Michael Fossel Michael is President of Telocyte

July 5, 2016

Dynamic versus Static – Going to Mars or Curing AD

Innovation requires novel thinking, not incremental actions.

We can cure age-related diseases – such as Alzheimer’s – not with funding, intelligence, or effort alone, but only if we reassess our assumptions. Until we look carefully at our conceptual foundations, we cannot expect to build a therapeutic structure. Ironically, the key problem lies in our looking at biology, medicine, and disease as static, passive processes. One would think we would see these processes as active and dynamic, but oddly enough, we don’t.

Consider an analogy: going to visit Mars.

Clearly, we need some essentials of life-support, such as oxygen and water. If we start by asking ourselves how much of each we need per day per person, then how many days and how many persons, we end up with an enormous need for both: huge amounts of oxygen, huge amounts of water. After all, we don’t want to run out of oxygen or water, do we?

Remember, however, that in a closed system (such as a vehicle going to Mars), that neither oxygen nor water are actually used up en route, only changed from one form (such as oxygen molecules) to another (such as carbon dioxide molecules). The water molecules may be in the form of body waste, but they are still present in the vehicle. And both oxygen and water – given energy and technical forethought – can be recycled and reused indefinitely. The practical question is not simply “how much oxygen and water do we need”, but “how efficiently and quickly can we recycle oxygen and water?” In short, the key question isn’t the static and passive one of “how fast are we using up our oxygen and water?”. The key question is the active and dynamic one of “how does the rate of recycling compare to the rate of oxygen and water use?”

The analogy is exact.

In the case of Alzheimer’s, for example, the key question isn’t “how can we prevent the accumulation of beta amyloid and tau protein?”, but rather “how can we increase the rate of recycling of molecules such as beta amyloid and tau proteins?” The former question would be like asking “how can we prevent the use of oxygen and water?”, while we should be asking “how can we increase the recycling efficiency of oxygen and water?”

Current approaches to treating Alzheimer’s disease focus inordinate funding, intelligence, and effort on the wrong question. Small wonder they fail.

April 12, 2016

Rational Behavior

We waste stunning amounts of money and effort on comprehensively ineffective trials.

As a recent article points out, in the past 15 years, there have been 123 Alzheimer drug failures and, while four medicines have been approved, none of them affect the progress of the disease. Symptomatic therapy at best, we have no medications – none – that have any effect on the disease or on its mortality. A quick look at clinicaltrials.gov lists almost 1,500 interventional trials aimed at treating Alzheimer’s disease, yet once again there is no evidence that any of these trials has resulted (or will result) in an intervention that changes the outcome of Alzheimer’s disease.

Federal funding for Alzheimer’s is estimated at almost half a billion dollars and some have estimated that Eli Lilly’s potential treatment for Alzheimer’s, solanezumab, may end up costing the company one billion dollars to achieve approval of that drug alone, even though there is no evidence that it actually prevents or cures the disease. The most optimistic interpretation of the statistical data of thousands of patients over many years, would be stretching it to suggest it might possibly delay cognitive decline and death by 2-3 months over an eight year period from diagnosis to death. Even that wishful thought is doubtful and scarcely any consolation to those enduring an extra handful of weeks in a skilled care nursing home (or having to pay for it).

No matter what the current target of choice – beta amyloid, tau proteins, inflammation, or any other target-du-jour – none of these targets have ever been shown to offer a glimmer of hope. Despite the history of repeated and consistent failure, we continue to spend (and vote to spend) money on these same drug targets. We eagerly bash our empty heads against the same solid brick wall, naively hoping that one day we fill find that the wall will be made of air (like the air in our brains, which leads to our irrational behavior). The apocryphal observation pertains: the definition of insanity is doing the same thing over and over and expecting a different result. We waste money and effort on ineffective and expensive trials aimed at targets that we know are futile.

The irony – and the tragedy – is that we can both prevent and cure Alzheimer’s disease, both effectively and inexpensively if we understand the actual pathology and target the underlying causes. We could do, effectively and inexpensively, what big pharma has failed to do ineffectively and expensively. What big pharma can’t do for one billion dollars, Telocyte can do for 0.5% of that figure, simply by aiming at the right target.

We need rationality, insight, and just enough funding to prove it can be done.

February 16, 2016

Unexamined Assumptions

The problem with curing Alzheimer’s is, as with so much of our understanding of aging and age-related diseases, that we make unexamined assumptions. Let me admit that many of our unexamined assumptions are either useful or reasonable. I assume that the sun will come up again tomorrow morning and that’s a useful and reasonable assumption. Useful, in that it allows me to plan my future, reasonable in that the sun has been coming up every morning for quite a while and is therefore likely to do so tomorrow as well. Certain unexamined assumptions are equally justifiable in dealing with Alzheimer’s disease. In the strictly poetic sense, Alzheimer’s certainly is the disease that “steals our souls”, yet no physician or researcher would actually make the assumption that the mind is some vague ethereal quantity that can be stolen by demons, let alone go on to promulgate a theory of Alzheimer’s pathology based on this assumption.

Yet we make exactly that same error, using an unexamined assumption, when we blithely assume that aging is simply the accumulation of damage and, pari passu, that Alzheimer’s disease is simply the accumulation of damaged molecules, be they amyloid, tau tangles, or altered mitochondrial enzymes. This unexamined assumption lies behind almost innumerable multi-million dollar FDA trials, academic papers, and clinical interventions. We assume, without even realizing we have made the assumption, that Alzheimer’s is merely the accumulation of damaged molecules.

