Michael Fossel Michael is President of Telocyte

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.

 

July 20, 2016

Curing Disease: More Insight Instead of Mere Effort

 

Curing disease correlates with insight, not blind effort.

There is an eternal trade-off between insight and effort. If we think carefully, understand the problem, and plan, then effort is minimized. If (as too often happens) we think carelessly, misunderstand the problem, and rely on hope instead of planning, then effort is not only maximized, but is usually a complete waste. Lacking insight, we foolishly flush both money and effort down the drain. In the case of clinical trials for Alzheimer’s disease – and in fact, all age-related diseases – this is precisely the case.

The major problem is a naïve complaisance that we already understand aging pathology.

If there was a single concept that is key to all of aging, it is the notion that everything in our organs, in our tissues, and in our cells is dynamically and actively in flux, rather than being a set of organs, tissues, cells, and molecules that statically and passively deteriorate. Aging isn’t just entropy; aging is entropy with insufficient biological response. Senescent cells no longer keep up with entropy, while young cells manage entropy quite handily. At the tissue level, the best example might be bone. We don’t form just bone and then leave it to the mercy of entropy, rather we continually recycle bony tissue throughout our lives – although more-and-more slowly as our osteocytes lose telomere length. This is equally true at the molecular level, for example the collagen and elastin molecules in our skin. We don’t finish forming collagen and elastin in our youth and then leave it to the vagaries of entropy, rather we continually recycle collagen and elastin molecules throughout our lives, although more-and-more slowly as our skin cells lose telomere length. Aging is not a process in which a fixed amount of bone, collagen, or elastin gradually erodes, denatures, or becomes damaged. Rather, aging is a process in which the rate of recycling of bone, collagen, or elastin gradually slows down as our shortening telomeres alter gene expression, slowing the rate of molecular turnover, and allowing damage to get ahead of the game. We don’t age because we are damaged, we age because cells with shortening telomeres no longer keep up with the damage.

The same is true not only of biological aging as a general process, but equally true of every age-related disease specifically. Vascular disease is not a disease in which our arteries are a static tissue that gradually gives way to an erosive entropy, but an active and dynamic set of cells that gradually slow their turnover of critical cellular components, culminating in the failure of endothelial cell function, the increasing pathology of the subendothelial layer, and the clinical outcomes of myocardial infarction, stroke, and a dozen other medical problems. Merely treating cholesterol, blood pressure, and hundreds of other specific pathological findings does nothing to reset the epigenetic changes that lie upstream and that cause those myriad changes. Small wonder that we fail to change the course of arterial disease if our only interventions are merely “stents and statins”.

Nor is Alzheimer’s a disease in which beta amyloid and tau proteins passively accumulate over time as they become denatured, resulting in neuronal death and cognitive failure. Alzheimer’s is a disease in which the turnover – the binding, the uptake, the degradation, and the replacement – of key molecules gradually slows down with telomere shortening, culminating in the failure of both glial cell and neuron function, the accumulation of plaques and tangles, and ending finally in a profound human tragedy. The cause is the change in gene expression, not the more obvious plaques and tangles.

Our lack of insight, even when we exert Herculean efforts – enormous clinical trials, immense amounts of funding, and years of work – is striking for a complete failure of every clinical trial aimed at Alzheimer’s disease. Naively, we target beta amyloid, tau proteins, phosphodiesterase, immune responses, and growth factors, without ever understanding the subtle upstream causes of these obvious downstream effects. Aging, aging diseases, and especially Alzheimer’s disease are not amenable to mere well-intended efforts. Without insight, our funding, our time, and our exertions are useless. Worse yet, that same funding time, and exertion could be used quite effectively, if used intelligently. If our target is to cure the diseases of aging, then we don’t need more effort, but more thought. However well intentioned, however much investment, however many grants, and however many clinical trials, all will be wasted unless we understand the aging process. Aging is not a passive accumulation of damage, but an active process in which damage accumulates because cells change their patterns of gene expression, patterns which can be reset.

Curing Alzheimer’s requires insight and intelligence, not naive hope and wasted effort.

 

 

May 12, 2016

Telomeres: Are They Worth Measuring?

It’s funny how often we make assumptions that are not only wrong, but that we are completely unaware of making. Having spent more than twenty years dealing with the clinical implications of cell aging, telomeres come to mind as an immediate example of this mistake.

