The Peter Attia Drive - Zone 2 training： impact on longevity and mitochondrial function, how to dose frequency and duration, and more ｜ Iñigo San-Millán, Ph.D. (#201 rebroadcast)

00:00:00.000 Hey, everyone. Welcome to the Drive podcast. I'm your host, Peter Atiyah. This podcast,

00:00:16.540 my website, and my weekly newsletter all focus on the goal of translating the science of longevity

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00:00:53.200 of the subscription. If you want to learn more about the benefits of our premium membership,

00:00:58.020 head over to peteratiyahmd.com forward slash subscribe. Welcome to a special episode of

00:01:06.240 The Drive. For this week's episode, we want to rebroadcast one of our most popular episodes,

00:01:11.080 which is the second conversation I had with Inigo San Milan in March of 2022, which was a deep dive

00:01:17.720 into all things pertaining to zone two exercise. Inigo is an internationally renowned applied

00:01:23.560 physiologist and assistant professor at the University of Colorado School of Medicine. His

00:01:28.500 research focuses on exercise-related metabolism, metabolic health, diabetes, and cancer. In this

00:01:34.600 conversation, we talk about Inigo's work with two-time Tour de France champion Tadi Pogacar,

00:01:40.760 looking at the type of training that he does and what we can learn about training and

00:01:46.980 cardiovascular physiology from the world's most elite performers. We talk about lactate and fat

00:01:52.040 oxidation as it relates to cardiorespiratory training and how carbohydrates in our food can

00:01:57.240 affect lactate. And we talk about what different lactate levels mean in the context of healthy

00:02:02.280 versus unhealthy people. We get into very specific detail around zone two exercise, how to measure it,

00:02:08.940 how to know you're in zone two, what to do if you don't want to use a lactate meter, how you can

00:02:14.640 structure your training around it, how to think about duration, timing, and frequency. Talk about

00:02:19.660 the importance and the compounding rate of improvement that can happen with zone two training,

00:02:24.380 VO two max training, high intensity training, and how different exercises of this nature can improve

00:02:29.800 your lifespan and healthspan. This is a rather tour de force episode when it comes to zone two training.

00:02:36.060 And obviously it's a term that many of you are very familiar with, but it's really great to go back

00:02:40.380 to the source where we started talking about this with Inigo several years ago and then follow it

00:02:46.000 up again in 2022. So without further delay, please enjoy or potentially re-enjoy my conversation with

00:02:51.580 Inigo.

00:02:52.120 Inigo, it is so great to be sitting down with you again. Last time, of course, we did this in person,

00:03:02.700 but these days I've become too lazy to travel around and do podcasts in person. So do it by video.

00:03:07.840 But that said, I really hope you can get out here to Austin so we can train together and do some cool

00:03:12.500 ex-fiz. And also I need to get out there to sort of do some of the ex-fiz stuff we've talked about,

00:03:17.980 but I almost don't know where to begin because there's so much stuff we talked about last time

00:03:22.720 that we want to double click on this time. There's so much that has changed in the interval from when

00:03:27.480 we spoke, gosh, probably two years ago, a little over two years ago. I thought one place we could pick

00:03:33.380 it up. Something we didn't really talk about last time was your work with Taddy Pogacar,

00:03:38.920 because of course, I don't think anybody knew who he was two and a half years ago. And of course,

00:03:43.240 now he is, I don't know. I mean, I think it's safe to say he has the potential to potentially go down

00:03:48.620 as the greatest Tour de France cyclist of all time, given how young he is, not to put that expectation

00:03:53.520 out there, but to win the tour at such a young age, to not just win the yellow jersey, but the white

00:03:59.020 jersey, polka dot jersey repeatedly, he looks like something of a different species almost.

00:04:06.700 And I say that not in the way that people typically say those things of cyclists in a

00:04:10.440 way that's suspicious of anything. So for the listeners who are not familiar with the Tour de

00:04:15.000 France, not familiar with your work with the UAE team and your work with Taddy Pogacar, maybe give

00:04:22.200 folks a little bit of an update as to what you've been doing in professional cycling over the past couple

00:04:26.400 of years. First of all, thank you very much for having me here. It's an honor, really excited for

00:04:30.960 this, and I appreciate the opportunity. I had a lot of fun last time, hope to have fun again.

00:04:37.260 My work with Taddy started in late 2018, when he signed up for the team. Yeah, I was introduced

00:04:45.100 to him by our CEO, Janetti, and our general manager, Machin, told me, hey, start working with this guy.

00:04:52.640 And he was what at the time, 19 maybe? Yeah, 19. He was 19 at the time,

00:04:58.340 just at turn 19. In fact, I started to work with him right away. I realized he had potential. And I

00:05:04.780 think like a couple of months earlier, no, or later, I forgot when we had that podcast,

00:05:10.360 I already told you about him. I told you like, we have a guy that has good potential. That was Taddy.

00:05:16.320 To put it in perspective, I mean, has good potential is one thing. To then go and do what

00:05:22.160 he did would make that statement the understatement of the century for folks who maybe don't follow

00:05:28.780 cycling as closely, right? Yeah. Yeah. I mean, I try to be cautious. I don't usually say that a lot

00:05:35.180 of people who have a good potential. We talked about it over dinner that night.

00:05:39.660 Yeah. Yeah. When I say someone has good potential, I don't usually say that lightly of anybody.

00:05:45.200 What did you see in him in 2018, 2019, that led you to believe that even amongst that class,

00:05:56.360 because professional cyclists from a physiologic standpoint are all very special individuals.

00:06:00.960 What did you see in him that made you think he has potential in your understated way?

00:06:06.680 The physiological testing we started doing right off the bat. I saw like amazing capabilities,

00:06:12.800 ability to clear lactate and to put out great amount of power for long periods of time.

00:06:19.420 So when you say that, was it specifically his FTP that impressed you or was it his,

00:06:26.820 as you said, lactate clearance, was it shorter bursts of power that were higher than FTP,

00:06:32.420 but the speed with which he could do or the successive repeats that he could do? I mean,

00:06:36.660 tell me some of the testing you were putting cyclists through and how he stood out.

00:06:41.280 It's kind of like similar tests that I did to you. And this is where I saw that at a given

00:06:46.480 power output, his lactate levels, blood lactate levels were extremely low. And since I've been

00:06:52.320 doing this specific protocol for 20 years with professional athletes, professional cyclists in

00:06:58.620 this specific case, that's where I have my cheat sheet, where I know I can categorize where people are.

00:07:04.640 He was like, whoa, wait on the other side, way above almost everybody that I had tested or around

00:07:10.900 the same category. And for that age, that's what I saw like, whoa, first of all, he is at a different

00:07:17.060 category and he's first year pro, pretty much a junior. And then that's where like I could see he

00:07:23.880 could sustain a high amount of power with very low lactate compared to the rest. And then throughout

00:07:29.600 the trainings, we use TrainingPeaks, the software, looking at TrainingPeaks,

00:07:33.820 that's where I would see his different abilities to sustain a given power output for the whole day

00:07:40.200 or for a specific effort, a glycolytic effort and a climb. You would see the power output that he would

00:07:46.400 be putting out. And so altogether, then I saw his trainability, how easy he would get the concepts,

00:07:54.020 how easy he would be comfortable with the training, how easy he would recover. I like the feedback.

00:08:00.040 I talk to him once, twice a day over WhatsApp to, you know, how the feedback. I know very well when

00:08:06.420 a hard week is or what a hard week is. And when you see this kid telling you, pretty good, I'm

00:08:13.700 recovering very well. When other ones are telling you, woof, I had to take it a little bit easier

00:08:18.280 today because I couldn't do this effort. And we're talking about high level pros. And you see this

00:08:22.640 kid telling you like, yeah, there's no problem. That's where you start putting together things.

00:08:26.620 And also around the same time with my two colleagues at the university, Angelo D'Alessandro

00:08:31.920 and Travis Nenkov, we started to develop in a platform for metabolomics where we can look at

00:08:36.620 hundreds, if not thousands of metabolites in the human body. And we did it at the Tour of California

00:08:41.880 in 2019, which was like around April. That's where he won it. And that's where we analyzed all his

00:08:48.880 metabolites. And we did already at the training camp in January 2019. And we already saw, wow,

00:08:55.380 this guy has different metabolites at the glycolytic level, oxidative level, recovery level. And we

00:09:02.840 confirmed that at the Tour of California. And this is where putting all together, yeah, this guy is

00:09:08.400 different. So going back to what you said about lactate, I assume that one of the data points that

00:09:14.220 is most telling of a cyclist is if you plot on the X-axis, watts per kilo, and on the Y-axis,

00:09:22.180 this lactate production. I mean, that might be one of the most telling graphs you could generate

00:09:27.740 to predict success in the Tour, correct? Absolutely. You see a normal tempo climbing

00:09:34.660 in the Tour de France. Tempo A, that is the whole peloton going up.

00:09:38.620 It's got to be four. Yeah, about five watts.

00:09:40.500 I was about to say, wow, yeah, I was going to say four and a half. Okay, so wow, the whole peloton

00:09:43.900 is going up at five watts per kilo. Yeah, something like that. And that's where you see like

00:09:49.200 someone at that intensity might have already six millimoles. So you can tell it's going to be

00:09:54.560 very tasking and others might have one, resting levels. It really, really predicts performance.

00:10:01.920 In fact, when we go to these training camps, I'm going to go next week for the first training camp

00:10:06.780 of the year with the team. We do this physiological testing and I do this protocol and I get this data.

00:10:13.740 So right away, I tell the team managers, this guy is way above the rest. These three guys are

00:10:19.800 really, really good immediately behind it. These two guys are in the third level. And then we have

00:10:25.680 all these guys that they're like really, really bad form. And it pretty much works. Then we do

00:10:31.380 different racing simulation and the telebook right away. This is how it is. So this is why it's very

00:10:36.920 predictive. And the same thing too, moving into the season, you see, okay, all these three guys are

00:10:42.300 going to be at a very good level when we start the season. This guy, we thought that he was going to

00:10:46.840 be a very good level. He's not there at all. When the season starts, you see that it reflects very

00:10:53.360 well what's going to happen. Yeah. That's one of the things about cycling that I really love. I mean,

00:10:57.380 I don't know if you saw, but I interviewed Lance Armstrong back in, oh gosh, probably back in June or

00:11:01.680 maybe it came out in September. But one of the things that we talked about was both on and off EPO

00:11:07.300 or blood transfusions. You sort of knew where you stood before the race based on your FTP in watts

00:11:15.100 per kilo. He talked about when he was off EPO, he could hold 450 watts for 30 minutes. So that would

00:11:22.860 be slightly above FTP at 70. I think he was 70 to 75 kilos, but it was in the ballpark of six watts per

00:11:29.820 kilo. And then of course on EPO, it was 7.1 watts per kilo, a huge difference. But you knew that number

00:11:36.380 going in and you sort of knew only the GC contenders could do that. I think that's the

00:11:41.780 thing that a lot of people don't understand about cycling, which is there's relatively few moments in

00:11:46.840 the tour when you need to sustain that level, but they always occur at the most important strategic

00:11:53.220 times. And that's sort of where the race is won and lost because the race is won and lost by minutes.

00:11:58.460 How many hours does it take to complete the tour? A hundred hours or something?

00:12:01.880 An average about four and a half, five hours a day. Yeah. So something like that. Yeah.

00:12:06.040 It's about a hundred hour race. And yet the difference between the first, second, third guy

00:12:11.380 will be in some cases, seconds, in some cases, a few minutes for someone to win by five minutes

00:12:17.620 is considered a blowout. And so what it really tells you is that there are a handful of minutes

00:12:23.040 in that race. There are a handful of climbs and time trials that set apart the winners from everybody

00:12:28.220 else. And to me, that's one of the beautiful things about cycling physiology is you have these

00:12:32.940 metrics. And now I think it's not just FTP, it's watts per kilo at lactate production. So it gets even

00:12:40.400 more into the critical physiology of recovery. And in fact, we use these metrics a lot for the

00:12:46.780 competition and we did it this year at the Tour de France. So knowing the power output that he could

00:12:51.980 sustain for, as you very well said, for specific times and climbs, we knew his capabilities.

00:12:58.500 And one of the things that we knew was that in the Alps, he was at a very, very high level.

00:13:05.000 That famous stage where he broke away and called the Rome 35 kilometers to the finish line,

00:13:10.500 we were seeing not only his data, but we see by knowing our writer's data, you can also guess

00:13:17.560 the other writer's data too. It's not rocket science. So we knew that he was at a very high level

00:13:24.020 and discussing the takes, you know, because it's part of the thing that we do. We observe

00:13:27.960 the data that we have, the data that we think the other ones have, and we structure a strategy for

00:13:33.820 the next day. And hey, does he have the legs to attack? Should be holding back? Or what should

00:13:39.240 we do? And clearly it was like, well, tomorrow, if he attacks 35 kilometers to the finish line,

00:13:45.120 he's going to get there with three minutes because the other guys, they're not at that level.

00:13:49.500 Why wait to the end of the tour where we can try to solve the situation? So we know his

00:13:53.400 capabilities very well and discussing this with him and the manager. Yeah, that was the strategy.

00:13:59.460 First test the legs. And like I, if you had in fact good legs, boom, go for it. And that's exactly

00:14:04.760 what he did. Now, how much of that are you going to determine after a night of sleep where you say,

00:14:10.900 we're going to look at his resting lactate first thing in the morning. We're going to look at his

00:14:15.040 heart rate overnight. We're going to look at his heart rate variability overnight. So in addition to

00:14:19.480 the subjective, for example, how he felt during the previous day's attacks, coupled with some of

00:14:25.320 that objective data, does that partially formulate the strategy also? Or is it mostly based on

00:14:30.880 historical data from training where you say, I know that when he's at this many watts per kilo for

00:14:37.800 this many minutes, he has the capacity to recover. The latter, where we have all that physiological data

00:14:44.260 and the trends. What we see at this level, these guys, they're so good at ignoring their feelings.

00:14:51.120 Sometimes it's just kind of how they wake up. You know his capabilities. So if he wakes up fresh,

00:14:57.680 it's like a baby. Boom. Then you're ready. And sometimes, yeah, it's just we try not to focus

00:15:03.860 on many other metrics that they, because we have already things. And sometimes heart rate variability

00:15:10.260 might not be very precise. And we don't want to put some ideas in the head that, and in fact,

00:15:16.580 speaking with him, you know, and I'm not going to mention any brand or anything, but looking at

00:15:20.660 heart rate variability someday, he'll say like, look, today, he told me that I was fatigued,

00:15:26.260 that algorithm, and I went out there and beat my record on the client. So obviously, I'm not fatigued.

00:15:32.060 Other days, it tells you you're in top form, and I feel a little more fatigued. So this is what

00:15:36.960 these algorithms we need to be careful sometimes, and might work with maybe general population. But

00:15:42.680 with this type of athletes, at this level, I really feel that it's better. Once you have all

00:15:47.960 the work done, you know their capabilities. Like, are you ready to go? It's like a top performer at

00:15:53.880 a theater. You have worked very hard. Now it's up to like, are you ready to go? Do you have a good

00:15:59.500 next lead? Are you ready to perform? And a good performer will say, yes, I'm ready to go.

00:16:04.360 I agree with you completely. Even for me, and I'm not a top level anything, I have not found the

00:16:11.480 predictors of readiness to be very accurate or to necessarily reflect how well I'm going to perform.

00:16:18.520 I've had amazing performances. By performances, I mean workouts. That's the only metric I'm

00:16:23.960 performing in. I've had amazing workouts when my prediction was that it would not be good. And I've

00:16:30.780 also had the prediction saying, you're on top of the world, and I not performed well. So I wish I

00:16:36.780 could say with more clarity what the frequency of those deviations or discordances are. But I can

00:16:43.060 agree that putting the wrong idea in somebody's head, when there's nothing you can do about it,

00:16:47.740 I mean, that's the other thing too. It's sort of like, at best, if it was perfectly accurate,

00:16:52.480 it would be great. Because you could say, look, today, maybe we shouldn't attack. Today,

00:16:55.900 it's damage control day. One of the things I want to ask you about here, and you've spoken about this

00:17:00.500 publicly, so it might be that you're just going to restate the views that you've shared publicly.

00:17:04.780 But I've always felt that now that we have such great transparency from that high octane era of

00:17:13.360 the maximum probably cheating in cycling, which in my view is kind of that two decades of the 90s and

00:17:20.500 2000s. We pretty much know now what kind of numbers cyclists were putting out when they were being

00:17:26.940 assisted by EPO and blood transfusions. And we sort of know that the best of the best were able to put

00:17:32.520 out somewhere between about 6.8 and 7.1 watts per kilo at FTP. We also know today that cyclists are

00:17:40.320 not doing that. Those numbers are nowhere to be found in the Peloton. Now that's information you and I

00:17:46.580 share confidentially, that's not public knowledge. But I know it, you know it, and anyone coaching

00:17:54.100 people at that level know that nobody's putting out 7.1 watts per kilo. You don't need to be at 7.1

00:18:01.420 watts per kilo to win the tour today. You could probably win the tour today at 6.1 watts per kilo.

00:18:06.660 Do you think that making that data public would put to rest a lot of the criticisms that say they've

00:18:15.280 just found new ways to cheat, but it's still basically a dirty sport? Because when you look

00:18:21.180 at the data objectively, it would be very hard to say that today based on what we know from the era

00:18:26.640 when drug use was rampant. No, I think you make a very good point. It frustrates me when people think

00:18:32.800 that they're doing 7 watts per kilogram, 7.2, and then you have the real data from the day. And this is

00:18:39.340 way lower. The short climbs where they would do maybe 7.2, now they're doing 6.3 maybe. And the

00:18:47.200 longer climbs, they're doing 5.5, 5.8. It frustrates me because I see this data. Gosh, I wish I could just

00:18:55.000 boom, release it. I have absolutely no problem with that. We debated it with the team. We're keeping

00:19:01.120 all this. At the end of the day, people can figure that out. And some people, when I see an internet,

00:19:06.020 as you can see the weight of the cyclist, the grade of the climb, when it starts, the time

00:19:11.940 and the wind, you can be very accurate at knowing that. And I see some people that are quite accurate

00:19:17.440 internet, but I see other ones are all over the map. The formula is 7.2. My gosh, I wish I could

00:19:23.660 show him, hey, this is the real data that we're seeing. Two points there is like one, it's private

00:19:29.580 data that the team considers like not release it. That's team policy. But the other one too,

00:19:35.460 is like, even if you release that data, there are always going to be people that are not going to

00:19:40.020 believe you or they might say, oh, they're probably altering the data or they're tricking it somehow

00:19:45.480 or putting more weight to the data. So it looks like there's less power output. I don't know if

00:19:51.680 it'll be an endless fight. I don't have the answer. I just have that frustration that I wish that I

00:19:58.380 could really show the data and people can see it. There's always going to be someone who is not going

00:20:03.660 to live it and going to make a lot of noise out of that. That's the other thing too, is like other

00:20:09.320 teams and other writers are releasing their data. So by releasing their data, you can see pretty much

00:20:15.200 where Pogacar is. Okay. If it's a minute ahead or 30 minutes, seconds, or sometimes with the same time,

00:20:21.900 you can see, you know, like, whoa, whatever the writer has done and has entered Pogacar's group or

00:20:27.100 30 seconds later and has done 5.9, Pogacar is going to be in that neighborhood. It's not going

00:20:32.300 to be seven, you know, with 30 seconds ahead. In the spirit of releasing data, the other thing

00:20:37.200 it would potentially do, especially if you could see it in real time. I don't know if you watch

00:20:40.780 Formula One, but one of the things about Formula One that I think the sport has been able to do

00:20:45.740 because of the advances in technology is make more of the data available to the viewer. If you're

00:20:51.860 watching Lewis Hamilton driving a lap, you see what he sees now. You can see, and it's not the

00:20:58.820 end of the world data, but you see his speed. You see what gear he's in. You see the difference

00:21:03.160 between throttle and brake pressure. They could show even more data, certainly. And someone who

00:21:08.040 drives would appreciate it if you really saw brake bias. And if you saw brake pressure and lockup and

00:21:13.280 things like that, and you can hear the drivers speaking with their race engineers. So it basically

00:21:18.980 allows you to come more and more into what they're doing. This year, they introduced a new camera

00:21:23.580 angle, which is what the driver sees. And I think it's fantastic because historically you see above

00:21:29.320 them and it looks so smooth, but that's not at all what it feels like to be in a race car. So now they

00:21:34.360 just literally put like a camera at their shoulder. And now you see how restrictive the halo is. You see

00:21:40.320 the bumps and it looks a lot faster. You know, I've had this discussion with a number of people,

00:21:45.220 which is if you could show the same sort of information in cycling, if every time the camera

00:21:50.560 went over to a cyclist, you saw their heart rate, their Watts per kilo, their speed, all of these

00:21:57.260 other things. And you could hear some of the communications back and forth with their teams.

