The Peter Attia Drive - November 04, 2024


#324 ‒ Metabolism, energy balance, and aging: How diet, calorie restriction, and macronutrients influence longevity and metabolic health | Eric Ravussin, Ph.D.


Episode Stats

Length

2 hours and 9 minutes

Words per Minute

155.30278

Word Count

20,148

Sentence Count

1,232

Misogynist Sentences

4

Hate Speech Sentences

11


Summary

Dr. Eric Ravison is the Director of the Nutrition Obesity Research Center at Louisiana State University's Pennington Biomedical Research Center and the Douglas L. Gordon Chair in Diabetes and Metabolism. Having published over 600 peer-reviewed articles, Eric is regarded as a world-renowned expert in obesity, metabolism, and aging, and has received numerous awards for his contributions to these fields.


Transcript

00:00:00.000 Hey, everyone. Welcome to the Drive podcast. I'm your host, Peter Atiyah. This podcast,
00:00:16.540 my website, and my weekly newsletter all focus on the goal of translating the science of longevity
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00:00:53.200 of a subscription. If you want to learn more about the benefits of our premium membership,
00:00:58.000 head over to peteratiyahmd.com forward slash subscribe. My guest this week is Eric Ravison.
00:01:07.260 Eric is the director of the Nutrition Obesity Research Center at Louisiana State University's
00:01:12.560 Pennington Biomedical Research Center, where he also serves as the Douglas L. Gordon Chair in Diabetes
00:01:18.700 and Metabolism. Having published over 600 peer-reviewed manuscripts, Eric is regarded as a
00:01:24.560 world expert in obesity, metabolism, and aging, and has received numerous awards for his contributions
00:01:29.920 to these fields. As discussed at the beginning of this podcast, Eric and I worked together for about
00:01:34.280 four years, roughly 15 years ago, and during that period of time, I just came to have such an admiration
00:01:40.520 for Eric, his curiosity, and his intellect when it comes to this field. We talk about Eric's
00:01:46.520 background and his extensive experience in metabolic research, in particular when it comes
00:01:51.000 to measuring energy expenditure, which turns out to be a very technically demanding problem. We go
00:01:56.580 through the various methods that this has done, including what is today regarded as the gold
00:02:00.800 standard. This, of course, is necessary because if you want to understand energy balance, you must
00:02:05.860 clearly be able to measure energy expenditure. We, of course, discuss energy balance, energy expenditure,
00:02:10.880 and food intake, how we regulate appetite, and the findings of a very important study that Eric did,
00:02:17.620 which look at the impact of manipulating the ratio of macronutrients to see if it would indeed change
00:02:22.300 energy expenditure. Disclosure, I was involved in the funding of that study. We then delve into the
00:02:28.600 calorie study, which looked at caloric restriction and discuss its insights as it pertains to the biomarkers
00:02:35.220 of both primary and secondary aging. We speak about the implications of GLP-1 agonists and similar drugs
00:02:41.940 in replicating the benefits of caloric restriction, and look to the future of this research and see
00:02:47.420 how new technology advancements like AI might come into play. So, without further delay,
00:02:52.680 please enjoy my conversation with Dr. Eric Ravison.
00:02:55.440 Well, Eric, thank you so much for joining me. Sorry that we can't be in person, but given that
00:03:06.020 you're in the south of France and I'm over here in Texas, that would have made it pretty difficult
00:03:10.480 because normally we're quite a bit closer. You're obviously in Louisiana. But anyway,
00:03:14.620 it's wonderful to see you again. It has been close to 10 years, right?
00:03:18.920 I think so. I think so. But I have found memories of our interactions.
00:03:23.800 Yes, as do I. I guess by way of background, maybe we can even just give people a bit of a sense of
00:03:29.680 how closely we did work together for four years. At the time, I was part of an organization called
00:03:35.120 NUSI, and you were one of the six principal investigators for what was a very audacious
00:03:41.840 experiment and part of something called the Energy Balance Consortium, along with Kevin Hall,
00:03:47.600 Steve Smith, Rudy Leibel, Mike Rosenbaum, and God, who am I missing? Mark Reitman.
00:03:53.960 Nevertheless, this was a once-in-a-lifetime opportunity to do something that had never
00:03:57.680 been done before, which was a multi-center, indirect calorimetry, inpatient study that was
00:04:03.120 really aimed at trying to at least pilot what would be necessary to do the definitive experiment
00:04:09.560 to answer a question that I'm sure we're going to talk about a lot today, which has to do with
00:04:13.880 the nature of calories and weight gain. I will leave it at that only by way of background to say that
00:04:19.060 we had the incredible pleasure of working together and really getting into the weeds of how one
00:04:24.880 technically tries to measure these things and how difficult it is on all of the challenges and
00:04:29.500 potential pitfalls of this. But let's just take a step back and maybe give folks a sense of your
00:04:33.680 life's work and your life's passion. You've been the head of Pennington Biomedical Research for how
00:04:38.380 many years now? Is it 20 years?