Hardly a week goes by without another claim that some particular intervention alters telomere lengths in human patients. Without exception, they are measuring telomeres in peripheral white blood cells. It’s easy to get blood samples and measure telomeres in circulating white cells. Unfortunately, not only are these telomeres the ones that matter least, but (if you’re trying to prove the value of your intervention) they’re almost worthless.

Measuring telomeres in your blood to see how old you are is a bit like looking at your hat size to figure out how tall you are. Whether it’s your peripheral blood telomeres or your hat size, it’s still the wrong measurement for the job.

There are two problems with measuring telomeres in blood cells (even totally ignoring arguments about technical methods, unreliable laboratories, and the mean length versus the shortest lengths of those telomeres).

The first problem is that the blood cells aren’t the key cells when it comes to aging and age-related diseases. If you really want to know where you stand clinically, you should be measuring the telomeres in the endothelial cells lining your coronary arteries, the glial cells in your brain, the chondrocytes in your joints, or several other places more closely related to the most common (and fatal) aging diseases. Few of us are willing to have biopsies taken from our coronary arteries, our brain, or our joints, but just because we are a lot more relaxed about giving a blood sample doesn’t mean that the blood sample is worth getting. It barely reflects what’s going on in your white cells, let alone what is going to end up causing disease and death.

The second problem is a more subtle, but more important. It boils down to this: most of your white cells aren’t circulating in your blood and the ones that do circulate are changing and dividing all the time, making them a poor reflection of what’s happening to the stem cells in your marrow. I wrote an academic review article about this in 2012 and discussed it in The Telomerase Revolution, but let’s look at it here. Imagine you can instantly and accurately measure every telomere in the body, including those in the bone marrow and peripheral venous circulation. Oddly enough, you’d discover that the blood tests aren’t reliable indicators of what’s happening in the marrow.

Let’s say that you measure all of the telomeres at time A and again at time B. In between A and B, you use an intervention such as gene therapy, TA65, mediation, dietary change, or whatever you think might be effective. At time A, you find that the telomeres in the hematopoietic cells of the marrow are 12 kbp long. At the same time (due to stress, infection, poor diet, inflammation, and generally poor health habits) there is rapid peripheral turnover, cell division, and telomere loss in the peripheral blood. As a result, the mean telomere length in the blood sample is only 8 kbp.

We then intervene.

At time B, you find that the telomeres in the hematopoietic stem cells in the marrow are now only 11 kbp long (showing that the patient has gotten older). Also at time B, since we might now have lowered stress, removed infections, decreased inflammation, and generally made the patient “healthier” with whatever intervention we may have chosen, their peripheral cells are now turning over more slowly, dividing less frequently, and losing less telomere lengths once they leave the marrow and enter peripheral circulation, so that the mean telomere length in the peripheral blood sample is now 9 kbp.

We could claim (as many articles do) that our clinical intervention “lengthened the peripheral telomeres!” The truth is that our intervention didn’t lengthen anything and we’re deluding ourselves (and whoever believes our claims). The peripheral telomeres that we sample at time B might be longer than the ones we sampled at time A, but the telomeres of the cells back in the marrow now have shorter telomeres. Our intervention may well have made the patient healthier and we might actually have slowed down the rate of telomere loss, but we definitely didn’t lengthen any telomeres, no matter how proudly we pat ourselves on the back.

Peripheral leukocytes are routinely used to assess telomere lengths (which is fine as far as it goes) and then used to assess clinical interventions, which is overreaching. If we do serial measures of peripheral telomeres every few months for a few years, then the validity will increase somewhat, but peripheral telomere measurements (no matter how often you measure them) are intrinsically an unreliable and invalid biomarker for what we really want to assess, which is “whole body telomere changes” or at least “marrow telomere changes” (in the case of blood cells).

Most of the available literature which suggests that we can slow or reverse telomere losses is – if it’s based on peripheral blood samples – misleading at best and unethical at worst.

January 20, 2016

Long Past Time

History provides perspective, probably because we keep repeating it.

Several hundred years ago, smallpox was the scourge of Europe. Treatment, such as it was, consisted of compassion, fluids, and a gamut of various herbs, bark, roots, and fungal preparations, none of which changed the mortality. The diligent healer of the late middle ages tried hard to find just the right plant preparation that would prevent or cure smallpox. By the late 1700’s there had been multiple cases of successful use of cowpox to vaccinate (from the Latin vacca for cow) people, with good results, culminating in Edward Jenner’s publication in 1798. Mind you, like many human discoveries, the process had actually been around a long time, if not particularly well known, well understood, or even believed.

