In this sixth episode, Tommy Wood, CSO Nourish Balance Thrive, explains that the majority of modern disease is caused by our environment and as such, under our control. He shares his experience that A.I. coupled with ordinary blood tests, can inform us of changes we can make to protect/optimize our health, or when sick, lower the cost by predicting which further tests to conduct.
Lee: Hello, and welcome to the Hyper Wellbeing podcast, Tommy.
Tommy: Oh, thanks for having me.
Lee: Tommy, let’s just jump in here. You still look young, you’ve got a fantastic resume, or as the British would say, I think, curriculum vitae. Where is the motivation coming from? What’s your driving force? What’s the mission you’re on?
Tommy: I guess I do have one, or I have two that I work on, alternatively, on essentially a daily basis. The first being that I believe that most chronic disease that we face today, is largely a result of our environment, and therefore, we ultimately have control over it. That’s pretty much what humans do. We are where we are today because we can control our environment. That’s one aspect of what I do. And the other aspect is neonatal neuroprotection, which is completely separate, although coming together in multiple ways, but that’s essentially babies who are born with some kind of brain injury, born prematurely, and then try to find ways to treat that. I think that those require fundamentally different approaches because it’s something that we ultimately have some control over. We may be able to prevent, many, many years in the future, most chronic diseases.
Tommy: The other one is these things just happen, and largely, at least currently, they’re out of our control, and therefore we may need more intensive therapeutic applications, more intensive modern medicine, which is something that we’re working on. Whereas, some of those metabolic and chronic diseases that I think we’ll talk about a lot today, I think they’re more in personal control, may not even need a health care system, if we knew how to look after ourselves properly. Those are the two missions, and things that I like to work on.
most chronic disease that we face today, is largely a result of our environment, and therefore, we ultimately have control over itTommy Wood
Tommy: I guess a lot of it comes from the fact that when I was growing up … You mentioned my CV. When I was growing up, it was instilled in me by my parents, who were both academics, that it’s important to get a good education. I do believe in that, and I’ve been lucky to be educated in some of the best institutions in the world. But then also, that work can be fun, and it’s entirely up to you. Nothing was ever micromanaged. Nobody ever asked me if I did my homework, I just had to crack on and do it myself. Then you know that you get out what you’re willing to put in.
Tommy: Where I am today is largely because I really enjoy what I do. I really enjoy talking to people who share common interests with me. Often, the connections and things that I’ve made, have involved me offering any help or information I might have with no real goal in terms of reciprocation. There’s always somebody who’s interested in talking to you, and maybe … I certainly don’t pretend to know everything, but maybe I know something I could be helpful with, and I’m willing to give your time, willing to give your thoughts and input, and then eventually some great stuff can happen down the line. That’s largely where I’ve … Largely what’s resulted in me being where I am today.
Lee: I greatly appreciate you take that attitude. I did actually pick up on it. We’ve never spoke before, but I’ve heard quite a few podcasts now with yourself on it, and I picked up on impression that you’re, what we’ll term, open. We’ll call it social. You make yourself available when you can, but I also pick up that you’re very pressed on time.
Tommy: Yeah, that does happen. I guess it’s a downside of … I guess it’s if you’re good at what you do, and I do like to think that I am most the time. I won’t pretend that it’s a uniform thing, but then particularly as you become involved in more things, or become more senior in various areas then more people want more of your time, and then it becomes … I now have to be a bit more selective than I was maybe a few years ago, but it’s still very important to me to be as open, and offer as much of my time as I can, because you never know what’s gonna come out of it.
Lee: Well, I appreciate getting a piece of Tommy, and I hope the good karma comes around. I saw that you also added another hat earlier this year as Research Scientist at the Institute for Human and Machine Cognition. Could you share a touch about the IMHC and what you’re doing there.
Tommy: Sure. So the IHMC is a non-profit research organization based in Florida, and the founder and CEO is a guy called Ken Ford, who’s probably one of the most decorated scientists that the U.S. has to offer. He was the White House Scientific Advisor for George Bush. He has won various medals from the National Science Foundation, which runs the funding for most of the non-biomedical research in the U.S., and NASA, and is incredibly well-connected, and incredibly intelligent, and just this fabulous and fascinating human being.
Tommy: Through some mutual friends, mainly Chris Kelly, and I think he got introduced to Ken through Robb Wolf. So everybody here is the sort of … Always hung out in the low-carb and keto areas at one time or another. Chris introduced me to Ken, and Ken without really knowing who I was, agreed to jump on a call with me and talk about some of my career options. This was a few years ago when I was finishing my Ph.D., and I was moving to the U.S., and I wasn’t really sure whether I should do a Post Doc, keep working in a lab, keep developing the academic side of my career, or just dive straight in and work full time with Nourish Balance Thrive, which is the company where I work optimizing health and performance in various people.
Tommy: Ken was willing to give me half an hour of his time to give some thoughts, which I really appreciated, and was actually very influential in what’s happened with me so far. We’ve been communicating regularly since. We have lots of common interests in health and performance. I’ve been to the IHMC to take part in small meetings, brainstorming about human training and performance, and that’s a lot of what they do is looking at the performance of humans in extreme environments. They have a lot of military contracts, they do a lot of work with NASA and astronauts.
Tommy: When I finished my Post Doc, Ken advised me to join as a visiting scientist, which means that I can use their resources to do some of my own research in health and performance, which is something that I am very interested in. But then, I can also potentially take part in some of the research that they’re doing. My own research, my Ph.D., my Post Doc, and now I’m just starting as a professor at the University of Washington, looking at hypoxic brain injury, largely. And obviously hypoxia, or low-oxygen, is something that a lot of those people performing in extreme environments get exposed to. So pilots, astronauts, there’s many times that they might be exposed to low levels of oxygen, which affects how your brain functions. They’re doing more research on that, and hopefully some of my expertise can be used there.
Tommy: It’s a great honor to be part of their incredible team. They have one of the best podcasts, I think, out there, Stem Talk. I’m just excited about what we can do in the future.
Lee: Yeah. I love Stem Talk, and I agree with you. It’s a great podcast, and also their videos on YouTube. You mentioned performance. If I quote you online, you state … A core interest of yours is easily accessible methods with which to track human health, performance, and longevity, so if we can focus there for a bit. Can you give some indication what these methods are across health, performance, and longevity?
Tommy: Absolutely. So there’s a big focus on this now, and coming from two different directions. I guess there’s the people who want to optimize health and performance themselves, which is a lot of the people that you and I interact with, and maybe a lot of the people listening to this. Then, there’s research efforts and efforts in the medical community to try and reduce the process of aging. A lot of the research focusing now, suggests that long-term health is going to be, or sustaining long-term health, is basically gonna be due to the process of preventing, or slowing down, the processes that contribute to aging.
Tommy: Then the question becomes, well, how do we measure aging. This is also very relevant to long-term health and performance because particularly if you want to perform at a given thing for a long period of time, and that could be cognitively at work, it could be in a sport that you participate in, it could be in your family life, just being old enough to play with your grandkids, or your great-grandkids. That could be your performance goal, and all of that is going to come down to ensuring that we’re having the right balance of growth, repair. That’s where a lot of the target of aging, or anti-aging, medicine is nowadays.
Tommy: We’re thinking about measuring these processes, there are a number of different ways we can do that. Telomere testing, people have heard of, which is very unreliable and usually unnecessary. I think a lot more interesting than that is going to be looking at epigenetic modifications of DNA, which is increasingly well described in the literature, but if you want to do it on yourself, it’s gonna cost you several thousand dollars, and you’re gonna have to wait several weeks for the test to come back.