We make the same unexamined assumption in looking at other age-related diseases and in the broader field of aging itself. We delve into the details of advanced glycation end-products (AGE), lipofuscin, cross-linking, and other molecular pools showing “accumulative damage”, all the time never realizing that we are making the same fallacy. We are working with completely unexamined (and erroneous) assumptions about how aging works. We naively assume that aging occurs – and age-related diseases follow – merely because things “rust” over time. We age because “molecules fall apart.”

 

Yet the data and logic both say differently. Let me give you a useful analogy: the cell phone. Consider a large pool (several thousand) of people who own cell phones. We know that if we examine any SINGLE cell phone, the best predictor of failure is how long it has been since production. If, however, we want to predict the percentage of failures in any large pool of owners, the best predictor is not time-since-production, but length-of-contract, that is, how often does it get turned over and replaced? Imagine two large pools of cell phone owners. In group A, the cell phones are replaced annually, with a failure rate (at equilibrium) of approximately 1%. In group B, the cell phones are replaced every ten years, with a failure rate (at equilibrium) of approximately 80%. In both groups, the rate of failure of any individual phone is the same. Furthermore, the rate of failure is only marginally related to the “genes”, i.e., whether the phone is an Apple iPhone, an Android, or some other type (a different “allele”). As the turnover rate (contract length to replacement) lengthens, the percent of failed cell phones climbs dramatically, regardless of the failure rate of any individual cell phone. In a pool of cell phones, “aging” is not a matter of passively accumulated damage, but of how actively we replace them.

The same is occurring in molecular pools in biological systems. The key predictor of “denatured” or dysfunctional molecules (e.g., AGE, beta amyloid microaggregates, cross-linking, elastin failure, collagen stiffening, etc) is not the rate of damage but the rate of turnover. In the case of cell aging, when we reset gene expression (reset telomere length) we reset the turnover rates (anabolism and catabolism rates) of all molecular pools to those typical of “young” cells. The outcome is that molecule pool turnover is more than sufficient to deal with typical rates of damage.

Without realizing it, most of us make the mistake of thinking of molecular pools as static and damage as purely accumulative. The reality is that such pools are dynamic and the key dependent variable (as with cell phones) is not the passive rate of damage, but the active rate of turnover.

Unless we understand – and examine – our assumptions, we can never expect to cure age-related diseases. Once we start down the wrong path, all the logic and data in the world can’t make up for the fact that we are looking in the wrong place. It’s time we stopped blaming “demons” and starting thinking carefully.

December 7, 2015

21st Century Science: Isn’t It About Time?

The other day I was asked about the role of denaturation of a particular protein in aging. It was a typical question that pretty much sums up the problem we have had in understanding (and doing anything about) aging during the past century. The problem is the question hides a flawed premise. It presupposes that molecules simply sit around and accrue damage. Put another way, the problem is that we look at molecules as part of as static pool rather than looking at the dynamic turnover that is the hallmark of metabolism.

Imagine a 1930 Duesenberg that has been lovingly cared for and is in pristine condition, even though it rolled off the assembly line 85 years ago. Compare this to my two-year-old car that already has a few rust spots. Was the Duesenberg better made than my car, that is, did it come with “better genes”? Was the Duesenberg exposed to less damage than my car, that is, did it have “fewer free radicals, less denaturing of its proteins, or a smaller rate of cross-linking”? No. The difference between that “ageless” Duesenberg and my own “aging” car is not the quality of the production line nor the exposure to sun, snow, salt, and dirt. The difference lies exclusively in the dynamics of its care. That Duesenberg was polished, aligned, oiled, repainted, repaired, and “recycled” on a regular basis. My own car is “aging faster” because I don’t care for it as frequently or as carefully as did the owners of that Duesenberg, and therein lies the entire difference between young organisms and old ones.

In aging organisms, it’s neither the genes nor the damage, but the slowing rate of recycling and repair that results in old cells, old tissues, old organisms, and age-related diseases.

Bizarrely and ironically, most people still look at biological systems and ignore the fact that they are alive, that they are dynamic, that they are constantly in flux. We look at a particular molecule – whether beta amyloid, collagen, GDF-11, or a thousand others – and we ignore the fact that these molecules are constantly being created, broken down, and replaced, but instead, we blindly focus on the damage itself. It’s true that as an organism ages any given pool of molecules shows an increase in damage – such as the aggregates of beta amyloid in early plaque formation – but the key is not the damage, the key is the slowing of the metabolic turnover. An accumulation of damage is not static and passively accumulative; it occurs because the rate of turnover falls as a result of changes in the pattern of gene expression. Whether we look at tau proteins, elastin, or any other molecular pool you want to look at, the key to the problem lies not in any particular gene nor in any particular source of damage. The key lies in the rate at which both anabolism and catabolism are replacing those molecules.

We don’t age because we accumulate damage, we accumulate damage because aging permits damage to accumulate.

A doctrinaire attention to “aging genes” and a catalog of one’s favorite sources of molecular damage will never result in cures to age-related disease. The key to intervention lies in the rate of molecular turnover, which responds to changing patterns of gene expression. Those who focus on genes and damage, to the exclusion of molecular turnover and gene expression, are perhaps some of our most highly-educated and intelligent minds of the 20th century…

…but it’s now the 21st century.

It’s time we caught up.

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.

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