established insights.

If the new Harvard Med hypothesis holds up, it still doesn’t address the issue of why the body should allow its brain to be destroyed by an inflammatory response. We know that anti-inflammatories have a big deterrent effect on AD. People who take NSAIDs have lower rates of dementia. In regions where the anti-inflammatory spice turmeric is a daily staple, the rate of dementia is a fraction of what it is in the West. So if the inflammation and amyloid accumulation turn out to be a response to real infections, not just auto-immunity, then the body is still making a big mistake in mounting this defense in a situation that actually does a lot more harm than good. One might be excused for thinking that evolution can’t afford such mistakes.


Background: Claims that early infections are associated with late mortality

My father’s Aunt Tillie (yes, that’s her real name) was a sickly child, and my great grandmother was in constant fear she was going to die. But she did manage to emerge from girlhood, and then went on to outlive three husbands.  It took a nursing home to kill her at the age of 92. I have heard other stories that give the impression this is typical: children who survive severe illness in infancy tend to exceptionally long lives. Could it be that this is a myth, and the opposite is statistically true?

I have a new acquaintance with a venerable guru of aging science, Caleb Finch. Finch’s second encyclopedia contains an account of researches by David Barker in the 1980s that correlate conditions in early life with late-life mortality. One of the claims is that an infant’s lung infections can lead to heart disease as well as stomach conditions and bronchitis late in life. If true, this would be the opposite of hormesis (my expectation). Finch cites supportive theory that the body’s supply of naive T cells is finite and not easily renewed, and that depletion of this reservoir might begin early in life.

I find Barker’s data in themselves inconclusive, because they are based on neighborhoods in England. It is too easy for me to imagine that those neighborhoods that are poor and disadvantaged have both sicker children and higher mortality among elders, with no individual causal relation between the two. The most economical explanation is the economic one.

Together with Eileen Crimmins, Finch wrote a series of papers about a decade ago [ref] purporting to build a case for the germ theory of aging. They look at cohort data from 19th and 20th century Europe, when mortality was in steady decline. Technology alone might be expected to produce concurrent decreases in old-age mortality and childhood mortality. But in fact the decrease in old-age mortality was delayed about 60 years behind the drop in childhood mortality, suggesting that it was the same cohort—the same individuals—who were benefiting. They take this as evidence that the benefit accrued just once, in childhood, and was remembered by the body later in old age. The lower level of inflammation persisted over a lifetime. Steadily increasing height during this period is taken as another indication that the lower burden of infections was producing generally improved health.

Maybe. I’ve been unable to find more direct evidence that would bear on the question whether infections early in life have a positive or a negative effect on longevity. In this 1989 study, rats raised germ-free lived 8% longer than conventional-clean, except if they were calorically restricted, in which case they lived 2% shorter. This 1971 study includes a comparison of 9 strains of mice raised in sterile vs conventional lab cages, and the differences appear to be as often positive as negative.

More recently, there has been appreciation of the complex interplay between bacteria and the immune system.  It’s the auto-immune response—when the body turns against itself—that is connected to the ravages of age.  But the relationship between bacteria and auto-immunity is not straightforward.  Some bacteria at some times of life are essential for training the immune response to distinguish between self and “other”, while other bacteria at other times of life contribute to the corruption of the immune response.  This new article from an MIT researcher summarizes how much we don’t know.  The article features a new demonstration of the way Lactobacillus reuteri, a beneficial gut bacteria and common probiotic ingredient, promotes growth and health of the thymus gland, through the anti-aging hormone FOXN1.


The Bottom Line

The article on a bold new hypothesis ends by recommending a familiar strategem: target drugs to interfere with pro-inflammatory pathways. I couldn’t agree more.

At the end of the day, the stronger evidence is for hormesis, in other words, that (modest) hardships tend to lengthen life span. Even without other, more direct evidence, the phenomena of hormesis alone would be sufficient to tell us that aging is a choice that the body makes, in other words, an evolved program. But not all hardships are created equal, and the balance of evidence for infectious disease is that infections are more likely to shorten life span (long after the symptoms of the infection are absent) than to lengthen it.


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Update: Cell Phones can cause Cancer

There’s a suppressed science correlating cell phone use with cancer risk.  It is suppressed because the health risks pose a basic threat to the business model of the booming cell phone industry, with looming regulation and a devastating spate of future law suits.  In defense of the scientific community, I hasten to add that there was no reason to suspect in advance that radio waves would have any biological effects whatever, based on well-established and conventional notions of how biochemistry works.  But the epidemiological evidence has been compelling for several years now, and it’s past time for the community to turn around.

