Michael Fossel Michael is President of Telocyte

October 10, 2017

Should everyone respond the same to telomerase?

A physician friend asked if a patient’s APOE status (which alleles they carry, for example APOE4, APOE3, or APOE2) would effect how well they should respond to telomerase therapy. Ideally, it may not make much difference, except that the genes you carry (including the APOE genes and the alleles for each type of APOE gene, as well as other genes linked to Alzheimer’s risk) determine how your risk goes up with age. For example, those with APOE4 alleles (especially if both are APOE4) have a modestly higher risk of Alzheimer’s disease (and at a lower age) than those with APOE2 alleles (expecially if both are APOE2).

Since telomerase doesn’t change your genes or the alleles, then while it should reset your risk of dementia to that of a younger person, your risk (partly determined by your genes) would then operate “all over again”, just as it did before. Think of it this way. If it took you 40 years to get dementia and we reset your risk using telomerase, then it might take you 40 years to get dementia again. If it took you 60 years to get dementia and we reset your risk using telomerase, then it might take you 60 years to get dementia again. It wouldn’t remove your risk of dementia, but it should reset your risk to what it was when you were younger. While the exact outcomes are still unknown, it is clear is that telomerase shouldn’t get rid of your risk, but it might be expected to reset that risk to what it was several years (or decades) before you were treated with telomerase. Your cells might act younger, but your genes are still your genes, and your risk is still (again) your risk.

The same could be said for the rate of response to telomerase therapy. How well (and how quickly) a patient should respond to telomerasse therapy should depend on how much damage has already occurred, which (again) is partially determined by your genes (including APOE genes and dozens of others). Compared to a patient with APOE2 alleles (the “good” APOE alleles), we might expect the clinical response for a patient with APOE4 alleles (the “bad” APOE alleles) to have a slightly slower respone to telomerase, a peak clinical effect that was about the same, and the time-to-retreatment to be just a big shorter. The reality should depend on how fast amyloid plaques accumulates (varying from person to person) and how fast we might be able to remove the plaque (again, probably varying from person to person). The vector (slope of the line from normal to onset of dementia) should be slightly steeper for those with two APOE4 alleles than for two APOE3 alleles, which would be slightly steeper than for two APOE2 alleles. Those with unmatched alleles (APOE4/APOE2) should vary depending upon which two alleles they carried.

To give a visual idea of what we might expect, I’ve added an image that shows the theoretical response of three different patients (a, b, and c), each of whom might respond equally well to telomerase therapy, but might then need a second treatment at different times, depending on their genes (APOE and other genes) and their environment (for example, head injuries, infections, diet, etc.). Patient c might need retreatment in a few years, while patient a might not need retreatment for twice as long.


October 4, 2017

The End Hangs on the Beginning

A major stumbling block in our understanding of age-related disease, such as Alzheimer’s, is a propensity to focus on large numbers of genes, proteins, etc., without asking what lies “upstream” that results in the associations between such genes (etc.) and the disease. While some would tout the advantages of using Artificial Intelligence to attack the problem, the problem with AI is that (like most scientists) it focuses on finding solutions only once the problem has been defined ahead of time. If, for example, we define Alzheimer’s as a genetic disease, then we will find genes, but will never reassess our unexamined assumption that AD is genetic. If we assume that it’s genetic, then we only look at genes. If we assume it’s due to proteins, then we only look at proteins. If we assume that it’s environmental, then we only look at the environment. Data analysis and AI, no matter how powerful, is limited by our assumptions. We tend to use large data analysis (and AI) in the same mode: without ever realizing we have narrowed our search, we assume that a disease is genetic and then accumulate and analyze huge amounts of data on gene associations. While AI can do this more efficiently than human scientists, the answers will always remain futile if we have the wrong question. Once we make assumptions as to the cause, we only look where our assumptions direct us. If we look in the wrong place, then money and effort won’t correct our unexamined assumptions and certainly won’t result in cures.

It’s like asking “which demons caused plague in Europe in the middle ages”? If we assume that the plague was caused by demons, then we will never (no matter how hard-working the researcher, how large the data set we crunch, or how powerful the AI we use) discover that the plague was caused by a bacteria (Yersinia pestis). If you look for demons, you don’t find bacteria. If you look for genes, you don’t find senescent changes in gene expression. The ability to find answers is not merely limited by how hard we work or how large the data sample, but severely and unavoidably limited by how we phrase our questions. We will never get anywhere if we start off in the wrong direction.

To quote the Latin phrase, “Finis origine pendet“. The end hangs on the beginning.

September 20, 2017

Genes and Aging

Several of you have asked why I don’t update this blog more often. My priority is to take effective interventions for age-related diseases to FDA phase 1 human trials, rather than blogging about the process. Each week, Outlook reminds me to update the blog, but there are many tasks that need doing if we are going to get to human trials, which remains our primary target.

