The Peter Attia Drive - #201 - Deep dive back into Zone 2

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

00:00:15.480 my website, and my weekly newsletter all focus on the goal of translating the science of longevity

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00:00:41.720 head over to peteratiyahmd.com forward slash subscribe. Now, without further delay,

00:00:47.740 here's today's episode. My guest this week is Inigo San Milan. Inigo was a previous guest on

00:00:55.620 the drive back in December of 2019. That episode was incredibly popular. We not only rebroadcasted

00:01:01.600 it, but we reached out to many of you for follow-up questions. And that, of course,

00:01:05.380 proceeded this episode. So we talk about a lot of stuff here. We begin the conversation

00:01:08.860 around Inigo's work with Tour de France winner, two-time winner now, Tadi Bogachar, looking at

00:01:14.620 the type of training that he does and getting a sense of really what the best of the best in the

00:01:18.620 world are capable of. And then, of course, now we can use that to sort of benchmark ourselves.

00:01:22.340 We speak specifically about lactate levels, fat oxidation, the relationship between watts and

00:01:26.800 lactate, how carbohydrates in food can affect our lactate. And then we talk about how equal

00:01:31.960 lactate outputs between an athlete and a metabolically unhealthy individual can mean

00:01:36.000 different things and how to interpret that. We get into very specifics around zone two exercise,

00:01:40.120 including many of the questions that people had around what metrics to use to know if you're in

00:01:44.060 zone two, if you're not using a lactate meter, how to structure an ideal zone two training program

00:01:49.240 with regards to duration, timing, frequency, the importance of compounding the rate of

00:01:54.140 improvement that can happen with zone two training. We talk a lot about VO2 max and high intensity

00:01:57.940 training, where that fits in with overall zone two training and how exercise can have such a large

00:02:03.620 impact on longevity. We speak about metformin and its potential impact on the mitochondria,

00:02:08.800 as well as NAD and claims that it can boost mitochondrial health.

00:02:12.600 We end by discussing healthy versus non-healthy mitochondria. And we speak about Inigo's study on

00:02:18.880 long COVID patients, which revealed effects on the mitochondria that were reminiscent of type 2

00:02:23.460 diabetes. As a brief reminder of his background, Inigo is an assistant professor at the University of

00:02:27.980 Colorado School of Medicine, where his area of research and clinical work focus on metabolism,

00:02:33.320 nutrition, sports performance, overtraining, diabetes, cancer, and critical care. He's also an

00:02:38.460 internationally renowned applied physiologist, having worked for the past 20 years with many

00:02:42.720 professional athletes and teams around the world, including, as I mentioned, the two times

00:02:47.640 Tour de France winner, Thaddee Pogacar. So without further delay, please enjoy my conversation with

00:02:54.380 Inigo Sanmilan. Inigo, it is so great to be sitting down with you again. Last time, of course, we did this

00:03:05.380 in person, but these days I've become too lazy to travel around and do podcasts in person. So

00:03:09.680 do it by video. But that said, I really hope you can get out here to Austin so we can train together

00:03:14.720 and do some cool ex-phys. And also I need to get out there to sort of do some of the ex-phys stuff

00:03:20.360 we've talked about. But I almost don't know where to begin because there's so much stuff we talked

00:03:25.120 about last time that we want to double click on this time. There's so much that has changed in the

00:03:29.920 interval from when we spoke, gosh, probably two years ago, a little over two years ago. I thought

00:03:35.380 one place we could pick it up, something we didn't really talk about last time, was your work with

00:03:40.720 Thaddee Pogacar. Because of course, I don't think anybody knew who he was two and a half years ago. And

00:03:46.040 of course, now he is, I don't know, I mean, I think it's safe to say he has the potential to

00:03:50.780 potentially go down as the greatest Tour de France cyclist of all time, given how young he is, not to put

00:03:56.000 that expectation out there. But to win the Tour at such a young age, to not just win the yellow

00:04:01.240 jersey, but the white jersey, polka dot jersey repeatedly, he looks like something of a different

00:04:07.320 species almost. And I say that not in the way that people typically say those things of cyclists in a

00:04:13.580 way that's suspicious of anything. So for the listeners who are not familiar with the Tour de

00:04:18.160 France, not familiar with your work with the UAE team and your work with Thaddee Pogacar, maybe give

00:04:25.380 folks a little bit of an update as to what you've been doing in professional cycling over the past

00:04:29.380 couple of years. First of all, thank you very much for having me here. It's an honor, really excited

00:04:33.840 for this, and I appreciate the opportunity. I had a lot of fun last time, hope to have fun again.

00:04:40.420 My work with Thaddee started in late 2018, when he signed up for the team. I was introduced to him by

00:04:49.660 our CEO, Giannetti, and our general manager, Machin, told me, hey, start working with this guy.

00:04:56.440 And he was what at the time, 19 maybe?

00:04:58.860 Yeah, 19. He was 19 at the time, just at turn 19. In fact, I started to work with him. Right away, I realized

00:05:06.320 he had potential. And I think like a couple of months earlier, no, or later, I forgot when we had that

00:05:12.540 podcast already told you about him. So like, we have a guy that has good potential. That was Thaddee.

00:05:19.540 To put it in perspective, I mean, has good potential is one thing. To then go and do what he did would

00:05:26.320 make that statement the understatement of the century for folks who maybe don't follow cycling

00:05:32.460 as closely, right?

00:05:33.520 Yeah. Yeah. I mean, I try to be cautious. I don't usually say that out loud of people who have a good

00:05:40.000 potential. We talked about it over dinner that night.

00:05:42.820 Yeah. Yeah. When I say someone has good potential, I don't usually say that lightly of anybody.

00:05:48.380 What did you see in him in 2018, 2019, that led you to believe that even amongst that class,

00:05:59.520 because professional cyclists from a physiologic standpoint are all very special individuals.

00:06:04.240 What did you see in him that made you think he has potential in your understated way?

00:06:09.280 The physiological testing we started doing right off the bat, I saw like amazing capabilities,

00:06:16.480 ability to clear lactate and to put out great amount of power for long periods of time.

00:06:22.100 So when you say that, was it specifically his FTP that impressed you or was it his, as you said,

00:06:30.580 lactate clearance, was it shorter bursts of power that were higher than FTP, but the speed with which

00:06:36.700 he could do or the successive repeats that he could do? I mean, tell me some of the testing you were

00:06:41.540 putting cyclists through and how he stood out. It's kind of like similar tests that I did to you.

00:06:46.860 And this is where I saw that at a given power output, his lactate levels, blood lactate levels

00:06:52.900 were extremely low. And since I've been doing this specific protocol for 20 years with professional

00:07:00.120 athletes, professional cyclists in this specific case, that's where I had my cheat sheet, where I

00:07:05.920 know I can categorize where people are. He was like, whoa, wait on the other side, way above almost

00:07:12.000 everybody that I had tested or around the same category. And for that age, that's what I saw like,

00:07:17.860 whoa, first of all, he is at a different category and he's first year pro, pretty much a junior.

00:07:23.540 And then that's where like, I could see he could sustain a high amount of power with very low lactate

00:07:30.660 compared to the rest. And then throughout the trainings, we use TrainingPeaks, the software,

00:07:36.020 looking at TrainingPeaks, that's where I would see his different abilities to sustain a given power

00:07:41.920 output for the whole day or for a specific effort, a glycolytic effort and a client would see the power

00:07:48.220 output that he would be putting out. And so altogether, then I saw his trainability, how easy

00:07:55.140 he would get the concepts, how easy he would be comfortable with the training, how easy he would

00:08:01.540 recover. I like the feedback. I talk to him once, twice a day over WhatsApp to, you know, how the

00:08:07.620 feedback. I know very well when a hard week is or what a hard week is. And when you see this kid

00:08:14.920 telling you, eh, I'm pretty good. I'm recovering very well. When other ones are telling you, woof,

00:08:19.600 I had to take it a little bit easier today because I couldn't do this effort. And we're talking about

00:08:23.840 high level pros. And you see this kid telling you like, eh, there's no problem. That's where you

00:08:28.580 start putting together things. And also around the same time with my two colleagues at the university,

00:08:34.340 Angelo D'Alessandro and Travis Nankov, we started to develop in a platform for metabolomics where we can

00:08:39.220 look at hundreds, if not thousands of metabolites in the human body. And we did it, the Tour of

00:08:44.580 California in 2019, which was like around April. That's where he won it. And that's where when we

00:08:51.280 analyzed all his metabolites. And we did already at the training camp in January, 2019. And we already

00:08:57.380 saw, wow, this guy has different metabolites at the glycolytic level, oxidative level, recovery level.

00:09:05.640 And we confirmed that at the Tour of California. And this is where putting all together, yeah,

00:09:10.840 this guy's different. So going back to what you said about lactate, I assume that one of the data

00:09:16.820 points that is most telling of a cyclist is if you plot on the X axis, watts per kilo, and on the Y

00:09:24.900 axis, lactate production. I mean, that might be one of the most telling graphs you could generate

00:09:30.920 to predict success in the Tour, correct? Absolutely. You see a normal tempo climbing

00:09:37.800 in the Tour de France. Tempo A, that is the whole peloton going up.

00:09:41.780 It's got to be four. Yeah, about five watts.

00:09:43.880 I was about to say, wow, yeah, I was going to say four and a half. Okay, so wow, the whole peloton

00:09:47.100 is going up at five watts per kilo. Yeah, something like that. And that's where you see like someone

00:09:52.740 at that intensity might have already six millimoles. So you can tell it's going to be very tasking

00:09:58.460 and others might have one resting levels. It really, really predicts performance. In fact,

00:10:05.560 when we go to these training camps, I'm going to go next week for the first training camp

00:10:09.940 of the year with the team. We do this physiological testing and I do this protocol and I get this

00:10:16.600 data. So right away, I tell the team managers, this guy is way above the rest. These three

00:10:22.400 guys are really, really good immediately behind it. These two guys are the third level. And

00:10:28.180 then we have all these guys that they're like really, really bad form. And it pretty much

00:10:33.100 works. Then we do different racing simulation and the telebook right away. This is how it

00:10:38.880 is. So this is why it's very predictive. And the same thing too, moving into the season,

00:10:43.160 you see, okay, all these three guys are going to be at a very good level when we start the

00:10:47.360 season. This guy, we thought that he was going to be a very good level. He's not there at

00:10:52.400 all. When the season starts, you see that it reflects very well what's going to happen.

00:10:58.400 Yeah. It's one of the things about cycling that I really love. I mean, I don't know if

00:11:00.900 you saw, but I interviewed Lance Armstrong back in, oh gosh, probably back in June or

00:11:04.840 maybe it came out in September. But one of the things that we talked about was both on

00:11:09.420 and off EPO or blood transfusions, you sort of knew where you stood before the race based

00:11:16.240 on your FTP in watts per kilo. He talked about when he was off EPO, he could hold 450 watts for

00:11:25.000 30 minutes. So that would be slightly above FTP at 70. I think he was 70 to 75 kilos, but

00:11:31.280 it was in the ballpark of six watts per kilo. And then of course on EPO, it was 7.1 watts per

00:11:37.080 kilo, a huge difference. But you knew that number going in and you sort of knew only the GC contenders

00:11:43.300 could do that. I think that's the thing that a lot of people don't understand about cycling,

00:11:46.580 which is there's relatively few moments in the tour when you need to sustain that level,

00:11:53.560 but they always occur at the most important strategic times. And that's sort of where the

00:11:58.280 race is won and lost because the race is won and lost by minutes. How many hours does it take to

00:12:02.740 complete the tour? A hundred hours or something?

00:12:05.020 An average about four and a half, five hours a day. Yeah. So something like that. Yeah.

00:12:09.220 It's about a hundred hour race. And yet the difference between the first, second, third guy

00:12:14.560 will be in some cases, seconds, in some cases, a few minutes for someone to win by five minutes

00:12:20.800 is considered a blowout. And so what it really tells you is that there are a handful of minutes

00:12:26.220 in that race. There are a handful of climbs and time trials that set apart the winners from

00:12:31.040 everybody else. And to me, that's one of the beautiful things about cycling physiology is you have

00:12:35.900 these metrics. And now I think it's not just FTP, it's watts per kilo at lactate production. So it

00:12:43.000 gets even more into the critical physiology of recovery. And in fact, we use those metrics a lot

00:12:49.520 for the competition and we did it this year at the Tour de France. So knowing the power output that he

00:12:54.940 could sustain for, as you very well said, for specific times and climbs, we knew his capabilities.

00:13:01.660 And one of the things that we knew was that in the Alps, he was at a very, very high level.

00:13:07.920 That famous stage where he broke away and called the Rome 35 kilometers to the finish line. We are

00:13:13.960 seeing not only his data, but we see by knowing our writer's data, you can also guess the other

00:13:21.500 writer's data too. It's not rocket science. So we knew that he was at a very high level and discussing

00:13:28.080 the ticks, you know, because it's part of the thing that we do. We observe the data that we have,

00:13:32.500 the data that we think the other ones have, and we structure a strategy for the next day. And hey,

00:13:38.600 does he have the legs to attack? Should be holding back or what should we do? And clearly it was like,

00:13:44.040 well, tomorrow, if he attacks 35 kilometers to the finish line, he's going to get there with three

00:13:49.300 minutes because the other guys, they're not at that level. Why wait to the end of the tour where we can

00:13:54.460 try to solve the situation? So we knew his capabilities very well in discussing this with

00:13:59.460 him and the manager. Yeah, that was the strategy. First test the legs and like I, if you had in fact

00:14:05.520 good legs, boom, go for it. And that's exactly what he did. Now, how much of that are you going to

00:14:10.500 determine after a night of sleep where you say, we're going to look at his resting lactate first

00:14:16.000 thing in the morning. We're going to look at his heart rate overnight. We're going to look at his

00:14:20.000 heart rate variability overnight. So in addition to the subjective, for example, how he felt during

00:14:25.560 the previous day's attacks, coupled with some of that objective data, does that partially formulate

00:14:31.080 the strategy also? Or is it mostly based on historical data from training where you say,

00:14:37.520 I know that when he's at this many watts per kilo for this many minutes, he has the capacity to recover.

00:14:43.800 The latter, where we have all that physiological data and the trends. What we see at this level,

00:14:50.580 these guys, they're so good at ignoring their feelings. Sometimes it's just kind of how they

00:14:56.420 wake up. You know his capabilities. So if he wakes up fresh, it's like a baby, boom, then you're ready.

00:15:04.500 And sometimes, yeah, it's just we try not to focus on many other metrics that they, because we have

00:15:10.040 already things. And sometimes heart rate variability that might not be very precise. And we don't want

00:15:17.120 to put some ideas in the head that any fight speaking with him, you know, and I'm not going

00:15:21.920 to mention any brand or anything, but looking at heart rate variability someday, he said like, look,

00:15:26.600 today he told me that I was fatigued, that algorithm. And I went out there and beat my record

00:15:32.660 on the client. So obviously I'm not fatigued. There are days it tells you you're in top form and

00:15:37.300 I feel a little more fatigued. So this is what these algorithms, we need to be careful sometimes

00:15:42.980 and might work with maybe general population, but with this type of athletes at this level,

00:15:48.220 I really feel that it's better. Once you have all the work done, you know their capabilities. Like,

00:15:53.920 are you ready to go? It's like a top performer at a theater. You have worked very hard. Now it's up

00:16:00.540 to like, are you ready to go? Do you have a good next lead? Are you ready to perform? And a good

00:16:05.520 performance say, yes, I'm ready to go. I agree with you completely. Even for me,

00:16:10.420 and I'm not a top level anything, I have not found the predictors of readiness to be very accurate or

00:16:19.160 to necessarily reflect how well I'm going to perform. I've had amazing performances by performances. I mean

00:16:25.300 workouts. That's the only metric I'm performing in. I've had amazing workouts when my prediction was

00:16:31.600 that it would not be good. And I've also had the prediction saying you're on top of the world and I

00:16:37.500 not performed well. So I wish I could say with more clarity what the frequency of those deviations

00:16:43.680 or discordances are, but I can agree that putting the wrong idea in somebody's head when there's

00:16:49.960 nothing you can do about it. I mean, that's the other thing too. It's sort of like at best, if it was

00:16:54.700 perfectly accurate, it would be great because you could say, look, today, maybe we shouldn't attack.

00:16:58.720 Today, it's damage control day. One of the things I want to ask you about here, and you've spoken

00:17:03.280 about this publicly, so it might be that you're just going to restate the views that you've shared

00:17:07.020 publicly, but I've always felt that now that we have such great transparency from that high octane era

00:17:15.740 of the maximum probably cheating in cycling, which in my view is kind of that two decades of the 90s and

00:17:23.660 2000s. We pretty much know now what kind of numbers cyclists were putting out when they were being

00:17:30.100 assisted by EPO and blood transfusions. And we sort of know that the best of the best were able to put

00:17:35.680 out somewhere between about 6.8 and 7.1 watts per kilo at FTP. We also know today that cyclists are

00:17:43.480 not doing that. Those numbers are nowhere to be found in the Peloton. Now that's information you and I

00:17:49.740 share confidentially, that's not public knowledge, but I know it, you know it, and anyone coaching

00:17:57.260 people at that level know that nobody's putting out 7.1 watts per kilo. You don't need to be at 7.1

00:18:04.600 watts per kilo to win the tour today. You could probably win the tour today at 6.1 watts per kilo.

00:18:09.840 Do you think that making that data public would put to rest a lot of the criticisms that say,

00:18:17.840 they've just found new ways to cheat, but it's still basically a dirty sport? Because when you

00:18:23.980 look at the data objectively, it would be very hard to say that today based on what we know

00:18:28.540 from the era when drug use was rampant. No, I think you make a very good point.

00:18:33.700 It frustrates me when people think that they're doing 7 watts per kilogram, 7.2,

00:18:39.700 and then you have the real data from the day. And this is way lower. The short climbs where they would

00:18:46.020 do maybe 7.2, now they're doing 6.3 maybe. And the longer climbs, they're doing 5.5, 5.8.

00:18:54.020 It frustrates me because I see this data. Gosh, I wish I could just boom, release it. I have

00:19:00.020 absolutely no problem with that. We debated it with the team. We're keeping all this. At the end of the

00:19:05.280 day, people can figure that out. And some people, when I see an internet, as you can see the weight of

00:19:11.040 the cyclist, the grade of the climb, when it starts, the time and the wind, you can be very

00:19:17.240 accurate at knowing that. And I see some people that are quite accurate on internet, but I see

00:19:21.460 other ones that are all over the map. The formula is 7.2. My gosh, I wish I could show him, hey,

00:19:27.520 this is the real data that we're seeing. Two points there is like, one, it's private data that the team

00:19:34.240 considers like not release it. That's team policy. But the other one too is like, even if you release

00:19:40.440 that data, there are always going to be people that are not going to believe you or they might say,

00:19:44.540 oh, they probably altering the data or they're tricking it somehow or putting more weight to the

00:19:50.920 data. So it looks like there's less power output. I don't know if it'll be an endless fight. I don't

00:19:57.600 have the answer. I just have that frustration that I wish that I could really show the data and people

00:20:03.840 can see it. There's always going to be someone who is not going to believe it and going to make

00:20:07.760 a lot of noise out of that. That's the other thing too, is like other teams and other writers

00:20:13.600 are releasing their data. So by releasing their data, you can see pretty much where Pogacar is.