Regardless of its provenance, regardless of its success, the major problem facing those who used vaccination to prevent smallpox was not technology, but common preconceptions. The idea of using an active biological agent – the cowpox virus – flew in the face of the common certainties about how to treat disease. Everyone “knew” that treatment lay in finding just the right plant, whether a root or a bark. Herbalists knew that if they worked hard and put enough resources into finding that perfect mixture of plant compounds, they could cure smallpox. The fact that they were looking in the wrong place, didn’t seem to occur to them.

Back to the future and listen to the echo of history.

We now know that we can reset gene expression in the microglia that play the key role in driving the pathology of Alzheimer’s disease. The data has been accumulating for 20 years, as have the numerous articles in the medical literature and the books and textbooks on this field. And yet, regardless of its provenance, regardless of its success, the major problem facing those who work to prevent and cure Alzheimer’s disease is not technology, but common preconceptions. The idea of using an active biological agent – like the human telomerase gene – flies in the fact of common certainties about how to cure Alzheimer’s. Everyone “knows” that treatment lies in finding just the right drug, whether monoclonal antibody or small molecule. Pharmacology companies know that if they work hard enough and put enough resources into finding that perfect set of molecules, they could cure Alzheimer’s. And once again, the fact that they are looking in the wrong place, doesn’t seem to occur to them.

The echo is hauntingly familiar. Once again, the advance of medicine lay (and will lay) not in finding the right herb (or the right antibody), but in finding a sophisticated and accurate understanding of the disease we are trying to treat. Just as nothing worked in the 18th century until we understood vaccination as a way of preventing smallpox and other viral diseases, so nothing will work in the 21st century until we understand resetting gene expression as a way of preventing and curing Alzheimer’s disease.

It’s time to start looking in the right place.

And it’s long past time to cure Alzheimer’s disease.

October 30, 2015

Chaos, traffic, and Alzheimer’s disease

We’re going to take an odd detour into both chaos theory and traffic flow in order to understand Alzheimer’s disease, so fasten your seatbelt. The key cascade of pathology that we’re going to look at (and explain) is the presence of beta amyloid plaques in patients with Alzheimer’s, but the principle applies equally to tau tangles and several other hallmarks of pathology seen in aging human patients with cognitive decline. Chaos theory and traffic flow will serve as useful analogies and help clarify the dynamics involved in human pathology, as well as potential cures.

To start with, let’s consider a simple example of chaos theory, in which a continual, linear event results in a sudden inflection and an unexpected, non-linear outcome. Imagine that you are trying to retrieve your iPhone in the middle of the night in order to listen to, for example, an audible book. The lights are out, your spouse is asleep and you gently pull on the earphones, using them to pull the iPhone toward you. Realizing that the slower you pull it, the less noise you make (and the less likely it is that you will waken your spouse), you provide a very slow, gentle traction. Unfortunately, the iPhone is on the bedside table and once it gets to the edge, it suddenly falls and produces a terrible racket, regardless of how slowly and quietly you’ve pulled it up until you reached the edge. The point here is that regardless of how noise and speed were related until you got to the edge of the table, there will come a sudden inflection point with an unexpected and non-linear increase in noise. In short, the amount of noise correlates linearly with speed until the inflection occurs and then the relationship between speed and noise becomes suddenly non-linear. As we will see, much the same thing happens to the clearance of beta amyloid (or tau tangles) and its relationship to neuronal death. Things seem to be going fine until some inflection point is reached, after which there is a sudden, unexpected inflection and the pathology (and cognitive decline) begins.

For the next analogy, consider traffic flow and construction slowdowns. Commuting to work each day, you (and the traffic generally) are moving along at a steady 55 mph as you approach an area of construction. In this area, the traffic slows to a speed averaging 10 mph, as a result of a traffic light at which the speed is 20 mph half the time (green light) and zero half the time (red light). However, you notice that despite this construction slowdown (which has been going on for several weeks), the traffic congestion always becomes noticeable at about the same spot and it never actually backs up indefinitely (as it might if the road was completely closed while traffic continued to arrive). As you think about it, you realize that the actual speed (55 mph versus 10 mph) isn’t the key here. The key question is the number of cars passing per unit time as they approach and as they go through the congested area. If the 55 mph cars are approaching at a rate of (say) 30 cars per minute (with a good distance between them) and the 10 mph cars are getting through the construction and the traffic light at the exact same rate of 30 cars per minute (although they are almost bumper-to-bumper), then the line of slow moving cars will only grow to a certain length before it achieves an equilibrium. We might find, for example, that despite the traffic congestion and as long as the number of cars passing each point per unit time remains equal (e.g., 30 cars per minute, regardless of how close the cars are to one another), then the line will only grow so far and no further.