Tommy: Myself, and the people that I work with at Nourish Balance Thrive, and Dr. Bryan Walsh, we wholeheartedly believe that you can get a lot of data, and most of what you need from subjective quality of life and simple blood tests. We’ve been building machine learning models to predict states that affect athletic performance from subjective questionnaires. So if I ask you about your sleep, your sex life, and whether you feel socially isolated or you enjoy your job, if we ask you those questions on a scale of one to five, and we feed those numbers into a machine learning model, I can predict if you have, say pre-diabetes, based on your subjective quality of life.
Tommy: That’s not necessarily that surprising if you know some of the things that can cause pre-diabetes, and I think that’s something that we’ll talk about as well. I can predict some of these early stages of chronic disease just by asking about your quality of life. I don’t need to do a fancy test.
Tommy: If we go up a step, maybe you can do a $50 blood test, something that anybody can get from their doctor, or in the U.S. now you can order it yourself, can we then extract more data from that? Is there something there? Is there some underlying signature of, say aging, if that’s where we’re gonna focus, that we can extract from that data. We do have some machine learning models, again, to … We ask the algorithm. If we give you these previous 100,000 blood tests, we tell you the age of the people they’re associated with, if I then give you this new blood test, how old do these blood test results look? Then, we have a model to predict chronological age. Sorry, but its biological age rather than chronological age. Your age in years.
Tommy: Other people are doing this. There’s a group called Aging.AI, based out of a company called Insilico Medicine at Johns Hopkins, and they have used … They have access to datasets just like we do. We have similar outputs, we use different algorithms to get our answer. The reason why I like our approach, and Chris has been building machine learning models that are explainable. The important thing is, great so you get an output, it tells you what your biological age is, what do you then do about it? The problem with a lot of machine learning algorithms is they’re a black box, so you don’t know why the algorithm thinks what it does.
I can predict some of these early stages of chronic disease just by asking about your quality of life. I don’t need to do a fancy test.Tommy Wood
Tommy: We’ve been developing explainable machine learning models so that I get an output that says “All right, your biological age is 10 years older than your chronological age.” So maybe I’m 34, I do my blood test, and it says I’m 44. I want to know why that is. So now, we can get that output out, and we can see there are some things that are in there that then I know how to manipulate. If you have elevated fasting blood glucose, or triglycerides, or there’s a number of metrics with your red blood cells that are very important. The mean corpuscular volumes, the average size of your red blood cells tells you something about nutrients, as does the red cell distribution width, how variable your red blood cell size is. We know these things correlate very closely with mortality as well, so then I can think of interventions, be they nutritional, or other lifestyle things. I can then manipulate those specific markers, and if they come down, then hopefully my predictive age comes down.
Tommy: The caveat is, if I do something to bring down my predicted age, or my biological age, does that mean that I will actually live longer? And the answer is, we don’t know yet. Hopefully, we found something that allows us to personalize an intervention that looks at the aging process in individual people, using very easily and cheaply available data. However, if that then results in them living longer, we just have to wait and find out, and hopefully run some studies and see whether it works out that way. I’d be surprised if it didn’t.
Lee: And if it’s not lifespan, it’s certainly gonna be healthspan, Tommy.
Tommy: Yeah, absolutely. I completely agree. There’s still a debate in terms of how long the human can actually live. Many people think that we’re probably gonna top out somewhere in the 120 years old, somewhere around there. In reality, most people don’t necessarily want to live longer, they just don’t … They want to have more life in their years rather than years in their life.
Lee: You want a complete systems failure right then, instead of lots of bugs and patches along the way. A rectangularization of the mortality curve.
Tommy: Exactly. I like Mark Sisson‘s version of it, which is “Live long, drop dead.” That’s essentially what …
Lee: Yeah, that’s perfect. I don’t know if you’ve had a chance to listen to any of my previous five guests in this podcast Tommy?
Tommy: No, I haven’t I’m afraid, but I am excited to listen to those. It’s been a … I actually haven’t listened to any podcasts the last few months just because I’ve been running around and traveling and stuff, so I’m … It will definitely be high on my list once I get back into my podcast listening in the next couple of weeks.
Lee: There’s some amazing overlap with a lot of what you’ve said, so I’m wondering which specific part I should pick up upon. I’ll pick up critically first. I ran the … I’ll pick up on the more negative one, which was I ran the bloodcalculator.com, which you’ve been involved in, and we’ll speak about that later. But in terms of the biological age score, which I know is not the main feature, it said I was 65 if remember, something of that order.
Tommy: Oh, wow.
Lee: But, I’m 42. Then my girlfriend, who’s 23, did it, and she had something like 60 years old. That was about … I can’t remember, but it was quite some time ago. So hopefully, that’s moved along. I also used the Insilico Medicine one, which required a lot more blood markers, and it wasn’t actually any better. So thought that it’s nice that people are applying AI to blood chemistry. I’m sure those models will get better. I’m very confident of them, but at the moment we’re at a very nascent stage, was my conclusion.
Tommy: But the Insilico Medicine, the Aging.AI version, and the blood calculator version, tended to agree, or were fairly close in their prediction?
Lee: They were … No, no, no Tommy, don’t depress me. They were fairly close in their prediction. It wasn’t like wildly … It wasn’t in order of a decade. I tell you Tommy, I’m looking good, I’m feeling good, I’m very fit, so I’m hoping something is not quite right more in the AI, and the data, then the actual physiological end here!
Tommy: Yeah. This is a big part of what we’re trying to figure out. The important thing is that these processes are very objective. And yes, a lot of the data that’s publicly available … So we have some of our own data from … We have a few thousand athletes worth of data, which are part of the models, and then there’s some publicly available data that comes from just average people. Then the question is, should I be comparing the blood test from somebody who’s fit, and active, and healthy, to a more standard, average population who are maybe not as fit and healthy? The answer is, right now, we don’t know.
Tommy: Something that we see very commonly, particularly in chronic, high-volume endurance athletes, their predicted age is usually one or two decades older than they actually are. So now the question becomes does high-volume endurance exercise cause premature, or accelerated aging, which is certainly possible in some tissues. So we know it’s probably pretty good for the heart, unless we’re taking it too far, and people obviously do that. But are there other aspects of physiology, other organs in the body that are maybe being pushed too hard by the amount of exercise the people are doing, and that’s being picked up on the … The algorithm is seeing that in the blood tests. I think that’s almost certainly gonna be part of it as well.
Tommy: There’s definitely a lot to be teased out. A lot of our models … So we can predict various nutrients deficiencies, toxic exposures, hormone issues. The sicker you are, basically, the more things you have predicted wrong with you, but that doesn’t necessarily mean that those are all current issues in you. It just means that there’s this underlying flavor of sick person that you can see from a blood test that actually has very little to do with the individual numbers themselves. A human certainly couldn’t see that pattern, so it’s important for us not to just say “Well, I don’t agree with this result, therefore, there must be something wrong with the algorithm.” There’s something underlying there, we just need to figure out exactly what it is.
Lee: Yeah, can you emphasize that part … The human cannot see that pattern. That pattern is of some significance. Can you emphasize what you’re meaning there for listeners?
Tommy: Yeah, absolutely. We spend a lot of time looking at blood tests, and we have various ways of thinking about individual test results that are maybe slightly different from a traditional approach. A traditional approach is that there is a normal range for a blood test, and that normal range is developed by taking a certain number of people, it’s usually a few thousand, those people who are doing this test, and then you create a bell curve from that data. The mean, which is the average, plus or minus two standard deviations, which covers 95% of the people who did that test. That’s all well and good, except for that fact that most of blood tests that you’re taking were taken by more average people. I don’t mean average in a bad way, I just mean everybody around you. A lot of those people are having those blood tests done because there’s something wrong with them, or they’re sick, they’re seeing the doctor, that’s why they’re having a blood test done.