00:20:19.940 Okay. If it's a minute ahead or 30 minutes seconds, or sometimes with the same time, you can see,

00:20:25.940 you know, like, whoa, whatever the writer has done and has entered Pogacar's group or 30 seconds

00:20:30.940 later and has done 5.9, Pogacar is going to be in that neighborhood. Not going to be seven,

00:20:36.120 you know, with 30 seconds ahead. In the spirit of releasing data, the other thing it would

00:20:40.780 potentially do, especially if you could see it in real time, I don't know if you watch Formula One,

00:20:44.860 but one of the things about Formula One that I think the sport has been able to do because of the

00:20:49.560 advances in technology is make more of the data available to the viewer. If you're watching Lewis

00:20:55.660 Hamilton driving a lap, you see what he sees now. You can see, and it's not the end of the world

00:21:02.420 data, but you see his speed. You see what gear he's in. You see the difference between throttle

00:21:07.020 and brake pressure. They could show even more data, certainly. And someone who drives would

00:21:11.780 appreciate it if you really saw brake bias. And if you saw brake pressure and lockup and things like

00:21:16.800 that, and you can hear the drivers speaking with their race engineers. So it basically allows you to

00:21:22.980 come more and more into what they're doing this year. They introduced a new camera angle,

00:21:27.240 which is what the driver sees. And I think it's fantastic because historically you see above them

00:21:32.800 and it looks so smooth, but that's not at all what it feels like to be in a race car. So now they just

00:21:37.900 literally put like a camera at their shoulder. And now you see how restrictive the halo is. You see

00:21:43.500 the bumps and it looks a lot faster. You know, I've had this discussion with a number of people,

00:21:48.380 which is if you could show the same sort of information in cycling, if every time the camera

00:21:53.720 went over to a cyclist, you saw their heart rate, their Watts per kilo, their speed, all of these

00:22:00.440 other things. And you could hear some of the communications back and forth with their teams.

00:22:05.060 Yes. That changes the sport strategically. Now you have to be careful what you say on the radio,

00:22:09.420 but it also allows you to see the human element of this sport a little bit more. Do you think that

00:22:15.140 will ever happen where you'll be able to flip on the Tour de France and you'll be able to actually

00:22:19.820 see real-time physiology? I would love it. It would be so much fun for the viewer and cycling has so many

00:22:27.680 possibilities to engage people more and be fascinated by the physiology and looking at these numbers.

00:22:34.140 It's already in a way, you see some cameras already installed in the front and the back.

00:22:39.500 It's called Vellon. You can see really cool images when they're preparing a sprint that is like

00:22:45.040 what feels inside. And you can see it's really scary. Sometimes you can appreciate how difficult

00:22:50.880 it is to be at 40 miles an hour sprinting or 35 miles an hour leading to a sprint or in a descent

00:22:57.140 at 60 miles an hour. Or 70 mile an hour descent.

00:22:59.440 Or 70 mile an hour descent. Exactly. And then you can see the power output in real time. I think it's

00:23:05.980 a great step. You don't see no other riders, but it's estimation only the riders who wear that Vellon

00:23:11.500 or that Vellon decides to do that. And I think that they're still not doing that with all the top

00:23:16.920 contenders. But I think it's a first step and obviously haven't spoken with them, but maybe it's

00:23:22.360 like, hey, let's see what's the feedback. And I think that people are loving it. I would expect that

00:23:26.820 this will increase. I would love at some point, you know, and as you know very well in the world of

00:23:31.620 biosensors, going to revolutionize sports where we're going to be able to see so many different

00:23:37.900 parameters of athletes in real time. Yeah. Imagine you could see lactate and glucose in real time.

00:23:44.180 Yeah, absolutely. Which of course is technologically feasible already.

00:23:47.320 Exactly. Yeah. I think that would love for all sports too. Imagine you can see an NBA basketball

00:23:53.180 game and see that the lactator of LeBron James compared to the other ones. I mean, I would love

00:23:59.380 to see that as a spectator. And I hope that someday we were able to see these parameters.

00:24:04.200 So last thing on the tour, talk to me about Ventoux this year. That was a tough stage. It looked like

00:24:10.800 his toughest stage. Is that a fair assessment? Yes, probably.

00:24:14.500 And what's amazing, I think, is the poise on that stage. It's hard to tell if he was really

00:24:19.040 struggling on the ascent of Ventoux or he was just deciding strategically, I'm going to conserve a

00:24:24.020 little bit of energy here. What was your take on that? Or what can you say about that?

00:24:27.780 It was a very difficult climb and a very long climb. Tade, his mentality is wired like a champion.

00:24:35.540 When someone goes and they were full gas in the last part, when you got attacked, Tade knew that

00:24:40.980 this is not going to be the top of Bon Ventoux. It's not going to be the end of the stage.

00:24:45.080 There's a very, very long descent. And I have some partners with me that they can help me out.

00:24:51.280 I'm not going to panic at all, but I'm not going to also waste a lot of energy. He also had a big

00:24:57.540 gap. A whole different thing would have been if he had 20 seconds. But having a big gap and knowing

00:25:03.320 that you have a big descent and how calmed he is, that's one thing that is a very important

00:25:08.920 strategy. This is what happened. This reminds me in a way what happened the first year that he was

00:25:14.720 pro when he was 19 at the Tour of California. It was the previous stage before Bear Lake,

00:25:20.720 top mountain in the Tour of California, where it's going to be decided. So the day before,

00:25:26.340 two cyclists, George Bennett and Ygitta attacked in a short but very steep climb. And there were only

00:25:32.120 like 12 riders left and Ygitta and Bennett attacked. Then there was like a descent and a long

00:25:38.640 highway all the way to the finish line. So there was plenty of time to catch him up, but Tade didn't

00:25:44.180 follow them up. Another rider would have just followed their will. And Tade decided, no, I'm

00:25:49.460 not going to follow them. We have time and I'm going to take the chance because I'm confident for

00:25:53.520 tomorrow. And when I asked him, as soon as he crossed the finish line, I asked him, are you okay

00:25:58.120 why you didn't follow their attack? He said, well, I just, I wanted to know who is going to be good

00:26:04.900 tomorrow. So I know those two guys are going to be good tomorrow, but I wanted to take my time

00:26:09.260 and see the other 10 guys, how they're breathing, what's their body language, take my time to observe

00:26:15.100 to start preparing my strategy for tomorrow. And in fact, that's what he did. They were then caught up

00:26:20.300 two, three kilometers to the finish line. So all those 12, 13 guys, whatever they were,

00:26:24.800 they got together. And the next day, in fact, he noticed those two guys attacked. He just followed

00:26:30.480 them and he just eliminated one by one. That's how this guy thinks. No panic. Plenty of time today.

00:26:36.440 I have a good gap in the GC. Why am I going to go full gas when I know that he is going to

00:26:42.600 go full gas and he might lose energy for tomorrow because he might pay for this at this time of the

00:26:48.660 tour de France. And we have plenty of time to catch him up. So that's kind of the strategy that he had.

00:26:54.320 How much time does someone like Teddy spend in zone two, which we're going to talk a lot about.

00:27:01.440 And let's do it more as percentage of training time. Cause I think absolute numbers will be

00:27:06.880 very large given that that's his job. But when you think about the percentage of time he spends

00:27:13.300 in that energy zone, how does it change over the course of the year? So presumably during the winter

00:27:19.720 months, a greater amount of his time would be spent there as he's base building right before a race,

00:27:25.220 when he's kind of sharpening, maybe less, what would be the range of time or percent rather? Yeah.

00:27:30.360 Yeah. You're right. When we talk about percentage, I like to put it this way, more like a percentage

00:27:35.780 of days dedicated to cultivate that energy system. Obviously, if you put in just every single minute

00:27:42.600 together, the majority is going to be that. But I would say more in days in the winter months might

00:27:48.700 be about 80%, 70 to 80% of the days. As the season gets closer, he starts increasing more the intensity

00:27:57.000 days and sessions when the start of the season racing. And you have, it depends. You might have

00:28:03.080 one stage race of five, seven days, and then you have five day block or one week to recover and then

00:28:09.180 you have the next stage race. So in that week, we do a lot of recovery. We might do some sessions

00:28:13.620 here and there. And then after a few blocks of races, that's where you have another long time to

00:28:20.640 train period to train, go to altitude, towards the Tour de France or towards the next goal. And that's

00:28:26.880 where you may revisit these different energy systems and train specifically. We alternate and each energy

00:28:33.980 system has a time in the year, in the calendar, where it's built in order to try to achieve what we want.

00:28:42.440 So let's remind people now, I've put out a few posts on social over, gosh, the past year and even in the

00:28:48.440 past little while. And anytime I'm talking about zone two, it's really one of the topics that

00:28:53.020 generates the most curiosity, the most inquiry from people. I think people really intuitively kind

00:28:59.400 of resonate with this. And then of course, a million questions follow because there's so much

00:29:04.360 minutiae and detail around it. And a lot of that we're going to cover today, but let's start from a

00:29:09.660 place of maybe someone hasn't heard the first podcast where we go through some of the semantics of

00:29:14.580 this. Define zone two. From my point of view, it is the exercise intensity at the one you are

00:29:22.020 stressing the mitochondria and oxidative capacity to the most. This is where you're recruiting mainly

00:29:28.200 type one muscle fibers. This is where you are mobilizing the highest amount of fat, both from

00:29:34.940 lipolysis, from maripose tissue, as well from fat oxidation inside the mitochondria. And this is also

00:29:41.200 where you stimulate all those bioenergetics, which is oxidative phosphorylation. This is where you burn

00:29:48.380 both the fat inside the mitochondria, as well as the glucose inside the mitochondria. There's not a very

00:29:54.680 high glycolytic flux that it's going to be transformed into pyruvate and reduced to lactate. But that flux

00:30:02.220 still is oxidized inside mitochondria. This is looking at from bioenergetics standpoint, this is what I would

00:30:09.780 consider the zone two. And what I have seen is that throughout the years is that this is the exercise

00:30:15.740 intensity that achieves or stimulates that mitochondrial function and fat oxidation and lactic

00:30:23.500 cleanse capacity the most. That's the other thing too. This is where other things involving lactate. So lactate

00:30:31.900 is a great fuel to the cells. It's in fact, it's probably the preferred fuel for the cells, for most cells in the body.

00:30:39.500 This is a work that my colleague and mentor and friend George Brooks discovered. I should

00:30:45.460 have him someday in the podcast because he's fascinating. I mean, I would not be surprised

00:30:49.740 if someday soon we hear that he wins a Nobel Prize. He's amazing. And every time I talk to him,

00:30:55.940 I'm still learning a lot of things. And I've been translating a lot of his research. That's how I

00:31:01.540 see that you have within the mitochondrial function, you see how lactate is oxidizing the mitochondria back to

00:31:07.860 energy. And that happens in those muscle fiber types. Those muscle fiber types and the mitochondria,

00:31:14.020 those fiber types also develop these transporters, which are MCT1s, which are the ones that transport

00:31:20.780 lactate inside the cell and inside mitochondria. So when you stimulate that training zone, you stimulate

00:31:27.600 all these energy systems and the components that come with them.

00:31:30.780 So let's talk about the different ways that one can go about estimating this. Based on the definition

00:31:37.000 you've just given, it seems to me that the purest way to estimate this would be via indirect

00:31:44.180 calorimetry, because that will actually tell us the fat oxidation. Is that a fair assessment?

00:31:49.940 Yes. It's a very good assessment that usually correlates with the fat max. That's how we call it too,

00:31:55.740 right? That's fat oxidation. And when you see there's, you start oxidizing fat and my increase

00:32:02.060 in cases and gets to a point that is, it maxes out, which is the fat max. And then it starts going

00:32:08.520 down sharply. That's exercise intense. It increases. So let's tell people how that's measured. We do this

00:32:14.440 with all of our patients and I find it to be not that easy to explain because there's some physiology

00:32:22.480 involved and there's some math involved, but let me try to see if I can explain this to folks. So

00:32:27.220 you hook me up to an indirect calorimeter. So you're going to put a little plug on my nose.

00:32:33.300 You're going to put a mask over my nose and mouth. That mask has the ability to measure the amount of

00:32:40.020 oxygen that I consume because it has a sensor for O2. So it knows that the O2 that's coming in

00:32:47.660 is at 21%. The air is coming in at 21% O2 and whatever I exhale is the difference between that.

00:32:54.740 So you can now tell how much O2 was consumed and you can have a similar sensor for carbon dioxide.

00:32:59.660 So you know how much carbon dioxide is produced. So it's very easy to measure consumed oxygen and

00:33:05.520 produced carbon dioxide provided you can completely isolate around the nose and the mouth. As you hook a

00:33:10.800 person up to some form of ergometer, usually a bike could be a treadmill, a rowing machine,

00:33:17.020 or something like that, you can increase the demand on the muscle. So you increase the wattage or the

00:33:22.360 speed or the something. You then get out these numbers, VO2 and VCO2, which are what we just talked

00:33:29.180 about. So consumption of oxygen, production of carbon dioxide. These numbers fit into a relatively

00:33:35.480 straightforward linear equation called the Weir equation. And it tells you three things and tells

00:33:41.700 you total energy consumption in kilocalories per minute. And then the ratio of VO2 and VCO2 tell you

00:33:51.380 how much of that energy is coming from fat oxidation and how much of it is glycolytic. So at any moment in

00:33:58.960 time, you can look at a VCO2 and a VO2, which are usually measured in liters per minute, and you can

00:34:06.620 convert that into a total grams of fat oxidation and a total grams of glucose oxidation per minute.

00:34:16.080 And so you could then plot on the x-axis work or power, and on the y-axis, you could plot fat

00:34:24.780 oxidation. Again, describe for people what the shape of that curve looks like and what differentiates

00:34:31.560 Pogacar from the average human being. You explained it very well. Yeah, those are based on

00:34:38.040 stoichiometric equations. The combustion of carbohydrates and fatty acids are done in the body.

00:34:43.860 Already in the 1920s, Francis Benedict, one of the first ones, probably the first one who started to look

00:34:49.180 into this at this level. Obviously, we have evolved to do it in a more automatic way with these indirect

00:34:55.840 colorimetry machines, or also metabolic cards. As exercise intensity increases, I mean, you need more oxygen,

00:35:03.060 so your VO2 increases, and then you produce or give up more CO2. So this is kind of what it shows. When you're in a

00:35:12.800 more lipolytic state, more fatty oxidation state, you still consume oxygen, but you do not produce as much CO2.

00:35:21.340 When you are more into a more glycolytic state, which is higher exercise intensities, when you're recruiting the

00:35:28.780 type 2 muscle fibers, and therefore using more glucose for energy purposes, you're going to consume more oxygen, and you're

00:35:36.240 going to produce more CO2. Plugging in all these numbers into these stoichiometric equations, it's going to

00:35:43.300 give you that profile, the X and the Y axis, and it's going to see what is the fat oxidation throughout

00:35:51.700 ramp state, a ramp test. And this is where you're going to see elite athletes like Pogacar, they have an

00:35:58.980 amazing fat oxidation capacity compared to other competitive athletes, or

00:36:03.920 recreationals, or people with even type 2 diabetes, or metabolic syndrome, or in a recent study that we have published

00:36:10.920 with COVID patients. So it reflects in a way, ultimately, what happens in your mitochondria, and how the mitochondria

00:36:19.460 oxidizes those fuels at different exercise intensities. So for example, let's say at the intensity of 200 watts, a lead

00:36:27.620 athlete doesn't need to incur in that glycolytic capacity as much as someone who is not very well

00:36:35.420 trained. So the lead athlete, they can still recruit slow twitch muscle fibers and rely a lot on fat to

00:36:43.580 produce ATP, because they have an amazing mitochondrial function, and they're very efficient metabolically

00:36:49.440 speaking. Therefore, they're going to be oxidizing a lot of fat. However, someone whose mitochondria are not

00:36:56.200 working as well, whether you are like a recreational athlete, or sedentary individual, or someone with type 2

00:37:04.000 diabetes, which is one of the hallmarks of the disease, that mitochondrial impairment or dysfunction

00:37:09.620 at 200 watts, you fully rely on glucose pretty much, because you cannot sustain that effort with fat

00:37:17.600 alone. And this is what you're going to be seeing this cast exchange, the CO2 and the VO2, you can just plot it

00:37:25.560 into the equation. And it's going to give you all that, what I call metabolic map, where you see the fat

00:37:31.940 oxidation, the carbohydrate oxidation, and then I plug in also the lactate. And that's where everything comes together

00:37:39.080 quite well. And you can then first, in an indirect way, calculate the mitochondrial function and metabolic

00:37:47.260 flexibility, how flexible they are at using fats or carbohydrates. And also, you can determine training zones. I've been using this

00:37:55.540 methodology for 16 years, 17, something like that. I didn't think to ask you this earlier, but if you

00:38:02.220 have it handy, do you want to pull up a graph of what fat oxidation looks like versus power, so that people

00:38:11.460 can see the difference between a highly trained individual, a reasonably trained individual, an untrained

00:38:19.060 individual, and at the other end of that spectrum, somebody with type 2 diabetes?

00:38:22.200 So this is from a publication that my colleague George Brooks and I published in 2017. This is the

00:38:31.400 formula. And we have realized that this is flipped. So we need to work now with the editor to change it

00:38:36.920 because the formula is flipped here in the methods section. Which is so funny, by the way. I like seeing

00:38:42.020 that. I'm embarrassed to say when we do this for our patients, we do it in two steps, which yields the

00:38:47.840 same result. But we first calculate energy expenditure using the Weir coefficients of 3.94 times VO2 minus

00:38:56.740 plus one point, I think it's 1.2 times VCO2. And then we convert that to fat ox and carbohydrate

00:39:06.560 oxidation using the ratio of VCO2 to VO2. And I never even thought to do what you've done here, which is so

00:39:14.340 much more logical, which is combine them into a single equation for each.

00:39:18.440 Well, we used what Fryant observed already in 1983. And this is Fryant's equation. And it's been

00:39:25.520 validated with tracers, stable isotope tracers.

00:39:28.980 Doubly labeled water.

00:39:29.820 Yeah. And that's what it shows. There's a very high correlation. Now, furthermore, in a study that we

00:39:35.240 were going to be publishing soon, we have validated this fat oxidation and carbohydrate oxidation

00:39:40.740 directly with mitochondrial respiration. So in muscle biopsies, we inject directly fatty acids,

00:39:49.480 pyruvate representative of carbohydrates, glutamine representative of amino acids. And then we can see

00:39:55.160 that there's a very high correlation between this indirect methodology to look at mitochondrial function

00:40:01.100 and the direct methodology, which is through a muscle biopsy and injecting the substrate and see how it's oxidized.

00:40:07.340 So these two graphs are really powerful. Let's talk about what the first graph is showing us.

