The State of Disease

Medicine sees autoimmunity as the immune system gone rogue. Why is this person's immune system attacking their own body? The research focuses on understanding the mechanisms of attack: which tissues are targeted, which inflammatory pathways are activated, what's different about these attacking immune cells. And the treatment follows this research, attempting to turn the immune response off in targeted ways so it stops attacking the body.

But every healthy body has cells that attack its own cells, called autoreactive immune cells, which serve useful purposes like clearing damaged cells and debris. Which means that what's happening in autoimmunity is similar to what we saw in cancer, in that it's a normal cellular process running without its normal controls. In healthy people this process is kept in check by regulatory T cells (Tregs) that suppress them before they can cause damage in healthy tissue. But in autoimmunity, a few things happen simultaneously: Treg production drops meaning there are fewer overall Tregs, and the remaining Tregs function less efficiently, meaning they are less able to regulate the way they’re meant to. And there is something called IL-2, which feeds both Tregs and autoreactive immune cells, which are the ones that always exist to attack your own tissue. And when Tregs are diminished, there's more IL-2 to go around and so the autoreactive cells get a lot more of it, which effectively ramps them up. You end up with a situation that's kind of like removing the police while simultaneously arming everyone in a crowd. The autoreactive cells that are normally suppressed can now attack freely and have more fuel to do so. Which means the question medicine should be asking is: why does the monitoring fail like we saw in cancer?

So this is what’s happening in autoimmune diseases, and medicine is genuinely mystified why autoimmune diseases cluster together. About 25% of people with one autoimmune condition develop at least one more - and for some conditions, the risk of developing a second is 4 to 10+ times higher than the general population. But when you understand what we just laid out, that autoimmune disease comes from systemic monitoring failure plus autoreactive activation, of course you'd see multiple autoimmune conditions develop. If your entire immune monitoring system is compromised while autoreactive cells are ramped up throughout your body, why would it only affect one tissue type? Or occur in one isolated spot in the body? Ibuprofen doesn’t just target inflammation in your hand, or your gut, it’s system wide because that's how the body works. The mystery isn't why they cluster - it's why medicine expected them not to.

Medicine has identified between 80 and 100 "different" autoimmune diseases, which as a whole affect 1 in 10 people. They keep discovering "new" ones every year, adding to the list like they're cataloging species. Hashimoto's thyroiditis\! Graves' disease\! Type 1 diabetes\! Rheumatoid arthritis\! Lupus\! Sjögren's syndrome\! Each one gets its own specialist, its own treatment protocol, its own research funding. Medicine acts like they've discovered 100 different mysteries. "Oh look, the immune system can attack the thyroid\!" "Oh wow, it can also attack the joints\!" "Can you believe it? it attacks the pancreas too\!" As if each one is a separate phenomenon requiring separate explanation. It's like "discovering" that water can make cotton wet, and wool wet, and silk wet, and declaring you've found 100 different wetting diseases instead of recognizing that water makes things wet. At this rate, they'll 'discover' 200 autoimmune diseases by 2050, each one treated like a breakthrough instead of recognizing they're all variations of the same failure.

And autoimmune clustering is just the beginning of a much bigger pattern; disease clustering extends far beyond autoimmune disease. Medicine uses the term "comorbidity" when diseases occur together - for example if you have both diabetes and heart disease, or depression and Alzheimer's. They think of "comorbidity" as separate diseases that just happen to coincide. But the clustering is far too consistent and predictable to be explained by chance alone.

In fact, over half of US adults have multiple diagnosed health conditions. It's not unusual to see patients with 5-7 conditions, and older adults having 5+ conditions means an average of 50 prescriptions, 14 different doctors, and 37 visits per year. And these conditions aren't accumulating randomly, they are clustering in predictable patterns. Depression with stroke, chronic pain, and Alzheimer's. Diabetes with heart disease, depression, and kidney disease. Asthma with cardiovascular disease, COPD, and depression. The more conditions you have, the more likely you are to develop more. When you look at the actual patterns, what you see is that certain diseases cluster in specific constellations. Alzheimer's, congestive heart failure, COPD, diabetes, and cancer cluster together at rates far beyond what chance would predict. About 80% of people with Parkinson's disease will develop dementia during the course of the disease. If you have depression you are about 40% more likely to experience a stroke. The list goes on and on, across every body system you could name.

