Predicting & Preventing Disease with Precision Medicine | Dr. Jeremy Nicholson
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Before we jump into today's episode, I'd like to note that while I wish I could help everyone by my personal practice, there's simply not enough time for me to do this at this scale. And that's why I've been busy building several passion projects to help you better understand, well, you. If you're looking for data about your biology, check out Function Health for real-time lab insights. If you're in need of deepening your knowledge around your health journey, check out my membership community.

Hyman Hive, and if you're looking for curated and trusted supplements and health products for your routine, visit my website, Supplement Store, for a summary of my favorite and tested products. Hi, I'm Dr. Mark Hyman, a practicing physician and proponent of systems medicine, a framework to help you understand the why or the root cause of your symptoms. Welcome to The Doctor's Pharmacy. Every week, I bring on interesting guests to discuss the latest topics in the field of functional medicine and do a deep dive on how these topics pertain to your health.

In today's episode, I have some interesting discussions with other experts in the field. So let's just trump right in. Well, Dr. Nicholson, welcome to the Doctors Pharmacy Podcast. I'm so happy to have you. You've come all the way from Australia, down under. You're here at the annual International Conference for Functional Medicine. I'm so privileged to be able to talk to you because you're one of the pioneers in a new field of medicine that is just going to be what everybody's doing in a few years. And you've been the pioneer in this field

what we call phenomic medicine. And we're gonna define what that is in a minute, but we're talking here about a new era, a new revolution in science and the science of medicine and the application of that science to treat complex chronic illness that doesn't lend itself well to a single biomarker treated with a single drug to create a single outcome. Like high blood pressure, blood pressure pill, lower blood pressure.

Biology is way more complicated than that. And in medicine, we kind of do what we do, but it's not really looking very deeply into the human body. And up until the last few years, we really haven't been able to

understand what's going on. We do a blood chemistry panel of 20 or 30 analytes. You might do a cursory physical exam. You might get a few x-rays or imaging here and there. But it's kind of the dark ages when it comes to really what now is available to us to understand the complexity of the human biology and to understand this world of the omic medicine, which is our genes, how they are expressed into what we call the phenome, which is

the body's expression of all the influences that have washed over us through our lifetimes. And we're gonna have you define it as well. And we're entering an era where we're moving away from a one-size-fits-all medicine to a highly personalized form of medicine that's based on your particular genes, biology, experiences, exposures. And that's gonna help us to identify patterns in your story, in your data,

and a lot more data than we're capturing now, which we're going to be able to capture more over time, to be able to create a predictive model of where you're headed on the continuum from wellness to illness.

And so your work has really done a lot of the sort of hard, sort of challenging work of making sense of an enormously complex array of scientific advances that have happened so fast that we can't even imagine how profound it is. And it's kind of akin, in my view, to sort of the discovery of the microscope or the discovery of like even the electron microscope to be able to see or the telescope to see what's happening in a world that we never saw before.

So can you kind of, before we get into sort of the omics and whatever, can you kind of talk about what is precision medicine, personalized medicine, and how does it differ from what doctors are doing now in conventional medicine, but I was taught in medical school?

Well thanks for that interesting introduction, covered a lot already. So precision medicine comes under a number of different titles, terms of stratified medicine, precision medicine, personalized medicine and all of those things

The different flavors of the same thing, but they're all about getting the right treatment for the right person based on some knowledge about their biology, some fairly deep knowledge about their biology. And to a lot of people,

These days, talking about scientists and doctors now, they think of precision or personalized medicine as being very genomically orientated. So your genes will tell you what is going on in your body and what sort of things you should look out for. But I think it was Francis Crick first described the genome as the blueprint for life.

And that's an interesting and revealing terminology basically coined in the 1950s. The blueprint is a set of plans for building something. So if you have a blueprint for a nuclear submarine, you can build that.

But it won't tell you about nuclear power, about the fact you're splitting atoms or anything like that, or even what electricity is. It doesn't tell you how the thing works. And your genes, of course, give you as an organism flexibility for living in a complex changing environment. The world changes all the time. And you have to have enough genomic, genetic flexibility to be able to accommodate to the changes

that exist. And when evolution occurs, it's your adaptability of your genes to go into new environments to capture new food sources. So there's an intrinsic variability in the genome which has good parts. It gives you adaptability, but it also allows you to go into new environments.

The thing that really changes whether you can go into an environment is actually the microbes that live in you. The microbes are an interface between you and the environment. So all environmental influences, dietary sources, pollutants, whatever it is, come through a microbial layer on your surface of your skin, your lungs, and of course your gut. And that modulates what happens in your body.

For a start, the genomic hypothesis that, you know, have been able to predict medical outcomes based just on human genomes is incomplete because it doesn't include all the microbial genomes, which are individual to all of us. Maybe 100 times as much genomic material as our own body. Maybe a lot more than that. So 100 trillion organisms living in us at any one time and about a kilogram in mass of microbial genomes.

mass. So there's that extra bit that goes from the genome to the

the metagenome, that's all the bugs that live with us, but all those environmental influences that you mentioned, including your differences in diet and your lifestyle, that is all continuous interaction throughout your life. So there's a conditional interaction between your genes, the microbes, and the world that happens from the time you're born to the time that you die. And those conditional interactions determine who you are. Who you are

is the result of everything. And unfortunately, genomic medicine, it has some very powerful applications, particularly in cancer medicine and things like that, and rare diseases.

But in fact, for most people, the environment carries much more power in determining your future and your future diseases than, in many cases, your actual genome itself. So your genes are not your destiny. They may predispose you to something, but it's the expression of those genes that's based on what washes over them throughout the course of your life. And we've got different sort of genomic potentials as well. So there are some people...

Refer them as Churchill genes and Winston Churchill got a Nobel Prize was Prime Minister twice and he drank and smoked heavily every day of his life until he's 90

And so we think about the Churchill genes, you know, we'd all like to be able to do that. And he actually managed to tolerate that. So there are some people that have very resilient genomes. It doesn't matter what you do, they still live for a long time. There are other people who have inborn errors of metabolism. They tend to die young, and there's not much you can do about it. And then there's the rest of us, where it's your genes and your environment that determine what happens to you. And precision medicine is by trying to capture the,

the gestalt of that, the totality of that, in order to make some judgments about you as an individual and how best to treat you going forward. Treatment isn't just treating diseases, it's also preventive medicine, right? So it's modifying your lifestyle so that you minimize the chances of getting disease in the future. So really this is a whole new way of thinking about health and disease based on

complexity and based on multiple variables that influence how your genes are expressed into the current

health state that you are, and it's dynamic all the time, and it's changing. It's changing based on everything you do, what you eat, how you move, what you think, your microbiome, environmental exposures, what we call the exposome, what you're exposed to throughout your life. And that, it seems like, is responsible for 90% to 95% of all chronic disease. It's not your genome. Correct. And yet, we've never really been able to look deeply into that until recently. And I said when I started digging into all this, I was like, wow, there's like...