00:40:13.060 So both of these graphs, it's important to note, have the same x-axis. In other words, the independent

00:40:19.760 variable here is the workload in watts. That's the metric that matters in cycling, which is, I think,

00:40:26.480 the easiest way to do this test. And so you're increasing wattage. This is a progressive increase in

00:40:32.680 workload. And what you're plotting on the y-axis, your dependent variable here in the first graph,

00:40:38.720 figure one, is blood lactate. What stands out to me is a couple of things. So you have the triangles

00:40:45.520 represent metabolic syndrome. The squares represent a modestly trained athlete. And then the little

00:40:52.920 diamonds represent a professional athlete. The first thing that stands out to me, and we're going to talk

00:40:57.880 about this later, so I'll put a little pin in this, is that the people with metabolic syndrome have a

00:41:02.520 resting lactate that's almost 2 millimole. Yes, we see already this. I think that it's going to become

00:41:08.760 more and more as a biomarker, like resting blood glucose levels. What is your resting lactate? You can

00:41:15.240 see already in patients with type 2 diabetes or profound metabolic syndrome that, yeah, as you said

00:41:21.520 perfectly, resting levels are in the neighborhood of like a 1.8, 1.5 to even 3. So one of the metrics

00:41:29.420 that we've discussed at length, and we'll revisit it, of course, is using this lactate level of about

00:41:34.700 2 millimole as being that threshold. So once lactate exceeds 2 millimole, the individual is now escaping

00:41:43.300 out of zone 2, and they're actually now into zone 3. So when you look at these data here, you can see that

00:41:48.680 the individual with metabolic syndrome is basically tapping out zone 2 initially. So any incremental

00:41:56.480 workload that is placed on them takes them right out of zone 2. For all intents and purposes, by the

00:42:02.480 time they're at 100 watts, they're already at the threshold of their zone 2. Now, conversely, when you

00:42:08.540 look at that medium-trained or reasonably well-trained individual, I think it's referred to as moderately

00:42:14.900 active, healthy individuals. They start out with a lactate of about 1, and it's not really until they

00:42:20.280 hit about 175 watts that they pass that inflection point. And then when you look at the professional

00:42:27.840 athletes, the professional endurance athletes specifically, they're starting out at a lactate

00:42:32.780 level of 0.5 millimole, and they stay relatively flat until they hit about 300 watts is when they finally

00:42:42.580 cross over that threshold. Now, what's not captured here is that as you move from left to right,

00:42:52.080 the athletes are getting lighter. So this graph, if I'm going to be critical of it, Inigo, I would say

00:42:59.400 it should be done in watts per kilo. And that would show a much starker difference between these. And in

00:43:06.400 our patients, when we benchmark them, we benchmark them in watts per kilo for this reason, so that you

00:43:11.740 normalize by weight. And I'm sorry to interrupt, but you're absolutely right. And that's how we do it

00:43:16.460 also. One of the reviewers didn't allow us to use watts per kilogram. Clearly that reviewer was an

00:43:22.480 idiot, so that's fine. I won't let it against you because the idiot reviewer. You know how it is in

00:43:27.280 review papers. You want to show something, and eventually it's changed, and it's not exactly

00:43:31.440 sometimes what you want to show, because otherwise they don't allow you to publish it. But anyways.

00:43:36.240 But what's amazing here is that person with metabolic syndrome is probably about one watt

00:43:43.100 per kilo easily. One to 1.3 watts per kilo is their zone too. When you look at the modestly trained

00:43:50.920 individual, they're about two watts per kilo. They probably weigh maybe two to 2.1, 2.2 watts per kilo.

00:43:58.580 That professional endurance athlete probably weighs in the neighborhood of 70 kilos. So they're in the

00:44:06.880 ballpark of 4 watts per kilo. For our patients, Inigo, we set the aspiration at 3 watts per kilo.

00:44:14.360 So again, our patients aren't professional athletes, but we think that 3 watts per kilo would be kind of

00:44:20.020 the elite level that we would want to see people. And then of course we stratify from there. Let's look at

00:44:25.460 the lower figure, figure 2, just beneath this. So here we're looking at the same group of individuals.

00:44:31.100 We have the same independent variable, which is work, but now we're calculating fat oxidation as a

00:44:38.900 function of that work. So now your dependent variable is fat oxidation, which again, very easy

00:44:43.460 to calculate via indirect calorimetry. Two things stand out again. The first is the obvious, which is

00:44:49.620 the fitter the individual, the higher their absolute capacity for fat oxidation. But something else

00:44:55.860 stands out to me, Inigo, and I have now seen this repeatedly across multiple data sets, which is a fit

00:45:02.860 individual actually increases fat oxidation to a local maxima before beginning that decline. Whereas

00:45:12.000 most mortals begin at a maximum and decline from there. Can you explain why that's happening?

00:45:18.420 I agree. I see this all the time. I think that on one hand is how you start a protocol. In this case,

00:45:25.300 we started like at one. We start about 1 to 1.5 watts per kilogram. And that obviously for an elite

00:45:32.100 athlete is below resting level. So this is what they're very low and they don't need to use much fat

00:45:38.300 for energy purposes until you push them more. And that's when you get to like 2, 2.5, 3, 3.5 watts per

00:45:45.580 kilogram, right? And again, this protocol comes originally from the work that I've been doing for

00:45:51.260 20 years, this same protocol with elite athletes. When you do the same protocol with other populations,

00:45:56.860 especially people with metabolic syndrome or not very fit, and you start at 1.5 watts per kilogram,

00:46:03.260 that might be too much. And I'm sure you have observed that if you start at 0.5 watts per kilogram,

00:46:08.620 you might see a higher fat oxidations, and then you might see the same phenomenon. So on one hand,

00:46:15.660 it's that protocol. But on the other hand, yeah, sure, like 0.5 watts per kilogram,

00:46:21.020 it's like nothing. It's close to resting levels. So it will take you for a long time. But that being

00:46:27.660 said, I think that one thing that we're doing with populations for more clinical populations is

00:46:32.620 really start at a very low level, even up to 50 watts or 25 watts sometimes. So we can establish

00:46:38.780 this point. Because if you start at 2 watts per kilogram or 1.5 watts per kilogram with someone with

00:46:44.260 a significant metabolic dysregulation, you're going to miss the fat max. Yeah. And I agree that we have

00:46:50.700 been struggling to tune our algorithm to exactly that. I actually think, and I had this discussion with

00:46:58.320 our team a week ago, which was the physiologists who are doing this with our patients are probably

00:47:04.540 overcooking the people who are not fit during the warmup. So they do a warmup and the warmup is

00:47:10.880 actually too stressful and it overcooks them. And then we're missing the true max fat. The next thing I

00:47:17.460 want to point out here, and let's just look at the fittest person, but it's true for all of them,

00:47:22.320 but it's easiest to see here. Fat max, so fat max ox, right? So maximum fat oxidation is occurring

00:47:30.160 earlier than lactate is 2. And that's true for all of them, except for the MetSyn person, because

00:47:36.960 it's so low. If you look at the moderately fit person, they're hitting maximum fat oxidation at

00:47:43.440 about 130 watts, but they're hitting lactate of 2 at 175 watts in the upper figure. And the professional

00:47:51.120 athlete is hitting an absolute fat oxidation maxima at a little shy of 250 watts, but they're hitting

00:48:00.220 lactate of 2 closer to 300 watts. So I guess the question then becomes, you've already answered part

00:48:08.060 of the question, which is we're really defining zone 2 as the place where maximum fat oxidation occurs.

00:48:14.380 But I guess this would suggest that using a lactate level of 2 is maybe overestimating

00:48:21.280 where that is. And should we be using a lower level of lactate, such as 1.5 or something like that?

00:48:28.120 This is what I've been learning all these years is that the blood lactate levels might change between

00:48:34.820 different groups. And it's everything related to the lactate kinetics and lactate oxidation in the

00:48:40.940 mitochondria. So for example, elite athletes, so this was part of my doctorate thesis and some of

00:48:48.020 these that never published it 20 something years ago, but the same blood lactate concentration does

00:48:55.100 not correspond in an elite athlete, does not correspond necessarily to the same lactate concentration

00:49:01.100 in a recreational athlete, the metabolic stress. So for example, 2 millimoles, 2 millimolar

00:49:09.200 of lactate in these elite athletes might be a higher metabolic stress than 2 millimoles in a metabolic

00:49:15.620 patient. So this is why it would be very difficult. For example, you can have, let's say, 2.5 millimoles,

00:49:22.280 you can have a metabolic syndrome patient exercising for a couple hours without a big deal. You try to do

00:49:30.280 that with a professional athlete and they're going to be hurting. And in fact, one of the things that I

00:49:35.160 observe is like I use the 4 millimole or millimolar, which is kind of that gold standard has been

00:49:40.220 forever, like the lactate threshold, et cetera. If you put a world-class athlete at 4 millimoles at the

00:49:46.820 intensity and power output that elicits 4 millimoles, and you put a recreational athlete at the power

00:49:54.600 output that elicits also 4 millimoles, and you say, now go, see who lasts the most. Intuitively, we're going to say,

00:50:01.460 obviously, it's going to be the professional athlete. It's the opposite. And this is the data that I saw

00:50:06.320 20-something years ago. The recreational athletes at the same blood lactate concentration would go about

00:50:13.040 30% longer periods of time. And that's because metabolically, it's not as tasking. And the main

00:50:19.580 reason is that the lactate that we see in the blood, it reflects the mitochondrial oxidation. So someone who

00:50:28.040 has, obviously, when we're talking about high power output, when you need a lot of glycolysis to produce

00:50:34.220 energy, you're going to produce lactate. Lactate is the mandatory, obligatory byproduct, not waste

00:50:40.740 product, but byproduct of glycolysis. So the higher the glycolysis, the higher the lactate. Now that

00:50:47.060 lactate has two routes mainly. One is going from the fast twitch muscle fibers to the slow twitch muscle

00:50:54.540 fibers. It's the lactate shuttle that George Bruce discovered and is oxidizing the mitochondria of

00:51:00.900 those slow twitch muscle fibers. If you have a very good lactic clearance capacity, you're going to be

00:51:07.200 oxidizing it very, very well for fuel. Therefore, you're not going to incur in the second step, which

00:51:13.400 is exporting it to the blood. When you have a poorer mitochondrial function, it's going to get to a point

00:51:19.620 that that capacity is going to get saturated at a lower power output. And therefore, you're going to

00:51:26.380 be forced to export that to the blood. So that's why looking at blood lactates might not mean the same.

00:51:32.660 I'm not saying that disparities are huge by no means. But as you very well said, those two millimoles

00:51:37.400 might not correspond in an elite athlete with a fat max, but might be more maybe towards 1.5. Whereas

00:51:43.820 maybe in someone with a more recreational or metabolic syndrome, it might correspond there. I don't know if

00:51:50.320 it makes sense.

00:51:51.640 It completely makes sense. And this is definitely the level of nuance I don't think we captured in the first

00:51:57.000 podcast. And I want to now ask a more telling question specifically for the middle person here. So the one

00:52:04.500 that's called the moderately active individual, where again, we have a disparity. So based on these data, the

00:52:10.660 moderately fit individual hits a lactate of two millimole at 175 watts, but hits a max fat oxidation

00:52:18.840 at gosh, 125 watts. So it's a 50 watt difference. So now the question for you is when that person comes

00:52:27.400 to you and says, in you go, I want to improve my metabolic function. I want to improve my mitochondrial

00:52:35.280 performance. I want to improve my fuel partitioning, my flexibility, all the things we talk about.

00:52:41.460 Are you going to train them as a zone two of 125 watts or as a zone two of 175 watts as represented by

00:52:49.720 these deltas? Normally, I would try to do something in the middle. Normally, it might not coincide

00:52:56.120 perfectly, but normally they do quite well. And another parameter, if you allow me, I can show you in this

00:53:02.960 paper. When decided, we see individually, the lactates, and then we see the fat oxidation.

00:53:10.140 But then where I decided to cross them over, this is what we saw in this graph over here.

00:53:15.640 So this is where you see the lactate versus the fat oxidation in the elite athlete, and the R is 0.97.

00:53:24.680 This is through Bonferroni equation. So this is an average of all of them. And this is where you see

00:53:29.900 the same pattern, the same graph for the moderately active. And this is also what you see in the

00:53:36.420 person with metabolic syndrome. The correlations are very, very strong. They're almost perfect.

00:53:41.660 So this is what normally fat oxidation and lactate, they go together.

00:53:47.280 So for people who are going to be listening to this in you go and not able to see what we're seeing,

00:53:52.700 can you describe the differences between these graphs? These are obviously showing the same data

00:53:59.220 that we discussed earlier, but now we're using two Y-axes. So let's even just talk about it as

00:54:05.200 looking at the elite athletes. So you're basically plotting the decline in fat oxidation, or in their

00:54:12.640 case, the initial increase in fat oxidation followed by a decline in fat oxidation. And on the same graph,

00:54:18.620 you're showing the increase in lactate production. Again, both plotted to the same X-axis of power.

00:54:25.520 Does the cross point here indicate any significance? So they're crossing at about

00:54:30.580 325 Watts. Is there anything about that that means anything? I mean, to me, I think it's an

00:54:35.540 artifact of the graph because it's really just a function of how you scale it, correct?

00:54:40.400 Yes, exactly. I mean, it shows to me that, yeah, the crossover point for blood lactate and fat

00:54:46.700 oxidation, very high, obviously in the elite athletes, very far to the right.

00:54:52.020 And then of course, in the moderately fit people, it's looks like it's closer to a hundred and

00:54:56.820 maybe 80 Watts. And in the unfit individual, it's about 125 Watts in person with metabolic syndrome.

00:55:03.400 If you started, and I'm sure you have seen this, but if you started with the metabolic syndrome,

00:55:08.500 for example, at 25 Watts, even in the recreational athlete, even earlier, you might see a similar

00:55:14.380 pattern as you would see in the elite athlete, but a much lower Watts, obviously. We just did the

00:55:20.380 same protocol for everybody just to show the concept, both fat oxidation and lactate go together.

00:55:27.500 And also when we look into, and I'm sorry, I should have gone this to this directly.

00:55:31.860 When we look into fat oxidation and carbohydrate oxidation, we see the same concept. So we see as

00:55:38.380 exercise intensity increases, you need to oxidize more carbohydrates. And then as exercise intensity

00:55:44.940 increases, you might get to the fat max. And then when you moment you switch to the glycolytic fibers,

00:55:50.860 you cannot use much fat for energy purposes. So you see a sharp decline and eventually fat oxidation

00:55:58.140 disappears. And it's all full glycolytic. And the same pattern we see in the rest of populations

00:56:03.980 with also very high statistical significances and correlations. All these elements, fat oxidation,

00:56:10.060 carbohydrates and lactate, they're very well connected. If we look in the other graph,

00:56:15.740 this is the correlation between lactate and carbohydrates. We see that overall, the correlations

00:56:21.900 are quite good because lactate is the by-product of glucose utilization. You may see that in the

00:56:29.020 elite athletes though, the gap is wider here. And this is for the same reason I was seeing earlier.

00:56:33.740 They use a lot of glucose. They're using so much fat there as well is really the point. So the bigger

00:56:39.500 the gap between the blood lactate curve and the carbohydrate oxidation curve, the more efficient the

00:56:45.500 individual is. The more they're able to oxidize fatty acid, then they have to require glucose.

00:56:52.300 And clear lactate.

00:56:53.420 Yes.

00:56:54.220 The mandatory by-product of glucose oxidation is lactate. So here the lactate doesn't show up in the

00:57:02.460 blood. It stays in the muscle. It's hard to disentangle those two because you mentioned a

00:57:08.300 good point that I omitted. This in part reflects the lactate shuttle. This in part reflects the ability

00:57:15.820 for them to reuse lactate as a fuel, as opposed to just letting it get out there with hydrogen and

00:57:23.820 start to poison sarcomeres. Let me see the other slide that you wanted to show that explains,

00:57:29.020 I think, how the MCT transporters work.

00:57:32.300 This is a little bit more of the bioenergetics of the cells of the main two

00:57:37.020 substrates, which are fatty acids and pyruvate and also lactate, right? So normally glucose goes

00:57:42.300 through glycolysis and it ends up, this is the cytosol. This is the outside of the mitochondria,

00:57:47.100 the inside of the cell. And glucose, when it enters the cell, it's oxidized to pyruvate.

00:57:52.860 That pyruvate needs to enter the mitochondria through what's called the mitochondrion pyruvate

00:57:59.260 carrier, and it's oxidized to acetyl-CoA, which enters the Krebs cycle. This is a complete

00:58:05.100 oxidation of glucose through oxidative phosphorylation in the Krebs cycle and electron

00:58:10.300 transport chain. Then fatty acids have the same mechanisms too. They also get converted to acetyl-CoA

00:58:17.740 through different mechanisms. Fatty acids are transporter through CPT-1 and then CPT-2,

00:58:22.940 go through beta-oxidation, acetyl-CoA and enter the cell. But every time that you use glucose,

00:58:29.980 you produce pyruvate and every single time that pyruvate is going to be reduced to lactate,

00:58:35.100 always. And this is the key concept. So when you have a constant glycolytic flux,

00:58:40.540 in one of the steps of glycolysis, you're going to utilize NAD and it's going to be

00:58:46.780 transformed to NADH plus hydrogen. So if you use this mechanism a lot, you're going to deplete NAD.

00:58:56.380 The only way that rescues NAD is the reduction of pyruvate to lactate, which replenishes NAD going

00:59:03.660 back for glycolysis. And this is absolutely necessary for the continuation of glycolysis.

00:59:08.860 But this lactate enters the mitochondria through a specific transporter, MCT-1, and has a specific

00:59:16.300 enzyme, LDH, that oxidizes lactate back to pyruvate and going back to the Krebs cycle.

00:59:23.660 So again, this is an extra fuel. But for that, you need to have these transporters very well developed.

00:59:30.300 Let me try to explain this to people who aren't able to see the graph, because this is such

00:59:35.740 an important point. So you're showing a picture of the mitochondria. We're looking at the outer

00:59:40.780 mitochondrial membrane. We're talking about three transporters, three things that let substrates

00:59:47.020 from the outside to the inside, where they will undergo the most efficient form of ATP production.

00:59:54.780 So the first is we have the fatty acids. They enter directly and they undergo an oxidation where they

01:00:00.940 get truncated into little two carbon chains and they enter the Krebs cycle. We get that one and we

01:00:05.420 know why that one's very good. What I think is very interesting here is when you contrast the two

01:00:11.260 different fates of glucose byproducts. So the traditional way that we think about this,

01:00:17.580 glucose being reduced to pyruvate, pyruvate directly entering the cell through its own carrier,

01:00:24.700 and then being converted to acetyl-CoA, which follows the same fate as the fatty acid.

01:00:30.220 Now, when energy demand increases, and we just looked at graph after graph that demonstrate that no

01:00:35.980 matter how fit you are at some point, you have to produce more lactate. So you now don't have

01:00:43.820 sufficient cellular oxygen to go down that first route. So you start making lactate. But if you have

01:00:51.660 enough MCT1 transporters on the outer mitochondrial membrane, you can now bring that lactate in the cell

01:00:59.260 and actually do the reverse of what just happened. Turn that lactate back into pyruvate, pyruvate becomes

01:01:05.020 acetyl-CoA, and everybody wins the game again. The game being won, of course, because now you're making

01:01:10.700 32 units of ATP instead of just the two units you would make converting pyruvate to lactate. So it begs

01:01:17.580 a very important question, which is, earlier when you spoke about what makes Pogacar so remarkable

01:01:25.580 physiologically, one of those things is he must have a boatload of MCT1 transporters on his outer

01:01:33.340 mitochondrial membrane. And that must explain in part why his lactate levels are so much lower than

01:01:40.780 everybody else's at a comparable work level. How much of that is genetic and how much of that is

01:01:46.780 a result of his training? Exactly. So you're right. He has a much higher level to oxidize lactate.

01:01:54.220 So there's a genetic component, no doubt about it. There's also an epigenetic component.