But this is only true to a point.

It might be, for example, that (as long as the number of cars per minute is equal both coming into and leaving the traffic congestion) the line will be a half-mile long if the construction zone has an average speed of 15 miles an hour twice as long at 10 miles an hour, but there comes a point – perhaps at 9 miles per hour, when the line suddenly has an inflection point and begins to grow wildly (and non-linearly) because the number of cars leaving per minute has no fallen below the number of cars arriving per minute. The relationship between speed (going through construction) and the length of the traffic line was linear until some critical point, at which the relationship took an inflection, the traffic backs up, and all hell breaks loose. Not merely an example of chaos theory, but chaos in action as traffic gridlock ensues.

Much the same is occurring in the brain as it ages. Microglial cells are perfectly adept at clearing beta amyloid as it is produced. Even as these cells senesce and their rate of clearance falls, the backup of beta amyloid “traffic” is not bad enough to cause pathology and it does not trigger neuronal death – or clinical Alzheimer’s disease. There comes a point, however, when chaos theory enters the picture, a sudden inflection occurs, neuronal death ensues, and inexorable cognitive decline becomes obvious.

Think of it this way. The key questions (with beta amyloid as an example) are these: 1) how fast is beta amyloid being produced (how many cars are coming down the highway per minute), 2) how likely are the beta amyloid molecules to be abnormal perhaps because of APOE4 genes (how fast are the cars moving), and 3) how well are the senescing microglia able to clear the beta amyloid molecules (how many cars can they get through the construction area per minute)?

These same questions play a role in understanding why current interventions (e.g., monoclonal antibodies) fail and why we might want to intervene directly in cell senescence. Most current experimental approaches, such a monoclonal antibodies, only serve to “tow away some of the backed-up cars in the traffic line”, while the critical variable is our ability to move cars through the area of congestion. In short, the problem is not a static one (can we remove cars), but a dynamic one (can we keep the cars moving). Once we get a problem with traffic flow (a non-linear accumulation of beta amyloid plaques), the key intervention is not “towing away cars”, but increasing the flow of traffic through the congested area. We should be treating microglia, not beta amyloid.

Curing Alzheimer’s requires that we understand the pathology and not in a naïve, static fashion. If we want to cure Alzheimer’s, we need to improve the traffic, not the cars. The most effective point of intervention is not beta-amyloid but microglia.

Which is how we plan to cure Alzheimer’s.

August 25, 2015

Alzheimer’s: One Disease?

Most of us have wondered about what causes Alzheimer’s. As commonly happens, we stumble badly when we make assumptions, even in asking questions, let alone in trying to answer those questions. The question “what causes Alzheimer’s?” presupposes that there is a single such disease (Alzheimer’s) and that we can define it well enough to ask about “its” cause. Neither of these is probably an accurate assumption. The reality is that there is considerable difficulty in agreeing on the “hallmarks” (the pathognomonic characteristics that define AD) and the “boundaries” between AD and other somewhat similar diseases on the differential diagnosis. Comparing Alzheimer’s to many other age-related neurological diseases can be humbling – and it should be. Small wonder we have so much trouble understanding the cause, let alone finding a cure when we don’t really know what we’re looking at.

Rather than just reinforce our preconceptions, let’s look at reality a bit more closely.

One of the things that has become clearer over the past century – and especially so over the past two decades – is that there is a remarkable amount of overlap in the pathology found in what we have thought of as different age-related neurological problems. This has become grudgingly accepted as we compare not only Alzheimer’s and Parkinson’s disease, but a host of other clinical problems, such as microvascular infarcts, vascular dementia, frontotemporal dementia, hippocampal sclerosis, Huntington’s disease, amyotrophic lateral sclerosis, dementia with Lewy bodies, and mixed dementia (a term that sort of sums up the problem we’re discussing). Just to restrict ourselves to the two classic diseases – AD versus PD – Alzheimer’s tends to have primarily cognitive rather than motor problems, whereas Parkinson’s tends to have primarily motor rather than cognitive problems. In reality, however, both Alzheimer’s and Parkinson’s patients tend to have some of both, particularly as their diseases progress. At the histological level, we tend to distinguish the locations of each disease, and at the neurochemical level we likewise make distinctions, yet there still remains overlap at almost any level, once we look more carefully.