00:22:01.900 Yes, that changes the sport strategically. Now you have to be careful what you say on the radio,

00:22:06.240 but it also allows you to see the human element of this sport a little bit more.

00:22:11.080 Do you think that will ever happen where you'll be able to flip on the Tour de France and you'll

00:22:15.460 be able to actually see real-time physiology? I would love it. It would be so much fun for the

00:22:21.940 viewer and cycling has so many possibilities to engage people more and be fascinated by the

00:22:28.440 physiology and looking at these numbers. It's already in a way, you see some cameras already

00:22:34.480 installed in the front and the back. It's called Vellon. You can see really cool images when they're

00:22:40.320 preparing a sprint that is like what feels inside. And you can see it's really scary. Sometimes you

00:22:46.320 can appreciate how difficult it is to be at 40 miles an hour sprinting or 35 miles an hour leading to a

00:22:52.840 sprint or in a descent at 60 miles an hour. Or 70 mile an hour descent.

00:22:56.260 Or 70 mile an hour descent. Exactly. And then you can see the power output in real time. I think it's a

00:23:02.960 great step. You don't see no other riders, but it's estimation only the riders who wear that Vellon

00:23:08.320 or the Vellon decides to do that. And I think that they're still not doing that with all the top

00:23:13.760 contenders. But I think it's a first step and obviously haven't spoken with them, but maybe it's

00:23:19.200 like, hey, let's see what's the feedback. And I think that people are loving it. I would expect that

00:23:23.660 this will increase. I would love at some point, you know, and as you know very well in the world of

00:23:28.460 biosensors, going to revolutionize sports where we're going to be able to see so many different

00:23:34.760 parameters of athletes in real time. Yeah. Imagine you could see lactate and glucose in

00:23:40.400 real time. Yeah. Absolutely. Which of course is technologically feasible already. Exactly.

00:23:45.200 Yeah. I think that would love for all sports too. Imagine you can see an NBA basketball game and see

00:23:51.860 that the lactator of LeBron James compared to the other ones. I mean, I would love to see that as a

00:23:57.220 spectator. And I hope that someday we were able to see these parameters.

00:24:01.020 So last thing on the tour, talk to me about Ventoux this year. That was a tough stage.

00:24:07.020 It looked like his toughest stage. Is that a fair assessment?

00:24:10.100 Yes, probably.

00:24:11.400 And what's amazing, I think, is the poise on that stage. It's hard to tell if he was really

00:24:15.880 struggling on the ascent of Ventoux or he was just deciding strategically, I'm going to conserve a

00:24:20.860 little bit of energy here. What was your take on that? Or what can you say about that?

00:24:24.620 It was a very difficult climb and a very long climb. Tade, his mentality is wired like a champion.

00:24:32.380 When someone goes and they were full gas in the last part, when you are attacked, Tade knew that

00:24:37.800 this is not going to be the top of Bon Ventoux. It's not going to be the end of the stage.

00:24:41.900 There's a very, very long descent. And I have some partners with me that they can help me out.

00:24:48.100 But I'm not going to panic at all, but I'm not going to also waste a lot of energy. He also had

00:24:53.920 a big gap. A whole different thing would have been if he had 20 seconds. But having a big gap

00:24:59.620 and knowing that you have a big descent and how calmed he is, that's one thing that is a very

00:25:05.460 important strategy. This is what happened. This reminds me in a way what happened the first year

00:25:10.980 that he was pro when he was 19 at the Tour of California. It was the previous stage before

00:25:16.580 Bear Lake, top mountain in the Tour of California, where it's going to be decided. So the day before,

00:25:23.180 two cyclists, George Bennett and Yigita attacked in a short but very steep climb. And there were only

00:25:28.940 like 12 riders left and Yigita and Bennett attacked. Then there was like a descent and a long highway

00:25:36.060 all the way to the finish line. So there was plenty of time to catch him up, but Tade didn't follow

00:25:41.300 them up. Another rider would have just followed their wheel and Tade decided, no, I'm not going to

00:25:46.560 follow them. We have time and I'm going to take the chance because I'm confident for tomorrow.

00:25:51.320 And when I asked him, as soon as he crossed the finish line, I asked him, are you okay

00:25:54.940 where you didn't follow their attack? He said, well, I just, I wanted to know who is going to be good

00:26:01.740 tomorrow. So I know those two guys are going to be good tomorrow, but I wanted to take my time

00:26:06.060 and see the other 10 guys, how they're breathing, what's their body language, take my time to observe,

00:26:11.940 to start preparing my strategy for tomorrow. And in fact, that's what he did. They were then caught

00:26:16.780 up two, three kilometers to the finish line. So all those 12, 13 guys, whatever they were,

00:26:21.640 they got together. And the next day, in fact, he noticed those two guys attacked. He just followed

00:26:27.320 them and he just eliminated one by one. That's how this guy thinks. No panic. Plenty of time today.

00:26:33.620 I have a good gap in the GC. Why am I going to go full gas when I know that he is going to

00:26:39.440 go full gas and he might lose energy for tomorrow because he might pay for this at this time of the

00:26:45.480 two of the friends and we have plenty of time to catch him up. So that's kind of the strategy that

00:26:50.060 he had. How much time does someone like Teddy spend in zone two, which we're going to talk a lot

00:26:57.920 about, and let's do it more as percentage of training time. Cause I think absolute numbers will

00:27:03.320 be very large given that that's his job. But when you think about the percentage of time he spends in

00:27:10.360 that energy zone, how does it change over the course of the year? So presumably during the winter

00:27:16.540 months, a greater amount of his time would be spent there as he's base building right before a race

00:27:22.020 when he's kind of sharpening, maybe less, what would be the range of time or percent rather? Yeah.

00:27:27.180 Yeah. You're right. When we talk about percentage, I like to put it this way, more like a percentage

00:27:32.600 of days dedicated to cultivate that energy system. Obviously if you put in just every single minute

00:27:39.440 together, the majority is going to be that, but I would say more in days in the winter months might

00:27:45.520 be about 80%, 70 to 80% of the days. As the season gets closer, he starts increasing more intensity days

00:27:54.400 and sessions when the start of the season racing and you have, it depends. You might have one stage

00:28:00.720 race of five, seven days, and then you have five day block or one week to recover and then you have

00:28:06.240 the next stage race. So in that week, we do a lot of recovery. We might do some sessions here and there.

00:28:11.240 And then after a few blocks of races, that's where you have another long time to train, period to train,

00:28:18.980 go to altitude towards the Tour de France or towards the next goal. And that's where you may

00:28:24.220 revisit these different energy systems and train specifically. We alternate and each energy

00:28:30.800 system has a time in the year, in the calendar where it's built in order to try to achieve what

00:28:37.760 we want. So let's remind people now, I've put out a few posts on social over, gosh, the past year and

00:28:44.880 even in the past little while. And anytime I'm talking about zone two, it's really one of the topics

00:28:49.600 that generates the most curiosity, the most inquiry from people. I think people really intuitively

00:28:55.960 kind of resonate with this. And then of course, a million questions follow because there's so much

00:29:01.200 minutia and detail around it. And a lot of that we're going to cover today, but let's start from

00:29:06.180 a place of maybe someone hasn't heard the first podcast where we go through some of the semantics

00:29:11.120 of this. Define zone two. From my point of view, it is the exercise intensity at the one you are

00:29:18.840 stressing the mitochondria and oxidative capacity to the most. This is where you're recruiting mainly

00:29:25.020 type one muscle fibers. This is where you are mobilizing the highest amount of fat, both from

00:29:31.780 lipolysis, from antipose tissue, as well from fat oxidation inside the mitochondria. And this is also

00:29:38.040 where you stimulate all those bioenergetics, which is oxidative phosphorylation. This is where you burn

00:29:45.220 both the fat inside the mitochondria, as well as the glucose inside the mitochondria. There's not a very

00:29:51.520 high glycolytic flux that it's going to be transformed into pyruvate and reduced to lactate, but that flux

00:29:59.040 still is oxidized inside mitochondria. This is looking at from bioenergetics standpoint, this is what I would

00:30:06.620 consider the zone two. And what I have seen is that throughout the years is that this is the exercise

00:30:12.560 intensity that achieves or stimulates that mitochondrial function and fat oxidation and lactic

00:30:20.320 clearance capacity the most. That's the other thing too. This is where other things involving lactate. So

00:30:28.140 lactate is a great fuel to the cells. It's in fact, it's probably the preferred fuel for the cells, for most cells

00:30:35.840 in the body. This is a work that my colleague and mentor and friend, George Brooks discovered.

00:30:42.100 Should have him someday in the podcast because he's fascinating. I mean, I would not be surprised

00:30:46.580 if someday soon we hear that he wins a Nobel prize. He's amazing. And every time I talk to him, I'm still

00:30:53.160 learn a lot of things. And then I've been translating a lot of his research. That's how I see that you have

00:30:59.720 within the mitochondrial function. You see how lactate is oxidizing the mitochondria back to energy.

00:31:05.700 And that happens in those muscle fiber types. Those muscle fiber types and the mitochondria,

00:31:10.860 those fiber types also develop these transporters, which are MCT1s, which are the ones that transport

00:31:17.660 lactate inside the cell and inside mitochondria. So when you stimulate that training zone, you stimulate

00:31:24.440 all these energy systems and the components that come with them. So let's talk about the different ways

00:31:29.760 that one can go about estimating this. Based on the definition you've just given, it seems to me

00:31:36.460 that the purest way to estimate this would be via indirect calorimetry, because that will actually tell

00:31:43.600 us the fat oxidation. Is that a fair assessment? Yes, it's a very good assessment that usually correlates

00:31:50.160 with the fat max. That's how we call it too, right? That's fat oxidation. And when you see that

00:31:55.140 you start oxidizing fat and may increase in cases and gets to a point that it maxes out, which is the

00:32:03.000 fat max, and then it starts going down sharply. That's exercise intense, it increases.

00:32:08.440 So let's tell people how that's measured. We do this with all of our patients, and I find it

00:32:13.880 to be not that easy to explain because there's some physiology involved and there's some math

00:32:20.760 involved. But let me try to see if I can explain this to folks. So you hook me up to an indirect

00:32:26.080 calorimeter. So you're going to put a little plug on my nose. You're going to put a mask over my nose

00:32:32.540 and mouth. That mask has the ability to measure the amount of oxygen that I consume because it has a

00:32:39.680 sensor for O2. So it knows that the O2 that's coming in is at 21%. The air is coming in at 21% O2.

00:32:47.940 And whatever I exhale is the difference between that. So you can now tell how much O2 was consumed

00:32:53.820 and you can have a similar sensor for carbon dioxide. So you know how much carbon dioxide is

00:32:57.980 produced. So it's very easy to measure consumed oxygen and produced carbon dioxide, provided you can

00:33:04.300 completely isolate around the nose and the mouth. As you hook a person up to some form of ergometer,

00:33:11.160 usually a bike, could be a treadmill, a rowing machine, or something like that, you can increase

00:33:15.900 the demand on the muscle. So you increase the wattage or the speed or the something. You then get out

00:33:21.880 these numbers, VO2 and VCO2, which are what we just talked about. So consumption of oxygen,

00:33:27.740 production of carbon dioxide. These numbers fit into a relatively straightforward linear equation

00:33:33.700 called the Weir equation. And it tells you three things. It tells you total energy consumption

00:33:40.380 in kilocalories per minute. And then the ratio of VO2 and VCO2 tell you how much of that energy is

00:33:49.980 coming from fat oxidation and how much of it is glycolytic. So at any moment in time, you can look

00:33:57.460 at a VCO2 and a VO2, which are usually measured in liters per minute, and you can convert that into

00:34:04.800 a total grams of fat oxidation and a total grams of glucose oxidation per minute. And so you could then

00:34:14.160 plot on the x-axis work or power, and on the y-axis, you could plot fat oxidation. Again, describe for

00:34:23.840 people what the shape of that curve looks like, and what differentiates Pogacar from the average

00:34:31.160 human being.

00:34:32.520 You explained it very well. Yeah, those are based on stoichiometric equations. The combustion of

00:34:37.480 carbohydrates and fatty acids are done in the body. Already in the 1920s, Francis Benedict, one of the

00:34:43.720 first ones, probably the first one who started to look into this at this level. Obviously, we have evolved,

00:34:49.300 do it in a more automatic way. With this indirect calorimetry, machines are called also metabolic

00:34:55.120 cards. As exercise intensity increases, I mean, you need more oxygen, so your VO2 increases, and then

00:35:03.040 you produce or give up more CO2. So this is kind of what it shows. When you're in a more lipolytic state,

00:35:11.820 more fatty oxidation state, you still consume oxygen, but you do not produce as much CO2.

00:35:17.780 When you are more into a more glycolytic state, which is higher exercise intensities, when you're

00:35:24.500 recruiting the type 2 muscle fibers, and therefore using more glucose for energy purposes, you're going

00:35:31.180 to consume more oxygen, and you're going to produce more CO2. Plugging in all these numbers into these

00:35:37.540 stoichiometric equations, it's going to give you that profile, the x and the y-axis, and it's going to

00:35:46.160 see what is the fat oxidation throughout ramp state, a ramp test. And this is where you're going to see

00:35:52.560 elite athletes like Pogacar, they have an amazing fat oxidation capacity compared to other competitive

00:35:59.660 athletes or recreationals or people with even type 2 diabetes or metabolic syndrome, or in a recent study

00:36:06.580 we have published with COVID patients. So it reflects in a way, ultimately, what happens in your mitochondria

00:36:14.280 and how the mitochondria oxidizes those fuels at different exercise intensities. So for example, let's say

00:36:21.400 at the intensity of 200 watts, a lead athlete doesn't need to incur in that glycolytic capacity as much as someone

00:36:30.940 who is not very well trained. So the elite athlete, they can still recruit slow twitch muscle fibers

00:36:37.840 and rely a lot on fat to produce ATP because they have an amazing mitochondrial function and they're very

00:36:45.280 efficient metabolically speaking. Therefore, they're going to be oxidizing a lot of fat. However, someone

00:36:51.280 whose mitochondria are not working as well, whether you are like a recreational athlete or sedentary

00:36:58.780 individual or someone with type 2 diabetes, which is one of the hallmarks of the disease,

00:37:04.500 that mitochondrial impairment or dysfunction at 200 watts, you fully rely on glucose pretty much

00:37:10.660 because you cannot sustain that effort with fat alone. And this is what you're going to be seeing

00:37:17.820 this cas exchange, the CO2 and the VO2. You can just plot it into the equation and it's going to give you

00:37:24.800 all that what I call metabolic map where you see the fat oxidation, the carbohydrate oxidation,

00:37:30.520 and then I plug in also the lactate. And that's where everything comes together quite well. And you

00:37:36.980 can then first, in an indirect way, calculate the mitochondrial function and metabolic flexibility,

00:37:44.680 how flexible they are at using fats or carbohydrates. And also you can determine training zones.

00:37:51.020 I've been using this methodology for 16 years, 17, something like that.

00:37:56.540 I didn't think to ask you this earlier, but if you have it handy, do you want to pull up a graph

00:38:02.380 of what fat oxidation looks like versus power so that people can see the difference between a highly

00:38:12.100 trained individual, a reasonably trained individual, an untrained individual, and at the other end of

00:38:17.560 that spectrum, somebody with type 2 diabetes? So this is from a publication that my colleague George Brooks

00:38:23.340 and I published in 2017. This is the formula and we have realized that this is flipped. So we need to

00:38:31.440 work now with the editor to change it because the formula is flipped here in the methods section.

00:38:36.880 Which is so funny, by the way. I like seeing that. I'm embarrassed to say when we do this for our patients,

00:38:41.900 we do it in two steps, which yields the same result, but we first calculate energy expenditure

00:38:48.420 using the Weir coefficients of 3.94 times VO2 minus plus one point, I think it's 1.2 times VCO2.

00:38:57.360 And then we convert that to fat ox and carbohydrate oxidation using the ratio of VCO2 to VO2. And I never

00:39:08.740 even thought to do what you've done here, which is so much more logical, which is combine them into

00:39:13.560 a single equation for each. Well, we use what Fryant observed already in 1983. And this is Fryant's

00:39:20.900 equation. And it's been validated with tracers, stable isotope tracers. Doubly labeled water. Yeah. And

00:39:27.200 that's what it shows. There's a very high correlation. Now, furthermore, in study that we were going to be

00:39:32.680 publishing soon, we have validated this fat oxidation and carbohydrate oxidation directly

00:39:38.160 with mitochondrial respiration. So in muscle biopsies, we inject directly fatty acids,

00:39:46.340 pyruvate representative of carbohydrates, glutamine representative of amino acids. And then we can see

00:39:52.000 that there's a very high correlation between this indirect methodology to look at mitochondrial

00:39:57.420 function and the direct methodology, which is through muscle biopsy and injecting the substrate

00:40:02.540 and see how it's oxidized. So these two graphs are really powerful. Let's talk about what the first

00:40:08.340 graph is showing us. So both of these graphs, it's important to note, have the same x-axis. In other

00:40:14.880 words, the independent variable here is the workload in watts. That's the metric that matters in cycling,

00:40:22.380 which is, I think, the easiest way to do this test. And so you're increasing wattage. This is a

00:40:27.480 progressive increase in workload. And what you're plotting on the y-axis, your dependent variable

00:40:33.780 here in the first graph, figure one, is blood lactate. What stands out to me is a couple of

00:40:40.040 things. So you have the triangles represent metabolic syndrome. The squares represent a modestly

00:40:47.600 trained athlete. And then the little diamonds represent a professional athlete. The first thing that

00:40:52.960 stands out to me, and we're going to talk about this later, so I'll put a little pin in this,

00:40:57.160 is that the people with metabolic syndrome have a resting lactate that's almost two millimole.

