Michael Fossel Michael is President of Telocyte

March 6, 2018

Aging and Disease: 1.4 – Aging, the Overview

How does aging work?

So far, in the prologue (section 0) and the section 1 posts, we have discussed a perspective, what aging isn’t (and is), and what we need to explain in any accurate model of aging. In this post, I provide an overview of how the aging process occurs, from cell division to cell disease, followed by a post on the common misconceptions about this model, which will complete section 1. Section 2 is a series of posts that provide a detailed discussion of cell aging, section 3 explores age-related disease, and section 4 maps out the potential clinical interventions in aging and age-related disease. In this post, however, I provide an outline or map of the entire aging process. This will shoehorn much of what we know about cellular aging and age-relaed disease into a single post, giving you an overview of how aging works.

Cell Division

Aging begins when cells divide. Before moving beyond this, however, we need to ask ourselves why cells divide in the first place. The impetus for cell division is itself a driving force for aging, and the rate and number of cell divisions will control the rate of aging. IF cell division “causes” aging, then what causes cell division? As with any comprehensive examination of causation, we immediately discover that if A causes B, there is always something (often ignored) that must have caused A in turn. In short, causation (and this is equally true of aging) is a cascade of causation that can be pushed back as far as you have to patience to push the question. In the case of cell division, the next upstream “cause” is often environmental and is related to daily living itself. For example, we loose skin cells because we continually slough them off and we therefore need our cells to divide and replace the cells that we lose. As with most tissues, the rate of cell division is strongly modulated by what we do (or what we’re exposed to). If we undergo repeated trauma or environmental stress, then we lose more cells (and consequently have more frequent cell divisions) than we would otherwise. In the knee joint, for example, cell division in the joint surface will be faster in those who undergo repetitive trauma (e.g., basketball players) than in those who engage in low-impact activities (e.g., yoga). In the arteries, cell divisions along the inner arterial surface will be faster in those suffering from hypertension than in those with lower blood pressure (and lower rheological stress). Not all cells divide regularly. While some cells rarely divide in the adult (muscle cells, neurons, etc.), those that do divide regularly – such as skin, endothelial cells in the vascular system, glial cells in the brain, chondrocytes in the joints, osteocytes in the bone, etc. – will vary their rate of division in response to trauma, toxic insults, malnutrition, infections, inflammation, and a host of other largely environmental factors. Putting it simply, in any particular tissue you look at, the rate of cellular aging depends on what you do to that tissue and those cells. Repeated sunburns induce more rapid skin aging, hypertension induces more rapid arterial aging, close head injuries induce more rapid brain aging, and joint impacts induce more rapid joint aging. In all of these cases, the clinical outcome is the acceleration of tissue-specific age-related disease. So while we might accurately say that aging begins when cells divide, we might equally go up one level and say that aging begins in whatever prompts cell division. Any procees that accelerates cell loss, accelerated cell division, and thus accelerates aging and age-related disease.

Telomere Loss

Cell division has limits (as Len Haylfick pointed out in the 1960’s) and tee limits on cell division are, in turn, determined by telomere loss (as Cal Harley and his colleagues pointed out in the 1990’s). Telomeres, the last several thousand base pairs at the end of nuclear chromosomes (as opposed to mitochondrial chromosomes), act as a clock, setting the pace and the limits of cell division. In fact, they determine cell aging. Telomeres are longer in young cells and shorter in old cells. Of course, it’s never quite that simple. Some cells (such as germ cells) actively replace lost telomere length regardless of chronological age, while others (such as neurons and muscle cells) divide rarely and never shorten their telomeres as the adult tissues age. Most of your body’s cells, those that routinely divide, show continued cell division over the decades of your adult life and show a orrelated shortening of their telomeres. Note (as we will in the next blog post) that it is not the absolute telomere length that is the operative variable, but the relative telomere loss that determines cell aging. Nor, in many ways, does even the relative telomere length matter, were it not for what telomeres control “downstream”: gene expression.

Gene Expression

As telomeres shorten, they have a subtle, but pervasive effect upon gene expression throughout the chromosomes and hence upon cell function. In general, we can accurately simplify most of this process as a “turning down” of gene expression. The process is not all-or-nothing, but is a step-by-step, continuum. Gene expression changes gradually, slowly, and by percent. The change is analogous to adjustments in an “volume control” rather the use of an on/off switch. Where once the expression of a particular gene resulted in a vast number of proteins in a given time interval, we now see 99% of that amount are now produced in that time interval. The difference may be one percent, it may be less, but this small deceleration in the rate of gene expression becomes more significant as the telomere shortens over time. Whereas the young cell might produce (and degrade) a pool of proteins using a high rate of molecular “recycling”, this recycling rate slows with continued cell division and telomere shortening, until older cells have a dramatically slower rate of molecular recycling. While you might suspect that a slightly slower rate of turnover wouldn’t make much difference, this is actually the single key concept in aging and age-related disease, both at the cellular and the tissue levels. We might, with accuracy and validity, say that aging is not caused by telomere loss, but that aging is caused by changes in gene expression and, even more accurately, that aging is caused by the slowing of molecular turnover.