Tommy: It’s worth bearing in mind that in the U.S., and the UK is certainly catching up, the majority of adults, so more than 50%, take at least one medication, have at least one chronic disease, and/or at least some flavor of chronic metabolic issues, say pre-diabetes or worse. The average person is sick. Do you then want to compare your own data to a bell curve that was generated in people who, on average, are not healthy? The answer is, no you don’t.
Tommy: We have developed our own ranges, based on published data, in terms of if you’re this marker goes above or below this certain range. Mortality starts to increase, disease risk starts to increase. So we can base it on actual published data rather than just the average of the people that did the test at the lab that you’re doing it at. Then, there are certainly various ways that you can look for patterns. So how markers interact, ratios of certain markers, that’s certainly very popular in the lipid and cardiovascular disease literature, but when you’re looking at …
Tommy: So we use close to 40 different markers. Again, it’s stuff that’s very easy to get from your doctor. A full blood count with a differential. You’re red blood cells, white blood cells, your basic lipids, cholesterol, triglycerides, some liver function and kidney function tests, and your blood glucose. That’s essentially it. When you then look at 10, or 15, or 20 of those markers, and the way that they move and cluster together, that might tell you something about your predicted age, but there’s no way any human can hold all of those patterns in their head, or would even see those patterns just looking at [crosstalk 00:24:30].
Lee: I think that’s of great significance Tommy. You just say it blasé sort of thing. That’s of huge significance. It’s like “Hey, let’s stop and look at this. This is major.”
Tommy: Yeah. I think this is where … This is why data science, artificial intelligence, machine learning, in healthcare, this is where the field is exploding because there are just things … We have so much data, and there are just things in that data that the average human, or even a well-trained and intelligent biostatistician are just never going to be able to find.
Lee: But the big issue you’ve got is the healthcare today is based in the paradigm of hey we get sick first, then we get treated. Why are we not using the data science to predict, to prevent, and to optimize instead? It can enable that new paradigm. I just get a bit upset when we’re only using AI for disease care.
Tommy: I completely agree. The main problem, if you want to call it a problem, stems from the fact that where most of the money and research is focused, and where clinicians are focused, people who work in the healthcare system, focuses on improving the quality of the care that they are currently providing. That is also where a lot of the data comes from. Where are people getting blood tests done? Where are people getting various genetic tests done, or imaging, MRI scans? These people are having them done because there is something wrong with them. They are currently sick, so the majority of the data except for longitudinal tracking data done in the population on average, and many governments are doing that. There’s big datasets in South Korea, there’s some in the UK, there’s some in the U.S., which just tracks the population on average. Most of the data is coming from healthcare, so therefore, you’re going to to get a skew of people looking at that because the power is in the data. The problem is that we just … Currently, the data on optimizers, the people who are trying to optimize their health, is siloed by each individual practitioner who is working with a small group of people to optimize their health, and that data isn’t being collected so it can be analyzed in a group setting.
Lee: By practitioner, you’re meaning a functional medicine doctor?
Tommy: Well, yes and no.
Lee: Who else is working in optimizing people?
Tommy: Well, many people.
Lee: The bio hacker community, or … Nourish Balance Thrive is a bit of an outlier. Would you not agree?
Tommy: Yeah. We are. The main reason I bock slightly at the use of the word functional medicine is just ’cause I think it’s terrible branding. There is a great number of people working in the functional medicine community, that’s what they call themselves. The problem with functional medicine is that if you work in traditional, if you want to call it, or allopathic, what ever you want to call it, the word functional is usually used to describe a process that either isn’t well-described, or isn’t well-understood, or is a diagnosis of exclusion, or you think the patient is making it up. Functional is just the wrong word to use.
Tommy: That’s just my own personal bone to pick with the word functional medicine, but you’re right, that is an area where a lot of people are working on this. They are also a number of self-taught health coaches, the bio hackers, people who are doing this for themselves, and doing it in groups. There’s people who follow the Bulletproof approach, which again not necessarily the best way to do it. There are these huge groups of online communities and practitioners.
Lee: Yeah. I’m excited you phrase it that way, Tommy because that’s what I … One of the things I noticed first was let’s say people doing Bulletproof, Quantified Self, et cetera, and I couldn’t help but notice this was more the type-write phase of word processing. It hadn’t progressed. It was these silos, as you called it. It hadn’t progressed into the hardware itself and became democratized.
Tommy: Yeah, that’s … The democratization of this process, giving access to anybody who wants it, and then also getting the data so that we can do something useful with it, is something that we’re very interested in doing. Whenever I work with people who worked in the software industry, they’re amazed that the healthcare data is so siloed, and so protected, and nobody wants to share it because that’s just not the way things are approached [crosstalk 00:29:37].
Lee: Very pure from computer science or engineering. That’s why I end up speaking with Ivor Cummings, or it’s actually how I came across Chris Kelly, which is how I cam across you, from listening to Chris Kelly. He was coming from the computer science angle, which matched myself, and it’s an insane industry when you look at healthcare from computer science or an engineering in perspective.
Tommy: Yeah, absolutely. But just to come back to your original frustrations, I certainly understand them, but we just need to find a way to standardize and collect all these different pockets of data, so that we can then apply these methods to optimizers, or people who are trying to do what ever they can to improve their health span or their long-term performance, rather than relying on data [crosstalk 00:30:27].
Lee: And it’s definitely going to happen. I spotted NBT, Nourish Balance Thrive, as one of the few heralding the way.
Tommy: Yeah, I certainly hope so. That’s part of our goal. Finding a way to both do research in this area so that we can show that what we think work does work, and then also finding ways to connect people to the resources that they need, be it in terms of coaching or interpreting their blood tests, and then finding ways to bring together many different areas of data so that we can really dig into it.
Lee: Tommy, we could be here all day because every time you speak there’s another five things. It not like we’re closing tabs down here. In my mind, we’re opening tabs up, but let me jump to-
Tommy: You should see how many tabs I have open at any one given time. That’s probably a side of how my brain usually works.
Lee: Excellent. So jumping back, you had mentioned that without even doing blood testing you could go through a questionnaire of 40 or 50 questions, I don’t know the exact figure, and you could determine a person’s health issues and in some kind of rank. I happen to know what you’re talking about because I found a link, which I don’t know if it’s publicly available anymore [it is]. I mean it works, I don’t see it advertised, but I know what the link is. I followed … I don’t know. You can tell me if it’s meant to be publicly available. I followed it. I answered the 50 questions, and I was quite surprised at the accuracy of it’s predictions of what my health issues would be in order to optimize myself.
Lee: For example, it listed glucose dysregulation, one, which I’ll explain, which is true. And second, it said a circadian rhythm disruption, which is also true because I’m getting exposed to computers every night, far, far, far too late, and I’m not using blue blockers. Is that link publicly available, and could you just briefly explain what we’re talking about here.
Tommy: Absolutely. This was our first foray into the machine learning world. This is all based on our own athlete data, so these are people who I believe you would want to compare yourself to. Whenever we had people come in, they did a questionnaire, and they often did it multiple times as they worked through us. It’s all of that stuff that we mentioned earlier. There’s some questions on digestion, and sleep, and sexual health, and emotional or mental health, all those kinds of things. It’s 51 questions, ranked on a scale of one to five. All our athletes did that, and at the same time they did a huge number of tests. They did very extensive blood testing, they did a DUTCH test, to look at cortisol and hormones, they did an organic acids test, which look at microbial stuff that’s going on in the gut. Also, give you a slight picture of metabolic health, maybe what’s happening inside your cells, and they also did multiple stool tests to look at what’s going on in their gut.