00:41:02.480 Yes, we see already this. I think that it's going to become more and more as a biomarker,

00:41:07.560 like resting blood glucose levels. What is your resting lactate? You can see already in patients with

00:41:13.260 type 2 diabetes or profound metabolic syndrome that, yeah, as you say perfectly, yeah, resting levels are

00:41:20.280 in the neighborhood of like a 1.8, 1.5 to even 3. So one of the metrics that we've discussed at length,

00:41:27.860 and we'll revisit it, of course, is using this lactate level of about 2 millimole as being that

00:41:33.760 threshold. So once lactate exceeds 2 millimole, the individual is now escaping out of zone 2,

00:41:41.180 and they're actually now into zone 3. So when you look at these data here, you can see that the

00:41:45.960 individual with metabolic syndrome is basically tapping out zone 2 initially. So any incremental

00:41:53.300 workload that is placed on them takes them right out of zone 2. For all intents and purposes, by the

00:41:59.300 time they're at 100 watts, they're already at the threshold of their zone 2. Now, conversely, when you

00:42:05.360 look at that medium-trained or reasonably well-trained individual, I think it's referred to as moderately

00:42:11.720 active, healthy individuals. They start out with a lactate of about 1, and it's not really until they

00:42:17.100 hit about 175 watts that they pass that inflection point. And then when you look at the professional

00:42:24.660 athletes, the professional endurance athletes specifically, they're starting out at a lactate

00:42:29.620 level of 0.5 millimole, and they stay relatively flat until they hit about 300 watts, is when they

00:42:38.940 finally cross over that threshold. Now, what's not captured here is that as you move from left to

00:42:48.020 right, the athletes are getting lighter. So this graph, if I'm going to be critical of it, and you go,

00:42:55.620 I would say it should be done in watts per kilo. And that would show a much starker difference between

00:43:02.580 these. And in our patients, when we benchmark them, we benchmark them in watts per kilo for this reason,

00:43:08.100 so that you normalize by weight. And I'm sorry to interrupt, but you're absolutely right. And that's

00:43:12.760 how we do it also. One of the reviewers didn't allow us to use watts per kilogram. Clearly that

00:43:18.640 reviewer was an idiot. So that's fine. I don't know. I won't let it against you because the idiot

00:43:22.840 reviewer. You know how it is in review papers. You want to show something, and eventually it's changed,

00:43:27.420 and it's not exactly sometimes what you want to show, because otherwise they don't allow you to

00:43:31.980 publish it. But anyways. But what's amazing here is that person with metabolic syndrome

00:43:37.420 is probably about one watt per kilo, easily. One to 1.3 watts per kilo is their zone too.

00:43:45.500 When you look at the modestly trained individual, they're about two watts per kilo. They probably weigh

00:43:52.000 maybe two to 2.1, 2.2 watts per kilo. That professional endurance athlete probably weighs in

00:43:59.160 the neighborhood of 70 kilos. So they're in the ballpark of four watts per kilo. For our patients,

00:44:07.440 Indigo, we set the aspiration at three watts per kilo. So again, our patients aren't professional

00:44:13.000 athletes, but we think that three watts per kilo would be kind of the elite level that we would want

00:44:18.580 to see people. And then of course we stratify from there. Let's look at the lower figure, figure two,

00:44:24.020 just beneath this. So here we're looking at the same group of individuals. We have the same

00:44:29.060 independent variable, which is work, but now we're calculating fat oxidation as a function of that

00:44:36.260 work. So now your dependent variable is fat oxidation, which again, very easy to calculate

00:44:40.860 via indirect calorimetry. Two things stand out again. The first is the obvious, which is the

00:44:46.620 fitter the individual, the higher their absolute capacity for fat oxidation. But something else stands

00:44:53.100 out to me, Indigo, and I have now seen this repeatedly across multiple data sets, which is a fit individual

00:45:00.420 actually increases fat oxidation to a local maxima before beginning that decline. Whereas most mortals

00:45:10.220 begin at a maximum and decline from there. Can you explain why that's happening?

00:45:15.240 I agree. I see this all the time. I think that on one hand is how you start the protocol. In this case, we started

00:45:22.620 like at one. We start about one to 1.5 watts per kilogram. And that obviously for an elite athlete is

00:45:29.560 below resting level. So this is what they're very low and they don't need to use much fat for energy purposes until you

00:45:37.160 push them more. And that's when you get to like 2, 2.5, 3, 3.5 watts per kilogram, right? And again, this protocol

00:45:44.600 comes originally from the work that I've been doing for 20 years, this same protocol with elite athletes. When you do

00:45:51.480 the same protocol with other populations, especially people with metabolic syndrome or not very fit, and you start at

00:45:57.540 1.5 watts per kilogram, that might be too much. And I'm sure you have observed that if you start at

00:46:03.740 0.5 watts per kilogram, you might see a higher fat oxidations, and then you might see the same

00:46:10.260 phenomenon. So on one hand is that protocol, but on the other hand, yeah, sure, like 0.5 watts per

00:46:16.700 kilogram, it's like nothing. It's close to resting levels. So it will take you for a long time. But

00:46:23.820 that being said, I think that one thing that we're doing with populations for more clinical populations is

00:46:29.480 really starting at a very low level, even up to 50 watts or 25 watts sometimes. So we can establish

00:46:35.620 this point because if you start at 2 watts per kilogram or 1.5 watts per kilogram with someone with

00:46:41.100 a significant metabolic dysregulation, you're going to miss the fat max. Yeah, I agree with you. We have

00:46:47.540 been struggling to tune our algorithm to exactly that. I actually think, and I had this discussion with

00:46:55.160 our team a week ago, which was the physiologists who are doing this with our patients are probably

00:47:01.380 overcooking the people who are not fit during the warmup. So they do a warmup and the warmup is

00:47:07.700 actually too stressful and it overcooks them. And then we're missing the true max fat. The next thing

00:47:14.180 I want to point out here, and let's just look at the fittest person, but it's true for all of them,

00:47:19.160 but it's easiest to see here. Fat max, so fat max ox, right? So maximum fat oxidation is occurring

00:47:27.000 earlier than lactate is 2. And that's true for all of them, except for the MetSyn person because

00:47:33.780 it's so low. If you look at the moderately fit person, they're hitting maximum fat oxidation at about

00:47:40.420 130 watts, but they're hitting lactate of 2 at 175 watts in the upper figure. And the professional

00:47:47.960 athlete is hitting an absolute fat oxidation maxima at a little shy of 250 watts, but they're hitting

00:47:57.060 lactate of 2 closer to 300 watts. So I guess the question then becomes, you've already answered

00:48:04.660 part of the question, which is we're really defining zone 2 as the place where maximum fat oxidation occurs.

00:48:11.200 But I guess this would suggest that using a lactate level of 2 is maybe overestimating

00:48:18.100 where that is. And should we be using a lower level of lactate, such as 1.5 or something like that?

00:48:24.920 This is what I've been learning all these years is that the blood lactate levels might change between

00:48:31.640 different groups. And it's everything related to the lactate kinetics and lactate oxidation in the

00:48:37.760 mitochondria. So for example, elite athletes, so this was part of my doctorate thesis and some of

00:48:44.860 these that never published it 20 something years ago, but the same blood lactate concentration does

00:48:51.920 not correspond in an elite athlete, does not correspond necessarily to the same lactate concentration

00:48:57.920 in a recreational athlete, the metabolic stress. So for example, 2 millimoles, 2 millimolar

00:49:06.020 of lactate in these elite athletes might be a higher metabolic stress than 2 millimoles in a metabolic

00:49:12.460 patient. So this is why it would be very difficult. For example, you can have, let's say, 2.5 millimoles,

00:49:19.120 you can have a metabolic syndrome patient exercising for a couple hours without a big deal. You try to do

00:49:27.100 that with a professional athlete and they're going to be hurting. And in fact, one of the things that I

00:49:31.980 observe is like I use the 4 millimole or millimolar, which is kind of that gold standard has been

00:49:37.060 forever like the lactate threshold, et cetera. If you put a world-class athlete at 4 millimoles at the

00:49:43.640 intensity and power output that elicits 4 millimoles and you put a recreational athlete at the power

00:49:51.420 output that elicits also 4 millimoles and you say, now go, see who lasts the most. Intuitively, we're going to

00:49:58.180 say obviously it's going to be the professional athlete. It's the opposite. And this is the data

00:50:02.640 that I saw 20 something years ago. The recreational athletes at the same blood lactate concentration

00:50:07.760 would go about 30% longer periods of time. And that's because metabolically it's not as tasking.

00:50:15.980 And the main reason is that the lactate that we see in the blood, it reflects the mitochondrial

00:50:22.500 oxidation. So someone who has, obviously when we're talking about high power output, when you need a

00:50:29.380 lot of glycolysis to produce energy, you're going to produce lactate. Lactate is the mandatory obligatory

00:50:36.020 by-product, not waste product, but by-product of glycolysis. So the higher the glycolysis, the higher

00:50:42.420 the lactate. Now that lactate has two routes mainly. One is going from the fast twitch muscle fibers

00:50:49.220 to the slow twitch muscle fibers. It's the lactate shuttle that George Bruce discovered and is

00:50:55.900 oxidizing the mitochondria of those slow twitch muscle fibers. If you have a very good lactic

00:51:01.700 clearance capacity, you're going to be oxidizing it very, very well for fuel. Therefore, you're not

00:51:07.740 going to incur in the second step, which is exporting it to the blood. When you have a poorer mitochondrial

00:51:14.020 function, it's going to get to a point that that capacity is going to get saturated at a lower power

00:51:20.620 output. And therefore, you're going to be forced to export that to the blood. So that's why looking at

00:51:26.780 blood lactates might not mean the same. I'm not saying that disparities are huge by no means. But as you

00:51:32.500 very well said, those two millimoles might not correspond in an elite athlete with a fat max, but might be

00:51:38.700 more maybe towards 1.5. Whereas maybe in someone with a more recreational or metabolic syndrome,

00:51:44.480 it might correspond there. I don't know if it makes sense. It completely makes sense. And this is

00:51:49.940 definitely the level of nuance I don't think we captured in the first podcast. And I want to now

00:51:55.500 ask a more telling question specifically for the middle person here. So the one that's called the

00:52:01.960 moderately active individual, where again, we have a disparity. So based on these data,

00:52:06.740 the moderately fit individual hits a lactate of two millimole at 175 watts, but hits a max fat

00:52:15.100 oxidation at gosh, 125 watts. So it's a 50 watt difference. So now the question for you is when

00:52:23.340 that person comes to you and says, in you go, I want to improve my metabolic function. I want to improve

00:52:30.760 my mitochondrial performance. I want to improve my fuel partitioning, my flexibility, all the things

00:52:37.480 we talk about. Are you going to train them as a zone two of 125 watts or as a zone two of 175 watts

00:52:45.460 as represented by these deltas? Normally I would try to do something in the middle. Normally it might not

00:52:52.540 coincide perfectly, but normally they do quite well. And another parameter, if you allow me, I can show you

00:52:59.440 in this paper. When decided, we see individually the lactates and then we see the fat oxidation.

00:53:06.880 But then where I decided to cross them over. This is what we saw in this graph over here. So this is

00:53:13.000 where you see the lactate versus the fat oxidation in the elite athlete and the R is 0.97. This is

00:53:21.820 through Bonferroni equation. So this is an average of all of them. And this is where you see the same

00:53:27.720 pattern, the same graph for the moderately active. And this is also what you see in the person with

00:53:33.880 metabolic syndrome. The correlations are very, very strong. They're almost perfect. So this is what

00:53:39.280 normally fat oxidation and lactate, they go together. So for people who are going to be listening to this

00:53:46.420 in you go and not able to see what we're seeing, can you describe the differences between these graphs?

00:53:53.380 These are obviously showing the same data that we discussed earlier, but now we're using two Y

00:53:59.760 axes. So let's even just talk about it as looking at the elite athletes. So you're basically plotting

00:54:06.160 the decline in fat oxidation, or in their case, the initial increase in fat oxidation followed by a

00:54:12.940 decline in fat oxidation. And in the same graph, you're showing the increase in lactate production.

00:54:18.120 Again, both plotted to the same X axis of power. Does the cross point here indicate any significance?

00:54:25.940 So they're crossing at about 325 Watts. Is there anything about that that means anything? I mean,

00:54:31.580 to me, I think it's an artifact of the graph because it's really just a function of how you scale it,

00:54:36.400 correct? Yes, exactly. I mean, it shows to me that, yeah, the crossover point for blood lactate and

00:54:43.340 fat oxidation, very high, obviously in the elite athletes, very far to the right.

00:54:49.320 And then of course, in the moderately fit people, it's looks like it's closer to a hundred and maybe

00:54:54.080 80 Watts. And in the unfit individual, it's about 125 Watts in person with metabolic syndrome.

00:55:00.440 If you started, and I'm sure you have seen this, but if you started with the metabolic syndrome,

00:55:05.200 for example, at 25 Watts, even in the recreational athlete, even earlier, you might see a similar

00:55:11.200 pattern as you would see in the elite athlete, but a much lower Watts, obviously. We just did the same

00:55:17.360 protocol for everybody just to show the concept, both fat oxidation and lactate go together. And

00:55:24.760 also when we look into, and I'm sorry, I should have gone this to this directly. When we look into

00:55:29.760 fat oxidation and carbohydrate oxidation, we see the same concept. So we see as exercise intensity increases,

00:55:36.720 you need to oxidize more carbohydrates. And then as exercise intensity increases, you might get to the

00:55:42.880 fat max. And then when you moment you switch to the glycolytic fibers, you cannot use much fat for

00:55:49.840 energy purposes. So you see a sharp decline and eventually fat oxidation disappears and it's all

00:55:56.720 full glycolytic. And the same pattern we see in the rest of populations with also very high statistical

00:56:02.880 significances and correlations. All these elements, fat oxidation, carbohydrates, and lactate,

00:56:08.800 they're very well connected. If we look in the other graph, this is the correlation between lactate

00:56:14.480 and carbohydrates. We see that overall the correlations are quite good because lactate is the byproduct of

00:56:22.800 glucose utilization. You may see that in the elite athletes though, the gap is wider here. And this is for the

00:56:29.280 same reason that we're seeing earlier. They use a lot of glucose. They're using so much fat there as

00:56:34.160 well is really the point. So the bigger the gap between the blood lactate curve and the carbohydrate

00:56:39.760 oxidation curve, the more efficient the individual is. The more they're able to oxidize fatty acid,

00:56:46.960 then they have to require glucose. And clear lactate. Yes. The mandatory byproduct of glucose

00:56:54.000 glucose oxidation is lactate. So here the lactate doesn't show up in the blood. It stays in the muscle.

00:57:01.920 It's hard to disentangle those two because you mentioned a good point that I omitted. This in part

00:57:07.840 reflects the lactate shuttle. This in part reflects the ability for them to reuse lactate as a fuel,

00:57:16.000 as opposed to just letting it get out there with hydrogen and start to poison sarcomeres.

00:57:22.800 Let me see the other slide that you wanted to show that explains, I think, how the MCT transporters

00:57:28.400 work. This is a little bit more of the bioenergetics of the cells of the main two

00:57:33.840 substrates, which are fatty acids and pyruvate and also lactate, right? So normally glucose goes

00:57:39.120 through glycolysis and it ends up, this is the cytosol. This is the outside of the mitochondria,

00:57:43.920 the inside of the cell. And glucose, when it enters the cell, it's oxidized to pyruvate. That pyruvate

00:57:50.800 needs to enter the mitochondria through what's called the mitochondria and pyruvate

00:57:56.080 carrier. And it's oxidized to acetyl-CoA, which enters the Krebs cycle. This is a complete

00:58:01.920 oxidation of glucose through oxidative phosphorylation in the Krebs cycle and electron

00:58:07.120 transport chain. Then fatty acids have the same mechanisms too. They also get converted to acetyl-CoA

00:58:14.640 through different mechanisms. Fatty acids are transporter through CPT-1 and then CPT-2,

00:58:19.760 go through beta oxidation, acetyl-CoA and enter the cell. But every time that you use glucose,

00:58:26.800 you produce pyruvate and every single time that pyruvate is going to be reduced to lactate,

00:58:31.920 always. And this is the key concept. So when you have a constant glycolytic flux, in one of the steps

00:58:38.240 of glycolysis, you're going to utilize NAD. And it's going to be transformed to NADH plus hydrogen.

00:58:47.200 So if you use this mechanism a lot, you're going to deplete NAD. The only way that rescues NAD

00:58:55.680 is the reduction of pyruvate to lactate, which replenishes NAD going back for glycolysis. And this

00:59:02.400 is absolutely necessary for the continuation of glycolysis. But this lactate enters the mitochondria

00:59:09.040 through a specific transporter, MCT-1, and has a specific enzyme, LDH, that oxidizes lactate

00:59:17.280 back to pyruvate and going back to the Krebs cycle. So again, this is an extra fuel. But for that,

00:59:23.360 you need to have these transporters very well developed. Let me try to explain this to people

00:59:29.200 who aren't able to see the graph, because this is such an important point. So you're showing a

00:59:34.560 picture of the mitochondria. We're looking at the outer mitochondrial membrane. We're talking about

00:59:40.160 three transporters, three things that let substrates from the outside to the inside,

00:59:46.080 where they will undergo the most efficient form of ATP production. So the first is we have the fatty acids.

00:59:53.920 They enter directly, then they undergo an oxidation where they get truncated into

00:59:58.720 little two carbon chains and they enter the Krebs cycle. We get that one and we know why that one's

01:00:02.960 very good. What I think is very interesting here is when you contrast the two different fates of

01:00:10.160 glucose byproducts. So the traditional way that we think about this, glucose being reduced to pyruvate,

01:00:17.520 pyruvate directly entering the cell through its own carrier, and then being converted to acetyl-CoA,

01:00:23.920 which follows the same fate as the fatty acid. Now, when energy demand increases, and we just

01:00:30.480 looked at graph after graph that demonstrate that no matter how fit you are, at some point

01:00:35.360 you have to produce more lactate. So you now don't have sufficient cellular oxygen to go down

01:00:43.200 that first route. So you start making lactate. But if you have enough MCT1 transporters on the outer

01:00:51.920 mitochondrial membrane, you can now bring that lactate in the cell and actually do the reverse

01:00:57.520 of what just happened. Turn that lactate back into pyruvate. Pyruvate becomes acetyl-CoA and everybody

01:01:03.600 wins the game again. The game being won, of course, because now you're making 32 units of ATP instead of

01:01:10.080 just the two units you would make converting pyruvate to lactate. So it begs a very important question,

01:01:15.600 which is, earlier when you spoke about what makes Pogacar so remarkable physiologically,

01:01:23.920 one of those things is he must have a boatload of MCT1 transporters on his outer mitochondrial

01:01:30.880 membrane. And that must explain in part why his lactate levels are so much lower than everybody

01:01:38.080 else's at a comparable work level. How much of that is genetic? And how much of that is a result of

01:01:44.560 his training? Exactly. So you're right. He has a much higher level to oxidize lactate. So there's

01:01:52.160 a genetic component, no doubt about it. There's also an epigenetic component. And as we know nowadays,

01:01:58.400 the genes are not your fate, necessarily. From the genes to be able to be transcribed and form a protein

01:02:07.040 with biological action, the probability is less than 20%, kind of what the science is showing,

01:02:13.520 roughly. This is the whole from genetics to transcriptomics, proteomics, and metabolomics.

