Transform Your Metabolic Health & Longevity by Knowing Your Unique Biology

00:00:00.320 | Welcome to the Huberman Lab podcast where we discuss science and science-based tools for everyday life.

00:00:05.680 | I'm Andrew Huberman and I'm a professor of neurobiology and ophthalmology at Stanford

00:00:14.080 | School of Medicine. My guest today is Dr. Michael Snyder. Dr. Michael Snyder is a professor of

00:00:19.440 | genetics at Stanford University School of Medicine. His laboratory focuses on how different people

00:00:24.640 | respond differently to different types of food and health interventions. And his overall goal

00:00:29.520 | is to figure out how different genes and proteins that different people express

00:00:33.200 | impact people's immune system function, reaction to different foods and diets, blood sugar regulation,

00:00:38.960 | immune system, and longevity. Today's episode could basically be summarized as, as you suspected,

00:00:45.280 | not everybody responds the same way to the same behavioral drug supplement or other treatment

00:00:50.880 | designed to improve health span and lifespan. For instance, the Snyder laboratory published a paper

00:00:56.080 | earlier this year, showing that different people spike insulin in response to different types of

00:01:00.560 | carbohydrates. Things like the glycemic index, which we may be familiar with because they are

00:01:06.240 | essentially a readout of how much a given food impacts blood sugar, depends on who you are.

00:01:12.160 | They identified so-called potato spikers, they literally refer to them as potato spikers in this paper,

00:01:17.120 | versus grape spikers. People whose insulin spikes in response to potatoes, but not grapes, and vice versa.

00:01:22.720 | And while this might seem kind of silly or trivial or micro slicing,

00:01:26.240 | the identification of these different subtypes of people in the general population who respond

00:01:30.720 | differently to different types of foods is extremely important. Because I think most all of us are

00:01:35.440 | getting a little bit tired of all these discussions about carbohydrates are good, carbohydrates are bad,

00:01:40.560 | these carbohydrates are good, these carbohydrates are bad, and on and on. It turns out it depends on

00:01:44.800 | which genes and which proteins you make. In other words, individual variability matters. We talk about

00:01:51.040 | that individual variability in the context of nutrition, also in the context of fiber. It turns

00:01:56.080 | out that fiber is something that people generally believe is good for your health. I certainly believe

00:02:00.160 | that. Well, different types of fibers impact people differently. Some people experience systemic

00:02:05.920 | inflammation of their brain and body when they eat certain types of fibers. That's bad. Other people

00:02:10.960 | experience systematic decreases in inflammation when they eat certain types of fibers. The key is to

00:02:16.720 | identify which category you're in and therefore which fibers to eat. And as it turns out, different

00:02:21.920 | foods have different fiber types. So, it's tractable. There are things you can do about it. We also talk

00:02:26.800 | about GLP-1 drugs and how those impact longevity. This is something that's very controversial and very

00:02:31.200 | timely right now. And we discuss how different psychological interventions. Yep. The Snyder

00:02:36.400 | lab has even looked at how different psychological interventions impact the genes you make and the

00:02:41.040 | proteins you make and their effect on health span and lifespan. So, today's discussion is sure to change

00:02:46.720 | your mind about a lot of things related to nutrition and fitness and medicine. However,

00:02:51.840 | I promise that thanks to Dr. Michael Snyder, it will not confuse you. In fact, it will clarify many things

00:02:57.520 | that perhaps before the episode were confusing to you and many other people. Dr. Snyder's laboratory

00:03:02.640 | is recognized for doing extremely rigorous analyses of the genes and proteins that can explain individual

00:03:08.080 | variability and what people should do or not do in order to maximize their health and longevity.

00:03:14.000 | Before we begin, I'd like to emphasize that this podcast is separate from my teaching and research

00:03:18.400 | roles at Stanford. It is, however, part of my desire and effort to bring zero cost to consumer

00:03:23.040 | information about science and science-related tools to the general public. In keeping with that theme,

00:03:27.840 | today's episode does include sponsors. And now for my discussion with Dr. Michael Snyder. Dr. Michael

00:03:34.000 | Snyder, welcome. Dr. Michael Snyder: Great to be here. I'd like to start by talking about glucose regulation

00:03:42.000 | and food and food choice, exercise, sleep, and how they all interact. But I want to make it very simple to start.

00:03:50.160 | How is it that what we eat impacts our glucose response? And maybe you could tell us a little bit

00:03:56.640 | about what a healthy glucose response looks like, because by most people's view,

00:04:03.120 | any inflection in blood glucose is a quote unquote spike. But what are the sorts of spikes that matter

00:04:08.960 | for health? And what are the sorts of spikes in blood glucose or what are called glucose excursions

00:04:13.840 | that you know, okay, well, that's a normal response to eating some food. And then it goes back down to

00:04:18.480 | baseline. I think this is especially important nowadays with all the interest in metabolic health,

00:04:23.760 | in how particular types of foods like processed foods are indeed far worse for us and on and on. So

00:04:30.160 | if you could just give us your view and understanding of glucose excursions, what they mean when they're good,

00:04:37.600 | when they're bad? Well, I would say that, you know, high, long, prolonged spikes is obviously pretty bad.

00:04:44.880 | But certain things like if you eat a grape, grapes pretty loaded with sugar, but it's a pretty transient

00:04:51.680 | spike, it'll go up. And so that would be a transit one. And actually, when you do strength training,

00:05:00.080 | for example, for exercise, you break down glucagon, which is a, you know, it's a polymer of sugar that you

00:05:06.240 | break down, gives you energy, that's important for when you're doing exercise and training, and that will

00:05:11.600 | give a glucose spike. I get a glucose spike every morning when I weight train. So that would be a normal

00:05:17.120 | healthy one, but it's transient, it goes away pretty quickly. What's quickly? Within 30 minutes, maybe most 60

00:05:25.360 | minutes. Now, I'm a special case, I'm a type two diabetic. So my spikes go higher and longer than most

00:05:31.840 | people. So yeah, mine are not good spikes, but we can get into that. So what is a good spike? Well,

00:05:39.120 | the calibration people mostly use this time and range. It's a simple metric, meaning if you're a healthy

00:05:45.840 | person, your glucose is normally for most people around 90. And if you're off, you will go higher

00:05:55.600 | than that. For most people, you want to keep your glucose between 70 and 140. If you're healthy,

00:06:01.920 | for diabetics, they say try and keep it between 70 and 180. And that is what people try to do. And most

00:06:10.080 | healthy people, it's pretty easy. And I think one of the things we've done, you've heard about continuous

00:06:15.360 | glucose monitors, these devices, and I'm wearing one, and some of your staff I know are wearing them

00:06:20.160 | as well. And they're over the counter now. You put these on your arm and they measure your glucose

00:06:24.560 | every five minutes. So you can see exactly what's going on. And so we put them on so-called normal

00:06:31.280 | people, pre-diabetics and some diabetics. It was already well known, diabetics will spike their glucose

00:06:36.640 | through the roof too high for too long. And then the people devised, especially type 1s, control mechanisms

00:06:43.120 | for releasing insulin and controlling all of that. But for the average person, that wasn't so well known

00:06:49.840 | at the time we were doing this. And it was a bit of a surprise to see that a lot of people, some did a

00:06:55.840 | very good glucose control, but some pre-diabetics were what we call moderate spikers. We came up and named

00:07:01.440 | glucotypes. It's a way of quantifying this. And then some people were spiking just as bad as diabetics and had no

00:07:08.320 | idea. And so it was a way of revealing what was going on. So it's recommended that you try to stay in

00:07:15.360 | this 71-40, but it is a bit arbitrary, but it's not a bad rule of thumb to work by for the average person.

00:07:22.320 | But again, some people have very, very good glucose controls. Some are moderate spikers and some are

00:07:28.080 | severe. And it's pretty clear that excessive spiking, especially in diabetics, is associated with

00:07:34.880 | cardiovascular disease and other things. There's some pretty strong papers out there on that. So

00:07:40.240 | you do want to keep it under control. And there's a very strong correlation between

00:07:44.720 | this time and range measurement I mentioned, and something called hemoglobin A1c. That's a measure of

00:07:51.200 | your steady state glucose. And so if you have high hemoglobin A1c, that's typically how we classify people

00:07:58.640 | for diabetes and pre-diabetes. If you're over 6'5 or over, you're classified as diabetic. If you're

00:08:04.560 | 5'7 to 6'4, you're pre-diabetic. And if you're under that, you're so-called normal. And this time and

00:08:10.880 | range will actually correlate very, very well with that. So it's a surrogate measure for that. But it's

00:08:16.160 | actually pretty cool because you can precisely see what's going on in real time, unlike a hemoglobin

00:08:23.040 | A1c measurement, which you get periodically. So if you want to dig into that further, I would say that

00:08:29.520 | you know, what's cool about these CGMs is that you wear them, like I'm wearing one now, you can wear them

00:08:36.000 | for about 14 days, depends on the particular device. And you see exactly what foods do what to you,

00:08:42.800 | and we're all different. So some people spike to bananas, some to potatoes, some to pasta, some to white

00:08:48.880 | bread, some to brown bread. And so this is shown by Aaron Siegel's lab at the Weissman and our lab had found

00:08:55.360 | something similar. And it's very personal. And so we've been spending a lot of time trying to dig into

00:09:00.880 | what's behind that. So different people, glucose spike to different foods. It's hard to predict on the basis of

00:09:07.600 | something like a chart of glycemic index, for instance. So if I understand correctly, and I have glanced at those

00:09:15.360 | papers, you know, I might be able to eat mango with nothing else, and my blood glucose doesn't go out

00:09:22.720 | of range, or at least not for very long. Whereas somebody else might have a very big and prolonged

00:09:28.880 | spike in blood glucose to mango. But maybe there are things they can eat that I can't eat, like, I don't

00:09:34.800 | know, sourdough bread or something. By the way, I can eat sourdough bread, but just by way of example.

00:09:38.720 | A hundred percent. Yeah.

00:09:39.600 | And so really the only way to know, as you're pointing out, is to measure. I want to talk a lot

00:09:44.960 | about measurement today. All right.

00:09:46.720 | For those that are just listening, not watching, Mike is wearing many sensors. How many sensors?

00:09:51.200 | You have got four watches on? I have my four watches and my ring,

00:09:53.840 | and even my hearing aids are sensors, believe it or not. So they are for hearing.

00:09:57.920 | We're going to get into all of that. All right.

00:10:00.080 | But maybe we could talk a little bit about some of the subjective experience of blood glucose

00:10:06.720 | excursions, both healthy and unhealthy. Most people are familiar with eating a big meal,

00:10:12.960 | like the, you know, the cliche is the, you know, the Thanksgiving meal after which you're tired,

00:10:17.440 | where you stuffed yourself with protein and carbohydrates and dessert, et cetera. Maybe some

00:10:21.200 | alcohol too, in some cases. But I think people are also familiar with, you know, eating a certain

00:10:28.400 | food. Like for me lately, I'll have my bowl of oatmeal with some berries and my protein drink after

00:10:34.480 | I train and I'm noticing with each successive year, I'm getting really sleepy after I eat this.

00:10:41.120 | And I've swapped out the oatmeal for a different carbohydrate recently, just some white rice,

00:10:47.520 | and I feel fine. And I don't think this is my imagination. I mean, in one case, I want to take

00:10:53.200 | a nap afterwards. In the other case, I'm good to keep going. And I generally have a lot of energy.

00:10:57.840 | So is what I just described atypical? What are some subjective effects of high glucose spikes?

00:11:03.840 | Yeah. Well, certainly sleepiness is one. I can put myself to sleep with a piece of pizza. I'm

00:11:10.080 | diabetic. I'm an unusual diabetic. We can talk about that too. And yeah, if I eat pizza, my glucose goes

00:11:16.720 | through the roof and I will get sleepy. So does that mean that you eat and you feel sleepy? Or there's a

00:11:23.040 | a period after you eat, because this is what I experienced, where I feel very energized for a

00:11:29.040 | short while. And then it's almost like my vision gets a little blurry and I feel kind of like,

00:11:33.680 | yeah, like I just want to curl up and take a nap, even if I slept great the night before. Is that a

00:11:38.640 | blood glucose response? I believe so. I mean, there are multiple things that affect sleepiness and you

00:11:43.360 | probably know this better than me since you've covered sleep more. But yeah, like tryptothanes,

00:11:49.440 | things like this can help induce sleep as well. But certainly glucose, these large glucose spikes,

00:11:55.520 | I can say personally, make me very, very sleepy. And alcohol can make a lot of people sleepy too.

00:12:02.320 | But you're right, there can be a lag because that first little shot of glucose can be a stimulant.

00:12:08.400 | But very soon that shot can go very, very large of glucose. And at least for me, it makes me very,

00:12:15.440 | very sleepy. So I think it's very normal. We've known for a long time that there are things that we

00:12:20.320 | can do to improve our sleep. And that includes things that we can take, things like magnesium threonate,

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00:15:13.680 | information, see the episode description. Yeah. There was this idea that if something is

00:15:19.680 | rather high on the glycemic index, meaning it spikes your blood sugar robustly, that by combining that

00:15:26.400 | food with another food, or let's say some fiber, as opposed to fruit juice, eating the whole fruit,

00:15:32.880 | which of course includes the fiber, at least in a different form, or adding some fat.

00:15:38.640 | So I've tried doing this, adding a bit more fat to that meal. But in some cases, it still happens.

00:15:44.960 | It doesn't matter if you try and blunt the blood glucose response with fat or with fiber. You just

00:15:49.840 | find that you get that kind of like buzz and then crash. And it's not the kind of crash where you can't

00:15:54.960 | do anything. It's actually more sinister than that. It's more of like a brain fog that then transitions into the

00:16:01.600 | desire to take a late morning nap, which if you've slept well the night before, you really shouldn't

00:16:06.160 | be feeling. Well, you can mitigate that, of course, by doing a walk and try and burn off a little bit

00:16:11.040 | of that glucose. We can get into that. Tell us about walks, because we've talked a little bit about those

00:16:15.360 | on this podcast before. But what is the effect of a short walk? And does it need to be a brisk walk?

00:16:20.240 | Yeah, I think brisk walks seem to be better. There's studies from other people on that. A brisk walk for 15

00:16:27.920 | minutes or 20 minutes after you eat will help suppress those glucose spikes. In fact, some of

00:16:38.480 | these companies that have set up around personalized management of glucose, I'm involved with one called

00:16:44.640 | January AI and there's others out there too. They actually recommend that if you eat something that

00:16:49.440 | spikes your glucose, you should take a brisk walk and that will suppress your spike. They'll actually

00:16:57.360 | teach you that. And you can see it personally. And so one thing we've done is, for example,

00:17:02.960 | most people spike to white rice. Believe it or not, it's high glycemic index, but glycemic is more

00:17:08.800 | personal than people give credit for. Anyway, you will spike your glucose, but if you take a brisk 20

00:17:14.240 | minute walk, you can just see that spike is much, much less. And is that simply due to the low level

00:17:19.520 | muscle contractions associated with walking, they're just acting as a glucose scavenger?

00:17:26.080 | That's what I assumed, yes, that you're burning it off.

00:17:28.800 | Did you see this study out of, I forget the university in Texas, I think it might have been

00:17:32.880 | University of Houston, where they looked at people doing what they called soleus pushups. Did you see

00:17:38.000 | this study? This is wild. So they basically had someone, subjects, there was more than one subject,

00:17:43.920 | of course, sit in a chair and essentially do the equivalent of what gym goers would call a seated

00:17:50.640 | calf raise. They called it a calf pushup, but all that nomenclature is kind of silly. What it really is,

00:17:56.560 | is keeping your toes on the floor and lifting your heels. It's like being like a knee bouncer in class,

00:18:01.520 | what we're all told we shouldn't do it. It turns out the soleus, even though it's only 1% of the

00:18:05.760 | total body musculature, acts as more of a glucose sponge than other muscles in the body, which sort

00:18:14.560 | of makes sense given the walking we've been talking about. And now people had to continue doing this,

00:18:21.680 | but it was pretty effective. And I would prefer to see people go out and take a walk after they eat,

00:18:27.600 | but not all of us can get up and walk after a meal. If you're on a plane, sure you can, you don't want

00:18:33.200 | to fill the aisle because people need to go to the bathroom. It gets impractical. So it's kind of

00:18:37.440 | interesting to think about just like what requirements are for low level muscular contraction. And I would

00:18:43.360 | always want to see people exercising more as opposed to less, but you could imagine given the number of

00:18:47.920 | devices that you're wearing, that after you eat a meal, that you would have just a low level muscle

00:18:52.800 | stimulator, just stimulating your soleus or something like that. Just scavenged glucose.

00:18:57.200 | You mean electrical or a physical one? Yeah, maybe. I think there's a lot of benefits,

00:19:02.160 | as you know, from exercise per se, you make all these things called exerkines that have

00:19:08.480 | a lot of benefits in general. So I think exercise probably broader than simply injecting yourself.

00:19:14.080 | Yeah, I do too. But anyway, maybe what you say would be helpful for people. You know, what I do,

00:19:20.960 | and there are others who do this too, you've heard of this phrase exercise snacks, especially for people

00:19:27.360 | who sit all day, the idea of getting up. And it used to be, well, get up and walk, you know, some brief

00:19:33.840 | walk. But now there's some ideas, well, maybe get up and do more than walk. Maybe do some of the things I

00:19:39.600 | hadn't heard the one you said, but maybe that's a better thing to do. Or air squats or something.

00:19:44.480 | Yeah, exactly. So we have people doing some squats now, running a study like that and see what it does

00:19:51.680 | to their VO2 max and overall, you know, health measurements. So, so I'm a big believer. Yeah,

00:19:56.880 | sitting for eight hours is probably not good for you. In fact, there are plenty of studies that show

00:20:01.040 | that. And these breaks are, are good for you. Even walking is better than nothing.

00:20:05.520 | Do you use a standing desk or a treadmill under your desk?

00:20:08.800 | I don't do the treadmill. I have tried the standing one. I find I don't concentrate

00:20:13.920 | as well when I'm talking with people. So after confess, I do, I prefer to sit so I can be a little

00:20:20.000 | more engaged. I do have a lot of meetings. So for me, that seems to be more effective,

00:20:24.880 | but it does mean I need to get up and take these breaks. And so I haven't, but for other people,

00:20:31.280 | I know they like standing tests. I've, I've heard from some people though, or it may not be overall

00:20:36.640 | as effective. So I don't know. Interesting. Yeah. Yeah. I think the exercise snacks are a terrific

00:20:41.360 | thing that, you know, air squats or even just pacing, these kinds of things. I think we underestimate the,

00:20:47.040 | the extent to which our evolutionary history drove a lot more movement every day.

00:20:53.520 | There's no way we sat eight hours a day in ancient times. Yes. I 100% agree. Yeah. Yeah.

00:20:59.920 | People had to be active. They had to be active to gather their food and deal with the elements. Yeah.

00:21:05.200 | So these glucose excursions, if they're brief, not a problem. But if people are finding that

00:21:10.800 | certain foods or food combinations are making them feel sleepy afterwards, I do think that the glucose

00:21:16.880 | monitors are useful for parsing which foods are doing what. I'd like to talk a little bit about

00:21:21.840 | about meal timing and food timing. Sure. For many years, just by virtue of preference,

00:21:27.920 | I will hydrate and I make sure to get electrolytes, water, and caffeine in the morning. Okay. And I

00:21:34.400 | try to exercise in the morning. If I don't, I'll do it in the afternoon, but generally in the morning.

00:21:41.120 | And my first meal always lands somewhere around 11 AM or so. Yeah. Roughly. Plus or minus an hour. Is there any

00:21:47.600 | evidence that introducing a period of fasting at one point in the day versus say later in the day,

00:21:54.160 | like having breakfast, lunch, and an early dinner versus lunch, an afternoon snack, and

00:21:59.360 | a typical dinner of, you know, between, you know, 6:30 and 8:30 PM? I think it's pretty typical,

00:22:05.920 | at least for Americans, is better or worse for glucose control in general health. I know your

00:22:12.080 | lab has been focused on, I guess it's called intermittent fasting, but this time-restricted

00:22:17.440 | feeding. Right. We're not talking about weight loss now. I'm just talking about glucose control.