Molecular Turnover

To understand molecular turnover is to understand aging. As we will see later in this series (including a mathematical treatment with examples), the predominant effect of slower molecular turnover is to increase the percentage of denatured or ineffective molecules. Examples would include oxidized, cross-linked, or otherwise disordered molecules due to free radicals, spontaneous thermal isomerization, or other disruptive, entropic processes. The cell’s response to such molecular disruption is not to repair damaged molecules, but to replace such molecules with new ones. This replacement process, molecular turnover, is continual and occurs regardless of whether the molecules are damaged or not. The sole exception to the use of replacement rather than repair is that of DNA, which is continuall being repaired. But even the enzymes responsible for DNA repair are themselves being continually replaced and not repaired. There are no stable molecular pools, intracellular or extracellular: all molecular pools are in dynamic equilibrium, undergoing continual turnover, albeit at varying and different rates. Some molecules are replaced rapidly (such as the aerobic enzymes within the mitochondria), others more slowly (such as collagen in the skin), but all molecular pools are in a condition of dynamic equilibrium. More importantly, if we are to understand aging, the rate of molecular turnover slows in every case as cells senesce and the result is a rise in the proportion of damage molecules. To use one example, beta amyloid microaggregates in the brain (in Alzheimer’s disease) occur not simply result because damage accrues over time (entropy). Amyloid microaggregates begin to form when the rate of glial cell turnover of beta amyloid molecules (the binding, internalization, degradation, and replacement of these molecules) becomes slower over time and is no longer keeping pace with the rate of molecular damage (maintenance versus entropy). The result is that beta amyloid molecular damage occurs faster than molecular turnover, and the the histological consequence is the advent of beta amyloid plaques. The same principle – the slowing of molecular turnover with cell aging – applies to DNA repair and the result in an exponential rise in cancer, as we will see in later sections. This general problem of slower molecular turnover applies equally within aging skin, where wrinkles and other facets of skin aging are not the result of entropy, but result from the failure of maintenance (e.g., turnover of collagen and elastin) to keep up with entropy. The incremental and gradual slowing of molecular turnover or molecular recycling is the single most central concept in aging. Aging isn’t caused by damage, but by the failure of maintenance to keep up with that damage. Aging results from insufficient molecular turnover.

Cell and Tissue Dysfunction

The slower molecular turnover and it’s outcome – an increase in dysfunctional molecules – results in a failure within and between cells. Within the cell, we see slower DNA repair, leakier mitocondrial membranes, an increase in the ratio of ROS/ATP production (creating more free radicals and less energy), decreasinly effective free radical scavengers, and a general decrease in the rate of replacement of those molecules that are damage, whether by free radicals or otherwise. For the cell itself, the outcome is a gradual loss of function and an increase in unrepaired DNA. With respect to free radicals, for example, it’s not that free radical damage causes aging, but that cellular aging causes free radical damage. As our cells age (and molecular turnover slows), our mitochondria produce more free radicals (since the aerobic enzyemes aren’t as frequently replace), the mitochondrial membranes leak more free radicals (since the lipid molecules in the mitochondrial aren’t as frequently replaced), free radicals are more common in the cytoplasm (since free radical scavenger molecules are as frequently replaced), and consequent damage becomes more common (since damaged molecules aren’t as frequently replaced). Free radicals do not cause aging: they are merely an important by-product of the aging process. As in cells, so in tissues: just as molecular turnover slows and results in cellular dysfunction, so do do we see dysfunction at higher levels: tissue, structural anatomy, and organ systems. Slowing of molecular turnover expresses itself in dysfunctional cells, an increase in carcinogenesis, and ultimately in clinical disease.

Age-Related Disesase

At the clinical level, the changes in cell and tissue function result in disease and other age-related changes. Wrinkles, for example, may not be a disease, but they result from exactly the same cellular processes outlined above. In each case, however, we see age-related changes or age-related diseases are the result of underlying “upstream” processes that follow a cascade of pathology from cell division, to telomere shortening, to epigenetic changes, to a slowing of molecular turnover, to growing cellular dysfunction. As glial cells “slow down” (in their handling of amyloid, but also in regard to mitochondrial efficiency and a host of other subtle dysfunctions), the result is Alzheimer’s and the other human dementias. As vascular endothelial cells senesce, the result is coronary artery disease, as well as heart attacks, strokes, aneursyms, peripheral vascular disease, and a dozen other age-related diseases and syndromes. As chondrocytes senesce, the result is ostoarthritis. As osteocytes senesce, the result is osteopororis. Nor are these the only manifestations. We see cell senescence in renal podocytes, in dermal and epidermal cells of the skin, in fibroblasts within the lung, and in essentially every tissue that manifests age-related changes. Age related disease and age-related changes are, at the clinical level, the predictable and ultimate outcomes of cellular aging.

The above model is accurate, consistent, and predictively valid, yet there have been a number of crucial misconceptions that have remained common in the literature, making it difficult for many people to grasp the model correctly. Next time, we will explore these errors before moving into the details of aging and disease.

Next: 1.5 – Aging, Misconceptions


February 20, 2018

Aging and Disease: 1.3 – Aging, What it IS

What IS aging?

An explanation of aging must account for all cells, all organisms, and – if we are candid – all of biology and isn’t merely entropy. Prior posts defined our boundaries: what we must include – and exclude. We know that we cannot simply point to entropy, wash our hands of any further discussion, and walk away with our eyes closed. Likewise, an honest explanation can’t simply consider humans and a few common mammals but ignore the entire gamut of Earth’s biology.

So, what IS aging? As a start, we might acknowledge that life has been on Earth for more than four billion years and during that entire time, life has resisted entropy. This serves as an excellent starting point: life might be defined as the ability to maintain itself in the face of entropy. In that case, we might rough out our initial definition: aging is the gradual failure of maintenance in the face of entropy.

We miss the point, however, unless we realize that aging is an active, dynamic process. Aging is not simply a matter of a failure of maintenance in the passive sense. To use an analogy, if entropy were an escalator carrying us downwards, then it is not the only process involved. It is countered by cell maintenance, which is precisely like walking upwards on the same escalator (see Figure 1.3a). Young cells are entirely capable, as are germ cells and many other cells, of indefinitely maintaining their position at the top of the escalator. Entropy and maintenance are equally balanced. Older cells, however, have a subtle (and sometimes not so subtle) imbalance, in which maintenance is less than entropy.

As aging occurs, the problem is not that the escalator (entropy) carries us downwards, but that we are no longer walking upwards (maintenance) at the same rate as the escalator. To view aging as the descending escalator alone is to miss the essential point of biology: life remains on this planet because cells and organisms “walk upwards” and maintain themselves indefinitely in the face of being “carried downwards” by entropy. The process is a dynamic balancing act. To explain aging, it is not enough to cite the escalator, but requires that we explain why maintenance fails, and then only in certain cells and at certain times, while remaining functional in other cells and at other times. Aging is far from universal. A valid explanation of aging must account for why aging occurs in some cases yet does not occur in other cases.