01:01:59.900 And as we know nowadays, the genes are not your fate necessarily. From the genes to be able to

01:02:07.740 be transcribed and form a protein with biological action, the probability is less than 20%,

01:02:14.860 kind of what the science is showing roughly. This is the whole from genetics to transcriptomics,

01:02:21.340 proteomics, and metabolomics. It's about 20% chances that one gene is going to be ultimately expressed.

01:02:27.580 Obviously, we're still trying to understand all this. So these elite athletes, probably they have

01:02:31.980 a much higher possibility. But there's a long journey. And this is where epigenetics occur.

01:02:38.460 It's like what you eat, how you rest, how you train. And I think that the training is also an important

01:02:44.380 component of this. This is, for example, why we train very, very specifically this energy system.

01:02:50.300 And we try to dial in as much as we can, specifically to try to stimulate this bioenergetics

01:02:56.540 system and increase the MCT1s, the transporters for lactate, as well as all the components in the

01:03:03.900 Krebs cycle, which is the mitochondrial respiration. And also to increase also the mitochondrial

01:03:10.140 pyrobotic carrier, because we might discuss later, this is already dysregulated in people,

01:03:15.340 or down-regulated in people who are sedentary. But the thing is like, if you see this next slide,

01:03:20.940 can you see it? Okay. This is what makes the difference in these athletes. So this is a fast

01:03:25.660 twitch muscle fiber and they use glucose. So this is when you're like a high exercise intensity is

01:03:31.900 climbing or running at a high intensity or swimming or whatever the activity you do,

01:03:37.420 you need glucose because glucose is, as you said very well, it yields less ATP,

01:03:42.460 but it does it much faster than the diesel gasoline, which is the fat. But when you use glucose,

01:03:49.340 you're always going to produce pyruvate. The higher the intensity, the more glucose you need,

01:03:54.300 more pyruvate you will need, and the more lactate that you will produce. So that lactate has,

01:04:00.220 as I said earlier, two routes. One route is like it's exported through the MCT force,

01:04:06.860 which is the transport of lactate outside the fast twitch muscle fibers,

01:04:10.860 something that also is trainable, the capacity to export lactate through high intensity exercise.

01:04:16.700 And then it travels to the adjacent slow twitch muscle fibers. We blow up this mitochondria in the

01:04:23.740 slow twitch muscle fibers. This is what will happen. The entrance of that lactate, it goes through

01:04:29.180 another transporter, MCT1 is the same family, but instead of four, it's called MCT1. I mentioned earlier

01:04:35.660 that lactate is converted to pyruvate and acetyl-CoA and goes into the Krebs cycle. So in these

01:04:42.540 well-trained athletes like Pogacar, for example, they have an amazing ability to oxidize the lactate

01:04:48.380 inside mitochondria. At some point, every single human gets to a point that they cannot sustain the

01:04:55.260 effort anymore. But what makes the difference is obviously it's like these guys can do 400 watts for

01:05:00.780 a long time versus a mere mortal who can not even do two strokes at 400 watts. So what happens is like

01:05:07.420 when you have a lot of the right MCT1 and mitochondrial function, this lactate is going to

01:05:13.580 increase and accumulate. And it's not lactate per se, but the hydrogen ions associated to lactate

01:05:20.220 elicit an acidosis of the microenvironment of the muscle, which is something that we know and we have

01:05:25.260 learned also from cancer, the famous cancer microenvironment, which is very acidic. And

01:05:30.380 that's going to interfere with different functions in the muscle with both the contractive force and

01:05:35.020 the velocity of the muscle fibers. I'm not saying that this is the cause of fatigue by no means,

01:05:39.820 because there are multiple theories and we still try to understand the central fatigue as well and

01:05:44.380 everything probably is interrelated or it must be interrelated. But the bottom line is like when this

01:05:48.940 lactate cannot be oxidized, it is exported to the blood. And this is why you see that people

01:05:55.100 with metabolic syndrome, for example, or type 2 diabetes who are characterized by having a very

01:06:00.540 poor mitochondrial function, they cannot during exercise oxidize this lactate. In the moment they

01:06:06.300 start using glucose, which is very fast also because they don't have the slow twitch muscle fibers

01:06:10.940 mitochondria to use fat, they need to rely on glucose. That's that metabolic reprogramming or

01:06:16.060 partitioning they have. They produce lactate, but they cannot oxidize the lactate. That's why this lactate

01:06:22.140 chooses mandatorily the route of being exported to the blood and in the blood then it goes to any

01:06:27.900 tissue in the body. So this is what I meant earlier about what is two millimoles versus one

01:06:33.180 millimole. Whereas Pogacar, for example, he oxidizes a lot of this lactate. So by the time that Pogacar

01:06:40.860 saturates this transporter and this mitochondrial capacity to oxidize lactate, it's a tremendous

01:06:47.260 amount of power output and a tremendous amount of glucose that he puts out. So this is why that

01:06:53.260 one millimole, 1.5 millimole in a world-class athlete necessarily represent the same metabolic

01:06:59.020 status of a 1.5 or 2 millimoles in the blood of a normal person. This is a fantastic tutorial in

01:07:05.820 muscle physiology. And again, this very important distinction between lactate production at the

01:07:13.820 local level and lactate that we measure at the global level. That's the challenge we have. When

01:07:19.420 we are measuring lactate, we cannot impute lactate clearance and lactate production. We can only impute

01:07:26.940 the sum of those. It's originally thought, right, that these athletes, they don't use as much glucose.

01:07:32.940 Well, in fact, that Richard shows and Brooks and his team showed it and others too, that

01:07:38.540 the well-trained athletes, in fact, they use more glucose because they have to. You cannot do 400

01:07:44.780 watts with a massive amount of carbohydrate oxidation. And this is what we also see in the

01:07:49.980 indirect calorimetry, that you see people, recreationals for people with metabolic syndrome,

01:07:54.940 they have like four grams per minute at max carbohydrate oxidation, whereas elite athletes,

01:08:00.620 they can get to six and a half grams per minute. It's massive amount of glucose and they produce

01:08:06.300 a lot more lactate. But the key, it doesn't show up in the blood. It's the rate of appearance in the

01:08:13.500 blood because it's oxidized in the muscle. So it doesn't show up in the blood. It's the balance of

01:08:19.660 lactate production and lactate oxidation without getting to the blood. And this is what it correlates a

01:08:27.020 lot also with fat oxidation as well and the graphs that I was showing earlier.

01:08:33.020 So one of the things I want to ask you about here that is a bit of a confounder when we do this type

01:08:37.740 of analysis is the carbohydrate content within the diet. So I'll share with you my data, but I've now

01:08:45.820 seen this with multiple people, including one individual who's remarkably fit. God, it's how many

01:08:51.900 years now, 10 years ago, I was on a ketogenic diet for three years. And the very end of that three

01:08:57.500 year period was when I kind of got back into cycling. At my fittest as a adult cyclist, I was

01:09:03.260 back eating a lot of carbohydrates, but there was about a six to 12 month period when I was still in

01:09:10.620 ketosis. I was kind of getting back into cycling shape. And I do have one VO2 max test from that window

01:09:18.620 of time, probably six months after getting back to cycling and still on ketosis. I've gone back and

01:09:24.540 looked at the data and they're very interesting. What I would observe is maximum fat oxidation was

01:09:31.420 1.3 grams per minute. And that occurred almost immediately. And it sustained until, so at the time

01:09:41.100 my FTP was about 4.1 watts per kilo, this would have been sustained until about 3.5 watts per kilo.

01:09:50.380 So at 3.5 watts per kilo, I was still oxidizing about 1.2 grams per minute. And then that sort of

01:09:57.740 fell off and glucose became then the dominant fuel source. At the completion of the test, when I was

01:10:04.540 done, you know, when I failed, I was obviously not oxidizing any fat and glucose oxidation was just

01:10:12.220 under six grams per minute, about six grams per minute, about 24 kcal per minute. So I've also seen

01:10:19.980 this with another athlete who's been in ketosis for seven years is a very fit cyclist. Actually,

01:10:27.100 he just sent me his data and it's comparable. In fact, he's much fitter than I was. So his 20 minute

01:10:33.420 FTP test is about 412 watts for 20 minutes. And surprisingly he has decent glycolytic power.

01:10:40.940 So that's the other thing is I never really had good power at the low end because I only cared about

01:10:45.100 time trialing. So it didn't matter how many watts I could hold for two minutes or three minutes. I only

01:10:48.780 cared about one hour, but this guy could still hold 1200 watts for 15 seconds. Even for three minutes,

01:10:57.180 he's north of 500 watts, 600 watts. And again, fat oxidation is, you know, one, 1.5 grams per minute.

01:11:05.020 So it becomes a bit confusing because it would be very difficult to define zone two by maximum fat

01:11:12.860 oxidation. So ketosis is an extreme example, but given how much our Q respiratory quotient,

01:11:19.580 the ratio of VCO2 to VO2 depends on baseline carbohydrate intake. How do we make the adjustment

01:11:26.540 so that we understand and we're not being misled? Because if you just looked at my data,

01:11:32.780 you would dramatically overestimate my mitochondrial efficiency. Is that a situation where you say,

01:11:38.700 well, actually the lactate, and unfortunately I don't have lactate data from that test. So I can't

01:11:43.820 tell you what my lactate levels were doing, but it might not be a problem in the Peloton because

01:11:49.660 you're not going to be in ketosis if you're trying to win the Tour de France. But we do see a great

01:11:54.940 degree of carbohydrate and fat variation in the diet amongst people that we're trying to test. How

01:12:01.180 do you make that correction? My humble opinion, what we see in these cases, because I see them all the

01:12:06.460 time too, is that there's an artifact in the metabolic heart. The metabolic heart measures gas

01:12:13.740 exchange. And then through the equations says, okay, this person must be burning fat or burning

01:12:20.460 carbohydrates. The equations are calibrated on high carb diets, presumably.

01:12:25.340 Yeah. So the thing is like, as you exercise, no matter what fuel you're using, you keep increasing

01:12:31.740 oxygen consumption. But if you don't have much carbohydrates, you're not going to produce much

01:12:36.860 CO2. So that's going to tweak or mislead my stoichiometric equation because the algorithm is going to

01:12:45.500 think that, oh, whoa, he's using a lot of oxygen and not producing enough CO2. So he's got to be

01:12:51.340 burning a lot of fat. That's when you see fats in north of one gram per minute. Those are fat

01:12:56.940 oxidation. I think they're an artifact. And I see this because three days later, when you change the

01:13:03.820 diet of that person, three days later, that person's fat oxidation might be 0.35. So there's no way that

01:13:11.820 the mitochondria adjusts first, like it reflects a very high fat oxidation capacity in someone who

01:13:18.620 we know very well, who is not an elite athlete, whose mitochondrial function is not incredibly high

01:13:24.860 to be able to oxidize so much fat. And in three days, reduces like by three or four times.

01:13:31.020 I attribute this to an artifact of the gas exchange. And this is where looking at lactate,

01:13:37.660 it should give you those parameters. Normally, what I see in these individuals is that you see

01:13:43.020 maximum lactates of two, three millimoles, because simply they don't have carbohydrates.

01:13:50.140 Also the thing where you see that, yeah, my maximum grams per minute of carbohydrates was in the six,

01:13:56.300 but you're in ketosis. So how can you have enough glycogen or glycolytic capacity

01:14:01.740 to elicit such a high carbohydrate production? Even when you're in ketosis, remember my blood

01:14:07.660 glucose is still four to five millimole. I would really like to see this studied because again,

01:14:14.700 even if you're only eating 50 grams of glucose a day, think of how much glycogen you're making

01:14:19.820 from all the glycerol, from all the fat that's being converted to ketone. So, I mean, I think Jeff

01:14:25.900 Volick and Steve Finney have looked at this and when they put people into very, very strict ketosis,

01:14:31.820 but do muscle biopsies, they're still seeing 60% of the glycogen content in the muscle that was there

01:14:39.180 under high carb conditions. I mean, I think my capacity to oxidize five and a half to six grams

01:14:45.180 of glucose per minute was still there. Just took a long time to get there, I think is the difference.

01:14:50.060 So I guess the question is, if the VCO2 estimation is off because of the stoichiometric coefficients,

01:14:58.620 do you think the VO2 estimation is off also? No, I don't think so because as you said very well,

01:15:05.500 ketones are used for energy purposes. And then we have a third element, which is absolutely key

01:15:11.340 in bioenergetics, which is glutamine. Glutamine is highly expressed and utilized. We have learned that

01:15:18.060 from ICU patients. ICU patients is a great model to study metabolism or stress metabolism. ICU patients,

01:15:26.860 they utilize for wound healing about three times more glucose at rest than what we have. And it's

01:15:34.220 part of the healing process. Glucose is instrumental for cell proliferation, wound healing, and part of it

01:15:40.060 is lactate too as a byproduct in a single molecule. But we see that, and this is a study that we published,

01:15:46.140 looking indirectly a methodology to look at glycogen. It's a pilot study we deal with ICU patients,

01:15:52.300 they don't have glycogen. When you say they don't have glycogen,

01:15:55.820 you mean liver glycogen, muscle glycogen, or depleted by how much? Depleted to what level?

01:16:01.740 Let's say that you have 500 grams of glycogen if you have a full high carbohydrate diet. So that might

01:16:08.940 not be the case of someone entering the ICU. First, because they might not be elite athletes,

01:16:13.740 or they might have maybe 300 grams, or they might not have that adaptation to homework glycogen. So

01:16:19.260 let's say they have 300 grams or so. By the time they get into that condition, the body uses about

01:16:25.740 three times the glucose at rest. Now, an athlete used that same glucose, but at higher intensities,

01:16:33.740 but only for a reduced amount of time, two hours, three hours, four hours. Whereas the ICU patient

01:16:39.340 is 24-7. So eventually, the body is going to run out of glycogen in the muscle, or it's going to be

01:16:46.060 under huge stress. The body has evolutionary mechanisms. This is a wonderful machine,

01:16:51.980 and it needs to continue. So it increases another route, which is glutaminolysis. So glutamine is an

01:16:59.340 excellent source of fuel. It enters directly the mitochondria. We have seen in our publication that

01:17:05.260 we're going to show when we publish it is that when we inject mitochondria with glutamate, it's

01:17:12.140 incredibly well oxidized. And what's the source of glutamate in these ICU patients? Are they

01:17:18.700 breaking down muscle? This is where cachexia comes into place. We know that pretty much every single

01:17:24.620 ICU patient becomes cachectic or suffers from muscle waste. And this is the syndrome,

01:17:29.980 post-ICU muscle waste syndrome. Why do they get cachectic or catabolic? And why they overexpress

01:17:37.340 tremendously levels of glutamine? Because they need it for either enter the Krebs cycle for energy

01:17:43.900 or for gluconeogenesis. So this is one of the things that we learn a lot from ICU. These ICU patients,

01:17:50.860 they have hyperglycemia, yet they're not giving them usually because they have hyperglycemia. It's

01:17:56.300 true too that in the acute ICU phase, they also have insulin resistance. But obviously this

01:18:03.900 hyperglycemia and ICU doctors historically have seen this. It's like, whoa, this patient has

01:18:09.180 hyperglycemia, poof, off the chart. So obviously we're not going to give them IVs of glucose. We're

01:18:14.620 going to give more protein and glucose. I mean, and in fact, glutamine has shown that increased survival

01:18:20.220 rate in these patients. Where is this hyperglycemia is coming from when you do not have glycogen?

01:18:26.460 It comes probably from proteolysis, where you break down protein from your muscles to release glutamine.

01:18:35.100 We would only know that if we understood hepatic glucose stores, because regardless of how much

01:18:39.180 glycogen is in the muscle, it's never going to make its way into circulation because the muscle

01:18:44.300 can't fully dephosphorylate it. So do we have a sense of what the hepatic glycogen content is?

01:18:50.700 Because I can't imagine the body would ever let anything compromise that, given that if the liver

01:18:58.380 can't produce glucose continuously, the brain dies. So it might be that this is true, true, and

01:19:05.500 unrelated, right? It could be that the muscles are depleting glycogen because of high utilization,

01:19:11.420 but the liver through gluconeogenesis has plenty of glucose. That's what's making it into the

01:19:18.940 circulation because of hypercortisolemia, because of other acute phase reactants. And so we have

01:19:25.500 hyperglycemia, but it's all being mediated by the liver, which has no trouble maintaining glycogen

01:19:31.020 levels. And again, from an evolutionary perspective, you much rather err on the side of hyperglycemia than

01:19:37.340 hypoglycemia under a period of stress. Absolutely, necessarily. And that's, I think, what's the source

01:19:42.860 of that gluconeogenesis? It's probably glutamine olysis coming from the muscle. So this is what

01:19:49.660 my hypothesis is, right? That those muscles, they eat themselves to feed themselves or to feed the rest

01:19:54.540 of the body. So that would suggest that exercising ICU patients would be important. Getting some load-bearing

01:20:01.820 resistance, even, of course, they're in a bed, but moving their extremities against a load,

01:20:06.780 supplementing with amino acids, could actually improve outcomes.

01:20:10.620 Yeah, absolutely. There's a lot of research in this area. My colleague, Paul Wiesmeyer, who used to

01:20:15.500 work here with me at the university, now he's in Duke. He's doing a lot of research and practical work

01:20:21.100 with that. With this, it's like, yeah, this hyperglycemia probably comes from gluconeogenesis.

01:20:26.380 Going back to where we started, yeah, it could be that there's a lot of glutamine released,

01:20:31.660 you know, when you're also ketoacidosis state as well, especially in the first phases of that.

01:20:37.820 We know cortisol is very high at first. The same thing that we see in ICU patients, that

01:20:42.780 two main parameters that are predictors of mortality at the ICU is hypercortisol anemia,

01:20:48.940 high cortisol levels, and high lactate levels, right? They both are completely related.

01:20:54.060 But anyways, yeah, I think this is fascinating. There's a great model

01:20:57.180 to understand metabolism, stress metabolism of these patients and the ICU patients. And

01:21:03.260 that's the other thing too, once you exercise, and this is a very important concept for people

01:21:07.820 with type 2 diabetes, with type 1 diabetes, and hyperinsulinemia is that you have insulin resistance

01:21:14.940 and you have difficulty to translocate, therefore, to translocate the GLUT4 transporters to the surface

01:21:21.580 of the muscle, the sarcolemma. And we know that probably the first tissue or organ where diabetes

01:21:29.260 debuts, starts, is the skeletal muscle. Because about 80% of the carbohydrates that we have,

01:21:35.260 they're oxidized in skeletal muscle, and because we're at rest, should be oxidized within the mitochondria

01:21:41.740 of skeletal muscle, that pyruvate. This is what we've done research and seen it clearly. But when you have

01:21:47.420 insulin resistance, you cannot translocate those transporters. Now we have a second way to translocate

01:21:55.020 those transporters that not many people know about, and that's muscle contraction.

01:21:59.580 This is the insulin independent glucose uptake, which also seems to be heavily dependent on fitness.