37 trillion per billion trillion chemical reactions every second in the body. And I don't know who counted them, but it's taking a while. But it's a lot of chemical reactions. We have 100,000 terabytes of data in our microbiome alone. And I

How does one doctor or one practitioner ever come to understand how all those things relate to each other, how they connect to each other, what to do about them, how to navigate that in a patient who's sitting in front of you? It's not something we learn at all about in medical school.

And so this whole field of phenomic medicine is actually encompassing all the omics, right? Your genes, your metabolome, your microbiome, your transcriptome, your proteome, all the omics, right? And there's probably more. I counted 257 things ending in the word omics. Yeah, your immunome, right? And all of those things are things that we have profound influence over. And there are things that get deranged or dysregulated

by how we live and what we do. So it's a very empowering message, but it's also like daunting. How does someone think of like, oh gosh, I go to my doctor and I get my 20 lab tests or 30 lab tests and my chem screen, my blood count, my cholesterol, checks my blood pressure, my weight, and now does a Kersh exam. How is that even coming close to figuring out what's going on? And it's not. The truth is it's not. We're looking for pathology. We're looking for end stages of problems that are picked up by these tests. And what you're now able to do and what you've done in your

in your phenome center in Australia is to help us to kind of map the landscape. It's almost like a new frontier of how we should be looking at human biology, not through the lens of diseases, but by the lens of the phenome. So can you kind of talk about what is the human phenome and how can we use it to guide a more personalized approach to healthcare that's not a one-size-fits-all issue?

Sure. So, as you point out, there's a lot of things you can measure, literally millions of variables in the human body that are measurable in the real world. Not everything that can be measured matters, not everything that's measured matters. That's Einstein said that. Einstein, right. So we have to get to like, what do we measure that matters, right? Yeah, exactly. So it's a multi-step process. The first thing is we have...

extraordinary technologies now that expand almost every day. So the number of things that we can measure about the body, the number of ways we can describe the body in, let's call it a multivariate biology space. So there is a mathematical part of reducing this data set into something that is more manageable.

But all of the different technologies are not really practical for the clinic or a doctor or even a major hospital. We're in the process of discovery at the moment, and discovery leads ultimately to translation, which is what we want. So our Phenoma Center, which is a collection of very expensive instrumentation designed to discover new human biology through chemistry,

But also do it at high throughput so we can look at thousands, hundreds of thousands of people if necessary. But we also are interested in once we've discovered out of the million things we measure, the 200 or things or maybe even 50 things that are new that are informative about the biology of the disease state that you either want to prevent or you want to treat.

then to make new translational technologies from that which can be deployed in a clinic or even potentially in the future in a doctor's surgery. So you take this vast space

of human biology, described my chemistry. You find statistically what the most important things are, and then you create a new mini technology. So it could be a lab on the chip sort of technology. It could be something even as simple as even a dipstick, which measures a new metabolite. Or we use a lot of spectroscopic tools, miniature spectrometers, which you could, which could

cost a fraction of the discovery technologies which you could deploy in a clinic. It reminds me of coloring books I had when I was a kid where you had to connect the dots and there's all these random dots on the page and you had to link them up together and you'd say, oh, this looks like a duck. This looks like a boat. And that's what you're doing. You're seeing all these random dots of biological data and you're connecting them to see where they're related and how they influence disease and what to do about it.

So that's absolutely true, right? But your analogy is slightly simplistic in that the duck is covered in a lot of other dots which are irrelevant. But you don't know that when you're measuring them. So the art and the science and the mathematics is designed to extract the shape of the duck from the background of the noise. I'm sure this is where AI and machine learning comes in. Well, AI isn't... We've been doing this for 40 years now.

I didn't call it AI then, we call it AI now, but the multivariate statistics. AI is a way of doing multivariate statistics. So AI is not new. It's just we can do it better now. Yeah, we can do it better. Ryan Reynolds here from Intmobile. With the price of just about everything going up during inflation, we thought we'd bring our prices down.

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This is kind of staggering when you think about the complexity, right? And you think about the amount of data we have. And we now actually can measure a human genome pretty affordably. We can measure the microbiome through tests that you can get through various functional medicine and other doctors.

I just did a panel the other day. It was a metabolomic panel. It was a commercial lab that just sent me out a kit to draw my metabolome. And these things are starting to kind of hit the consumer health market. They're quite not in the doctor's office yet, although some genetic testing is. But I find that...

that if we really look at disease, what we're actually doing in medicine today is waiting until people have something serious or something that's measurable on a pathological basis

And we know, and this is from my original textbook in medicine called Robbins and Cotran, The Pathologic Base of Disease, it says every pathological change, anything you see on a microscope or on an imaging scan is always preceded by some biochemical change.

And what you're looking for is these early biochemical signals that precede disease and the patterns in that data that can tell you about that particular person's unique thing. And I believe it's going to blow up our whole notions of disease because through the lens of systems biology and systems medicine, which is essentially what you're doing, it's what we try to do at the Institute for Functional Medicine and with functional medicine is apply this, take learnings from

the work that you're doing and others to try to kind of say, okay, where can we kind of try to accelerate the adoption without hurting anybody of this medicine to help understand these patterns in the data? And so I wondered if you kind of talk about

how we begin to kind of sift through all that. Because, you know, when I look at a patient, I do a lot more in-detail analysis of lab testing, but it's still just on the surface, right? And I'm just so excited for the moment when we'll be able to actually do these tests at scale

see these patterns happening for you and realize that we're all different in our manifestations. So two people with depression or two people with Alzheimer's or two people with autism or two people with autoimmune disease or whatever, diabetes, are not the same. And we're treating them all the same today in medicine. This is where precision medicine comes in.

So how does the role of doing some of these diagnostics, like the metabolome, the microbiome, how do we start to think about learning from this? And what are you learning in your research that can actually start to make sense for people clinically?

Yeah, well let's just start that precision medicine aspect first. I mean the idea of one size fits all comes very much from the pharmaceutical industry. Yeah. Right, the blockbuster drug. And this is not that long ago, 25, 30 years ago drug companies were trying to discover that drug which they could

treat everybody with ulcers, everybody with arthritis, whatever, and find that drug which is a $10 billion a year thing. And we know that's difficult to do. And actually, all the easy ones have been fat.

So the pharmaceutical industry is in a bit of a hard place now because it's looking still for Blockbuster drugs and they they don't really exist so much anymore And in fact precision medicine is the opposite of that. We're trying to divide people down and actually ultimately we're all individuals There is an exact treatment for you right irrespective what disease you've got because of your background physiology which is made throughout the whole of created throughout your life and

And the pharmaceutical industry is not interested in that because it cannot make vast amounts of money out of one chemical product. But on the other hand, we still have this enormous task of measuring all of the things that we need to measure. And one of the reasons I spend a lot of my time working on metabolism

is that the metabolic phenotype is actually incredibly useful because it captures a lot of the gene-environment interactions that you need to know about precision nutrition, about health prevention, disease prevention, and about stratifying patients when they actually do get a disease. So a phenome is the expressed...

output of all the gene environment interactions in terms of things you can physically measure. So your height and your weight, you know, phenomic properties, but so is your blood cholesterol, so is your urinary creatinine, and literally a million other things as well. All of those things... Probably a billion. Whatever it is, it's a bigger number than you thought it was.