Aging is not the escalator but is a combination of two forces: entropy carrying cells into dysfunction and maintenance ensuring that cells remain functional. Aging occurs only when maintenance is down-regulated. If maintenance is not down-regulated, then the cells and the organism do not age. Aging cells, such as many somatic cells, age because they down-regulate maintenance. “Immortal” cells, such as germ cells, do no age because they do not down-regulate maintenance.

We might try an analogy to see where it takes us, comparing biological aging to “aging” in a car. We could say that aging in a car is not simply what happens as the car undergoes weathering and degradation over time. Rather, car aging would be what happens if we fail to maintain the car on a regular and detailed basis. There are exceptional antique cars that have been in active use longer than most human lifetimes, but they are in excellent shape not because they had better parts (i.e., have the right genes) or were made by a better manufacturer (i.e., are part of the right species), but because they were maintained scrupulously and carefully on an almost daily basis by generations of owners. Such cars are oiled, painted, repaired, realigned, and cared for on an almost daily basis, compared to most cars that are lucky to be cared for annually. The critical difference is not the chronological age of the car nor the amount of wear-and-tear, but the frequency and excellence of their maintenance. Given frequent and excellent maintenance, sufficient to keep up with entropy, a car can last indefinitely, while with sloppy and merely annual maintenance, cars typically last only a few years before “aging” takes them off the road.

In a sense, organisms are no different: the degree of aging is not just a matter of time or entropy, but of the quality and frequency of maintenance. Likewise, aging is not purely a matter of which genes or what species pertain to that organism. Rather, aging is a matter of the rate of repair and recycling within cells, that is, maintenance in the face of entropy.
It’s not the genes, it’s the gene expression.

Let’s use another example, that of water recycling. Every molecule of water that you ingest has been recycled endlessly, but the speed and efficiency of that recycling determines the quantity and quality of the water you drink. Imagine that we plan a trip to Mars. If the average astronaut needs 2 liters per day and 4 astronauts are on a 2.5-year roundtrip to Mars, we might calculate that we need to bring 7 tons of water. But that (incorrectly) assumes no recycling. We can get by on a lot less water, depending on how we recycle. The amount we need to bring with us depends not only on the amount the astronauts use daily, but on the quality and rate of recycling (from urine, for example). The faster the recycling, the less water we need to carry along. The better the quality of our recycling, the longer we can stay healthy.

In a “young” and efficient cell, we recycle molecular pools rapidly and effectively. In an old cell, however, the rate and effectiveness of the recycling decreases. The analogy for our Mars trip would be slower recycling, along with an increasing percent of contaminants that are not being removed in our water recycling unit. The outcome, whether in aging cells or a mission to Mars, is gradually increasing dysfunction. Aging cells no longer function normally (as when they were young cells) and our sickening astronauts no longer function normally either (as when they started out on Earth).
As another example, you oversee a huge office building with multiple daily customers and hundreds of employees. Every night, your cleaning crew comes through, mopping the solid floors, vacuuming the carpets, cleaning the windows, and (when necessary) repainting the walls. Maintenance is frequent and excellent; as a result, the building always looks new (i.e., young). Now let’s radically cut back on your maintenance budget. Instead of daily maintenance, the carpets are vacuumed once every two weeks, the floors are mopped once a month, the windows are cleaned once a year, and repainting occurs once a decade. The resulting problem is not due to the amount of dirt (the entropy), nor the quality of the vacuum, the mop, the washer fluids, or the paint (think of these as the quality of your genes). The problem isn’t the dirt nor is it the cleaning crew, but the rate of maintenance. The outcome is that your building looks dirty and is increasingly incapable of attracting clients or customers – or for that matter, incapable of retaining employees. This parallels the changes in aging cells: the genes (the cleaning products) are excellent and the quality of repair (the cleaning staff) are both excellent, but the frequency of maintenance is too low to maintain the quality of the building. In aging cells, molecular turnover is too slow to keep up with entropic change.

This same analogy could be applied to home repairs, garden weeding, or professional education. The problem is not entropy, but our ability to resist entropy and maintain function. Aging occurs because cell maintenance becomes slower. The quality of gene expression is fine, but molecular turnover (see figure 1.3b) – the “recycling rate” – declines. This effect is subtle but pervasive and the result is increasing dysfunction. This concept – the failure of maintenance to keep up with entropy — is not only central to aging but can account for all of aging and in all organisms, whether at the genetic level, the cellular level, the tissue level, or the clinical outcome – age-related disease.

Aging is a dynamic process, in which entropy begins to gain as maintenance processes become gradually down-regulated.

In subsequent posts, we will explore the detailed mathematics of this change, reviewing the formula and the primary variables, letting us see the remarkable results that occur in terms of denatured molecules and cellular dysfunction. For now, however, let’s look at a few specific clinical examples in human aging, all of which we’ll return to in later posts, when we consider age-related diseases in great detail.

In human skin, between cells, we see changes in collagen and elastin (among dozens of other proteins) as we age. Many people mistakenly assume that these changes are a simple, static accumulation of damage over a lifetime, but these changes are anything but static. These molecules are in dynamic equilibrium, in which the molecules (and their complex structures) are constantly being produced (anabolism) and broken down (catabolism). The overall rate of recycling (the overall metabolism) is high in young skin, with the result that at any given time, most molecules are undamaged and functional (and relatively new). This rate slows with aging, however, with the result that molecules remain longer before being “recycled” and the percentage of damaged and dysfunctional molecules rises, slowly but inexorably. In old skin, molecules “sit around” too long before being recycled. Old skin isn’t old because of damage, but because the rate of maintenance becomes slower and slower. Naïve cosmetic attempts to “replace” skin collagen, elastin, moisture, or other molecules fail because they are transient interventions. By analogy, these cosmetic interventions would be like – in the case of our old, dirty office building – suggesting that we will send in one person, one night, to clean one window pane. Even if you notice a small, transient improvement, the problem isn’t resolved by bringing in one person for a single visit, it requires that we resume having the entire cleaning crew come in every night. Intervening in skin aging is not a matter of providing a few molecules, but of increasing the rate of turnover of all the molecules.