01:22:06.380 The fittest athletes here require virtually no insulin to translocate glucose into the muscle

01:22:13.740 through the insulin-independent pathway. I think we may have even discussed this,

01:22:18.060 I don't know, over dinner one night, but you look at the type 1 diabetics who are highly,

01:22:23.180 highly active, require very little insulin. Exactly. This explains hypoglycemia in these

01:22:30.300 patients shortly after they start exercising. They might have something to eat and they inject

01:22:34.860 themselves with insulin, and there's nothing you can do once you have insulin on board. So that insulin

01:22:40.220 is going to translocate those transporters and it's going to start bringing insulin inside. I mean,

01:22:45.180 sorry, glucose. In the moment you start exercising, you do the same function through contraction of

01:22:50.300 exercise of the muscles. So you have two mechanisms acting at the same time, pulling more glucose inside

01:22:57.500 the cells, leading to hypoglycemia. So this is what we learned a lot with persons with people with type

01:23:02.940 1 diabetes and exercise, and then we can prevent them. So for example, do not inject yourself before

01:23:08.780 exercising because exercise alone is going to take care of that glucose. But we can take these concepts

01:23:15.740 also with people with type 2 diabetes, that they have an insulin resistance or pre-type 2 diabetes.

01:23:21.180 It's like, why not exercising right after you eat that carbohydrate you have? You have insulin

01:23:27.580 resistance already, but when you exercise, you're not going to need that insulin. And yet you can

01:23:33.180 translate those transporters and you bring glucose levels down. And I'm sure that you see this all

01:23:38.620 the time where your glucose sensor. Yes. I've gone periods of time when I've done incredibly

01:23:44.860 frequent lactate testing. So lactate testing every 30 minutes for a day or something insane like that,

01:23:50.140 which is incredibly expensive and incredibly painful on your fingers. But you learn how much,

01:23:55.260 for example, a meal impacts lactate. So when I wake up in the morning, my resting lactate level varies.

01:24:05.500 I've been tracking this over a period of probably 40 days. So 40 days of tracking. What range do you

01:24:12.780 think my morning resting lactate level has been over a 40 day period in the morning? First thing in the

01:24:18.380 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

01:24:27.980 a pretty big variation and probably median level of about 0.8. Yeah. In the neighborhood of wine,

01:24:35.980 which is normally in the fit individual. Yes. So then what I can do is I can eat a very high carb

01:24:41.820 breakfast and go and do a zone to ride or don't eat anything at all and go into a zone to ride,

01:24:49.900 very different lactate performance curve. So the high carb meal raises lactate. So it becomes a bit of an

01:24:56.620 artifact in a way, which now gets me to, we've talked about this at the level of

01:25:02.540 the most precision possible, the way in which I would measure it in a patient. You would measure

01:25:08.380 it in a world-class athlete where we have the ability to do indirect calorimetry and lactate testing.

01:25:14.860 But now I want to talk about it in the way that we train people, normal people. So we've talked about

01:25:21.580 this call it difference between the lactate level that you measure in the blood, which is now heavily

01:25:29.020 influenced by production and clearance. And then we've talked about the gold standard, which would

01:25:33.820 probably be fat oxidation, but even that can be confounded. But let's take off the table,

01:25:39.100 the people who are consuming a high fat, low carbohydrate diet, because that confuses things a

01:25:43.500 bit. If I have a patient and I'm looking at their biometrics and we do a zone two test based on

01:25:51.580 looking at their fat oxidation during an escalated test of part of a VO2 max test. And it comes back

01:25:57.980 that their maximum fat oxidation, which is 0.3 grams per minute occurs at a wattage of 1.5 watts per kilo.

01:26:08.780 That's a pretty average person. And I say, I want that number higher, both the absolute number of

01:26:14.700 fat oxidation, but where it occurs on the graph. Now I want you in a year to be 2.5 watts per kilo.

01:26:22.860 Let's talk about two things. One, how they should train. And that means duration, intensity,

01:26:29.420 frequency, et cetera. And secondly, what we should use as the readout to know we're in the right training

01:26:37.740 zone, given that they won't be able to train daily or weekly or whatever frequency within

01:26:42.380 direct calorimetry. And by the way, let's assume that some people will want to use the point of

01:26:48.380 care lactate meters and some people will not. Let's start with what's our surrogate for training zone,

01:26:55.020 starting with what we knew. So we learned that 1.5 watts per kilo was maximum fat oxidation,

01:27:02.220 but we want to increase that to 2.5. So what metric do you use to train them?

01:27:07.100 Normally what I do is like starting with the metabolic test. I translate that information into

01:27:13.020 whether it's watts or speed or heart rate. All of them normally, they correlate quite well

01:27:19.660 and you can individualize it. There are people that don't have a power meter. Okay. You can do

01:27:23.740 heart rate, for example, or people that just obviously they run or they walk can do speed or

01:27:28.860 heart rate as well. Very good surrogate. So that's the first metric, the surrogate.

01:27:33.420 Then it's about, at least from my experience, the three main principles that I've learned over the

01:27:40.540 years and how to apply this. So first is frequency. Before we go to the frequency and the duration,

01:27:47.420 I do want to go back and ask you another question. We have some patients who don't want to use a lactate

01:27:53.500 meter either because it's cumbersome or somewhat intimidating. We also add another metric, which

01:27:59.580 is relative perceived exertion, RPE. I'll tell you what my rule of thumb is, but I'd like you to

01:28:06.460 sharpen it, refine it, throw it out, make it better, whatever. I tell patients based on my experience,

01:28:12.380 so I don't know how extrapolatable that is, when I'm in zone two as confirmed by lactate levels.

01:28:19.820 So call it 1.7 to 1.9 millimole, which is what I target. I can carry out a conversation because I

01:28:26.940 do most of mine on a Wahoo kicker. I put my bike on a Wahoo kicker. I can spend the entire 45 minutes

01:28:32.700 on a phone call, but it's not as comfortable as this discussion here. I'm a little more strained,

01:28:39.580 but if I can't talk, if I feel like I can't talk, I'm too high in the intensity. Do you think that

01:28:46.620 that's a reasonable surrogate for people to use across the spectrum of not particularly fit all

01:28:53.500 the way up to Pogacar? 1,000%. And I use the same metrics also with people who you mentioned,

01:29:00.300 they don't want to do a lactic meter or they don't have access. I get hundreds of emails about

01:29:06.700 where can I do this test or is there anything that I can do? And I agree 100% with everything that we know

01:29:13.500 at the granular cellular level by injecting fuels and substrates directly into the mitochondria.

01:29:19.260 We cannot get more cellular level and scientific that the surrogate or the specific section

01:29:24.620 exertion, it works beautifully. I know that people are coming out with different algorithms based on

01:29:29.500 higher variability or DFA, one alpha, et cetera. But honestly, I agree 100% with you. I always tell

01:29:36.780 people if you can exercise whatever the exercise you do and maintain a conversation like you and I are

01:29:42.060 doing, you're way too easy. You're probably zone one. If you can talk, but it's some form of strain,

01:29:48.140 you can talk for two hours, but we're talking a little bit like that.

01:29:53.100 You're just at that threshold. Put it this way. The other litmus test I tell people is

01:29:57.740 the person on the other end will know you are exercising.

01:30:00.540 Exactly.

01:30:01.260 You will not be able to mask from them that you are exercising.

01:30:04.460 Exactly. And in fact, I have many conference calls with people that I know to be respectful,

01:30:09.580 but I do it on the bike. They call me and I'm on the bike, either outside or in the trainer. And

01:30:14.460 they're like, you're exercising, right? Because you can feel it. But yet, I can maintain a full

01:30:19.020 hour meeting on the bike without bothering the other person because they can understand me.

01:30:23.340 But as I said, if you cross to the point where you cannot maintain that conversation,

01:30:28.540 you need to breathe much faster because you're producing more CO2. And that's probably because you're

01:30:33.660 already transitioning from the slow twitch muscle fibers to the fast twitch muscle fibers,

01:30:37.980 more glycolytic, more lactate, more CO2, more buffering capacity. So it seems old school,

01:30:44.140 but it works beautifully. Agreed. And the other thing I do,

01:30:47.420 because I really like people to triangulate and give them a starting point. So if someone has not

01:30:52.220 done a metabolic test yet, and that's usually the case by the way, is that we're starting with just

01:30:56.620 a zone two training protocol. I also give them some ranges on heart rate. Now here I have found much

01:31:02.460 more variability. So the first thing I say is to do this, you do need to know your maximum heart rate.

01:31:07.900 Not your predicted maximum heart rate, but your actual achieved maximum heart rate.

01:31:12.300 In my experience, personally, my zone two is actually at about 78 to 81% of my maximum heart

01:31:21.820 rate. But I know that for less trained people, it's lower. So I tell people a broad range of 70 to 80%

01:31:30.460 of your realized maximum heart rate is a good place to start and then make adjustments based on relative

01:31:38.860 perceived exertion. I agree. What do you know about heart rate? I would agree that I usually also say

01:31:45.500 the same thing somewhere between 70 to 80. That being said, right, if you want to be very

01:31:50.060 precise, it's a big range. Exactly. So you can be at 70, let's say at 1.7 millimoles. And then at 80,

01:31:58.380 you can be at 5 millimoles. You're completely away from one zone. But as you said, it's a good starting

01:32:03.260 point. And as you very well said, and I agree 100% with you, it's like, yeah, then you tweak it with

01:32:08.700 your perceived exertion. The other thing too, with the heart rate, and this is where the heart rate

01:32:14.540 variability, there are different interpretations. So the modern interpretation of heart variability

01:32:20.780 is the differences between bit to bit. And that's where there are different algorithms. For me,

01:32:26.380 the heart rate variability, it's more at a broader spectrum, and it's more on the adrenergic

01:32:32.700 activation that you have. So for example, you're fatigued today. First of all, normally, you're going

01:32:38.620 to wake up with your resting heart rate a little bit higher than normally. If your normal heart rate,

01:32:43.820 let's say it's 50, and you're in fatigue, you might wake up with 65. So that alone is a

01:32:50.380 heart rate variability concept. It varies from the norm to one day. So that's our red flag that you

01:32:56.540 might be tired that day. It might not be super sensitive, but it is very sensitive for elite

01:33:00.860 athletes, without a doubt. The second aspect is like when you go out there and exercise. As you

01:33:06.220 might see, there are days that you are like 130 beats per minute, whatever you think you're going to

01:33:11.820 is 130, 138, for example. But some days, it's really hard to get the heart rate. You're already

01:33:19.420 struggling at 110 beats per minute or 115 beats per minute, where that's not the norm. That's another

01:33:25.740 deviation. That's a variability of the heart. So this is what I've been historically used for heart

01:33:31.260 rate variability, which tells me a lot more information. This is what all the athletes

01:33:36.460 also tell you like, man, my heart rate doesn't get up today. You see on training peaks, you know,

01:33:41.740 you see when someone is fatigued, they do an interval and they know they always 180,

01:33:45.980 185, let's say the lactic threshold. And today they cannot get up until more than 170.

01:33:51.820 You see in the competition, the first week of the Tour de France, their maximal heart rate,

01:33:56.460 let's say it's 195. Last week, the maximal heart rate is 170. That's what I interpret by

01:34:03.180 heart variability. And I know that a lot of people might criticize me because all that has nothing to

01:34:07.740 do well. No, I think it's macro versus micro. I agree. I read it as macro versus micro. I'll share

01:34:13.260 with you an interesting self-experiment I've done a couple of times. It's not pleasant,

01:34:17.180 but it's interesting. If I take a huge dose of a beta blocker and the only beta blocker you can do

01:34:23.420 this with, if you have low blood pressure, as I do, you have to be careful. But propranolol

01:34:28.060 is fine because it really, it disproportionately lowers heart rate, but not blood pressure.

01:34:33.420 But I've done this experiment a few times to test an idea, which is,

01:34:37.340 would taking all of the gas out of my heart rate, allow me to push harder and generate

01:34:45.340 a higher zone too. And it turns out it does. So my zone two is just under three watts per kilo.

01:34:52.220 I really want to talk with you about getting over three watts per kilo. I'm still furious because

01:34:56.060 in July, remember I was at 2.95. I was just kissing on the door of three. I've come back,

01:35:03.260 you know, I'm now at about 2.75 to 2.85. So I've lost a bit.

01:35:07.740 It's aging too.

01:35:10.060 We're going to talk about training in a moment. So, and for me, I'm at that upper end of maximum

01:35:14.700 heart rate. So I'm going to be doing that at about 80, 81% of maximum heart rate. But if I took

01:35:20.220 propranolol, 60 milligrams of a time release propranolol, I will be able to get over three

01:35:26.140 watts per kilo. And I'll do it at a heart rate of 68% of maximum, but it feels horrible. I feel

01:35:35.100 like I'm going to die. It is the worst feeling in the world. And it's not pain. I don't know how to

01:35:42.700 explain it other than it feels like what it feels like when you're over-trained. It feels like you

01:35:47.420 just can't get moving. It's like an engine that's being taken from 9,000 RPM to 6,000 RPM,

01:35:54.300 but yet somehow is able to generate the horsepower, but it just doesn't feel right. So that's my drug

01:36:00.860 cheating way to get over three watts per kilo, but more to illustrate the point, right? Which is when

01:36:05.500 you put the governor on heart rate, you can get there at a lower heart rate. Subjectively,

01:36:10.720 it's a miserable feeling. Yeah. And this is kind of in a way what happens when you're fatigued,

01:36:15.940 when you don't have enough fuel. Again, going back to like my heart, it doesn't get up today. And I'm

01:36:20.920 struggling if you were taking some beta blocker. But the thing is that it has to do a lot with fuel.

01:36:27.000 For example, and I experiment this a lot too. I try to understand how this works. So I do maybe

01:36:32.840 intermittent fasting for a few days and I go out there and good at adjusting at that. And I cannot

01:36:39.920 do that. I know others can do it and I admire that, but I can see my heart rate right away.

01:36:45.440 When you don't have enough glycogen in storages, it's very possible that adrenergic activity is

01:36:50.560 decreased. You need to break down glycogen. And we know that what takes to break down glycogen is

01:36:55.960 phosphorylase in the muscle, and that's directly regulated by catecholamines. So when there's a

01:37:02.660 decrease in glycogen, this is my hypothesis, right? When there's a decrease in glycogen storages,

01:37:08.200 because of the evolutionary mechanisms that humans have, the brain is the boss. The brain says like,

01:37:13.580 I don't care about your legs, but don't use up all the glycogen because you have to give me and the

01:37:18.640 liver has to give me glycogen as well. So I'm not going to shut you down completely of breaking down

01:37:24.160 glycogen, but I'm going to slow you down. So I'm going to release less catecholamines so that you

01:37:30.020 break down less glycogen. The collateral effect of that is the heart because the heart contractility

01:37:37.000 is regulated by catecholamines as well. So this is why using that, my version of heart rate variability

01:37:42.760 it's quite useful. I've been using it incredibly successfully for 25 years with my athletes

01:37:48.060 where I see that, hey, your heart rate is not going up today. It usually is 185, 190, for example,

01:37:54.440 when you do a lactic threshold, for example, and today it was 170. So tomorrow, take it easy or

01:38:00.120 pile up on glycogen, I mean on carbohydrates, or take an easy day and you'll see how you're going to be

01:38:04.840 very responsive the next day, the following day. And in fact, that's what happens. I would say 10 out of

01:38:10.440 10 times, but let's say 9 out of 10 times, right? But I do that with myself as well.

01:38:15.240 And I see is also, I work a lot with the head. You think a lot and the brain uses about 100 to 125

01:38:21.900 grams of glucose daily. When you go, and I don't know that fact, when you work a lot of hours and

01:38:28.700 thinking and thinking and thinking and stressed, the brain might need a lot more glucose. So that's

01:38:34.660 training your glycogen estranges from the brain, probably, and even from the muscles, because the

01:38:39.140 muscle can release glucose to be utilized as well. Yes. The muscle has phosphorylase and can be

01:38:45.220 degraded the glycogen and that glucose can go to the circulation as well to feed other organs.

01:38:51.220 I didn't realize that we had glucose 1-phosphatase in the muscle. I thought the muscle glycogen

01:38:56.080 fate was sealed in the muscle.

01:38:58.380 It's possible. There are a few studies. I'm happy to send them to you. I cannot refer them

01:39:02.540 out of memory, but the muscles can also release glucose and export glucose outside.

01:39:09.760 I assume this is a relatively small amount compared to what the liver is doing.

01:39:13.720 Yeah, absolutely. Exactly. But it's possible too. So those days where I'm thinking a lot and I'm not

01:39:19.420 very stressed and I'm not dieting or anything, I just go out there and I'm dead. And I'm sure that

01:39:25.600 many people listening to this feel the same way. Like, what the hell is going on today? I don't have

01:39:30.460 energy at all today. And you will see that your heart rate doesn't get up those days. And you can

01:39:35.780 get to that by just training five hours a week or seven hours a week. And sometimes people say,

01:39:40.600 like, look, I cannot be overtrained because I only train five hours a week. Yeah, but you're overworked.

01:39:46.240 That's a big artifact when you're training. That's what most of us aspire to pre-retire

01:39:51.120 before 60, you know, so we can have more time to exercise and less time to work. But yeah,

01:39:57.240 that's what I do this. I take a day off completely. I sleep more. I increase my

01:40:02.460 carbohydrate intake. And the following day, I can even break my PR on a climb or something. I feel

01:40:08.620 like a million dollars. So resting recovery is key for that. I think this is a very important point.

01:40:14.680 And it's actually something I've only been able to pay attention to in the last year,

01:40:18.820 which is I used to judge my performance by training load. I used to use training peaks when I was

01:40:27.360 training. I don't anymore. But the concepts of acute and chronic training balance, any day that

01:40:32.200 was suboptimal could be explained by training volume in some capacity. But now my training volume

01:40:38.640 is relatively low. It's 10 hours a week of total training. That's both cardio and strength. This is

01:40:43.640 not a lot of training. And yet when I'm under stress work-wise, I'm just doing too much. I don't

01:40:49.920 even use the word stress. It has a real negative connotation to it. I just mean when I'm overworked,

01:40:55.840 when I'm doing too much, my performance, I have to either adjust my parameters for what I deem

01:41:02.220 successful, or I just have to cut back on the actual training a little bit to make time for more sleep or

01:41:10.160 more relaxation. So I think that's a very important point that is easily lost. So we've got a very good

01:41:17.140 handle on the metrics we're going to be using. So now let's talk about two scenarios. The first is the

01:41:24.060 person who is new to this type of training. So they've listened to this podcast or they're one of

01:41:29.900 my patients and I've made the case convincingly to them that you really need to do this type of

01:41:35.520 training. I want to come back by the way, to a justification for that. So let's explain why

01:41:41.580 high intensity training is not sufficient, but we'll park that for a moment. But they really don't

01:41:46.140 have much of a background in this type of training. Maybe they do some high intensity training. They do

01:41:50.340 some weights, they play some tennis, but they really don't do the sort of steady state sustained

01:41:56.100 cardio that we're talking about. How would you structure a training program in dose, duration,

01:42:01.680 frequency for that individual? And tell me a little bit about the choices that you would make if they're

01:42:07.480 agnostic to running, walking, cycling, rowing, swimming. I have my biases there, but I want to

01:42:14.640 kind of hear what you have to say about it. I want to apologize to many of your audience because I get

01:42:20.560 a lot of emails asking me about these questions and it's hard to keep up. Well, that's why we're doing

01:42:25.320 the podcast. So you don't have to apologize. It's easier to do it this way. I appreciate it this way,

01:42:29.920 but see, I get emails. And before I used to see people here at the university, but now the

01:42:34.800 university don't have these services. I'm trying to convince them that the services are important

01:42:39.600 to offer to population. But anyways, I want to apologize because I cannot answer to everybody.

01:42:44.880 I have the three main rules or parameters that I have learned over the years. So one is the duration.