00:22:22.720 | There's a lot to unpack there. So we have some studies where we put CGMs on people,

00:22:28.560 | smart watches. We can track their activity. They did food logging and exercise logging as well,

00:22:36.320 | tracked them in incredible detail. And they were also very well phenotyped for their glucose

00:22:42.160 | dysregulation. And we should probably talk about that a little bit about muscle insulin resistance,

00:22:46.320 | beta cell defects, things like that. So we were trying to relate what was their, what the

00:22:53.760 | glucose dysregulation, some phenotype with their lifestyle. And not just their lifestyle,

00:22:58.640 | what they did, but when they did it. And what we found is that, first of all,

00:23:03.040 | some simple things already known is that if you have your bigger meal first thing in the morning,

00:23:09.680 | you generally have lower glucose and don't, and not later at night. So people had their biggest meal,

00:23:15.440 | their biggest energy consumption. Later in the day is dinner, which is awkward socially,

00:23:20.800 | because that's what most of us have our big meal or many of us do. Those folks will have a higher

00:23:26.720 | glucose and starchy vegetables as well known. Those folks have higher glucose, but interesting fruits,

00:23:32.480 | people ate a lot of fruits as their major source of carbs had lower. That's because of the fiber

00:23:36.960 | that's in there that helps them. Turns out most people don't get enough sleep. And so those who slept

00:23:41.840 | longer actually had lower glucose. But some of the things we could tease out were,

00:23:47.520 | when should you exercise? If you look at the party line out there from various studies, well,

00:23:52.000 | you should exercise in the afternoon to get your best benefit. But we found that that depends on the

00:23:57.920 | form of dysregulation you have. If your muscle is resistant, you actually get better benefit by

00:24:04.000 | exercising in the morning for glucose the next day. If you're muscle insulin resistant. Right.

00:24:09.360 | Okay. So to unpack that a little bit. So you probably know that, you know, you eat something,

00:24:16.320 | you get glucose if it's sugary, and your insulin obviously, you know, helps control that,

00:24:21.760 | stimulates your cells and take that up. And if you're insulin resistant, especially muscle,

00:24:27.280 | because muscle is a major consumer of glucose, means you're not taking up your glucose right. So you're

00:24:33.680 | insulin resistant, and you're don't take up glucose, and you wind up with high glucose spikes.

00:24:38.160 | But there are other forms of diabetes. So to break this down, or glucose dysregulation,

00:24:42.880 | there are people who don't make insulin early in life, that would be called type one.

00:24:46.960 | You can still become insulin deficient in making insulin later in life for type two.

00:24:53.360 | But you can also have what are called beta cell defects. So insulin is produced by your pancreas,

00:24:59.280 | your beta cells. And I myself in type two diabetic, I have a beta cell defect, took me a while to figure

00:25:04.800 | that out. Meaning, I may consume fine, my cells respond, but I don't release it from the pancreas.

00:25:09.920 | And then there's things called hepatic insulin resistance. So your liver is insulin resistant,

00:25:16.480 | and other forms as well, fat insulin resistance as well. So we've now gotten into dividing up diabetes.

00:25:25.120 | So, you know, basically, classically, people will group people into type one, which is 10% of people,

00:25:30.640 | or type two, which is the other 90% of diabetics. Well, it turns out that's a really broad category that

00:25:37.520 | can easily be subdivided into what we call sub-phenotypes, these different forms of glucose dysregulation.

00:25:43.840 | And we think that's a big deal, because it affects the drugs you take. So for example,

00:25:48.960 | I am a beta cell defect, and I didn't respond. I went through exercise, used to be a runner,

00:25:57.200 | and I shifted to weight training about, it'll almost be nine years soon, with the idea of building muscle

00:26:03.680 | mass, which failed miserably. My glucose was gradually going up. So I shifted to weight training,

00:26:09.360 | I gained 10 pounds of muscle mass. I do whole body MRI, 20 of them in the last eight or nine years.

00:26:15.440 | And I basically did gain 10 pounds of muscle mass that had no effect on my glucose control. And the

00:26:22.400 | reason for that was that I'm not muscle-inter resistant. I'm a beta cell defect. So I can

00:26:28.800 | gain as much muscle as I want. It's not going to help me release insulin from my pancreas. So knowing

00:26:33.920 | your sub-phenotype is a big deal. But then I respond to certain drug, Rapinolide, that actually promotes

00:26:38.960 | that release. So knowing your sub-phenotype determines your drugs. But it also turns out

00:26:44.240 | this whole lifestyle thing I mentioned earlier is a big deal, and coming back to some of the food stuff.

00:26:50.000 | So we found that if you're basically insulin resistant, muscle-inter resistant,

00:26:58.480 | you will spike to potatoes and pasta, but not if you're insulin sensitive. And if you have beta cell defect,

00:27:04.800 | you also spike to potatoes. So you actually, you can sub-phenotype people according to what their

00:27:11.840 | glucose dysregulation is, and that affects how you react to foods. And so then the obvious thing to do

00:27:18.960 | is modify your eating behavior on those foods so that you can basically live a healthier life is the idea.

00:27:28.320 | And so how are you going to sub-phenotype? Well, the way we do it now is super expensive. It's,

00:27:33.200 | you know, we do these gold standard tests, take several hours, hundreds if not thousands of dollars,

00:27:39.360 | depends how you do it. We, believe it or not, can do it just from a simple glucose curve.

00:27:44.480 | So you may not realize that when you put one of these glucose monitors on you,

00:27:50.160 | and you drink a shot of glucose, you'll have a curve. And that shape is different for different people,

00:27:56.960 | and that depends on their sub-phenotype. So meaning if your muscle is resistant, you'll have a certain

00:28:02.960 | shape. And if your beta cell is a different shape, and if you're a combination of things,

00:28:07.520 | and there are other factors, by the way, that play in here, like your microbiome. So the gut's in your,

00:28:11.440 | the microbes in your gut all play in this. And so they basically affect the shape of your curve.

00:28:18.000 | And now we're not there yet, but we're good for some of these, like for muscle and so resistant. We can

00:28:23.840 | quite accurately predict whether your muscle is resistant just from the shape of that glucose curve,

00:28:29.520 | which you can get now from an over-the-counter purchase at, at a drug store.

00:28:34.080 | Super interesting. There's a, as you mentioned, a ton to unpack there. I just want to make sure

00:28:38.240 | I understand a couple of the points you made before we go forward. You said the vast number of, of papers

00:28:46.080 | that have explored ideal exercise timing point to the afternoon as the best time. I've seen those papers

00:28:51.920 | also. And my takeaway from those, the kind of gestalt of, of, of those papers in my view is that if

00:28:59.040 | you're interested in performance, that the afternoon is better because your body's warm, body temperature

00:29:04.640 | tends to be appropriate for performance. Whereas, although some people wake up ready to go first thing in the morning,

00:29:12.080 | most people don't feel as energized first thing in the morning. Some do, but most don't.

00:29:17.760 | But if I understand correctly, for many people, in particular people with muscle insulin resistance,

00:29:23.520 | doing resistance training would be preferable to doing cardiovascular training for blood glucose

00:29:29.920 | regulation. And doing that resistance training early in the day, it sounded like you were going to tell

00:29:36.240 | us that it sets a kind of a, a trend toward better glucose regulation throughout the day. But I don't

00:29:40.800 | want to, uh, lead the witness here. I want to make sure that that's true before we conclude that.

00:29:45.440 | Well, we haven't taken apart for that particular study, the difference between resistance training

00:29:51.040 | and, and there's more of a general activity measurement. So people are more active in the morning,

00:29:56.560 | if they're muscle insulin resistant will benefit, have better glucose levels the next day. So we

00:30:04.080 | haven't yet done resistance, but I'm very interested in this. In fact, we have a separate study around

00:30:09.440 | high intensity training running versus long distance running. Uh, and can happy to talk about that,

00:30:15.520 | but that's still in progress. So I, I wouldn't say we've totally done what you've gotten at,

00:30:20.560 | but we would like to dissect the resistance training versus a aerobic or endurance type of training. Uh,

00:30:27.200 | I mean, the bottom line is of course, exercising anytime is better than not exercising at all. So I,

00:30:33.360 | I think we'd all agree with that, but we do think you get better glucose benefits if you are muscle

00:30:38.880 | and resistant during the morning. And I also do believe that, yeah, building your muscle mass will help,

00:30:44.000 | with actually reducing muscle resistance. Thank you for that clarification.

00:30:49.920 | You mentioned different types of diabetes. So general categories are type one diabetes.

00:30:54.720 | Uh, these people don't make insulin. They need to inject insulin or, or, or deliver insulin through

00:31:00.080 | a time release mechanism or something of that sort. Type two diabetes, I understand to be insulin

00:31:04.560 | insensitivity, which, um, is bad. You want your cells to be sensitive to insulin so that insulin can bring

00:31:11.280 | the glucose into those cells so they can use them. Right. You're now subdividing this type two diabetes,

00:31:17.040 | the insulin insensitivity into muscle insulin insensitive as well as other tissues being

00:31:23.920 | insensitive. What percentage... But it's more than that. Meaning there's a beta cell defect where you

00:31:29.440 | don't release insulin from your pancreas. That's has nothing to do with insulin resistance. That's more

00:31:36.400 | a mechanistic thing. Now, why that, that defect exists isn't so clear. Uh, Mike is kind of interesting,

00:31:42.880 | uh, although he still don't fully understand it. But, um, then there's also incretin defects. So

00:31:48.640 | incretin are these GLPs that everybody's heard about. Ozempic is a mimic of those and

00:31:53.520 | Mongero and things like that. Uh, and so there are people with defects that way. So we're all different,

00:32:01.200 | uh, and we can now subtype that. We can say this person's got mostly an incretin defect. This one's

00:32:06.720 | muscle ins resistant. This is a beta cell defect. Uh, and so, and some people are combinations of those. It's

00:32:13.040 | not pure one or the other. So we think actually the subtyping is a big deal because again, it determines

00:32:21.040 | your lifestyle choices you might make to better control your glucose and of course drug responses

00:32:27.600 | as well. So we think that's important. We know that many, many people in the United States and elsewhere

00:32:35.440 | sadly are overweight or just clinically overweight. And I think it's about 30% of people in the United

00:32:43.760 | States are clinically obese. When you talk about type two diabetes and these different, um, subphenotypes

00:32:50.960 | as you're referring to them. Right. Um, what percentage of people in the United States do you think

00:32:56.480 | are type two diabetic that have some sort of either insulin, um, insensitivity and that's the reason

00:33:06.800 | versus, you know, they're making plenty of insulin, but they can't release it. I mean, what, what sorts of

00:33:10.640 | numbers are we talking about here? Because I think for listeners, they're probably thinking like,

00:33:14.160 | okay, like I, uh, as long as I don't eat too much sugar, I feel fine. Does that mean that they don't

00:33:18.080 | have type two diabetes? People who, um, perhaps are of a healthy weight, does that mean they don't have

00:33:23.920 | type two diabetes or any of these insulin management problems? It sounds like we don't know the real

00:33:29.040 | numbers, but if you were to guesstimate what the percentages are of people out there who have

00:33:33.600 | some issue with insulin management at a physiological level.

00:33:37.600 | Uh, well, if you include beta cell defects as part of insulin management, then the number is probably

00:33:43.680 | very high. But I honestly don't know the answer. I don't think we fully know the answer because

00:33:48.320 | people haven't done this subphenotyping like I've described. We don't know how many people have

00:33:53.360 | incretin defects. We are getting there with insulin resistance and such, but I don't think we're fully

00:33:59.280 | there. But I want to correct something that you said. I mean, it's very much the case when you see someone

00:34:04.880 | who's thin, you can't assume they're not diabetic. This is very common, especially in South Asians,

00:34:09.920 | to see thin diabetics. Uh, and I'm a good example. No one would call me overweight, uh, by any definition,

00:34:17.760 | that I'm a diabetic and I have a beta cell defect. Uh, and I used to think a lot of people who are thin

00:34:23.920 | diabetics probably have beta cell defects, but it's not that simple. It's some do and some don't. Some are,

00:34:29.680 | some are insulin resistant. And so, um, and then there are other people, believe it or not, who are

00:34:35.040 | very obese by any clinical measure, what have you. And they have very good glucose control. So there are

00:34:41.520 | a lot of things we don't fully understand and a lot of it probably does. It fits in this idea that this is

00:34:47.920 | not a simple process. Uh, we have many organ systems involved in glucose control. Your liver, your pancreas,

00:34:54.640 | your muscles we mentioned, but even your brain is a major glucose consumer. Uh, and so we have all these

00:35:00.160 | different organ systems. And then on top of that, we have all these different biochemical pathways that are

00:35:05.440 | engaged as well. We mentioned the insulin one, but there's incretin, uh, which are these GLP things that promote

00:35:12.640 | insulin release, but they probably have other effects as well. I don't fully understand. I don't think

00:35:17.680 | everyone does all the effects of incretins. They're these, their receptors are all over the place. And

00:35:23.280 | in fact, some of these drugs you may have heard are actually now being touted as maybe

00:35:27.120 | anti-longevity drugs because they seem to improve cognition and stuff. Now, whether that's tied to

00:35:33.040 | weight and things like that is less clear. As anti-longevity drugs or as longevity drugs?

00:35:38.400 | As longevity drugs. All right. Thank you for that correction. Yeah. Yeah. Uh, actually just for fun.

00:35:42.720 | Yeah. Let's explore for a moment some of the things that we've heard these GLP-1 drugs, uh, are

00:35:48.800 | effective for. Yeah. Uh, certainly for, um, diabetics to better, type 2 diabetics to better control

00:35:57.680 | their, uh, blood glucose. Yeah. If I can intersect there. Yeah. I am a type 2 diabetic and they work

00:36:03.120 | great for me. I, my hemoglobin A1c got to 8.4, which, you know, it's not the highest, but it's

00:36:08.640 | pretty high. And I went on the GLPs and I went down to 5.7. Just like that? Pretty fast. Independent

00:36:14.960 | of weight loss? No. Well, initially, yes. It's a little complicated. I went on a lower dose thing

00:36:21.520 | called, um, for Siga. And that one dropped me down to about the 6.4, 6.5 level. And I didn't lose too

00:36:30.160 | much weight. I did lose some, uh, and then I went on Mangera because I had some nausea effects. That is a

00:36:35.680 | common side effect. They were modest, but they were there. And I went, and so I shifted to Mangera,

00:36:40.240 | which is a more potent version. And that dropped me down to 5.7. And I did lose weight. I went from 144

00:36:46.960 | to what I am now, 128, which I didn't like to be honest. And it, but I can tell you my, I mentioned

00:36:52.720 | I do whole body MRIs. I've done 20, uh, as I say, over the last almost nine years. And I could just see

00:36:59.680 | my fat evaporator once I went on these, I'm the coldest guy in the room now. Uh, but you maintain

00:37:05.120 | muscle mass because you do resistance training. Mostly. How many days per week are you doing it?

00:37:09.840 | I do it every day. So, but I have light days cause you know, you can't strain yourself

00:37:14.800 | hard every day or that's a problem. So I have light days with more reps and then heavier days for more

00:37:20.480 | of the strain stuff. And then I have a specialty day where I do like snatches and things and build my

00:37:25.200 | core, this sort of thing. Uh, and so, uh, combination of, of those things. And so I do it every day.

00:37:31.760 | And the goal was to keep my muscle mass up. And I mostly did it cause I do get measured a lot.

00:37:37.200 | Although it plummeted when I got in a bike accident and hurt my shoulder, uh, and then certain exercise

00:37:43.280 | couldn't do. And so those things, as you might imagine, diminished. So I did lose some muscle as a

00:37:48.160 | consequence of that. I have mostly built my strength back up, not entirely back to where it was.

00:37:54.880 | So it's still there, but yeah, it's not a hundred percent. And then there's a question of how much

00:38:00.480 | strength versus muscle mass is important. I don't have, maybe, you know, the answer to that. I don't

00:38:05.600 | know. Uh, but anyway, I do try to keep it up. It's down a bit, uh, in terms of muscle mass and a touch and

00:38:13.280 | strength as well. I do my, again, my hemoglobin A1c isn't too bad, but I don't like losing that much.

00:38:21.760 | I'll be honest with you. I thought I looked a little gaunt. So I actually am now backing off on

00:38:28.160 | the Mongero. I don't do it every week like you're supposed to. I'm on the lowest though. So I'm a great

00:38:32.000 | responder there. And by the way, when you get in these drug responses, it turns out I'm metformin

00:38:37.040 | non-responder. I did try that early on. Oh, this is interesting. So just to remind people,

00:38:41.680 | metformin and then the poor man's version of it is berberine, which is sold as a supplement. They basically do the same thing.

00:38:45.760 | They lower blood glucose. In fact, I will tell anyone that decides to take metformin or berberine

00:38:53.680 | that if you don't consume enough starchy carbohydrates with it, it can give you a brutal

00:39:01.920 | headache because you become hypoglycemic. I didn't know that.

00:39:04.480 | Oh, it's really rough. Years ago, I used to take a little bit of berberine. I used to do these cheat

00:39:10.960 | days as many years ago. I would eat really clean all week. And then I would like a Saturday, I would

00:39:15.840 | just go for it like anything you wanted. And I felt lousy. You'd have these energy, you know, peaks and

00:39:23.280 | valleys. And then you just felt like by the end of the day, you're just like, I'm done with food for the

00:39:28.320 | next 10 years. And of course, you fast the next day, you feel fine. You go right back to it. But

00:39:33.040 | it wasn't healthy. But taking berberine, it was remarkable because it would allow me and other

00:39:38.480 | people that recommended it to me that you could just eat like an entire box of donuts and feel fine

00:39:43.200 | because it would blunt your blood glucose response. However, if you don't have enough

00:39:46.880 | glucose in your system, you become hypoglycemic and you get these brutal headaches. So anyway, that's a

00:39:56.160 | little- And this is becoming a big deal now, right? Hyperglycemia is now being recognized as a big

00:40:02.400 | concern actually. So, and people are picking up a lot of this with the CGMs. Interesting. And this is

00:40:07.600 | because people are taking Monjaro and taking other things that are dropping their blood glucose. Yeah.

00:40:11.360 | And just, it's probably been out there more than people realize in the first place that, and now with

00:40:15.920 | the CGMs, people realize, well, if you, we talked about these glucose spikes. Well, it's very common if you

00:40:21.680 | get a really giant spike, you make a lot of insulin. So the consequences, then you come down on the other

00:40:27.680 | side and you actually get too low glucose from those spikes. So, so people are recognizing that

00:40:33.120 | and that can, people are now concerned about that. Certainly leads to fatigue. Yeah. Glucose troughs are

00:40:38.880 | definitely bad. I don't do any sort of cheat day anymore. I actually, just a few years ago, I just quit

00:40:43.920 | eating bad food. Yeah. I don't eat non, I don't eat, you know, or I aim for, you know, 90% of my food

00:40:50.960 | intake to come from, you know, whole unprocessed foods. Yeah, great. And then occasionally a slice

00:40:55.920 | of pizza or a bowl of ice cream or something, no big deal. Right. Especially if you're exercising

00:41:00.240 | regularly, but so to go back to these, these drugs, these, these GLP-1 agonists was basically what they

00:41:09.120 | are. Right. And we had a guest on here, Zachary Knight, who's at UCSF, Howard Hughes investigator,

00:41:13.680 | who kind of shocked me by telling me that these drugs, all increased levels of GLP-1 in the blood

00:41:21.520 | and brain by about thousand fold. Yeah. That any less doesn't really have an effect on appetite,

00:41:28.240 | doesn't have an effect on the various things they're designed to, to do. So these are massive,

00:41:34.080 | super physiological increases in GLP-1 that people are achieving with these drugs. I know nowadays,

00:41:39.840 | some people are starting to get them from compounding pharmacies and micro dosing them. Right. To great

00:41:44.160 | effect, actually. Okay. The big pharma companies don't like this because it's sold at a fraction of the

00:41:49.760 | price and you can get away with very low dosages. This is what I want to do, by the way.