The same problem occurs in aging bones. The problem that lies at the heart of osteoporosis is not “low calcium”, but the rate at which we turnover our bony matrix. Looking solely at calcium as one example, osteoporosis not a static problem (add calcium), but a dynamic problem (increase the rate of calcium turnover). Moving our attention from minerals to cells, young bone is constantly being taken apart (by osteoclasts) and rebuilt (by osteoblasts). The result is continual remodeling (recycling) and repair. Bone turnover is a continual process that slows with age. Young fractures heal quickly and thoroughly. In old bone, however, the rate of remodeling falls steadily, and rebuilding falls slightly behind. The result is that we have decreased matrix, decreased mineralization, decreased bone mass, and an increasing risk of fractures. The fundamental problem underlying osteoporosis is not “a loss of bone mineral density”, but an inability to maintain bony replacement. It’s not the calcium or the phosphorous, but the osteocytes themselves. Loss of bone mineralization is a symptom, not the cause of osteoporosis.

A more tragic and more fatal example is Alzheimer’s disease. Until relatively recently, the leading pathological target was beta amyloid, a molecule which (like tau proteins and other candidates) shows increasing damage and denaturation (plaques in the case of amyloid) in older patients, especially in patients with Alzheimer’s disease. Again, however, amyloid is not a static molecule that is produced, sits around, and slowly denatures over a lifetime. Amyloid is continually produced and continually broken down, but the rate of recycling falls as we age. The result is that the percentage of damaged amyloid (plaque) rises with age, solely because the rate of turnover is slowing down. As we will see, the cells that bind, internalize, and breakdown this molecule become slower as we age. To address Alzheimer’s, we don’t need to remove amyloid or prevent its production, we need to increase the rate of turnover. Beta amyloid plaques are a symptom, not the cause of Alzheimer’s disease.

Wherever we look — an aging cell, an aging tissue, or an aging organism – we see that aging is not a static, linear loss of function due to entropy. Rather, aging is a dynamic process in which the rate of recycling – whether of intracellular enzymes, extracellular proteins, aging cells, or aging tissues – becomes slower as cells senesce. Aging is a programmed failure of maintenance at all biological levels. This is equally true of DNA repair, mitochondrial function, lipid membranes, proteins, and everything else we can measure in an aging system.

We’ve had a glimpse at the core of aging. Let’s explore an overview of how changes in gene expression translate into cell dysfunction, tissue failure, clinical disease, and aging itself.

Next time: Aging, the Overview

February 13, 2018

Aging and Disease: 1.2 – Aging, What We Have to Explain

Our understanding is limited by our vision.

If we look locally, our understanding is merely local; if we look globally, our understanding becomes more global; and if we look at our entire universe, then our understanding will be universal. When we attempt to understand our world, we often start with what we know best: our own, local, provincial view of the world around us, and this limits our understanding, particularly of the wider world beyond our local horizon.

Trying to explain the shape of our world, I look at the ground around me and – perhaps not surprisingly – conclude that the world is probably flat. After all, it looks flat locally. Trying to understand the heavens, I look up at the sky around me and – perhaps not surprisingly – conclude that the sun circles the earth. After all, the sun appears to circle over me locally. Trying to understand our physical reality, I look at everyday objects and – perhaps not surprisingly – conclude that “classical physics” accounts for my universe. After all, classical physics accounts for typical objects that are around me locally. As long as we merely look around, look up, and look at quotidian objects, these explanations appear sufficient.

But it is only when we look beyond our purely local neighborhood – when we move beyond our provincial viewpoint, when we give up our simple preconceptions – that can we begin to understand reality. Taking a broader view, we discover that the Earth is round, that the sun is the center of our local star system, and that quantum and relativity physics are a minimum starting point in trying to account for our physical universe.

To truly understand requires that we step back from our parochial, day-to-day, common way of seeing world and open our minds to a much wider view of reality. We need to look at the broader view, the larger universe, the unexpected, the uncommon, or in the case of modern physics, the extremely small and the extremely fast. Time, mass, energy, and other concepts may become oddly elusive and surprisingly complicated, but our new understanding, once achieved, is a lot closer to reality than the simple ideas we get from restricting our vision to the mere commonplace of Newtonian physics. This is true of for branch of science, and for human knowledge generally.

The wider we cast our intellectual nets, the more accurately we understand our world.

To understand aging demands a wide net. If our knowledge of aging is restricted to watching our friends and neighbors age, then our resulting view of aging is necessarily naïve and charmingly unrealistic. If we expand our horizons slightly, to include dogs, cats, livestock, and other mammals, then we have a marginally better view of aging. But even if we realize that different species age at different rates, our understanding is only marginally less naive. To truly understand aging, we need to look at all of biology. We need to look at all species (not just common mammals), all diseases (e.g., the progerias and age-related diseases in all animals), all types of organisms (e.g., multicellular and unicellular organims, since some multicellular organisms don’t age and some unicellular organisms do age), all types of cell within organisms (since somatic cells age, germ cells don’t, and stem cells appear to lie in between the two extremes), and all the cellular components of cells. In short, to understand aging – both what aging is and what aging isn’t – we need to look at all life, all cells, and all biological processes.

Only then, can we begin understand aging.

To open our minds and examine the entire spectrum of aging – so that we can begin to understand what aging is and how to frame a consistent concept of “aging” in the first place – let’s contrast the small sample we would examine in the narrowest, common view of aging with the huge set of biological phenomena we must examine if we want to gain comprehensive and accurate view of aging, a view that allows us to truly understand aging.