And neurodegeneration clusters the same way. Alzheimer's and Parkinson's share so much pathology that at autopsy, about 60% of Alzheimer's patients have Lewy bodies - the supposed "hallmark" of Parkinson's. MS patients have about twice the risk of developing Alzheimer's disease. The boundaries between these "different diseases" blur the moment you look closely. Medicine draws boundaries between them, but the bodies keep showing all of them bleeding into each other.

When researchers analyzed 10 million patients to look at the pattern of comorbidities, they identified very well-defined disease clusters. Metabolic syndrome clusters together: obesity, high cholesterol, hypertension, diabetes. Autoimmune and inflammatory conditions cluster together. Mental health disorders cluster with chronic pain. Cardiovascular diseases cluster together. The pattern is there, clear and consistent, across millions of people. And medicine sees these clusters and says they share "risk factors." Which truly, if you translate what this means from medical jargon into common parlance means: we see the pattern, but since we treat each disease as its own discrete entity with its own specialist, we never step back far enough to see what's creating the cluster.

Disease state

So let's do that now. If we look across all of medical research, and then step back so we can see the full picture, it becomes clear that there's a specific physiological state that precedes all chronic disease. Medicine has identified some of its markers: high blood sugar, hypertension, inflammation, and obesity, and noticed these appear upstream of hundreds of conditions. But they stopped there, treating these markers as causes rather than symptoms. They never asked what was upstream of those markers. What could explain why they were happening in the first place?

When we look at the full picture to see where disease actually begins, maintains itself, and progresses, a clear physiological state emerges. The chemicals being maintained in this state cause Tregs to downregulate and become less effective, for example, and this not only explains autoimmune disease but the clearance failures in cancer too. In cancer, this same chemical state suppresses the NK cells and cytotoxic T cells that normally eliminate aberrant cells thus stopping the abundance of cells that leads to the natural selection process that produces cancer. And when we look below at all the rest of medicine's chronic disease categories, we will see it cleanly explains them as well. From here forward we'll call this upstream disease state pathostasis. Patho meaning disease, stasis meaning steady state. Pathostasis is the disease state medicine has been meticulously documenting piece by piece but has never assembled whole. And it explains…everything.

So what exactly is pathostasis? It's what happens when the body's adaptive and useful acute stress response, which is designed to activate briefly then resolve once a threat passes, gets stuck on. Here's what that looks like chemically:

This isn't controversial; every value in this table comes from mainstream medical research. What's never been recognized is that this chemical configuration IS the chronic disease state, not a risk factor for it or a contributor to it, but the actual mechanism itself.

Before we go further, let's clarify what we mean by the acute stress response and how pathostasis relates to it. When we say 'stress' here, we're not talking about missing your kid's recital or having too many emails. Medicine and the wellness industry both saw the correlation between disease and stress, and so started to recommend things like “self care” and destressing. But while the correlation was correct, the cause was not. That’s why taking a bath, going on vacation, or going for a daily walk, isn’t actually curing anyone of anything. It might help make you feel less stressed in the moment, but it’s not addressing the engine that’s keeping the pathostatic chemicals turned on. So you can't address pathostasis by ‘reducing stress’ in the colloquial sense. For long term change, you have to address the conditioning that creates this engine, which we will address in part five. Which also means that you don’t need to feel “stressed” to be sick. And conversely you can feel stressed and be perfectly healthy. Acute stress is a natural, normal body response.

So pathostasis is the state of these chemicals being stuck on. The cumulative burden of time spent in pathostasis, and the degree of chemical dysregulation, we will call pathostatic load. When medical research documents 'chronic stress,' they're actually measuring load, even if they don't realize it.

While in this state, due to prolonged exposure to these chemical changes that our bodies weren’t evolved to maintain, your clearing systems fail, your immune system dysregulates, inflammatory processes go haywire, and disease develops. And though it seems random: why did person A get cancer while person B got depression? What we can tell from the data is that it isn't as random as it may seem. Let’s think about it mechanistically. Imagine a chain. If a chain were to get rusty and weathered, and someone dropped something heavy on it, is it just going to break where the thing hit it? Or is it going to break at its weakest point - where there's the most rust, where the latch is damaged, where it's been rubbing against something? It can be either or both. Where your system got the blow, and/or where there was already damage or vulnerability. This is what we see happening with the development of disease; it shows up where there's already vulnerability - genetic predisposition, prior damage, existing strain, or it develops where it received the blow, like lung cancer in smokers. And then, once that system starts failing, those failures create more stress on adjacent systems in that same cluster, and the next most vulnerable point in that system breaks.