00:41:52.720 | Yeah. And no nausea. Right. And oftentimes they're combined with

00:41:56.160 | some other things that off the top of my head, I can't remember, but oh, right. Some of these more

00:42:02.000 | experimental peptides like SS-31, which are designed to improve mitochondria and people are getting

00:42:07.040 | really spectacular effects from the micro dosing of compounded, compound pharmacy GLP-1 agonists. But

00:42:15.040 | even those are probably boosting GLP-1 several hundred fold. So none of this is like natural

00:42:20.720 | for the body. And yet there are other positive effects. Like I've heard of reduced craving of

00:42:27.840 | alcohol. What are some others that you've heard of?

00:42:30.000 | Cognition is a big one. And it's certainly something people worry about a lot as they get older. It's

00:42:35.600 | almost becoming the number one thing people worry about as they get older, getting dementia-related

00:42:41.440 | conditions. So, and there's, you know, we'd like to see more studies out there, but there's some

00:42:46.960 | evidence that it may improve cognition. Now, how much of that is intertwined with weight loss and things

00:42:53.120 | like that, I don't think has been totally deconvoluted. So I think we need to sort all that

00:42:58.320 | out. But yeah, but people are now, you know, you may know that people used to talk about metform and

00:43:04.720 | this diabetes drug as potentially the longevity drug, that this may be the way to live a lot longer,

00:43:11.200 | healthier. And the side effects are not high, as far as we know, if at all, for most people.

00:43:17.840 | And now a lot of people are very interested in these GLPs as possible longevity drugs. And

00:43:24.080 | there are trials underway to look at this sort of stuff. So we'll see, you know, what ways they

00:43:30.240 | improve people. I will say, as long as we're on this topic, you are a perfect example of a very diligent

00:43:38.800 | patient, meaning you're taking these GLP-1 drugs. You're, as you mentioned, aiming for taking lower

00:43:45.760 | dosages, maybe even quote unquote, micro dosing. But you're also resistance training daily,

00:43:51.520 | alternating heavy and light days. You do your exercise snacks. You, you know, you're getting

00:43:58.480 | brisk walks after you eat. I mean, I think it's important to point out that you're doing all the

00:44:03.920 | things that help maintain muscle mass, cognition, et cetera, while taking these GLP-1s. Many people won't,

00:44:10.960 | or just unless they're highly motivated to, they just, they want a drug that's going to melt the fat

00:44:16.560 | away. And they are unwilling or uninterested to do the, the exercise piece. What, if any data from your

00:44:24.960 | genomics data and these large scale studies that you're doing point to the fact that the combination

00:44:30.640 | of augmenting GLP-1 with these drugs and exercise is, is beneficial. Is it all just about maintaining muscle

00:44:37.200 | mass? Uh, good question. I don't know, but it's pretty clear that people do do strength training.

00:44:43.280 | Again, larger studies would be nice, but it's pretty clear that they can reduce their muscle mass loss.

00:44:48.160 | That that's clear. And it's definitely been the case for me. I mentioned my bike accident. I went from

00:44:53.120 | pretty good about maintaining muscle mass and I did lose some when I lost some of that. Um, so I can tell

00:44:59.120 | you personally had an effect. Don't cycle. I tell my friends, we, I know so many people have been on a

00:45:05.280 | bicycle. You're traveling next to these 3,000 pound, uh, vehicles moving much faster than you. People are

00:45:11.280 | texting. I, I say this out of love, uh, for the audience and for, and for you, even though we, we just

00:45:16.480 | met, uh, we're colleagues at Stanford, um, all these years. And, and I have to say everyone I know who cycles

00:45:23.680 | regularly gets hit by a car eventually. I know it's three staffer faculty that are dead. Oh, right. But

00:45:29.760 | then again, I lived in the area for a long time. Yeah. Back on Woodside Road, you know, cars just,

00:45:34.080 | just taken out or, or had to dodge a car and, and, um, ran to a tree. So dead, brain damage, injured.

00:45:41.840 | What do I have to do to convince you to run instead of cycling? Well, I do have a theory that you're,

00:45:45.920 | you know, you're cycling versus your health. There's an inverse relationship or it's a constant,

00:45:51.280 | I should say, meaning, uh, I'll probably get killed by a car possibly someday, but I'll stay healthy

00:45:56.320 | in the meantime, because it is my form of aerobic exercise. But we need you around Snyder. But I say

00:46:01.280 | this, I don't know why anyone would, would do this instead of swimming or. But I don't go up those,

00:46:05.040 | but I don't go up those mountain things where there's no even bike paths that they have.

00:46:10.080 | It's not the cyclists, it's the cars I work. Yeah, correct. But there's no room in some of those

00:46:15.280 | places to go. So I mostly, I mean, I, I do it to go to lab and back and I do it. It's also a form of

00:46:23.040 | mental release for me at the end. I do, I love what I do, but I do work long hours and I, it's just a

00:46:28.640 | great release to get that bike ride home at the end of the day. Do you wear a helmet? Uh, of course.

00:46:33.760 | Yeah. And that's turned out to be pretty critical when I've had my, I've had more than one accident,

00:46:38.480 | eight to say. Uh, but, um, but never, no car has run into me. I'm thankful for, but I, I hit a rock

00:46:46.240 | and got knocked out once. So I, or something like that. I, I don't know. I woke up briefly in a,

00:46:51.120 | in a ambulance and then more. Telling you Stanford professors, this is the way Stanford professors

00:46:56.560 | get taken out. Yeah. Well, but I'll say healthy in the meantime. And, and I like to think I'm pretty

00:47:01.760 | healthy now, uh, minus my diabetes. You seem very robust. I mean, I, I hope you don't mind

00:47:08.320 | me sharing that you are, uh, about to hit 70 soon and you are clearly cognitively, uh, whip smart and,

00:47:16.160 | um, and fast and physically you seem very robust. And, um, you mentioned getting these whole body MRIs

00:47:22.720 | and the fat just kind of disappearing as you were doing these GLP-1 agonists and weight training.

00:47:28.000 | I want to make sure I continue to, you know, I'm big on the weight training. I'm glad you're doing

00:47:32.800 | that because I think it's huge. Yeah. It's, it's not just about taking a drug. Um, and you can do a lot

00:47:38.080 | with just lifestyle and we'll talk more about that, but I have a question about, um, subcutaneous versus

00:47:43.520 | visceral fat. Yeah. You know, we hear that fat around the viscera, around our organs is the one

00:47:48.720 | to really worry about. Um, and anytime I hear something like that, I think, okay, that sounds

00:47:53.600 | like a reason to not lose fat elsewhere, but you know, what do we know about the, the health risks

00:47:58.880 | of intravisceral fat versus subcutaneous fat? Yeah. I'm not an expert here, but it does seem pretty

00:48:04.960 | clear that obviously fat around your organs isn't good. Fatty liver being a good example.

00:48:10.320 | And by the way, when I went on GLPs, my, I had a little bit of fatty liver just disappeared.

00:48:16.000 | So I think a lot of people are thinking this way that your pancreas is and beta cells in particular,

00:48:22.480 | very subject to stress. And fat does put stress on your organs, no question. And so it may be one of the

00:48:30.560 | reasons, you know, your pancreas and your beta cell in particular is very sensitive to fat is because

00:48:37.360 | it does cause stress. We know fat is very associated with inflammation. So obesity is a good example,

00:48:43.120 | more BCR, higher BMI, again, not perfect correlation, but higher inflammation. And so all that does tie

00:48:52.320 | together and your immune system is tied in this in ways I would say we don't fully understand. But

00:48:58.320 | in general, the party line is a visceral fat is worse. And I think it's because of putting stress

00:49:04.800 | on your organ systems, uh, yeah, say versus subcutaneous. I'd like to take a quick break and

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00:51:57.120 | I'd like to talk a little bit about meal timing and sleep. I do my best to eat my last bite of food at least

00:52:05.920 | a couple of hours before I go to sleep. It doesn't always happen. What do we know about how evening and

00:52:13.040 | nighttime meals impact sleep and next day glucose levels and regulation? Well, the party line is that

00:52:20.160 | you should not eat three hours before sleeping. And I believe that, and that's true from the studies we've

00:52:27.680 | run. That people who do have a gap and actually people who walk after dinner have lower glucose the

00:52:33.680 | next day. And if you go into the evening with a high glucose spike, in general that correlates with poor

00:52:41.360 | sleep. So I think it's more complicated than that. I think, again, the party line will be, well,

00:52:49.600 | your glucose is kind of high at night and gradually goes down during the day and spike in the morning.

00:52:54.560 | You get a cortisol spike, as you probably know, when you wake up and that's normal and that's healthy,

00:52:59.600 | helps energize you for the day. And cortisol and glucose are related. But when you actually look at

00:53:05.360 | people's glucose patterns, it's much more complicated than that. And I think a lot of that has to do with

00:53:10.720 | what their subphenotype is. This is what we don't fully understand as we're trying to sort this out.

00:53:16.240 | And what you did the day and especially the evening before eating that big piece of pizza and then

00:53:21.840 | falling right asleep probably is not a great thing for you. You will go to bed with a high glucose spike

00:53:27.920 | for many people. Again, unless you have perfect glucose control. So, you know, I think getting your

00:53:34.080 | glucose under control, it is a bit of a problem for me. We tend to eat late in my household just because

00:53:40.560 | both my wife and I work kind of late. And so, we tend to eat a little bit later, but I definitely

00:53:47.440 | do better if I can try and eat earlier. And then I definitely don't snack before bedtime, that sort of

00:53:53.360 | thing. And these days I try not to make my biggest meal my dinner, which again can lead you into sleep with

00:54:00.320 | that. And we always take a walk. We have dogs and walk our dog after dinner. It's become a routine.

00:54:05.680 | You mentioned earlier about behavior and I think the key for good behavior is to get

00:54:10.400 | into these routines where you can just get into that. And I think it really makes a difference.

00:54:16.880 | So, yeah, always, and as I'm sure you know, going to bed. People, we had found that in some of our

00:54:23.280 | studies as well. Going to bed the exact same time, those folks have lower glucose than those who

00:54:30.160 | have highly variable sleep timing. Now, that's not so great for me because I travel a fair amount.

00:54:35.200 | Likewise. But I try when I'm not traveling to keep constant hours, at least that part I'm okay at.

00:54:41.680 | I think we forget sometimes the number of interesting things that happen in sleep. And one of the most

00:54:48.880 | interesting papers, to me anyway, in the last few years was a paper that I saw where they essentially

00:54:53.760 | had people breathe into a tube while they were sleeping and evaluated the different types of

00:54:59.120 | metabolism that were occurring during sleep. And it turns out that as we go from light sleep to deep

00:55:05.280 | sleep and then more rapid eye movement sleep as the night progresses, the brain and body transition

00:55:10.560 | through essentially every form of metabolism, glucose metabolism, ketogenic metabolism,

00:55:16.240 | a mixture of the two. And it seems like sleep is this, we don't know if it's like a test run or if

00:55:22.720 | it's a reboot or we don't know what to call it, right? But it's just very clear that during sleep,

00:55:27.280 | there's a lot of metabolism happening. So when you tell me that getting to bed at roughly the same time

00:55:32.320 | or the same time every night improves blood glucose regulation, my first thought is, oh, well,

00:55:36.960 | that makes sense. Because if you go to bed at the same time, then you're eating at roughly the same time,

00:55:40.320 | you're exercising at roughly the same time. But it could also be the case that in sleep,

00:55:44.720 | we're getting a tuning up of the metabolic processes for the brain and body. Is there any evidence that

00:55:51.360 | supports that? Yeah. Again, I don't know from the metabolism standpoint. I like to say the things we do

00:55:58.800 | the most, we understand the least. Nutrition, right? How exactly does that work on all your different organs?

00:56:05.280 | Sleep. You know, I do like the idea of the sleep. You may know your, you would know this better than

00:56:11.520 | me, but your spinal fluid and such expands and contracts. The idea of emptying out the garbage,

00:56:17.920 | so to speak. Yeah, literally rinses out your system. Yeah. And I like that concept. I think,

00:56:22.320 | and, you know, to what extent that is beneficial, I'm sure it is. I don't know. And all the other

00:56:29.520 | facts, but even people argue what's better for your REM versus deep sleep,

00:56:33.600 | even some of that is debated by experts in the field. Again, I'm not a sleep expert. I have a

00:56:39.520 | tendency to move into fields I know nothing about. So because I'm so naive, I hope to learn something,

00:56:44.720 | especially these areas that aren't so well understood. So it's an area we're going to be

00:56:49.680 | studying a lot more around the glucose control. But there's no question, if you look at some people,

00:56:54.880 | they're spiking really bizarrely. And I have mixed days myself. I'm trying to sort that out. Somewhere I do

00:57:01.120 | hit the party line, higher glucose gradually go down by the morning. But then I have nights where I'm

00:57:06.960 | quite irregular. And I want to correlate that with what's going on. And it's not just me,

00:57:11.680 | it's true of a lot of people. And I don't think that's sorted out in my mind. And I think metabolism

00:57:17.280 | in general, some way we can talk about the micro sampling stuff. But we found that we had 32 people

00:57:24.000 | drink this Ensure Shake while they were fasted. And they all reacted very differently to it. This is

00:57:29.200 | during the day now, not sleep. And for some people, it was pro-inflammatory, for others,

00:57:34.160 | anti-inflammatory. So interesting. I assume a lot of this got set early in life because your whole

00:57:39.760 | microbiome, so backing up a little bit, just so people realize that, you know, you have a lot of

00:57:45.760 | microbes. You have, in fact, more microbes in you than our human cells. And they're critical for digesting

00:57:51.760 | your food and all this. And they're, they heavily interact with your immune system. 70% of your

00:57:56.960 | immune cells are in your gut. So you have this whole interplay between your immune system and your gut.

00:58:02.720 | And obviously, then the food you eat, which goes through your small intestine first, and the small

00:58:09.040 | molecules like glucose get absorbed. But then all the fibers, the big molecules go into your,

00:58:13.520 | your culinary, your large intestine, where they basically, you know, are interacting with these

00:58:20.160 | immune cells. So I think a lot, and a lot of that gets probably set early in life. In fact, people

00:58:25.440 | have shown your microbiome gets set in your first three years of life. So I think that interplay all

00:58:32.160 | gets established. And then you are reacting to some of that, your food later in life. That's at least

00:58:38.960 | the postulate. Not that you can't modify it. In fact, you know, switching from carnivore to veggie diets,

00:58:44.880 | and there were Mediterranean type diets, which are sort of healthier, like fish heavy,

00:58:49.680 | veggie diets, I think, are helpful for people. But I do think some of this gets set early. And I think

00:58:58.480 | getting that set right, I think we probably need to, as a society, get that all set a lot earlier,

00:59:05.760 | probably now too. And it's estimated, some work from Justin Sonnenberg, that, you know, native

00:59:12.640 | populations, these aboriginal, they have three times the number of microbes that, say, people in the US.

00:59:19.440 | So we just don't have the same community that is probably handling diverse foods and probably making

00:59:27.200 | essential ingredients for our health that we're now missing. So we probably need to restore that in some

00:59:34.720 | fashion. Otherwise, this obesity and diabetes trend is just going to continue.

00:59:39.200 | I totally agree. I think the gut microbiome is, without question, one of the more fascinating

00:59:45.360 | aspects of our biology. And in no small part, because of the way that it interacts with the

00:59:51.280 | brain by the vagus nerve. You know, everyone's obsessed these days with the vagus nerve as a

00:59:57.120 | calming pathway. But it's got a bunch of different avenues within it. And it is the major route by which

01:00:03.600 | your gut communicates with your brain. And I do want to just say one thing in fairness to

01:00:10.320 | an observation. I completely agree with you that many people who've been eating, certainly standard

01:00:17.200 | American diet, sad to think that anyone still does that anymore, because it's such a terrible diet. I

01:00:22.320 | think everyone agrees on that, a lot of processed foods. But you mentioned switching carnivore for

01:00:29.200 | more Mediterranean or plant-based. I have seen that work for many people. I will just also mention,

01:00:35.120 | in fairness, and this relates to the gut microbiome, there do seem to be some people who,

01:00:42.160 | despite their best effort to eat fiber, fruits, vegetables, fish, so-called Mediterranean diet,

01:00:47.600 | that for whatever reason, they have persistent autoimmune issues. And I have observed over and

01:00:54.560 | over again, that if they switch to an elimination diet that's largely just meat, believe it or not,

01:01:01.840 | and nothing else, they seem to resolve those autoimmune issues. Now, I personally don't follow that diet.

01:01:06.640 | I don't think it's the healthiest diet out there. It's very hard to stick to. But in my mind, it seems like

01:01:13.440 | the data are pointing to the idea that there are diverse microbiomes out there set up early in life,

01:01:19.120 | and probably genetics play a role also. You're a professor of genetics, so hopefully that's not too

01:01:23.440 | heretical an idea. By the way, some of this has been broken down of, say, how much is your microbiome

01:01:30.560 | for general glucose levels versus genetics. And I think for the general microbiome, it's about 20-30%,

01:01:40.400 | depends on the cohort that was studied. There's some work from the Weissman. And then for genetics,

01:01:46.000 | it may be about 20% as well. So 20% of your microbiome is determined by your genetics.

01:01:50.880 | No, the other way around, sorry, of your glucose levels, 20-30% is determined by your microbiome,

01:01:58.800 | and about 20% by your genetics. And the rest by lifestyle.

01:02:02.240 | Yeah. Okay. That's a useful set of metrics. Yeah.

01:02:05.760 | Yeah. I mean, I just have to believe based on the observation of people who are really careful,

01:02:10.320 | really care about their health, they're not doing standard American diet, and they've tried vegan,

01:02:14.640 | they've tried vegetarian, they've tried omnivore without many processed foods. And then they try

01:02:21.760 | ketogenic diet, and they feel better. And then they go full, just meat, and their issues disappear.

01:02:28.720 | Yeah. And you kind of have to acknowledge that.

01:02:32.080 | Right. Right.

01:02:32.240 | I'm not saying you have to, but I'm going to acknowledge it.

01:02:34.240 | I will also say that most people seem to do well on an omnivorous diet. I think

01:02:39.200 | 90% of people in the world are probably omnivores.

01:02:41.760 | Yeah. And I find it so interesting that as we support the gut microbiome, our health generally

01:02:50.160 | improves. That just seems to be the case. I'd like to talk for a moment about fiber.

01:02:54.720 | Sure.

01:02:55.280 | Because I think there's general agreement in the medical community that fiber is important. Reduces

01:03:02.880 | risk of cancer, improves digestion, adds bulk to food, reduces inflammation, just on and on and on.

01:03:10.000 | But then again, our colleague, Justin Sonnenberg and Christopher Gardner,

01:03:14.400 | Yeah.

01:03:14.880 | Both of whom have been on this podcast before, did this really nice study of comparing

01:03:18.320 | increasing fiber in the diet versus increasing intake of low sugar fermented foods. And it's

01:03:24.240 | very clear that the increase in low sugar fermented foods supported proliferation of the healthy gut

01:03:29.520 | microbiota, reduced the inflammatome. Whereas increasing fiber allowed some people to reduce

01:03:36.880 | inflammation, other people's levels of inflammation went up. And so this brings us to this question of

01:03:43.280 | when we talk about fiber as a general category, maybe that's too broad.

01:03:47.920 | It is.

01:03:47.920 | Could you tell us about the two major types of fiber, which foods tend to deliver one or the other

01:03:55.360 | type of fiber, and if indeed there are differences in which fiber are best for different people?