01:02:20.160 It's about 20% chances that one gene is going to be ultimately expressed. Obviously, we're still

01:02:25.200 trying to understand all this. So these elite athletes, probably they have a much higher

01:02:29.680 possibilities. But there's a long journey. And this is where epigenetics occur. It's like what you eat,

01:02:36.320 how you rest, how you train. And I think that the training is also an important component of this.

01:02:42.800 This is, for example, why we train very, very specifically this energy system. And we try to

01:02:47.680 dial in as much as we can specifically to try to stimulate this bioenergetics system and increase the

01:02:55.040 MCT-1s, the transporters for lactate, as well as all the components in the Krebs cycle, which is the

01:03:02.320 mitochondrial respiration. And also to increase also the mitochondrial pyrobotic carrier, because

01:03:08.560 we might discuss later, this is already dysregulated in people or down-regulated in people who are sedentary.

01:03:15.040 But the thing is like, if you see this next slide, can you see it? Okay. This is what makes the

01:03:20.000 difference in these athletes. So this is a fast twitch muscle fiber and they use glucose. So this

01:03:25.680 is when you're like a high exercise intensities, climbing or running at a high intensity or swimming

01:03:32.560 or whatever the activity you do, you need glucose because glucose is, as you said very well, it yields

01:03:38.400 less ATP, but it does it much faster than the diesel gasoline, which is the fat. But when you use glucose,

01:03:46.160 you're always going to produce pyruvate. The higher the intensity, the more glucose you need,

01:03:51.120 more pyruvate you will need, and the more lactate that you will produce. So that lactate has, as I said

01:03:57.680 earlier, two routes. One route is like it's exported through the MCT force, which is the transport of

01:04:04.720 lactate outside the fast twitch muscle fibers, something that also is trainable, the capacity to export

01:04:10.640 lactate through high intensity exercise. And then it travels to the adjacent slow twitch muscle fibers.

01:04:17.760 We blow up this mitochondria in the slow twitch muscle fibers. This is what will happen. The entrance

01:04:24.000 of that lactate, it goes through another transporter, MCT1 is the same family, but instead of four, it's

01:04:30.000 called MCT1. I mentioned earlier that lactate is converted to pyruvate and acetyl-CoA and goes into the

01:04:36.960 Krebs cycle. So in these well-trained athletes like Pogacar, for example, they have an amazing ability

01:04:44.000 to oxidize the lactate inside mitochondria. At some point, every single human gets to a point that they

01:04:51.040 cannot sustain the effort anymore. But what makes the difference is obviously is like these guys can

01:04:56.480 do 400 watts for a long time versus a mere mortal who can not even do two strokes at 400 watts. So what

01:05:03.520 happens is like when you have a lot of the right MCT1 and mitochondrial function, this lactate is going to

01:05:10.400 increase and accumulate. And it's not lactate per se, but the hydrogen ions associated to lactate

01:05:16.960 elicit an acidosis of the microenvironment of the muscle, which is something that we know and we have

01:05:22.080 learned also from cancer, the famous cancer microenvironment, which is very acidic. And that's going to interfere

01:05:28.080 with different functions in the muscle with both the contractive force and the velocity of the muscle

01:05:33.360 fibers. I'm not saying that this is the cause of fatigue by no means because there are multiple

01:05:37.680 theories and we still try to understand the central fatigue as well and everything probably is

01:05:42.000 interrelated or it must be interrelated. But the bottom line is like when this lactate cannot be oxidized,

01:05:47.920 it is exported to the blood. And this is why you see that people with metabolic syndrome, for example,

01:05:54.160 or type 2 diabetes who are characterized by having a very poor mitochondrial function,

01:05:59.360 they cannot during exercise oxidize this lactate. In the moment they start using glucose, which is

01:06:04.320 very fast also because they don't have the slow twitch muscle fibers mitochondria to use fat,

01:06:09.360 they need to rely on glucose. That's that metabolic reprogramming or partitioning they have.

01:06:14.480 They produce lactate, but they cannot oxidize the lactate. That's why this lactate chooses

01:06:19.920 mandatorily the route of being exported to the blood. And in the blood then it goes to any tissue

01:06:25.040 in the body. So this is what I meant earlier about what is two millimoles versus one millimole.

01:06:30.880 Whereas Pogacar, for example, he oxidizes a lot of this lactate. So by the time that Pogacar saturates

01:06:38.400 this transporter and this mitochondrial capacity to oxidize lactate, it's a tremendous amount of power

01:06:45.040 or output and a tremendous amount of glucose that he puts out. So this is why that one millimole,

01:06:51.040 1.5 millimole in a world-class athlete necessarily represent the same metabolic status of 1.5 or 2

01:06:57.440 millimoles in the blood of a normal person. This is a fantastic tutorial in muscle physiology.

01:07:04.160 And again, this very important distinction between lactate production at the local level and lactate that

01:07:12.960 we measure at the global level. That's the challenge we have. When we are measuring lactate,

01:07:18.240 we cannot impute lactate clearance and lactate production. We can only impute the sum of those.

01:07:25.520 It's originally thought, right, that these athletes, they don't use as much glucose. Well, in fact,

01:07:30.640 the Richard shows and Brooks and his team showed it and others too, that the well-trained athletes,

01:07:36.560 in fact, they use more glucose because they have to. You cannot do 400 watts with a massive amount of

01:07:43.840 carbohydrate oxidation. And this is what we also see in the indirect calorimetry that you see people,

01:07:49.760 recreationals for people with metabolic syndrome, they have like four grams per minute at max

01:07:54.880 carbohydrate oxidation. Whereas elite athletes, they can get to six and a half grams per minute. It's

01:08:00.480 massive amount of glucose and they produce a lot more lactate. But the key, it doesn't

01:08:07.760 show up in the blood. It's the rate of appearance in the blood because it's oxidized in the muscle.

01:08:13.600 So it doesn't show up in the blood. It's the balance of lactate production and lactate oxidation

01:08:19.440 without getting to the blood. And this is what it correlates a lot also with fat oxidation as well

01:08:26.800 in the graphs that I was showing earlier. So one of the things I want to ask you

01:08:31.360 about here that is a bit of a confounder when we do this type of analysis is the carbohydrate content

01:08:37.200 within the diet. So I'll share with you my data, but I've now seen this with multiple people,

01:08:44.400 including one individual who's remarkably fit. God, it's how many years now? 10 years ago,

01:08:49.680 I was on a ketogenic diet for three years. And the very end of that three-year period was when I kind

01:08:55.440 of got back into cycling. At my fittest as a adult cyclist, I was back eating a lot of carbohydrates,

01:09:01.760 but there was about a six to 12 month period when I was still in ketosis, I was kind of getting back

01:09:09.840 into cycling shape. And I do have one VO2 max test from that window of time, probably six months after

01:09:17.440 getting back to cycling and still on ketosis. I've gone back and looked at the data and they're very

01:09:23.040 interesting. What I would observe is maximum fat oxidation was 1.3 grams per minute. And that

01:09:31.440 occurred almost immediately. And it sustained until, so at the time my FTP was about 4.1 watts per kilo.

01:09:41.840 This would have been sustained until about 3.5 watts per kilo. So at 3.5 watts per kilo,

01:09:49.440 I was still oxidizing about 1.2 grams per minute. And then that sort of fell off and glucose became

01:09:57.920 then the dominant fuel source. At the completion of the test, when I was done, you know, when I failed,

01:10:02.640 I was obviously not oxidizing any fat and glucose oxidation was just under six grams per minute,

01:10:10.640 about six grams per minute, about 24 kcal per minute. So I've also seen this with another athlete

01:10:19.120 who's been in ketosis for seven years. He's a very fit cyclist. Actually, he just sent me his data.

01:10:26.160 And it's comparable. In fact, he's much fitter than I was. So his 20 minute FTP test is about 412 watts for

01:10:33.280 20 minutes. And surprisingly, he has decent glycolytic power. So that's the other thing is I never really

01:10:39.680 had good power at the low end because I only cared about time trialing. So it didn't matter how many watts I

01:10:43.920 could hold for two minutes or three minutes. I only cared about one hour. But this guy could still hold

01:10:48.720 1200 watts for 15 seconds. Even for three minutes, he's north of 500 watts, 600 watts. And again, fat

01:10:58.080 oxidation is, you know, 1.5 grams per minute. So it becomes a bit confusing because it would be very

01:11:06.320 difficult to define zone two by maximum fat oxidation. So ketosis is an extreme example. But

01:11:13.840 given how much RQ, respiratory quotient, the ratio of VCO2 to VO2 depends on baseline carbohydrate intake,

01:11:21.360 how do we make the adjustment so that we understand and we're not being misled? Because

01:11:26.960 if you just looked at my data, you would dramatically overestimate my mitochondrial efficiency.

01:11:34.240 Is that a situation where you say, well, actually the lactate, and unfortunately, I don't have

01:11:38.240 lactate data from that test. So I can't tell you what my lactate levels were doing, but it might not

01:11:44.480 be a problem in the Peloton because you're not going to be in ketosis if you're trying to win the Tour de

01:11:49.040 France. But we do see a great degree of carbohydrate and fat variation in the diet amongst people that

01:11:56.800 we're trying to test. How do you make that correction? My humble opinion, what we see in these

01:12:01.840 cases, because I see them all the time too, is that there's an artifact in the metabolic heart.

01:12:08.560 The metabolic heart measures gas exchange and then through the equations says, okay, this person

01:12:14.880 must be burning fat or burning carbohydrates. The equations are calibrated on high carb diets,

01:12:21.280 presumably. Yeah. So the thing is like, as you exercise, no matter what fuel you're using,

01:12:27.120 you keep increasing oxygen consumption. But if you don't have much carbohydrates, you're not going to

01:12:33.040 produce much CO2. So that's going to tweak or mislead my stoichiometric equation because the

01:12:41.040 algorithm is going to think that, oh, whoa, he's using a lot of oxygen and not producing enough CO2.

01:12:47.200 So he's got to be burning a lot of fat. That's when you see fats in north of one gram per minute.

01:12:53.120 Those are fat oxidation. I think they're an artifact. And I see this because three days later,

01:13:00.000 when you change the diet of that person, three days later, that person's fat oxidation might be

01:13:05.600 0.35. So there's no way that the mitochondria adjusts first, like it reflects a very high fat

01:13:12.720 oxidation capacity in someone who we know very well, who is not an elite athlete, whose mitochondrial

01:13:19.120 function is not incredibly high to be able to oxidize so much fat. And in three days,

01:13:25.520 reduces like by three or four times. I attribute this to an artifact of the gas exchange. And this

01:13:32.000 is where looking at lactate, it should give you those parameters. Normally, what I see in these

01:13:38.080 individuals is that you see maximum lactates of two, three millimoles, because simply they don't have

01:13:45.600 carbohydrates. Also the thing where you see that, yeah, my maximum grams per minute of carbohydrates

01:13:51.920 was in the six, but you're in ketosis. So how can you have enough glycogen or glycolytic capacity

01:13:58.560 to elicit such a high carbohydrate production? Even when you're in ketosis, remember my blood glucose

01:14:05.120 is still four to five millimole. I would really like to see this studied because again, even if you're

01:14:12.000 only eating 50 grams of glucose a day, think of how much glycogen you're making from all the glycerol,

01:14:18.240 from all the fat that's being converted to ketone. So, I mean, I think Jeff Volek and Steve Finney have

01:14:24.240 looked at this and when they put people into very, very strict ketosis, but do muscle biopsies,

01:14:30.640 they're still seeing 60% of the glycogen content in the muscle that was there under high carb conditions.

01:14:37.920 I mean, I think my capacity to oxidize five and a half to six grams of glucose per minute was still

01:14:43.440 there. It just took a long time to get there, I think, is the difference. So I guess the question is,

01:14:49.600 if the VCO2 estimation is off because of the stoichiometric coefficients, do you think the VO2

01:14:57.040 estimation is off also? No, I don't think so because, as you said very well, ketones are used for energy

01:15:03.920 purposes. And then we have a third element, which is absolutely key in bioenergetics, which is

01:15:09.520 glutamine. Glutamine is highly expressed and utilized. We have learned that from ICU patients.

01:15:16.880 ICU patients is a great model to study metabolism or stress metabolism. ICU patients, they utilize

01:15:24.960 for wound healing about three times more glucose at rest than what we have. And it's part of the

01:15:31.440 healing process. Glucose is instrumental for cell proliferation, wound healing. And part of it is

01:15:36.960 lactate too as a byproduct in a single molecule. But we see that, and this is a study that we published,

01:15:42.960 looking indirectly at a methodology to look at glycogen. It's a pilot study we deal with the ICU

01:15:48.240 patients. They don't have glycogen. When you say they don't have glycogen, you mean

01:15:53.840 liver glycogen, muscle glycogen, or depleted by how much? Depleted to what level?

01:15:58.400 So let's say that you have 500 grams of glycogen if you have a full high carbohydrate diet. So that

01:16:05.600 might not be the case of someone entering the ICU. First, because they might not be elite athletes,

01:16:10.560 or they might have maybe 300 grams, or they might not have that adaptation to hormone glycogen. So let's

01:16:16.320 say they have 300 grams or so. By the time they get into that condition, the body uses about three

01:16:22.800 times the glucose at rest. Now, an athlete used that same glucose, but at higher intensities,

01:16:30.560 but only for a reduced amount of time, two hours, three hours, four hours. Whereas the ICU patient

01:16:36.160 is 24-7. So eventually, the body is going to run out of glycogen in the muscle, or it's going to be

01:16:42.880 under huge stress. The body has evolutionary mechanisms. This is a wonderful machine,

01:16:48.800 and it needs to continue. So it increases another route, which is glutaminolysis. So glutamine is an

01:16:56.160 excellent source of fuel. It enters directly the mitochondria. We have seen in our publication that

01:17:02.080 we're going to show when we publish it, is that when we inject mitochondria with glutamate,

01:17:08.720 it's incredibly well oxidized.

01:17:10.800 And what's the source of glutamate in these ICU patients? Are they breaking down muscle?

01:17:17.120 This is where cachexia comes into place. We know that pretty much every single ICU patient becomes

01:17:23.120 cachectic or suffers from muscle waste. And this is the syndrome. For ICU muscle waste syndrome,

01:17:29.680 why do they get cachectic or catabolic? And why do they overexpress tremendously levels of glutamine?

01:17:36.480 Because they need it for either enter the Krebs cycle for energy or for gluconeogenesis.

01:17:42.720 So this is one of the things that we learn a lot from ICU. These ICU patients, they have

01:17:48.160 hyperglycemia, yet they're not given them usually because they have hyperglycemia. It's true too that

01:17:54.160 in the acute ICU phase, they also have insulin resistance. But obviously, this hyperglycemia,

01:18:01.760 and ICU doctors historically have seen this. It's like, whoa, this patient has hyperglycemia,

01:18:07.040 poof, off the chart. So obviously, we're not going to give them IVs of glucose. We're going to give

01:18:11.840 more protein and glucose, I mean, and fatias. And in fact, glutamine has shown that increased survival

01:18:17.040 rate in these patients. Where is this hyperglycemia coming from when you do not have glycogen?

01:18:23.280 It comes probably from proteolysis, where you break down protein from your muscles

01:18:30.080 to release glutamine. We would only know that if we understood hepatic glucose stores,

01:18:34.880 because regardless of how much glycogen is in the muscle, it's never going to make its way into

01:18:39.440 circulation because the muscle can't fully dephosphorylate it. So do we have a sense of

01:18:44.800 what the hepatic glycogen content is? Because I can't imagine the body would ever let anything

01:18:50.880 compromise that, given that if the liver can't produce glucose continuously, the brain dies.

01:18:59.840 So it might be that this is true, true, and unrelated, right? It could be that the muscles

01:19:04.720 are depleting glycogen because of high utilization, but the liver through gluconeogenesis has plenty of

01:19:13.520 glucose. That's what's making it into the circulation because of hypercortisolemia, because of

01:19:19.280 other acute phase reactants. And so we have hyperglycemia, but it's all being mediated by the

01:19:24.960 liver, which has no trouble maintaining glycogen levels. And again, from an evolutionary perspective,

01:19:30.080 you much rather err on the side of hyperglycemia than hypoglycemia under a period of stress.

01:19:36.880 Absolutely, necessarily. And that's, I think, what's the source of that gluconeogenesis? It's

01:19:42.240 probably glutamine olysis coming from the muscle. So this is what my hypothesis, right? That those

01:19:47.920 muscles, they eat themselves to feed themselves or to feed the rest of the body.

01:19:51.920 So that would suggest that exercising ICU patients would be important. Getting some

01:19:58.000 load-bearing resistance, even, of course, they're in a bed, but moving their extremities against a load,

01:20:03.600 supplementing with amino acids could actually improve outcomes.

01:20:07.440 Yeah, absolutely. There's a lot of research in this area. My colleague, Paul Wiesmeyer, who

01:20:12.000 used to work here with me at the university, now he's in Duke. He's doing a lot of research and

01:20:17.280 practical work with that. With this, it's like, yeah, this hyperglycemia probably comes from

01:20:21.760 gluconeogenesis. Going back to where we started, yeah, could be that there's a lot of glutamine released,

01:20:28.240 you know, when you're also ketoacidosis state as well, especially in the first phases of that.

01:20:34.640 We know cortisol is very high at first. The same thing that we see in ICU patients, that

01:20:39.600 two main parameters that are predictors of mortality at the ICU is hypercortisol anemia,

01:20:45.760 high cortisol levels, and high lactate levels, right? They both are completely related.

01:20:50.960 Anyways, yeah, I think this is fascinating. There's a great model to understand metabolism,

01:20:55.920 stress metabolism of these patients in the ICU patients. And that's the other thing too, once you

01:21:01.680 exercise, and this is a very important concept for people with type two diabetes, with type one

01:21:06.320 diabetes, and hyperinsulinemia is that you have insulin resistance and you have difficulty to

01:21:13.120 translocate. Therefore, to translocate the GLUT4 transporters to the surface of the muscle,

01:21:19.200 the sarcolemma. And we know that probably the first tissue or organ where diabetes

01:21:26.160 debuts starts is the skeletal muscle. Because about 80% of the carbohydrates that we have,

01:21:32.080 they're oxidizing in skeletal muscle. And because we're at rest, or should be oxidized within the

01:21:37.520 mitochondria of skeletal muscle, that pyruvate. This is what we've done research and seen it clearly.

01:21:43.120 But when you have insulin resistance, you cannot translocate those transporters. Now we have a second

01:21:50.720 way to translocate those transporters that not many people know about, and that's muscle contraction.

01:21:56.400 This is the insulin independent glucose uptake, which also seems to be heavily dependent on fitness.

01:22:03.200 The fittest athletes here require virtually no insulin to translocate glucose into the muscle

01:22:10.560 through the insulin independent pathway. I think we may have even discussed this,

01:22:14.880 I don't know, over dinner one night, but you look at the type one diabetics who are highly,

01:22:20.000 highly active require very little insulin. Exactly. This explains hypoglycemia in these

01:22:27.120 patients shortly after they start exercising. They might have something to eat and they inject

01:22:31.680 themselves with insulin, and there's nothing you can do once you have insulin on board. So that

01:22:36.480 insulin is going to translocate those transporters, and it's going to start bringing insulin inside.