(Unlike x-rays and nuclear power, cell phone radiation is not “ionizing radiation”, and cannot break chromosomes or cause mutations.  The mechanism by which it interacts with biological processes remains wholly unknown.)

Last week, data from a major study were released confirming our worst fears.  This was based on rats, not humans, so all the provisos about indirect evidence and correlation vs causation don’t apply.  Rats live just two years, so the exposure time was short compared to humans.

They chronically exposed rodents to carefully calibrated radio-frequency (RF) radiation levels designed to roughly emulate what humans with heavy cell phone use or exposure could theoretically experience in their daily lives. The animals were placed in specially built chambers that dosed their whole bodies with varying amounts and types of this radiation for approximately nine hours per day throughout their two-year life spans.

Despite the short duration of the experiment and despite the fact that there were only 90 rats in each group, cases of rare cancers were reported in the test rats, but none in the controls.

An interesting twist in the results is that there is a hint that rats exposed to cell phone radiation lived longer.  There is precedent for this in many kinds of hormetic experiments.  For example, intermittent, low levels of ionizing radiation cause an elevated cancer incidence, but for those that don’t get cancer, there is a small tendency for increased life span.

Is this a big cause for concern, or a tempest in a teapot?

Quantifying the risks for humans remains very uncertain.  For humans, there are no precise measures of exposure, and for rats, we don’ know how to translate the results to human terms.  This kind of uncertainty combined with huge economic stakes leads inevitably to strong language and exaggerated claims on both sides.

For me as a consumer, this has been a subject about which I’m happy to hide my head in the sand.  When I’ve been forced to think about it, I’ve concluded that cautionary measures are warranted, but I’ve been slow to follow through.  Another big topic which I don’t want to think about is the speculative effect of cell radiation on neural activity–thought in the present moment.  Does cell phone radiation affect concentration?  Productivity?  Headaches?  My best guess is that there are some people for whom these effects are a palpable reality.

…so let me take this opportunity to make a public commitment to do at least the easiest things in precaution.  We can take advantage of the fact that all radiation falls off steeply with distance from the source.  A huge transmitter on a tower half a mile from your home yields much lower radiation levels than a single cell phone transmitter that is half an inch from your brain.

  • Always use cell phone with headphones or on speaker phone, well away from the head.
  • Get the wifi hubs in your home and office off your desk, and keep them on the opposite side of the room from your workspace.
  • Install wired connection for your laptop so the computer that is closest to you doesn’t need wifi for your daily usage.

This much is easy, and it is a minimum.  I don’t for a moment mean to imply that it is irrational to do much more to safeguard our bodies and our families from microwave radiation.

Scientific Mystery

I’ve already said that there are powerful theoretical reasons to believe that low-level radio waves should have no biological effects.  We now know that there’s something amiss in those powerful theories.  For more than a century it has been a foundational assumption of biology that living cells are no more than very complicated chemical reactors, and that the fundamental mechanisms of biochemistry are one with the fundamental mechanisms of inorganic chemistry.  I daresay we now know this not to be true.  Life is playing some special tricks that non-living bags of chemicals don’t play.  It would be overreaching to go back to the 19th Century notion of vitalism; my bets are on quantum processes at the single-molecule level.  I learned just last month that visionary biophysicist Stuart Kaufmann has been writing about this subject.  I predict that Quantum Biology is the next revolution.

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“No animal dies of old age in the wild”

True, but that’s not really the relevant question to ask.  In fact, aging has a major impact on mortality in the wild, and this poses a dilemma for evolutionary theory.  In the earliest stages of senescence, already an individual may be losing its competitive edge.  When an epidemic passes through, those with compromised immune function are the first to die.  When a predator is chasing the herd, those that cannot run quite as fast as they used to are caught at the back of the crowd.  In this way, aging can have a big effect on fitness even if no one is “dying of old age”.

In 1951, Peter Medawar put forward the first modern theory for the evolution of aging.  He was a self-made Brazilian giant, 6 foot 5, as charismatic as he was brilliant, and at the age of 36 he had achieved a prestigious appointment at University College, London.  For his inaugural address, he chose to tackle an Unsolved Problem of Biology, and asked how aging in nature could be reconciled with Darwinian evolution.