00:04:39.060 I have been for 24 years at Pennington. I was Associate Executive Director for Clinical Science.
00:04:46.900 I'm not the head of the Pennington. I joined after spending two and a half years at Eli Lilly.
00:04:52.740 And before I was 15 years intramural NIH. And the reason I came to this country was to build the
00:05:00.500 first metabolic chamber or indirect calorimetry chamber to measure energy expenditure in people
00:05:07.940 over periods of hours and days. Tell folks a little bit about what it means to be intramural
00:05:13.180 versus extramural NIH. I think when people hear NIH, they sort of have a vague sense of what it is,
00:05:18.840 but maybe that distinction isn't clear to most people.
00:05:21.800 Yeah, the NIH budget is about $33 to $35 billion. But there is a group which is intramural,
00:05:30.580 but most of the money, 80 to 85 percent, goes to all the academic institutions
00:05:36.480 doing biomedical research in the country. I like to be intramural.
00:05:41.520 Just so folks understand what that means, that means you are an employee of the NIH. You work at the
00:05:46.220 NIH campus, and your funding comes from the organization that you work for, unlike someone
00:05:51.320 who's at Stanford or Harvard, who's receiving extramural NIH funds.
00:05:56.200 Correctly. And I was intramural, but based in Phoenix, Arizona, because I worked a lot with the
00:06:02.060 Pima Indians, who have, as you know, the highest prevalence of type 2 diabetes and the second highest
00:06:08.140 prevalence of obesity in the world. But intramural, what I like, you are judged after the facts.
00:06:14.440 You have a budget, and you can do whatever you want. But every three years, you are judged.
00:06:20.820 Whereas extramural, as you know, we chase these grants, and you have to basically provide preliminary
00:06:27.020 data, hypotheses, and you are judged before doing the study. And I think you can be much more creative
00:06:33.840 being intramural than extramural. I'm sure that my colleagues intramural are going to hate me that
00:06:40.120 I say that, but it's true. They should enjoy to be judged after the facts rather than before.
00:06:46.960 So tell us a little bit about Pennington. It's obviously a pretty unique institution. You've been
00:06:52.780 there, as you say, for 24 years. But yet, I suspect it's a place that most people listening to us won't
00:06:57.800 necessarily be familiar with.
00:06:59.160 It's becoming, I think, the largest institution for research in nutrition and obesity. We concentrate
00:07:07.880 mostly on nutrition and obesity. We have about 500 people working at Pennington, and everybody
00:07:14.500 is doing research. We have no teaching. I mean, yes, I have postdocs and things like that, but no formal
00:07:21.260 teaching. And we do research, and we chase. We have maybe a budget, a functional budget of $80 million
00:07:28.660 per year. 50% or 45% of that is NIH. Extramural money coming to Pennington. We do some sponsored
00:07:38.280 projects for pharma or biotech. We have grants from associations like the American Diabetes Association
00:07:46.180 or American Heart Association and so on. And we do basic science, clinical science, and population
00:07:54.280 science, basically, which is to reach the community and implement some of the discovery into the
00:08:01.840 community.
00:08:03.060 Yeah. So the other thing you mentioned a few minutes ago, Eric, was the words metabolic chamber
00:08:08.220 and indirect calorimetry. And I think at some point, because this is going to come up in our discussion
00:08:14.000 as we get into the weeds on metabolism, it's going to be necessary, I think, for the listener to kind
00:08:20.160 of understand how those techniques work. I know I've discussed this on previous podcasts. There's at
00:08:24.980 least probably half a dozen episodes where I've explained how one uses the ventilation of oxygen and
00:08:32.240 CO2 to quite accurately estimate energy expenditure and substrate utilization. But it can never be a bad
00:08:40.620 thing to explain it one more time. So why don't you explain how it works? And you can even use the
00:08:47.140 example of when I was in the chamber for a couple of days, 10 years ago, when I was out at Pennington as
00:08:52.760 a subject or pretend subject.
00:08:55.300 Yeah, there's two things, indirect calorimetry and direct calorimetry. You generate your energy metabolism or
00:09:03.880 ATP by oxidative process. And you oxidize carbohydrate, fat, and a little protein. You don't want to oxidize
00:09:12.680 too many proteins. And this basically build up these ATPs, which are used online for generation or
00:09:21.860 maintenance of the cells or activity and so on. Now, when you have this metabolism, you produce heat.
00:09:30.000 If you have no exercise, no external work, all the energy which is provided in generating this ATP is
00:09:39.560 lost as heat. And this is direct calorimetry. And I was fortunate when I did my PhD back in Lausanne,
00:09:47.660 Switzerland, to have access to both indirect and direct calorimetry. You can really do fantastic
00:09:55.520 studies. We did a study of measuring in vivo what we call the PO ratio. How many oxygen do you need
00:10:04.360 to generate one ATP and all these kind of things by the combination of these two techniques. Now,
00:10:10.860 going to indirect calorimetry, this is an easier one than direct.
00:10:15.700 And sorry, just to interrupt you for a second, Eric, when you're doing direct calorimetry,