01:22:41.680 I mean, sorry, in the moment you start exercising, you do the same function through contraction of the

01:22:48.000 muscles. So you have two mechanisms acting at the same time, pulling more glucose inside the cells,

01:22:55.200 leading to hypoglycemia. So this is what we learned a lot with persons with people with type 1 diabetes

01:23:00.320 and exercise, and then we can prevent them. So for example, do not inject yourself before exercising,

01:23:06.720 because exercise alone is going to take care of that glucose. But we can take these concepts also with

01:23:12.960 people with type 2 diabetes that they have insulin resistance or pre-type 2 diabetes. It's like,

01:23:18.480 why not exercising right after you eat that carbohydrate that you have? You have insulin

01:23:24.480 resistance already, but when you exercise, you're not going to need that insulin. And yet you can

01:23:30.000 translocate those transporters and you bring glucose levels down. And I'm sure that you see this all the

01:23:35.680 time where your glucose sensors. Yes. I've gone periods of time when I've done incredibly frequent

01:23:42.080 lactate testing. So lactate testing every 30 minutes for a day or something insane like that,

01:23:47.040 which is incredibly expensive and incredibly painful on your fingers. But you learn how much,

01:23:52.160 for example, a meal impacts lactate. So when I wake up in the morning, my resting lactate level varies.

01:24:02.320 I've been tracking this over a period of probably 40 days. So 40 days of tracking. What range do you

01:24:09.600 think my morning resting lactate level has been over a 40 day period in the morning? First thing in the

01:24:15.200 morning? I would say neighborhood of 0.8 to 1.2, 1.3. Pretty good guess. So 0.3 to about 1.1. But that's

01:24:24.800 a pretty big variation and probably median level of about 0.8. Yeah. In the neighborhood of wine,

01:24:32.880 which is normally in the feed individual. Yes. So then what I can do is I can eat a very high carb

01:24:38.640 breakfast and go and do a zone two ride or don't eat anything at all and go and do a zone two ride.

01:24:46.720 Very different lactate performance curve. So the high carb meal raises lactate. So it becomes a bit of an

01:24:53.440 artifact in a way, which now gets me to, we've talked about this at the level of the most precision

01:25:00.480 possible, the way in which I would measure it in a patient. You would measure it in a world-class

01:25:06.320 athlete where we have the ability to do indirect calorimetry and lactate testing. But now I want to

01:25:12.400 talk about it in the way that we train people, normal people. So we've talked about this call it

01:25:19.920 difference between the lactate level that you measure in the blood, which is now heavily influenced

01:25:26.320 by production and clearance. And then we've talked about the gold standard, which would probably be

01:25:31.360 fat oxidation, but even that can be confounded. But let's take off the table, the people who are

01:25:36.960 consuming a high fat, low carbohydrate diet, because that confuses things a bit.

01:25:40.960 If I have a patient and I'm looking at their biometrics and we do a zone two test based on

01:25:47.920 looking at their fat oxidation during an escalated test of part of a VO2 max test.

01:25:53.440 And it comes back that their maximum fat oxidation, which is 0.3 grams per minute occurs

01:26:01.760 at a wattage of 1.5 watts per kilo. That's a pretty average person. And I say, I want that number higher,

01:26:10.160 both the absolute number of fat oxidation, but where it occurs on the graph.

01:26:14.320 Now I want you in a year to be 2.5 watts per kilo. Let's talk about two things. One,

01:26:22.640 how they should train. And that means duration, intensity, frequency, et cetera. And secondly,

01:26:28.640 what we should use as the readout to know we're in the right training zone,

01:26:35.200 given that they won't be able to train daily or weekly or whatever frequency within direct

01:26:39.520 calorimetry. And by the way, let's assume that some people will want to use the point of care

01:26:45.520 lactate meters and some people will not. Let's start with what's our surrogate for training zone,

01:26:51.840 starting with what we knew. So we learned that 1.5 watts per kilo was maximum fat oxidation,

01:26:59.040 but we want to increase that to 2.5. So what metric do you use to train them?

01:27:03.920 Normally what I do is like starting with the metabolic test. I translate that information into

01:27:09.840 whether it's watts or speed or heart rate. All of them, normally they correlate quite well

01:27:16.480 and you can individualize it. There are people that don't have a power meter. Okay. You can do

01:27:20.560 heart rate, for example, or people that just, obviously they run or they walk,

01:27:24.800 can do speed or heart rate as well. Very good surrogate. So that's the first metric, the surrogate.

01:27:30.240 Then it's about, at least from my experience, the three main principles that I've learned over the

01:27:37.360 years and how to apply this. So first is a frequency. Before we go to the frequency and

01:27:43.760 the duration, I do want to go back and ask you another question. We have some patients who don't

01:27:49.040 want to use a lactate meter, either because it's cumbersome or somewhat intimidating. We also add

01:27:54.880 another metric, which is relative perceived exertion, RPE. I'll tell you what my rule of

01:28:00.880 thumb is, but I'd like you to sharpen it, refine it, throw it out, make it better, whatever.

01:28:06.720 I tell patients based on my experience, so I don't know how extrapolatable that is,

01:28:12.320 when I'm in zone two, as confirmed by lactate levels, so call it 1.7 to 1.9 millimole, which is what

01:28:20.400 I target. I can carry out a conversation because I do most of mine on a Wahoo kicker. I put my bike

01:28:26.160 on a Wahoo kicker. I can spend the entire 45 minutes on a phone call, but it's not as comfortable

01:28:32.800 as this discussion here. I'm a little more strained, but if I can't talk, if I feel like I can't talk,

01:28:40.080 I'm too high in the intensity. Do you think that that's a reasonable surrogate for people to use

01:28:45.840 across the spectrum of not particularly fit all the way up to Pogacar?

01:28:51.760 One thousand percent. And I use the same metrics also with people who you mentioned,

01:28:57.120 they don't want to do a lactate meter or they don't have access. I get hundreds of emails about

01:29:03.520 where can I do this test? Or is there anything that I can do? And I agree a hundred percent with

01:29:08.960 everything that we know at the granular cellular level, by injecting fuels and sustrates directly

01:29:15.280 into the mitochondria. We cannot get more cellular level and scientific that the surrogate or the

01:29:20.560 specific section exertion, it works beautifully. I know that people are coming out with different

01:29:25.120 algorithms based on how a variability or DFA, one alpha, et cetera. But honestly, I agree a hundred

01:29:32.160 percent with you. I always tell people, if you can exercise whatever the exercise you do and maintain

01:29:37.520 a conversation like you and I are doing, you're way too easy. You're probably zone one. If you can talk,

01:29:42.640 but it's some form of strain. You can talk for two hours, but we're talking a little bit like that.

01:29:49.920 You're just at that threshold. Put it this way. The other litmus test I tell people is

01:29:54.560 the person on the other end will know you are exercising.

01:29:57.360 Exactly.

01:29:58.080 You will not be able to mask from them that you are exercising.

01:30:01.280 Exactly. And in fact, I have many conference calls with people that I know to be respectful,

01:30:06.480 but I do it on the bike. They call me and I'm on the bike, either outside or in the trainer. And

01:30:11.280 they tell you, you're exercising, right? Because you can feel it. But yet I can maintain a full hour

01:30:16.400 meeting on the bike without bothering the other person because they can understand me.

01:30:20.160 But as I said, if you cross to the point where you cannot maintain that conversation,

01:30:25.360 you need to breathe much faster because you're producing more CO2. And that's probably because

01:30:30.240 you're already transitioning from the slow twitch muscle fibers to the fast twitch muscle fibers,

01:30:34.800 more glycolytic, more lactate, more CO2, more buffering capacity. So it seems old school,

01:30:40.960 but it works beautifully.

01:30:42.640 I agree. And the other thing I do, because I really like people to triangulate and give them

01:30:46.960 a starting point. So if someone has not done a metabolic test yet, and that's usually the case,

01:30:51.760 by the way, is that we're starting with just a zone two training protocol.

01:30:55.680 I also give them some ranges on heart rate. Now here I have found much more variability.

01:31:00.320 So the first thing I say is to do this, you do need to know your maximum heart rate,

01:31:04.720 not your predicted maximum heart rate, but your actual achieved maximum heart rate.

01:31:09.120 In my experience, personally, my zone two is actually at about 78 to 81% of my maximum heart

01:31:18.640 rate. But I know that for less trained people, it's lower. So I tell people a broad range of 70 to 80%

01:31:27.280 of your realized maximum heart rate is a good place to start and then make adjustments based on

01:31:35.280 relative perceived exertion.

01:31:36.640 I agree.

01:31:37.440 What do you know about heart rate?

01:31:39.280 I would agree that I usually also say the same thing somewhere between 70 to 80.

01:31:44.960 That being said, right, if you want to be very precisely-

01:31:47.120 That's a big range.

01:31:47.760 It's a big range, exactly. So you can be at 70, let's say at 1.7 millimoles,

01:31:53.920 and then at 80, you can be at five millimoles. You're completely away from one zone. But as you

01:31:59.200 said, it's a good starting point. And as you very well said, and I agree 100% with you, it's like,

01:32:04.240 yeah, then you tweak it with your perceived exertion. The other thing too, with the heart rate,

01:32:09.520 and this is where the heart rate variability, there are different interpretations. So the modern

01:32:15.600 interpretation of heart variability is the differences between bit to bit. And that's where there are

01:32:20.960 different algorithms. For me, the heart rate variability is more at a broader spectrum,

01:32:27.360 and it's more on the adrenergic activation that you have. So for example, you're fatigued today.

01:32:33.520 First of all, normally, you're going to wake up with your resting heart rate a little bit higher

01:32:38.400 than normally. If your normal heart rate, let's say it's 50, and you're being fatigued,

01:32:43.440 you might wake up with 65. So that alone is a heart rate variability concept. It varies from the norm

01:32:50.880 to one day. So that's a red flag that you might be tired that day. It might not be super sensitive,

01:32:55.840 but it is very sensitive for elite athletes, without a doubt. The second aspect is when you go out there

01:33:01.600 and exercise. As you might see, there are days that you are 130 beats per minute, whatever you think

01:33:08.080 your zone 2 is 130, 138, for example. But some days, it's really hard to get the heart rate. You're

01:33:15.920 already struggling at 110 beats per minute, or 115 beats per minute. Well, that's not the norm.

01:33:21.840 That's another deviation. That's a variability of the heart. So this is what I've been historically used

01:33:27.600 for heart rate variability, which tells me a lot more information. This is what all the athletes also

01:33:33.600 tell you, like, man, my heart rate doesn't get up today. You see on training peaks, you know,

01:33:38.560 you see when someone is fatigued, they do an interval, and they know they're always 180,

01:33:42.800 185, let's say, the lactic threshold. And today, they cannot get up until more than 170.

01:33:48.640 You see in the competition, the first week of the Tour de France, their maximal heart rate,

01:33:53.200 let's say it's 195. Last week, the maximal heart rate is 170. That's what I interpret by heart rate

01:34:00.320 variability. And I know that a lot of people might criticize me, because all that has nothing to do

01:34:04.800 well. No, I think it's macro versus micro. I agree. I read it as macro versus micro.

01:34:09.760 I'll share with you an interesting self-experiment I've done a couple of times. It's not pleasant,

01:34:14.000 but it's interesting. If I take a huge dose of a beta blocker, and the only beta blocker you can do

01:34:20.320 this with, if you have low blood pressure, as I do, you have to be careful. But propranolol

01:34:24.960 is fine, because it really, it disproportionately lowers heart rate, but not blood pressure.

01:34:30.240 But I've done this experiment a few times to test an idea, which is, would taking all of the gas out

01:34:37.760 of my heart rate, allow me to push harder and generate a higher zone two? And it turns out it

01:34:44.960 does. So my zone two is just under three watts per kilo. I really want to talk with you about getting

01:34:50.400 over three watts per kilo. I'm still furious because in July, remember I was at 2.95. I was

01:34:57.040 just kissing on the door of three. I've come back, you know, I'm now at about 2.75 to 2.85. So I've

01:35:03.920 lost a bit. It's aging too. We're going to talk about training in a moment. So, and for me, I'm at

01:35:10.320 that upper end of maximum heart rate. So I'm going to be doing that at about 80, 81% of maximum heart rate.

01:35:16.000 But if I took propranolol, 60 milligrams of a time-release propranolol, I will be able to get

01:35:22.400 over three watts per kilo. And I'll do it at a heart rate of 68% of maximum. But it feels horrible.

01:35:31.520 I feel like I'm going to die. It is the worst feeling in the world. And it's not pain. I don't

01:35:39.200 know how to explain it other than it feels like what it feels like when you're over-trained.

01:35:43.600 It feels like you just can't get moving. It's like an engine that's being taken from 9,000 RPM

01:35:49.840 to 6,000 RPM, but yet somehow is able to generate the horsepower, but it just doesn't feel right.

01:35:56.080 So that's my drug cheating way to get over three watts per kilo, but more to illustrate the point,

01:36:01.680 right? Which is when you put the governor on heart rate, you can get there at a lower heart rate.

01:36:06.880 Subjectively, it's a miserable feeling.

01:36:08.800 Yeah. And this is kind of in a way what happens when you're fatigued, when you don't have enough fuel.

01:36:14.640 Again, going back to like my heart, it doesn't get up today and I'm struggling if you were taking some

01:36:19.840 better blocker. But the thing is that it has to do a lot with fuel. For example, and I experiment

01:36:25.920 this a lot too. I try to understand how this works. So I do maybe intermittent fasting for a few days and I go

01:36:32.800 out there and good at adjusting at that and I cannot do that. I know others can do it and I admire that,

01:36:40.240 but I can see my heart rate right away. When you don't have enough glycogen storages,

01:36:44.960 it's very possible that adrenergic activity is decreased. You need to break down glycogen.

01:36:49.920 And we know that what it takes to break down glycogen is phosphorylase in the muscle, and that's directly

01:36:55.840 regulated by catecholamines. So when there's a decrease in glycogen, this is my hypothesis, right?

01:37:02.240 When there's a decrease in glycogen storages because of the evolutionary mechanisms that humans have,

01:37:08.000 the brain is the boss. The brain says like, I don't care about your legs, but don't use up all

01:37:13.200 the glycogen because you have to give me and the liver has to give me glycogen as well. So I'm not

01:37:18.240 going to shut you down completely of breaking down glycogen, but I'm going to slow you down.

01:37:23.680 So I'm going to release less catecholamines so that you break down less glycogen. The collateral

01:37:29.920 effect of that is the heart because the heart contractility is regulated by catecholamines as

01:37:35.520 well. So this is why using that, my version of heart rate variability, it's quite useful. I've

01:37:41.120 been using it incredibly successfully for 25 years with my athletes, where I see that, hey, your heart

01:37:47.280 is not going up today. And usually it's 185, 190, for example, when you do a lactic threshold,

01:37:52.240 for example, and today it was 170. So tomorrow, take it easy or pile up on glycogen, I mean,

01:37:58.320 on carbohydrates or take an easy day and you see how you're going to be very responsive the next day,

01:38:03.840 the following day. And in fact, that's what happens. I would say 10 out of 10 times, but

01:38:08.240 let's say nine out of 10 times, right? But I do that with myself as well. And I see is also,

01:38:13.600 I work a lot with the head. You think a lot. And the brain uses about 100 to 125 grams of glucose

01:38:20.240 daily. When you go, and I don't know that fact, when you work a lot of hours and thinking and

01:38:25.920 thinking and thinking and stressed, the brain might need a lot more glucose. So that's training

01:38:32.000 your glycogen estranges from the brain, probably, and even from the muscles, because the muscle can

01:38:36.320 release glucose to be utilized as well. Yes. The muscle has phosphorylase and can be degraded the

01:38:42.880 glycogen and that glucose can go to the circulation as well to feed other organs.

01:38:47.360 I didn't realize that we had glucose one phosphatase in the muscle. I thought the

01:38:52.000 muscle glycogen fate was sealed in the muscle. It's possible. There are a few studies. I'm happy

01:38:57.200 to send them to you. I cannot refer them out of memory, but the muscles can also release glucose

01:39:05.040 and export glucose. I assume this is a relatively small amount compared to what the liver is doing.

01:39:10.080 Yeah, absolutely. Exactly. But it's possible too. So those days where I'm thinking a lot and

01:39:15.920 I'm not very stressed and I'm not dieting or anything, I just go out there and I'm dead.

01:39:21.680 And I'm sure that many people listening to this feel the same way. Like what the hell is going on

01:39:26.000 today? I don't have energy at all today. And you will see that your heart rate doesn't get up those

01:39:31.280 days. And you can get to that by just training five hours a week or seven hours a week. And

01:39:36.480 sometimes people say like, look, I cannot be overtrained because I only train five hours a week.

01:39:40.880 Yeah, but you're overworked. That's a big artifact when you're training. That's what most of us aspire

01:39:46.880 to pre-retire before 60, you know, so we can have more time to exercise and less time to work.

01:39:53.680 But yeah, that's what I do this. I take a day off completely. I sleep more. I increase my

01:39:59.200 carbohydrate intake. And the following day I can even break my PR on a climb or something like feel

01:40:05.360 like a million dollars. So resting recovery is key for that. I think this is a very important

01:40:11.120 point. And it's actually something I've only been able to pay attention to in the last year,

01:40:16.320 which is I used to judge my performance by training load. I used to use training peaks when

01:40:23.840 I was training. I don't anymore. But the concepts of acute and chronic training balance, any day that

01:40:28.960 was suboptimal could be explained by training volume in some capacity. But now my training

01:40:35.120 volume is relatively low. It's 10 hours a week of total training. That's both cardio and strength.

01:40:40.000 This is not a lot of training. And yet when I'm under stress work-wise, I'm just doing too much. I

01:40:46.560 don't even use the word stress. It has a real negative connotation to it. I just mean when I'm overworked,

01:40:52.560 when I'm doing too much, my performance, I have to either adjust my parameters for what I deem

01:40:59.040 successful or I just have to cut back on the actual training a little bit to make time for more sleep

01:41:06.720 or more relaxation. So I think that's a very important point that is easily lost. So we've got

01:41:13.200 a very good handle on the metrics we're going to be using. So now let's talk about two scenarios.

01:41:19.840 The first is the person who is new to this type of training. So they've listened to this podcast

01:41:25.680 or they're one of my patients and I've made the case convincingly to them that you really need to

01:41:31.440 do this type of training. I want to come back by the way to a justification for that. So let's explain

01:41:37.920 why high intensity training is not sufficient, but we'll park that for a moment. But they really don't

01:41:42.880 have much of a background in this type of training. Maybe they do some high intensity training. They do

01:41:47.120 some weights, they play some tennis, but they really don't do the sort of steady state sustained

01:41:53.200 cardio that we're talking about. How would you structure a training program in dose, duration,

01:41:58.560 frequency for that individual? And tell me a little bit about the choices that you would make if they're

01:42:04.240 agnostic to running, walking, cycling, rowing, swimming. I have my biases there, but I want to kind

01:42:11.520 of hear what you have to say about it. I want to apologize to many of your audience because

01:42:16.880 I get a lot of emails asking me about these questions and it's hard to keep up.

01:42:21.200 Well, that's why we're doing the podcast. So you don't have to apologize. It's easier to do it this

01:42:24.800 way. I appreciate it this way, but see, I get emails. And before I used to see people here at

01:42:30.000 the university, but now the university don't have these services trying to convince them that the

01:42:35.440 services are important to offer to population. But anyways, I want to apologize because I cannot answer to

01:42:40.800 everybody. I have the three main rules or parameters that I have learned over the years.

01:42:45.520 So one is the duration. We have in mind sometimes that this is like endurance training, long days,

01:42:51.920 like I only have six hours a week or seven hours a week at most to do this type of training or less.