Tommy: Then if you have the questionnaire data, and you have all this objective data looking at pretty much every fluid we could get our hands on, then you can … The machine picks up patterns in the answers from the subjective questions that then we can use to predict some of those things that you could see on what are, essentially, quite expensive tests. The data that we used to generate on every person who came to us was, essentially, several thousand dollars of mass spectrometry, whereas now, because we can predict a lot of this stuff, we can usually start smaller, and predict a lot of what we might want to look at.
Lee: Tommy, again, you just casually state something which is of huge significance. You just walked past that one. I do have to pause you and ask you to elaborate that for people who are listening who just are not aware of what you’re actually meaning there. Hey, we can actually, with a low cost, predict what could be wrong with you, or what you might want to test more, with simple tests.
Tommy: Yeah, absolutely. That’s … This is a big part of our goal, or my goal. Coming from the UK, I believe in socialized healthcare, I believe in socialized medicine. I believe that everybody should have access to this, and it shouldn’t be behind some kind of insurance or paywall. But at some point, you have to collect the data, and that data is expensive to collect. There are always gonna be those first people, those pioneers, that help to do that, and that’s essentially what a lot of our clients have done.
Tommy: This is freely available. It’s called our Elite Performance Analysis Tool. If you go to the Nourish Balance Thrive website, it’ll ask you if you want to do the seven minute analysis, there’s a button, and this is essentially the tool that anybody can get access to it. The interesting thing is you mentioned blood glucose dysregulation, and you mentioned circadian rhythm disruption, then all of a sudden I’m wondering maybe when the algorithm says that your blood test look older than you actually are [crosstalk 00:35:51].
Lee: I actually wondered, and I can actually-
Tommy: [crosstalk 00:35:53] together.
Lee: Yeah, I do. And I can actually briefly just say about the glucose dysregulation. I’ll take recently. A previous guest of mine, Joseph Antoun, influenced me such that I took a five day water fast. It ended on a Friday, I then pricked my finger on Sunday, and it was 6.3 mmol/L [113 mg/dL], and in your opinion it’s … I was like “Oh, bejesus.” I was cooking dinner at the time, I stopped cooking, I was scared stiff, and I went running for 45 minutes. I came back, pricked my finger again, it hadn’t changed. I was like “No, this is impossible.” I checked the next morning, it hadn’t changed. I went to hard cardiovascular training for 90 minutes, it didn’t change, it was maybe 6.2 mmol/L [111 mg/dL]. In the afternoon, it was the same. When I ate, it when up to say 6.9 mmol/L [124 mg/dL], but within an hour it was back at that 6.3. I assumed the meter was broken, an Accu-Check. I went and bought another one, it said the same.
Lee: So after a few days of panic, I went … I did a bit of studying, I went and got insulin tested, and I came to the conclusion it’s something termed physiological insulin resistance. It appears that my muscles had started to spare glucose, which I believe is an evolutionary adaptation. So once I saw that the triglycerides were low, there was no other signs of metabolic ill-health that I could see easy. Insulin was low, nice and low, but the glucose was high. You’re kind of pre-diabetic at that point. I just concluded hey, I feel well, the insulin is low, that could be the glucose dysregulation that it’s picking up upon, which may be adding to my biological age perception.
Tommy: Yeah, I’m sure it is because if your fasting glucose is elevated, that’s quite a strong input into the algorithm in terms of predicted age. If we try and extract an optimal range from the algorithm, if you’re trying to predict the inflection point. Above which point does your fasting glucose dramatically increase your predicted age, it’s around 90 mg/dL [5 mmol/L], divide by 18 to get it in mmol/L. It’s somewhere around five, somewhere between 4.5 and five. When you look at the published data, you actually see the same thing. You see a dramatic increase in mortality once you go above, around that point. And then, once you go up from there, actually mortality doesn’t increase that much, even if blood sugar goes up even higher. So most of the damage is done once you go up above that point.
Tommy: Now, if people are low-carb, or keto, they may have elevated fasting blood glucose because they have an exacerbated dawn phenomenon, but that will often be the highest blood glucose of the day, and it will then come down during the day. So does that in itself matter? To be honest, we don’t really know. However, when I think about spending very long periods of time fasting, or low-carb, or Keto, if your fasting blood glucose starts to creep up, I don’t always just tell myself it’s physiological insulin resistance, and not to worry about it. I think there’s going to be some benefit, pretty much in anybody, in keeping their blood glucose essentially below 90, below 5 [crosstalk 00:40:07] fasting …
Lee: Even if insulin is low-
Tommy: And then … Yes ’cause glucose in itself is causing issues. It glycostulates proteins, it’ll effect your circulating LDL, which may then increase it’s risk of being oxidized, which could accelerate [crosstalk 00:40:24].
Lee: Yes, I have been shown more oxidized LDL.
Tommy: Glucose itself … Yeah, glucose itself is issue. We like to focus on insulin, and maybe we can talk about that some more, but insulin itself is not necessarily the problem. It’s the upstream issues that are then causing the body to produce more insulin. Yes, the insulin itself can cause issues, but even if you’re keeping insulin low, if you have chronically elevated blood glucose, for what ever reason, I don’t think you can just tell yourself [crosstalk 00:40:59].
Lee: Well, I appreciate that. And while talking of that, for years, anytime you or Chris have mentioned an optimal range for any biomarker, I’ve snipped it and saved it. But I was … You might mention a blog or podcast, and I’ve been collecting them over time so I have a good idea what optimal ranges are instead of the lab ones, which as you said, are an average of sick people. I was wondering, does Nourish Balance Thrive publish that?
Tommy: Yeah. All of them are available through blood calculator. That is currently behind a paywall of sorts. You have to become a member to use it. We have people who frequently, if they’re interested in optimizing their health, they’ll show up, briefly pay for a membership so they can use the calculator, and then cancel the membership again, and that’s fine. We’re very happy for people to access it in what ever way they want. Then as soon as you run some blood tests through the calculator, every test that you run, that we have an optimal range for, you just see the optimal range right there on the screen. So if you’ve run your blood test through the calculator, the optimal ranges are in there, and you are free to use them however you would like. If you’re happy to share your blood test results, you can share those, and then the optimal ranges are on there.
Tommy: If you look at … Anybody can access the references that we use to make the blood calculator ranges. They are freely available on the website. Then you can go and dig around in those references and decide if we’ve picked the right ranges [crosstalk 00:42:39]-
Lee: And in health and wellness … There’s just one more thing on my mind here. In health and wellness space, there’s a lot of companies selling a lot of products for wellness, be it microbiome, or genetic testing. And although is sounds fancy, and I think it’s a relatively high-cost, I’ve noticed that most people would benefit through simple blood chemistry. Simple blood chemistry is really cheap. And then that really made me, although I haven’t met Chris, build a real connection with Nourish Balance Thrive intellectually because Chris got very excited about Brian Walsh, who has helped I understand, tremendously behind blood calculator. And bloodcalculator.com takes and … I think it’s like 39 biomarkers that are fairly cheap to obtain, I think it’s 65 U.S. dollars. I know here in Europe I pay, I think, it was like 50 Euros to get the biomarkers. It was pretty cheap. Do you have any views on this sort of expansion that you keep seeing into evermore purported benefits of microbiome, or genomics, that actually don’t offer as much value as what blood chemistry can offer?