- Maybe a trillion things. - But the important thing is you don't have to measure a billion things or a million things because there's a lot of redundancy in the data. So there are things that one metabolite might capture, might capture the information that you need about a whole pathway, one or two metabolites. It becomes the ratios of those things that tell you about differential activities. So what we call now artificial intelligence or pattern recognition methods

are actually designed to extract those principle features in the complex data set, multivariate data set, and say, well, of all the things that you've measured, it's these 15 or 20 that describe pretty much all the biology, the difference between a normal person and a person with a particular sort of disease, or all the different subtypes of a particular disease. And it might not be things we're measuring at all clinically now, right? Most of it you wouldn't be, no.

Right, like David Furman in the 1,000 Immunum Project, which basically a thousand people look at their cytokines and their immune, he calls it the immunome, and found that there were four cytokines, four markers that I never heard of that are probably buried in my immunology textbook or maybe discovered after I graduated medical school. Yeah, yeah. And that were highly effective.

correlated with advanced aging and chronic disease. And those things now can be available as a clinical blood test, which you can use to track over time. I was talking to Richard Isaacson last night, who you might know is an Alzheimer's researcher who's doing a lot of innovative work around a systems biology approach to Alzheimer's. And he said they've come up with this new diagnostics called a P-PT.

I don't know, something, something, P tau, some number, I don't know what it was. But he said it's like a biomarker that actually found changes as you change people's

lifestyle habits that affect their brain. So you can see the increasing or worsening of Alzheimer's or the improvement in Alzheimer's through this biomarker. But he might have looked at a thousand things before he came up with this one thing. So that's what you're talking about is signal from noise. How do you detect the signal from the noise? Absolutely so. And the answer is statistics and a very large N. So you have to be able to sample. N would be a lot of people. N is the number of people. In order to make these sorts of discoveries, you really

need to be looking at thousands and thousands of people to build the basic mathematical models. That's for most disease. I mean, if it's a rare disease, I mean, or an inborn area of metabolism where the number of people might be very, very small, but the effect is very, very large. So you don't necessarily need a big N to discover what is wrong. But for most diseases, things that kill most of us,

then you do need literally thousands of people to make those sorts of discovery using the appropriate sort of technology. And what's the appropriate technology? Well, it's one that gives you the right answer. And unfortunately, there's quite a lot of different technologies. So you have to look at thousands of people with a number of different technologies to do the sort of discovery that's necessary to be able to realize

refine out of that the small number of markers that you could then productize if you like because ultimately it's a commercial angle all of these things anything that's going to be successful clinically and in the in the big world will have a will have a commercial angle to it because somebody's got to validate it and it's got to be made and manufactured so tolerance etc etc so when we think about

Precision medicine and the sort of discovery biology we need to do we need to think about all the possible problems are going to come up in order to make that work in the real world so you have to take a very long view into the into the future about what's going to stop so I've got this great

new marker, is it going to be practical to measure it in the real world? Is it going to cost $15,000 per time you analyze it? And if it is, it's probably not going to work generally. If it's going to cost $5, then you're talking business. So we're looking for that magic bit that's not only good science, good biology, and good medicine, but it's also cost effective.

Yeah, it's true. I mean, and I think we're well on the way to doing that. It's amazing how much medicine has changed in the last even decade, you know? Sure. I mean, when I graduated medical school, we hadn't even decoded the human genome, you know? Sure. Right? And now we not only can decode the human genome, but we can do large throughput analysis of, you know, just tens of thousands of molecules that are in our body. And, you know, like people don't even understand that

probably half or a third of the metabolites in your blood are from your microbiome, right? So like, wait a minute, you're gonna check your poop by checking your blood and it's like, wow, this is such a different world. And it allows us to sort of look at this continuum phenomenon. You know, the 2009 White House, I'm sorry, the 2009 Whitehall to Courts study was published in The Lancet, looked at a whole series of factors

that we could look at that would precede disease. So what were the sort of predictive things that you can actually measure that show what's happening? And one of the things that they found was that high insulin levels precede

high glucose by as much as 13 years. So doctors just check glucose, and this is something that's sort of an easier thing to understand for people, and they check it and it's like, okay, well your blood sugar seems all right, she must be all right, you don't have diabetes, fine. But the insulin levels go up before glucose, and I've seen this for decades, 'cause I measure insulin, but it's less than 1% of doctors that measure insulin.

But it's actually probably one of the most important biomarkers. Now there's a new, and you mentioned the ratios, there's a new test that's been now developed that looks at insulin and something called C-peptide, which is sort of a precursor molecule for insulin.

and the ratio of insulin and C-peptide through mass spectrometry, which is a very, very accurate test. And that test is highly predictive of someone's degree of insulin resistance, which is one of the biggest drivers of all chronic disease. So this is something, you know, one of the tests, it could be like more like five or $10. It tells you a lot that kind of the other data might not be as important. Can you kind of talk more about this whole idea and what you're finding around this continuum concept of disease from optimal health,

to pre-symptomatic disease to symptomatic to full-blown disease to death.

Yeah, so the idea is that we all can be considered to be existing. Wait, so the reason I'm asking you is because I think phenomic medicine is the first time we've been able to think about actually looking at that continuum. Because doctors don't do that. They just wait until you've got something and then they treat you. Well, and doctors are very highly siloed, you know, gastroenterologists, nephrologists, neurologists and stuff like that. But that's one of the things that systems biology really teaches you is that all those things are connected together.

And it's very difficult to look at a patient just from one medical angle. There'll be other things that are connected. The organ systems in the body don't work in isolation. They work together as part of the system. The immune system connects everything together. So looking at multi-systems is very important.

But so from our point of view, thinking about, we tend to think in the way we conceptualize it is thinking of people occupying a metabolic space or a phenomic space. It doesn't just have to be metabolites, but I tend to measure metabolites a lot. So we think in metabolic spaces. So what I mean by that, so if you've got say, let's say three parameters from your blood, you have glucose, creatinine and urea, you can have a three dimensional space. That would be your urea, creatinine, glucose space.

But of course there's thousands and thousands of things you can measure. So you can have thousand dimensional spaces and you occupy, if I took a blood sample from you now, you would occupy a particular position in space and so would I. And it wouldn't be the same space. We'd be separated by some hyperspace difference. And then tomorrow morning it might be different. Oh yes, what we'll do is we will be hovering around in our own, within our own metabolic sphere, if you like, except the sphere isn't in three dimensions, it's sort of...