01:42:57.840 There's no way I can do that. It's usually less because they might have six hours a week

01:43:02.080 for total exercise. And we're going to take half of that for strength training.

01:43:06.000 Exactly. Which is very important. As you know, it's where I fail because I should do more of that.

01:43:12.320 And I try to get a little bit more of time to do that. It's not easy, but I aspire really to dial

01:43:17.920 that in. But yeah, you're right. They might have less than six hours and they might think like, well,

01:43:22.240 I'm not an endurance athlete, so you need to do four hours to accomplish this. So therefore,

01:43:27.440 I'm just going to move to do just high intensity and just get out of the way. That's not

01:43:32.080 completely true. You can accomplish very important mitochondrial adaptations and very

01:43:38.240 important metabolic adaptations by exercising one hour. Let's start by the duration. If you try to do

01:43:44.320 that one hour to one hour and a half range, you're on target. Is that total or one setting? Meaning,

01:43:50.960 is it one to one and a half hours per week or does that need to be in one continuous exercise bout?

01:43:57.680 So the frequency that I see is that this type of training ideally needs to be done between three

01:44:04.160 to four days a week, ideally. And how can I know this? I know this because I've seen in the laboratory

01:44:11.280 everything. The person who trains one day at these zones or two days or three days or four days or high

01:44:16.400 intensity, low intensity, and I see the adaptations. How do I see the adaptations? Again, looking at fat

01:44:21.760 oxidation, lactate cleanse capacity, both surrogates of mitochondrial function. I've been identifying the

01:44:27.440 dose of that training. So if you train once a week there, chances are that you're going to deteriorate

01:44:33.840 over time. And especially as we age, something that I see, for example, in high intensity exercisers

01:44:40.560 and bodybuilders, they have a very poor amount of kind of function compared to people who do more,

01:44:47.120 a little bit of everything. So one day a week is not going to work. Two days a week, it might maintain

01:44:52.800 what you have. But if you are new to an exercise program, it might not be enough. Three days a week,

01:45:00.000 now we're starting to see, for sure. Four days a week, now we're talking. Ideally, five days a week

01:45:05.280 or six, but not everybody has, obviously, six days a week to train. But I think that you are a very busy

01:45:10.640 guy. I'm a very busy guy. Try to squeeze four or five days a week, maybe six in the summer, but four

01:45:16.080 to five days is achievable for most individuals and put aside an hour to an hour and a half. So

01:45:22.800 I would say that four days a week is ideal. That's the first principle. The second principle is the

01:45:28.000 duration. Going back to what I was saying, with one hour, maybe Poirazza needs four hours, five hours

01:45:34.640 to keep increasing those huge mitochondria for a long time. But a mere mortal, especially someone who

01:45:41.760 might be pre-diabetic or might be out of fitness or hasn't exercised in a long time or someone who

01:45:47.200 coming from a disease or a mother who just had a baby and has been out of safe for a while, one hour,

01:45:53.600 if you walk or if you run, might be very, very good for you. One hour walk or run, you might have to

01:46:00.080 bring it up. That's part of the plan too. You cannot start off the bat with one hour. You might start by

01:46:05.360 20 minutes, 30 minutes, 40 minutes, increasing it, maybe about an hour. And if you bike, for example,

01:46:10.480 about an hour, 20 minutes, hour and a half, that's what I see that if you do that for four days a

01:46:17.040 week, things are starting to move. Even if you bike on a trainer where you can be much more efficient

01:46:22.640 and you can really get straight to the wattage and stay there. We tell patients, again, it depends

01:46:28.720 where they are in their cycle, but if they're starting out, I mean, we'd be happy if they give us

01:46:32.760 30 minutes, three to four times a week of dedicated exercise. I can't do zone two on the road. I can really

01:46:40.000 only do it on the trainer. I just can't stay at a constant level on the road with starting and

01:46:45.120 stopping and wind and hills and stuff like that. That's a very good point. That's why an hour and

01:46:50.160 a half on the bike, it might actually be one hour or so because you have all these artifacts,

01:46:55.760 but you're right. When you're on the trainer, you isolate everything completely. And what I also

01:46:59.920 recommend is about an hour if you can get there. But again, you know, like, yeah, sure. You might,

01:47:04.720 to me, it's, it's, it feels like a torture sometimes to be an hour on the trainer. I hate

01:47:09.840 it. I like to be outside, but we have had to do it. I do it. I watch a movie or just catch up on

01:47:15.840 work. I have one of those special desks where I can type or read articles or answers and emails.

01:47:21.840 It's a low key activity because again, you know, you're not very sharp to think very intellectually.

01:47:26.880 But yeah, one hour might do the trick. What I've seen is like, yeah, in those people who haven't

01:47:30.640 done much at all, even 30 minutes, 20 minutes might start moving the needle, but eventually

01:47:36.240 it's not enough dose. The body needs more. If you can get to a goal about an hour to an hour and a

01:47:42.480 half, that should really work in my modest opinion, in my experience. So that's the duration. And the

01:47:49.520 third is always the frequency, which we have talked about, which is usually the zone two. That being said,

01:47:54.800 I think that it's also important to stimulate other energy systems like the glycolytic system.

01:48:02.080 And again, continue with the model that we do with elite athletes. People think that elite athletes,

01:48:08.080 whatever the sport are, all they do is high intensity all the time and intervals, intervals.

01:48:13.920 And it's the exact opposite. If you look at the workload of an elite athlete, whether that elite

01:48:19.680 athlete is, especially in individual sports, it's easier to see this, whether it's a triathlete or a

01:48:24.480 cyclist or a marathon runner or a swimmer, a hundred meter swimmer is under a minute.

01:48:29.760 Maximal exercise. If you look at the workload, it's very similar. The majority of the sessions

01:48:35.760 are in the lower intensity. They're not intervals, intervals, intervals. And I always say, we cannot be

01:48:40.720 so naive to think that the best coaches and athletes in the world haven't figured this out when they're

01:48:45.440 always trying new things and they want to try the cutting edge things. Obviously they have said,

01:48:50.720 oh, our sport is swimming under a minute. All we need to do is like intervals, intervals,

01:48:55.920 intervals, intervals. Well, if you look at what swimmers do, they train. And if you ask Michael Phelps,

01:49:01.840 hours and hours and hours and hours and hours, because if you can travel through the competition

01:49:07.440 in that under a minute, what a slightly better function to clear lactate, even if it's one millimole

01:49:14.320 or less, the muscle contractual force might be improved. So all the hours and hours and hours

01:49:21.600 might be that just to improve a fraction of a second. But anyway, so this is what I'm seeing that

01:49:26.240 these concepts of glycolytic capacity and high intensity training, they're necessary, but they're

01:49:32.400 not what the elite athletes do. The elite athletes have the best metabolic function of any humans.

01:49:39.600 Why not try to imitate their philosophy of exercise? And so just to come back to the

01:49:45.440 frequency duration question, I think the answer to the following question is going to be the more

01:49:51.280 frequent training sessions. But if you compared four training regimens that were four hours a week each,

01:49:57.280 one of them would be four 60 minute sessions. One of them would be three 80 minute sessions. One of them

01:50:05.760 would be two two hour sessions. And then one of them would be one four hour session. So it's the

01:50:10.720 same total volume and notwithstanding the brain damage of one four hour session. Is it safe to say

01:50:16.800 that the four 60 minute sessions, because it's a higher frequency would be the optimal one there?

01:50:23.280 I would say so. I think from my experience that it might be better is the frequency. It's like if you

01:50:28.560 take a medication, if you take a medication twice the dose and only three days a week might not work as

01:50:35.040 well as if you take the right dose every day. Because at the end of the day, we're talking about

01:50:39.680 the whole exercise as medicine, right? How do we prescribe that? What's the dose? What's the

01:50:44.560 frequency? I'm assuming that you will have to take it as many days as possible. I would say that it's

01:50:50.480 better to do that. That being said, obviously, if you have the weekend and you have the possibility,

01:50:56.160 which I don't have to do three hours, go ahead. And another thing I wanted to point out is that

01:51:02.320 for many people, they need that adrenaline for training. So other people don't care.

01:51:07.040 Other people say, wow, I love this. I don't like to kill myself into high intensity,

01:51:11.440 but I think you need to do some high intensity, right? At some point.

01:51:14.880 I want to talk about that. So how do we bring in the other energy systems of the four pillars

01:51:19.440 of exercise in my world? Stability, strength, low end aerobic, which I describe really as,

01:51:27.120 talk about it as kind of mitochondrial efficiency, and then high end aerobic, which is peak aerobic

01:51:32.240 capacity slash anaerobic performance. So anaerobic power, peak aerobic, low end aerobic mitochondrial

01:51:40.240 efficiency, strength, stability. Of those four, I, for some reason, struggle to make the time

01:51:47.360 for the peak aerobic in part because one, it's the least enjoyable. If we're going to be brutally

01:51:53.760 honest, if you're doing it right, it hurts the most. It's also no longer as relevant because I don't

01:51:59.440 compete at anything. I actually really enjoyed that type of training when I competed because you have

01:52:05.040 to spend time in that energy system and you see the rewards of 60 minutes of repeating two minute

01:52:10.880 intervals or something like that. So if we're really talking about this from the lens of health,

01:52:16.080 maximizing health, the data are unambiguous that VO2 max is highly correlated with longevity.

01:52:24.320 There are not many variables that are more strongly correlated, but the levels don't have

01:52:28.480 to be that high. Pogacar's VO2 max is probably 85. It's probably in the 80s, at least in terms of

01:52:35.600 milliliters per minute per kilogram. But someone my age to be considered absolutely elite, which means the

01:52:43.440 top 2.5 to 2.7% of the population, which carries with it a five-fold reduction in risk to the bottom

01:52:50.960 25% of the population. My VO2 max requirement is about 50 to 53 milliliters per minute per kilogram.

01:53:00.480 So the question is, can I use that as the gauge for how much high-intensity training I need to do,

01:53:06.800 basically just enough to make sure I maintain that VO2 max? Or do you think about it in a different way?

01:53:13.280 Well, I think about it more by energetics, energy systems. Ultimately, and we know that longevity

01:53:20.160 is also high-related with mitochondrial function and metabolic health. I think that more and more,

01:53:26.080 and this is what you see in so many fields in medicine nowadays, everybody is stumbling

01:53:31.440 upon mitochondria. So there's an aging process where we lose mitochondrial function. And there's

01:53:37.120 like a sedentary component where we lose mitochondrial function. I wish that we could have a medication,

01:53:43.680 a pill that you could take it and increase the mitochondrial function, because it would increase

01:53:47.600 metabolic health and longevity. But the only medication that we know is exercise. Within exercise,

01:53:53.440 the dose that we see that improves the most, and also is sustainable in the long-term,

01:53:59.200 which is another important concept. Very high-intensity training is not sustainable. Very

01:54:04.800 extreme diets are not sustainable. If you combine both, it's even worse. And this is what a lot of

01:54:09.840 people are doing together, but you need to have some sustainability. But this is important to improve

01:54:14.560 that mitochondrial function. But going back to high-intensity, I think it's necessary because

01:54:20.240 we also lose glycolytic capacity as we age, and it's important to stimulate it. As you very well said,

01:54:25.840 for all of us who are not competing, I couldn't care less about being super high-intensity. I'm

01:54:32.160 not competing. But that said, I want to have also my adrenaline rush.

01:54:35.280 But how much does it feed into it? So for example, if, and I've often thought about this now,

01:54:40.320 as I just want to make sure my zone two is above three watts per kilo, would I be better off taking

01:54:46.400 that extra training? If I have one additional training session per week, should I make it an

01:54:50.960 additional zone two workout? I do four now. Should I be doing a fifth one or should I be taking that

01:54:58.480 fifth one and doing a VO2 max protocol? And that's what we'll typically prescribe to our patients is a

01:55:04.240 four by four protocol of highest intensity sustained for four minutes, followed by four minutes of

01:55:10.000 recovery, and then repeat that four or five, six times. When you put a warmup and cool down on either

01:55:16.240 end of that, that's a little over an hour. Would you spend that hour doing that in an effort to make

01:55:21.920 your zone two even better? Or would you just do an extra hour of zone two?

01:55:27.120 I agree that if you have a fifth day, you can convert it into any type of high-intensity

01:55:32.800 session, structured. What I can tell people also, hey, you're a cyclist or a runner,

01:55:37.760 you want to go with your friends on the clock ride. That's your group ride.

01:55:40.480 The group ride, go ahead and boom, go at it. Or if you don't have that possibility,

01:55:45.280 this is my situation, for example, where I don't have the time to train more than an hour and a

01:55:50.240 half, usually two hours max. So what I do almost on every session, I do my zone two. So it's clean.

01:55:56.960 And at the end, that's when I do a very high intensity interval.

01:56:00.560 Tell me the duration. So if you did an hour of zone two.

01:56:03.360 Yeah. So I do usually, let's say an hour and a half.

01:56:06.160 So you'll do an hour and a half of zone two, three or four times a week.

01:56:09.280 I shoot for four or five. Not all the time is easy, but yeah, I shoot for five and I try to be

01:56:14.320 strict on that. But, and unfortunately that where I live, I live more in a highlands area. So you have

01:56:20.480 to go up. So the last part, I just go at it. Sometimes you find another cyclist and you just

01:56:25.760 compete, you know, to see who's the fastest in that short climb. But I tried to do like a good

01:56:30.880 five minute interval, roughly. I arrive home like, man, I kicked my ass today. This kicked my ass today.

01:56:38.160 Or sometimes you try it and you don't have the energy. As I mentioned earlier, oh my gosh,

01:56:42.480 I can barely move the pedals today. I just quit and go home. But when I feel fresh,

01:56:47.920 I stimulate that glycolytic system. What we know well, too, is that that increases the

01:56:52.880 mitochondrial function. It takes months or years increasing the glycolytic system. It takes much,

01:56:59.200 much less amount of time. You can do that in weeks or months. If you stimulate on a regular base,

01:57:04.960 two days a week or three days a week, at the end of that zone two, that's where you can target both

01:57:11.120 energy systems, the oxidative mitochondrial system and the glycolytic energy system.

01:57:16.640 We don't blunt the benefit we had from the zone two, if we immediately follow it with the zone five.

01:57:22.640 No, because that's done, right? What do you see? It's like if you do the same things in the middle.

01:57:26.800 But you don't want to do the reverse order. You don't want to start with the high intensity.

01:57:30.160 Exactly. One of the things like, because you start having all these hormonal responses,

01:57:33.600 and also you see you have high lactate levels in the blood. And what we know very well is like

01:57:37.920 lactate inhibits lipolysis. So if you have a high interval in the middle or the beginning,

01:57:44.240 and you don't clear lactate very well, you might have high lactate levels for a while,

01:57:50.000 and it's going to inhibit lipolysis. Also, another study we have under review,

01:57:54.880 lactate at the autocrine level decreases the activity of CPT1 and CPT2. So it interferes with

01:58:01.840 the transport of fatty acids as well. So that's where like, if you do all this, you might change

01:58:07.440 things. You have high corticillinemia as well. I'm glad you raised that because I explain this to

01:58:12.560 patients when they say, I went out and did a two hour ride today. And it showed me that I spent 45

01:58:19.840 of those minutes, 45 of those 120 minutes were in zone two. So I did 45 minutes of zone two. And I

01:58:24.720 say, no, you didn't really do it because you were going up and down and up and down and up and down.

01:58:29.120 And so that's not the same as spending 45 minutes in the dedicated energy system.

01:58:34.320 Right. I mean, when I look at the training peaks, you see the elite athletes, they're like

01:58:39.520 more power output and heart rate. This is like goes together. Incredible. Whereas, yeah, you're

01:58:44.880 right. Up and down and down, the average might be zone two, but actually you're between oscillating

01:58:49.600 zone one, zone three, zone four all the time. So if you don't mind sharing in watts per kilo,

01:58:54.400 what is your zone two in Colorado where you're at altitude? I don't look so much into this. I have

01:59:01.120 done so many tests in my life. Since I was 15 years old, I was using a heart rate monitor talking

01:59:08.080 about 1986 when the first heart monitors came out. What you're getting at is you don't like to have a

01:59:14.080 lot of data when you're doing it. You're going off RPE and you're not looking at your power meter

01:59:19.040 or a heart rate monitor and you're not poking your finger when you're done. I do it here and there

01:59:23.360 because I still want to look at this and I do metabolic testing here and there, but I've done so much

01:59:28.400 on me since I was 15 years old and I was obsessed by this. I got to a point that I know my body quite

01:59:34.800 well. I can just go by the sensations and, but here and there I double check. But it's hard for you to

01:59:40.720 then get at what I've observed. The few times I've tried to do my zone two at altitude, like in Colorado,

01:59:47.920 it's a enormous discount. I feel like it's a 20% discount at altitude. Yeah. Mine's around 2.5,

01:59:54.880 2.8, something like that watts per kilogram when I do it. At sea level, you'd be over three probably

02:00:01.840 based on what I experienced it going in the reverse direction. Yeah. I would say roughly.

02:00:06.080 And one thing that I'm very proud of is that I have been doing, because I do sporadically this

02:00:11.280 testing and I know my PRs because that's another thing. We have climbs here and one day I go for this

02:00:16.080 climb and I go full out on that climb, right? I'm 50 now. I have the same metabolic parameters

02:00:23.040 than when I was 40. To me, I'm very proud of this. And when you say parameters, you don't mean

02:00:28.240 times up the climbs. Which parameters are the same? Lactating power output, VO2. I look at time

02:00:35.920 as well. The PR that I had, it was similar. What's your VO2 max now? So my VO2 max now is

02:00:42.480 four liters per minute. So that's about 51, 52. You could easily raise that if you lost three kilos,

02:00:50.320 which you could probably do. Yeah, yeah, yeah. Yeah. And the thing is because I've,

02:00:53.360 obviously when I was a cyclist, I was 141, 143 pounds. So my VO2 was... And you were probably,

02:01:00.560 your VO2 was five and a half liters or something. It was 76.7. Let me see. It was 4.5, I believe.

02:01:07.840 It was about 4.8, something like that. 30 years later, I have decreased only about 0.5, 0.7,

02:01:15.520 which, well, I'm really happy about that because I'm not training like I did. But this is one of

02:01:21.040 the parameters. But in a decade, I haven't decreased my parameters. So this is to me,

02:01:27.120 it's a proving point to myself at least, that doing this routine, it helps to maintain

02:01:33.440 that metabolic health that you had a decade ago. Now, can you do this 10 more years and when I turn 60?

02:01:41.280 I don't know. But what I know is that from others, I'm seeing it. So I see a typical person

02:01:47.920 who just retired, as I discussed earlier, aspired to pre-retire at the age of 60 or a little bit

02:01:54.000 before. And these are like people like us who are struggling to squeeze in time, do five hours here,

02:01:59.920 six hours a week here, or 10. But then they have the whole time in the world, sleeping,

02:02:05.520 they're not overworked, they can exercise. It's unbelievable and super inspiring how much they

02:02:13.280 improve in their 60s. I've seen people in their 70s with the metabolic parameters of people active,

02:02:22.320 morally active, in their 30s. World champion in the cycling was 81, in the category of 80 to 85,

02:02:30.320 believe me there's a category of that. Metabolic parameters were those of someone in their 30s.