This is why cardiovascular diseases cluster with kidney disease and stroke risk, for example. Hypertension develops because your blood vessels are constricted due to the elevation of norepinephrine, epinephrine, vasopressin and cortisol from pathostasis, and then the damage from that creates more load on your heart, and heart disease develops. Then that heart damage affects your kidney’s ability to function optimally, and kidney disease develops. The vascular damage affects your brain, and stroke risk increases. It's not four separate diseases. It's progressive failure in an already-compromised vascular system, each failure creating conditions for the next.

The same pattern plays out in metabolic clusters. The chemical cocktail of pathostasis creates the exact conditions for diabetes: increased glucose production, and insulin tolerance/resistance. When this is expressed, this metabolic dysfunction affects the cardiovascular system, and heart disease develops. The inflammatory state from both affects more metabolic processes. The pattern cascades through related systems, all connected through the same metabolic infrastructure that was vulnerable to begin with.

Autoimmune conditions cluster together, which makes sense because if your immunity is already a weak point, then it’s easier for further autoimmune diseases to tack on to the first. Again, these are not separate diseases randomly occurring in the same person; they're progressive failure in an interconnected body system.

This explains everything medicine finds puzzling about comorbidity. It explains why "comorbidity" rates are so absurdly high - they're not actually CO-morbidity, they're the same morbidity expressing in related systems. It explains why treating each disease separately downstream doesn't stop new ones from developing - because you're not addressing the upstream state that's causing the failures. It explains why lifestyle interventions often fail; because telling someone to eat better and exercise more doesn't address why they got sick in the first place. They don’t address the pathostasis that’s driving it all.

So let’s look at how this plays out across the spectrum of diseases. To read this tree, you can look at the letters on the chemicals in Level 0, and the numbers on the level 1 and 2 disorder/disease mechanisms, and see how those map to the example diseases below. This tree shows that chronic diseases cascade down from level 0 chemistry. Levels 1 and 2 map out commonly studied cascade pathways medicine has documented but never unified. The disease list is a representative snapshot, not an exhaustive list.

You will notice how 'real' diseases, 'functional' disorders, and 'psychiatric' conditions all trace back to the same Level 0 chemicals? That's because these divisions never existed in biology, only in medical specialization. An emergency room doctor, a psychiatrist, and a rheumatologist could all be treating the same patient for what they think are three different diseases, chest pain, depression, and arthritis, never realizing they're all looking at different expressions of the same Level 0 chemistry.

So let’s walk through what we're looking at here, because this is quite a lot. It’s all of medical research finally assembled into one picture. And let’s also be really clear that this is a conceptual framework, not a biochemical flowchart. We are using this table to present the unifying cascade that happens in pathostasis, not to perfectly map every single mechanistic change.

At the very top, Level 0 is the chemical picture of the body in pathostasis like we showed in the first chart, and it explains in a clean domino effect, every single chronic disease we know about. Notice how cortisol (A) appears in almost every disease pathway? Or how immune dysfunction (mechanisms 8, 9, 10) shows up everywhere? These aren't coincidences - they're the common threads medicine missed by studying diseases separately.