01:04:01.600 | Right. So as you're alluding to, fiber is very heterogeneous, very different.

01:04:07.840 | And we even break it down further than that. You're probably thinking of, you know,

01:04:11.520 | soluble versus insoluble or resistant starch versus starch. But I look at fiber as like just a giant

01:04:18.960 | community of different substrates, if you will. So we have long chains, short chains, hydrophobic,

01:04:24.720 | hydrophilic, positive, negative. It's like saying all animals are the same. Humans are the same as

01:04:30.080 | cockroaches, the same as cats and dogs. You just can't lump that broadly.

01:04:32.720 | You can't, and their effects are very, very broad. And so we've started tearing this apart. I was a

01:04:37.920 | chemistry undergrad by training, so I guess that's where I'm coming at this. So we just started,

01:04:43.600 | and being somewhat practical too, we started putting people on, we took two common fibers,

01:04:49.120 | arabinozylan and inulin, which are these two, just commonly used, arabinozylans,

01:04:56.080 | and emphyseum husks, and it's associated with mesomucil and inulins and those chicory

01:05:00.480 | pea fiber things.

01:05:01.520 | Well, could you, before we dive into this, what are some foods that one type of fibers

01:05:06.080 | is more abundant in versus the other type of fiber?

01:05:08.320 | Well, metamucil is a good example for the, the, um, arabaziland would be in that.

01:05:15.200 | And arabaziland is kind of interesting as the name sounds, the chemist has arabinose and,

01:05:22.160 | and it does have some glucose, but it has polyphenols in it too. And,

01:05:26.160 | I don't know if you probably have covered this on your show.

01:05:28.000 | No, not yet, but they're super important.

01:05:29.680 | They are, they're, they're, and they're being, especially in the last, I'd say,

01:05:33.680 | you know, six, 10 years, being more and more appreciated for all the positive effects as

01:05:38.000 | antioxidants and the inflammatory. So, uh, anyway, they're part of arabaziland. This inulin is a

01:05:44.560 | glucose polymer, but they're short chain and long chain. That has different properties as well too.

01:05:49.200 | Uh, that's in various, uh, um, certain fruits and certain, uh, other things.

01:05:55.440 | And when we went into this, if you read the literature, you would say, well, there'd be,

01:06:01.680 | some say said, um, well, inulin lowers your glucose and others say, no, has no effect.

01:06:07.760 | And some saying it lowers your cholesterol and others, it doesn't. Same with arabaziland. It was

01:06:12.240 | all over the map. Although there might've been more of a consensus about this arabaziland lowering

01:06:17.440 | cholesterol. So we just did it. We took 18 people. I know it doesn't sound like very many,

01:06:22.240 | but they did a, what's called a crossover study where they went on increasing doses where they

01:06:26.960 | took either 10 for the first 10 grams a day for the first week as a supplement, 20 the next week,

01:06:32.240 | 30 the next week, and then did a washout and then switched to the other one. So they're,

01:06:37.200 | they're randomized. They might do a arabaziland in the first period and then inulin in the second,

01:06:42.160 | then a mixed fiber, which the party line would say is, is supposed to be the best for you. So we put,

01:06:47.040 | and then we do what we're known for these deep measurements, these deep, we measure as many

01:06:52.240 | molecules of people's blood and as well as clinical measures. And so what we discovered

01:06:57.280 | is that as a general rule, arabaziland did reduce cholesterol and actually quite substantially. It went

01:07:04.800 | down about 25%. So this is in metamucil, but what other, um, what sorts of foods contain high amounts

01:07:11.600 | of the, of this compound? Most do actually. Oh, okay. So broccoli? Yeah. Broccoli, yeah. Kale, lettuce,

01:07:18.400 | cabbage. Yeah. Okay. Okay. So this is like the, when we think of fiber, we think of... But they have,

01:07:22.000 | but they have other things as well. So these are generally mixtures. Like apple fiber will have three

01:07:27.440 | major types of fiber. It's back to this heterogeneity of fibers. So we're now getting into

01:07:32.240 | others like beta glucans, another fiber, resistant starch is yet another one. So there's a whole series

01:07:38.480 | of these fibers out there, yet they're not studied for their individual effects. And it may be the case,

01:07:44.400 | of course, the complex mixture is a big deal, uh, as well, meaning getting the right combination. But we're

01:07:51.120 | starting with individual fibers, trying to see what their effects are. And then we will do a combination.

01:07:57.040 | So we're just finishing up a study where same thing, instead of two fibers, we added two more,

01:08:02.640 | beta glucan and resistant starch. And we're trying to see their effects of supplements. Uh, and the idea

01:08:09.120 | ultimately is, is I think people do supplements. That's why we're doing supplements. Not that I'm a big fan.

01:08:14.960 | I'd rather they, you know, healthier, unprocessed food or both, but yeah, most people don't get enough.

01:08:20.960 | You probably know that, um, it's recommended women have at least 25 grams of fiber a day, men 35.

01:08:27.840 | And a number of the people get is something like 12 to 15. Wow. They're off by a factor of two in

01:08:34.560 | their amount of fiber they consume. So, you know, minimally supplements could help bring that up.

01:08:40.800 | Anyway, uh, I mentioned that rhabinozionin as a general, lowered most people's cholesterol. And by the way,

01:08:48.240 | neither affected glucose. So we think other things are important for that. And, um, but if you look at

01:08:54.880 | individuals, we did see some people where rhabinozionin had zero effect, meaning their cholesterol

01:09:00.800 | stayed flat, even when they went to the higher dose of 30 grams per day. Yet their inulin promoted their

01:09:08.720 | decrease, uh, decrease, uh, in, in cholesterol. So what's going on? Well, we don't know, but to me,

01:09:14.960 | it's logical that your microbiome, maybe it's your immune, maybe it's other parameters are playing

01:09:19.200 | into this. So this is why ultimately what I want to do is just get your microbiome, do a blood draw and

01:09:25.440 | say, aha, here's the foods that will be healthy for you. And here's the ones that won't. I think this is

01:09:30.720 | very personalized and complex. It comes back to what you're saying before about meats and things having

01:09:36.720 | different effects on people. And you probably know a lot of people with bipolar. Now the, the solution

01:09:42.800 | for a lot of people is a ketogenic diet, right? Which, and it seems to really work. There are studies out

01:09:47.920 | there where it's been very transformative. Which is remarkable. I mean, if we really just take a step

01:09:52.880 | back, it's like for ever, you know, bipolar depression was one of the most difficult things

01:09:59.920 | to treat. And it turns out the ketogenic diet can be very effective in some people, in some cases,

01:10:05.600 | curing people, not every person, but that's a remarkable breakthrough. I agree. You know,

01:10:10.480 | and, and as you said earlier, I think it's such a key, uh, thing for people to keep in mind. We

01:10:15.120 | understand the least about the things we do the most. So you can imagine for many years, people are

01:10:19.200 | eating like every, everyone eats sooner or later. And, um, some of these people are dealing with

01:10:24.320 | serious mental health issues and the foods they were eating very well were exacerbating their symptoms.

01:10:30.960 | Yeah. It's just wild to think about. But then when we talk about, and I've heard you say, you know,

01:10:35.840 | food is medicine. I think most people don't think of food as medicine. I think most people think as

01:10:41.520 | food is something, uh, they need that they crave, that they enjoy, uh, and that eventually becomes

01:10:49.520 | problematic for them. You know, I don't think people really understand the extent to which what

01:10:53.840 | they put in their mouth can support them, that it really can be health promoting. Yeah. Right. I think

01:10:58.960 | it's because we are so calorie oriented, like, oh, you know, it's all a battle between what you take in

01:11:03.760 | versus what you burn. Yeah. But you really view food as medicine. Oh yeah. Because I think we are,

01:11:09.280 | I mean, the way I look at it, we're homeostatic systems. We're very, and complex ones at that,

01:11:14.320 | right? We have all these organs, all these biochemical pathways. And, you know, the one

01:11:18.880 | we also understand at least is people's behavior that came up earlier and I'm sure it will come up again.

01:11:24.400 | Uh, and you have to tune all this stuff to keep it right. And in general, most people do pretty well,

01:11:32.160 | but I think we could, uh, all improve that, I'm sure. And that is the goal. It's to keep this,

01:11:38.400 | you know, your car, right? You want, if you want it to run forever, you want to keep all the systems

01:11:43.040 | working right and in balance. You don't let things get off too far. And I think there's a tendency,

01:11:48.240 | and I think there's a problem with medicine today. We wait till things are broken and then try and fix it.

01:11:53.760 | And so obviously what you want to do is have people as well-tuned cars for their entire life and then,

01:12:00.480 | you know, pass away then. That's how it should work. Uh, and so I think that's what we want to do,

01:12:07.920 | keep people tuned. And so we probably don't get off to a good start early in life when we start people

01:12:15.920 | with all these not so good diets, like all of the success of processed food and sugar and losing our

01:12:22.480 | microbiome diversity. I think we really want to keep our car off and running right from the get-go.

01:12:28.960 | It's, you know, it's a little bit late for some of us because we're probably a little bit

01:12:33.760 | hardwired, although I think we can tune that. I try to do that as best I can, I guess.

01:12:38.480 | Seems to be doing a good job.

01:12:39.440 | Yeah. Well, anyway, we'll do it the best we can. So.

01:12:42.160 | When I, um, travel, I will occasionally take a probiotic

01:12:47.040 | in addition to all the other things I'm doing to support my gut microbiome. I do take a supplement

01:12:51.040 | to support gut microbiome. I also try and eat lots of fruits and vegetables. I will say I'm very

01:12:56.000 | intrigued by the, these fiber data, different types of fiber data. I'm intrigued because I noticed that

01:13:02.400 | some vegetable foods just don't agree with me, even if I'm careful to chew them properly and do all

01:13:07.280 | that. Um, and I find that over time I've just oriented towards eating the same, you know, six to eight

01:13:12.640 | vegetables, but, uh, I'm tempted to do the following experiment. Tell me if this is a good experiment,

01:13:17.200 | Snyder. Uh, if I'd be, uh, get a shot at a sabbatical in your lab, keep eating the same thing I'm

01:13:23.040 | eating, exercise the same, do it, do things that the way I'm, I'm doing them now, but try a supplement

01:13:30.080 | like you said, Metamucil, which is one particular type of fiber, and do the before and after, um,

01:13:37.200 | LDL cholesterol, ApoB, blood glucose regulation with a continuous glucose monitor. Then stop, do a washout,

01:13:45.360 | swap that out for increasing like inulin fiber through some other source. So, so in other words,

01:13:51.200 | add, add in a, a pure fiber source, uh, on top of an existing diet and see how that impacts, um, blood

01:13:58.640 | metrics and subjective wellbeing. Yeah, I think that would be good. I'd love to know your microbiome and

01:14:04.800 | these are the sorts of things we're trying to sort out now. I don't have an answer, but I imagine the

01:14:09.760 | microbes you have in you, they have certain hydrolases that break down these fibers and everybody's

01:14:16.240 | microbiome is very, very different. Uh, so we, we have communities of microbes and, and every

01:14:22.400 | person's community is different. And so they, we have these enzymes hydrolases that do break down these

01:14:28.400 | fibers. And my guess is that we already know that yours is going to be different from mine. And so maybe

01:14:34.800 | if you eat a certain fiber, you're not as prepared to handle it as the next person.

01:14:39.600 | So this is why we need to collect the right data and it may be at the end where you need to add

01:14:45.120 | the right probiotic, the right microbe to go with that fiber to better get the tuning you're looking

01:14:52.560 | for. And in the long run, if you probably want permanent, you know, uh, um, incubation of this,

01:15:01.120 | this probiotic into your gut, you may actually have to add a community because they're all interdependent.

01:15:07.360 | They get personalized again early. And so you basically formed your own personal guild.

01:15:12.320 | And so one problem with probiotics is that they, you know, they don't stick that well. Uh, a lot of them wash out.

01:15:20.240 | Although what a prolonged use can, can help colonize some of that may be possible.

01:15:24.880 | And they're cumbersome, they're expensive, they require refrigeration, most of them.

01:15:29.040 | Yeah, that's right.

01:15:30.240 | I personally feel fortunate that I don't have what I would consider chronic gut issues. I just avoid

01:15:36.560 | certain foods.

01:15:37.200 | Yeah, but are you avoiding it because you're getting inflammation? You said some don't agree with you.

01:15:42.000 | Is that because of gas or is that because of inflammation?

01:15:45.680 | It's more of an inflammatory response. Yeah.

01:15:48.320 | I can just kind of feel like you don't feel well and I feel kind of like overtaken by some process,

01:15:53.760 | which that's what I'm like, you know, this is a poor man's, uh, I extract to, uh, you know, um,

01:15:59.760 | But if you can figure out which fibers might be inducing that specifically, maybe you can avoid those

01:16:05.280 | foods with those fibers. I don't know. And again, fiber seems to be very personalized. So I think

01:16:11.760 | it is something you can try. It's a pretty easy experiment to do. I think most people like the idea

01:16:17.360 | of, um, fibers. Again, we like to do individual fibers because ultimately I want to understand the

01:16:23.360 | effect of every fiber and make combinations that would be personalized for people. But, uh, you know,

01:16:29.440 | if you were to get apple fiber or oatmeal is, yes, it's got a lot of, uh, Metamucil and, and the

01:16:36.160 | Arabazionine, but it has other things in there too. And it's probably true that the combinatorics

01:16:41.600 | are important. Uh, and we'll get there at some point with the combinatorics.

01:16:48.000 | I mean, I, I guess I'm a, you know, I am a big data guy. I like the idea

01:16:52.240 | with 8 billion people on the planet. If we even got 1% of those, uh, doing food logging with sugar

01:16:59.360 | monitors and things like that, we'd have a lot of combinatorics all figured out.

01:17:03.760 | Well, you've got a hundred people in your lab. You're running clinical trials all the time,

01:17:07.040 | right. Uh, your human subject, uh, requirements are big. Uh, I, maybe we'll provide a link to,

01:17:13.440 | uh, where people can participate in some of these studies. Yeah. We have studies running all the time.

01:17:18.160 | Yeah. I, cause I know a number of people will be interested to do that. And we're going to talk

01:17:21.600 | more about sensors and, uh, air quality. We've got, uh, uh, a bit more to cover in each domain,

01:17:26.960 | but I think it's really important. Uh, and thank you for breaking up this broad category that we've

01:17:33.440 | all heard about fiber into meaningful categories and just even people's understanding that different

01:17:39.840 | people react differently to different fibers, uh, is really important. A family member of mine was

01:17:45.120 | told that they needed to take Metamucil to get more fiber, had zero impact on their LDL, zero impact

01:17:52.000 | on, um, other important markers. I might suggest to them that they consider taking a different, uh, fiber

01:17:58.240 | supplement in the effort to control. Maybe for them, inulin will be the trick. Great. I, I, this

01:18:03.360 | is the first I'd heard of it at, well, when I was listening to one of your talks. Um, it's a good thing

01:18:08.880 | you have a hundred people in your lab. By the way, folks, having a hundred person lab is, um, exceedingly

01:18:15.760 | rare and, um, we're a little smaller now, but yeah, we're still. Yeah. Well, it's very impressive. Your,

01:18:21.840 | your vigor is undeniable and, um, and I'm just lucky to have amazing people in my lab. I consider myself

01:18:28.240 | very fortunate. Well, I will say not just because you're sitting here, I'm not just saying it to be

01:18:32.000 | kind. Uh, many people in your lab have reached out, uh, for reasons related to collaborations,

01:18:37.200 | et cetera. And everyone in your lab speaks extremely highly of you and working with you. Um, which is not

01:18:42.880 | always the case in large laboratories or small ones, but they, they adore you. I'd like to take a quick

01:18:48.960 | break and acknowledge one of our sponsors function. Last year, I became a function member after searching

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01:20:35.200 | I'd like to talk about organ aging and organ health as a separable set of features from general aging and

01:20:45.040 | general health. I think you are one of the first people that I ever heard say, "Listen, our organs

01:20:50.160 | don't all age at the same rate." Just like most people eventually die because some organ goes first

01:20:57.200 | and then it cascades into other things. We need to start thinking about organ health

01:21:01.840 | in the same way we think about organ disease. We need to start thinking about organ age

01:21:05.600 | as independent things. Like maybe my liver is much older than my heart at a genetic level,

01:21:12.160 | at a functional level. What are your thoughts on this and how can we start to parse organ age?

01:21:19.360 | So I'd like you to comment on that. And also perhaps this idea that we just age linearly is not correct.

01:21:28.240 | That maybe there are some cliffs that come about it at particular phases of life. Can you talk about

01:21:34.320 | these things? Yeah, let me tell you a little how we got into this. So we set up, it comes from my

01:21:40.400 | philosophy that I think, you know, medicine is broken. We tend to do sick care rather than health care.

01:21:45.840 | So we started when I moved to Stanford now 16 years ago, this idea, maybe we should, first of all,

01:21:52.400 | you don't measure people very much when they're healthy. You don't measure them very often.

01:21:56.320 | So just, you know, it started with me, but the goal was to do a bigger group, which we did,

01:22:01.120 | profiling people, collecting as much data as possible while they're healthy. So we, you know,

01:22:08.000 | people would get blood, their microbiome, all urine, and we would take these and do what's called

01:22:14.960 | omics measurement. We'd make as many measurements from their blood as possible on top of deep clinical

01:22:20.800 | measurements, using all these new tools. And we would do it every three months and we do it while

01:22:26.400 | they're healthy. If they got ill, like from a viral infection, things like that, we would take more

01:22:31.760 | samples to be able to collect more carefully to see what was going on when they first got ill.

01:22:36.880 | And so we've been running this study on me now for about 15 and a half years.

01:22:44.160 | And for this group of people about almost 12 and a half years. So we've been profiling this group of

01:22:50.960 | people. Some have dropped off by now, because it takes a lot of energy to be part of one of these,

01:22:56.400 | that particular study. But anyway, others have come in. And so, yeah, we've been running this for

01:23:02.080 | some time. And the idea is to see what a healthy profile looks like. How does it change over time,

01:23:07.360 | which we interpret as aging? You know, what happens when people first get ill? And we're very enamored

01:23:14.240 | by these technologies. In fact, we invented some of them, our lab did, for these omics technologies,

01:23:19.920 | like something called RNA-seq, where we can measure all your transcripts. And we have ways of following

01:23:27.200 | all your proteins with protein chips and things like that. So our lab did invent a lot of these,

01:23:32.880 | they're called the omics technologies. So it's ways of collecting big data from, again, your blood, your urine,

01:23:38.640 | and even your microbiome. And so we basically sequenced people's genome, made all these measurements,

01:23:45.200 | and followed them over time. Well, I was going to say, we were also curious whether we could use

01:23:50.240 | some of these technologies, like genome sequencing, and, you know, this method for measuring transcripts,

01:23:57.760 | are any seeking things for better, you know, maybe managing people's health. And then we brought in

01:24:03.840 | the wearables when they were first fitness trackers. We thought, well, maybe they're a little more

01:24:07.760 | interesting than just fitness trackers. So we put them on for health monitoring. And I can tell when we

01:24:13.200 | started, it was a bit controversial at the time. A lot of the physicians are not like sequencing the

01:24:17.680 | genomes of healthy people. This shows when we, it was right after genome sequencing was first coming out.