There had been no evolutionary theory of aging in the 50 years since August Weismann had disavowed his own.  Medawar was astute enough to realize that Weismann was correct to seek an evolutionary understanding of aging.  Aging cannot be understood from thermodynamics or physical processes of attrition.  No physical law requires aging.  Medawar was also correct in judging that Weismann’s proposed solution was no solution at all.  “Weismann caters twice round the perimeter of a vicious circle.  By assuming that the elders of his race are decrepit and worn out, he assumes all but a fraction of what he has set himself to prove.”

Medawar proposed the theory that natural selection can only work on living, reproducing individuals.  But in the wild, there are so many hazards that can lead to death that, past a certain age, there are very few remaining alive.  In nature, everyone dies before they reach old age.  This creates a “selection shadow”.  Bodies are evolved to be healthy, strong or fertile up to the age where there are still survivors in nature.  But at advanced ages, natural selection has never had an opportunity to work her magic, so we should not be surprised that the organism is ill-adapted and falls apart.

We get old and die because of evolutionary neglect.  Natural selection needs living, reproducing individuals to select from, or it is ineffectual; hence we expect that aging takes over and the body deteriorates soon after that age at which predators and disease and other hazards of the wild have thinned the population near to zero.

The rest is history

Very quickly, Medawar’s idea was enshrined in the canon of evolutionary theory.  Building on Medawar, two more ideas were added.  One was the concept of “mutational load”.  If there was no natural selection at work for “late-acting genes”, then random mutations would creep in, and this would account for the organism going to pot.  This became the Mutation Accumulation theory.  The other was the idea that selection at late ages may be weak but not zero, and it could then be overpowered by the drive to maximize fertility early in life, even if it had bad consequences for fitness later on.  This became the Antagonistic Pleiotropy theory.

The idea that, in the wild, no one lives long enough to die of old age made a great deal of intuitive sense.  George Williams (of the pleiotropy theory) added a refinement: that the early stages of senescence would likely have consequences for individual competitiveness, so he based his theory on the idea that selection against aging was weak but not zero.  But everyone was agreed that the fitness consequences of aging were very slight, if not actually negligible.

Evolutionary theory went on to develop on this basis, and continued to be embellished for 40 years.

Fact check

The inconvenient truth came to light gradually, and several decades on.  In physics and chemistry, experimental science is an attractive calling because practitioners get to hang out in a lab and perform magic with nifty apparatus and spiffy electronics.  But experimental ecology is a field science requiring travel to remote locations, and many lonely, patient hours of observation, away from the comforts of home.  The work is often left to doctoral students who are in no position to protest.

So it was 25 more years before evidence started to accumulate that could bear on the question, how many animals in the wild are dying from the (early) effects of aging?

In principle, it is not hard to determine an answer.  Collect carcasses in the woods and use established forensic techniques to estimate the age of the animal when it died.  Once you have enough cases, you can plot a curve:  how many deaths? (on the y axis) vs what age? (on the x axis).  For example:

How to interpret the results?  If there were no aging in the wild, then we must expect that the percentage of individuals dying at every age is the same.  But the number remaining gets smaller and smaller, so the absolute number of deaths would go down with age.  The math tells you that “no aging” corresponds to a falling exponential curve.


If the number that we actually find is flat with age, or even if it declines with age but not as rapidly as an exponential curve, this is evidence that aging is taking a toll on fitness in the wild.

It was 1991 before Daniel Promislow first collected and interpreted the appropriate statistics for 56 different mammals in the wild.  He was a doctoral student at Oxford, and this study launched his career.  In 46 of the 56 species, he found an increasing risk of death with age.  In several species, data were complete enough that he was able to detect a Gompertz curve, meaning that for a given individual, risk of death climbs exponentially with age.


The Gompertz shape of the mortality curve had been known for 150 years—nothing new there.  The surprise was that previous to Promislow, scientists had thought that the Gompertz shape only applies in protected environments, like humans in civilization and animals in zoos.  In the wild, it was expected that (according to Medawar) everyone dies too early to see the rising shape of the Gompertz curve.

The significance of these results was not lost on Promislow.  He boldly asserted that his results conflicted with the accepted evolutionary theories for aging.  He was also modest and tactful enough to allow for reasons that his conclusion might be premature, and that adjustments could be made to permit the evolutionary theories to hold their own.