10,000 dimensions. So think about us oscillating that during the day and you are oscillating in your space and your space and my space, if we're both healthy, will be fairly similar. As soon as we get a disease, we're going to move in the space because the different parameters are going to change. So the sort of...

advanced mathematical tools including AI are about looking at where we are in that space, the particular markers for us that make us unique and also how that changes in time. And that is essentially what we do. So we build spaces in M dimensions, a large number of dimensions, and we look about how a disease

impacts on that occupancy space, that position in space. And we'd look at a disease as a process of a movement, a trajectory through space. So you start in one space, let's call it your healthy space, which you're hovering around a bit in. You get some disease and you move significantly in space. And when you recover, you should go back to where you started. Now, this is quite interesting conceptually. And we've learned

We've learned a lot from studying COVID over the last couple of years. COVID has been the biggest hit in human biology that we've had since the flu in 1918. That's a giant synchronized hit in human biology. So that produces population level effects that we can see. And one of the things that we...

from a metabolic mapping point of view is when people get COVID-19, we've now got a lot of data on this, is they move in metabolic space. They actually move in lots of different dimensions. COVID affects a lot of organs, makes it really interesting for people doing metabolism. It's non-obvious. But not for people who have it. No, exactly.

Well, I've had it a couple of times. It's no fun, I can tell you. Right, and then the idea of mapping that movement into the abnormal space, which is a highly inflammatory space, and then mapping the movement as you recover back. Now, as we know with COVID, particularly interesting example is because a lot of people don't recover. They end up with something called long COVID or post-COVID-19 syndrome, where they're actually physiologically abnormal. And then we started thinking about

the ways of measuring that. We've done a lot of work on this. But we also started thinking about it from the point of view of reinfection, because there's been lots of reinfections. People have it three, four, five times. And the more times you have it, the more times you're more likely are to get long COVID. It's cumulative. So what we think about this now, and I think this is relevant for all of human diseases,

I'd say most, I haven't studied all human diseases, but let's say a large number of human diseases, is they can be considered as miniature each time you get a disease.

It can be different diseases you have a little journey in metabolic space from your normal space into abnormal space and then back again the important thing is When you come back to your normal space you don't come to it back to the exactly the space you started you shift slightly and the effect of that overview your lifetime is Aging so you're metabolically aging through a series of trajectories and you the important thing is there are now a

omics measurements you can make that map that space and there's mathematics for reducing it so we can start thinking about localized journeys in

due to an individual episode of disease and also potentially lifetime journeys as you age and become sort of more biologically incompetent as you get older, which is the aging process. I mean, aging is not a disease. Aging is natural. And death is the thing that we all worry about, but it's premature death is what we're trying to avoid through our technology. Precision medicine,

is effectively like trying to avoid premature death averaged over the whole of your lifetime. You brought up something really interesting. You said aging is not a disease, right? But, you know...

Neither is having a high insulin, but it definitely drives disease. So where on the continuum do you sort of name the disease? And we have these arbitrary cutoffs. If your blood sugar is 126, you have diabetes. If it's 125 or 24, you don't. Well, we know just that's ridiculous, right? It's also population-specific, I mean, or genetically specific.

What's true of Japanese isn't true of American. For sure, for sure, for sure. So we have this sort of arbitrary cut-offs where we say you now have entered into a disease. But this phenomenon, this continuum of dysfunction in aging, for example, is that there's breakdowns as normal physiological processes that don't manifest as a disease, but that make you get biologically older.

So we now know there are interventions that you can do to change that trajectory. So in a way, a lot of people are talking about aging as a disease and treating it as a disease and understanding the underlying mechanisms of, they call the hallmarks of aging, for example, the things that happen that are in common.

with people as they age, like mitochondrial dysfunction or inflammation or change in the microbiome or epigenetics or telomeres or zombie cells. These are things that we don't really typically measure in traditional medicine, but we can now. We can start to look at these things and see, okay, well, if I'm

doing these five lifestyle things or taking this supplement or this drug, I can reverse my biological age. And I just did this, it was so fascinating to me. And I still kind of worry about the validity of some of the tests and the reproducibility, but I did this lab called True Diagnostic where they do biological DNA methylation testing so they can look at your biological age.

And I did it two years ago. And then I was 43, I mean, I was 62 at the time. I just did it and I'm gonna turn 65 this year in a few months and I'm 39.

And I did a number of things on purpose to see if I could move that, right? So I changed what I ate. I changed my supplement regimen. I added rapamycin, which I don't recommend everybody take. I'm a guinea pig for myself. I tried various technologies like plasmapheresis to clean my blood. I did a number of different therapies to see if I could move it. And it moved. And I wouldn't say having a biological age of 43 at 62 was bad. It wasn't a disease. It was damn good, right? But...

What was I more on the continuum towards disease and breakdown at 43 biologically than I am at 40 39 I think so right and so that's fascinating to me It's like I'm not treating a disease by doing these therapies. I was trying to optimize This status of my phenome essentially, right and

And that's what I think is super exciting is understanding this concept of the exposome. So maybe you can just take a few minutes and help people understand how much control they have over what happens to them in their life through their health and understanding through the lens of the exposome and how that interacts with our genome and our microbiome. And you talk a lot about that. Yeah. Yeah.

Well, let's start with the microbiome, which is probably the most complicated part of it. So the microbiome develops from the time that you're born. You are pretty much aseptic before you're born. That's not absolutely true. We now know there are bugs that live inside you even when you're in utero.

But you get a lot as soon as you're out in the big, wide world. And that changes very rapidly over the first six months of life. The microbiome fully develops. It doesn't become like an adult microbiome until about three. It takes about three years to mature even the microbes in you. And it's that early microbiological change

development that tunes your immune system. So your immunology is set up from the time, the first year or two of life. And in fact, when it comes to understanding long-term chronic disease, a lot of the stuff that we've got to fix is in those first two or three years. If those are bad years, then you're never going to be able to fix it, right? So I don't think there's that appreciation of the importance of having a healthy body

very young childhood with the right sort of minimizing very adverse immunological microbiological exposures. So there's all of that which is all part of your development but it's inevitable that we get infections in our early life. You can't avoid it and that's part of building up your long-term immunity and part of building up your long-term immunity.

metabolism and all of these developmental processes have metabolic signatures that go with them and in fact they turn out to be some of the easiest things we talked at the beginning about there's so many things you can measure but in fact we would say that of all the things you can measure metabolic profile is probably the easiest you can get urine samples you can get blood samples very very easily those are easy samples to get it's what clinicians look at all the time so a lot of our technology is geared to getting the diagnostic and prognostic

features out of things that are readily clinically available and if not non-invasive then minimally invasive. So again part of the science is mapping those sorts of changes in metabolism in urine and plasma peripheral fluids if you like back to much deeper things that are happening in the microbiome, your immune system and actually also its organ specific physiology and pathology which develops over years.

And it's really all the things that we do that affect this interaction, right? It's what we eat. It's exercise. It's our thoughts. It's sleep. It's environmental toxins. It's our microbiome. It's...