Medicine’s favorite red herring: obesity and fat

In levels one and two we are showing byproducts of level zero, downstream cascades that medicine talks a lot about and sees causing a lot of other stuff. For example, notice obesity is on the level 2 list, secondary cascades. This means it’s a symptom of disease, not the cause. In fact, why don't we look at obesity a little more closely; use obesity as a case study to see how this tree can shake out the truth that medicine has been missing, since it's blamed for so much. Medicine sees that a lot of disease happens in people who are 'overweight,' and they conclude weight gain causes disease. They've even noticed that belly fat specifically correlates with certain diseases, so they declare belly fat is especially dangerous. But rather than asking WHY the body would preferentially store fat around organs during certain conditions, they just declare the fat itself is the problem. Lose the weight, they say, and the disease will improve. But JUST losing weight doesn’t actually help. In 2004 when Klein et al. removed 28-44% of abdominal fat via liposuction, they found no change in insulin sensitivity, no change in inflammatory markers, and no change in blood pressure, glucose, insulin, or lipid concentrations. And this was about 12% of overall body fat removal. They then tracked these same people for 1.5 to 4 years after the liposuction and these same results persisted. There have been multiple meta-analyses of similar studies and some show no effect at all and some show inconclusive results. If fat were really causing disease, wouldn't you expect losing it to provide some consistent benefits?

Given that losing fat alone doesn’t seem to change much, let's think about what's actually happening at Level 0 and Level 1 when weight gain occurs in pathostasis. You have elevated glucagon (E) and cortisol (A) driving chronic hyperglycemia (5). Your body is producing more glucose than it needs because your stress response thinks you need immediate energy available. That glucose has to go somewhere. Insulin’s job is to get the cells to open the door and let in glucose, so when glucose rises like this, initially, insulin rises as well, to shuttle it into cells. But just like your body needs more and more alcohol to get you drunk the more you drink, the more insulin the system has, the more insulin is needed to perform the same amount of glucose shuttling. So the cells become tolerant (medicine calls this resistance) to insulin's signal, and now you have high glucose and high insulin circulating in your bloodstream. Insulin does two other things as well. It promotes fat creation, and stops fat from breaking down. So when there are chronic high levels of insulin in the blood it makes it very easy to gain weight and very hard to lose it.

And cortisol which is also elevated in pathostasis specifically promotes visceral fat accumulation - fat around your organs. In acute danger having readily accessible energy stores near your vital organs makes evolutionary sense. You might need that energy fast. The problem is that when you’re in pathostasis and these chemicals persist, your body just keeps packing fat into your midsection month after month, year after year. You're stuck in storage mode without an efficient release mechanism.

So where did this idea come from then? If there isn’t really any medical basis for it? It turns out the idea of body fat as the cause of disease came from the same guy who proposed that eating fatty foods was bad. In the 1950s, a physiologist named Ancel Keys started pushing what he called the diet-heart hypothesis, which posited that eating saturated fat raises cholesterol which he thought caused heart disease. He had access to data from 22 countries and in an effort to prove his idea, he only used data from the 6 that supported his hypothesis. Rather than reexamine his idea once he saw the data didn’t cleanly fit, he just ignored the findings that didn’t match. He was ridiculed in the scientific community for his antiscientific methods. Two epidemiologists published a devastating critique pointing out that Keys had data from 22 countries but only used 6, and that he was studying a "tenuous association" rather than proof of causality. They showed that if he had included all 22 countries the correlation essentially disappeared. In fact they were even able to show that if you picked a different set of 6 countries you could show the exact opposite effect that he was trying to prove. After being ridiculed he wanted to prove his detractors wrong, so he decided to conduct a study. But he used the same cherry picking methods from his original study, chose 7 countries where the data best fit what he wanted to see, used cohorts that weren’t representative of their countries, used inconsistent measurement methods, and through this research “proved” his hypothesis. This somehow worked and got him onto the board of the American Heart Association, and eventually on the cover of Time magazine in which he promoted "the evils of fat" including both body fat and dietary fat as one unified evil.

Keys was also the person who named BMI Body Mass Index, which later got adopted by the NIH and then used by the world health organization to recognize obesity as an epidemic. BMI actually came from one statistician in the 1830s who was trying to define “the average man”. To determine this he gathered data of Scottish and French military men’s height and weight, and came up with a formula that he felt represented it: weight/height^2. This was just based on his observation that these European military men didn’t tend to get wider as they got taller. So no actual medical or even scientific basis and it wasn’t intended for medical purposes. It was just some guy trying to figure out the mathematical correlations between human physical characteristics. But when Keys renamed it the Body Mass Index, it somehow took hold, and now every doctor's office in America uses it to tell people they're diseased. They came up with arbitrary numbers of normal based on European averages, and mortality statistics, and determined this to be the health bar for the world. No consideration for how height and weight may differ for women, or Asian people, or African people, or literally anyone else.