The narrow view, the most common stance in considering aging, examines aging as we encounter it in normal humans (such as people we know or people we see in the media) and in normal animals (generally pets, such as dogs and cats, and for some people, domesticated animals, such as horses, cattle, pigs, goats, etc.). This narrow view leaves out almost all species found on our planet. This sample is insufficient to make any accurate statements about the aging process, with the result that most people believe that “everything ages”, “aging is just wear and tear”, and “nothing can be done about aging”. Given the narrow set of data, none of these conclusions are surpring, but then it’s equally unsurprising that all of these conclusion are mistaken.

A broad view has a lot more to take into consideration (see Figure 1), which is (admittedly) an awful lot of work. The categories that we need to include may help us see how broad an accurate and comprehensive view has to be. We need to examine and compare aging:

  1. Among all different organisms,
  2. Within each type of organism,
  3. Among all different cell types, and
  4. Within each type of cell.


Lets look at these categories in a bit more detail.

When we look at different organisms, we can’t stop at humans (or even just mammals). We have to account for aging (and non-aging) in all multicellular organisms, including plants, lobsters, hydra, naked rats, bats, and everything else. And not only do we need to look at all multicellular organisms, we also need to account for aging (and non-aging) in all unicellular organisms, including bacteria, yeast, amoebae, and everything else. In short, we need to consider every species.

When we look within organisms, we need to account for all age-related diseases (and any lack of age-related diseases or age-related changes) within organisms. Diseases will include all human (a species that is only one tiny example, but that happens to be dear to all of us) age-related diseases, such as Alzheimer’s disease and all the other CNS age-related diseases, arterial aging (including coronary artery disease, strokes, aneurysms, peripheral vascular disease, cogestive heart failure, etc.), ostoarthritis, osteoporosis, immune system aging, skin aging, renal aging, etc. But we can’t stop there by any means. In addition to age-related diseases within an organism, we need to look at aging changes (and non-aging) whether they are seen as diseaeses or not, for example graying hair, wrinkles, endocrine changes, myastenia, and hundreds of other systemic changes in the aging organism.

When we look at different cells, we need to account for the fact that some cells (e.g., the germ cell lines, including ova and sperm) within multicellular organisms don’t age, while other cells in those same organims (e.g., most somatic cells) do age, and some cells (e.g., stem cells) appear to be intermediate between germ and somatic cells in their aging changes.

When we look within cells, we need to account for a wild assortment of age-related changes in the cells that age, while accounting for the fact that other cells may show no such changes, even in the same species and the same organism. In cells that age – cells that senesce – we need to account for telomere shortening, changes in gene expression, methylation (and other epigenetic changes), a decline in DNA repair (including all four “families” of repair enzymes), mitochondrial changes (including the efficacy of aerobic metabolism enzymes deriving from the nucleus, leakier mitochondrial lipid membranes, increases in ROS production per unit of ATP, etc.), decreased turnover of proteins (enzymatic, structural, and other proteins), decreased turnover of other intracellular and extracellular molecules (lipids, sugars, proteins, and mixed types of molecules, such as glycoproteins, etc.), increased accumulation of denatured molecules, etc. The list is almost innumerable and still growing annually.

If we are truly to understand aging, we cannot look merely at aging humans and a few aging mammals, then close our minds and wave our hands about “wear and tear”. If we are to understand aging accurately and with sophistication, then we must not only look at a broader picture, but the entire picture. In short, to understand aging, we must stand back all the way in both time and space, and look at all of biology.

To understand aging, we must understand life.

February 7, 2018

Aging and Disease: 1.1 – Aging, What it Isn’t

Filed under: Aging diseases,Alzheimer's disease,mitochondria — Tags: , , , — webmaster @ 9:29 am

It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.

– Mark Twain

Twain was right, particularly when it comes to the aging process: there is a lot we think we “know for sure that just ain’t so”. For example, most people (without even thinking about it and with a fair amount of naïve hand-waving) assume that all organisms age and equate aging with entropy. In other words, they think that “aging is just wear-and-tear”. We assume that aging “just happens” and that nothing can be done about it. After all, we all get old, things fall apart, things rust, everything wears out, so what can you expect? But as with Twain’s remark, the trouble is that we are quite sure of ourselves and we what we think is completely obvious, turns out to be completely wrong. We are content to gloss over our faulty assumptions and move to faulty conclusions. It’s bad logic, bad science, and a bad way to intervene in the diseases of aging. Without thinking about it, we conclude that aging is as simple as our preconceptions, which turn out to be erroneous.

Aging isn’t simple and our preconceptions are wrong.

As with most concepts that we don’t examine meticulously, aging is a lot more complex than we realize. Aging isn’t just entropy, it isn’t just wear-and-tear, and it isn’t many things that people blithely believe it to be. Let’s look at a few examples that make us back up and reconsider how aging works. Let’s start with your cells, and then your mitochondria.

We could take any cell in your body, for example a skin cell on the back of your hand. How old is that skin cells? Since we shed perhaps 50 million skin cells every day, there’s a good chance that the cell we are thinking about is only a day or so old, or at least a day or so since the last cell division. But that last division was from a “mother” cell that was there before the cell division resulted in two “daughter” cells. So perhaps our skin cell, counting the age of the “mother” cell is a week or so old? But that “mother” cell, in turn, derived from a dividing cell that was there several weeks ago, backwards ad infinitum to the first cells that formed your body. In fact, every cell in your body is certainly as the whole body, so perhaps that skin cell is a few decades old. You might say that the skin cell has the same age that you see on your driver’s license. Except that your entire body is the result of a cell (ova) from your mother and a cell (sperm) from your father, and each of those cells was already a few decades old (or however old your parents were) when the sperm and ovum became “you” when they joined at fertilization. But, of course, your parent’s germ cells came from their parents, whose germ cells came from their parents, and we can trace that lineage of germ cells back to… Well, all the way back to the origin of life on Earth. So in a very real, very strictly accurate biological sense, every cell in your body is 3.5 billion years old.