01:24:22.720 | And, you know, they were worried we were going to turn everybody into hypochondriac. It's going to cost

01:24:28.000 | millions of dollars. And most people have warmed up to it now, not a hundred percent. A lot of people

01:24:32.480 | still don't like that. They still don't like the wearables. I'm sure we'll talk about that. But anyway,

01:24:37.280 | we did show that a lot of people learned some pretty important things from their genome. One young guy

01:24:42.000 | turned out he had a mutational heart gene and his father died right around the time we sequenced

01:24:47.680 | his genome. His father died of a heart problem. And sure enough, he has a heart defect that was

01:24:53.120 | uncovered by his genome sequence. So we had examples like that. And then same with the wearables uncovered

01:24:59.280 | things. All kinds of things popped up. Actually, 49 people had what we would call major health discovery

01:25:05.520 | just in the first three and a half years of running the study and somewhere with the wearables, with all kinds of

01:25:11.200 | things. That was the thing. It was no one technology. What we're doing is we're getting a much more complete

01:25:16.640 | picture of people's health. And we discovered these things then before they have symptoms. So we're profiling

01:25:21.200 | people while they're healthy. And we're looking for things that might be off. And so the way I like the analogy I like to use is that

01:25:30.880 | if your health is a thousand piece jigsaw puzzle, the way when you go to a physician's office today, we would say they measure five or six of those thousand pieces.

01:25:40.000 | They just don't get a very good picture. We're trying to measure five or six hundred pieces, get a much clearer picture.

01:25:46.720 | And so 49 people, we uncovered something pre-symptomatically, caught some with early lymphoma, two people with pre-cancer,

01:25:54.640 | two people with serious heart issues, one from the genome sequencing, one from the wearables.

01:25:59.600 | So this is part of a study. Has this been commercialized?

01:26:03.760 | Like if I want to RNA-seq or deep-seq or this is, by the way, just a nomenclature. If I want to

01:26:11.520 | look at mutations I might have or how healthy or how sick different organs or cells of mine are,

01:26:19.840 | what's available to me nowadays? Yeah. So we spun off a medical version of this. This is QBio that does

01:26:25.920 | whole body MRI, which most people will tell you that most physicians will tell you, you should not do that.

01:26:30.880 | Oh, let's pause there for a second. Cause I will say I've done a Pernovo scan.

01:26:34.800 | Yeah.

01:26:35.120 | They're not a sponsor of the podcast, but I did Pernovo scan.

01:26:38.960 | Yeah.

01:26:39.200 | And...

01:26:40.960 | What'd you think?

01:26:42.000 | I thought it was great. I watched the first segment of a documentary on Netflix while my body got scanned.

01:26:47.440 | I'm not claustrophobic. So going into the tube was no big deal. I got to see,

01:26:52.960 | thankfully, I, you know, I think you're allowed one white spot on the brain per decade of life.

01:26:58.960 | I'm approaching 50 in a few months. I've got... So up to five would be okay. I've got one little

01:27:03.920 | one, which is good because I did some high impact sports early in my life and some martial arts where

01:27:10.320 | I got hit in the head and I don't recommend doing that, folks. So I was a little worried about that.

01:27:16.880 | I learned that my intravisceral fat is very low. So I, that was relieved to see that.

01:27:23.040 | Yeah.

01:27:23.280 | Yeah.

01:27:23.360 | And, you know, for the most part, it provided a useful baseline.

01:27:29.440 | A good friend of mine since childhood, who's a chair of neurosurgery, not at Stanford, but at a nearby

01:27:35.600 | university, told me that it is not uncommon for him, like on a monthly basis, someone will reach out

01:27:43.680 | saying, "Hey, I went in for a whole body MRI and discovered that I've got a tumor on my optic chiasm,

01:27:48.880 | or I've got a small glioma." And you said physicians don't like that people are getting

01:27:54.240 | these whole body MRIs. I'll set him out as an example of a physician who appreciates that people

01:28:03.120 | are doing this. Now then, he's a surgeon. Surgeons like to cut. He's perhaps one of the finest

01:28:09.280 | neurosurgeons in the world. I think all the neurosurgeons I've spoken to admire him tremendously. So,

01:28:14.800 | but I agree that many physicians don't like the idea of people getting scanned because that means

01:28:22.400 | they get calls of concerned, quote, unquote, hypochondriacs. But in my mind, that speaks to the

01:28:29.040 | deficits of the medical community, not to the deficits of, of, of the scanning technologies, right?

01:28:35.600 | I mean, I mean, I mean, it's kind of, if you step back from, it's kind of crazy, right? Like doctors,

01:28:42.000 | it's just, I mean, from a purely just like, if we just made it completely a-emotional, it's more

01:28:48.160 | business for them if somebody has problems. So that doesn't square with their response. There's something

01:28:53.680 | about people advocating for their own, um, health exploration, controlling their own health exploration,

01:29:01.680 | that really seems to vex a lot of doctors. They don't like it. And it doesn't make any sense to me.

01:29:06.880 | Like, like, wouldn't you want your patients to be health minded?

01:29:09.120 | I think it's part of the broken healthcare system, right? They have 15 minutes to spend with you.

01:29:13.600 | Yeah.

01:29:13.920 | So when people show up with their, I mean, the number one concern about whole body MRIs is

01:29:19.120 | they'll find nodules, right? If you go high enough resolution, you're guaranteed to find nodules.

01:29:23.840 | Yeah.

01:29:24.320 | Men have in their prostate, women have in their ovaries. If you go high enough resolution,

01:29:27.440 | 100% of the time, then people show up and say, well, I got these nodules.

01:29:32.080 | And, you know, nodules are cell growths and they can be benign cell growths.

01:29:35.360 | Yeah. Or they're just not even growing. They're just there. They may have showed up early in life.

01:29:39.920 | And I mentioned, I've had 20 of these things and I have nine nodules. And the point is,

01:29:46.000 | it's not whether you have nodules or not, do you have any growing nodules?

01:29:49.200 | Right. Right.

01:29:50.080 | And that's the key. And if you've never done a baseline, you'll never know if they're growing.

01:29:54.160 | So I'm happy to say none of my nine nodules that have been spotted are growing.

01:29:57.840 | I'm relieved to hear that.

01:29:58.320 | And I know that. So, and you've probably seen a similar situation, but a friend of mine,

01:30:03.840 | you know, woke up one day and couldn't move his arm. And so they rushed him to the emergency room.

01:30:10.800 | They did, they scanned the relevant area. They saw he had a tumor on his spine. So they

01:30:16.080 | took it out and things seemed fine. Then they did a whole body MRI follow up later and they found

01:30:22.320 | three more nodules. So the question is, were they there to begin with or had his tumor metastasized?

01:30:30.400 | No way to know. They had no baseline. So I think having these baselines is super important for everyone.

01:30:36.880 | I think people bulk at the cost. So it's about, as I recall,

01:30:40.080 | it's about $2,000 to get one of these whole body scans. I think we can assume that the cost is going to

01:30:46.320 | come down just as everything whole genome sequencing is going to come down. Maybe even insurance would

01:30:51.520 | cover it at some point. I mean, it's so trivially easy to do once you have, you know, a place that

01:31:00.880 | will do it, that if the cost were to come down, I think you'd save tons and tons of lives. I see it

01:31:06.080 | as a boon to the medical industry, not just for making money, but for improving people's health.

01:31:11.280 | Right.

01:31:11.280 | I mean, as you said, when you go to the doctor, they measure, they put a thermometer in your

01:31:16.400 | mouth. They take your blood pressure, take your height, take your weight, ask you a few questions,

01:31:20.000 | ask you if anything's changed. And then you're like, it's almost like better off just

01:31:24.880 | like calling them up on the phone at this point. You can do all of that stuff at home.

01:31:29.920 | You can. And in fact, we should be doing that stuff at home anyway. We can talk about that later.

01:31:34.480 | But yeah, what QBIO does is they do whole body MRI and they've designed ways that they can do it in

01:31:40.400 | about 40 minutes, 35 to 40 minutes. So it saves a lot of time. And then they also do some, a medical

01:31:48.080 | version of what I was telling you before. They don't do, for example, the transcript on the RNA-seq stuff,

01:31:53.280 | some of that, because they have set it up in a way that it's actionable information because they,

01:31:59.440 | you can then take the data to your physician who will know what to do with it.

01:32:03.360 | Great.

01:32:03.840 | And so, and yeah, it turns out, just like you're saying, just from the first 100 plus people,

01:32:10.480 | they discovered early ovarian cancer, all pre-symptomatically, just like in our study, the 49

01:32:16.080 | people who found their things pre-symptomatically. They found, you know, cardiovascular conditions are

01:32:22.560 | pretty serious. They found even early pancreatic cancer, which is almost never found early. And so they

01:32:29.200 | discovered these things. And sometimes it was by the longitudinal measurements, they saw things shift.

01:32:36.320 | Sometimes at what we call multivariate, they'd see several things shifting. We discovered that and as

01:32:40.800 | well, we might see one thing off. And you'd say, well, I don't know. But when you see three things all going in

01:32:47.680 | the same direction, you worry about that. And a good example is if you go to a physician today and

01:32:53.440 | your glucose is high and it's normally been low and it might spike up, they'll say, well, you know,

01:32:58.720 | have you, were you ill yesterday or something like that? All that explains it. Let's ignore it. Come

01:33:04.240 | back in two years, right? And that's just not enough. And yeah, and that might have been a clue for

01:33:10.800 | something big. And we've seen that in our study. We'll see somebody who shifted off their liver enzymes

01:33:16.400 | and they'll come to me and say, Mike, I'm still in the normal range even. You know, they're,

01:33:20.880 | they're, and this is why we're big on baselines. That's a big theme in our work. No way your healthy

01:33:25.600 | baseline is like the MRIs. And they'll be running in the low end of a normal range for their liver

01:33:31.600 | enzyme. And suddenly it'll double, but still be in a normal range. And they'll call me up and say,

01:33:38.080 | hey, what's going on here? I said, I don't know. Why don't you go get another measurement? Sure enough,

01:33:41.920 | then they shifted out a normal. So I think the trajectories of these measurements is key. I think

01:33:47.840 | knowing how you're progressing is a big deal. And that's how we think, just like your car, if you see

01:33:54.640 | something going off, you want to see it when you catch the first symptoms, not once your car is

01:33:59.840 | broken down on the side of the road, the engine's blown up or something. So I think that's how we

01:34:04.800 | have to shift medicine. Amen to that. A thousand times over. Let's talk about some of the sensors you're

01:34:12.320 | wearing and what people can monitor now. You talked about continuous glucose monitors, and that's

01:34:20.160 | non-invasive. I mean, you don't even feel it going in. It's just basically a sticker thing. But what are

01:34:26.480 | some of the other things? Most people are familiar now with sleep tracking. And of course, that's pulling

01:34:33.520 | heart rate data and a few other things. But yeah, walk us through what's possible now with non-invasive

01:34:38.720 | trackers. And maybe let us know which particular ones you're wearing. This isn't a promotion of

01:34:46.880 | particular products. I'm just very curious. You're armed to the teeth with sensors here.

01:34:51.600 | So what do you got? Yeah, I'm a big measurement guy.

01:34:54.000 | Yeah, well, you're a Stanford faculty after all. So I have my, this is my Fitbit. This is my Apple

01:35:02.240 | Watch. And then I happen to have a company that's called Sensomics that has two different, this is a

01:35:06.720 | new one they have out, and then the older one. And so they all measure heart rate, heart rate variability,

01:35:13.440 | and reasonably accurate, meaning, you know, not that far off. And so, again, for the listeners,

01:35:20.160 | resting heart rate, everybody knows. But heart rate variability is an important measurement,

01:35:24.640 | more and more appreciated these days. When you're ill, your variability drops. And both

01:35:30.000 | those are fairly accurate these days for most devices. Oh, and I have a ring. This one happens

01:35:35.200 | to be a circle. I used to wear an aura ring. It's not an aura ring? Which one is that?

01:35:40.800 | It's called circle. They have their different parameters. So there's no right or wrong to this.

01:35:46.080 | You have the same thing. You have to match it to your lifestyle. Some, you know, you charge them

01:35:51.680 | while you're in the shower. They're charged for five days. And others, you have to charge for an hour,

01:35:56.000 | hour and a half to keep it going. So you have to find the one that works best for you. I do think

01:36:01.360 | wearing them overnight, it's a great time for health monitoring. So I'm a big fan of that.

01:36:06.560 | Anyway, they measure that. Some measure blood oxygen. Some of that's accurate. Some it's not

01:36:10.960 | accurate. Depends on the device. Some measure skin temperature. Again, some of that's accurate.

01:36:17.040 | Some it's not. Depends on the device. They also measure something called galvanic stress response.

01:36:22.640 | Some do. That's conductance on your skin. And that is not something we normally measure in a

01:36:28.240 | doctor's office. But it turns out it has value for hydration. Because when you have dryers, like when

01:36:33.840 | you're diabetic, you'll have drier skin. And I should have figured this out earlier when I first became

01:36:38.720 | diabetic, I got itchy because my skin got dry. Anyway, you can measure that with your smartwatch

01:36:44.880 | and get that in real time. The galvanic skin response. Yeah. And also as a measure of stress,

01:36:50.080 | when you're stressed, you sweat more. And so you can pick that up as well with these devices. So there's a

01:36:56.560 | fair number of things. And then some of them you can measure, you know, an EKG and sleep, of course,

01:37:02.320 | super important. Their accuracy for the stages is still questionable. It depends on the device.

01:37:08.240 | They're getting better though. I use an eight sleep. And I will look, I'm now in the habit of only

01:37:16.160 | looking at the data every few days. Okay. Because I'm doing an experiment on myself where I measure my

01:37:22.560 | subjective feelings of rest and alertness and energy and compare it to the data. And the only way to do

01:37:29.760 | that properly is to not glance at the data first thing in the morning. Okay. Right. Because it just

01:37:33.440 | biases how you feel. Our colleague, Ali Crum at Stanford has done some nice experiments where they

01:37:38.640 | tell people after a genuinely poor night's sleep, they got a great sleep, or they tell people after

01:37:44.640 | a great night's sleep, they got poor sleep and they show them a sleep score and they give them some data

01:37:48.880 | and it's false data basically. And people's levels of alertness, wellbeing, et cetera, are strongly biased

01:37:56.640 | by what they are told their sleep was like, as opposed to what it was actually like. This is a big deal.

01:38:03.200 | Right. And I think speaks to all the beautiful studies that Ali's done because she finds stuff

01:38:07.920 | like this all the time. Right. And nutrition and wellbeing and these mindset effects are really

01:38:12.560 | powerful. So I look at my sleep data maybe once every two or three days. Right. And I'm constantly

01:38:18.960 | striving to get more REM sleep. By the way, warming your sleeping environment in the last two hours of

01:38:24.240 | sleep will dramatically increase the amount of REM sleep you get. I learned that trick from Matt Walker

01:38:28.720 | and it works spectacularly well. I'll have to give it a try. Yeah. Matt taught me that trick and I'm

01:38:33.440 | getting close to two and a half hours of REM sleep now. Wow. And I only sleep about six and a half,

01:38:38.960 | seven hours to feel rested. Nice. So it's pretty spectacular. And I think I got it. I got to try it.

01:38:43.600 | I thank Matt for that tip. It's one of my biggest weaknesses. I don't sleep that well.

01:38:47.440 | Yeah. So cool bed in the beginning. Right. I do do that. The night and then the opposite toward morning.

01:38:52.240 | Interesting. So Matt taught me that trick and it's like,

01:38:55.120 | whoa, it's completely... That is so cool. I now emerge from sleep feeling so much better. Right.

01:38:59.680 | Unless I was having a disturbing dream, in which case you got to like go think about something else.

01:39:04.560 | But in any case, the sleep trackers, right, on the eight sleep, because the tracker is stationary,

01:39:12.960 | it's fixed to the mattress. My understanding is that it's more accurate than if the tracker is on a limb

01:39:19.120 | where you could be moving, because that will disrupt sleep stage measurement. But I don't know if that's

01:39:24.960 | actually true or not. I don't know. I haven't measured it. I haven't looked at the data on that.

01:39:29.040 | Okay. Yeah. So what about HRV? We're hearing more and more that HRV is perhaps even more interesting

01:39:35.840 | than resting heart rate. I think it probably is. What are some things that we can do to improve our HRV?

01:39:42.160 | What should our HRV be? How much control do we have over HRV range? This kind of thing.

01:39:47.760 | Well, exercise is supposed to be one of the best ways to do this. Again, I'm not a cardiologist. I'm

01:39:53.040 | not an expert there. I don't know for sure, but I know personally, keeping my stress down and sleeping

01:40:01.280 | better seems to help. I've noticed that. That makes sense. Recently, yeah.

01:40:06.640 | And one of these AI programs, again, happens to come from January. They take all your data,

01:40:11.280 | bring it in. And they were like looking at us and my HRV, believe it or not, went up like 28% or some

01:40:16.800 | incredible number. Yeah. And I was trying to figure out what it was due to it. And I think I'm sleeping

01:40:22.160 | better actually. Are you a meditator? No, I used to, and I know I need to make more time. In some sense,

01:40:30.400 | maybe my bike ride is the equivalent of that at the end of the day. And on the weekends, I

01:40:35.040 | try and do a little bit of gardening. That's my form. I am a big believer you need some form of

01:40:41.440 | calmness. And I used to meditate for like five minutes after exercise. I need to get back to that

01:40:47.280 | for sure. There's some interesting data on just maybe give this a try as an experiment. Periodically

01:40:53.520 | throughout the day, just do a deliberate to lungs empty exhale, which activates the vagal

01:41:00.000 | pathway to the sinoatrial nodes, slows your heart rate down. There's evidence that will improve your

01:41:04.400 | HRV both in waking and sleep states. Is that right?

01:41:07.120 | Yeah. Just try it out. So see what you think. So one minute every day or?

01:41:09.920 | No, no, no. Just periodically throughout the day, just remember to dump all your air,

01:41:14.080 | as the free divers would say, just . Yeah.

01:41:16.800 | Really long exhale. I haven't tried the breathing stuff.

01:41:19.920 | Yeah. A lot of people are saying that's really good.

01:41:21.840 | You just intersperse it so there's no breath work. You don't have to set aside time.

01:41:24.720 | Yeah.

01:41:25.120 | I'll ask you something different related to stress. It goes back to some sleep data. You seem to love

01:41:31.520 | your work. Like your... Oh, I love it.

01:41:33.280 | Before we came in here, you're like, "I love my job." You know? There are really interesting data out of

01:41:39.440 | the sleep lab at Stanford that show that positive next day anticipation is one of the strongest

01:41:46.000 | determinants of sleep quality. I didn't know that. And that it really does seem to be that if you are

01:41:51.280 | excited about your life, you can get by with less sleep because the amount of quality sleep you get

01:41:56.320 | is higher. Okay. So maybe you don't need to meditate. You just need to continue to do what you love.

01:42:00.240 | Maybe. Yeah. No, I do love what I do. And for me, there's no better rush than a great result.

01:42:06.160 | I'm an academic at heart. We spin off the companies to try to get, I think, the things we're doing,

01:42:13.040 | you know, I hope out to a broader group of people, which, you know, it also is a way of showing the

01:42:19.680 | stuff really works and that it's not all BS that you're doing in a lab. So I do love what I do. And

01:42:26.560 | I don't know. I'm very fortunate. I have amazing people in my lab, as I mentioned before, who

01:42:31.680 | they come up with a lot of the ideas. I view us as a team that try to push forward on these various

01:42:38.880 | things. I try to create an open environment where people aren't afraid to share ideas and

01:42:44.720 | and push things forward. Yeah. Anyway, I realized we got away from the organ aging part. Yeah. If you

01:42:50.720 | want to go back to that. Let's go back to that. And then I would like to also get back to psychological

01:42:55.040 | factors and mental health. On the aging, I mentioned how we're doing all these measurements and tracking

01:43:00.160 | people over time. We've now been doing this for over 12 years on this 109. Some have dropped off,

01:43:06.000 | and say new ones have popped on. And what we discovered by just looking at the healthy time

01:43:11.680 | points is that people, you know, they do change over time, even in the healthy times, but they're all

01:43:19.600 | changing differently. Meaning we look at the biochemical pathway. Some will have their top biochemical path,

01:43:25.600 | dilated cardiomyopathy pathway changing, or sorry, that was dilated. Sorry, that was hyper trophic

01:43:34.080 | cardiomyopathy signaling pathway shifted. Other people, it's metabolic. Some are immune. We call these

01:43:41.200 | agotypes, aging pathways. And I kind of like that a little bit better than organ aging, because some of

01:43:46.880 | the things you pick up are like oxidative stress, which go across lots of organs, or, you know, the,

01:43:52.960 | you know, inflammatory, inflammation, that's kind of cross-organ as well. So we call these agotypes, aging

01:44:00.640 | patterns that we see. And it turns out, everybody's different. So some people will be the cardio, some people

01:44:08.160 | be the metabolic, some are liver, some are kidney, based on the markers we see in the blood, and some

01:44:14.000 | are immune, and some are all, all the above or parts thereof. So we're all different. And what's cool about

01:44:20.160 | it is it's actionable information, meaning we, a metabolic gauger, when you, you actually see that,

01:44:26.800 | they'll see how they're shifting. And again, have another company involved in this, they do this micro

01:44:33.920 | sampling, I'm sure we'll get into, where they measure your metabolic patterns. And by the way,

01:44:38.720 | we think your metabolism is the best way to see the shifts of all the different, proteome is good too.