Temperature, climate, weather, everything. And when I put my healthcare hat on, I mean, it's the simple things that are important. So we talk about all these incredibly expensive, complex technologies. But common sense is important too. So the single best thing that you can do for your life is have a healthy diet and do a reasonable amount of exercise. If you look at WHO statistics, you know,

the biggest single killer of humans is cardiovascular disease, statistically. 80% of premature death...

due to cardiovascular disease is preventable by healthy diet and exercise and not smoking those are really 80% of the world's biggest killers and that's changing the expose on Yes, exactly so you're basically talking about things we have in our control which is a very empowering message Yeah, and you know, it's like not like we're waiting for some big gene discovery. We're gonna get a gene

splicing editing technology that's going to fix us and prevent us from being sick. That's a long, long way away from now and may never be possible. No, because most of these conditions are polygenic, right? It's like not just one gene, like Down syndrome gene, which could be affected or, you know, if you have Huntington's chorea or some rare condition like muscular dystrophy, great. You can edit your genes out. But most of the stuff people are suffering from is just polygenic. It's complicated and it's influenced by our environment more than the genes. Absolutely.

What I'd love you to do sort of next is to help unpack the story of long COVID because this is something you focused on with your team and it's an application of phenomic medicine that I think has real fruit to bear. I mean, I'm a practicing physician. I can tell you I see a lot of cases of long COVID. It's not a rare problem.

And there are long COVID clinics in medical centers all across the country that I personally think do a lousy job of actually helping people because they don't understand the condition. They try to medicate the symptoms, but without really understanding the biology of it. And I think we are seeing data emerge around the biology of what's happening.

But it's not stuff often you can get within sort of an average doctor's visit or looking at sort of anti-muscarinic or autoimmune antibodies or various kinds of cytokines or various biomarkers that are elevated. And with the phenomic medicine that you're doing, you can sort of take this almost novel condition and say, what does it look like? What are the things that go wrong? How do we start to learn about what's

why this is happening and what we can do about it. So can you tell us a story of one, how you're using long COVID as a way of really applying phenomic medicine and what you're learning from it and what you're seeing the patterns are that you're finding and what are the therapeutic sort of hopeful,

things that we see on the horizon as a result. Right. Again, a lot of stuff to ask. I know. I ask long questions. I'm sorry. I want to know everything. My mother always asked me, you know, not what I learned in school today, but what questions did you ask? So I've been in the question business for a long time. Fair enough. So

If we just think about that, from the point of view of my laboratory, there's peculiar bits of history here. I was previously, as you know, at Imperial College London. About five years ago, we moved to Australia. So we can basically expand on the phenomic medicine program and build a new phenome center really just to look at that.

Our new laboratory, new laboratory, was opened in October 2019. You think about that, where we are in relation to COVID. It's like three months before. Holy cow, that's good timing. So we sort of put this $50 million laboratory together and then we're looking for things to do and COVID appears. And when you build expensive laboratories, you need to do important things with them. So we had a whole list of things, you know, cardiovascular disease, diabetes and all the other stuff.

And then COVID just went to the top of the list. So our approach to the problem was to work with international collaborators. And Australia, as you may recall, was one of the last out the gate with COVID because it's quite geographically isolated. And also from Australia, we could watch it happening across the world. Australia shut down fairly quickly to get in or out. And it basically prevented the disease for a couple of years. It kept

pretty much kept it out. And Australia still has the lowest mortality for COVID than any other country in the world. It's quite extraordinary. But so we started to build all these databases based on stuff from Harvard and Cambridge and all the other stuff.

And we were studying, of course, initially the acute disease, but you have to understand long COVID, you have to understand the acute disease and what it can do first. And the first thing that comes out of it is it's incredibly heterogeneous. So COVID is heterogeneous in its expression in human populations. There are some people that get incredibly, let's just go back to the original Wuhan variant,

You've got people who had incredibly severe respiratory disease that would put them from catching the bug to going into intensive care in a week or less than that. And once you're in intensive care, you're in deep trouble, as you know. You don't have a place to avoid. And there are other people exposed to the same...

genetic subtype of the bug that have almost no effects. So you have this diversity of severity and that still persists. And symptoms. And symptoms. So you can have respiratory symptoms,

They were more important earlier on in terms of severity, but there's neurological symptoms, there's GI symptoms, there's kidney. There's almost every... Blood clotting. Yeah, blood clotting, skin lesions in children, you know, Kawasaki-like disease, a whole range of things. Almost everything that you could think of. Yeah.

For me, anecdotally, it's a lung disease. And I was thinking, what does urine teach you about lung diseases? Not necessarily that much. And then we looked at the first samples we saw from COVID, which would have been probably March 2020. Yeah.

It lights up everything. I've never seen in your what urine or plasma I've never seen anything that lights up the body like this. Oh, you know, we got a big story here What do you mean lights up? I mean, I mean every pathway was was abnormal, right? So there was there were things related to renal metabolism Liver metabolism there were changes in life of proteins is just wherever you looked and

Wherever you looked, there was alterations. Whichever technology you used, there were things that were different. Normally, think of trying to find the right technology to get the right diagnostic.

But because this is such a spectacular systemic disease, and in fact, you know, the essence of the disease is really its systemic involvement and its immunological involvement. And so we asked the question, if you've got all these sub-effects in renal, whatever, microbiome is altered as well, how do you know when it's over, right? It's not when you stop coughing, right?

Of course, some people didn't stop coughing, right? But it's not when you stop coughing, it's when your system by chemistry goes back to normal. So we got samples from people who'd had this, this is now a year or two later. And we start to look at people with long COVID. People who, for instance, people who had never been hospitalized that had COVID once. And we had that in Australia. We had pretty good control of that because...

of the way that the protection was politically implemented in Australia. So we ended up with people who only had mild infection, never hospitalized. But if you look at their biochemistry, they were still abnormal six months or a year afterwards. So a whole series of things that were different.

Just the people who had long COVID or everybody? No, no, these were everybody. Anybody, anybody and everybody after COVID. For some biochemical features, there are things that do not return to normal even after a year, even if you have no symptoms. Wow. And we call that occult long COVID, right? It's something that's hidden. Are you saying this is 100% of people that you tested? I think there will be 100% of people ultimately that have some long-term biochemical effects of having one infection of COVID. Wow.

Even if they didn't weren't ill to start with and also somewhat alarmingly this appears to apply to children as well Wow, right. So I mean if you recall Donald Trump famously said you don't have to worry about children They hardly get it because of course he was an expert on many diseases But and that's that's actually not that's not true There are physiological effects in children, which are potentially quite serious So what we had was a whole series of different met metabolic patterns

and immunological biomarkers which indicate different subsystem failures different organ failure different levels of severity etc so we can take a panel of those and monitor any anybody from their blood actually or their urine but the blood is is easier in this respect for functional recovery for kidney gut you name it whatever it is there are biomarkers which have to

have to normalize. - And these aren't the normal things you get on your blood panel when you go to the doctor, right? - There are a few things, but only a tiny percentage of them. So a lot of these things are things that we discovered in our lab and other people have discovered them and verified those as well. So what we're thinking about now is taking a blood sample and from that metabolic panel, metabolic profile, we can say, well, look, whatever your symptoms are like, it looks as though you've still got liver damage or you've got new onset diabetes, which is a common effect.