In working on age-related disease, however, I am reminded that we can do very little unless we understand aging. Most of us assume we already understand what we mean by aging, but our assumptions prevent us from a more fundamental and valid understanding of the aging process. In short, our unexamined assumptions get in the way of effective solutions. To give an analogy, if we start with the assumption that the Earth is the center of the solar system, then no matter how carefully we calculate the orbits of the planets, we will fail. If we start with the assumption that the plague results from evil spirits rather than Yersinia pestis, then no matter how many exorcisms we invoke, we will fail. We don’t fail because of any lack of effort, we fail because of misdirected effort.

Our assumptions define the limits of our abilities.

When we look at aging, too often we take only a narrow view. Humans age, as do all the mammals and birds (livestock and pets come to mind) that have played common roles in human culture and human history. When most people think of aging, they seldom consider trees, hydra, yeast, bacteria, or individual cells (whatever the species). Worse, even when we do look at these, we never question our quotidian assumptions. We carry our complacent assumptions along with us, a ponderous baggage, dragging us down, restricting our ability to move ahead toward a more sophisticated (and accurate) understanding. If we looked carefully, we would see that not all cells age and not all organisms age. Moreover, of those that age, not all organisms age at the same rate and, within an organism, not all cells age at the same rate. In short, neither the rate of aging, nor aging itself is universal. As examples, dogs age faster than humans and, among humans, progeric children age faster than normal humans. The same is true when we consider cells: somatic cells age faster than stem cells, while germ cells (sperm and ova) don’t age at all. So much for aging being universal.

The key question isn’t “why do all things age?”, but rather “why does aging occur in some cases and not in others, and at widely different rates when it occurs at all?” The answer certainly isn’t hormones, heartbeats, entropy, mitochondria, or free radicals, for none of these can explain the enormous disparity in what ages and what doesn’t, nor why cells age at different rates. Nor is aging genetic in any simplistic sense. While genes play a prominent role in how we age, there are no “aging genes”. Aging is not a “genetic disease”, but rather a matter of epigenetics – it’s not which genes you have, but how those genes are expressed and how their expression changes over time, particularly over the life of the organism or over multiple cell divisions in the life of a cell. In a sense, you age not because of entropy, but because your cells downregulate the ability to maintain themselves in the face of that entropy. Cell senescence effects a broad change in gene expression that results in a gradual failure to deal with DNA repair, mitochondrial repair, free radical damage, and molecular turnover in general. Aging isn’t a matter of damage, it’s a matter of no longer repairing the damage.

All of this wouldn’t matter – it’s mere words and theory – were it not for our ability to intervene in age-related disease. Once we understand how aging works, once we look carefully at our assumptions and reconsider them, our more accurate and fundamental understanding allows suggests how we might cure age-related disease, to finally treat the diseases we have so long thought beyond our ability. It is our ability to see with fresh eyes, to look at all organisms and all cells without preconceptions, that permits us to finally do something about Alzheimer’s and other age-related disease.

Only an open mind will allow us to save lives.


November 22, 2016

Teaching Cells to Fish

Aging is the slowing down of active molecular turnover, not the passive accumulation of damage. Damage certainly accumulates, but only because turnover is no longer keeping up with that damage.

It’s much like asking why one car falls apart, when another car looks like it just came out of the showroom. It’s not so much a matter of damage (although if you live up north and the road salt eats away at your undercarriage, that’s another matter), as it is a matter of how well a car is cared for. I’ve see an 80-year-old Duesenberg that looks a lot better than my 4-year-old SUV. It’s not how well either car was made, nor how long either car has been around, but how well each car was cared for. If I don’t care for my SUV, my SUV rusts; if a car collector gives weekly (even daily) care to a Duesenberg, then that Duesenberg may well last forever.

The parallel is apt. The reason that “old cells” fall apart isn’t that they’ve been around a long time, nor even that they are continually being exposed to various insults. The reason “old cells” fall apart is that their maintenance functions slow noticeably and that maintenance fails to keep up with the quotidian damage occurring within living cells. If we look at knees, for example, the reason that our chondrocytes fail isn’t a matter of how many years you’ve been on the planet, nor even a matter of how many miles a day you spend walking around. The reason chondrocytes fail is because their maintenance functions slow down and stop keeping up with the daily damage. As it turns out, that deceleration in maintenance occurs because of changes in gene expression, which occur because telomeres shorten, which occur because cells divide. And, not at all surprisingly, the number of those cell divisions is related to how long you’ve been on the planet (how old you are) and how many miles you walk (or if you play basketball). In short, osteoarthritis is distantly related to your age and to the “mileage” you incur, but not directly so. The problem is not really the age nor is it the mileage; the problem is the failure to repair the routine damage and THAT failure is directly controlled by changes in gene expression.

So what?

The telomeres and gene expression may play a central role, but if your age and the “mileage” is distantly causing all those changes in cell division, telomere lengths, gene expression, and failing cell maintenance, then what’s the difference? Why bother with all the complexity? Why not accept that age and your “mileage” are the cause of aging diseases and stop fussing? Why not simply accept age-related disease?

Because we can change it.