01:44:44.400 | And my, my colleague, Tony Viscoras, he basically has looked at this organ aging stuff as well from

01:44:50.960 | the proteome extent, from proteome, meaning group of proteins. He's, he's followed this. And same thing,

01:44:57.520 | you can follow this, these agotypes, if you will, these aging patterns. And the information

01:45:03.760 | is totally actionable. You can see, as I say, for the metabolic gauger,

01:45:07.840 | some of the folks seeing this, they lost weight, or they exercised, and they improved their patterns.

01:45:12.720 | Now, I'm not saying they got younger, but they did improve their age of types. And so,

01:45:17.680 | I think the information is very actionable. And so, again, and this is one where we commercialize,

01:45:23.520 | because I want to, it's a very simple task. You can get these little drops of blood, mail it in,

01:45:28.240 | and they'll profile 650 metabolites. And, and the information is actionable. They make recommendations.

01:45:34.960 | And it's not just exercise more, eat better, but very, very specific.

01:45:38.400 | What, what is the name of this company?

01:45:40.240 | It's called Iolo, I-O-L-L-O.

01:45:42.320 | And this is now commercially available.

01:45:44.320 | It is.

01:45:44.320 | So, if I want to, so if I want to figure out my agotype, did I get that right?

01:45:48.400 | Right.

01:45:48.480 | My agotype, I can do that by sending in a few drops of blood, and it will tell me.

01:45:53.520 | Correct.

01:45:53.920 | They'll send you a kit. It's a very special kit, because not any,

01:45:57.440 | like putting things on cellulose is not the best way to save your blood.

01:46:01.360 | Anyway, it's a special kit. You mail it in. Yeah, with something called metabolomics and mass

01:46:07.600 | spectrometry, you can profile. It's a targeted assay, 650 metabolites. And they cover all these areas,

01:46:14.160 | many, most of it's in the scientific literature. It's just not in the clinical labs, like things

01:46:20.080 | around your kidney function, your heart, things like this. And they give you these profiles. And

01:46:24.560 | they say, these are normal. These are going off. And then they can even predict your, again,

01:46:30.400 | biological age. So, you may know your biological age is not necessarily your chronological age,

01:46:35.520 | your age and years. And if that goes, if things are off and maybe are not so good direction,

01:46:42.160 | you can actually take action. You can say, well, all right, my inflammation's fine. But my heart

01:46:48.480 | age is off. And they can give you very specific recommendations to do around that. Or if it's

01:46:53.520 | kidney, again, same thing. Maybe eat more of certain things and avoid other things.

01:46:58.480 | Cool. I'm going to try it. So let's talk about biological age, because I think the first time I

01:47:04.000 | heard about the concept of measuring one's biological age versus chronological age was from David Sinclair

01:47:11.360 | when he was referencing Horvath clocks. That was some years ago. And then, of course, Brian Johnson

01:47:18.400 | likes to boast his biological age. He has a biological age competition, I think, online with some folks.

01:47:25.920 | And then, there are also folks like my friend Peter Atiyah, who will be very direct in telling you that

01:47:34.160 | he doesn't think much of biological age when it's a number to assess whole body age.

01:47:40.720 | He's like – I won't use the words that he uses, but he doesn't think it's worth anything at all,

01:47:46.000 | frankly, as a measure. But here, you're talking about something distinctly different. You're talking

01:47:50.800 | about the progression of aging of different organs or different organ systems.

01:47:55.280 | I think the Horvath clocks are correct, meaning they do measure biological age. But the problem

01:48:01.760 | is it's not actionable. What do you do? Your methylation pattern, that's a modification of DNA,

01:48:07.680 | has shifted, and it gives you an overall value. Well, what do you do with that? You don't know,

01:48:14.080 | you wouldn't – yeah. And they can predict something called grim age these days, your time to death,

01:48:19.200 | your mortality. Oh, nice. Same thing. I mean, what are you going to do with that? What's special about the

01:48:25.040 | age of types is that they're breaking it down. And so they say, all right, your immune age is off,

01:48:31.440 | you can do X. Your oxidative stress is off, you do Y. So it's basically actionable information. So I

01:48:41.120 | think it makes all the difference. And conceptually, it makes a lot of sense, too. It's like your car.

01:48:46.240 | I know I keep coming back to that analogy. But your car gets older. But certain parts wear out first.

01:48:53.280 | Well, maybe some people do. They replace their whole car. But generally, you would fix the parts

01:48:58.240 | that are wearing it. And ideally, you'd catch it before they break. And I think that's how we think

01:49:03.280 | of age of types. You can go in. And so I mentioned this company earlier. Iola, what they do is they're

01:49:09.440 | tracking your age of types because they're doing these deep metabolic profiles. And they actually make,

01:49:16.160 | they use AI, they pull in things and make very specific recommendations. And then you can,

01:49:22.320 | you know, they'll tell you exact foods to eat and things like that. And 95% of people improve their

01:49:29.200 | markers. Again, I'm not going to say they're getting younger, but at least they're improving their metabolic

01:49:34.400 | markers in the right direction. And so it's actionable information. And it makes a lot of sense.

01:49:40.720 | How powerful role do genetics play in determining potential lifespan? Shortly before starting this

01:49:48.800 | discussion, I looked at the chart of longest living humans. They're all deceased now. But I think the

01:49:55.920 | record is 122 years and some change. And some people think she may have cheated,

01:50:02.960 | but it's not clear. Oh, really? That was a French woman? Yeah, that's right. 120 plus or minus

01:50:08.880 | five years seems to be kind of what people consider a, you know, a spectacularly long life. Yeah, that's

01:50:16.000 | right. Yeah. And that does seem to be the cap. And so, you know, most of our research is built around

01:50:22.240 | extending health span. It is the case that for lifespan in general, it's estimated to be about

01:50:29.440 | 16% of your lifespans due to genetics. One six. One six. That's it. Yeah. And now there's a big error

01:50:36.160 | bar on that. That comes from twin studies and family studies. So although it's thought that for people

01:50:42.640 | live to be 100 or older, then it might be higher. Some people have said 60%. So to live to be really long,

01:50:51.520 | you may need good genes in general, but there's still a lot there, right? There's another 40%

01:50:55.920 | that's due to lifestyle. But for the average person, it's only one six. So your lifestyle is by far your

01:51:02.880 | biggest factor. And you look at people in these blue zones, these areas where people, there's an enrichment

01:51:08.000 | for people live to be 100 or more. They have several things in common. One is they tend to eat

01:51:14.240 | a diet with not much ultra processed foods or processed foods in general. And generally, they tend to be

01:51:21.040 | towards the Mediterranean vegan kind of diet. They eat animal proteins, as I understand, but it's more

01:51:27.840 | fish and chicken. Yeah, that's correct. And less red meat. Yeah. And they're eating a lot of vegetables.

01:51:33.200 | Yes, for sure. And getting fiber through that as well. And then they tend to have,

01:51:40.000 | they're fairly active, meaning, but their form of activity can vary. And they have really good social

01:51:47.280 | networks. So either through family or through community networks. And so that's pretty clear. My

01:51:53.280 | prediction is they probably sleep pretty well, too. I don't know if that's been as well measured as the

01:51:58.720 | other parameters. So I think you do need all of those things if you want to live a long, healthy life.

01:52:04.320 | And that weight may vary from one person to the next. And I think that's the kind of thing we want

01:52:12.880 | to look at. Again, I view people as a combination of things or genetics or epigenetics. I don't know if I

01:52:20.960 | told you all the details of when I became diabetic. It was predicted from my genome. Atul Butte actually

01:52:26.240 | predicted this from something called apologetic risk score, these ways of analyzing genomes. And I'm at

01:52:32.160 | the extreme end. That doesn't work for most people, by the way. But I'm at the extreme end that worked for

01:52:37.040 | me. So he predicted as high risk for diabetes. But I didn't become diabetic until after a viral infection.

01:52:43.200 | It's very strong correlation. And because I measure myself a lot, I figured this out as respiratory

01:52:49.200 | syncytial virus, which actually, you know, it's not that common adults is more common now. But anyway,

01:52:57.840 | I was literally in bed, which is a little unusual for me. And I got a very high temperature. And I wound up

01:53:05.520 | several weeks later becoming diabetic. It's very fascinating, because we actually looked at the

01:53:11.200 | modification of my DNA. It's called DNA methylation. It actually shifted in something like a hundred

01:53:16.960 | metabolic genes in their control regions, called the promoters. And so, the thought is that I was

01:53:24.800 | genetically at risk, and then in combination with this viral infection, this environmental, that's what

01:53:30.160 | triggered my diabetes. Now, I don't think that's true of most people. We're tracking people, I may have

01:53:35.760 | mentioned. In the first part of the study, we saw nine people become diabetic, as we've been

01:53:40.800 | tracking them. And seven gradually became diabetic, as though it was, you know, accumulation of something.

01:53:47.520 | But two people, one of which was me, something triggered it, meaning it kind of got there and

01:53:53.840 | stayed. It wasn't just a transient spike. And so, how often this, you get these genet,

01:54:00.720 | they're called epigenetic modifications happening is not so clear. But it's now the case, you may know,

01:54:07.120 | with COVID, two to four percent of people are becoming diabetic after a COVID infection. So,

01:54:13.360 | it's not unreasonable to think that they're having epigenetic changes like me. It hasn't been measured.

01:54:18.960 | That's something we'd like to pursue. But the effects of these viral infections and stuff, you may know a

01:54:24.960 | lot of people get something called chronic fatigue syndrome after some adverse, say, pathogens. It's not

01:54:31.440 | always clear what's causing it. It seems to be different for different people. But the idea of these intense stresses,

01:54:36.720 | diseases may be from a viral infection or other pathogen, triggering some long-term chronic effects

01:54:42.720 | is maybe more common than people realize for autoimmune disease, for chronic fatigue syndrome,

01:54:49.440 | in my case for diabetes, may be, as I say, more prevalent than people realize.

01:54:54.880 | It's so interesting to think about viral infections setting off a bunch of things that are acute,

01:55:01.120 | like rise in temperature, GI tract disruption, et cetera. But then, as you said, longer-term changes in

01:55:08.160 | genes related to metabolism, inflammation, and other pathways, setting a genetic predisposition in motion,

01:55:16.640 | kind of like flicking the domino that was already kind of tilted.

01:55:22.640 | Once again, that homeostatic system concept that you're, yeah, maybe if your genetics is a little bit

01:55:29.040 | weaker, we've noticed, yeah, that we found a new, if you will, set of genes involved in ALS, and that

01:55:38.640 | those genes tend to be underexpressed in, you know, called IPS-derived motor neurons, the relevant cell

01:55:45.920 | types for ALS patients. So it may be that, you know, if your genetics is a little weaker in some areas

01:55:52.240 | than others, and other things could trigger that sort of thing. So I like that general concept that we're,

01:55:59.120 | in some cases, maybe that's beneficial. I'm not saying getting ALS is beneficial, but maybe we're tuned

01:56:05.360 | certain ways, because in ancient times, we had to deal with things like TB and stuff, and the idea that

01:56:11.680 | you would be, well, the classic is sickle cell, right? Folks with sickle cell mutations might be more

01:56:17.280 | resistant to malaria. So maybe some of this tuning helps you in some ways, but is adverse in other ways,

01:56:24.640 | or makes you more susceptible, let's put it that way.

01:56:27.680 | : Yeah, I've heard, you know, here and there about data linking herpes virus to Alzheimer's,

01:56:38.000 | for instance. And you could imagine how it might not be directly related to the symptoms or the

01:56:45.440 | pathology of herpes virus, but that something about the neural inflammation caused on the trigeminal nerve,

01:56:53.280 | which is where the herpes virus lives, that's why people get cold sores, this is HSV-1.

01:56:57.200 | : Which is very common, right?

01:56:59.600 | : Right.

01:56:59.600 | : I think, and most people just combat it and they don't get cold sores.

01:57:02.960 | : Sure.

01:57:03.520 | : But that something about the, the inflammation of that trigeminal nerve pathways,

01:57:09.360 | maybe it breaches the blood brain barrier in certain people, and then it sets off a cascade that we

01:57:14.560 | eventually call Alzheimer's. : Right.

01:57:15.840 | : So these correlations, because that's really all that they are.

01:57:21.280 | : Correct.

01:57:21.600 | : And these multifactorial, I think the way you described it earlier is the best way. You know,

01:57:28.160 | if you have a thousand piece jigsaw puzzle, you want to know which pieces are, you know,

01:57:33.680 | slightly out of alignment or missing entirely. But what we call diseases like Alzheimer's or autism

01:57:40.560 | or diabetes presumably are different combinations of puzzle pieces missing.

01:57:47.280 | : I think so.

01:57:48.080 | : And I think until now, medicine and the general public has been trained to think of disease as like,

01:57:56.960 | those puzzle pieces are missing. And that's what we call Alzheimer's. That's what we call autism. That's what we call diabetes.

01:58:05.520 | And what I'm realizing in talking to you today is that that's far too simplistic.

01:58:10.800 | : Yeah, I mean, there are cases.

01:58:11.840 | : It can't be that, it can't be that simple.

01:58:13.920 | : That's correct. A good example would be Huntington's, right, where you have an expansion of a specific

01:58:21.440 | genetic locus. There are elements that shift there. And that's highly associated with Huntington's. Those would be

01:58:29.200 | single condition things that trigger it. And that does happen, but that's not most disease. That's

01:58:34.320 | more of the exception than the rule. And by the way, even in those cases, there are people that escape it.

01:58:39.360 | : Oh, you have escapers.

01:58:40.480 | : Yeah, who have somehow escaped that. Not always understood, although they may hold clues to

01:58:46.400 | perhaps how others could be helped.

01:58:49.440 | : You mentioned ALS. We've not covered ALS on this podcast before, but just very briefly,

01:58:54.800 | my understanding is a few years ago, there was a lot of interest in SOD and superoxide dimutase, an enzyme

01:59:02.240 | being involved in the degeneration of motor neurons, which is what ALS used to be called Lou Gehrig's

01:59:08.720 | disease. But ALS, people, Stephen Hawking had ALS, right? : Absolutely.

01:59:12.880 | : What is the role of superoxide dimutase? And is there anything protective in terms of

01:59:19.040 | behavior or supplementation drugs that people can take to protect themselves against neurodegeneration

01:59:24.000 | of motor neurons or central neurons? You know, we talk a lot about what to do once it's started,

01:59:28.560 | but there's not a lot of discussion about how to protect your neurons, just as a general theme,

01:59:32.960 | like protect the health of your neurons by doing or taking X.

01:59:36.400 | : Right. Well, first of all, I'm not an ALS expert. This is where my genetics came in.

01:59:41.200 | And then we came up with new ways of analyzing genomes. And we applied it to ALS for reasons we

01:59:46.560 | thought might work. Here I just had an amazing postdoc, Sai Zong, and a great collaborator,

01:59:54.560 | Jonathan Kupernak, who basically sort of said, "Mike, this is a great problem to apply these new

02:00:01.040 | methods we had for analyzing." So there were seven genes known, and we wound up finding 690 genes,

02:00:06.880 | and that's true with these new AI methods we have for analyzing genomes. And it explains a lot more

02:00:12.560 | what's called the heritability of the disease. And then, yeah, and that's how I got into it. But,

02:00:19.520 | I mean, there still is no cure for ALS. And how to modify lifestyle, I don't know, but I do know

02:00:27.440 | I'm on sabbatical at UC Irvine right now. And there's, you know, people who are trying to take

02:00:33.760 | this sort of thing on. We'll see how well it works. It is clear there is a study that if you over exercise,

02:00:40.320 | that's worse for you for ALS. But whether that helps you predict, I don't know. So I think it's still,

02:00:48.000 | yeah, not very much known there, at least not to me. You may know more than I do.

02:00:53.200 | No, I, you know, I'm very interested in what one can do to protect against neurodegeneration.

02:00:58.240 | The one that I'm very intrigued by, and here I am not promoting this specifically for everybody,

02:01:05.920 | but years ago, and this is purely anecdotal, but years ago, I was in the office of Richard Axel

02:01:13.040 | at Columbia, Nobel Prize winner for discovering the molecular basis of olfaction, et cetera.

02:01:17.920 | And I observed what many people had told me I would observe, which is that he chewed no fewer

02:01:22.640 | than like six pieces of Nicorette in a 90 minute meeting. And I asked him, I said, what's the deal?

02:01:28.960 | And he said, well, I used to smoke, but I don't smoke because it causes cancer. But I like the nicotine

02:01:34.320 | for the cognitive stimulation. And he looked at me and he said, and it's protective against Parkinson's

02:01:39.520 | and Alzheimer's. I said, really? And he goes, yeah, read up about it. And indeed,

02:01:43.280 | I went and looked and it does seem to be neuroprotective. Now it also raises blood

02:01:48.160 | pressure. It's highly habit forming slash addictive. Most people I know that take two

02:01:52.880 | milligrams of a, of a nicotine gum or a pouch suddenly are taking four, six, eight, then they're

02:01:59.520 | taking a canister every two days. Like it's very habit forming very fast. So it's not something I

02:02:04.000 | recommend. But I'm very intrigued by the idea of this substance, nicotine, when it's not smoked,

02:02:10.400 | vaped, you know, dipped or snuffed that it might actually be neuroprotective. Richard's a molecular

02:02:14.560 | biologist by training. He's not somebody who just says stuff when it comes to science. Sometimes he

02:02:20.720 | just says stuff. He's kind of an out, known to be kind of an outrageous guy. But the data are kind of

02:02:25.520 | interesting, like in rodent studies, that nicotine can be protective in the face of a, of a bunch of

02:02:31.840 | different insults to dopamine neurons, like a comp, a combined low grade head injury with something

02:02:41.520 | else like hypoglycemia, right? The, the two hit model. But it's not a head injury that would kill

02:02:46.080 | neurons. It's not hypoglycemia that would kill neurons. But when they, they, when they coincide,

02:02:49.760 | the so-called two hit model, then you start losing neurons. And in some cases like nicotine can be,

02:02:54.080 | this kind of thing. Okay. So I'm intrigued by things that one could potentially

02:02:58.880 | do to protect neurons, aside from wearing a bike helmet, which I'm relieved to hear that you do.

02:03:04.400 | Okay. In any case, uh, room for further exploration. Yeah. Of course there's motor neurons

02:03:08.800 | for ALS. Right. Motor neurons for ALS. So I don't know how similar or different, yeah. Yeah. Yeah.

02:03:14.240 | Yeah. It's super interesting. I don't think anyone wants to lose their motor dopamine or any other

02:03:19.680 | neurons. So it's, it's, uh, you know, with rare exception, we don't replace them. So, um,

02:03:24.720 | I think that's going to be a really important area going forward. Right now it's mostly the don'ts.