But if we assume that aging is just entropy, then we have explain why that line of germ cells (that resulted in your entire body) didn’t undergo any entropy (i.e., didn’t age) for 3.5 billion years and yet your somatic cells are now undergoing entropy (i.e., aging) in your body and have been aging since you were born. Why do somatic cells suffer from entropy, if germ cells don’t? Does entropy only work in certain cells and not in others? Apparently so. And if that’s true, then we can’t just wave our hands and invoke entropy as the entire explanation, can we? We have to explain something more subtle and complicated: why entropy results in aging in some cases (the somatic cells in your body) but not in other cases (the line of 3.5 billion year-old germ cells that led up to you having a body in the first place). How interesting. So much for just invoking the concept of entropy and walking away satisfied.

Entropy almost certainly plays a key role in aging, but we can’t simply leave it at that. We need to think a bit harder. Sometimes entropy wins (your body and most of its cells age in a matter of decades) and sometimes entropy doesn’t appear to win at all (your germ cell line didn’t age for 3.5 billion years). Why sometimes and not other times?

One way that some people have tried to explain this is to invoke mitochondrial damage, but an almost identical problem surfaces in the case of mitochondrial entropy. Given the prevalence of aging explanations based on free radical theory (reactive oxygen species, etc.), mitochondrial dysfunction is an obvious suspect for an explanation of aging. We know that older mitochondria make more free radicals, leak more, and those free radicals aren’t scavenged as well, so perhaps all of aging is a mitochondrial problem? Perhaps entropy simply causes mitochondrial damage and that’s why we age. Perhaps entropy works by aging our mitchondria, right?

Except that mitochondrial entropy can’t explain aging either.

If aging were the result of “aging” mitochondria, damaged by entropy (high internal mitochondrial temperature, free radicals, loose protons and electrons, and a general accumulation of mitochondrial damage over time), then we are still left with an embarrassing conundrum. To understand the problem, let’s ask a simple question: how old are your mitochondria? Mitochondria divide fairly constantly, depending on the cell and its energy demands. In some cells (such as liver cells), with high energy demands, mitochondria are dividing all the time, in others with low energy demands, mitochondria divide much less frequently. On the other hand, since every mitochondria in every cell in your body derived from the mitochondria that were present in you as a fertilized zygote, we might reasonably say that your mitochondria are all the same age as your body, i.e., all of your mitochondria are a few decades old, and as time goes by, your mitochondria simply wear out, right?

Well, no.

Every mitochondria that you had as a fertilized zygote was derived from your mother’s ovum, which supplied all of your original mitochondria, so your mitochondria are as old as you are. Well, as old as you are plus as old as your mother was when you were conceieved. Oh, and plus the age of her mother and her mother and so on, ad infinitum back as far as the very first mitochondrial inclusion in the very first eukaryotes (or so). So every mitochondria in your body is about 1.5 billion years old and they’re doing pretty well for their age. But that means that if we want to blame aging entirely on mitochondrial dysfunction (and mitochondria surely play a major role in aging), we are still left with a conundrum. We have to explain why all of those dividing mitochondria (which were at least 1.5 billion years old) hadn’t aged for 1.5 billion years, and now all of your mitochondria are having significant problems after only a few decades. Why do your mitochondria suddenly start aging when they were doing so well for the last 1.5 billion years? The problem is that your mitochondria really do showing aging changes, but the mitochondra from your mother clearly didn’t until you came along. Worse yet, we have to explain both of these effects (aging and non-aging) simultaneously if we want to explain aging at all. How can we do both? We can’t simply wave our hands (again) and blame entropy unless we can simultanously explain why entropy works sometimes and in some cells (liver cells, for example), but entropy doesn’t work at other times and in other cells (the mitochondria in the germ cell line, for example). Again, why sometimes and not other times?

If entropy were an entirely sufficient explanation, they why does entropy age some cells (and some mitochondria) and not other cells (and other mitochondria)? If we restrict our explanation of aging solely to entropy, then we have a problem. We can’t just say that entropy does cause aging (because sometimes it doesn’t) nor can we say that entropy doesn’t cause aging (because sometimes it does). Entropy plays a role in aging, but not always.Why? What we have to do, if we really want to explain aging, is explain why entropy varies in biological systems. Sometimes entropy wins, sometimes it doesn’t.

Our preconception about entropy – wear-and-tear – as the sole cause for aging is a common misconception and not always noticed. It creates a subtle, but pervasive bias in our thinking about biolgy and aging. Even once we realize that entropy can’t explain all of cell or mitochondrial aging, we still find entropy creeping back into our thinking, but disguised under a different form. We tend to think of Alzheimer’s, for example, as what happens when beta amyloid, tau proteins, or mitochondria undergo entropy and cause neuronal death and clinical disease. We think of skin aging as what happens when collagen and elastin undergo entropy and cause wrinkles and aging skin. Some people blame aging on entropy of the endocrine system, concluding that all of aging comes about because of entropy in a gland or hormonal tissue. The fact that aging can occur in some organisms without endocrine systems (and that replacing hormones doesn’t stop aging) doesn’t change their misconception. But whatever guise it hides under, entropy by itself, cannot explain aging or age-related disease. There are too many odd things to explain, too many exceptions, too many cases where entropy explains one finding, but not another finding. Entropy can explain this cell, but not that cell. Entropy can explain this mitochondria, but not that mitochondria. Entropy simply can’t explain aging in toto. We have to dig a bit further.

Entropy, as an explanation of aging, only works if we close our eyes and ignore most of biology. As we’ll see in the next blog, there is a lot of biology that needs to be accounted for if we are going to explain how aging works. However we try to shoehorn entropy into being the entire explanation, aging cannot be entropy alone. As we will see, entropy does play a crucial role, but we cannot simply cite entropy, wave our hands, and say we understand aging. Aging is not entropy: aging is entropy plus something else, something subtle and complex, but something crucial to a complete understanding of aging.