02:02:35.760 Healthy, active. So this is incredibly inspiring. Then I think that we are rewriting what's been

02:02:42.800 taught to us in the books. Was that person an elite athlete? Were they a professional athlete

02:02:48.000 in their 20s and 30s? Never. And this is what struck me. He was a smoker, hypertensive, and he started

02:02:55.760 cycling because he needed to change his lifestyle in his 40s. Because that's the same question like,

02:03:00.880 wow, you must have been doing this all your life. I'm like, no. I started riding my bike when I was

02:03:04.960 in my 40s. I was a smoker, I was heavy, I was hypertensive, like what? So it's incredible 40 years

02:03:12.080 later. What I take away from that as well is the benefits and the importance of compounding. You see,

02:03:18.800 you alluded to it earlier, and I think the listener could be forgiven if they missed this point. You can

02:03:24.640 make relatively quick changes in your glycolytic efficiency. You can take an untrained person with

02:03:31.120 a VO2 max of 20 mil per gig per minute, and you could take them from 20 to 30 in a period of months

02:03:39.600 with the right amount of training. A 50% improvement in a few months. It's very difficult to see a 50%

02:03:47.200 improvement in mitochondrial function in a few months. You've already made this point, but I just

02:03:52.800 want to restate it because it's important to set expectations, and it speaks to why this level of

02:03:58.880 training should be thought of in the same way that you think of accumulating wealth. It's day in and day

02:04:04.960 out, day in and day out, small compounded gains over years and years and years is why a 40-year-old

02:04:14.240 overweight smoker can become a world champion at 80 because he probably never once again got out of

02:04:21.680 shape in that 40 years. Absolutely, and this is incredibly inspiring. When I see these people in

02:04:26.800 their 60s just retired, and they come to do their first test, and one year later they come back,

02:04:32.640 it gives me the goosebumps because it is like, oh my gosh, I'm 64, I feel as strong as when I was in

02:04:41.200 my 30s. And like, oh, and of course no medications, really good state of mind, which is absolutely key for

02:04:48.880 longevity. They eat in moderation, that they can have a little bit of everything, which is also in my modest

02:04:55.280 opinion, it's part of the enjoyment of life, eating what you like in moderation as well. So it's an

02:05:01.920 incredibly inspiring. In a way, we're rewriting what we've been thought for years, that once you turn

02:05:08.000 40, everything is going down. You can really, really change. And again, you know, you own your

02:05:13.920 own body, and you can really take ownership of that and improve it at any age. You mentioned drugs. I

02:05:19.760 want to talk about one drug in particular, and maybe some supplements. You and I have spoken so much

02:05:24.400 about this, and myself and another person are committed to funding a study that we're going to be doing

02:05:29.760 once we get through kind of the backlog of COVID issues at the university. The question really

02:05:35.680 arises around the use of metformin, and whether or not there's a true impairment of mitochondrial

02:05:42.240 function, or whether the elevated lactate levels we see in patients taking metformin is an artifact of

02:05:49.360 the drug itself, but says nothing of the mitochondrial function. Do you have any more insight into this

02:05:55.760 question that we struggle with greatly because we have some patients who take metformin who receive

02:06:01.280 much benefit from taking metformin, but it makes it confusing to interpret their zone two data. And

02:06:09.200 it makes me ask the question, in those patients, it's maybe less relevant, but now it becomes relevant

02:06:14.080 when we think about using metformin as a gyroprotective agent, an agent to enhance longevity.

02:06:19.440 We need a lot of research on that, I think, to understand this better. Definitely, it seems to

02:06:24.720 work in many patients. Obviously, for those ones in the pre-diabetic first stage diabetes,

02:06:30.160 it's a very good medication. It's been used for a long time with good results. But how about the

02:06:35.280 long-term results? We know that metformin inhibits complex one, which is key for mitochondrial function

02:06:42.160 in the lectoon transport chain. We don't know the long-term effects of metformin in longevity. This is

02:06:48.320 where I think that we need more information as well. We see someone showing up with lactate of 3.5

02:06:54.400 millimoles at rest. And the first thing I ask is like, are you on metformin? And many times I say,

02:06:59.840 yes. And I'm sure you see the same thing, right? And I say, wow, it's definitely an artifact. And why

02:07:04.720 do you see at rest 3.5 millimoles or 3 millimoles of lactate? They're fat oxidation commensurately

02:07:11.600 suppressed because when you metabolically test them on the cart, do you see in that individual

02:07:18.400 a very, very low fat oxidation? If not, it might suggest that that lactate level of 2 or 3 millimole

02:07:25.600 is an artifact, but doesn't really speak to what's happening in the mitochondria, right?

02:07:29.120 I haven't seen people taking metformin as medication for longevity, for example, or for

02:07:34.960 health. What I see people on metformin are already clinical patients.

02:07:38.320 So of course they're low. Yeah. So they're taking metformin in the first

02:07:42.400 place because of their clinical condition, which is driven by a mitochondrial impairment

02:07:46.960 or dysfunction. It's difficult to discern, but I mean, I'm sure you have more experience

02:07:51.520 of people taking metformin. We do. But that's why this study that

02:07:55.280 we're eventually going to get around to doing is going to be so important because it will answer

02:07:59.440 this question directly. We can do it with a muscle biopsis. And as you say, does it really mess up

02:08:05.120 with the whole mitochondrial function or even like the mitochondrial function overall overwrite

02:08:11.040 that inhibition of complex one and overwrite other pathways? I don't think we know the answer to that.

02:08:16.800 Do you have an insight into any other supplements, no shortage of supplements that are out there

02:08:23.120 that are touted as longevity boosting agents and mitochondrial health agents? So the most talked

02:08:29.600 about of all of these, I think is the precursors to NAD. Most common of these would be NR or NMN,

02:08:37.440 both of which are pretty clear that they are precursors to NAD. There's certainly some debate

02:08:42.960 about how clinically relevant it is. Do you have a point of view on whether or not taking a supplement

02:08:49.920 that boosts NAD at least in the plasma? I still don't know how well it's boosting NAD in the cell,

02:08:56.800 but do you have a sense of if that is beneficial to the mitochondria, both theoretically, but more

02:09:02.480 importantly, experimentally? I don't think we have the answer, but I think we need to be cautious

02:09:06.880 about how we interpret this data. It's definitely been shown multiple times that NAD levels at the

02:09:13.920 cellular level and even mitochondrial level are decreased with aging. Therefore, the whole thing,

02:09:18.640 whoa, if it's low, let's take it. But it's not only NAD. If you look at so many metabolites

02:09:24.960 at the cellular level and mitochondrial level, they're down-regulated with aging. The question

02:09:29.440 is why are they down-regulated? It's because mitochondria per se to start out with is down-regulated,

02:09:36.480 so it doesn't need so much NAD because it cannot take it, or other supplements, or other metabolites.

02:09:42.240 This is at least how I think of. NAD, as we mentioned earlier, is very important in glycolysis.

02:09:48.480 And redox status to maintain redox. And it's very important in the visceral 3-phosphate 2-3-biphosphoglycerate

02:09:56.240 phosphate, where NAD is utilized to convert glycolysis 3-phosphate to 2-3-phosphoglycerate,

02:10:02.480 but it's depleted. And this is why the only thing that rescues that is lactate, right? As we mentioned.

02:10:07.600 Now, taking NAD, is that going to increase longevity? I don't think so. That's my opinion,

02:10:13.600 because longevity is not just one supplement, or two, or three, or four, or five. It's a compendium

02:10:19.120 on an incredible amount of things that happen at the cellular level. And I don't think that one

02:10:23.600 supplement. I remember those days where resveratrol was the thing for longevity. And everybody was,

02:10:30.400 not everybody, a lot of people were buying resveratrol. And there are studies with mice showing that

02:10:34.800 increased 50% longevity in mice, so there are four less do-it in humans. Well, as you probably know,

02:10:40.960 a lot of people started to take in resveratrol when they were 50 and they're dead now. It

02:10:45.280 doesn't increase longevity in humans. The data in the mice, we can debate the

02:10:50.000 merits of that. I want to ask you about a theoretical risk though. You kind of alluded to it. Isn't there

02:10:54.560 a scenario under which too much NAD could be harmful? I don't know if this study has been done, but if you

02:11:01.840 took cancer patients or patients who had tumors that were undiagnosed and gave them, if you doubled their NAD

02:11:09.600 levels, wouldn't you actually favor the tumor's metabolism? Well, in fact, we have done that

02:11:17.440 pilot study with mice. The whole thing is like looking at, and my area of research in cancer is

02:11:22.560 cancer metabolism. And we know that glycolysis is key for cancer and NAD is absolutely indispensable to

02:11:30.320 feed that glycolysis. The question is like, as you said, would NAD increase that glycolytic rate or

02:11:39.360 glycolytic flux? Therefore, would be favoring more cancer phenotype? So what we did, we haven't published

02:11:47.440 that. It's a pilot study. We just were curious about it. And we had two mice. We have NN of eight mice,

02:11:54.800 four and four. So what we did is we transfected tumors, triple negative breast cancer. It's very

02:12:00.240 aggressive and it grows very, very fast. One group, we give them just water. And the other group,

02:12:06.720 nicotinamide ribocyte, which is the NAD precursor. Because NAD, obviously, as you know, you cannot

02:12:12.640 take it. You need to take the precursor. And we observed the tumor growth over 23 days. After that,

02:12:18.880 the IRB at the university, because you cannot have animals with high tumors. So it was a flank tumor

02:12:26.160 and you need to harvest them. We were measuring every five days, the tumor growth. And we saw in

02:12:32.400 these animals that there was about 15% increase in tumor growth in the NAD group.

02:12:38.000 You saw that difference with only four mice in each group?

02:12:41.680 It's four and four, but all consistent. We had statistical significance even with a small four.

02:12:47.920 I mean, there was no cross results. All the four mice, they grew cancer at a higher rate in the NAD

02:12:54.960 than the control group. Again, that's where like, obviously, this is not like publishable.

02:13:00.640 Is that a study you'll repeat at a sufficiently powered size?

02:13:04.960 I would love to. This is why we just did this pilot study. We had, because we have many mice and say,

02:13:10.240 hey, let's leave it a shot. And let's see, because there's a lot of hype of the NAD. And

02:13:14.400 we saw this. Love to do it at a much higher level because my question, which might be a disruptive

02:13:21.840 question is like, what if you have a small tumor that you're unaware of, like in the pancreas or in

02:13:27.760 the colon or in the lung? Could NAD over time, day after day after day, could favor that glycolytic

02:13:35.920 flux to that tumor and increase the growth? I've never looked because it just kind of

02:13:40.240 occurred to me when you had that slide up earlier, earlier, and you showed the mitochondrial slide.

02:13:44.720 It occurred to me that you have that lactate escape from the tumor. Hey, this would feed it.

02:13:48.960 But has anybody in the literature examined this question? It seems like a very

02:13:53.040 reasonable question to ask. There are a couple of studies. I think once a review is more at the

02:13:58.160 conceptual level. And this is what got me thinking like, yeah, this is something that

02:14:02.640 for us working in cancer metabolism, we look into this. Obviously, one of the things that

02:14:08.400 we have shown is that lactate is an oncometabolite. Lactate, we have shown, have a first paper and we

02:14:13.920 have like a good six, seven papers more to come, working hard for three years looking into this.

02:14:20.000 But we saw that lactate regulates genetic expression of the most important genes in breast cancer.

02:14:26.880 We're seeing the same thing now with lung cancer. And lactate, as we keep talking about this,

02:14:31.920 is the mandatory byproduct of glycolysis. And as Warburg saw in 1923, the characteristic of

02:14:38.720 cancer cells, or most cancer cells, is the high glycolytic flux. But what struck Warburg was not

02:14:44.160 the glucose itself, it was the lactate production. So anyways, we are showing that it's an oncometabolite.

02:14:51.520 So if you have a high glycolytic rate in a cell, you're going to produce a lot of lactate.

02:14:56.400 You cannot clear that lactate. It's going to drive cell growth and proliferation as we're seeing.

02:15:01.920 And in fact, we're now blocking lactate production, both through genetic engineering,

02:15:07.760 as well as DCA, for example. And we're seeing that cancer growth and proliferation completely stops

02:15:15.280 within hours. Now that poses an interesting dilemma, which is exercise would increase your capacity

02:15:23.760 for clearing lactate in the long-term, but in the short-term raises lactate. So it begs the question,

02:15:30.480 in a cancer patient specifically, what's the net impact of exercise?

02:15:35.600 This is what we're working on, the hypothesis, you know, with my colleague, George Brooks.

02:15:40.000 He's shown that acute response to lactate, it increases overexpressions of about 600 and

02:15:47.680 something genes. I forgot right now. All these genes are involved in cellular homeostasis and

02:15:52.320 in the benefits of exercise. We know very, very well through his work that lactate is a signaling molecule.

02:15:58.880 Now, the question is like, we know this at an acute exposure, which is exercise. You do exercise,

02:16:04.960 boom, boom, boom, you're out. But cancer doesn't do that. Cancer accumulates lactate,

02:16:10.960 and it keeps accumulating. This is the main responsible for the tumor microenvironment,

02:16:15.600 which is acidic. And the more acidic the tumor microenvironment, the more metastatic the cancer

02:16:21.360 is and the more aggressive. Like the more glycolytic the tumor is, and this is very well documented,

02:16:27.040 the more glycolytic the tumor is, the more aggressive it is. And the more lactogenic,

02:16:31.440 that is more lactate, the tumor produces, the more aggressive it is. Now, why is that lactate

02:16:38.240 accumulating? That's what we need to try to find out. But we know that that is not acute anymore.

02:16:42.960 It's chronic exposure to lactate. Can exercise counteract that? When we see that exercise might

02:16:49.840 be beneficial for many patients. But again, going back to the right intensity, we know particles which are

02:16:56.480 exosomes. There are micro vesicles in the body. They remain responsible for metastasis. We have

02:17:02.640 seen that, and this is another publication we're going to have in breast cancer cells and lung cancer

02:17:07.120 cells. We are looking at the protein content and the microRNAs of those exosomes released by these

02:17:12.960 cancer cells. It's incredible the information that they have. If you were to genetically engineer

02:17:19.760 a molecule, they can, you know, inject it into a tissue and transform into cancer, you would

02:17:25.920 replicate an exosome. It has all the components needed. On the other side, muscles also release

02:17:32.800 exosomes. And this could be one of the benefits of exercise as an organ in the crosstalk between

02:17:41.040 skeletal muscle and many organs. We know that if you have very good muscle health, your health

02:17:47.920 overall, your metabolic health is going to be good. Could you be releasing great exosomes? They're

02:17:52.720 very pro-oxidative, which counteract the glycolytic phenotype of cancer. And could those exosomes travel

02:17:59.040 directly to the cancer cells and counteract that and penetrate inside the cancer cells and transform

02:18:06.720 the glycolytic phenotype of the cancer cells into more oxidative phenotype and keep cancer at bay?

02:18:12.960 We don't know yet. We're suspecting that we're scratching the surface of something that potentially

02:18:18.320 could be a very interesting thing to understand better the effects of exercise as well as neuro

02:18:23.800 therapeutics. The deeper I go in the rabbit hole into all things that relate to longevity, the more

02:18:31.360 convinced I am that if you're going to rank order things, if you were forced to rank order things,

02:18:35.840 there's nothing that ranks above exercise as the single most potent tool or agent we have to impact

02:18:43.600 longevity. And yet, paradoxically, in the acute setting, exercise seems to do everything incorrectly.

02:18:50.880 In the very short acute setting, if you look at it in that narrow context, exercise does not appear to

02:18:57.600 be geoprotective. But of course, when you look at the chronic impacts of exercise and what's taking place

02:19:04.400 after the bouts of exercise, the data seem undeniable. I want to kind of pivot from exercise

02:19:10.320 a bit into a subset of that, which is something you published this year in long COVID patients.

02:19:16.960 So we'll link to the study so people can see it. But you demonstrated that in people with long COVID,

02:19:24.240 even previously healthy people, they basically, from a mitochondrial standpoint,

02:19:29.680 end up looking like people with type 2 diabetes when they're done in terms of fat oxidation,

02:19:35.520 lactate production. So first question for you is what fraction of patients recovering from COVID

02:19:42.240 do you believe are susceptible to that phenotype?

02:19:45.760 Everything is started by National Jewish Hospital is probably, as you know, is with Mayo Clinic competing

02:19:51.840 for the top one pulmonology hospital in the country. You have these people with long COVID who are

02:19:59.040 struggling. They go up the stairs and they can't breathe. So the first thing they do is they go

02:20:03.840 to different doctors and they end up going to this top hospital. So they do a pulmonary function

02:20:09.600 test and it's completely normal. Then they, okay, the next species is because COVID also

02:20:15.360 affects the cardiac muscles. Let's look at the cardio function. It's completely normal.

02:20:19.920 They're very good at this hospital where they do metabolic testing. They do a CPET testing. That's

02:20:25.920 how I call it medically, right? Physiological testing. And they even do lactate. I've been interacting

02:20:30.960 with them a few times. So they do lactate as well. So they contacted me and said,

02:20:36.080 Inigo, look, we've seen these patients. We have 50. 25 of them, they had previously underlying

02:20:42.160 conditions. The other 25, they were normal people. And in fact, most of them, they were morally active.

02:20:49.600 Some of them, they were doing marathons, triathlons. The average is 50. So they're not

02:20:55.040 very old either. But their pulmonary function is completely normal and cardiac function is completely

02:21:00.240 normal. So we suspected there's some metabolic issue here. So they send me all the information,

02:21:05.200 the raw information. And I applied the methodology that we've been discussing,

02:21:09.520 looking at fat oxidation and lactate production as a surrogate for metabolic function and metabolic

02:21:16.240 flexibility and mitochondrial function. And I was shocked because they were significantly worse

02:21:22.640 than people with type 2 diabetes and metabolic syndrome, which could explain why these people

02:21:28.480 cannot go up the stairs and where before they were doing marathons. Now, what are the mechanisms?

02:21:35.040 We know that viruses, multiple viruses are known to hijack mitochondria for their own benefit,

02:21:41.600 for reproduction. Could COVID do the same thing? We are suspecting it. And we're trying to understand

02:21:47.760 that at a more cellular level. Now, unfortunately, the majority of this long COVID, because as you know,

02:21:55.600 there are people with long COVID syndromes that within weeks, months, they improve, they go back to

02:22:00.640 normal. But there are a handful of people that I'm assuming they're going to be growing, that after one

02:22:06.800 year, they haven't improved a bit. This is the concern. Like, can we use exercise as a therapeutic

02:22:12.880 way to stimulate mitochondrial function, if in fact, there's a mitochondrial dysfunction, which is severe,

02:22:18.960 because if that's the situation, it's going to expose these patients to multiple diseases. So this is an area of concern.

02:22:26.240 And this isn't talked about as much as what I think people initially spoke about here, which is

02:22:33.120 basically myocarditis. Now, of course, we know that the risk of myocarditis is actually

02:22:38.800 much higher in young males through the Moderna vaccine than it's ever going to be with COVID. But

02:22:45.360 the rate with COVID is not zero. It's, I believe it's 2.3 cases per, it's going to be a big difference.

02:22:52.240 I think it's 2.3 cases per 100,000 of people with COVID are getting myocarditis. Most of those are

02:22:59.040 transient. They recover. Not all of them are. So a subset are not. But this mechanism would be

02:23:04.880 distinct from just myocarditis. Myocarditis, of course, speaks to the inflammation of the cardiac

02:23:08.880 muscle that would explain depressed ejection fraction. But what you're describing is a far more

02:23:14.000 diffuse problem, is a global insult on the mitochondria in the skeletal muscle, correct?