01:42:50.500 We have in mind sometimes that this is like endurance training, long days. Like I only have it six

01:42:56.280 hours a week or seven hours a week at most to do this type of training or less. There's no way I can

01:43:01.820 do that. It's usually less because they might have six hours a week for total exercise. And we're going

01:43:07.620 to take half of that for strength training. Exactly. Which is very important. As you know,

01:43:12.320 it's where I fail because I should do more of that. And I try to get a little bit more of time to do

01:43:18.200 that. Oh, it's not easy, but I aspire really to dial that in. But yeah, you're right. They might have

01:43:23.280 less than six hours. And they might think like, well, I'm not an endurance athlete. So you need

01:43:28.080 to do four hours to accomplish this. So therefore I'm just going to move to do just high intensity

01:43:33.180 and just get out of the way. That's not completely true. You can accomplish very important mitochondrial

01:43:39.980 adaptations and very important metabolic adaptations by exercising one hour. Let's start by the duration.

01:43:46.700 If you try to do that one hour to one hour and a half range, you're on target.

01:43:51.220 Is that total or one setting? Meaning is it one to one and a half hours per week? Or does that need

01:43:57.980 to be in one continuous exercise bout? So the frequency that I see is that this type of training

01:44:04.960 ideally needs to be done between three to four days a week, ideally. And how can I know this? I know

01:44:11.860 this because I've seen in the laboratory everything. The person who trains one day at these zones or two

01:44:18.040 days or three days or four days or high intensity, low intensity, and I see the adaptations. How do I

01:44:23.100 see the adaptations? Again, looking at fat oxidation, lactate cleanse capacity, both surrogates of

01:44:28.340 mitochondrial function. I've been identifying the dose of that training. So if you train once a week

01:44:34.240 there, chances are that you're going to deteriorate over time. And especially as we age, something that

01:44:40.140 I see, for example, in high intensity exercisers and bodybuilders, they have a very poor amount of

01:44:46.720 kind of function compared to people who do more, a little bit of everything. So one day a week is not

01:44:53.200 going to work. Two days a week, it might maintain what you have. But if you are new to an exercise

01:44:59.680 program, it might not be enough. Three days a week, now we're starting to see for sure. Four days a week,

01:45:06.100 now we're talking. Ideally five days a week or six, but not everybody has obviously six days a week to

01:45:11.120 train. But I think that you are a very busy guy. I'm a very busy guy. Try to squeeze four or five days a

01:45:17.500 week, maybe six in the summer. But four or five days, it's a chief of work for most individuals. And put

01:45:23.060 aside an hour to an hour and a half. So I would say that four days a week is ideal. That's the first

01:45:29.100 principle. The second principle is the duration. Going back to what I was saying, with one hour,

01:45:34.440 maybe Poratzer needs four hours, five hours, to keep increasing those huge mitochondria for a long

01:45:41.460 time. But a mere mortal, especially someone who might be pre-diabetic or might be out of fitness

01:45:47.460 or hasn't exercised in a long time, or someone who's coming from a disease or a mother who just

01:45:53.100 had a baby and has been out of say for a while, one hour, if you walk or if you run, it might be very,

01:45:59.840 very good for you. One hour walk or run, you might have to bring it up. That's part of the plan too.

01:46:05.740 Cannot start off the bat with one hour. You might start by 20 minutes, 30 minutes, 40 minutes,

01:46:10.380 increasing it. It may be about an hour. And if you bike, for example, about an hour, 20 minutes,

01:46:16.420 hour and a half, that's what I see that if you do that for four days a week, things are starting to

01:46:21.860 move. Even if you bike on a trainer where you can be much more efficient and you can really get

01:46:27.900 straight to the wattage and stay there. We tell patients, again, it depends where they are in

01:46:32.540 their cycle, but if they're starting out, I mean, we'd be happy if they give us 30 minutes,

01:46:37.540 three to four times a week of dedicated exercise. I can't do zone two on the road. I can really only

01:46:43.460 do it on the trainer. I just can't stay at a constant level on the road with starting and

01:46:48.360 stopping and wind and hills and stuff like that. That's a very good point. That's why an hour and a

01:46:53.460 half on the bike, it might actually be one hour or so because you have all these artifacts. But

01:46:59.160 you're right. When you're on the trainer, you isolate everything completely. And what I also

01:47:03.140 recommend is about an hour if you can get there. But again, you know, like, yeah, sure. You might,

01:47:08.080 to me, it's, it feels like a torture sometimes to be an hour on the trainer. I hate it. I like to be

01:47:13.960 outside, but we have had to do it. I do it. I watch a movie or just catch up on work. I have one

01:47:19.800 special desks where I can type or read articles or answers and emails. Low key activity because

01:47:26.540 again, you know, you're not very sharp to think very intellectually. But yeah, one hour might do

01:47:31.220 the trick. What I've seen is like, yeah, in those people who haven't done much at all, even 30 minutes,

01:47:36.180 20 minutes might start moving the needle. But eventually it's not enough dose. The body needs

01:47:42.460 more. If you can get to a goal about an hour to an hour and a half, that should really work in my

01:47:48.480 modest opinion and my experience. So that's the duration. And the third is always the frequency,

01:47:54.040 which we have talked about, which is usually the zone two. That being said, I think that it's also

01:48:00.160 important to stimulate other energy systems like the glycolytic system. And again, continue with the

01:48:06.620 model that we do with elite athletes. People think that elite athletes, whatever the sport are,

01:48:12.700 all they do is high intensity all the time and intervals, intervals. And it's the exact opposite.

01:48:18.480 If you look at the workload of an elite athlete, whether that elite athlete is, especially in

01:48:24.160 individual sports, it's easier to see this, whether it's a triathlete or a cyclist or a marathon runner

01:48:29.020 or a swimmer, a hundred meter swimmer is under a minute. Maximal exercise. If you look at the

01:48:35.380 workload, it's very similar. The majority of the sessions are in the lower intensity. They're not

01:48:40.840 intervals, intervals, intervals. And I always say we cannot be so naive to think that the best coaches

01:48:46.560 and athletes in the world haven't figured this out when they're always trying new things and they

01:48:50.080 want to try the cutting edge things. Obviously, they have said, oh, our sport is swimming under a

01:48:56.200 minute. All we need to do is like intervals, intervals, intervals, intervals. Well, if you

01:49:00.840 look at what swimmers do, they train. And if you ask Michael Phelps, hours and hours and hours and

01:49:07.120 hours and hours. Because if you can travel through the competition in that under a minute,

01:49:11.760 with a slightly better function to clear lactate, even if it's one millimole or less,

01:49:18.660 the muscle contraction force might be improved. So all the hours and hours and hours might be that

01:49:25.760 just to improve a fraction of a second. But anyway, so this is what I'm seeing that these concepts of

01:49:30.520 glycolytic capacity and high intensity training, they're necessary, but they're not what the elite

01:49:37.220 athletes do. The elite athletes have the best metabolic function of any humans. Why not try to

01:49:43.900 imitate their philosophy of exercise? And so just to come back to the frequency duration question,

01:49:50.480 I think the answer to the following question is going to be the more frequent training sessions.

01:49:55.640 But if you compared four training regimens that were four hours a week each, one of them would be

01:50:02.260 four 60 minute sessions. One of them would be three 80 minute sessions. One of them would be two two

01:50:10.400 hour sessions. And then one of them would be one four hour session. So it's the same total volume

01:50:14.940 and notwithstanding the brain damage of one four hour session. Is it safe to say that the four 60

01:50:21.220 minute sessions, because it's a higher frequency would be the optimal one there? I would say so. I think

01:50:28.160 from my experience that it might be better is the frequency. It's like if you take a medication,

01:50:33.120 if you take a medication twice the dose and only three days a week, might not work as well as if

01:50:38.760 you take the right dose every day. Because at the end of the day, we're talking about it. The whole

01:50:43.360 exercise is medicine, right? How do we prescribe that? What's the dose? What's the frequency? I'm assuming

01:50:49.060 that you will have to take it as many days as possible. That would say that it's better to do that.

01:50:54.560 That being said, obviously, if you have the weekend and you have the possibility,

01:50:59.480 which I don't have to do three hours, go ahead. And another thing I wanted to point out is that

01:51:05.200 for many people, they need that adrenaline for training. So other people don't care. Other

01:51:10.540 people say, whoa, I love this. I don't like to kill myself into high intensity, but I think you need

01:51:15.480 to do some high intensity, right? At some point. I want to talk about that. So how do we bring in the

01:51:19.900 other energy systems? Of the four pillars of exercise in my world, stability, strength,

01:51:27.400 low-end aerobic, which I describe really as, talk about it as kind of mitochondrial efficiency,

01:51:32.540 and then high-end aerobic, which is peak aerobic capacity slash anaerobic performance. So anaerobic

01:51:39.440 power, peak aerobic, low-end aerobic mitochondrial efficiency, strength, stability. Of those four,

01:51:46.900 I, for some reason, struggle to make the time for the peak aerobic in part because one, it's the

01:51:55.300 least enjoyable. If we're going to be brutally honest, if you're doing it right, it hurts the

01:51:59.120 most. It's also no longer as relevant because I don't compete at anything. I actually really enjoyed

01:52:04.980 that type of training when I competed because you have to spend time in that energy system and you see

01:52:10.180 the rewards of 60 minutes of repeating two-minute intervals or something like that. So if we're really

01:52:16.860 talking about this from the lens of health, maximizing health, the data are unambiguous that

01:52:23.360 VO2 max is highly correlated with longevity. There are not many variables that are more strongly

01:52:29.840 correlated, but the levels don't have to be that high. Pogacar's VO2 max is probably 85. It's probably

01:52:36.300 in the 80s at least in terms of milliliters per minute per kilogram. But someone my age to be

01:52:44.120 considered absolutely elite, which means the top 2.5 to 2.7% of the population, which carries with it

01:52:51.200 a five-fold reduction in risk to the bottom 25% of the population. My VO2 max requirement is about

01:52:58.400 52-53 milliliters per minute per kilogram. So the question is, can I use that as the gauge for how much

01:53:08.300 high-intensity training I need to do basically just enough to make sure I maintain that VO2 max? Or do you

01:53:14.820 think about it in a different way? Well, I think about it more by energetics, energy systems. Ultimately,

01:53:21.140 and we know that longevity is also high-related with mitochondrial function and metabolic health. I think that

01:53:28.220 more and more, and this is what you see in so many fields in medicine nowadays, everybody is stumbling

01:53:34.580 upon mitochondria. So there's an aging process where we lose mitochondrial function, and there's like a

01:53:41.040 sedentary component where we lose mitochondrial function. I wish that we could have a medication,

01:53:47.080 a pill that you could take it and increase the mitochondrial function because it would increase

01:53:50.420 metabolic health and longevity. But the only medication that we know is exercise. With an exercise,

01:53:56.860 the dose that we see that improves the most, and also is sustainable in the long term,

01:54:01.940 which is another important concept. Very high-intensity training is not sustainable. Very

01:54:07.920 extreme diets are not sustainable. If you combine both, it's even worse, and this is what a lot of

01:54:13.140 people are doing together. But you need to have some sustainability, but this is important to improve

01:54:17.800 that mitochondrial function. But going back to high-intensity, I think it's necessary because

01:54:23.020 we also lose glycolytic capacity as we age, and it's important to stimulate it. As you very well said,

01:54:28.900 for all of us who are not competing, I couldn't care less about being super high-intensity. I'm not

01:54:35.560 competing. But that said, I want to have also my adrenaline rush. But how much does it feed into it? So

01:54:40.740 for example, if, and I've often thought about this now as I just want to make sure my zone two is above

01:54:46.280 three watts per kilo, would I be better off taking that extra training? If I have one additional training

01:54:52.200 session per week, should I make it an additional zone two workout? I do four now. Should I be doing

01:54:58.180 a fifth one? Or should I be taking that fifth one and doing a VO2 max protocol? And that's what we'll

01:55:05.840 typically prescribe to our patients is a four-by-four protocol of highest intensity sustained for four

01:55:11.300 minutes, followed by four minutes of recovery, and then repeat that four, five, six times. When you put a

01:55:18.180 warm-up and cool down on either end of that, that's a little over an hour. Would you spend that hour

01:55:22.940 doing that in an effort to make your zone two even better? Or would you just do an extra hour of zone

01:55:29.620 two? I agree that if you have a fifth day, you can convert it into any type of high-intensity

01:55:35.500 session, structured. What I can tell people is, hey, you're a cyclist or a runner. You want to go with

01:55:41.800 your friends on the club ride. That's your group ride. The group ride, go ahead and boom, go at it.

01:55:45.940 Or if you don't have that possibility, this is my situation, for example, where I don't have the

01:55:51.380 time to train more than an hour and a half, usually two hours max. So what I do almost on

01:55:56.500 every session, I do my zone two. So it's clean. And at the end, that's when I do a very high intensity

01:56:02.920 interval. Tell me the duration. So if you did an hour of zone two. Yeah. So I do usually, let's say

01:56:08.180 an hour and a half. So you'll do an hour and a half of zone two, three or four times a week.

01:56:12.340 I shoot for four or five. Not all the time. It's easy. But yeah, I shoot for five and I try to be

01:56:17.600 strict on that. But, and unfortunately that where I live, I live more in a Thailand area. So you have

01:56:23.740 to go up. So the last part, I just go at it. Sometimes you find another cyclist and you just

01:56:28.980 compete, you know, to see who's the fastest in that short climb. But I try to do like a good five

01:56:34.460 minute interval, roughly. I arrive home like, man, I kicked my ass today. This kicked my ass today.

01:56:41.360 Or sometimes you try it and you don't have the energy. As I mentioned earlier, oh my gosh, I can

01:56:46.000 barely move the pedals today. I just quit and go home. But when I feel fresh, I stimulate that

01:56:52.060 glycolytic system. What we know well too is that that increases the amount of kind of function. It takes

01:56:57.660 months or years. Increasing the glycolytic system, it takes much, much less amount of time. You can do

01:57:04.740 that in weeks or months. If you stimulate on a regular base, two days a week or three days a week,

01:57:10.360 at the end of that zone two, that's where you can target both energy systems, the oxidative

01:57:16.200 mitochondrial system and the glycolytic energy system.

01:57:20.840 We don't blunt the benefit we had from the zone two if we immediately follow it with the zone five.

01:57:26.060 No, because that's done, right? What it seems like if you do the same things in the middle.

01:57:30.160 But you don't want to do the reverse order. You don't want to start with the high intensity.

01:57:33.340 Exactly. One of the things like, because you start having all these hormonal responses. And also you see,

01:57:37.720 you have high lactate levels in the blood. And what we know very well is that lactate inhibits

01:57:42.100 lipolysis. So if you have a high interval in the middle or the beginning, and you don't clear lactate

01:57:48.980 very well, you might have high lactate levels for a while, and it's going to inhibit lipolysis.

01:57:55.400 Also, another study we have under review, lactate at the autocreen level decreases the activity of CPT1

01:58:03.000 and CPT2. So it interferes with the transport of fatty acids as well. So that's where like,

01:58:08.860 if you do all this, you might change things. You have high cortisone, cortisone anemia as well.

01:58:13.460 I'm glad you raised that because I explain this to patients when they say,

01:58:17.220 I went out and did a two hour ride today. And it showed me that I spent 45 of those minutes,

01:58:24.180 45 of those 120 minutes were in zone two. So I did 45 minutes of zone two. And I say, no,

01:58:28.260 you didn't really do it because you were going up and down and up and down and up and down.

01:58:32.180 And so that's not the same as spending 45 minutes in the dedicated energy system.

01:58:37.700 Right. I mean, when I look at the training peaks, you see the elite athletes, they're like

01:58:41.800 more power output and heart rate. This is like goes together. Incredible. Whereas, yeah,

01:58:48.000 you're right. Up and down and down, the average might be zone two, but actually you're between

01:58:52.260 oscillating zone one, zone three, zone four all the time.

01:58:54.680 So if you don't mind sharing in watts per kilo, what is your zone two in Colorado where you're at

01:59:00.540 altitude? I don't look so much into this. I have done so many tests in my life. Since I was 15 years

01:59:08.560 old, I was using a heart rate monitor talking about 1986 when the first heart monitors came out.

01:59:15.440 What you're getting at is you don't like to have a lot of data when you're doing it. You're going off

01:59:19.360 RPE and you're not looking at your power meter or a heart rate monitor and you're not poking your

01:59:24.340 finger when you're done.

01:59:25.620 I do it here and there because I still want to look at this and I do metabolic testing here and

01:59:29.920 there, but I've done so much. And me, since I was 15 years old and I was obsessed by this,

01:59:35.740 I got to a point that I know my body quite well. I can just go by the sensations and,

01:59:41.140 but here and there, I double check.

01:59:42.540 But it's hard for you to then get at what I've observed the few times I've tried to do my zone two

01:59:48.480 at altitude, like in Colorado. It's an enormous discount. I feel like it's a 20% discount at

01:59:55.260 altitude.

01:59:56.480 Yeah. Mine's around 2.5, 2.8, something like that watts per kilogram when I do it.

02:00:02.100 At sea level, you'd be over three probably based on what I experienced it going in the reverse

02:00:07.380 direction.

02:00:07.820 I would say roughly. And one thing that I'm very proud of is that I have been doing,

02:00:13.320 because I do sporadically this testing, I know my PRs, because that's another thing. We have

02:00:17.880 climbs here and one day I go for this climb and I go full out on that climb, right? I'm 50 now. I

02:00:23.760 have the same metabolic parameters than when I was 40. To me, I'm very proud of this.

02:00:29.520 And when you say parameters, you don't mean times up the climbs. Which parameters are the same?

02:00:34.680 I'm lactating power output, VO2. I look at time as well. The PR that I had, it was similar.

02:00:42.140 What's your VO2 max now?

02:00:43.920 So my VO2 max now is four liters per minute. So that's about 51, 52.

02:00:50.000 You could easily raise that if you lost three kilos, which you could probably do. Yeah.

02:00:54.740 Yeah. And the thing is, because I've obviously, when I was a cyclist, I was 141, 143 pounds.

02:01:01.560 So my VO2 was... And you were probably, your VO2 was five and a half liters or something.

02:01:06.400 It was 76.7. Let me see. It was 4.5, I believe. It was about 4.8, something like that.

02:01:13.940 30 years later, I have decreased only about 0.5, 0.7, which, whoa, I'm really happy about that

02:01:21.420 because I'm not training like I did. But this is one of the parameters. But in a decade,

02:01:25.820 I haven't decreased my parameters. So this is, to me, it's a proving point to myself, at least,

02:01:32.500 that doing this routine, it helps to maintain that metabolic health that you had a decade ago.

02:01:40.200 Now, can you do this 10 more years and when I turn 60? I don't know. But what I know is that

02:01:47.220 from others, I'm seeing it. So I see a typical person who just retired, as I discussed earlier,

02:01:53.420 aspired to pre-retire at the age of 60 or a little bit before. And these are like people like us. We

02:01:59.520 are struggling to squeeze in time, do five hours here, six hours a week here, or 10. But then they

02:02:06.320 have the whole time in the world, sleeping. They're not overworked. They can exercise. It's unbelievable

02:02:14.080 and super inspiring how much they improve in their 60s. I've seen people in their 70s with the

02:02:22.060 metabolic parameters of people active, morally active, in their 30s. World champion in the cycling

02:02:30.460 who's 81, in the category of 80 to 85. Believe me, there's a category of that. Metabolic parameters

02:02:36.700 were those of someone in their 30s, healthy, active. So this is incredibly inspiring.