The Evidence Piles on

In 1998, Robert Ricklefs expanded on Promislow’s results by including more mammal surveys and some birds.  Ironically, he titled his piece Confirmation of a Fundamental Prediction, but in fact the results made all the extant theories for evolution of aging quite untenable.  He fitted mortality curves for each of the species in the study, and reported parameters from these curves.  From these data, it is a small further step to answer the question, What proportion of deaths in species can be ascribed to aging?  Ricklefs set up the equations and provided all the parameters, but he never completed the calculation.  Later, I filled in those numbers, the “percentage of senescent deaths” for each species.  You can read them in the column highlighted in orange.


As you can see, there are no animals for which the impact of senescence in the wild is negligible.  Many are clusted in the range 15-30%.  Some are over 70% — meaning, roughly, aging is reducing fitness in these species by more than 2/3.

Heroic field work

All the above work is based on field studies, data compiled after the fact through searching for remains.  But the cleanest kind of study would be an experiment, planned in advance, where individual animals could be tracked in the wild and their fates determined by direct observation.  As a Canadian grad student in the early 2000s, Russell Bonduriansky set himself the daunting task of individually labeling, releasing, and recapturing thousands of antler flies to answer directly, how did their risk of death change with age?  His doctoral work was stunning enough to be profiled in Nature.  The result: 28% of antler fly deaths were due to aging.


Nature doesn’t care if you die once your fertility is gone

The numbers above present a dilemma for evolutionary theory.  Scientists dealing loosely with this question sometimes say, animals die once their fertility is ended.  It’s no surprise that evolution has permitted these animals to age and die once they have reproduced and replaced themselves.  But the theory can’t escape so easily, for two reasons.

First, this doesn’t answer the question, but only kicks the can down the road.  Yes, there is no selective advantage to be gained by continuing to live on past the end of fertility.  But why should fertility decline in the first place?  Why haven’t we all adopted the growth pattern of trees and lobsters, continuing to grow and produce more offspring with each passing year?  (Or, if there are size constraints that keep land animals from growing forever, at least we should be maintaining our fertility, not losing it with age.)

Second, responding to the argument about “once they have replaced themselves”…  We should note that this is a flat denial of the dominant “selfish gene” view of evolution.  In standard evolutionary theory, there is no such thing as “enough”, because individuals are in an arms race to dominate the next generation with their genes.  If I have 6 offspring and you have 7, it will not be very many generations before my descendants are completely crowded out by yours (according to the way standard evolutionary calculations are performed).  This perspective highlights the evolutionary paradox that natural selection has tolerated declining fertility and increasing mortality in so many different animal species.

The bottom line

Sixty years after Medawar, it is untenable to maintain that aging exists in a “selection shadow”.  The negative consequence of aging for individual fitness is a force to be reckoned with.  But theorists have yet to face this particular monster.  I still hear Medawar’s hypothesis cited as gospel regularly in papers and at conferences.  The disconnect between theory and observation is stark.

Two footnotes

  1. The idea of “late-acting genes” made sense in the 1950s when Medawar and Williams were formulating their theories, but we now know that all living things have extensive machinery (epigenetics) for deciding when to turn particular genes on and off.  Williams imagined that if a gene is beneficial at one stage of life, we would be stuck with it at another stage, when it is detrimental.  We now know that genes are routinely turned on and off as needed.
  2. The idea that fitness depends on maximizing the number of offspring is enshrined in standard evolutionary theory, which is the “selfish gene” model.  But there are many ways we know this cannot be right.  Producing too many offspring can be just as disastrous for a species as producing too few.  This is the inspiration for my Demographic Theory of Aging.
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Epigenetics of Aging, and Prospects for Rejuvenation

Last week, I attended the tail end of a Keystone conference on Epigenetic Regulation of Aging, followed by a one-day brainstorming session to kick off a project called GILGA-mesh, intended to take this bull by the horns. Though the subjects of the two days were virtually identical, the approach and attitudes of the scientists in attendance set very different tones.  Both days featured smart, creative and careful scientists, but they saw the same material through different frameworks.  Sometimes philosophy makes a difference.

For readers who know me less well, I should introduce my perspective: I believe that aging is an evolved epigenetic program.  When we are young and growing, particular genes are turned on and off with exquisite timing to determine the growth and development of bones, muscles, and organs.  When we are old, the program continues, more slowly and more diffusely, but inexorably nonetheless.  Genes are turned on that destroy us with inflammation and cell senescence and auto-immunity and programmed cell death, while the systems that protect us from pathogens and from free radical damage are gradually shut down.  Evolution has left nothing to chance.