02:03:29.920 | Don't get a head injury. If you do, don't get a second one, quit the sport. People always say,

02:03:35.120 | I, you know, I, I play rugby and I got a really bad concussion. What should I do? And I go,

02:03:39.600 | find a new sport. And they never liked that answer, but you know, um,

02:03:43.120 | Back to behavioral modification. Yeah, exactly. It's mostly don'ts. Um,

02:03:47.360 | I'd like to talk about some things that might seem a little bit more in the esoteric realm. Okay.

02:03:53.840 | Let's start with, uh, low esoteric, but still in the kind of area that now people are talking about,

02:04:00.480 | um, which used to be considered kind of woo, which is air quality.

02:04:04.800 | Yeah.

02:04:05.600 | Everyone agrees pollution is bad. What people don't agree upon so much is how much otherwise like

02:04:13.920 | permissible air, like not during a fire or, um, living in a city versus a suburb versus, uh,

02:04:20.560 | in a rural area, uh, pesticides, et cetera, you know, how air quality impacts our health.

02:04:26.000 | You've got a device on the table that literally is measuring how's our air quality in here,

02:04:29.760 | by the way. Uh, you're good. You're at PM 2.5 at three PM 10 of four. Okay. Yeah.

02:04:35.920 | Which is very low by the way. Yeah. We've turned off the AC for,

02:04:39.600 | for recording purposes afterwards. We tend to ventilate. Yeah. It was one earlier. So, uh,

02:04:44.240 | yeah, but we had fires here in LA not long ago. Right. How?

02:04:48.000 | Probably would have gotten to 200, maybe more. I mean that it was dreadful. Yeah.

02:04:52.880 | It was really bad. Yeah. And a lot of people and animals are still suffering, um, symptoms,

02:04:58.640 | you know, so, um, so what's the logic behind this device and, and what's, I mean, I imagine you brought

02:05:04.480 | it here for a reason. Well, no, I bring it all the time. It's always next to me. Oh,

02:05:08.960 | you carry this everywhere. Oh yeah. I've been doing this for eight or 10 years now. And if a restaurant or

02:05:13.440 | another space doesn't have a good air quality, you, you just leave, is that? No, uh, probably.

02:05:20.480 | You inform them and then leave? Uh, people ask and I, I'm always honest. I tell them what it is.

02:05:26.720 | I, hasn't been so bad where we'll get bad is during the fire, but there are a few times. Um, so I'm doing it,

02:05:34.800 | backing up a little bit. It's a very underexplored area. And that's kind of, again,

02:05:39.200 | the academic side of me. I want to understand how does your environment impact your health? And

02:05:45.440 | it's not just air, but I, that's the area we decided to start in. And you know, what are you breathing

02:05:51.280 | right now? You have no idea, right? And so that's the principle. I'm a sort of big data guy. As you can

02:05:58.320 | tell, I do all these measurements on the inside. What about the outside? And we know from plenty of work

02:06:04.480 | from others. You mentioned, you know, particulates in the air. This is where the PM 2.5, that's thought

02:06:09.680 | to be the stuff that penetrates your lungs and causes all kinds of problems. Goes from the lungs

02:06:14.960 | into the bloodstream and can cross the blood brain barrier. Yeah. And it's, yeah, not good. So anyway,

02:06:20.880 | the, um, and these days, as you know, plastics and microplastics have, have erupted as a, as a pretty big

02:06:28.320 | health concern, but nobody's a hundred percent sure what it means, but they do know now that when

02:06:34.560 | you dissect people's brains of folks who have died and you'll see microplastics and they're everywhere.

02:06:39.760 | Um, and so what is it doing to your health? I don't think we fully know, but we're starting by just

02:06:47.440 | trying to measure this stuff. So we've decided to start with airborne, but you could argue, you know,

02:06:52.640 | what are you drinking? What's in your food? That's all very relevant by the way. Um, but we'll start

02:06:58.080 | with the air. Uh, and, and so what we're doing here, it's not just measuring PM 2.5 and PM 10. It's basically,

02:07:06.240 | um, there's, it's, uh, it's sucking up air. There's a pump in here and underneath the intake valve,

02:07:13.280 | there's a filter that captures all the particulates like pollen, bacteria, fungi, and under that there's

02:07:20.480 | a chemical absorbent. It's called zeolite, captures both hydrophobic, hydrophilic, positive, negative,

02:07:26.240 | and then not in real time, but offline, we'll measure all the biologicals like the fungi, the pollen,

02:07:34.720 | the whatever that's captured on the filter and we'll measure the chemicals using something called mass

02:07:39.520 | spectrometry, the things that have an airport that measures, you know, bombs and things like that.

02:07:44.720 | So we're trying to measure that in real time to see what's going on. And then we try and correlate

02:07:51.920 | what's outside with what's inside, because we'll measure your blood as well with these deep profiles.

02:07:58.160 | And so what we've discovered is, first of all, they're, you know, you'll be getting exposed to we,

02:08:03.600 | we, for me, I'll do one of these during the week, one on the weekend. So it's not, we don't do it

02:08:08.240 | every five minutes kind of thing, because you have to collect enough sample. But we will basically

02:08:13.840 | determine, you know, what kind of exposure you're getting. And, and if you're at high risk for certain

02:08:20.240 | things, you may want to know this, like asthma or allergies, what are you exposed? And there,

02:08:24.720 | I can give you an example. I used to have moderate allergies. Now they're pretty mild, but because

02:08:30.000 | allergies can fluctuate a bit. And they would come every spring, I just assumed it was pollen,

02:08:36.880 | but what is pollen in the end, but I assumed it was pine. But when we did the correlation,

02:08:43.600 | well, it turns out it correlates better with eucalyptus. And then it's like, duh,

02:08:49.280 | I should have realized this, but I don't get them on the northeast where there's no eucalyptus.

02:08:55.600 | And so in the end, it makes a lot of sense. So that one hasn't affected my lifestyle, meaning I still have a big

02:09:03.680 | eucalyptus tree out back that I've not chopped down. Mind you, it's on Stanford land, so I can't do that

02:09:09.280 | anyway. But yeah, at least I know what's going on. But then like on the chemical side, which is very

02:09:18.480 | interesting, we discover there's DEET everywhere, even in my office at Stanford DEET.

02:09:24.400 | The insect repellent, the carcinogenic insect repellent. I used it years ago when I was a camp

02:09:30.000 | counselor. And then one day someone said, someone on the maintenance staff said, take some DEET,

02:09:35.840 | put it into a Ziploc bag and put that Ziploc bag into a glass jar. And I was like, okay. And I did that.

02:09:44.240 | And within a few hours, the plastic bag was completely disintegrated.

02:09:49.120 | Ouch.

02:09:50.320 | And I was slathering that stuff on my skin way back when. And I lived with mosquito bites for

02:09:55.920 | the rest of the summer. I'm like, I'm not putting this stuff on my skin.

02:09:58.160 | Yeah, of course, I had to worry about getting West Nile or something else.

02:10:01.760 | Not in Yosemite. You had to worry about getting Giardia, but that's a different issue from the water.

02:10:07.680 | Interesting. And same with pesticides in most places. And carcinogens, of course, are everywhere.

02:10:16.320 | But their types vary. And the amounts vary a lot. So like when I'm in UC Davis giving talks or something,

02:10:23.280 | I get a pesticide exposure because all the fields are out there. Yeah. And same with when I was in Fresno.

02:10:29.280 | So you can see these correlations. And so that's what we're doing. We'll measure what's where.

02:10:36.800 | And then we'll measure how does that relate to what's going on inside. So we can see what microbes

02:10:42.560 | are outside relating to inflammation markers like cytokines, things like that on the inside.

02:10:48.640 | And same with some of the chemical markers like your glucose levels. And right now that's mostly

02:10:55.520 | been built as models around me. But we're trying to run the study with a lot of people. So we can,

02:11:01.920 | first of all, even break it down further. What's the difference between your kitchen and your

02:11:05.920 | living room and outside your house? And the same thing, how does that relate to some of the levels

02:11:11.680 | of key markers, your metabolites, your inflammatory markers? So we want to correlate that. We know

02:11:19.120 | studies from others have shown pesticides correlate with Parkinson's and things like this. So we want to

02:11:26.400 | see what's going on there. I can tell you some fun stuff that we just made. Again,

02:11:31.600 | these are all correlations. Now we do something called mediation analysis. It can let you get a

02:11:36.800 | little better about causality. Not proof in many cases, but a better idea. Anyway, here's a fun thing

02:11:43.920 | we discovered. We found a correlation between something called pyridine, which used to be common in paints,

02:11:51.360 | it's in other places too. They've recently don't put it in paints, but pyridine exposures

02:11:57.520 | are associated with lack of fungi, meaning I'll have a more bacterial plant or other exposure.

02:12:02.320 | So my house was painted by a green guy, no pyridine in the paints there. So I get a fungal exposure when

02:12:09.440 | I'm at home. And so is that good or bad? I don't know. But imagine I was very allergic to black molds.

02:12:15.760 | So maybe I do want pyridine in my plate. I know a lot of people who struggle with mold.

02:12:21.200 | We can make that association with the allergies, of course. Anyway, you get the idea. We're trying to

02:12:25.520 | correlate what's going on in the outside with the inside. Well, in that case, with other outside

02:12:31.920 | things, but later with the inside. So yeah, we're measuring to make these things. That'll lead to

02:12:37.360 | hypotheses that we could then probably test by either mouse models or in humans who live in

02:12:45.120 | certain places who wind up sort of testing whether they're trying to or not. Imagine you live near,

02:12:50.640 | you know, obviously you live near certain areas, you will see if you live near, you know, mines,

02:12:57.840 | you'll see autoimmune disease, things like that. So we can try and make these associations and then you

02:13:04.080 | correlate with similar people who aren't living near mines to, you know, try to test that.

02:13:10.240 | I love that you're linking outside environment with internal, you know...

02:13:15.040 | Yeah, I feel like it's a totally unexplored area and a pretty important one.

02:13:19.200 | Yeah. Yeah. And I think the fires in LA, among other things, have sensitized people to this

02:13:24.560 | notion of air quality in a real way. It's a shame it took that. But it does seem to be a theme that's

02:13:32.000 | persisting. People are starting to think about like, yeah, how clean or dirty is my air? And I

02:13:36.080 | think the interest and emphasis on microplastics recently is interesting. I did an episode about

02:13:41.520 | microplastics. We had Shauna Swan on the podcast. I mean, I think it's been known for a long time that

02:13:46.160 | these microplastics, BPAs and phthalates, so-called forever chemicals, have been an issue. I think that

02:13:52.240 | people are now just shocked to learn how many of these things we've accumulated and maintained in

02:13:57.920 | our body. And they're all over our body too. Yeah. And the health effects are still unclear.

02:14:02.160 | Right. I mean, it's really unclear. They've been talked about endocrine disruptors and things like

02:14:06.640 | this. Yeah. I mean, I filter my water and I try not to drink out of plastic disposable bottles.

02:14:14.320 | That seems to be an important one. But you know, there was a recent study-

02:14:17.600 | I've only recently switched. I should have done it eons ago.

02:14:20.000 | We should have done it years ago, right? But there's a recent study showing that actually the

02:14:23.520 | glass bottles contain more microplastics than plastic bottles because of what's on the lines,

02:14:28.480 | the underside of the caps. I see.

02:14:30.240 | But what's less discussed around that study is that that was focused on the glass and plastic cap

02:14:37.040 | configuration in Europe. It's different here. So it's like, it really needs to be explored. I think

02:14:43.280 | simple ways to measure one's own environment using sensors like the one that you have here for the air,

02:14:48.800 | as well as for water, it's gonna be really, really important. Yeah.

02:14:52.880 | So I'm grateful that you're commercializing so many of these things. I can tell you are a data guy,

02:14:57.680 | but the fact that you translate things into real world tools is so valuable. Speaking of which,

02:15:03.280 | I'm gonna be very direct about this. Two Stanford faculty talking about measuring lots of biomarkers

02:15:11.280 | from a single drop of blood, screams of Theranos. Let's just call it what it is and not dance around it.

02:15:16.400 | Which was a spectacular failure that involved, apparently, at least the courts decided,

02:15:25.200 | there was a lot of corruption and lying and stuff there. However, that was some years ago,

02:15:30.560 | and you were not involved with that. And so the technology has now evolved to the point where

02:15:35.760 | my understanding is that you are able to measure lots of biomarkers from a single drop of blood.

02:15:41.920 | Right. Thousands.

02:15:43.840 | So that's exciting because no one likes to get their blood drawn. I guess if there might be a subset of

02:15:50.400 | people. But so tell us about that. What is that pursuit called? What are you measuring? Why are you

02:15:58.240 | measuring it? And maybe underscore the real value of like single drop of blood analysis.

02:16:03.520 | First of all, we don't get measured very often when we're healthy. This idea that we mostly practice

02:16:09.120 | sick care, not health care. And why do you go to physician all the time when you're healthy to get

02:16:14.400 | measured? I think that's a barrier to getting measured. So can we come up with more, you know,

02:16:20.640 | facile ways of measuring people? The wearables are obviously one and they're perfect because they're,

02:16:26.720 | you know, passive monitoring and continuous. So you're really collecting a lot of data just in

02:16:31.600 | the background. I mean, the inconvenience is wearing and charging these things. But we don't measure

02:16:38.640 | what's on the inside. And I think that still has value. And the idea about trying to set up home

02:16:44.480 | tests for this sort of thing, I think is powerful. So that was the motivation. That was the motivation for

02:16:50.480 | Theranos, I think, too. And our, you know, shtick, if you will, was to try and do this. But we're not

02:16:59.440 | trying to measure the exact clinical values because some of that is hard. How do you measure LDL droplets

02:17:06.720 | in micro samples? It's probably doable, but it's a lot trickier. We were just trying to, it fits with our

02:17:13.120 | idea of doing deep data profiles on little drops of blood. And the key is to find a format that would

02:17:19.200 | keep the analytes, as we call them, the molecules stable. And so we test them. We spent seven years

02:17:26.400 | actually trying different things, finding formats. The old format was to use paper, actually, cellulose

02:17:32.720 | to collect the stuff. And that doesn't work very well. The analytes oxidize. It's a mess. And so ultimately,

02:17:39.600 | we test a lot of things out there. We were trying to invent a few of our own. And the net result was we

02:17:45.040 | we did settle on some that were out there, tested them. They're being used in a more limited fashion.

02:17:50.000 | And then we showed you could actually do the kinds of things we do. The metabolomics is called lipidomics.

02:17:55.200 | And proteomics. And again, with certain configurations, the proteins turn, most of them are quite stable. Not 100%,

02:18:04.240 | but most are. We can measure all this. Metabolites, same thing. Most are lipids. Some are, some aren't.

02:18:10.880 | So we figured out which ones are, which ones aren't. And then we basically did just that. We showed you

02:18:17.440 | could do this, did fun experiments. Like in my case, we took a sample every hour for seven straight days

02:18:24.080 | to try and correlate. Around the clock? Well, at night when I was sleeping, no. But although when I

02:18:30.960 | did wake up, I would take a sample sometimes, yeah. Well, it's just a drop. Yeah, not so great for sleep

02:18:37.120 | disruption, I suppose. But anyway, and the idea there was a correlate, you know, what's going on

02:18:43.440 | with, and I was wearing a CGM and a smartwatch. I could follow activity, doing food logging, all that sort

02:18:49.760 | of stuff. And in the end, we're trying to correlate basically people's activities,

02:18:56.000 | people's biochemistry and physiology with their activities and heart rate and things like that.

02:19:02.880 | And so we found literally thousands of correlations. That's pretty cool. A lot of which is known, right?

02:19:08.400 | After your insulin goes up after your glucose. But we can precisely measure. For me, it's 10 minutes.

02:19:16.160 | We know exactly the magnitude with certain kinds of food and that sort of thing.

02:19:20.320 | We also discovered, I don't know if this will go anywhere, but we're pursuing it. Alpha-synuclein,

02:19:26.400 | which is involved in Parkinson's and dementia, actually showed an interesting pattern. It seemed to fluctuate

02:19:32.720 | with stress, actually. Goes up with stress?

02:19:36.480 | Yeah, well, that's what we're trying to figure out, what kinds of stress. So I don't think we have that

02:19:41.360 | sorted out yet. So anyway, I'll leave it at that because we don't have it all sorted. So that's the

02:19:48.720 | thing. We're trying to measure that, see exactly what it correlates with. And then maybe that's a useful

02:19:55.680 | assay for trying to manage that and therefore push off dementia. That's the hypothesis. No guarantee that's

02:20:02.720 | right. But these are the kinds of observations we make that I'd like to see if they turn into real

02:20:09.840 | world value that we could then help, you know, maybe get out there to help people in some fashion.

02:20:16.400 | Very cool.

02:20:16.880 | So this is the kind of stuff we do it. These are what you're calling observational trials,

02:20:22.640 | take deep data measurements on people to better see what's going on, make hypotheses, and then,

02:20:29.600 | yeah, ideally roll it out into the real world. I love it. Well, let's go further into what most

02:20:36.880 | people consider kind of esoteric, at least in this half of the world, but it's not really

02:20:42.400 | esoteric at all, has tremendous precedent, which is acupuncture. I think for people who know,

02:20:49.920 | acupuncture makes perfect sense as something that would be a valuable tool, right? Thousands of years

02:20:56.160 | of data and practice, less known about mechanism, but Chufu Ma's lab at Harvard in recent years has been

02:21:04.000 | studying how different needle configurations impact different organs that's in mouse models, but, you know,

02:21:09.680 | different inflammatory molecules or anti-inflammatory molecules. So there's some mechanistic data

02:21:14.000 | starting to come out. You have an interesting story about acupuncture and perhaps what it can

02:21:20.560 | offer or not offer in terms of health support.

02:21:24.400 | I'm down on sabbatical at UC Irvine with Shasta Malik, who runs an integrative health institute where

02:21:31.200 | they bring in nutrition, exercise, and things like acupuncture into trying to better manage people's

02:21:37.200 | health and lives. And it's been very fascinating for me because they're doing it on the clinical side.

02:21:43.600 | I'm kind of a big data measurement guy and

02:21:46.960 | and so I want to see what's going on and if there's ways that make sense to collaborate. And as you point out,

02:21:52.240 | acupuncture has been around for 3,000 years or some incredible number. There must be something to it,

02:21:58.480 | right? People use it a lot for pain and apparently for fertility and other things as well.

02:22:03.680 | Yeah, it's shown to be effective in a number of domains and I've had quote-unquote standard MDs,

02:22:08.640 | including our director of pain medicine, Sean Mackey on this podcast, who's like, yep,

02:22:12.160 | there is evidence acupuncture can work.

02:22:13.920 | And there are plenty of people swear by it and she uses it for blood pressure, okay, for blood pressure

02:22:21.200 | management. So I run a little high on the blood pressure. Not, nobody's overly panicked,

02:22:28.080 | but you know, I tend to be in the high 130s, but I guess because it's getting a very large grain out,

02:22:35.360 | I was in the low 140s. And so I measured myself right before acupuncture, you know,

02:22:41.280 | very specific time of day with my monitor at home. And yeah, I was running 140 over the low 80s,

02:22:48.800 | something like 82, 83, did, you know, five measurements. So did the acupuncture, which is

02:22:54.720 | designed for blood pressure and diabetes. And maybe I can go off the GLPs if all this works. But

02:23:00.640 | anyway, the next day I measured at the exact same time and son of a gun, it was 25 points lower as the

02:23:06.720 | high teens, like 118. It was unbelievable. I can show you the data. And the other one went to like 72,

02:23:14.480 | right? Some, the diastolic. So I just, with one treatment, that was electroactive puncture,

02:23:21.680 | I should say. So they zap you. And they, yeah, had 30 some points and, and they've added a few more

02:23:28.320 | since. So you do it every week for eight weeks. So I've now done four of these things. And I can tell

02:23:34.240 | you that my blood pressure stayed low. It's running in this one high one teens, maybe 120,

02:23:42.080 | which is pretty good, roughly where you want to be. And the other is always around maybe 74. So it's

02:23:48.880 | like, it was never running like that before. I can show you my data. It's great. It's pretty incredible.