The question isn’t “why does this happen?” so much as “what can we do about it?” We can’t change your age and it’s hard to avoid a certain amount of “mileage” in your daily life, but we CAN change telomeres, gene expression, and cell maintenance. In fact, we can reset the entire process and end up with cells that keep up with damage, just as your cells did when you were younger.

Until now, everyone who has tried to deal with only the damage (or the damaged cells) failed because they focused on damage rather than focusing on repair. For example, if you focus only on cell damage (as most big pharma and biotech companies do when they go after beta amyloid or tau proteins in trying to cure Alzheimer’s disease), then any clinical effect is transient and the disease continues to progress – which is why companies like Eli Lily, Biogen, TauRx, and dozens of other companies are frustrated. And small wonder. Or if you focus only on the damaged cells (and try removing them), then the clinical effect is not only transient, but will end up accelerating deterioration (as discussed in last week’s blog, see figure below) – which is why companies like Unity will be frustrated. Their approaches fail not because they don’t address the damage, but because they fail to understand the deceleration of dynamic cell maintenance that occurs with age – and fail to understand the most effective single clinical target. The key target is not damage, nor damaged cells, but the changes in gene expression that permit that damage, and those damaged cells, to lead to pathology. We can’t cure Alzheimer’s or osteoarthritis by removing senescent cells, but we can cure them by resetting those same cells.

Why you shouldn't kill senescent cells.

Why you shouldn’t kill senescent cells.

In the cases of removing senescent cells (an approach Unity advocates), wouldn’t it be better to remove the damaged cells and then reset the telomeres of those that remain? But why remove the damaged cells if you can reset them as well, with the result that they can now deal with the damage and remove it – as well as young cells do?

Why remove senescent cells at all?

While you could first remove senescent cells, then add telomerase so that the remaining cells could divide without significant degradation of function, why would you bother? You could much more easily, more simply, and more effectively treat all the cells in an aging tissue, reset their aging process and have no need to ever remove senescent cells in the first place. Instead of removing them, you simply turn them into “younger” and more functional cells. For an analogy, imagine that we have a therapy that could turn cancer cells into normal cells. If that were true, why would anyone first surgically remove a tumor? If you could really “reset” cancer cells into normal cells, there would be no need to do a surgical removal in the first place. While there is no such therapy for cancer cells, the analogy is still useful. Removing senescent cells is not only counter-productive, but (if we reset gene expression) entirely unnecessary.

Removal is unnecessary (both as to cost and pathology), risky, and medically contraindicated. You’d be performing a completely unnecessary procedure when a more cost-effective and reliable procedure was available. It would be exactly like removing your tonsils if you already had overwhelming data showing that an antibiotic was reliable, cheap, and without risk.

A cell with full telomere lengths – regardless of prior history – is already superior. The accumulated damage is not a static phenomenon, but a dynamic one. Reset cells can clean up damage. This is not merely theory, but supported well in fact, based on both human cells and whole animal studies. We shouldn’t think of damage as something that merely accumulates passively. All molecules are continually being recycled. The reason some molecular pools show increased damage isn’t because molecules denature, but because the rate of turnover slows, thereby allowing denatured molecules (damage) to increase within the pool.

Try this analogy: we have two buildings. One is run by a company that invests heavily in maintenance costs, the other is run by a company that cut its maintenance budget by 50%. The first building is clean and well-kept, the second building is dirty and poorly-kept. Would you rather raze the second building and then rebuild it or would you rather increase the maintenance budget back to a full maintenance schedule and end up with a clean building? This is precisely the case with young versus old cells: the problem is not the dirt that accumulates, the problem is that no one is paying for routine maintenance. There are cells that are “too senescent” to save, but almost all the cells in human age-related disease can be reset with good clinical outcome. There is no reason to remove senescent cells any more than (in the case of a dirty building), we need to send in the dynamite and bulldozers.

Too often, we try to approach the damage rather than looking at the longer view. Instead of addressing the process, we address the outcome. It’s like the problem that often occurs in global philanthropy, where we see famine and think we can solve the problem with food alone. While the approach is necessary – as a stopgap – many are surprised to find that simply providing free food for one year, results in bankrupt farmers and recurrent famines in the following years. Or we provide free medical care in a poor nation, then wonder why there is a dearth of medical practitioners in years to come, without realizing we have put them out of business and accidentally encouraged them to emigrate to someplace they can make a living and feed their families. We intend well, but we perpetuate the problem we are desperately trying to solve. Treating famine or medical problems, like treating the fundamental causes of age-related disease, is not simple and cannot be effectively addressed with band aids and superficial interventions, such as addressing damage alone or removing senescent cells. Effective clinical intervention – like effective interventions in famine or global healthcare – require a sophisticated understanding of the complexity of cell function, an understanding of the dynamic changes that underlie age-related pathology.

An adage (variously attributed to dozens of sources) about fish and fishing provides a useful analogy here:

Give a man a fish, and you feed him for a day.

Teach a man to fish, and you feed him for a lifetime.

If we want to intervene effectively in age-related diseases – whether Alzheimer’s, osteoarthritis, or myriad other problems of aging – we shouldn’t throw fish at medical problems.

We should teach our cells to fish.


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