Which means many people labeled 'overweight' by these arbitrary standards aren't sick at all. They're just larger than a formula designed around 19th century European military men said they should be. Their blood markers are fine, their energy is fine, their bodies are functioning exactly as they should. The medical system has pathologized normal human variation in body size, then spent decades trying to 'fix' people who were never broken. Meanwhile, the people who ARE sick, the ones actually in pathostasis, aren't sick because they're storing fat. They're storing fat more than healthy people because they're sick.

So this one guy single handedly vilified body fat, dietary fat, coined BMI leading to it becoming a clinical measurement tool, and convinced everyone cholesterol was bad—all without any actual evidence. And the question isn't really why this one guy thought these wrong things; people think wrong things all the time. The question is how and why the entire system bought in, amplified his wrongness, and protected it for seven decades. And why it's all still largely believed and implemented today across the globe.

Keys was the co-principle investigator on a study meant to prove his hypothesis. They studied over 9000 people in controlled settings where they could actually measure dietary compliance, from 1968-1973, and they found two key things. One, that lowering saturated fat did in fact reduce cholesterol. And two, that reducing cholesterol didn’t reduce heart death. In fact the participants in the study who had greater reductions in cholesterol had higher risk of death. The inverse of what his hypothesis predicted. So what happened with this study? They just…never published it. It sat in the lead investigator Ivan Frantz’s basement until his son found it in 2011. When asked why they never published it Frantz said “We were just disappointed in the way it came out.” The most rigorous study ever done to test his hypothesis proved it was wrong, and they didn’t like the results so they just sat on it. Frantz’s son helped get it published in 2016, but by then it was all so institutionalized there was really no reversing course. It got published and completely ignored.

The truth is that cholesterol is actually good for you and necessary for immune function and brain function, every cell membrane requires it, and many other vital processes. It is so vital that 80% of your cholesterol is produced “in house” in your body. When you are in pathostasis your body produces more of it because it’s so beneficial, and as is the pattern we keep seeing over and over, medicine saw elevated cholesterol in sick people and assumed correlation meant causation. And we have spent decades trying to lower people’s cholesterol. Statins are a front line drug for people with heart disease and statins do actually provide benefits. Medicine thinks this is because of the cholesterol lowering function, but statins also reduce inflammation and improve endothelial function. When they use drugs that ONLY reduce cholesterol, they see no benefits at all on cardiac health. When they added ezetimibe (a non-statin cholesterol lowering drug) to statins, it lowered cholesterol even further but showed no additional mortality benefit. Same with PCSK9 inhibitors - they lower cholesterol dramatically but don't reduce death rates. The drugs that lower cholesterol without the anti-inflammatory effects don't save lives. Statins which have anti-inflammatory effects do. The mechanism medicine attributes the benefit to isn't actually the mechanism producing the benefit.

And here's what makes the obesity-as-cause narrative particularly insidious: when people lose weight through extreme caloric restriction without addressing Level 0, they often don't get healthier. They might see some temporary improvement in certain markers, but the underlying chemicals are still there. Their body is still in pathostasis, still producing the same hormonal environment, still generating the same inflammatory state. And because their body is still trying to store energy in response to that stress signal, the weight almost always comes back. Medicine sees this and concludes people lack willpower, that they couldn't maintain the weight loss. What actually happened is their body was fighting to return to the state Level 0 was commanding it to maintain.

But when weight loss happens as a result of turning off Level 0 - which we'll talk about in detail later - the weight comes off and stays off because you've addressed the cause. The body is no longer getting the chronic stress signal to store energy. Insulin sensitivity improves because insulin is no longer chronically elevated. Fat cells begin functioning normally again.

The weight loss isn't the treatment, it's the side effect of treating the actual disease state.

One of the most common criticisms you will hear about new theories or ideas is that 'correlation doesn't equal causation' and yet here they've built an entire treatment paradigm around mistaking a symptom for a cause. They saw a correlation - obesity occurs alongside disease - and declared it causal, with no mechanistic explanation for why having more adipose tissue would cause such diverse conditions. And they did this while ignoring all the data that suggests otherwise. Having more fat cells doesn't cause diabetes any more than having a runny nose causes a cold. They're both just observable symptoms of an upstream process. Yet we've built entire industries, treatment protocols, and social stigmas around treating the weight as if it were the disease itself.