02:02:41.920 And I think that we're rewriting what's been taught to us in the books.

02:02:47.920 Was that person an elite athlete? Were they a professional athlete in their 20s and 30s?

02:02:53.020 Never. And this is what struck me. He was a smoker, hypertensive, and he started cycling because he

02:02:59.920 needed to change his lifestyle in his 40s. Because that's the same question. Like, wow, you must be

02:03:04.840 doing this all your life. Like, no. I started riding my bike when I was in my 40s. I was a smoker. I was

02:03:10.000 heavy. I was hypertensive. Like, what? So it's incredible 40 years later.

02:03:16.000 What I take away from that as well is the benefits and the importance of compounding.

02:03:21.720 You see, you alluded to it earlier, and I think the listener could be forgiven if they missed this

02:03:26.560 point. You can make relatively quick changes in your glycolytic efficiency. You can take an untrained

02:03:33.080 person with a VO2 max of 20 ml per kg per minute. And you could take them from 20 to 30 in a period of

02:03:41.920 months with the right amount of training. A 50% improvement in a few months. It's very difficult

02:03:49.040 to see a 50% improvement in mitochondrial function in a few months. You've already made this point,

02:03:55.800 but I just want to restate it because it's important to set expectations. And it speaks to why

02:04:00.660 this level of training should be thought of in the same way that you think of accumulating wealth.

02:04:06.340 It's day in and day out, day in and day out, small compounded gains over years and years and years

02:04:15.100 is why a 40-year-old overweight smoker can become a world champion at 80 because he probably never

02:04:23.500 once again got out of shape in that 40 years. Absolutely. And this is incredibly inspiring.

02:04:28.800 When I see these people in their 60s just retired and they come to do their first test and one year

02:04:34.940 later they come back, it gives me the goosebumps because it is like, oh my gosh, I'm 64. I feel

02:04:42.920 as strong as when I was in my 30s. And like, oh. And of course, no medications, really good state of

02:04:50.020 mind, which is absolutely key for longevity. They eat in moderation, but they can have a little bit of

02:04:56.320 everything, which is also in my modest opinion, it's part of the enjoyment of life, eating what

02:05:01.960 you like in moderation as well. So it's incredibly inspiring. In a way, we're rewriting what we've

02:05:08.640 been thought for years, that once you turn 40, everything is going down. You can really, really

02:05:14.180 change. And again, you know, you own your own body and you can really take ownership of that and

02:05:20.260 improve it at any age. You mentioned drugs. I want to talk about one drug in particular and maybe

02:05:25.020 some supplements. You and I have spoken so much about this and myself and another person are

02:05:30.240 committed to funding a study that we're going to be doing once we get through kind of the backlog of

02:05:35.480 COVID issues at the university. The question really arises around the use of metformin and whether or not

02:05:43.000 there's a true impairment of mitochondrial function or whether the elevated lactate levels we see in

02:05:49.920 patients taking metformin is an artifact of the drug itself, but says nothing of the mitochondrial

02:05:56.060 function. Do you have any more insight into this question that we struggle with greatly because

02:06:01.420 we have some patients who take metformin who receive much benefit from taking metformin,

02:06:06.760 but it makes it confusing to interpret their zone two data. And it makes me ask the question,

02:06:13.800 in those patients, it's maybe less relevant, but now it becomes relevant when we think about

02:06:18.080 using metformin as a gyroprotective agent, an agent to enhance longevity.

02:06:22.840 We need a lot of research on that, I think, to understand this better. Definitely, it seems to

02:06:28.040 work in many patients. Obviously, for those ones in the pre-diabetic, first stage diabetes,

02:06:33.440 it's a very good medication. It's been used for a long time with good results. But how about the

02:06:38.580 long-term results? We know that metformin inhibits complex one, which is key for mitochondrial function

02:06:45.300 in the electron transport chain. We don't know the long-term effects of metformin in longevity. This

02:06:51.480 is where I think that we need more information as well. We see someone showing up with lactate of 3.5

02:06:57.660 millimoles at rest. And the first thing I ask is like, are you on metformin? And many times I say,

02:07:03.100 yes. And I'm sure you see the same thing, right? And I say, wow, it's definitely an artifact. And why do

02:07:08.160 you see at rest 3.5 millimoles or 3 millimoles of lactate?

02:07:12.280 Their fat oxidation commensurately suppressed? Because when you metabolically test them on the

02:07:18.600 cart, do you see in that individual a very, very low fat oxidation? If not, it might suggest that

02:07:26.060 that lactate level of 2 or 3 millimole is an artifact, but doesn't really speak to what's

02:07:31.060 happening in the mitochondria, right?

02:07:32.300 I haven't seen people taking metformin as medication, you know, for longevity, for example,

02:07:37.960 or for health. What I see people on metformin are already clinical patients.

02:07:41.940 So of course they're low.

02:07:43.240 Yeah. So they're taking metformin in the first place because of their clinical condition,

02:07:47.520 which is driven by a mitochondrial impairment or dysfunction. It's difficult to discern,

02:07:52.940 but I mean, I'm sure you have more experience of people taking metformin.

02:07:56.680 We do. But that's why this study that we're eventually going to get around to doing is going to

02:08:00.980 be so important because it will answer this question directly.

02:08:04.280 We can do it with a muscle biopsis. And as you say, does it really mess up with the whole

02:08:08.940 mitochondrial function or even like the mitochondrial function overall, overwrite that inhibition of

02:08:15.240 complex one and overwrite other pathways? I don't think we know the answer to that.

02:08:20.060 Do you have an insight into any other supplements, no shortage of supplements that are out there

02:08:25.980 that are touted as longevity boosting agents and mitochondrial health agents? So the most talked

02:08:32.900 about of all of these, I think, is the precursors to NAD. Most common of these would be NR or NMN,

02:08:40.740 both of which are pretty clear that they are precursors to NAD. There's certainly some debate

02:08:46.180 about how clinically relevant it is. Do you have a point of view on whether or not taking a supplement

02:08:53.100 that boosts NAD, at least in the plasma? I still don't know how well it's boosting NAD in the cell,

02:09:00.420 but do you have a sense of if that is beneficial to the mitochondria, both theoretically, but more

02:09:05.680 importantly, experimentally? I don't think we have the answer, but I think we need to be cautious

02:09:10.020 about how we interpret this data. It's definitely been shown multiple times that NAD levels at the

02:09:17.120 cellular level and even mitochondrial level are decreased with aging. Therefore, the whole thing,

02:09:21.800 whoa, if it's slow, let's take it. But it's not only NAD. If you look at so many metabolites

02:09:27.700 at the cellular level and mitochondrial level, they're downregulated with aging. The question

02:09:32.660 is, why are they downregulated? It's because mitochondria per se to start out with is downregulated,

02:09:39.480 so it doesn't need so much NAD because it cannot take it, or other supplements, or other metabolites.

02:09:45.180 This is at least how I think of NAD. It's, as we mentioned earlier, it's very important in

02:09:50.720 glycolysis and redox status to maintain redox. And it's very important in the visceral 3-phosphate

02:09:57.260 to 2,3-biphosphoglycerate phosphate, where NAD is utilized to convert glycerin 3-phosphate to 2,3-phosphoglycerate,

02:10:05.640 but it's depleted. And this is why the only thing that rescues that is lactate, right? As we mentioned.

02:10:10.760 Now, taking NAD, is that going to increase longevity? I don't think so. That's my opinion,

02:10:16.940 because longevity is not just one supplement, or two, or three, or four, or five. It's a

02:10:21.560 compendium on an incredible amount of things that happen at the cellular level, and I don't

02:10:26.120 think that one supplement. I remember those days where resveratrol was the thing for longevity,

02:10:32.780 and everybody was, not everybody, a lot of people were buying resveratrol, and there are studies

02:10:36.980 with mice showing that increased 50% longevity in mice, so they're a force to do it in humans.

02:10:42.400 Well, as you probably know, a lot of people started to take in resveratrol when they were 50,

02:10:47.020 and they're dead now. It doesn't increase longevity in humans.

02:10:50.960 The data in the mice, we can debate the merits of that. I want to ask you about a theoretical risk,

02:10:55.960 though. You kind of alluded to it. Isn't there a scenario under which too much NAD could be harmful?

02:11:01.800 I don't know if this study has been done, but if you took cancer patients or patients who had tumors

02:11:08.220 that were undiagnosed and gave them, if you doubled their NAD levels, wouldn't you actually

02:11:15.080 favor the tumor's metabolism? Well, in fact, we have done that pilot study with mice. The whole

02:11:22.780 thing is like looking at, and my area of research in cancer is cancer metabolism, and we know that

02:11:28.120 glycolysis is key for cancer, and NAD is absolutely indispensable to feed that glycolysis. The question

02:11:36.240 is like, as you said, would NAD increase that glycolytic rate or glycolytic flux? Therefore,

02:11:45.420 would be favoring more cancer phenotype? So what we did, we haven't published that. It's a pilot study,

02:11:51.700 which is, we're curious about it, and we had two mice. We have NN of eight mice, four and four. So

02:11:59.460 what we did, we transfected tumors, triple negative breast cancer. It's very aggressive, and it grows

02:12:04.740 very, very fast. One group, we give them just water, and the other group, nicotinamide ribocyte,

02:12:12.380 which is the NAD precursor, because NAD, obviously, as you know, you cannot take it. You need to take

02:12:16.780 the precursor, and we observed the tumor growth over 23 days. After that, the IRB at the university,

02:12:23.940 because you cannot have animals with high tumors. So it was a flank tumor, and you need to harvest

02:12:30.820 them. We were measuring every five days the tumor growth, and we saw in these animals that there was

02:12:37.040 about 15% increase in tumor growth in the NAD group. You saw that difference with only four mice in each

02:12:44.560 group? It's four and four, but all consistent. We had statistical significancy, even with a small

02:12:50.900 four. I mean, there was no cross results. All the four mice, they grew cancer at a higher rate in the

02:12:57.840 NAD than the control group. Again, that's where, like, obviously, this is not, like, publishable.

02:13:04.220 Is that a study you'll repeat at a sufficiently powered size?

02:13:08.760 I would love to. This is why we just did this pilot study. We had, because we have many mice,

02:13:13.280 and say, hey, let's give it a shot, and we see, because there's a lot of hype of NAD, and we saw

02:13:18.120 this. Love to do it at a much higher level, because my question, which might be a disruptive

02:13:24.980 question, is, like, what if you have a small tumor that you're unaware of, like in the pancreas, or in

02:13:31.040 the colon, or in the lung? Could NAD over time, day after day after day, could favor that glycolytic

02:13:39.180 flux to that tumor and increase the growth? I've never looked, because it just kind of occurred

02:13:43.740 to me when you had that slide up earlier, earlier, and you showed the mitochondrial slide. It occurred

02:13:48.380 to me that you have that lactate escape from the tumor. Hey, this would feed it. But has anybody in

02:13:53.620 the literature examined this question? It seems like a very reasonable question to ask.

02:13:57.800 There are a couple of studies. I think once I review, it's more at the conceptual level. And this is

02:14:03.200 what got me thinking, like, yeah, this is something that, for us, working in cancer metabolism, we look

02:14:09.400 into this. Obviously, one of the things that we have shown is that lactate is an oncometabolite.

02:14:14.600 Lactate, we have shown, have a first paper, and we have, like, a good six, seven papers more to come,

02:14:20.900 working hard for three years looking into this. But we saw that lactate regulates genetic expression

02:14:26.160 of the most important genes in breast cancer. We're seeing the same thing now with lung cancer.

02:14:32.400 And lactate, as we keep talking about this, is the mandatory byproduct of glycolysis. And as Warburg

02:14:38.920 saw in 1923, the characteristic of cancer cells, or most cancer cells, is the high glycolytic flux.

02:14:45.400 But what struck Warburg was not the glucose itself, it was the lactate production. So anyways, we are

02:14:52.240 showing that it's an oncometabolite. So if you have a high glycolytic rate in a cell, you're going to

02:14:58.240 produce a lot of lactate. You cannot clear that lactate. It's going to drive cell growth and

02:15:03.660 proliferation, as we're seeing. And in fact, we're now blocking lactate production, both through genetic

02:15:10.200 engineering, as well as DCA, for example. And we're seeing that cancer growth and proliferation

02:15:16.820 completely stops within hours. Now that poses an interesting dilemma, which is exercise would

02:15:24.140 increase your capacity for clearing lactate in the long-term, but in the short-term raises lactate.

02:15:31.460 So it begs the question, in a cancer patient specifically, what's the net impact of exercise?

02:15:38.540 This is what we're working on, the hypothesis, you know, of my colleague, George Brooks.

02:15:42.820 He's shown that acute response to lactate, it increases overexpressions of about 600 and

02:15:51.020 something genes. I forgot right now. All these genes are involved in cellular homeostasis and

02:15:55.600 in the benefits of exercise. We know very, very well through his work that lactate is a signaling

02:16:01.020 molecule. Now, the question is like, we know this at an acute exposure, which is exercise.

02:16:07.080 You do exercise, boom, boom, boom, you're out. But cancer doesn't do that. Cancer accumulates lactate

02:16:14.140 and it keeps accumulating. This is the main responsible for the tumor microenvironment,

02:16:18.860 which is acidic. And the more acidic the tumor microenvironment, the more metastatic the cancer

02:16:24.480 is and the more aggressive, like the more glycolytic the tumor is. And this is very well documented.

02:16:30.380 The more glycolytic the tumor is, the more aggressive is. And the more lactogenic, that is more lactate,

02:16:35.860 the more produces, the more aggressive is. Now, why is that lactate accumulating? That's what we need

02:16:42.920 to try to find out. But we know that that is not acute anymore. It's chronic exposure to lactate.

02:16:48.760 Can exercise counteract that? When we see that exercise might be beneficial for many patients,

02:16:55.520 but again, going back to the right intensity, we know particles which are exosomes,

02:17:00.560 there are microvesicles in the body. They're main responsible for metastasis. We have seen that,

02:17:06.920 and this is another publication we're going to have in breast cancer cells and lung cancer cells.

02:17:11.080 We are looking at the protein content and the microRNAs of those exosomes released by these

02:17:16.260 cancer cells. It's incredible the information that they have. If you were to genetically engineer

02:17:22.440 a molecule, they can inject it into a tissue and transform into cancer, you would replicate an

02:17:29.880 exosome. It has all the components needed. On the other side, muscles also release exosomes.

02:17:37.300 And this could be one of the benefits of exercise as an organ and the crosstalk between skeletal muscle

02:17:45.180 and many organs. We know that if you have very good muscle health, your health overall,

02:17:51.660 metabolic health is going to be good. Could you be releasing great exosomes? They're very

02:17:56.320 pro-oxidative, which counteract the glycolytic phenotype of cancer. And could those exosomes

02:18:01.680 travel directly to the cancer cells and counteract that and penetrate inside the cancer cells and

02:18:09.340 transform the glycolytic phenotype of the cancer cells into more oxidative phenotype and keep cancer

02:18:15.760 at bay? We don't know yet. We're suspecting that we're scratching the surface of something that

02:18:21.060 potentially could be very interesting thing to understand better the effects of exercise,

02:18:26.040 as well as neuro-therapeutics. The deeper I go in the rabbit hole into all things that relate to

02:18:32.520 longevity, the more convinced I am that if you're going to rank order things, if you were forced to

02:18:38.220 rank order things, there's nothing that ranks above exercise as the single most potent tool or agent we

02:18:45.940 have to impact longevity. And yet paradoxically, in the acute setting, exercise seems to do everything

02:18:53.060 incorrectly. In the very short acute setting, if you look at it in that narrow context, exercise does not

02:19:00.220 appear to be geoprotective. But of course, when you look at the chronic impacts of exercise and

02:19:06.100 what's taking place after the bouts of exercise, the data seem undeniable. I want to kind of pivot from

02:19:12.580 exercise a bit into a subset of that, which is something you published this year in long COVID

02:19:19.160 patients. So we'll link to the study so people can see it. But you demonstrated that in people with

02:19:26.080 long COVID, even previously healthy people, they basically, from a mitochondrial standpoint,

02:19:33.540 end up looking like people with type 2 diabetes when they're done in terms of fat oxidation,

02:19:38.660 lactate production. So first question for you is, what fraction of patients recovering from COVID

02:19:45.040 do you believe are susceptible to that phenotype? Everything started by National Jewish Hospital is

02:19:51.920 probably, as you know, is with Mayo Clinic competing for the top one pulmonology hospital in the country.

02:19:58.380 You have these people with long COVID who are struggling. They go up the stairs and they can't

02:20:04.540 breathe. So the first thing they do is they go to different doctors and they end up going to this

02:20:09.400 top hospital. So they do a pulmonary function test and it's completely normal. Then they, okay, the next

02:20:16.220 species is because COVID also affects the cardiac muscles. Let's look at the cardio function. It's

02:20:21.940 completely normal. They're very good at this hospital where they do metabolic testing. They do a CPET

02:20:28.560 testing. That's how you call it medically, right? Physiological testing. And they even do lactate.

02:20:33.080 I've been, I've been interacting with them a few times. So they do lactate as well. So they contacted

02:20:38.340 me and said, Inigo, look, we're seeing these patients. We have 50, 25 of them. They had previously

02:20:44.400 underlying conditions. The other 25, they were normal people. And in fact, most of them, they were

02:20:51.720 morally active. Some of them, they were doing marathons, triathlons. The average is 50. So they're not

02:20:57.980 very old either, but their pulmonary function is completely normal and cardiac function is

02:21:03.180 completely normal. So we suspected there's some metabolic issue here. So they sent me all the

02:21:08.000 information, the raw information. And I applied the methodology that we've been discussing,

02:21:12.800 looking at fat oxidation and lactate production as a surrogate for metabolic function and metabolic

02:21:19.400 flexibility and mitochondrial function. And I was shocked because they were significantly worse

02:21:25.400 than people with type 2 diabetes and metabolic syndrome, which could explain why these people

02:21:31.660 cannot go up the stairs and where before they were doing marathons. Now, what are the mechanisms?

02:21:38.240 We know that viruses, multiple viruses are known to hijack mitochondria for their own benefit,

02:21:44.800 for reproduction. Could COVID do the same thing? We are suspecting it. And we're trying to understand

02:21:50.940 that at a more cellular level. Now, unfortunately, the majority of this long COVID, because as you know,

02:21:58.940 there are people with long COVID syndromes that within weeks, months, they improve, they go back

02:22:03.780 to normal. But there are a handful of people that I'm assuming they're going to be growing, that after

02:22:09.840 one year, they haven't improved a bit. This is the concern. Like, can we use exercise as a therapeutic

02:22:15.780 way to stimulate mitochondrial function if, in fact, there's a mitochondrial dysfunction, which is

02:22:21.860 severe? Because if that's the situation, it's going to expose these patients to multiple diseases.

02:22:27.500 So this is an area of concern. And this isn't talked about as much as what I think people initially

02:22:34.080 spoke about here, which is basically myocarditis. Now, of course, we know that the risk of myocarditis

02:22:40.700 is actually much higher in young males through the Moderna vaccine than it's ever going to be with

02:22:47.680 COVID. But the rate with COVID is not zero. It's, I believe it's 2.3 cases per, it's going to be a

02:22:55.060 big difference. I think it's 2.3 cases per 100,000 of people with COVID are getting myocarditis.