Tommy: Absolutely. We’re at a point, still, where phenotype, which is your physiology, is much more important in terms of figuring out what you should do to optimize your diet and lifestyle, than say genotype, which is measuring your genetics. Yes, there’s a lot that is available. We often look at the gut. A lot of the people who come and work with us have gut issues. However, we’re generally looking for pathogens, or things that are in there and are almost certainly causing issues, which we then treat. If you looking at the patterns of the microbiota in general, there’s actually not as much that we know in terms of how to intervene or change that, or how those things are actually effecting physiology as some people would like to suggest.
Tommy: There are certainly a lot of companies … It’s actually very clever of them. What they’ve done is they have some stool testing technology, and they get you to give a stool sample, and at the same time, they get you to answer a whole lot of questions about yourself. Subjective questions, which I’ve already told you can be very good at predicting health issues. They also get you to do some kind of metabolic test. Maybe they get you to do an oral glucose tolerance test so they can tell whether your insulin resistant, or what your metabolic health is like. Then what you’re essentially doing … They’re selling you a stool test, but what they are doing is collecting data on your subjective quality of life, your lifestyle habits, and your metabolic health, and then they’re gonna try and mine that data to look for correlations. So upfront they’re telling you that your stool test is gonna tell you some information about your health, whereas what you’re actually doing is paying for them to collect the data to then find something interesting. There may well be something that comes out of that, but upfront you are just providing them the data to do something later on rather than doing anything that’s gonna be particularly useful to your own health in that moment in time. Most of these testing companies, that’s the stage that they’re at.
Tommy: When you look at genetics, there are many different ways. I’ve done it myself. You do your 23andMe, and then you run it through various companies, and then you get your nutrigenomics. That’s something that’s very hot at the moment. How do you alter your diet based on your genetics? The answer is, we don’t know, but people will give you plenty of ideas as to what you might want to do. But how many studies have actually tested whether you respond to a certain nutrient or lifestyle intervention based on genetics? Pretty much none. And those studies that have looked at it have shown that genetic really don’t matter that much.
Tommy: There’s also some published data where they’ve looked at commercial genetic testing and compared their answers in terms of single-nucleotide polymorphism, SNPs, compared that to a more rigorous testing in a lab, and there’s a lot of false-positives, there’s a lot of false-negatives. These commercial tests aren’t necessarily that reliable. There’s a load of really interesting information. I’m really excited about where the future of genetics and microbiome testing will go, but at the moment there are tests that we know, that we understand very well. We know the areas, we know what they mean, we know the long-term outcome. There are studies where you can see if people … If their tests look like this, this is what their disease risk is 10, 20 years down the line, and that’s blood testing.
Tommy: For the foreseeable future, I think that we should continue to focus on blood tests because we understand them so much better than all these other tests. Like I said, I’m excited about where some of this more advanced testing can go, but right now you should look at your phenotype, you should understand your own physiology, and some basic blood tests.
Lee: Not only is a blood test cheap because it’s ubiquitous, but it also hasn’t been mined as you mentioned earlier.
Tommy: Yeah, ’cause they want … People want to use the fancy data processing on fancy data, whereas blood tests are old hat, so people haven’t extracted them for all that they’re-
Lee: Yeah, so you’ve covered that very nicely. That notion that testing for the perfect diet for you, using nutrigenomics, is rubbish, and probably also microbiome testing for the ideal diet is most likely rubbish still at this point.
upfront you are just providing them the data to do something later on rather than doing anything that’s gonna be particularly useful to your own health in that moment in time. Most of these testing companies, that’s the stage that they’re atTommy Wood
Tommy: Yeah, there’s some people who are probably closer than others. The guys at DayTwo, that’s the testing company, they’re looking at gut microbiota, and they have a lot of data where … I think they took 1,000 individuals and they gave them continuous blood glucose monitors, and they tracked their diet, and saw how their blood glucose responded to various foods. Then they gave them tailored diets based on minimizing blood glucose excursions. Obviously, it was very variable from person to person, and then they correlated that with the gut microbiota. And that test is now commercially available. They went through the process of academically collecting a huge amount of data so that then-
Lee: Yeah, DayTwo is an excellent company, and it’s very nice work to correlate glucose spikes with your microbiome. And actually, I plan to put them on my invite list on this show, Tommy.
Tommy: Yeah, that’s great. I think, like I said, there’s huge potential there, we’re just not there yet. But if anybody’s close I think-
Lee: Hey Tommy, let me jump on a bit. Simply, do you think the healthcare we have today does a bad job of prevention and prediction?
Tommy: Yeah [laughter]. I guess that’s a bit of a loaded question because obviously the answer is kind of in there. In terms of disease prevention, if you’re talking about chronic-
Lee: Would you say most chronic disease is a metabolic disease?
Tommy: Yes. They’re almost-
Lee: So a majority of disease today is chronic.
Tommy: Yes. Well, and/or has some metabolic underpinnings. So in terms of preventing those, modern healthcare doesn’t do a great job, but it’s worth bearing in mind that previously disease prevention was things like infectious disease, and-
Lee: Absolutely. 20th century was a public health success. Do you see … Maybe it’s another loaded question Tommy. Do you see … You’re making me laugh here [laughter]. Do you see healthcare changing from today’s sickness model of disease care, to one I’ve coined healthcare for healthy people? One that’s predictive, preventative, aims at optimizing health. Can you seriously tell me that you see that system changing to that paradigm, or would you more align with my view that secondary healthcare is underway emerging from computer science? It’s computer science moving towards health and wellness? Or data science moving towards health and wellness. It’s secondary, it’s consumer-driven, it’s data-driven, it’s not institutionalized, it’s networked and sensor laden.
How do you alter your diet based on your genetics? The answer is, we don’t know.Tommy Wood
Tommy: Yes and no. Absolutely yes, for the kind of people listening to this podcast, the kind of people that we are full-time clients at Nourish Balance Thrive. That kind of ground up, self-quantification approach is going to become, I think, increasingly popular. Particularly as data becomes easier to measure. Your OURA ring and your Apple watch, you’re digital phenotyping, they call it. You’re basically collecting data about yourself, without really having to think about it, and then somebody can figure out how that then should be integrated into your lifestyle approaches.
Tommy: I think that’s going to become increasingly common. However, I also believe that most people don’t need that. Most chronic disease is a function, or a result, of the environment that we’ve built around ourselves. If we can help people to modify their environment themselves, I don’t really think that that needs much data. I don’t think it needs really intensive technology. Most of what I would recommend very much comes from an ancestral kind of approach, and it can be done without any healthcare, doesn’t need doctors, doesn’t need hospitals, doesn’t necessarily need-
Lee: You’re meaning, maybe don’t eat 24 hours a day. You’re suggesting something ridiculous like don’t eat as soon as you wake up.
Tommy: Yes. Something ridiculous like eat food that’s actual food, get some sleep, spend some time moving, spend some time with loved ones. For the majority of people, if they did just that, we’d save billions, if not trillions, eventually of dollars, and pounds, and euros on healthcare. That doesn’t require intensive data, it doesn’t require anything complicated.
Tommy: So yes, I’m really into advanced technologies, I’m really into understanding data, predictive models, all that stuff, but there’s just this part of me that comes back to the fact that if we could each just modify our-
Lee: Can you give a quick introduction to modifying environment? First of all, you’re including diet, and nutrition, and it but what else are you including? For example, I won’t wash my clothes in commercial soap, don’t use fluoride toothpaste, the list goes on. I store food in glass. Is it this type of modification you’re meaning?