It's yet another example of bailing water out of the boat without trying to fix why it was sinking in the first place.

GLP-1

Now that we know all of this, let’s come back to the GLP-1 ‘mystery’. All of the diseases GLP-1s act on are downstream of the same upstream dysfunction (pathostasis - chronic stress chemistry that never turns off). It’s not on the list of pathostatic chemicals above, because GLP-1s haven’t been thought of as a key player in the stress response, but the medical research shows that in acute stress, GLP-1s elevate, and are part of the acute stress chemical cascade. And in pathostasis, GLP-1s are depleted. So it makes sense that if you have been stuck in pathostasis for a long time, artificially adding back in one of these depleted chemicals would have an effect on everything downstream of these chemicals. Which as we have figured out here, is every chronic disease. The reason one drug works on "many diseases" is because they're actually one disease with many manifestations. And just like many other drugs we artificially inflate, whether alcohol, or dopamine in Parkinson’s patients, the body eventually builds up both a tolerance and a dependence. Which is what the early users of this drug are reporting. After 12-15 months, people stop losing weight, and if they go off the drug immediately, they gain most of the weight right back. Doctors are starting to recommend that patients stay on the drug, in an attempt to create a new set point for the body’s weight, but we don’t yet know what will happen when we take people off this drug after that time. Because now the body is used to having this chemical in its system, and removing it could be no big deal, or it could make everything worse than it was at baseline. This is something that should be tested long term.

Diabetes

Alright let’s walk through another example from the mapping above. Take diabetes, which medicine sees as a distinct metabolic disease, treats with insulin and glucose management, and considers it largely irreversible. What do we see when we trace it through the tree? Elevated cortisol (A), epinephrine (C), and glucagon (E) at Level 0 - drive chronic hyperglycemia (5). Your body keeps producing glucose as if you need immediate energy, even when you're sitting still. That excess glucose forces insulin production higher and higher, trying to shuttle all that glucose into cells. But over time, those cells build a tolerance (resistance) to insulin's signal. When you expose receptors to more of a substance than they were designed to handle, they downregulate to protect themselves.

So now that you've built up a tolerance to insulin, the pancreas has to work overtime trying to overcome that tolerance by producing even more insulin. This chronic overstimulation eventually exhausts the pancreatic beta cells that produce insulin. When they fail, insulin production drops - that's F at Level 0, depleted insulin, which also leads to weight loss, which you would think would have been a hint that weight was downstream. This insulin drop combined with the ongoing glucose elevation from A, C, and E, plus the inflammation from mechanism 10, you get the full picture of Type 2 diabetes at position 13 in Level 2. It's not a separate disease entity, but pathostasis hitting a vulnerable metabolic system. The tree shows exactly how A, C, E, F → 5, 10 → 13. Every step is documented in medical literature. They just never connected it all back to Level 0.

Cancer

We already talked about cancer, so let's see how it maps on the tree. Remember how we discovered that cancer happens when immune clearance fails and cells accumulate, leading to natural selection at the cellular level? Look at the tree: Immune suppression and dysfunction (8) which causes chronic inflammation (10) where selection pressure intensifies and impaired clearance systems (17). All of it tracing back to the chemicals at Level 0 - elevated cortisol (A), elevated cytokines (N), and elevated histamine (M). The Warburg metabolism we talked about? It shows up at mechanism 7, driven by cortisol (A), epinephrine (C), glutamate (H), and cytokines (N). But it's not causing cancer - it's just what stressed, proliferating cells do. The real drivers are the failed clearance and immune dysfunction. Based on your mapping above, cancer = A, C, N, H → 7, 8, 10, 17. Though mechanism 7 (Warburg) is more of a marker than a driver, the key pathogenic mechanisms are 8 (immune suppression), 10 (inflammation), and 17 (impaired clearance). Chapter three explained how cancer isn't a random mutation lottery but a predictable outcome of failed clearing in bodies stuck in pathostasis. Now we can see it mapped perfectly - the immune failure, the inflammatory environment, the clearance breakdown - it's all one cascade from Level 0.