As we will soon see, aging is entropy in the face of failing maintenance.


Next: 1.2 – Aging, What We Need to Explain

December 1, 2017

Big Pharma: Still Looking for the Horse

About a century ago, in a small American town, the first automobile chugged to a stop in front of the general store, where a local man stared at the apparition in disbelief, then asked “where’s your horse?” A long explanation followed, involving internal combustion, pistons, gasoline, and driveshafts. The local listened politely but with growing frustration, then broke in on the explanation. “Look”, he said, “I get all that, but what I still want to know is ‘where is your horse?’”

About three hours ago, in a teleconference with a major global pharmaceutical company, I was invited to talk about telomerase therapy and why it might work for Alzheimer’s, since it doesn’t actually lower beta amyloid levels. I explained about senescent gene expression, dynamic protein pools whose recycling rates slow significantly, causing a secondary increase in amyloid plaques, tau tangles, and mitochondrial dysfunction. The pharmaceutical executive listened (not so politely) with growing frustration, then broke in on the explanation. “Look”, she said, “I get all that, but what I still want to know is how does telomerase lower beta amyloid levels?”

In short, she wanted to know where I had hidden the horse.

The global pharmaceutical company that invited me to talk with them had, earlier this year, given up on its experimental Alzheimer’s drug that aimed at lowering beta amyloid levels, since it had no effect on the clinical course. None. They have so far wasted several years and several hundred million dollars chasing after amyloid levels, and now (as judged by our conversation) they still intent on wasting more time and money chasing amyloid levels. We offered them a chance to ignore amyloid levels and simply correct the underlying problem. While not changing the amyloid levels, we can clean up the beta amyloid plaques, as well as the tau tangles, the mitochondrial dysfunction, and all the other biomarkers of Alzheimer’s. More importantly, we can almost certainly improve the clinical course and largely reverse the cognitive decline. In short, we have a new car in town.

As with so many other big pharmaceutical companies, this company is so focused on biomarkers that they can’t focus on what those markers imply in terms of the dynamic pathology and the altered protein turnover that underlies age-related disease, including Alzheimer’s disease. And we wonder why all the drug trials continue to fail. The executive who asked about amyloid levels is intelligent and experienced, but wedded to an outmoded model that has thus far shown no financial reward and – worse yet – no clinical validity. It doesn’t work. Yet this executive met with me as part of a group seeking innovative approaches to treating Alzheimer’s disease.

Their vision is that they are looking for innovation.

The reality is that they are still looking for the horse.

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.


March 21, 2017

The Frustration of (Not) Curing Alzheimer’s

I am deeply frustrated by two plangent observations: 1) we squander scant resources in useless AD trials and 2) AD can easily be cured if we applied those same resources to useful AD trials. Applying our resources with insight, we will cure Alzheimer’s within two years.

The first frustration is that most pharmaceutical firms and biotech companies continue to beat their heads against the same wall, regardless of clinical results. Whether they attack beta amyloid, tau proteins, mitocondrial function, inflammation, or any other target, the results have been, without exception, complete clinical failures. To be clear, many studies can show that you can affect beta amyloid or other biomarkers of Alzheimer’s disease, but none of these studies show any effect on the clinical outcome. In the case of amyloid, it doesn’t matter whether you target production or the plaques themselves. Despite hundreds of millions of dollars, despite tens of thousands of patients, not one of these trials has ever shown clinical efficacy. Yet these same companies continue to not only run into walls, but remained convinced that if they can only run faster and hit the wall faster, they will somehow successfully breach the wall. They succeed only in creating headaches, accompanied by lost money, lost opportunities, and lost patients. The problem is not a lack of intelligence or ability. The researchers are – almost without exception – some of the most intelligent, well-educated, technically trained, and hard-working people I know. The irony is that they are some of the best 20th century minds I know. The problem, however, is that it is no longer the 20th century. If you refuse to adapt, refuse to change your paradigm, refuse to come into the 21st century, you will continue to get 20th century results and patients will continue to die of Alzheimer’s disease. Money and intelligence continues to be dumped into the same clichéed paradigm of pathology, as we aim at the wrong targets and misunderstand how Alzheimer’s works. And the result is… tragedy.

The second frustration is that we already know the right target and we already understand how Alzheimer’s disease works. We are entirely able to cure and prevent Alzheimer’s disease now. At Telocyte, we already have the initial resources we need to move ahead, but it is surprising how difficult it is for some people — wedded to 20th century concepts — to grasp the stunning potential, both clinically and financially of what we are about to do at Telocyte. We can not only reverse Alzheimer’s disease, but we can also cut the costs of health care while creating a stunningly successful biotech company in the process. We have the right tools, the right people, the right partners, and the sheer ability to take this through FDA trials. Already, we have several lead investors committed to our success. We are asking for a handful of additional investors, those who can see what the 21st century is capable of and who can understand why Telocyte is both the best clinical investment and the best financial investment in innovative medical care.


January 9, 2017

Conceptual Blinders


A week or so ago, an AI beat the world’s reigning champion in the game of Go.

The odd thing is not that it happened, but how it was done. By itself, the victory would just be one more example of “computers beating humans”, but there is a far more interesting and important facet to this event. Not only did the AI beat the world’s Go masters and the reigning world champion, but it did it, not by being better at using the known strategies and tactics, long the province of Go adepts, but by using “unconventional positions“ and “moves that seemed foolish but inevitably led to victory” (WSJ, January 5, 2017). In short, the AI went into playing the game without conceptual blinders. It developed novel (and effective) strategies based on reality, rather than on preconceived views of how the game “ought” to be played. Had the AI been programmed by Go masters, it wouldn’t have fared as well. It succeeded because it lacked the limitations that we as human beings unknowingly use when we approach a problem.

go-game-boardIF our assumptions create limits, then our outcomes are limited.