02:23:19.760 That's what we suspect from this data, which again is indirect, from the indirect

02:23:24.320 calorimetry in the lactate, that it points out towards mitochondrial dysfunction. So that's what

02:23:29.920 we need to do now, biopsies to understand this out of better detail. What the heck is going on?

02:23:36.400 Could be at the microtrophusion level too. It might not be at the muscle per se,

02:23:40.960 it might be at the microfusion in the blood, in the capillaries.

02:23:44.720 Meaning something like microthromboses that are preventing perfusion and raising lactate that way?

02:23:51.920 Could be, could be. That's what we need to find out. But we know from other viruses that they

02:23:57.120 hijack mitochondria. They interfere especially with the fission and fusion processes. Some causes

02:24:04.400 that increase fission, some other causes increase fusion, some other causes increase elongation.

02:24:09.520 So we know there's a wealth of studies out there from virology showing that, yeah, many viruses and

02:24:16.880 bacteria, they hijack mitochondria. They disrupted significantly. But most of the times, like myocarditis,

02:24:25.040 it subsides, it's restored. Shortly after the symptoms are gone, why this virus is different? That's

02:24:32.640 what we are trying to understand. Why people after one year, by the way, you know, most of these people,

02:24:37.920 they had just normal mild course of COVID. They were not hospitalized. They were not in the ICU.

02:24:43.280 Any evidence or inkling that if people go back to exercising too intensely following recovery,

02:24:51.760 it could exacerbate this problem? And do you have a sense of which strains this was?

02:24:56.320 Your work would have been predominantly alpha and not delta and obviously not omicron, correct?

02:25:01.520 Yeah. Even a mixture between the original variant and delta, so not omicron.

02:25:07.440 So in this population, which again is presumably mostly alpha, maybe some delta,

02:25:12.720 what was the distribution of male and female?

02:25:15.200 We have 35 females and 15 males, more female predominant.

02:25:20.480 Which again, maybe is too small a sample to know. That could be more an indication of who's

02:25:24.880 seeking out. And again, we don't really know the denominator. We don't know what this represents.

02:25:29.360 Is this one in a hundred thousand? It could be one in a million if this was everybody that's

02:25:33.600 reporting it at the time. Our guess is it's a rare event. It can last that long. But we're talking

02:25:39.680 about millions of people infected, right? If it's one in a million, we're talking about a population

02:25:45.440 that is going to need help. I want to kind of go back to just a few other questions that we didn't

02:25:50.000 get to. So not necessarily in any thematic order. What's the relationship between or how predictable,

02:25:56.800 I should say, is the relationship between zone two as defined by maximum fat oxidation

02:26:02.880 and VO2 max? So if you run somebody through a CPET and you figure out that their VO2 max is at four

02:26:10.080 liters, how predictably can you say at X percent of that, you will be at maximum fat oxidation?

02:26:17.600 There's another study that we're preparing the manuscript with 225 subjects where we look at

02:26:24.160 fat oxidation, VO2, and the relationships. Going back to the same thing, we tend, and historically,

02:26:31.440 the research studies with exercise have been done based on VO2 max. That's been the parameter to

02:26:37.520 prescribe exercise. How many times we read X amount of subjects, they were exercising for six months at

02:26:43.280 60% of VO2 max or whatever. Now, that's another thing that I've been thinking of years.

02:26:48.320 And by the way, when they say that, do they mean 60% of the heart rate that produced VO2 max,

02:26:56.160 or 60% of the power that is their max power at VO2 max? Yeah. I mean, there's so many different ways you

02:27:03.600 can do this that I've always found that you have to get into the methodology very closely.

02:27:07.520 I agree. I agree 100%. And this is where I think we need to dial things in better because yeah,

02:27:12.880 60% of the power output, the intensity might be translated into power output, 60% of VO2 max,

02:27:19.680 and then you translate into power output, or you translate into heart rate.

02:27:23.360 Or is it 60% of the VO2? So for example, if somebody's four liters VO2, and then they hit that at 300

02:27:31.600 watts, would 60% be 2.4 liters, which of course is not a very helpful way outside of a laboratory

02:27:39.280 to prescribe exercise to somebody? Or would it be 180 watts, which is 60% of the 300 watts?

02:27:47.600 Yeah, exactly. I think that normally the studies, they look at where do you hit 60% of VO2 max?

02:27:53.920 How many watts is this? Or what's your heart rate?

02:27:57.040 What's the wattage that corresponds to 60% of your max VO2?

02:28:02.880 And in our study, what we are seeing, and this is what, because I've been curious about this,

02:28:06.480 because we look at the cardiorespiratory adaptations to exercise, and we look at the

02:28:10.720 cellular adaptations to exercise. Do they really correspond? We know very well with athletes,

02:28:17.120 you can improve tremendously at the cellular level, but not at all at the cardiorespiratory

02:28:23.360 level, at least based on the VO2 max, which is the representative of the cardiorespiratory

02:28:28.560 adaptations to exercise. An example that I was given when I give talks, an athlete who used to be

02:28:34.880 an average professional, the VO2 max was 72.3 or something like that. And then two years later,

02:28:42.400 he is a very good professional. The VO2 max is the same, but the lactate levels were incredibly

02:28:48.720 better. I forgot, at five watts per kilogram, he was at five millimoles, and now he's at 1.7.

02:28:54.640 This is where the magic happened to this specific athlete. It was at the cellular level.

02:28:59.040 We see this across the board, right? Exactly.

02:29:01.520 VO2 max at the elite level does not come close to predicting performance.

02:29:05.840 Not at all. This is why we're putting together this study with all this population of different

02:29:11.520 from people with metabolic syndrome all the way from to the France athletes. So longitudinally,

02:29:16.560 we see that, yeah, sure, VO2 max corresponds with fitness in the same manner that watts corresponds with

02:29:24.800 fitness. So we can also imply that instead of doing a VO2 max to look at longevity and fitness,

02:29:31.680 we can also do a power test or a speed test and a treadmill because we're going to see the same

02:29:37.440 thing. Those ones who are very poorly active, they have a very poor fitness, they're going to have a

02:29:42.400 lower VO2 max, they're going to have a lower power output, they have a lower speed, lower lactate

02:29:48.080 cleanse capacity. VO2 max has been forever a great surrogate for fitness, cardiorespiratory fitness and

02:29:54.480 longevity. But we wanted to see if in fact it's really that specific. So in our study, we see that

02:30:01.200 people in different categories. At the same VO2 max, they might be in different metabolic states.

02:30:08.320 So some people at the same VO2 max might be oxidizing a lot more fat or a lot more carbohydrates. So

02:30:15.600 that means that does not correspond to the same metabolic status. I would have thought that most

02:30:22.000 people by the time they're at VO2 max, they would be disproportionately carbohydrate. So really,

02:30:27.760 you're just saying how much fat oxidation still remains there is really what you're saying. And

02:30:32.720 I'm assuming a very untrained person has zero fat oxidation by the time they reach VO2 max. Whereas

02:30:40.160 a more highly trained person would still have some amount, they might still be at 0.2 or 0.3 grams per

02:30:45.920 minute. Yeah. For example, we see that like a sedentary individual at 75% of the VO2 max might be around

02:30:53.680 three millimeters. Whereas a world-class athlete at the same percentage of VO2 max is about one and a

02:31:01.040 half. So metabolically, they're different. Yet the VO2 max is the same. So if we prescribe exercise based

02:31:08.080 on VO2 max, we might not do things correctly. And the same thing with carbohydrate oxidation,

02:31:14.080 that at a 75% of a VO2 max, like a sedentary individual oxidizes about two grams per minute,

02:31:22.000 where an elite athlete oxidizes about three grams per minute. So that's a significant difference.

02:31:27.680 And we also see it at 50% already. So this is why, longitudinally, they correspond quite well.

02:31:33.840 And same thing as fat oxidation. Fat oxidation at a 50% of VO2 max is about 75% of your CO2 max,

02:31:41.680 0.23 in the sedentary. It's 0.6 in an elite athlete. We look at the different intensities,

02:31:49.840 for example, that an athlete that can have one millimole of lactate within the same group,

02:31:55.600 not just comparing group, but we can see that someone within the very same group,

02:32:00.480 whatever the category they are, the lactate and the VO2 max don't correlate. The correlations are

02:32:07.760 sometimes 0.2 or 0.1 or 0.3.

02:32:11.520 That's the R squared, you're saying? Yes. No correlation.

02:32:15.440 Very poor correlation. When we talk about individual groups, when we look at specific

02:32:20.000 one parameter, which is lactate, with the VO2 max, it doesn't really correspond. So anyways,

02:32:26.240 this is what I think that we have learned a lot over these last decades, where we can really pinpoint

02:32:32.320 more at the cellular level to improve metabolism, more than at the cardiorespiratory function,

02:32:38.880 which is very important. Absolutely. They both are going to improve. But I think that if we want to

02:32:44.080 prescribe exercise, it's going to be more specific. If we look at cellular surrogates,

02:32:50.960 like lactate, like fat oxidation, for example, then looking at VO2 max or meds. I mean,

02:32:56.720 don't get me into there. That's very prehistoric in my model's opinion. I don't want to offend anybody,

02:33:03.600 right? But the whole med concept, use for exercise, prescription, it's hard to swallow in today's

02:33:10.240 times. Yeah. I was just about to say, I mean, it served its purpose in the 1950s. When we think about

02:33:15.840 some of the muscle biopsy data, again, this term of mitochondrial function, it's such an important

02:33:21.680 part of longevity because it is one of the hallmarks of aging is declining mitochondrial function.

02:33:27.120 I usually explain to patients that the type of physiologic exercise that we're prescribing,

02:33:33.280 this zone two exercise, is the way to measure mitochondrial function. It's both the treatment

02:33:39.520 and the test. But I'm guessing on the cellular level, there's even more that we can talk about.

02:33:44.720 The last thing I really want to talk about today, because I know we've been going for a while,

02:33:48.080 you've been generous with your time. When you get into the omics, when you start to biopsy the

02:33:52.720 muscles, when you start to look at the mitochondria in a way that we can't do it in a regular clinical

02:33:58.080 setting, what else are you seeing that's differentiating the healthy from the unhealthy

02:34:03.600 mitochondria or the high functioning from the low functioning mitochondria?

02:34:08.080 Again, I keep talking about papers that wouldn't publish it, but we've been working for

02:34:11.440 three years quite hard. And now we cannot continue doing this. We need to start writing the papers,

02:34:16.880 right? You need more postdocs. You need more graduate students and postdocs to help with the

02:34:22.320 writing. But we have completed a pretty cool study, and they're writing the manuscript now,

02:34:27.120 looking between sedentary and active. We know already there are a bunch of research

02:34:32.080 showing at the cellular level the difference between people with type 2 diabetes or

02:34:36.560 metabolic syndrome and active individuals or even sedentary. We want to see also or want to show that

02:34:44.320 people who are sedentary, they already have problems. And we wanted to compare them with

02:34:50.000 more active people who should be kind of how we should be as humans. So we looked into the mitochondria,

02:34:56.160 into mitochondria. So we looked at there's significant dysregulation at the mitochondrial

02:35:01.840 level everywhere you look in the mitochondria in sedentary individuals. You see a decreased

02:35:07.680 capacity to oxidize, to burn glucose in terms of pyruvate, fatty acids, amino acids. You see a

02:35:15.760 significantly decrease in our electron transport chain as well, all the complexes. And you see

02:35:21.600 also a significantly decreased capacity in the transporters of different substrates. One thing

02:35:27.520 that it really caught our attention, and we think that this is something that we really want to

02:35:32.720 emphasize and hopefully others in the future, is that we have identified that there is the mitochondrial

02:35:39.600 pyruvate carrier, which is, as I discussed earlier, that's the transporter of pyruvate into the mitochondria,

02:35:46.480 which is dysregulated already. Significantly down-regulated in sedentary individuals compared to

02:35:53.200 active individuals. Then we are matching it with the pyruvate flux, the oxidation itself. So both

02:35:59.440 the transporter and the flux are significantly dysregulated. What does this mean?

02:36:05.360 That's going to shuttle pyruvate to the other way it's going to get in the cell, which is through

02:36:10.320 lactate. Exactly, exactly. What are the implications of this? So again, these people don't have diabetes

02:36:17.200 or prediabetes. This could be a healthy person who's not active. And this is what, unfortunately,

02:36:23.200 this being the model in most research papers out there, comparing the unhealthy with a sedentary

02:36:30.560 healthy individual. I've been pushing for years that the model should not be the healthy sedentary

02:36:36.720 individual because that is the intervention. As humans, we're meant to walk or to exercise.

02:36:43.760 So we need to look at perfection to understand imperfection. The intervention of human evolution

02:36:50.320 has been becoming sedentary. And in fact, I had a hard time to get an IRB to study. I have a hard time

02:36:57.440 with the community to convince them that using active people as the gold standard to understand

02:37:04.240 imperfection. That's the way to go. But anyways, what we see is that these people already, they

02:37:09.600 don't have clinic, but yet they have a significant downregulation. They don't have clinical signs.

02:37:14.640 Clinical symptoms, sorry. They're not clinical symptoms. They're the healthy sedentary individuals.

02:37:19.280 They don't have insulin resistance and they don't have downregulation of GLUT4 transporters.

02:37:24.640 Even hyperinsulinemia? Are they hyperinsulinemic when challenged with the glucose tolerance test?

02:37:31.680 These people, they have no symptoms. They haven't reported any glucose tolerance test. Normal people.

02:37:38.400 And then they have a significant disruption in this mitochondria pyruvate carrier, which might mean that

02:37:45.120 the first door that might be jammed is that entrance of pyruvate inside mitochondria. Most of the research

02:37:51.920 in diabetes has done more at the peripheral level, if you will, glucose levels, more at the surface

02:37:57.200 levels of the cell, the GLUT4, the insulin resistance, the pancreas release of insulin,

02:38:01.680 beta cells, et cetera. But what's the fate of glucose once it enters the cell? And this is what we're

02:38:08.560 looking to this. So, and the fate is pyruvate, but what's the fate of pyruvate? As you said very well,

02:38:13.360 does it enter the mitochondria or is shuttled to, or reduced to lactate? So, I think that this is

02:38:20.080 important to see because it could be a marker down the road. Because again, these people don't have

02:38:25.440 clinical symptoms, yet they have a significant dysregulation in their glucose metabolism. So,

02:38:31.520 could this be 10, 15 years ahead of clinical symptoms and insulin resistance? This is more reason

02:38:38.240 also to consider sedentary individuals to see how they have a metabolic dysregulation already.

02:38:43.600 Same thing we're doing at the fat oxidation level. The CPT-1 and CPT-2, the transporters of fat,

02:38:49.680 they're significantly down-regulated as well. So, that means they're not going to be able to

02:38:54.320 transport fat very well, which also matches to the fat oxidation itself, where we inject fatty acids

02:39:00.720 into the mitochondria that are not oxidizing well. So, they all match as well. So, they have a

02:39:05.840 dysregulation already that is significant compared to moderate active individuals at the glucose

02:39:11.120 metabolism and fat metabolism. Then, we see that many of these people, I mean, who have diabetes or

02:39:18.080 metabolic syndrome, they have what's called intramuscular triglycerides, the fat droplet,

02:39:23.760 and it's adjacent right by the mitochondria. In elite athletes, it's also there, that fat droplet,

02:39:28.880 but it's very active because about 25 to 30 percent of the fat oxidation comes from

02:39:34.160 that fat droplet adjusting to mitochondria, which it could probably is an evolutionary mechanism to

02:39:40.240 not rely on the adipose tissue, which might take time and have something right away there.

02:39:45.120 So, when you say it's metabolically active, the difference between the intramuscular fat

02:39:49.040 of the athlete and the intramuscular fat of the person with type 2 diabetes,

02:39:52.960 is it the flux then? In the person with type 2 diabetes, it's a static source of fat.

02:39:58.160 In the athlete, it's constantly turning over and being oxidized and replenished.

02:40:02.320 Yeah, exactly. Whereas in this population, it continues to grow. My colleague Brian Bergman

02:40:08.080 from the university is working a lot into the content of what's inside these fat droplets.

02:40:13.280 But one thing that we know is they're very high in ceramides and diglycerides,

02:40:18.800 and especially ceramides are key in the atherosclerotic process. Atherosclerosis,

02:40:23.920 it's a hallmark of cardiovascular disease. Ceramides are key for this process. Historically,

02:40:29.280 it's been thought and it's been shown that ceramides come from the liver, they're released.

02:40:33.280 But we're seeing that these intramuscular triglycerides are high in ceramides.

02:40:37.440 So, could this be a connection between also cardiovascular disease and type 2 diabetes?

02:40:42.800 In the high turnover, high flux one, you're not accumulating them as much?

02:40:46.640 Yes. People who end up having type 2 diabetes, they accumulate fat droplet. Athletes as well,

02:40:53.760 that's the athlete's paradox. But athletes, as you said, they keep turning around and it's very active.

02:40:58.480 Whereas people with type 2 diabetes or obesity, it keeps growing. It releases pre-inflammatory

02:41:04.240 mediators and it also is high in ceramides, which are key in atherosclerosis. So this is where we're

02:41:10.160 trying to establish the connections between type 2 diabetes and cardiovascular disease at the

02:41:14.640 mitochondrial level as a nexus. Because we know that about 80% of people with type 2 diabetes,

02:41:20.160 they also have cardiovascular disease and vice versa, which is what we call cardiometabolic disease.

02:41:25.280 So could the nexus of all that are mitochondrial impairment? That's what we believe.

02:41:30.560 Well, what I take away from this is we probably have to do a third podcast in a couple of years,

02:41:34.800 because there's going to be a lot of data that's going to be published then that isn't published

02:41:39.680 now. There's going to be a lot more questions that we're going to have answered. Again, I'm still

02:41:44.240 really yearning to understand the effect of metformin in terms of pure mitochondrial function

02:41:49.280 and performance in a trained individual. So as always, I can't thank you enough for your

02:41:54.480 generosity of insight and look forward to talking tomorrow when we have a call about some other

02:41:59.600 nerdy stuff we're going to get into. But thank you so much, Inigo. And also congratulations on the

02:42:04.000 remarkable success of your team and Pogacar, who's an amazing cyclist to watch. He's got everybody

02:42:10.240 very excited about the Tour de France again. Well, thank you very much, Peter. All the

02:42:14.160 listeners, I really appreciate what you do. The first time I met you, we were two and a half

02:42:19.280 hours talking about mitochondria. And at first I thought like, this guy's crazy. There's nobody

02:42:23.920 out there who's going to be interested in listening to two and a half hours about mitochondria

02:42:27.840 and metabolic health. You showed me, yeah, the cancers are out there. And I was in a moment where

02:42:33.520 I was, not many people seem interested in this. And you were already an inspiration for me to

02:42:40.000 continue doing this. And there are remarkable work that you're doing to educate people and inspire

02:42:45.600 people. It's transformational. So I really appreciate the invitation. It's just an honor.

02:42:50.240 Thanks for being with us today. Thank you very much.

02:42:52.800 Thank you for listening to this week's episode of The Drive. It's extremely important to me to provide

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The Peter Attia Drive - July 08, 2024

Zone 2 training： impact on longevity and mitochondrial function, how to dose frequency and duration, and more ｜ Iñigo San-Millán, Ph.D. (#201 rebroadcast)

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