Neurodegenerative diseases

Remember how we saw neurodegeneration clustering earlier - Alzheimer's and Parkinson's sharing so much pathology that half of Alzheimer's patients have Lewy bodies at autopsy, MS patients developing Alzheimer's at 2-4x the normal rate? The boundaries blur because they're not actually separate diseases. They're the same upstream process hitting different brain regions.

If we look at what the research shows across all of these conditions, the same thing comes first, before the protein aggregates and plaques that medicine points to as causes, they found the same thing in every single neurodegenerative condition: reduced blood flow (hypoperfusion). Hypoperfusion precedes neurodegeneration in Alzheimer's, Parkinson's, ALS, Huntington's, MS, and frontotemporal dementia.

The evidence is robust across all of them. And this makes perfect sense when you trace it through the tree. The pathostatic chemicals we've been tracking - norepinephrine, epinephrine, vasopressin, cortisol - all cause vasoconstriction at mechanism 1. That's their job during acute stress: shunt blood toward muscles and away from non-essential functions. But when these chemicals stay elevated chronically, the vasoconstriction becomes chronic too. And the brain regions that get hit first are the ones supplied by small terminal vessels, the last stops on the vascular supply chain, or the areas with the highest metabolic demands and the least backup blood supply.

And medicine already knows hypoperfusion causes dementia. That's what vascular dementia IS - cognitive decline from reduced blood flow. They diagnose it all the time. They even have a category called 'mixed dementia' for when they can't cleanly separate what's vascular from what's Alzheimer's, because the boundaries blur so often. So they know hypoperfusion causes cognitive decline. They know Alzheimer's shows hypoperfusion before plaques appear. And yet nobody thought to check whether the same mechanism was driving Parkinson's, ALS, Huntington's, MS. Each specialty documented hypoperfusion in their own disease, published it in their own journals, and never looked across.

This explains everything that otherwise makes no sense about these diseases. Lucid periods in Alzheimer's patients, where someone who hasn't recognized their family in months suddenly knows everyone's name and recalls old memories perfectly. Good days and bad days across all these conditions. Stress making symptoms worse, because vasoconstriction tightens further and more neurons go dormant. Exercise helping, because improved blood flow brings neurons back online. The dramatic placebo responses in Parkinson's we talked about in chapter 2, where patients produced real dopamine and reduced their tremors by 70%, none of that is possible if the neurons are dead. Dead cells don't start working because you believed in a sugar pill. They don't come back online because you had a good night's sleep or went for a walk. But dormant cells can, and do, whenever perfusion improves enough to support their metabolic needs.

Medicine has spent decades and billions of dollars trying to clear amyloid plaques and Lewy bodies, treating these protein aggregates as the cause of neurodegeneration. But patients can have extensive plaques with no cognitive symptoms, and severe dementia with minimal plaques. The proteins aren't causing the disease. They're accumulating because the clearing systems we talked about in chapter 3 are failing, for the same reason they fail everywhere else in pathostasis: the body's resources are being redirected toward survival, not maintenance.

But if hypoperfusion is the driver rather than the plaques or the proteins, that raises a question: what's actually happening to these neurons? Are they dying, as medicine assumes? Or is something else going on? The answer has significant implications, and we'll examine it in the next chapter when we look at the predictions pathostasis generates.

. . .

And medicine has been meticulously documenting all of these things for over a century. Every mechanism in this tree is documented in their literature. The elevated hormones, the physiological effects, the cascading failures, all of it measured and published in thousands of studies across every medical specialty. The pieces are all there, but what they haven't done is step back far enough to see it's all connected.

It seems almost unthinkable that something so simple could have been sitting there in plain sight. If this were true, wouldn't someone have noticed by now?

But history shows that the most important scientific discoveries often hide in plain sight, waiting for someone to connect pieces that everyone else kept in separate boxes. And history also shows us that the simpler and more far-reaching the discovery, the fiercer the resistance. Not because it's wrong, but because accepting it means admitting we've been looking at the problem backwards.

So before we go any further, let's pressure test this the way any scientific theory should be pressure tested: by looking at the rules for what makes a theory good. What separates revolutionary science from pseudoscience? When we apply those criteria - the same ones that validated germ theory, evolution, and plate tectonics - which explanation actually holds up?

Medicine's framework, with its hundreds of separate diseases and unclear mechanisms?

Or this one?