[I first wrote an academic paper about this idea in 2013, excited by a paper by Aviv  Johnson on methylation, but unaware that Tom Rando had written on the same lines the previous year. Jeff Bowles had hinted at similar ideas in a paper more than a decade earlier. Soon the field was broken wide open by the work of a bio-statistician.
Steve Horvath ran a computer analysis on thousands of genes as they are  expressed in young and old humans, and produced an “epigenetic clock” that could accurately report how old a person using measurementis of methylation in 353 DNA sites in particular.]



Epigenetics is a new science in the 21st century.  All the cells in one body have the same DNA (pretty much), but differernt genes are “expressed” (translated into proteins) in different tissues and at different times, and this is what controls the body’s metabolism.  In fact, only 2% of our DNA is genes, and 98% determines how the DNA is folded and spooled, opened and closed at particular times and places, and this in turn controls gene expression.  We are 2% genetic and 98% epigenetic.

There is a language called the “genetic code” which determines how genes are translated into proteins.  It was decoded by Francis Crick and others in the 1950s.  It is as simple as it can be, and is completely understood.  There is another language, the “epigenetic code” that determines gene expression.  It is anything-but-simple, with a convoluted and self-referential syntax that we are just beginning to understand.  The epigenetic code starts with signals embedded in the DNA that serve as “start” and “stop” codons. The stretch in between comprises a piece of a gene, a kind of Gutenberg movable type that is transcribed from the chromosome and then spliced and combined to form functional RNAs and proteins. The complicated part of the epigenetic code is implemented as a pattern of methyl and acetyl groups.  These are little chemical decorations that attach to the DNA and to the “histones” (spools around which DNA is wound up in the cell nucleus for safe storage).  The methyl and acetyl groups are continually being attached and removed according to instructions that come from within the cell and other instructions that are passed through the blood. It is the methyl and acetyl groups that determine how the DNA is folded and spooled, which effectively turns particular genes on and off as needed.

The part of the epigenetic code on which we have the best handle at present is called “methylation of CpG islands”.  Long stretches of DNA have CGCGCGCG… on one strand, complemented by GCGCGCGC… on the other.  Often the C’s in this region get an extra methyl group, turning from cytosine to 5-methylcytosine.  Then this stretch becomes a “repressor region,” a signal to NOT express the adjacent gene.

DNA methylation can be persistent, turning a gene off for decades at a time.  When a cell divides and its DNA is copied, the methylation pattern can be copied with it.  This accounts for some of the persistence of epigenetics, and the way gene expression can be inherited across generations.

DNA methylation has been appreciated for 30 years, but two recent developments make the subject attractive and accessible to research.  (1) There is now a simple lab/computer technique for reading the methylation pattern from DNA.  It relies on commercially available, automated machinery for PCR to sequence a full genome before and after chemical modification of the methylated C’s.  (2) There is now a simple lab/computer technique for changing the methylation state of any chosen target site in the DNA.  It is based on CRISPR technology that is taking genetics labs by storm the last two years.

from Hannum et al., 2013, Genome-wide Methylation Profiles

from Hannum et al., 2013, Genome-wide Methylation Profiles

Epigenetics and aging

Three years ago, Horvath demonstrated that there are specific patterns of methylation associated with particular ages of the body.  It’s not just that the fresh, clear pattern of youthful gene expression becomes muddied and random with age—although there is some of that.  But it’s also true that some genes that are active in youth become inactive as we get older and (especially) that other genes that were suppressed in youth become activated in old age.  What Horvath’s paper says is, “show me  methylation pattern of a person’s cells, and I can tell you how old s/he is.”


Is epigenetics a cause or effect of aging?

The correlation between aging and epigenetic status is established beyond dispute.  But what does it mean?  This is the big question.  Most researchers think of the body as programmed by evolution to be as strong and healthy as possible.  So, when different genes are expressed in old age, they find it natural to assume that the body is protecting itself in response to damage that it has suffered over the years.  We express different genes when we are older because we need different genes when we are older.  This was the predominant attitude at the first conference (where I was present just for the last day).