Long COVID is not really a disease in its own right. It's a collection of other diseases that we already know that have been accelerated by having exposure to COVID. And the important thing about that is, and this is also a hopeful thing, is if we find those markers of your disease, of your subset of long COVID from a

a blood analysis, we say, well, okay, you're a diabetic now. You need to have the medicines already available for that. So this occult long COVID where you don't necessarily have to have symptoms associated with it, in most cases, they're things that are, you've gone from pre-disease into a disease state, accelerated by COVID, or you've gone into a pre-disease state. So again, an accelerated-

It is terrifying, but the important thing is you can do, if you know it, if you've been screened, you can do something about it because there are already lots of therapies. The things that we don't know so much about, although we are learning about them from the biochemistry, things like the neurological effects. So there's a lot of neurochemical effects. The brain fog and the body dysfunction. Which is also a really common part of long COVID, chronic fatigue.

And in fact, so here's another sort of bright side to the story is that COVID is now shining a light on lots of diseases that we already know, but we find new things out about those diseases because COVID has accelerated them in particular people that didn't have them before. So if you look at chronic fatigue, there is a set of chronic fatigue syndrome. There's a

a syndrome which is usually without an etiological agent. Most people agree it's probably a viral origin, but we can be pretty much certain of that with COVID because people get this brain fog and other neurological problems as a result of COVID. We know what that etiological agent was, and there are molecular biomarkers that go with that. They go with brain dysfunction. Well, one of the ones that we think is really interesting is the tryptophan-kineuronine pathway.

And that's got a lot, a lot of the tryptophan-related metabolites and neurotransmitters, you know, there's a whole range of...

Serotonin. Serotonin, yeah, for instance. And that pathway is really, really disturbed. It also is one of the ones that stays disturbed for the longest after you've had your COVID infection. And so we're thinking about what this would, you know, what this is about. And by the way, when you go to your doctor, you're not getting your tryptophan and urinate levels measured, but you're looking at these things with your deep phenomic analysis and you're seeing that, oh, this seems to be a persistent pattern in these patients. Yes.

But if you look at that pathway and things that are disordered in that pathway, there's actually loads of diseases. Huntington's disease, there's Parkinson's disease, there's HIV-induced dementia. All of those things have got defects in the tryptophan, kynurenine pathway. This is a really long list of diseases. And that's actually something that we think is probably important for

medicine in general that that irrespective of all the other stuff that yeah measuring that pathway is actually deeply insightful for a lot of diseases because it's because it's it's the thing that responds and gets worse when there's inflammation from any source whether it's covid or whether it's

And that's because that pathway is very, the enzymology, if you like, is very immunologically controlled. So, for instance, things like TNF-alpha, interferon, gamma, et cetera, stimulate the indole dioxygenase enzymes, which convert,

IDO, right. Yeah, exactly. The IDOs, exactly. So the tryptophan to kynurenine transfer is very much modulated by that, those immune factors. Just to break that down a little bit so we can, because not everybody's a PhD in biochemistry. The phenomenon you're talking about is inflammation.

interferes with a critical enzyme called IDO, it's called IDO, that is involved in taking tryptophan from your diet, from turkey or whatever you're eating,

and converting it into serotonin. And when there's inflammation, that process is affected and you end up creating molecular byproducts that are quite toxic to the brain, like quinolinic acid, that create inflammation in the brain and can cause any host of neuroinflammatory diseases, which range from autism to Alzheimer's, from anxiety to OCD, all of which are brain inflammation conditions. So there's a final common mechanisms and pathways.

but a variety of insults, right? Because inflammation can come from your microbiome. It can come from COVID. It can come from sugar in your diet. It can come from a million things. So I think this is such an important thing that you're bringing up, which is that there's a lot of stuff that we've,

never looked at that is where the problem is. You know, there's a joke that I often tell when I'm giving a lecture, which is this guy's looking on the street for his keys under this lamppost, and his friend comes by and says, what are you doing? He said, well, I'm looking for my keys. He said, where'd you drop them? Well, I dropped them down the road. He says, why are you looking over here? He says, well, the light's better. So we're used to looking where we can see the light, which is our typical chemistry and blood count, but it's actually not where the problem is.

And with phenomic medicine, we're actually for the first time able to shine a light on a lot of other things that we didn't ever look at before in the history of medicine that can now help us predict what's going on. I mean, the thing you mentioned there, quinolinic acid, that's a really interesting metabolite. It's massively elevated when you actually have the active COVID infection. So that's sort of the end, it's sort of quite a few steps away from tryptophan.

Quinolineic acid is used as a striatum straight or neurotoxin an experimental one in rats Really if you dose rats with quinolineic acid you can make experimental Parkinsonism. Yeah. Well, that's pretty worrying, isn't it? Right. So this is how you know one an infectious disease can lead to something totally different downstream as a complex interaction

which is immunological. It's also dietary related, depending on, and also potentially microbiome related because the microbiome has a lot of activity in that pathway too. Yeah, it's amazing. And what you're talking about is all these overlapping factors

that seem to be separate, right? But actually have the same underlying common mechanisms, but just manifest differently in different people depending on their genetics and predispositions and how their body uniquely responds to it. So this is really what we're talking about around precision medicine. Well, that is systems medicine to me. Systems medicine allows you to visualize the complexity of it

so that you can be more efficient and precise in your interventions. It's great. It's amazing. And you talk about this sort of patient journey phenotyping around COVID-19. Can you explain that? It's what you were talking about before of tracking what happens over time and if people regress to more of a normal phenotype. Well, this is an ongoing job. It's a big job because you have to...

that happen to be statistically powered. So what we're trying to do is look at populations and the way that they respond to infections. COVID is one of them. So if you, we have, there is lots of epidemiological studies where samples have been collected for many, many years, framing them with the original one looking at heart disease.

There's a study in Western Australia called the Busselton Study. It's a similar, it's a bit like framing where you're looking for heart disease and diabetes over a long period of time. And we've had access to the Busselton Study. So we already had run thousands of people from Western Australia

who were part of the normal population. So we're describing what normal Australian biology looks like. We've got a lot of beer in there. Well, yeah, that is part of metabolite in Australia. Beer metabolites? Yeah, fosters. And so when you're looking at... So that's a reference point. So usually you think about measuring, taking these samples to try and create new biomarkers for future studies.

events by studying the population over many years. But we can also use the reference frame for the population biochemistry. This is Australian biochemistry. So when somebody's had a journey due to COVID, they go out of that space and we can measure whether they should be within the population by mapping them biochemically through time. And in fact, we've just been given another million dollars by the state for

extending the Busselton study and resampling people now after their last sampling, which was probably five years ago, because almost all of the people have had COVID. So we can measure the before and after COVID status and we can find all of those particular

potential long COVID people that didn't maybe the occult long COVID, they don't even know they've got it and we can make medical recommendations how to improve their health knowing that COVID has had certain knock-on effects in different parts of their systemic metabolism. So this is very, to me, this is very real, this is very translational. So we're also mixing for the first time I think ever

epidemiological studies with real clinical studies, real-time clinical studies where we're monitoring trajectories of people in and out of the normal population, the normal population being defined by an epidemiological sample profile. And so that becomes, and then to have that actionable so we can find people who have latent disease as a result of COVID or anything else for that matter, and then saying, right, well, you need to go to the doctor and get this, this, and this tested and sorted out. That is very practical part of

translational. So what are you seeing with the data you're learning? Because you're doing a phenotyping of long COVID where you're seeing these abnormalities that track across symptoms and explain how people feel. And there are actually biomarkers that you can use to track the trajectory of any treatment, whether you're not treating them or you're given conventional approaches or other approaches. What kind of things are emerging that help you

think differently therapeutically about how to treat patients. Because it's not a single pathway that creates a single disease with a single drug, right? It's a very different, you're talking about systems medicine. So how do you start to apply what you're learning to patients with long COVID? Because there's millions and millions and millions, anywhere from 6% to maybe up to 30% of people. And maybe you're saying 100% of people have asymptomatic long COVID. Wow. What do we start to do with that data?

