https://youtubetranscript.com/?v=kbSZ698iSrs
One of the things that the non-medical listeners and watchers of this podcast might not know is that, there’s a lot of overlap in symptoms between different hypothetically different illnesses. So let’s take depression as a case in point. When I was assessing my clients for depression, the first thing I always tried to figure out was, are they just ill? Because there’s all sorts of evidence associating depression, particularly with immunological dysfunction. So I would inquire into their sleep habits and their eating habits, and also their associated health conditions to find out if we could, because my sense was before we diagnosed something as psychological, we should take a look and see if there’s actually something causing it. Depression is a relatively nonspecific cluster of syndromes. Now, you’re pointing to a whole set of syndromes that have relatively nonspecific symptoms, some of them even more difficult to diagnose, and easier to be skeptical about in relationship even to their existence, as say fibromyalgia and chronic fatigue syndrome. That’s hard to dissociate from general depression and anxiety and a global neuroticism or even a hypochondriasis. Now, you’re saying, your first claim is that 20 percent of the population is likely to be experiencing these symptoms, but we don’t see this Sears chronic inflammatory response syndrome in 20 percent of people, because essentially we’re placing them in the wrong bins. So let’s walk through what the symptom constellation is for chronic inflammatory response syndrome, that’s Sears, and how you think we should go about distinguishing that from, say, fibromyalgia, which is poorly understood, or chronic fatigue syndrome, which is poorly understood, or depression. Why do you think that your category system, which places all these people in the box of chronic inflammatory response syndrome, why do you think that that’s preferable to the approach that’s being used by physicians now? Because you’re making a lot of radical claims here, and I’m certainly not in a position to dispute them, but you know what they say, radical claims require radical evidence, and you’re saying, well, first of all, that 80 percent of our buildings are in serious trouble, that 20 percent of the population is suffering dreadfully as a consequence, and that there are genetic predispositions to this, and that many, many people with many other disorders are fundamentally misdiagnosed, and that this is actually the root cause of their symptoms, like including absolutely devastating diseases like Alzheimer’s. So, what is it? Let’s go through, first of all, what are the symptoms that point to SIRS as far as you’re concerned, and then what do you use to prove that that’s the condition? As Dr. Shoemaker said, we have roughly 30 biomarkers. These are tests which can distinguish ill people, or what we call cases, from healthy people, what we call controls. We have roughly 30 of them, and all of them have been validated to show that they separate cases from controls. When we look at the diagnosis of SIRS, you have to have objective evidence that shows that you have several of these biomarkers, you know, I mean, at least four or maybe five or more before you can actually even make the diagnosis. The statistical likelihood of finding a healthy person who had five abnormal biomarkers out of the five we draw or the 10 that we obtain is so small. I mean, it’s in the one to a million. Then when you start looking at a larger group of people, maybe several people in the same hall, or in the same office building, or in the same school, when you start looking at that and each person’s probability of having those abnormal biomarkers multiplies by the next person’s, and then multiplies by the next person’s, by the time you get to 10 people, you have such astronomically low probability that this is a freak accident that it can’t be dismissed. I think what the main problem is and why this hasn’t been seen before in chronic fatigue patients or irritable bowel patients or fibromyalgia patients is because most physicians or many physicians don’t run the tests that we do. We are looking specifically at the innate immune system as the possible root cause for these different symptoms. And if they ran the tests that we do, they would see the same kind of data that we have. My data is very similar to Dr. Shoemaker’s. I’ve seen roughly 2,000 patients, 2,000 that I’ve evaluated this. For him, it’s much more because he’s been doing it much longer than I have. And our data is very similar. Okay, so your argument basically is, and I just want to walk through this very carefully so that everyone listening understands, is that you’ve identified a number of biomarkers. You said 30 overall, but apparently you concentrate on something like 5 to 10. Now, there’s a probability that any given test is going to produce a result that’s positive falsely. So someone will be diagnosed as abnormal on that evaluated dimension, but in truth not be abnormal. But that probability declines as a function of the number of tests administered. So maybe there’s a 1 in 20 chance that any given test will show that you have the condition. But there’s a 1 in 400 chance that two tests would show that and a 1 in 8,000 chance that three tests would show that. And so your case basically is that as you accumulate evidence of the biomarkers, you decrease the probability of a false diagnosis. And there aren’t biomarkers, as far as I know. There certainly aren’t biomarkers for depression. So that’s not specific, what would you say, physical or chemical biomarkers. You know, sometimes there’s elevated cortisol or decreased cortisol, but the markers are very nonspecific. So if you’re correct and there are specific biomarkers for SERS, that implies that it can be more accurately diagnosed than the other conditions with which it might be confused. And so what are the prime biomarkers that you guys use to make the diagnosis? And why did you pick those and how valid do you think they are and why? We need to start with a case definition. The case definition in 2003 that our group came up with was modified in 2008 by the U.S. Government Accountability Office. When they looked at the potential for exposure, this is what CDC used with Fisteria back in 1996. You didn’t get sick from a microalgal bloom unless you’re exposed to it. So the potential for exposure is number one. Number two is symptoms the same or similar to those seen in published peer-reviewed literature. The third element is laboratory findings the same or similar to those seen in published literature. And then the fourth is objective response of biomarkers to treatment. So if we then say what biomarkers have stood the test of time, back in 2000 it was trial and error by finding HLA was the explanation of why did some people get sick and other people didn’t. Was there a risk factor like cigarette smoking or alcohol use or age or underlying illness with diabetes? No, no, no, no. It was based on genetic markers. So individually immune responses became our first biomarker. Actually, the first biomarker came from the EPA with Ken Hudnell. Been studying the neurotoxicologic features of visual contrast sensitivity, which is a mechanism to see an abnormal neurologic function of vision. Contrast is one that’s going to be stabilized over time and is adversely affected as velocity of flow of red cells and retina and neuro-rheumatoid nerve head increases. So VCS was our first, HLA was our next. In that group, there was a regulatory neuropeptide, melanocyte stimulating hormone, which is essentially negative in all cases and normal in all controls. And then with treatment, we saw improvement in MSH, not as much as what we wanted. And that was the impetus to keep on. Scott mentioned cytokines in 1986. Nineteen eighty five was the first publication of a paper on cytokines. And here we are in 1996 postulating that this cytokine effect could be huge. And now if you fast forward to covid, it’s a cytokine storm. And everyone that drugs knows what a cytokine storm is, they’re buying covid tests. They’re looking for mechanisms that we have been studying. And cytokine storms are part of innate immune response. So you’ll have it in covid, but you have it in SERS2. And covid doesn’t have the same HLA that we know of yet, but we’ll probably find it doesn’t have the same VCS. And it’s a sorting process. So we took then inflammatory markers, TGF beta one. No lab was running that. So I hired a lab to prove that there was such a marker. And then we showed it with the abnormal and showed it in its height with some of the worst illnesses of all. Then we treated it with medications that were available over the counter or with with informed consent. And then every time we had re-exposure, here we came to the prospective acquisition of illness, proof of causation. We took people that could have been sick from one building, fixed them all. They had a lab, the biomarkers were the same. And then with informed consent, they stopped all medicines and stayed away. The suspect building three days, nothing. Put them back in the building on day one. At the end of day one, laboratory findings changed. Day two, laboratory changes, finding changed again. Day three, we had the exact syndrome of labs, VCS and symptoms prospectively proven upon re-exposure only. No other choices could have been affected. It wasn’t depression in three days. It was SERS in three days.