The other possible interpretation is my own, and it has become common among those who are closest to the field of epigenetics.  It is that epigenetic changes with age are means of self-destruction.  The body is programmed to die, and its suicide plan is laid out in the form of transcribing an unhealthy combination of genes.  This idea flies in the face of traditional evolutionary theory.  (How could natural selection prefer a genome that destroys itself and cuts off its own reproduction?)  Nevertheless, the evidence for this hypothesis is robust.  The genes that are turned on don’t protect the body—quite the opposite.  Genes for inflammation are dialed up.  Genes for the body’s defense against free radicals are dialed down.  Cell turnover is dialed down.  DNA repair is dialed down. The mechanisms of programmed cell death (apoptosis) are strengthened in healthy cells, at the same time that they are perversely weakened in cells that are a threat to the body, like infected cells and cancer cells.


How will we determine who is right?

In my opinion, the existing evidence heavily favors the hypothesis that aging is caused by epigenetic changes, rather than the other way around.  When we look at the kinds of changes that occur, they seem to be pouring fuel on the fire, not putting it out.  Protective genes are turned off and inflammatory genes are turned up.  I also think that
parabiosis experiments provide a strong clue.  Three researcher groups (at Stanford Harvard, Berkeley) have shown that injecting blood plasma from a young mouse into an old mouse makes the old mouse healthier, and relieves some problems associated with age.  The blood plasma contains no cells—only signal molecules that are the product of gene expression.  This is powerful evidence that youthful gene expression is supporting a strong and youthful body, and (conversely) that the kind of gene expression that characterizes old age is not doing the body any good.

But the ultimate experiment will be to re-program gene expression in an old mouse and see if there is a rejuvenating effect.


My proposal

As of now, the GILGA-Mesh project is dominated by numbers geeks (like me) who practice the “Google approach” to bioinformatics.  Huge databases of gene expression are screened for epigenetic candidates that seem to be well-correlated with good outcomes.  I think what we need is an infusion of biolochemists who understand something about the body’s signaling networks, and can orient us toward “upstream” and “downstream” molecules.  Here’s my proposed program:

  1. Repeat Horvath’s (human) analysis for mice.  In other words, identify several hundred places where methylation is different in young and old mice.
  2. Determine which genes are associated with these regions.  (Map needed for this should already be available.)
  3. Look at the set of genes and identify transcription factors. These are likely to be “upstream”, in that they control other genes.
  4. Start with old mice.  Use CRISPR to change the methylation status in a handful of promoter regions that control transcription factors, making them match the methylation status of young mice.
  5. Measure metabolic functions to see if the old mice are more healthy or less after these procedures.  Look particularly for changes in inflammation, propensity for cancer, and especially life span.

If this experiment goes as I expect, we will be ready for rejuvenation experiments in humans.


How does the body know how old it is?

Even further upstream, is there a central master clock that dictates the body’s epigenetic expression, and thereby determines our biological age?  Logically, it seems that the body would need an accurate clock to time the events of growth and development.  Evolution likes to re-use the parts she has created, and it would not surprise me if the developmental clock morphs into an aging clock.

have reasoned that there are two possibilities.  It may be that there is a timekeeper, probably in the neuro-endocrine regions of the brain, that controls the processes of development and aging.  This possibility is supported by works of Kasper Daniel Hansen and Claudia Cavadas.  If this pans out, it would present the handiest target for true rejuvenation in humans.  But it also may be that epigenetic expression itself is a kind of clock that is diffused through the body.  Today’s gene expression includes transcription factors that control tomorrow’s gene expression, and so epigenetic state may be a feedback loop, or self-contained clock.  This may also be a target for rejuvenation, but a little accessible, harder to address or to tinker with.

Random notes—other things I learned last week

I was tickled to find how many members of the GILGA-mesh team already support the
programmed aging perspective that I have advocated.  I was particularly gratified to receive encouragement from Caleb Finch, a grand old man of the field who wrote the
encyclopedia of aging in 1990, and continues a very active research program today.

From Finch, I learned that infections in childhood and even in the womb can have a serious effect on diseases of old age, decades after the fact.  He hypothesizes a lifelong burden of inflammation.  Evidence includes an elevated incidence of heart disease for the cohort born just after the influenza epidemic of 1918.

I was chagrined to learn that air pollution, especially particulate matter, is associated with increased risk of dementia.  This poses a personal dilemma for me, as I plan to spend the summer at the lab of Meng-qiu Dong in Beijing.

I learned that hospital errors are the third leading cause of death in the US, accounting for about 10% of all deaths, about the same number as smoking.  Maybe you already read that in the New York Times.


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