Let's start with what the statistics are. There are a lot of statistics around, a lot of studies now on long COVID. I think the correct number is about 6 to 7% of people have some sort of symptomatic long COVID, maybe at two years, even three years now. And if you've got it at two or three years, you're probably not going to get rid of it. It's become a chronic disease.

disease. So that's the first thing is putting biochemistry around that, that allows you to say, well, look, let's look as though you have long COVID based on this biochemical profile. Now that's actually quite important to people because a lot of doctors, as you know, do not know. Well, they say, yeah, well, you're feeling tired, you know, it's your age and it's easy to dismiss. And that's what a lot of chronic fatigue patients have actually experienced. A very poor response of the medical community.

community. And that's what I had chronic fatigue syndrome and I had to cure myself from that. That's how I learned all this. It's, it's, it's miserable. Yeah. It's horrible. The worst thing you could possibly imagine. It's like you haven't slept for three days, but you just woke up. Well, I had, I did, I had a long COVID, um, as a result of getting COVID in the first wave, um,

I was one of the first people in Australia to get it because I'd gone to a conference in Italy in February 2020. Do you remember? That was one of the first ones that kicked off. And I came back so tired when I got back. It must be jet lag. It was jet lag that didn't go for three weeks or four weeks. And two months later, with our own technology, we diagnosed...

that I actually had had COVID because my biochemistry three months after I'd had my episode was still the same as active COVID patients. So this lived experience gave me a little bit of insight into what might be going on. But I can tell you, I don't have to tell you, chronic fatigue is truly miserable. Fortunately, I think I'm largely fine.

through that, but it did leave me with diabetes. So thank you very much. - Like type two? - Type two diabetes I was left with. I also have atherosclerosis now, which I didn't used to have. - Really? - And in fact, the cardiovascular side, that's one of the... - Damages your blood vessels. - Well, and there's very strong biomarkers for that actually, which is, we're very interested in at the moment

Like what? Well, the apolipoprotein B100, apolipoprotein A1 ratio. So for those that don't know, the B100 is a transporter lipoprotein, a supermolecular complex that actually helps cholesterol get into blood vessels. This is ApoB you're talking about? It's ApoB, yeah.

And so it's atherogenic. And the A1 does the opposite. So the ratio is actually very predictive of your atherosclerosis risk because it's part of the active transport process of cholesterol. But it's also an important long-term risk for myocardial infarction, stroke. So you're saying that ratio changed with COVID. It's dramatically changed during the active infection. This work goes back decades.

30 years on the the relationships we make a lipoproteins be one and Cardiovascular disease You go from being a normal person to being an intermediate to high risk within about three days Right of catching COVID it really changed. It's dramatic right and that then persists for some time, right? and that's one of the things we monitor in the long code with people is there a ba1 and

or abnormal. And some people, well, of course, as you get older, your ABA tends to get worse and it gets worse with age.

obesity and things like that as well, unsurprisingly. But COVID causes an acceleration of that enormously. And when we were looking at samples from the UK, and the UK got it really, really bad. The Wuhan, I mean, they had people dying in the corridors and hospitals and stuff.

The people that were six months after their episode, we still have people in ultra high risk of cardiovascular disease as a result of their COVID exposure. So that's another thing. So that's something that's

the infection impacts on long-term cardiovascular health. But there's a way of monitoring that, and that's something we could do now. - You can monitor all this stuff and you see these changes. What about treating it? Are you finding any therapeutic applications of phenomic medicine? In other words, where you not just treat diabetes 'cause you have it after COVID, but where you can actually say, gee, there's these autoantibodies, for example, that are forming against your nervous system tissue, which we now can measure.

And in, for example, Europe, they're doing studies looking at plasmapheresis, where they filter the blood, clean out all the antibodies and all the crap from your blood and put in new protein and put back your cells. And they're finding significant improvement. I've personally seen with my long COVID patients, it's one of the things that really helps a lot. So I'm wondering if the biochemical profiles with the right therapies could actually go back to a more normal pattern. Yeah.

And not even the occult long COVID pattern you're talking about. Yeah. So, I mean, so all those things like plasma, phoresis, et cetera, I mean, it's difficult. When you're talking about millions of people, that's not really very practical. Not scalable, no. Okay. So for your patients, they're lucky, right? Yeah. And we're lucky actually in the West that we can do something about this in the developed world.

But there's a lot of people that can't do anything about it. So one of the things we're thinking about, so let's just come back to tryptophan pathway for a minute. There are drugs, you know, the indomethacin is a good old drug, an IDO inhibitor. It's sort of banned, certainly banned in Australia because it causes problems in long-term sort of renal insufficiency, renal papillary necrosis and things like that. But there are obviously, once you start to find particular molecular targets,

that are abnormal, whether it's in COVID or long COVID, then you can think about drug therapy to selectively try and change that. But we were actually interested in sort of dietary intervention. So for instance, you get a lot of the tryptophan, et cetera, from the diet. Just restricting tryptophan is not the solution because one of the...

Effects of long code is actually having low low tryptophan. Yeah, right anyway, and the part of that is because it's metabolism is accelerated So just adding more tryptophan does not help especially if it's been metabolized to quinoline acid, which is poisonous Maybe b6 could help because it activates that enzyme indeed. So so again

Again, thinking about alternative drugs which we might use, but also we found that there are sort of natural inhibitors. There are several natural products in certain foodstuffs in plants. Phytochemicals. Yeah, phytochemicals, exactly, that inhibit...

some of those enzymes in that pathway and we we haven't done it yet in the next year we will do some sort of nutritional intervention study where we're adding these phytochemicals all the original material it turns out that the the plant sage has got high levels of these things so sage might be a natural if you like cure uh for long covid but don't quote me on that because we haven't proved it yet but but but we're thinking about this in this holistic way that

You learn about the biochemistry, you think about, well, can you fix it with a drug, or can you fix it with a dietary intervention? Life-solve diet, the exposure, right? All of those, all of those. Fixing your microbiome, who knows? All these things can start to be therapeutic tools, and then you can track how they're doing across this continuum to disease. But the solution for you might not be the same as the solution for me. Exactly. Because that's precision medicine. That's why you have to kind of map out each person's individual... Exactly, yeah.