02:23:54.160 | So it does seem to be working now. How long does it last? I'm only halfway through my treatments.

02:23:58.960 | I don't know, but I will track all this stuff. Right. So I'm a responder, no question to this treatment.

02:24:06.640 | I love hearing it. I haven't done acupuncture in years. So it's, and I've done it. Yeah. Years ago,

02:24:11.120 | when I was a postdoc, a stressful time in my life, and then a junior professor, also a stressful time

02:24:16.240 | in my life, you know, a lot of uncertainty, right? And grants and things of that sort.

02:24:19.520 | My sister suggested I go see a acupuncturist and I got a lot out of it in terms of stress reduction.

02:24:28.000 | We'll put a link to it in the show note captions, but I'll also send you these papers from Chufu Ma's

02:24:32.720 | lab that I mentioned a few months ago. Yeah. First of all, not that this means everything, but published as

02:24:37.840 | articles and letters in nature, which has a very high bar for, you know, most papers get rejected,

02:24:45.040 | obviously, as you know. And what they found is interesting that the combination of needle placements

02:24:51.120 | turns out to be vitally important. So in this one paper that Chufu has, he shows that, for instance, if the

02:24:56.720 | if the needles are inserted into like the equivalent of like the palm area and the foot area and some

02:25:03.680 | flank area, you get an increase in inflammatory cytokines. Whereas if you change that combination,

02:25:09.280 | you get a decrease in inflammatory cytokines. But what's really beautiful about these papers is he maps

02:25:13.680 | it to specific output from the spleen, regulated by the vagus nerve, regulated by the these receptors

02:25:22.720 | at the level of the skin. So mechanistically, it all makes sense. It's just that these thousands of years

02:25:27.440 | of charts and data that have been collected in humans, you know, clinical practice has never been

02:25:34.080 | parsed mechanistically. Right. So I'm 100% a believer that there's a mechanistic basis that it's not just

02:25:39.360 | all placebo. Some of it might be placebo, much like some of the GLP appetite suppression might be placebo,

02:25:46.240 | but a lot of it probably isn't. So in any case, I'm a fan of the rigorous exploration of things that

02:25:54.560 | have been thought to work for many, many years. And it's always gratifying when you see, oh, like,

02:25:58.480 | here's a mechanism. Yeah, it really does work. I mean, I go into the stuff completely open. It may not work.

02:26:04.960 | And I don't know, I didn't even, and she said, oh, because first of all, she said, well, just try

02:26:09.680 | acupuncture. I wasn't even sure what kind she was going to try. So in the end, she said, oh, yeah,

02:26:14.240 | we'll do blood pressure and diabetes. Now they've added on some stress points as well. And I don't

02:26:20.400 | consider myself probably in a high stress job, but I don't consider myself a very stressful person.

02:26:25.440 | You don't seem stressed. Yeah, I think I generally handle all right. But anyway, they're putting all these

02:26:31.360 | things on me. And I didn't know what I was going to have 24 hours later, is it going to work? I don't

02:26:36.480 | know. But the data, I mean, that was a pretty big jump, right? Speaking of fun and things that are,

02:26:43.360 | at least on the face of them, kind of out there, I have one final question, which is,

02:26:49.120 | my understanding is a few years ago, your laboratory was involved in looking at big data sets,

02:26:56.480 | genomics, proteomics, etc., from people who had attended a Tony Robbins event. I don't know what

02:27:03.520 | the control condition was. And I only know this because I believe it was a postdoc or a student

02:27:08.880 | in your lab had reached out about some protocols that we had going in my lab in collaboration with

02:27:14.480 | the psychiatry department. Could you describe the contour of this study? And I realize it's not published

02:27:21.520 | yet, but if there were any preliminary findings that you could share with us, I think that would

02:27:25.680 | be interesting. I'm interested generally in immersive events and psychological health. And

02:27:32.160 | there are interesting data comparing attendance of these events, which by the way, I have no financial

02:27:37.920 | relationship to, never met Tony in person or anything like that, with prescription antidepressant

02:27:42.800 | treatments. And they actually measure up pretty well in terms of, I forget how long-term the study was.

02:27:47.760 | So I'm generally an open person when it comes to ideas. What was the study and what did you find?

02:27:52.960 | Maybe to put it in context, so this all started when a postdoc joined my lab, was very interested

02:27:58.160 | in mental health and knowing that we're good at measurements and the idea. And I thought about a lot

02:28:04.080 | and I realized that we don't measure mental health very well, right? Surveys are still the gold standards

02:28:10.160 | for most things. And so how do you know if you're getting better? You do more surveys? That whole

02:28:15.120 | concept is very unsatisfying to me. So we thought with the wearables, right? There's got to be a lot of

02:28:22.080 | physiology around this thing. This biochemistry, we do a lot of micro sampling, mentioned earlier,

02:28:28.480 | where you can now profile deeply. So we thought we could bring this kind of stuff maybe. And we're still,

02:28:33.680 | it's a growing area in the lab. I'm very interested in this because I feel like there's a lot going on

02:28:39.520 | in the mental health space. It's just unexplored. And the biggest problem is we just don't have good

02:28:44.320 | biomarkers. And for the meetings I've been at for this stuff, that keeps popping up number one. We don't

02:28:50.000 | have good biomarkers. So we think the digital, meaning from the wearables, the micro sampling could ultimately

02:28:58.960 | prove to give us good biomarkers. We're already seeing some evidence of that now. So we ran several

02:29:04.160 | studies. We did one with Byron Katie, who runs one of these immersive programs. And I don't know any

02:29:10.560 | about this stuff. And so I basically said, all right, we're going to do this. Let's bring in first. We

02:29:15.600 | brought a colleague, George Slavich, who you may or may not know. He's basically an average childhood,

02:29:21.840 | but knows a lot more than I do about the childhood. And I met him. He's a very, very bright guy.

02:29:26.560 | So he, you know, we came up with some surveys because we have to compare up against something.

02:29:31.920 | We put smartwatches. The one on Byron Katie didn't quite work out, but we did do blood sampling and

02:29:37.280 | stuff for her and even microbiome for people before and after. And that case, it went out for a way.

02:29:43.600 | And then we, so we ran that study. And then shortly thereafter, we ran a pilot one with Tony Robbins,

02:29:50.800 | where we had a smallish number of people who did the Tony Robbins, and we profiled them, you know,

02:29:57.920 | before, right before, immediately after. And then at that point, I think that study was done out for

02:30:06.560 | several months. And then I'll tell you about the larger one in a minute. And so we had them do these

02:30:13.840 | surveys and things. And, and I went in, I have no idea if this stuff works or not. And son of a gun,

02:30:20.240 | these people really did improve by these questionnaires, by the standards in the field.

02:30:25.520 | Uh, basically they improve their markers, their mental health, their mental health. Yeah. By the

02:30:31.520 | surveys. So that first, and that was true for the Byron Katie one, it was true for the Tony Robbins one.

02:30:38.160 | And the Byron Katie one, we now have some of the omics data back in there. They do seem to improve

02:30:42.960 | in their inflammatory markers as well. Wow. So we have some data there that's not yet published.

02:30:47.920 | Her stuff for people that aren't familiar, and I'm, I'm, this is a very top contour thing, is a lot of

02:30:53.280 | reframing, um, as I understand through language, testing assumptions, counter, you know, uh, challenging

02:31:00.480 | internal beliefs, external beliefs. Uh, I, I'm, I'm, again, I'm just scratching the surface and I'm

02:31:05.200 | probably getting some of it wrong, but just for those that don't know who Byron Katie is, whereas

02:31:08.800 | Tony Robbins, I think more people are familiar with, those are very immersive events. There's a lot of

02:31:13.280 | high energy activity, also some breath work stuff done. Um, some, uh, it's supposed to be very intense.

02:31:20.880 | I've never done it myself. Almost like, um, hip self-hypnosis type stuff where people direct themselves

02:31:25.680 | down, uh, a memory that's very painful memory. That's very positive. A lot of somatic, um, stuff. I mean,

02:31:32.960 | you know, there's a wide palette there, but anyway, hopefully that gives a little more context for

02:31:37.440 | people. So anyway, we did see a positive result, uh, on the pilot study and that was 20, I don't know,

02:31:43.360 | 27 people. I may have the number wrong, but it's a small number. Uh, and then we now have done a, um,

02:31:49.840 | a follow-up and, um, well, I should say actually for, uh, the first one that actually went out even further

02:31:58.240 | now. They have some additional data points, but in the follow-up with there, we did a much bigger

02:32:02.720 | one at 600, almost 700 people who went through Tony Robbins. And then we had another set of people

02:32:08.560 | who didn't do Tony Robbins, who we also profiled. And same thing. They see they wore smart watches.

02:32:15.200 | We had to scramble to get the IRB approval. It's always a rate limiting step. Uh, so we didn't get as

02:32:20.400 | many wearables on folks as head of time, but we do do the micro sampling. We did do all the surveys and we

02:32:25.200 | have a battery of wellness surveys. It wouldn't be official depression scores and things, but they're

02:32:30.960 | things about, you know, are you depressed and anxiety and burnout and all kinds of stuff.

02:32:36.720 | So we, we, it's a series of questionnaires. They, they did it before, they did immediately after one

02:32:41.840 | month, three months, six months, one year. And it's a pretty sizable study now. Like I say, it's almost 700

02:32:47.600 | people who did it, 700 people who were controls, but I will say the caveat is they're not randomly

02:32:54.800 | assigned because there are people who did it, did it, signed up for it. And the people who didn't do it,

02:33:00.000 | well, they did it separate. So, um, that's the only caveat that I see, but the bottom line is the ones who

02:33:06.480 | did do it. Once again, they improved in all, like virtually all these things, anxiety, depression,

02:33:13.120 | significantly. Yeah. Uh, and we have just put together paper on the psychological part now.

02:33:20.000 | Uh, and then on the, we're still doing the omic stuff. So we actually did the micro sampling. I

02:33:26.560 | mentioned earlier where they gave samples before for not everybody, not everybody signed up for that,

02:33:31.680 | but it's like 130, 140 people who did the micro sampling before the, you know, immediately after

02:33:38.960 | each of those same time points. And so we will see that data is still coming in, uh, and hopefully we'll

02:33:46.640 | know in a few months. But, uh, at least on the survey stuff, these people did all improve and that control

02:33:54.240 | group, which was separate, did not. And it is significant. So I'm sure we'll put the paper up on

02:34:00.240 | either bio archive, which is this preprint thing, uh, or can even send your copy. I'll, uh, see if my,

02:34:08.000 | uh, person who's been running that's up for that. So anyway, um, yeah, it does work. It's pretty amazing

02:34:14.720 | actually. So again, people, a lot, not everybody's in the so-called depressed state or whatever. It's kind

02:34:21.600 | of worked out half and half, uh, and their values all improved, not again, not a hundred percent, but

02:34:28.240 | pretty darn, most of them that sort of surprised me. And we didn't obviously in the control group,

02:34:37.440 | we didn't see anything. So it looks pretty good. Wow. Well, I love how you are willing to explore these

02:34:45.200 | sorts of things. Um, people are asking, Mike, what the hell are you doing here? And I said, I don't know.

02:34:50.960 | I'll just let, but let's take it like thousands of people do this stuff. Shouldn't somebody look at

02:34:56.160 | this? I think the answer is yes. I know people, um, who I would characterize as highly motivated

02:35:04.400 | generally toward their health and, um, careers, et cetera, uh, relationships, um, who had, uh, pain

02:35:11.680 | points of struggle in one or several domains of life, or just were in a kind of a, like, you know, aimless

02:35:20.000 | part of life or struggling with something, uh, uh, who went and did these, uh, one of these immersive

02:35:25.520 | seminars and, and reported, and it does seem from the outside as well to be positively transformed.

02:35:32.400 | Right. They continue to do the work on their own. Um, that's correct. You know, they continue to do

02:35:38.880 | practices that, that they learned there on their own. Right. Seems to be an important component. But,

02:35:44.400 | you know, I think, um, what's exciting about these, these kinds of experiments and conversations to me

02:35:50.240 | is that whereas five years ago, certainly 10 years ago, any discussion about, let's just think about some

02:35:56.400 | of the themes that we've touched on. Right. Um, breath work, long exhales, slow your heart rate.

02:36:02.800 | We know that. So the respiratory sinus arrhythmia increases HRV. We know that. Right. Um, I asked you

02:36:08.880 | about meditation. You don't meditate, but, uh, but exercise. Well, I used to. Yeah. And I'd like to get

02:36:14.000 | back to it. And certainly there are data to support it. Absolutely. Yeah. Resistance training. You know,

02:36:19.040 | when I was, I'm about to turn 50, as I mentioned, when I was in high school, the only people who did

02:36:23.280 | weightlifting were bodybuilders, people going off to the military or preseason football players.

02:36:28.000 | They told us it would turn to fat if we stopped and we shouldn't weight train. Right.

02:36:31.840 | We know that's completely false. Everyone should weight train. Women should weight train. Men should

02:36:35.920 | weight train. Especially as you get old. Right. Yeah. Um, Byron Katie, Tony Robbins have entered the

02:36:42.240 | conversation. Um, uh, their work that is acupuncture. You're parsing diabetes into

02:36:51.920 | these subcategories or phenotypes. We're now, we're no longer talking about talking about fiber as a

02:36:56.720 | single thing. You've now divided that into separable, actionable, uh, paths for, you know, addressing

02:37:04.160 | one's health, improving one's health. And so, you know, this really just brings me to what I've,

02:37:08.640 | you know, been thinking more and more as I've read your work and, and certainly after today's conversation,

02:37:13.600 | which is that I'm so grateful that somebody like you who is into big data, you like numbers,

02:37:21.120 | you like statistics, you like, um, proteomics, genomics, RNA-seq, you know, I mean, this is serious

02:37:27.280 | science that you're willing to look at what's out there, what people are doing, what they're willing

02:37:32.000 | to do and ask, what are the things to avoid? What are the things to do more of? And really

02:37:36.880 | customizing it for people's needs. Um, I think it's truly important slash heroic work because it really

02:37:44.000 | would take somebody in your position, uh, you know, at least until very recently, you were chair of the

02:37:48.720 | department of genetics, but you're professor of genetics, trained at Caltech and all these places

02:37:52.640 | to really embrace, you know, the, these different, uh, directions in health with serious mechanistic

02:38:00.400 | reductionist approaches, but then be able to step back and say, here's what I do. Here's what people

02:38:05.280 | are doing. Here's what seems to help. Here's what we don't know. And, uh, there seems to be basically

02:38:10.880 | no limit to what, um, you're willing to explore using these highly rigorous tools. So I just want to

02:38:15.600 | really extend my gratitude. And I know the gratitude that people who listen to this and watch this are

02:38:21.760 | surely feeling because things have been very siloed up until recently. And you're one of the people I

02:38:28.000 | really see as, as putting, um, sand and hopefully concrete between those silos, because this notion

02:38:33.440 | of health and health practices is really just one thing. And we, we need to be less siloed. So thank you

02:38:38.960 | for doing that. Oh, sure. I think you bring up a good point. I think we're trained to be siloed. That's

02:38:45.200 | part of the problem as you go through graduate school and things like that, even medicine, right? You have people

02:38:50.880 | trained in very specific areas, so they never look at the whole. Yet we know, again, that we are

02:38:56.560 | homeostatic systems that involves all these different things. And you'll never solve it. Like, I like to say

02:39:03.440 | when I got, um, because everybody on my father's side has died of heart problems and I used to have high

02:39:09.520 | cholesterol until I went on satins. I'm on PCSK9 inhibitors and they're amazing. Uh, and you know, um,

02:39:17.600 | my heart guy would tell me, well, you need to raise your sense. He didn't think it was low enough. He

02:39:22.320 | said, well, when I do that, my glucose goes up and that's very textbook by the way. Uh, and I, and I

02:39:28.560 | finally called him. I said, look, your job has stopped me from getting a heart attack, but you don't care if

02:39:32.640 | I have all these other complications. Right. And I would say the same to the diabetes people. I'd say, well,

02:39:38.720 | you know, you're trying to control my glucose, but you do some of these other things. And I just

02:39:43.280 | don't think that's the right way you want to look at people. We need to bring in all the data,

02:39:47.440 | all these things we've touched on these points about genetics and epigenetics and lifestyle.

02:39:53.040 | And I think the whole, you know, communication side, the whole socialization, very understudied.

02:39:59.440 | I also like it from the academic side, because when you go in these areas where you don't know anything,

02:40:03.760 | you're, even when you stumble around, you're going to learn something. So that's kind of how I view

02:40:07.920 | our work in mental health and now socialization, I hope. Uh, so I just hope that we can learn some

02:40:14.560 | kind of cool stuff that will be useful. And then I think now we're in an amazing position, right?

02:40:20.480 | Where we, the tools with AI, because no one person can do this, right? You don't want a doctor who

02:40:25.120 | doesn't use AI now that you want someone who can pull in all that information. And this is what the

02:40:30.960 | companies are really good at. Again, it's one reason we spin these things off. Like January has this,

02:40:36.400 | they call it mirror that builds kind of like, it'll take all your data, your genomics data, all your

02:40:42.080 | reports, all these various things and runs an AI engine, obviously trained in a certain fashion and

02:40:48.720 | gives you back a incredibly long report. But although you do get a summary so you can decipher it. And then

02:40:55.520 | it pulls all the stuff together to make insights. And so for example, I didn't realize I knew my CD8 T

02:41:01.520 | cells. Again, this gets a little specialized, but they were low, uh, which I did see on the report,

02:41:08.480 | but it has this whole zinc recommendation thing. I don't know if that's right, but I'm going to look

02:41:12.720 | into it more. It can make suggestions that no doctor is going to figure out with all the stuff. So you do need

02:41:18.800 | these new systems. And that is the future. We're all going to have our own personalized systems pulling data.

02:41:25.120 | I mentioned earlier about Iolo, same thing about your metabolic profile, pulling other information

02:41:30.720 | to give you recommendations. That's going to be true. Again, those are specific examples for me,

02:41:35.200 | but I think that's your, every one of your doctors of the future is going to have to do this stuff.

02:41:40.960 | Otherwise you're not going to get full value out of all these measurements, which we should be doing

02:41:45.360 | that will better improve our health. I love it. It's a, it's a beautiful vision. And I can see a day

02:41:50.720 | not too far from now where if somebody has a whole body skin data set, uh, some blood tests, maybe they

02:41:56.880 | have some tracking data, they just upload it to a website and their physician runs it through AI and

02:42:02.400 | makes of it what they can. Um, it certainly won't be everything that's possible, but that's certainly

02:42:07.520 | better than not taking those data into account. And of course, physicians can also still choose

02:42:11.760 | to ignore it all. Most of them do now by being totally unaware that it exists or saying, oh yeah,

02:42:18.000 | you said your heart rate variability was reduced for a week, but what does that mean to me? It could

02:42:21.840 | be any number of things, right? But now that they can start to make sense of it if they choose to,

02:42:26.400 | I think, um, it's important, uh, important because after all people can't forget the physicians work

02:42:32.560 | for you, not the other way around. So. 100% agree. Yeah. Well, thanks so much for the work that you're

02:42:38.880 | doing. Uh, I've been told, and I strongly believe that in the world of science, there are map makers and

02:42:44.720 | there are explorers and the explorers are the ones that really, uh, make the discoveries that matter and

02:42:51.200 | you're clearly an explorer. And I'm grateful for the work you're doing. I'm also grateful that you took the time

02:42:57.520 | to come talk to us today. So I'd love to get updates in the, in the not too distant future.

02:43:01.680 | Meanwhile, I'll see you back at the farm. Thanks so much for having me here. It's been a blast.

02:43:06.240 | Thank you for joining me for today's discussion with Dr. Michael Snyder to learn more about his

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Transform Your Metabolic Health & Longevity by Knowing Your Unique Biology | Dr. Michael Snyder

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