Perhaps there is a single, common, underlying causative pathology that results in BOTH of these diseases. Could both AD and PD be two different manifestations of a shared problem?

This same question surfaces when we look carefully at the vascular dementias: they overlap in many ways with the classical “non-vascular” etiologies. Again: could all of these have a common underlying factor with disparate clinical presentations? We see the same problem when we look at age-related neurological dysfunction in animal models, such as laboratory-created Alzheimer’s models in mice, as well as the “normal” decline in any wild species (such as mice or rats). We go to a lot of trouble to introduce human genes into laboratory species in order to produce a “mouse model of Alzheimer’s”, yet these animals show behavioral declines even in the wild and when we introduce human genes, it’s certainly not clear that we end up with a mouse model that teaches us anything useful when we want to find a cure.

We could put all of these clinical changes together by positing that they derive from a common cellular problem, that of cell senescence. Different patients have different genes and different patterns of gene expression, so their disease expressions differ, some having AD, some having PD, some having any number of other disease phenotypes. Different animals (humans versus mice, for example) likewise have differing genetic and epigenetic settings, so their disease expressions also differ, humans showing beta amyloid and tau protein changes, mice showing a different pattern, but all showing behavioral and cognitive decline over time, whatever the individual pathway the pathology uses to express itself.

Consider our diagram of the “Common Pathological Pathways in Age-Related CNS Failure” (see figure A). The proposition illustrated in this diagram is that of a single underlying problem, with multiple possible pathways, and a shared outcome: age-related CNS failure. One cause, multiple pathways (often defined as different diseases), but one outcome. Whatever the pathway chosen, the outcome is an increasing neurological dysfunction with age.

 

Figure A08-25-15 Figure A

In the case of particular diseases (or particular species), the clinical phenotype depends on which cells are senescing fastest (e.g., glial cells in the brain, endothelial cells in the arterial tree, etc.) and which protein products (e.g., beta amyloid, tau protein, alpha synuclein, etc.) are most likely to cause problems first, depending upon the genetic landscape and the epigenetics of the individual patient or the individual species. If we now label the common diagram with specific diseases and species, we get something like the second diagram (see figure B).

 

Figure B08-25-15 Figure B

If we really want to understand, and cure, Alzheimer’s, then we need to start by understanding (and curing) our own preconceptions. It is only when we look at not only the clinical data, but a wide panoply of species that we can truly understand any of the diseases that we see day-to-day.

One cause, multiple pathways, and a single shared outcome: CNS failure.

Curing Alzheimer’s becomes – as it has been for a century – a fool’s errand if all we target are the specific genes and proteins that we (naively) think of as the hallmarks of the disease. If we truly want cure Alzheimer’s, then it’s time we understand the disease and it’s high time we target the actual causes of not only Alzheimer’s disease, but the entire spectrum of age-related neurological diseases that should be labelled under a common rubric, diseases of cell senescence.

It’s time we understand Alzheimer’s and time we cure it.

July 15, 2015

How Does Alzheimer’s Work?

 

Alzheimer’s disease steals our souls.

We lose our humanity when it destroys the neurons that make up a critical part of our brains, but why those neurons die has always remained a mystery since “senility” was first noted, thousands of years ago. Even in the past century, since it was first described clinically by Dr. Alois Alzheimer in a 1907 medical article, we not only haven’t cured the disease, we haven’t even understood it. In this blog, we will come to understand exactly how it works — and what can be done to cure it.

Part of the reason we are slow to understand diseases (and many other things, for that matter) is the tendency to engage in magical thinking. We identify an association, mistake it for a causation, and then we are mystified when our naïve interventions fail. This error may seem obvious, but we make this same mistake repeatedly in medicine and in other aspects of daily life. In the case of Alzheimer’s diseases, we repeatedly identify a protein, a gene, or another product, and we naively try to intervene, then are left clueless and shocked when our best efforts fail utterly. The classic case has been that of beta amyloid plaques, common in most cases of Alzheimer’s disease, when we try to remove or prevent their formation and then cannot understand why all of our interventions fail so spectacularly. There have been hundreds of human trials aimed at beta amyloid, for example, yet none of them have proven effective. Why not?