The same problem – our own assumptions – proscribes the limits of what we can do in science and medicine. If we simply program a computer to “delay the onset of Alzheimer’s disease by lowering all known risk factors”, it might succeed, but the solution would be limited by how we set up the problem. In short, assumptions limit outcomes. If we merely restrict the program to lowering risks, then a computer program can’t show us how to cure Alzheimer’s. Such a program might, for example, recommend dietary changes, moving away from major highways and pollution, lowering blood pressure, avoiding infections, improving dental hygiene, lowering stress, and a myriad other changes that might delay Alzheimer’s. But the programs, the questions we pose, presuppose that Alzheimer’s can’t cured or prevented, only delayed. If we preclude finding a way to win, then all we find is a better way to lose.

Consider the historical analogs. If I want more efficient communication, I don’t ask a computer to design a better telegraph. If I want more efficient transportation, I don’t ask the computer to design a faster horse. If I want to cure polio, I don’t program a computer to design a better iron lung. And if I want to cure Alzheimer’s, I shouldn’t design a better way to attack amyloid, tau proteins, inflammation, or mitochondrial dysfunction. Merely because I’ve already assumed that those are the only strategies, I have limited my outcomes. If Alzheimer’s interventions are restricted to merely optimizing old strategies, we will never cure it.

Why be satisfied with a better telegraph, a faster horse, or a more efficient iron lung?

Programmed solutions, based on preconceived limits are a case of GIGO: “garbage in, garbage out”. True advances in science and medicine are not incremental; they demand innovative perceptions and constant reexamination of our premises. The example of an AI beating the world’s reigning Go champion wasn’t the result of incremental improvements in coding all of the Go strategies known to previous champions into a program and then tasking the program with implementing those accepted strategies. The AI was tasked with winning, regardless of previously accepted strategies. As a result, the AI actually WON, unexpectedly, but reliably, using innovative, startling, and unexpected approaches.

If we want to cure Alzheimer’s disease, we can’t use incremental approaches to time-worn (and uniformly ineffective) strategies. Like the AI playing Go, we need to stop focusing on accepted strategies and ask the fundamental question: how do we win? Not “how do we optimize the same old strategies?”, but how do we actually WIN? We shouldn’t rely on “programmed” approaches; we should toss out our preconceived programs, and ask how to win. With regard to Alzheimer’s disease, we need to stop asking how to optimize losing strategies and ask how to cure Alzheimer’s. Not “how do we lower amyloid levels?” or “how do we reduce tau tangles?”, but how do we cure and prevent the disease in the first place? If we really want to make a difference, then we need to free ourselves from our preconceptions and our old programming, and begin to ask the fundamental question: how can we cure Alzheimer’s?

Truly innovative approaches demand a ruthless reassessment of our assumptions.

We will cure Alzheimer’s only if we have the wit to truly use our own intelligence, with honesty, perceptiveness, and a willingness to examine reality.

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.


November 15, 2016

Close to a Cure

We are now within two years of a cure for Alzheimer’s disease.

What a brash and disruptive claim! What hubris! Yet events are coming together, underlining a new and far more complete understanding of the disease, illuminating the cause, supporting the ability to intervene, safely and effectively. We finally see a way to intervene in the basic pathology, underlining the potential to both prevent and cure Alzheimer’s disease.

But why has it taken so long? Why was Alzheimer’s disease first defined 110 years ago, and yet remains totally beyond our ability to intervene even now? Why have all other approaches, whether those of big pharma or those of biotech, failed utterly? Why has not a single clinical trial shown any ability to change the progress of this frightening disease? Why is Alzheimer’s disease not only called “the disease that steals human souls”, but also called the “graveyard of companies”? Why has every single approach (which has at most shown only an effect on biomarkers, such as beta amyloid), still failed to show any change in the cognitive decline in patients with this disease? Why have we failed universally, until now?

Because every approach has concentrated on effects, not on causes.

Currently, most approaches target beta amyloid, many target tau proteins, and some target mitochondrial function, inflammation, free radicals, and other processes, but no one targets these problems as a single, unified, overarching process. Alzheimer’s isn’t caused by any one of these disparate processes, but by a broader, more complex process that results in every one of these individual problems. Beta amyloid isn’t a cause, but a biomarker. Equally, tau proteins, phosphodiesterase levels, APOE4, presenilins, and a host of other markers are effects, not causes. The actual cause lies upstream and constitutes the root cause of the dozens of separate effects that are the futile downstream targets of every current FDA trial aimed at Alzheimer’s disease. Understanding this, we will be targeting the “upstream” problem, rather than the dozens of processes that others target individually and without success. Our animal studies support the ability to effectively intervene in human disease: when we say that we are about to cure Alzheimer’s disease, we base claim that on a clear and consistent theoretical model, supported by equally clear and consistent data.

Within the next few months, we will begin our FDA toxicity study, preparatory to obtaining an IND that will permit us to begin our FDA human trial. Our toxicity study will take 6 months and will meet FDA requirements for human safety data. Our first human trial is planned to begin one year from now and is intended to show not only safety, but a clear efficacy. We will include a dozen human volunteers, each with (not just early, but) moderate Alzheimer’s disease and our human trial will last 6 months, including a single treatment and multiple measurements of behavior, laboratory tests, and brain scans. We expect to show unambiguous cognitive improvement within that six-month period. We are confident that we cannot merely slow, not merely stop, but reverse much of the cognitive decline in our twelve patients. We intend to demonstrate an ability to cure Alzheimer’s disease clearly and credibly.

Curing Alzheimer’s requires investments of money, time, and thought. The toxicity study costs 1 million dollars; the human trial costs 2.5 million dollars. Telocyte has half a million dollars committed to this effort and at least one group of investors with a firm interest in taking us all the way through the human trials. We are close and we grow closer each day.

After 110 years, we are about to cure Alzheimer’s.

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