Tommy: Yeah, absolutely. All of that becomes important in various different areas. The exposures that we have on a daily basis, that’s something that we, again, we try and predict with the calculator, some of the more common things. But equally, there’s a common sense approach to this that can be taken. So food, like you mentioned, we can … People love to argue about macronutrients, and whether we should be eating animals or plants. I think for most people it doesn’t really matter that much, as long as you’re just consuming food in a way that your body is used to seeing it. Industrial processing essentially divests the macronutrients and the calories from the hormonal responses that we have to them.
Lee: That was very succinct, Tommy. That was very elegant.
Tommy: Thanks. So basically, as long as you’re not doing that, you’ve probably done … Again, we’re talking about the Pareto principle. The 20% that gets you the 80%. That’s probably all you need to do for food. Filtering your water-
Lee: Is that only in America, or is that also in continental Europe?
Tommy: I would … I think it’s worse in America. I would probably do it anywhere. There’s … Particularly, say if you were in Britain, there’s still gonna be pipes that are breaking down, leeching iron or lead. And there’s a really nice paper that came out in the U.S. that looked at lead exposure largely from municipal water. It’s obviously within … In most places it’s within the amounts that the government says are okay, but that lead exposure accounts for … Or by their calculations, accounted for about a third of ischemic heart disease. It was something like 20%-
Lee: I’m using a charcoal filter. Is that good enough or do I need the more expensive reverse osmosis?
For the foreseeable future, I think that we should continue to focus on blood tests because we understand them so much better than all these other tests.Tommy Wood
Tommy: A charcoal filter that’s been … So the commercial filters will tell you what they’re filtering out in what quantities. A charcoal filter should reduce the lead content. You should be able to get data from the company that’s made your water filter. The average Brita water filter, say, does not filter out lead, but they do have filters for lead, and they’ll tell you how well they work. I, personally, use a reverse osmosis … I have a counter top reverse osmosis system. But again, the important thing is reduce the overall exposures without completely going crazy about it. The majority of the water I drink is reverse osmosis filtered by myself at home. If I then have tap water somewhere else, because I’m thirsty and I need some water, and that’s all that’s available, I don’t worry about it because this is total exposure thing rather than trying to get rid of everything. You can drive yourself crazy trying to do that as well.
Tommy: So water, then I guess organic food may be more beneficial. Particularly, there are certain pesticides that some people don’t respond well to. Then all the other things that you talked about. Storing food in glass rather than plastic, minimizing the number of cosmetics that you use, phthalates and parabens and stuff. That’s something that we see fairly frequently. If we look at … We used to do some more advanced testing-
Lee: That calculator was claiming I’m using anti-bacterial hand washes.
Tommy: Yeah, so there’s two parts to that. Just to finish my thought, that’s often the impetuous that people need to then go through their personal care products and think “Actually, maybe I shouldn’t be using that.” I think that that’s generally a good thing.
Tommy: There’s two parts of it. One is some of the predictions look very similar. There may be something else that looks a lot like an anti-bacterial hand wash in terms of the phenotype, and then you get both predicted at the same time. That’s something that we’re actively working on. The other thing could be that you were previously exposed, or again, exposed to something that causes a similar phenotype. So we can’t predict everything, so there are gonna be many things that you’re exposed to that cause your blood test to look like you’ve been exposed to something that the has seen before. There’s some overlapping predictions that may be something else, that looks like … On your blood test that looks like anti-bacterial hand soap. That’s just part of the deal of machine learning is that the algorithm can only predict stuff that it’s seen previously. Those are a finite number of things currently, so there’s always going to be a bit of detective work based on outputs and stuff like that.
Most chronic disease is a function, or a result, of the environment that we’ve built around ourselves. Tommy Wood
Tommy: When you do a test, any test, any diagnostic test, there’s gonna be false-positives, and false-negatives. That gives you the sensitivity and specificity of the test, of which all the predictions that we have on the calculator, those are available on the website. You can see what the sensitivity and specificity are. But what you need then, is a pre-test probability. You know what’s the likelihood that I have been exposed to anti-bacterial hand wash, such that it will effect my blood tests. If you know that that likelihood is very, very low, then when your pre-test probability is low, then when you get that outcome, you can be fairly certain that that’s maybe not an issue for you. We give you all this data, but it still requires some thinking through. It requires cortical input from the user.
Lee: Is that model continuously learning? I’ve never heard Chris or yourself state that anywhere, and it might be obvious that it is. Chris only speaks that he had, I don’t know, it was 1,000 people. He kept a few hundred behind to check the model after, but I’ve never heard it said that this model is continuously learning.
Tommy: Yeah, so for the subjective questionnaire data that we talked about earlier, that’s 1,000 of our own athletes. For the blood tests, [crosstalk 01:00:29] prediction [crosstalk 01:00:30]-
Lee: But it’s always increasing and you’re always checking the model?
Tommy: Tens of thousands. So yes and no because what … As we get new silos of data, which is happening, then the model is retrained, or the models are retrained. When we get some … We are on the side, collecting people who have all the input markers, and have tested a certain outcome. Say if we predict elevated mercury, and they’ve done a Quick Silver Mercury Tri-Test to whether they actually have elevated mercury, then we can feed that back into the model. The continuously learning part doesn’t happen automatically, but as we have robust sets of data to add back in, then they get retrained.
Lee: Okay, appreciate it. And for your interest I did bloodcalculator.com, I also went through the top five, and then I double checked it by asking my girlfriend to do it. Just to give you an example, for me it listed cryptosporidium up there in the top three. I did have crypto 15 odd years ago, caught if from a public swimming pool. I found … I thought “Come on, it was so long ago, how is that possible.” Then I had my girlfriend do it, and it listed high, in top five again, or top three, that she’d been exposed to a wood paint, a type you put on fences. It just so happens she’d spent the summer helping her grandmother repaint a wooden fence. So how does it come up with that pattern for something that occurred almost two decades ago?
Tommy: So again, it comes back to what these patterns look like. Cryptosporidium … The predictions on the calculator are based on having positive antibodies to a certain infection, so that’s where the test data comes from. It’s possible that a previous infection leaves a lasting signature in the blood test data, that’s one option. The other option is that there are other infections or other things that you were exposed to that look like cryptosporidium in terms of the pattern that they produce. And then you have one of those, but the algorithm knows cryptosporidium, so that’s what gets predicted. Those are both possibilities. It’s also perfectly possible that you’ve picked up crypto again, if you haven’t ruled that out [crosstalk 01:03:13].
Lee: I think you know when you have it, let me tell you that.
Something ridiculous like eat food that’s actual food, get some sleep, spend some time moving, spend some time with loved ones. For the majority of people, if they did just that, we’d save billions, if not trillions, eventually of dollars, and pounds, and euros on healthcare.Tommy Wood
Tommy: Yeah, well I guess it sort of depends on what your normal state of digestion is. That’s one of the things that we pick up fairly frequently, and people are often like “Oh, yeah. I get a bit bloated, and I have some gut issues.” So you may have been effected very severely, but it’s something that we see when people, they’re like “Oh, I have this kind of meal, and yeah I don’t really feel very good, or I get a little bit of diarrhea, and I don’t really worry about it.” ’cause they think that that’s normal. It does kind of depend, but there could be something else that looks like crypto.
Tommy: It’s the same for other environmental exposures. So maybe there’s still some stuff hanging around from when your girlfriend was painting these fences, or maybe there’s something else that looks like that on blood tests. So again, it’s what’s likely, what’s happened. It’s not a diagnostic tool, it’s to help you figure out where you might want to look in terms of then improving your long-term health. So it allows you to really narrow stuff down, with a huge amount of data that you didn’t have access to previously, but it does still require a bit of detective work on your part. We’re working on making the detective work that you have to do much less because we want it to be a really useful tool that anybody can use.