Alzheimers disease cascade

The reason lies in magical thinking: knowing that some diseases (such as Sickle Cell) are clearly a genetic disease, and knowing that there are genetic correlations with Alzheimer’s disease, we conclude that Alzheimer’s is also a “genetic disease” and that if we could only find just the right gene, we would know how to cure the disease. Unfortunately, Alzheimer’s isn’t a genetic disease. Despite all of the candidate proteins, genes, and gene locations we are still investigating, these are correlations, not the cause of the pathology. Whether we look at beta amyloid (and its precursor protein in several variant forms), presenilin, APOE4, R4YH, UNC5C, SORL1, CLU, CR1, PICALM, TREM2, A2M, GST01 & 02, BAB2, CALHM1, TOMM40, CD33, ADAM10, PLD3, or any of the dozens of other candidates (the list grows longer by the day), none of these “cause” Alzheimer’s disease.

Alzheimer’s is not a genetic disease, Alzheimer’s is an epigenetic disease. All of those genes (I just saw another one published this morning) contribute to the risk, yet none of them — not a single one of the identified genes — causes Alzheimer’s. To quote a previous blog, each of them is a tree, but Alzheimer’s is a forest. When we focus on trees, we forget the broader pathology of the forest.

To use another common analogy, each of the genes identified with Alzheimer’s is like a submerged rock. As we age, the problem is not the hidden genetic rocks — such as APOE4 — but the fact that the water level is gradually falling, until the hidden rocks become exposed and cause a medical shipwreck. Treating APO-E4 will not resolve the problem. Alzheimer’s is not caused by the amyloid protein itself, which is necessary to neuronal function when present in appropriate amounts, but to the failure of amyloid clearance by aging microglia. The aging microglia becomes less and less capable of recycling and maintaining appropriate levels of not only beta amyloid, but a number of other things a well. This becomes apparent earlier in those with an APOE4 gene, but the problem is ubiquitous and not restricted to a single gene product. APOE4 wouldn’t be a problem is the microglial function was up to snuff, as it is in young adults. As the microglia age, as the water level falls, we expose the hidden rocks — the barely sufficient turnover of amyloid proteins in the case of those with two APOE4 alleles. To extend the water analogy, consider the two most well-known of those hidden rocks: APO-E4 and APO-E2. The first (the more dangerous allele) is a rock that lies just a few feet under the water, while the second (the safer allele) is a rock that lies a bit deeper down in the water. Neither of these hidden rocks are a problem when the lake water level is high (i.e., when we are young and our microglial clearance of amyloid is high). However, as the water level falls (i.e., as we age and microglial clearance begins to fall due to epigenetic shifts induced by telomere shortening), we expose first the APO-E4 rock (particularly in those with two copies of the APOE4 gene) and then, much later in life, the APO-E2 rock (in those who are lucky enough to have two copies of the APOE2 gene). Nor are these the only hidden genetic rocks. The rocks include not only the long list of “Alzheimer’s genes” given above, but literally hundreds of other risk factors, factors that become increasingly exposed as our microglia age and fail to protect us. As we age, as the water level falls, we expose risk-after-risk, rock-after-rock, gene-after-gene until we run aground and our minds go down for good.

The solution is not to find each and every genetic rock and hope to prevent disaster by filing down the rocks one-by-one, but to simply raise the water level again. Once we reset gene expression — not only theoretically, but based on animal trials — the pathology resolves. When we go after the key causal element in the pathology, when we reset gene expression in the microglial cells, the neurons are no longer at risk. If we want to cure Alzheimer’s, we need to aim at the cause of the disease, not at the genes, not at the proteins, not at the tangles, not at the microaggregates, and not at the plaques. To date, not one of these approaches has been effective.

Alzheimer’s doesn’t begin in the neurons; Alzheimer’s begins in the microglia. The key to curing Alzheimer’s is not to identify genes, but to reset gene expression and the key to resetting gene expression is to use telomerase therapy.