02:23:01.260 Most of those are transient. They recover. Not all of them are. So a subset or not. But this mechanism

02:23:07.720 would be distinct from just myocarditis. Myocarditis, of course, speaks to the inflammation of the

02:23:11.760 cardiac muscle that would explain depressed ejection fraction. But what you're describing

02:23:16.440 is a far more diffuse problem, is a global insult on the mitochondria in the skeletal muscle, correct?

02:23:23.500 That's what we suspect from this data, which again is indirect, from the indirect calorimetry in the

02:23:28.420 lactate, that it points out towards mitochondrial dysfunction. So that's what we need to do now,

02:23:34.120 biopsies to understand this out of better detail. What the heck is going on? Could be at the

02:23:40.300 microprofusion level too. It might not be at the muscle per se. It might be at the microfusion in the

02:23:46.300 blood, in the capillaries. Meaning something like microthromboses that are preventing perfusion and

02:23:53.880 raising lactate that way? Could be. Could be. That's what we need to find out. But we know from other

02:23:59.300 viruses that they hijack mitochondria. They interfere, especially with the fission and fission processes.

02:24:06.980 Some causes increase fission. Some other causes increase fission. Some other causes increase elongation.

02:24:13.300 So we know there's a wealth of studies out there from virology showing that, yeah, many viruses and bacteria,

02:24:20.600 they hijack mitochondria. They disrupted significantly. But most of the times, like myocarditis, it subsides.

02:24:29.300 It's restored. Shortly after the symptoms are gone, why this virus is different. That's what we are

02:24:36.480 trying to understand. Why people after one year, by the way, you know, most of these people, they had

02:24:41.540 just a normal mild course of COVID. They were not hospitalized. They were not in the ICU.

02:24:47.320 Any evidence or inkling that if people go back to exercising too intensely following recovery,

02:24:54.620 it could exacerbate this problem. And do you have a sense of which strains this was? Your work would

02:25:00.480 have been predominantly alpha and not delta and obviously not omicron, correct?

02:25:05.460 Yeah. Even a mixture between the original variant and delta, so not omicron.

02:25:11.200 So in this population, which again is presumably mostly alpha, maybe some delta,

02:25:15.660 what was the distribution of male and female?

02:25:18.860 We have 35 females and 15 males, more female predominant.

02:25:24.220 Which again, maybe is too small a sample to know. That could be more an indication of who's seeking

02:25:28.440 out. And again, we don't really know the denominator. We don't know what this represents. Is this one in

02:25:33.400 a hundred thousand? It could be one in a million if this was everybody that's reporting it at the time.

02:25:37.900 So our guess is this rare event can last that long, but we're talking about millions of people

02:25:44.540 infected, right? If it's one in a million, we're talking about a population that is going to need

02:25:49.280 help. I want to kind of go back to just a few other questions that we didn't get to. So not

02:25:54.420 necessarily in any thematic order. What's the relationship between, or how predictable I should

02:26:00.320 say is the relationship between zone two as defined by maximum fat oxidation and VO2 max. So if

02:26:07.680 you run somebody through a CPET and you figure out that their VO2 max is at four liters,

02:26:14.340 how predictably can you say at X percent of that, you will be at maximum fat oxidation?

02:26:21.440 There's another study that we're preparing the manuscript with 225 subjects where we look at

02:26:27.360 fat oxidation, VO2, and the relationships. Going back to the same thing, we tend, and historically,

02:26:34.160 the research studies with exercise have been done based on VO2 max. That's been the parameter to

02:26:40.400 prescribe exercise. How many times we read X amount of subjects, they were exercising for six months at

02:26:46.540 60% of VO2 max or whatever. Now, that's another thing that I've been thinking of years.

02:26:51.560 And by the way, when they say that, do they mean 60% of the heart rate that produced VO2 max or 60%

02:27:00.380 of the power that is their max power at VO2 max? Yeah. I mean, there's so many different ways you can

02:27:06.980 do this that I've always found that you have to get into the methodology very closely.

02:27:10.860 I agree. I agree 100%. And this is where I think we need to dial things in better because yeah,

02:27:15.880 60% of the power output, the intensity might be translated into power output, 60% of you to max,

02:27:22.980 and then you translate into power output or you translate into heart rate.

02:27:26.340 Or is it 60% of the VO2? So for example, if somebody's four liters VO2, and then they hit that

02:27:33.760 at 300 watts, would 60% be 2.4 liters? Which of course is not a very helpful way outside of a laboratory

02:27:42.400 to prescribe exercise to somebody? Or would it be 180 watts, which is 60% of the 300 watts?

02:27:50.900 Yeah, exactly. I think that normally the studies, they look at where do you hit 60% of VO2 max?

02:27:56.920 How many watts is this? Or what's your heart rate?

02:28:00.260 What's the wattage that corresponds to 60% of your max VO2?

02:28:06.000 And in our study, what we are seeing, and this is what, because I've been curious about this,

02:28:09.660 because we look at the cardiorespiratory adaptations to exercise, and we look at the

02:28:13.640 cellular adaptations to exercise, do they really correspond? We know very well with athletes,

02:28:20.200 you can improve tremendously at the cellular level, but not at all at the cardiorespiratory level,

02:28:27.040 at least based on VO2 max, which is the representative of the cardiorespiratory adaptations

02:28:32.320 to exercise. An example that I always give when I give talks, an athlete who used to be

02:28:37.800 an average professional, the VO2 max was 72.3 or something like that. And then two years later,

02:28:45.640 he is a very good professional. The VO2 max is the same, but the lactate levels were incredibly

02:28:51.920 better. I forgot, at five watts per kilogram, he was at five millimoles, and now it's at 1.7.

02:28:58.220 This is where the magic happened to this specific athlete. It was at the cellular level.

02:29:02.300 We see this across the board, right? VO2 max at the elite level does not come close to predicting

02:29:08.420 performance. Not at all. This is why we're putting together this study with all this population of

02:29:14.400 different, from people with metabolic syndrome all the way from two of the France athletes. So

02:29:18.560 longitudinally, we see that, yeah, sure, VO2 max corresponds with fitness in the same manner

02:29:26.640 that watts corresponds with fitness. So we can also imply that instead of doing a VO2 max to look at

02:29:33.300 longevity and fitness, we can also do a power test or a speed test and a treadmill, because we're going

02:29:39.860 to see the same thing. Those ones who are very poorly active, they have a very poor fitness, they're

02:29:45.340 going to have a lower VO2 max, they're going to have a lower power output, they have a lower speed,

02:29:50.640 lower lactate cleanse capacity. VO2 max has been forever a great surrogate for fitness.

02:29:56.180 Cardio risk between fitness and longevity. But we wanted to see if in fact it's really that specific.

02:30:02.580 So in our study, we see that people in different categories, at the same VO2 max, they might be in

02:30:09.980 different metabolic states. So some people at the same VO2 max might be oxidizing a lot more fat

02:30:16.360 or a lot more carbohydrates. So that means that does not correspond to the same metabolic status.

02:30:23.320 I would have thought that most people by the time they're at VO2 max, they would be disproportionately

02:30:29.660 carbohydrate. So really, you're just saying how much fat oxidation still remains there is

02:30:34.200 really what you're saying. And I'm assuming a very untrained person has zero fat oxidation by the time

02:30:40.920 they reach VO2 max, whereas a more highly trained person would still have some amount, they might still

02:30:47.340 be at 0.2 or 0.3 grams per minute. Yeah. For example, we see that like a sedentary individual

02:30:53.180 at 75% of the VO2 max might be around three millimoles, whereas a world-class athlete at the

02:31:00.140 same percentage of VO2 max is about one and a half. So metabolically, they're different, yet the VO2 max is

02:31:08.440 the same. So if we prescribe exercise based on VO2 max, we might not do things correctly. And the same thing

02:31:16.120 with carbohydrate oxidation. At a 75% of VO2 max, like a sedentary individual oxidizes about 2 grams per minute,

02:31:25.340 where an elite athlete oxidizes about 3 grams per minute. So that's a significant difference. And we also see it at

02:31:31.920 50% already. So this is why longitudinally, they correspond quite well. And same thing as fat oxidation. Fat

02:31:39.060 oxidation at a 50% of VO2 max is about 75% of your CO2 max, 0.23 in the sedentary, it's 0.6 in an elite athlete.

02:31:50.320 We look at the different intensities, for example, that an athlete that can have one millimole of lactate

02:31:57.400 within the same group, not just comparing group, but we can see that someone within the very same group,

02:32:03.720 whatever the category they are, the lactate and the VO2 max don't correlate. The correlations are

02:32:10.660 sometimes 0.2 or 0.1 or 0.3.

02:32:15.140 That's the R squared, you're saying?

02:32:16.760 Yes.

02:32:17.500 No correlation.

02:32:18.660 Very poor correlation. When we talk about individual groups, when we look at specific one

02:32:23.460 parameter, which is lactate, with the VO2 max, it doesn't really correspond. So anyways,

02:32:29.160 this is what I think that we have learned a lot over these last decades, where we can really

02:32:34.960 pinpoint more at the cellular level to improve metabolism more than at the cardiorespiratory

02:32:41.680 function, which is very important. Absolutely. They both are going to improve. But I think that

02:32:46.300 if we want to prescribe exercise, it's going to be more specific. If we look at cellular surrogates,

02:32:53.940 like lactate, like fat oxidation, for example, then looking at VO2 max or meds, I mean,

02:32:59.740 don't get me into there. That's very prehistoric. In my modest opinion, I don't want to offend

02:33:06.360 anybody, right? But the whole med concept, use for exercise, prescription, it's hard to swallow

02:33:12.460 in today's times.

02:33:14.460 Yeah. I was just about to say, I mean, it served its purpose in the 1950s. When we think about some

02:33:19.320 of the muscle biopsy data, again, this term of mitochondrial function, it's such an important

02:33:24.820 part of longevity because it is one of the hallmarks of aging, is declining mitochondrial

02:33:29.880 function. I usually explain to patients that the type of physiologic exercise that we're

02:33:35.600 prescribing, this zone two exercise, is the way to measure mitochondrial function. It's both

02:33:41.780 the treatment and the test. But I'm guessing on the cellular level, there's even more that we

02:33:46.840 can talk about. The last thing I really want to talk about today, because I know we've been going

02:33:50.840 for a while, you've been generous with your time. When you get into the omics, when you start to

02:33:55.300 biopsy the muscles, when you start to look at the mitochondria in a way that we can't do it in a

02:34:00.480 regular clinical setting, what else are you seeing that's differentiating the healthy from the unhealthy

02:34:06.820 mitochondria or the high functioning from the low functioning mitochondria?

02:34:11.180 Again, I keep talking about papers that wouldn't publish it, but we've been working for three years

02:34:15.180 quite hard. And now we cannot continue doing this. We need to start writing the papers, right?

02:34:20.700 You need more postdocs.

02:34:22.080 Yeah.

02:34:22.320 You need more graduate students and postdocs to help with the writing.

02:34:26.000 But we have completed a pretty cool study, and they're writing the manuscript now,

02:34:30.240 looking between sedentary and active. We know already there are a bunch of research showing

02:34:35.700 at the cellular level, the difference between people with type 2 diabetes or metabolic syndrome

02:34:40.600 and active individuals or even sedentary. We want to see also, or we want to show that people who

02:34:48.000 are sedentary, they already have problems. And we wanted to compare them with moderately active

02:34:53.920 people, which would be kind of how we should be as humans. So we looked into the mitochondria,

02:34:59.440 into mitochondria. So we looked at there's significant dysregulation at the mitochondria level

02:35:05.360 everywhere you look in the mitochondria in sedentary individuals. You see a decreased

02:35:10.700 capacity to oxidize, to burn glucose in terms of pyruvate, fatty acids, amino acids. You see a

02:35:19.080 significantly decrease in electron transport chain as well, all the complexes. And you see also a

02:35:25.580 significantly decreased capacity in the transporters of different substrates. One thing that it really

02:35:31.600 caught our attention and we think that this is something that we really want to emphasize

02:35:36.420 and hopefully others in the future is that we have identified that there is the mitochondrial

02:35:42.820 pyruvate carrier, which is, as I discussed earlier, that's the transporter of pyruvate into the mitochondria,

02:35:49.660 which is dysregulated already. Significantly downregulated in sedentary individuals compared to

02:35:56.060 active individuals. Then we are matching it with the pyruvate flux, the oxidation itself,

02:36:01.600 so both the transporter and the flux are significantly dysregulated. What does this mean?

02:36:09.340 That's going to shuttle pyruvate to the other way it's going to get in the cell, which is through

02:36:13.560 lactate. Exactly, exactly. What are the implications of this? So again, these people are, they don't have

02:36:19.420 diabetes or prediabetes. This could be a healthy person who's not active. And this is what,

02:36:25.640 unfortunately, this being the model in most research papers out there comparing the unhealthy,

02:36:31.580 with a sedentary, healthy individual. I've been pushing for years that the model should not be

02:36:38.660 the healthy, sedentary individual because that is the intervention. As humans, we're meant to walk or

02:36:45.600 to exercise. So we need to look at perfection to understand imperfection. The intervention of human

02:36:52.980 evolution has been becoming sedentary. And in fact, I had a hard time to get an IRB to study. I have a

02:37:00.240 hard time with the community to convince them that using active people as the gold standard to

02:37:06.620 understand imperfection, that's the way to go. But anyways, what we see is that these people already,

02:37:12.800 they don't have clinic, but yet they have a significant downregulation.

02:37:16.420 They don't have clinical signs. Clinical symptoms, sorry. They're not clinical symptoms.

02:37:20.380 They're the healthy sedentary individuals. They don't have insulin resistance and they don't have

02:37:25.440 downregulation of GLUT4 transporters. Even hyperinsulinemia? Are they hyperinsulinemic

02:37:31.300 when challenged with the glucose tolerance test? These people, they have no symptoms. They

02:37:37.480 haven't reported any glucose tolerance test. Normal people. And then they have a significant

02:37:43.660 disruption in this mitochondria pyruvate carrier, which might mean that the first door that might

02:37:49.900 be jammed is that entrance of pyruvate inside mitochondria. Most of the research in diabetes

02:37:55.600 has done more at the peripheral level, if you will, glucose levels, more at the surface levels of the

02:38:01.140 cell, the GLUT4, the insulin resistance, the pancreas release of insulin, better cells, etc. But what's

02:38:07.040 the fate of glucose once it enters the cell? And this is why we're looking to this. And the fate is

02:38:13.480 pyruvate. But what's the fate of pyruvate? As you said very well, does it enter the mitochondria or

02:38:18.100 is shuttled to or reduced to lactate? So I think that this is important to see because it could be a

02:38:25.500 marker down the road because, again, these people don't have clinical symptoms, yet they have a

02:38:30.580 significant dysregulation in their glucose metabolism. So could this be 10, 15 years ahead

02:38:37.240 of clinical symptoms and insulin resistance? This is more reason also to consider sedentary individuals

02:38:43.540 to see how they have a metabolic dysregulation already. Same thing we're doing at the fat

02:38:48.420 oxidation level. The CPT-1 and CPT-2, the transporters of fat, they're significantly downregulated

02:38:54.660 as well. So that means they're not going to be able to transport fat very well, which also matches

02:39:00.300 to the fat oxidation itself, where we inject fatty acids into the mitochondria that aren't oxidizing

02:39:05.520 well. So they all match as well. So they have this regulation already that is significant compared

02:39:11.700 to moderate individuals at the glucose metabolism and fat metabolism. Then we see that many of these

02:39:19.240 people who have diabetes or metabolic syndrome, they have what's called intramuscular triglycerates,

02:39:25.440 the fat droplet, and it's adjacent right by the mitochondria. In elite athletes, it's also there,

02:39:31.400 that fat droplet, but it's very active because about 25 to 30% of the fat oxidation comes from

02:39:36.880 that fat droplet adjacent to mitochondria, which it could probably is an evolutionary mechanism to

02:39:43.000 not rely on the adipose tissue, which might take time and have something right away there.

02:39:48.560 So when you say it's metabolically active, the difference between the intramuscular fat of the

02:39:52.620 athlete and the intramuscular fat of the person with type 2 diabetes, is it the flux then? In the

02:39:58.280 person with type 2 diabetes, it's a static source of fat. In the athlete, it's constantly turning over

02:40:03.480 and being oxidized and replenished. Exactly. Whereas in this population, it continues to grow.

02:40:10.220 My colleague, Brian Bergman from the university is working a lot into the content of what's inside

02:40:15.080 these fat droplets. But one thing that we know is like they're very high in ceramides and

02:40:21.020 triglycerides. And especially ceramides are key in the atherosclerotic process. Atherosclerosis,

02:40:27.200 it's a hallmark of cardiovascular disease. Ceramides are key for this process. Historically,

02:40:32.480 it's been thought and it's been shown that ceramides come from the liver, they're released.

02:40:36.520 But we're seeing that these intramuscular triglycerides are high in ceramides.

02:40:40.680 So could this be a connection between also cardiovascular disease and type 2 diabetes?

02:40:45.880 In the high turnover, high flux one, you're not accumulating them as much?

02:40:50.580 Yes. People who end up having type 2 diabetes, they accumulate fat droplet. Athletes as well,

02:40:57.080 that's the athlete's paradox. But athletes, as you said, they keep turning around and it's very active.

02:41:01.780 Whereas people with type 2 diabetes or obesity, it keeps growing. It releases pre-inflammatory

02:41:07.460 mediators. And it also is high in ceramides, which are key in atherosclerosis. So this is where we're

02:41:13.460 trying to establish the connections between type 2 diabetes and cardiovascular disease at the

02:41:18.000 mitochondrial level as a nexus. Because we know that about 80% of people with type 2 diabetes,

02:41:23.540 they also have cardiovascular disease and vice versa, which is what we call cardiometabolic disease.

02:41:28.320 So could the nexus of all that are mitochondrial impairment? That's what we believe.

02:41:33.600 Well, what I take away from this is we're probably going to have to do a third podcast in a couple of

02:41:37.740 years because there's going to be a lot of data that's going to be published then that isn't published

02:41:42.880 now. There's going to be a lot more questions that we're going to have answered. Again, I'm still

02:41:47.220 really yearning to understand the effect of metformin in terms of pure mitochondrial function

02:41:52.540 and performance in a trained individual. So as always, I can't thank you enough for your generosity

02:41:58.240 of insight and look forward to talking tomorrow when we have a call about some other nerdy stuff we're

02:42:03.580 going to get into. But thank you so much, Inigo. And also congratulations on the remarkable success of

02:42:08.540 your team. And Pogacar, who's an amazing cyclist to watch, he's got everybody very excited about the

02:42:14.560 Tour de France again. Well, thank you very much, Peter, all the listeners. I really appreciate

02:42:18.640 what you do. The first time I met you, because we were two and a half hours talking about mitochondria.

02:42:24.360 And at first I thought like, this guy's crazy. There's nobody out there who's going to be

02:42:28.020 interested in listening to two and a half hours about mitochondria and metabolic health. You showed me,

02:42:33.200 yeah, the concerts are out there. And I was in a moment where I was, oof, not many people

02:42:38.340 seemed interested in this. And you were already an inspiration for me to continue doing this.

02:42:44.260 And the remarkable work that you're doing to educate people and inspire people. It's

02:42:49.880 transformational. So I really appreciate the invitation. It's just an honor.

02:42:53.940 Thanks for being with us today.

02:42:55.180 Thank you very much.

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The Peter Attia Drive - March 28, 2022

#201 - Deep dive back into Zone 2 ｜ Iñigo San-Millán, Ph.D. (Pt. 2)

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