Lee: Do you think you are democratizing functional medicine, even though you hate the term?
Tommy: Yes [laughter]. Absolutely. That’s a big part of what we want to do. We … The calculator focuses, or is pitched, mainly at practitioners actually. So people, and it could be anybody, it could be a functional medicine practitioner, an M.D., or somebody else, who’s using this. Or it could be health coaches who want to … Personal trainers who want to provide a bit more input into their clients diets and lifestyles than they were able to do previously. I think that, that process is the democratization of healthcare. Giving people access to this information as cheaply and easy as possible.
Tommy: At the moment, it still requires some knowledge of the nuances of how the test works, and how blood tests work, but maybe eventually we’ll get to a point where anybody can do this and it’s pretty foolproof, and it will give you the top three or four things that you can do to improve your health. But again, like I said, the other side of that is that I could probably tell you what most people need to do to improve their health, the question is whether I can get them to actually do it.
Lee: Appreciate that. I see the time here Tommy. Just a couple more questions if I may?
Lee: So jumping back to the issue that health is not … Healthcare today views health a binary – sick or not sick. You, at Nourish Balance Thrive, have a lot of individuals who would be classified as healthy. Can you give any insight into what issues you’re seeing in people who are allegedly healthy? That’s people who are not manifesting outward symptoms. What I want to do is make the point that probably half the population is not healthy, even if they would be classified as healthy. Give an example of what we’re meaning by optimization, and the fact that there is no such thing as a healthy person. It’s a spectrum.
Tommy: Yeah, this is … There’s this interesting thing that’s going on in the functional medicine space, if we’re gonna keep using that term. I understand why people use it ’cause everybody uses it. It’s that people know [crosstalk 01:06:59]-
Lee: Can we use any other term I wonder?
Tommy: Yeah, so there was a time when we were using the term sustained health engineering, but it’s a bit of a mouthful, but it does what I want it to do. It’s not really medicine. It involves a system based and root cause approach, so therefore, it’s more like engineering. The idea is to sustain health rather than treat disease. That was our term. If somebody can think of something that’s a little bit more concise, I’d love to hear it because I think functional medicine does need … In my mind, it needs to be rebranded just because the terminology is always gonna be at odds at what’s happening in more traditional healthcare.
Tommy: There’s a problem in that more testing means that we can potentially start to say that everybody’s sick, or there’s something wrong with everybody. There is some push-back from that. There are other people in the space who are rallying against all the extra testing [crosstalk 01:08:13] because they’re-
Lee: The ‘worried well’, Tommy.
Tommy: Yeah, that’s exactly it. These people worry about creating more of the worried well. I do worry about that too, but equally I think that there’s a lot of stuff that we know and we are increasingly seeing from the data that I don’t want to then normalize sickness. I think there’s some people in the functional medicine space that are almost normalizing sickness because they’re too worried about creating the worried well. It’s a fine balance, don’t get me wrong.
Tommy: But things that we’re seeing, and I think this is generally what’s happened, is that people don’t know what it is to feel good. You’re constantly … People talk about dips in blood sugar, that’s why you feel tired in the afternoon, and that’s why you need to eat all the time. And like I mentioned earlier, in terms of digestion and they’re like “Oh, everybody gets a bit bloated, or a bit constipated, or a bit of diarrhea from time to time. That’s just normal.”, and so we’ve lowered the bar in terms of what normal feels like. You don’t really realize that until you actually feel really good. That’s something that we notice in a lot of the people we work with. The interesting side of that is that as you start to feel better, then your normal becomes much better than often it’s very hard to look back and think “Oh yeah, I didn’t really feel good before,” because your normal is slowly changing. Finding ways to quantify that improvement is important as well. Blood tests are part of that.
Tommy: People who gravitate to work with us tend to have a lot of gut issues. That’s something we talk about a lot [crosstalk 01:09:55]-
Lee: But that’s the population at large, would you not say? It’s not just the people who work with NBT, right?
It’s not really medicine. It involves a system based and root cause approach, so therefore, it’s more like engineering. The idea is to sustain health rather than treat disease. Tommy Wood
Tommy: Yeah, absolutely, but this is something that is happening in the population at large who would otherwise think-
Lee: Yeah, can you elaborate on gut issues, e.g. parasites, and other things you’re seeing in this population typically? Just to give an idea ’cause most people seem to think they’re healthy, but a lot of the population, for example, has SIBO.
Tommy: Yeah, and that in itself, requires a diagnostic process and then some treatment, and is becoming a recognized thing in the gastroenterology community, which I think is important, SIBO is. We see a lot of people … Again, it’s a function of A, what’s happening in the general population, but then also what’s happening in the people that work with us. Many of them are athletes, or compete in some kind of sport, or train regularly. They don’t need to be elite level, but many of them have that kind of aspect of their lifestyle.
Tommy: There’s a number of parasitic infections. We see a lot of people who do obstacle course racing, and when you spend your weekends crawling through mud on farms, a lot of stuff crops up, and that’s not really surprising. Issues with H-pylori are very common, again, also very common in the population at large. It’s not necessarily that we need to eradicate it, but when it becomes … Overtakes that niche, it becomes problematic. You mentioned SIBO, so the overgrowth or dysbiosis of a single or small number of populations of bacteria, particularly in the small bowel. We certainly see a fair amount of that. A lot of it is gonna come down to some of those things we talked about. Certainly, the gut microbiomes is dramatically effected by diet, which then effects the way that the gut then interacts with the gut microbes as well.
Tommy: Then also, fostering certain bacterial species and the exposures that we have, and whether we’ve properly tuned our immune systems to be able to deal with things. That’s a big part of the issues with chronic disease nowadays, is … If you think about the hygiene hypothesis, are we being exposed to parasites at the right times, are we being exposed to microbes at the right times, are we stressing the immune system enough such that it knows what is an external threat versus self, we call it. That’s part of the formation of autoimmune diseases. We haven’t trained the immune system well enough. All of this then feeds into how your gut formulates the microbiota that are in there, as well as antibiotic exposures, and whether you were born by a normal vagina birth, or caesarean section. All this stuff comes into play, and then it’s often a case of just figuring out what’s best for that individual person in terms of should we treating something that’s in there, should we be altering the diet to control symptoms, or try and alter some of the stuff that’s going on.
Tommy: It’s often a pretty tricky path. If people have had gut issues for a long period of time, it often becomes about longer-term symptom control, and just making sure that you feel as good as you can. I don’t think we know exactly what the ideal gut microbiota should look like, just like we don’t know what the ideal diet should look like. We’re not at a point where we can individually manipulate these things and expect a certain outcome, but we certainly have some good tools in terms of how we can improve symptoms [crosstalk 01:13:26].
Lee: I can … I certainly concur, and if we had time I would have elaborated on a point. I’ve discovered new normals, Tommy. I thought I was doing very well. I thought I felt well and maybe another time, another show, I’ll be able to elaborate that, but that’s really sparked my passion. One thing that’s not been emphasized, and I think we should, is that you might not take care of environment today, and you might feel okay, but what I’ve learned particularly listening to yourself, and Chris, and functional medicine doctors, is that, illnesses, modern illnesses, tend to show up five, 10, 20, 30, 40 years away, and you could have prevented it by cleaning up your environment. As you speak, maybe you should emphasize that point that, even if you feel good today, you’re actually chipping away at something that will manifest in the future like chronic fatigue, or fibromyalgia, or arthritis.