May 12, 2015

The Telomerase Revolution

My new book, The Telomerase Revolution, is now finished and is being copy edited by the publisher. Oddly enough, it’s already selling well in preorders. Amazon.com says that it is now the “#1 release in medical research”, which is a delightful surprise, since it won’t actually be published and available to the public until October. For those of you who would like to order a copy, here is the link to Amazon.com:

  • http://www.amazon.com/Telomerase-Revolution-Enzyme-Aging%C2%85-Healthier/dp/194163169X/ref=sr_1_1?ie=UTF8&qid=1426777801&sr=8-1&keywords=telomerase+revolution

The book is a careful and clear discussion of how aging works in cells, how it causes the clinical diseases of aging, and what we can do to cure age-related disease. There is a good clear chapter on vascular aging and neurodegenerative disease — especially Alzheimer’s disease — that a lot of reviewers find especially intriguing. Len Hayflick, the researcher who first described cell aging more than fifty years ago, calls the chapter “superb”. Matt Ridley, author of several best sellers including The Rational Optimist, Genome, and The Red Queen, says that he read the chapter with “real fascination” and tells me “I badly want to read more of the book”.

If anyone would like to do a book review, please contact me, and I will arrange to send you a review copy.

May 6, 2015

Lymphocyte telomeres are not a good disease marker

A friend pointed out that a recent Danish study suggested that short telomere lengths in circulating peripheral lymphocytes account for about a quarter of the variance in mortality. Does this mean that lymphocyte telomere lengths (LTL’s) are really only a minor factor in age-related disease and mortality? Probably, but it’s not the important question. A better question is whether or not telomere shortening accounts for age-related disease and mortality, which it does.

In regard to the Danish study, I would expect that result. People seldom die directly as a result of immune senescence and to the extent that they DO die of immune senescence, the figure of 25% of the variance strikes me as about right. Most people die of vascular aging and there is no a priori reason) to believe (nor data to suggest) that the telomere lengths of the vascular endothelium have any direct relationship to the telomere lengths of circulating lymphocytes. People may have short endothelial telomeres in their coronary arteries and advanced vascular aging, without necessarily having short lymphocyte telomeres that show up when we look at the circulating blood cells. Endothelial cells (which cause vascular aging) are not the same as lymphocytes (which are involved in immune aging). Within any one patient, we would expect some correlation between the rate of telomere loss in one type of cell (endothelial cells) and the rate of telomere loss in a different type of cell (lymphocytes), but the correlation will not be high and will certainly not be causal. It’s disappointing to see large (and expensive) clinical studies that try to chase down lymphocyte telomere lengths and expect them to predict overall disease. Lymphocyte telomere lengths will be related to some diseases (cancer comes to mind, and the data supports this relationship) but not to other diseases. For those of you who would like to know more, read my biomarker paper for a partial discussion of this illogical thinking (Fossel, 2012). Whatever were they thinking (or NOT thinking)?

If we want to accurate predict (I’d rather cure) the risk of age-related diseases and death, we would need to acquire reliable measures of changing telomere lengths in, for example, the vascular endothelium and microglial    cells, as well as other cells and tissues. I’m sure that the circulating lymphocytes account for some of the variance in mortality, but not only can’t we restrict ourselves to lymphocytes, but there remain the (totally ignored) issue of circulating vs other, non-circulating lymphocyte reserves. Even if we can prove that lymphocyte telomere lengths (LTL’s) rise with a prolonged intervention (for example, using dietary change, telomerase activators, exercise, or other potential interventions), a peripheral increase in telomere lengths may still mask a decline in actual decline in overall telomere lengths as newer lymphocytes enter the circulation from the marrow and other repositories. The cells haven’t “become younger”, rather we are merely sampling a different set of cells.

My usual analogy applies here. If I were to sample the ages of the residents living in a single city block and find that over a twenty year period the mean age of the residents goes from 70 to 30 years old, that does NOT mean that we have made those residents any younger, only that the older residents have moved (or died) and that a totally different population of younger residents has replaced them. In fact the overall population of the city (or the country) may have undergone an increase in mean age, even if the particular city block that I measure shows a decrease in the mean age of its residents.

In a parallel fashion, when we measure circulating LTL’s, we are only measuring a single sample of circulating lymphocytes, not an entire population of the body’s lymphocytes. So even if I could prove a clinical intervention appeared to result in all of the circulating LTL’s getting longer, that doesn’t prove anything about the mean telomere lengths in the body as a whole. We certainly can’t claim that we have improved the immune function or “reversed aging” in lymphocytes. Such conclusions are not only invalid, they are naïve to the point of embarrassment.

If we really want to show that telomerase therapy can lower mortality or cure age-related disease, then we need to look at mortality and disease, not lymphocytes.

 

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