- Yeah. - Kind of biology, which is what phenomic medicine really is about. To me, it's what I think is one of the most exciting areas in medicine, which is finally the understanding that the way we're looking at disease is so outdated based on individual diagnoses that are all treated the same by conventional medicine.

these patterns in the data that you're seeing with deep phenomic analysis, even within long COVID, for example, they're not, it's not a uniform condition and different people have different manifestations of it. And the treatments are going to be different depending on what it is rather than just a one size fits all treatment. So that's kind of the promise here. I wonder, you know, how, how do you see this kind of,

one, five, 10 years from now, is this gonna be in the clinic? Are doctors gonna be doing this? Are we gonna be able to get deep phenomic analysis of us? Because I co-founded a company called Function Health, which is essentially designed to get a deep phenomic analysis

analysis of each individual and use sort of medical intelligence and computing power to help make sense of it, like you're talking through math, right? - Yep. - And we're going to get regular blood work now. We're measuring Apo A and Apo B and all these things that we're talking about. We're also gonna be looking at your omics and metabolome and microbiome, your genome. We're gonna be looking at biosensor wearable data, your medical history, looking at all that information.

In order to help create a kind of predictive model of where you're headed and what you can do along that continuum and hopefully get to 100 healthy years. But we're doing it outside the healthcare system because it's so hard to change things from the inside. Oh, yes. Right? And people want it. They want to know their data. Yeah.

So where do you see this sort of going and how do we start to adopt this? And you're doing a lot of the hard grunt work in the lab over decades that have gotten to this point, but how do we get to kind of where this is available to everybody? Yeah, so I was previously the head of surgery and cancer at Imperial in a big clinical academic department, which was immense fun for 10 years. But I became limited. Sorry, this is a...

Not as bad as it sounds, but limited by the National Health Service. So the National Health Service is a fantastic institution. I am a big fan, right? Because it does so much good for so many people for no money, right? Personally. But it's also like a leviathan. It's difficult to shift its direction, right? And I became quite frustrated with that. And that was one of the reasons I wanted to move to Australia to build a new lab more connected with Asia. Wasn't it better weather? The weather is truly extraordinary, right?

So it's 101 outside in Las Vegas today, and that's pretty common for about three months in Western Australia. But anyway, one of the things was to set up a phenome sensor that actually was trying to address not just clinical problems,

It's on a hospital campus when our lab is but also the epidemiological type problems, but also, you know diet healthy nutrition as well So we're thinking about you know humans in the total environment and there's a way of and the the Australian doesn't have a National Health Service in the way that UK has and

And it has a lot of linked hospital services, but it's federally funded and it's very well funded from the point of view of medicine. So one of the things that we wanted to do is have this more holistic approach that we thought would be easy to implement in Australia. But we've already got two

I think two translational diagnostics that have come out of the COVID-19 work that aren't actually really related to COVID-19 at all. So we've found a better way of measuring ABA1 on a really small NMR spectrometer. So a lot of the work we do is on these discovery spectrometers, which are $2 million each. Well, we've now got it working on a $100,000 machine, which is still expensive, but

the actual reagent cost is zero. So it's radio technology, so it's reagent-free technology. And we've patented that, and we're now looking at translating these miniature NMR spectrometers to the clinic for general cardiovascular assessment. So that's a translational step. The other thing is that it's really fascinating, and actually a discovery from acute COVID,

is we found a load of really weird and wonderful metabolites, initially in the urine, but we found them in plasma as well, that are all cytosine derivatives. And when you look at them, if you're in medicinal chemistry, you go, that looks like an antiviral drug or that looks like an anti-cancer drug. We've now found a dozen of them. They're completely new to human biology, right? Published just a couple of months ago.

And it turns out that they're part of an ancient immune system, the viperin, the virus inhibitory protein mechanism, that creates antiviral drugs when you have a virus infection. Your own body. Your own body. And so the drug companies think they invented combinatorial chemistry. Actually, nature did it about 3 billion years ago. So we discovered a whole new piece of biology. Right?

from COVID-19 urine patients. And that turns out to be relevant for all viral infectious diseases. There's now a urine test for active viral infection, which comes from our work on COVID-19. When I was at Imperial, I was the head of...

Intensive care came to me one day and said, you know, if you've got a test that could distinguish people of active viral infections versus bacterial infections, that would be really useful. Because at the moment, we've got to do lots of different testing sometimes a day. We've got something now that can do it in two minutes. That's right. Which...

but that came out of the COVID research, right? - So it's not gonna be one single thing, but you're gonna, you know, it's me imagining a world of future where we're gonna be able to do sort of lower cost or very low cost, like your human genome was, I don't know, a billion dollars to first decode, now it's $300, where we're gonna scale these things up to be able to do deep genomic analysis on individuals

At scale and from those learnings see the patterns in the data See what sort of signal from noise and be able to then develop diagnostics and therapeutics that help to kind of restore the body To optimal function and reverse that continuum from disease backwards towards wellness. That's kind of what the promises of this That is the promise. Yeah, but I think the important thing is it's got to be everything you do is

has got to be on a clinically relevant time scale. So with genomics, you know, if you do deep genome sequencing, I know it's got cheaper now, but it can't be done on a...

the same day. And if you think about the way that most doctors work, then they send something down to the path lab and it comes back soon and they say, crap means this and whatever it is. You need to have something where there's a turnover of just a few hours in order to make it clinically relevant for actionability. There's no point in being able to diagnose something six months later. And so we're very committed to the translational technology that gives you rapid

Because that's really impactful. Yeah, and I feel like we're just at the beginning of this frontier where first is understanding the biology and then is figuring out how to apply novel therapeutics, which aren't going to be, I don't think, a single targeted therapy.

pathway or mechanism, but really understanding a systems approach, what Lacoste and Barbarosi call a multimodal approach to multi-causal diseases, right? Using multiple kinds of things, like you have to treat all the things that are going on, not just one. So, I mean, I'm just so excited about this. I'm so excited about the work that you've done at your institute and the ability for us to learn from that, and particularly around long COVID. I think it's one of those things that's causing so much disability, so much disease, so much suffering.

It's a little scared me a bit when you said that everybody who's had COVID has some biochemical signature that there's still dysfunction going on. It's probably true of influenza and other diseases as well. It's just that we don't know it. Yeah, it's quite amazing. Well, again, thank you so much, Dr. Nichols, for your work. We're going to keep following it. I hope everybody learned something. I think, you know, this is a fairly high level discussion, but...

Why I wanted to bring it to you all was because this is where medicine is going. This is what you're all going to be getting, hopefully, in the next five to 10 years, more and more. And I think with the advent of machine learning and AI and technology and our ability to do deep analytics and phenomic analysis, we're going to learn so much. And this is going to be today what seems like the dark ages in medicine. And we're going to have the light shown upon us to understand these

the deep biology of what we're actually now understanding is the true nature of disease, which is a systems problem. It's a network problem. And we have to treat things that way. So thanks so much for being here at the Institute for Functional Medicine. You came a long way from Australia. And I saw you were coming. I'm like, I got to have you on the podcast. So thank you so much for joining us on The Doctor's Pharmacy and for your work and contribution to the betterment of humankind. Thank you.

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