Tommy: Yeah, that’s a really important point. And again, this is something that we’re trying to do our bit to help with, is to close some of it’s loop. So humans are really bad about long-term investments and thinking about the long-term. We want rapid return on our investments, we want to see that the things we are doing are working right away. So how often, when you start … You listen to a podcast, and you hear about this fabulous supplement that’s gonna do something in terms of your disease risk, how often do you then take that supplement every day for the rest of your life? You don’t, you take it for a month, then you get bored, and you don’t buy a new bottle, and who knows whether it ever did anything.
Tommy: It’s the same thing with all of these lifestyle changes. How do I know if I improve my diet, whether I’m gonna live longer, in 60 years time I’m gonna see that benefit? The answer is, right now, you don’t. However, by building these tools that can track these underlying trends or patterns in our blood biochemistry, and we know how they relate to certain disease risks, and then lifespan. Are we then able to track the changes that your body is seeing in response to interventions more rapidly? Can we close that loop more rapidly so you can say “Oh, yes. This thing that I’m doing is helping me.”, and then therefore, I can keep doing it.
Lee: You know you’re describing the future of medicine, Tommy, right?
Tommy: Yeah, so this is … And again, I don’t think we’re there yet, but this is part of what we’re trying to do is we need to be able to track the things that we’re doing, to prevent disease in the long-term, in the short-term so that we an know that we’re moving in the right direction. That’s something that’s been lacking, and that’s where I think blood testing is gonna be a crucial aspect of it because it’s so cheap, so well understood, this ubiquitous data. There’s a lot to see in there, and so anybody can get a blood test every three months. Then you can actually track what you’re doing in real time rather than just making some broad scale changes, or not making the changes because you can’t see the difference that it’s making in the short-term.
Lee: I can only concur. That’s a stark contrast with public health today for chronic disease. It simply messages eat healthy whole grains, or eat five fruit and veg a day. It’s a misguided destination, and there’s no real loop to be closed.
Tommy: Yeah, and when you give recommendations like that, a lot of it comes from nutritional epidemiology, which is one of the most broken scientific disciplines that exists, and most of the information you get out of it is essentially useless. So then, there’s the giving people this advice, are they doing it, do we know if it’s having a long-term benefit, and in reality we just don’t really know. I think I have a fairly good idea of what most people could do to improve their health, and their healthspan, but again where the data becomes useful is the fact that most people are unlikely to just make changes in lifestyle and then keep it that way. You need something to show that it’s working, something to continue to give you the motivation to do it, then that’s where I think the data becomes useful.
Lee: Last two questions, Tommy, and I’ll be brief. Tying into that, what is five things you would recommend most people do to prevent disease and optimize their health? Just in bulletpoint terms, what are five?
Tommy: Yeah, so eat real food. I think we talked about what that encompasses. Hopefully, that’s understandable. Take care of your circadian rhythm. Maybe that should’ve come first, and that has some sub-bullet points, which is expose yourself to light when it’s light, and make sure that it’s dark when it’s dark. That’s … Those are both very important, not just-
Lee: So don’t sit at the computer at 2:00 a.m. like I do seven nights a week.
Tommy: Definitely don’t do that. That’s literally … That’s really one of the worst things you can do for your health, so try and avoid that as much as possible. Beyond that, I think that you should move frequently. I think squats are one of the best things that anybody can do. Squats or dead lifts. Pick up something heavy occasionally, and then the rest of the time just don’t be sitting down continuously. Once you’ve touched those things, then the important factors are gonna be spend some time with people that you love and you enjoy being around. Again, don’t do that on the computer, do that in real time, touch them, play with them, get a dog. That’s one of my favorite health hacks is the dog.
Tommy: Then do something that … Find something in life that has meaning to you, be that your job, or other people, or something that [crosstalk 01:19:44].
Lee: Very Blue Zones. And I hope a cat is included.
Tommy:Cats are fine. I grew up with cats, but now I have … Me and my wife have dogs. I must say that the cat doesn’t make you go outside, wrestle, walk, [crosstalk 01:20:02], stuff that-
Lee: I hope not.
Tommy: No, so that’s why I like the dog ’cause it forces you to play, forces you to get outside, forces a decent circadian rhythm, those are many of the things that I enjoy about the dog. So once you’ve done that you’re right, it often comes down to those things that we talk about from the Blue Zones.
Lee: That’s quite funny. My girlfriend’s been wanting a dog and the reason I told her I didn’t want a dog is because it would wake me up early, and it’ll keep me going with the sun cycle.
Tommy: Yeah, exactly. That’s why the dog goes to sleep when it’s dark outside, and wakes up when it’s light outside. If you have a dog, you’re forced to do that. That’s one of the things that helps me make sure I go to bed at a reasonable hour is I know that the dog is gonna want to wake up at sometime between 6:00 and 7:00, so then I’m gonna have to get up.
Lee: Yeah, we borrowed a dog and her family, and the dog would wake me at 6:30 everyday. Final question Tommy, before you started I looked at the Nourish Balance Thrive website, and you know, it’s focused on athletes. People may not get the connection here when I’m touting this company as a signal, as a harbinger of the future of healthcare, so could you maybe elaborate on that before we call it a day here?
Tommy: Absolutely. The company was founded by Chris Kelly and his wife, and another doctor, Jamie Kendall-Reid. Chris and Jaime met through mountain biking. They were both … They both have their UCI Pro cards, so they were both professional level mountain bikers. They didn’t make money riding mountain bikes, but they rode it at that level. They rode it at the elite level. Chris founded the company because his health fell apart, and then he fixed it through various functional medicine approaches, and then he thought “Oh, there must be lots of people like me.” And then, initially, a lot of those people were like him. They were endurance athletes, so it was an athlete focused company, and I do a lot of my work with athletes, and that’s … I have an athletic background as well, and so that’s where we come from. We use a lot of athlete focused language because that’s a lot of what informs us in terms of what becomes the way that we work with people.
Tommy: However, that translates really nicely over to people who just want to perform for as long as possible. And like I said earlier, performance doesn’t need to be in a race, it could be in the bedroom, or it could be in the boardroom, or it could be in the dining room. There’s plenty of places where people want to perform and be functional, both cognitively and physically for as long as possible. Pretty much everything that you could learn from the elite level athlete, and keeping them going for as long as possible, is then relevant to those people. We work with a lot of people who just have performance goals, whatever they may be. We’ve learned a lot from working with and being athletes, but that applies to anybody, A, who has a chronic health condition that they want to try and reverse, or anybody who just wants to perform as long as possible. Working at the pointy end of performance, I think there’s a lot you can learn, and those are the lessons that we apply to pretty much anybody who thinks they might benefit from it.
Lee: I appreciate it, and I look forward to the company updates and the website updating in due course. Just to make the point, Chris was not only just a professional mountain biker, but he was also a programmer at Yahoo!, so he’s really another computer scientist who’s been moving to health.
Tommy: Yeah, so he came over to the U.S., Yahoo! funded him, brought him to Silicon Valley. He also worked, spend time as a software engineer for Amazon, and at a quantitative hedge fund, so a lot of predictive modeling, and stuff like that, which then becomes a big part of what we do because of his abilities to code, and his knowledge in that area. So then, that integration between health and wellness, and performance, and the data science is largely driven by his experiences and knowledge. I think that that’s why we can take the approaches that we do.
Lee: Well, Tommy, I highly appreciate getting a piece of you today. Getting some of your time. You’ve been very kind, and gracious, and informative.
Tommy: It’s been a pleasure.
Lee: So again, highly appreciate it, and I hope that the good karma comes back around for you.
Tommy: Oh, thank you very much. This is really great. I very much enjoyed it, and like I said, I really look forward to listening to other episodes of the podcast.
Lee: Please do. Thank you again, Tommy. Bye.