00:10:20.300 obviously when it comes to something like food, if you want to know the energy content of food,
00:10:23.780 you can burn the food and measure the heat. When you're doing it otherwise on a living organism,
00:10:28.780 is it possible to do direct calorimetry on something as large as a human? Or is that something you're
00:10:33.900 typically doing on a mouse or something that is small enough that the chamber in which you can
00:10:39.120 measure changes in heat is much smaller and easier to manage?
00:10:42.780 No, we can do that in humans. I was fortunate to be at a place which had one of the two direct
00:10:50.380 calorimeter. At the time, there was one in Bethesda. It doesn't exist anymore. The one in Switzerland
00:10:56.760 doesn't exist anymore. I wish I had a picture to show you, but this is a basically, I would say,
00:11:03.140 1.2 meters by 1.2. It's a little bit bigger than a cubic meter box. And you recover all the heat,
00:11:13.440 and you have dry heat by convection, and you have a layer, a gradient light layer capturing the heat
00:11:21.840 production. You collect the evaporative heat losses from perspiration, expiration, and so on.
00:11:31.220 And you merge all that, and you have a complete heat balance of the person. And we measure these two
00:11:38.400 kinds of heat, and this is basically equal to your metabolic rate. You generate energy by oxidation of
00:11:47.700 substrate, and the byproduct is heat. And with that exercise or external work, energy in is equal energy
00:11:57.680 out. And this is what we measured, and I did a lot of these studies during my PhD. But then at that time,
00:12:05.220 we decided to build a metabolic chamber, which is like an hotel room in which you can live one day
00:12:13.020 or two days. And I think you stayed for two days in one of these rooms at Pennington in Baton Rouge.
00:12:19.520 And here, we measure oxygen consumption and CO2 production. Oxygen is used to oxidize the substrate.
00:12:27.660 It produces CO2 and water. And knowing oxygen consumption, CO2 production, you can calculate
00:12:36.720 the energy expenditure or the energy generated by this oxidative process. And you can also calculate
00:12:44.540 the substrate that you oxidize. If the ratio between the VCO2, the CO2 production, and the oxygen
00:12:53.220 consumption is one, you oxidize carbohydrate. If it's 0.7, you oxidize fat. And protein is something
00:13:02.240 in between, 0.82, depending on the protein.
00:13:06.280 Yeah. And so basically, by measuring just these two things, the actual concentration of oxygen that's
00:13:13.780 being consumed and the rate at which it's being consumed, and the same with production of CO2,
00:13:18.580 you can really infer two things. One, the total energy consumption, total calories consumed,
00:13:26.560 Kcals. And by looking at the ratio of the VCO2 and the VO2, you can calculate what fraction of that
00:13:34.380 is coming from oxidizing carbohydrate versus fat. Having spent probably a total of eight days of my
00:13:40.860 life inside metabolic chambers across a period of a couple of years, it never ceases to amaze me.
00:13:46.280 Never. Just how accurately these rooms work. Because I use an indirect calorimeter all the time
00:13:53.480 measuring VO2 max. It's basically the exact same technology, but it's easier because you're
00:13:58.760 strapping the mask to your face so you have perfect access to exactly the O2 consumption and the CO2
00:14:06.860 production. But it's doing the exact same calculation. It's going to tell you exactly how much energy you're
00:14:12.360 utilizing and where the substrate comes from. And of course, in that situation, you're interested in
00:14:17.080 knowing the maximum amount of VO2 or O2 consumption. So what would you estimate is the error on the hotel
00:14:25.040 room-sized indirect calorimeter where you don't have the luxury of just slapping a mask to the person's face
00:14:31.340 for a few days? Yeah. When I was at NIH, we did a lot of reliability testing in the same person,
00:14:40.140 or you can calibrate the system. You calibrate the system with standard gas that you know the exact
00:14:47.320 concentration to calibrate the analyzers. But you can also mimic someone by burning alcohol or propane,
00:14:55.440 and you can vary the rate of burning. And this is what we did when we did this study with four
00:15:02.280 different chambers. We validated the chambers once against the other one, and we accepted to have
00:15:10.500 3% deviation for CO2 or oxygen based on stoichiometry. You know exactly how much alcohol or propane you burn.
00:15:20.860 You know how much CO2 should be produced and how much oxygen has been consumed. And this is what we did.
00:15:27.440 And you are right. They are very, very precise. And you don't have the inconvenience of the mask. I mean,
00:15:33.100 you couldn't measure with a mask for 24 hours or two days. Right. Because when I was in that chamber for
00:15:38.920 a couple of days on separate occasions, we were trying to replicate as much as possible my life.
00:15:45.240 So I had three meals prepared. I had an exercise bike. I had weights in there, equipment to do everything.
00:15:53.360 And we were very interested in seeing how that would compare with, for example, what we knew I was
00:15:59.160 experiencing in the outside world based on when we could put a mask on me. And also, separately, if you may
00:16:05.380 recall, Eric, we also spent about 10 days using doubly labeled water, which I'm sure we'll talk about at some
00:16:10.880 point as well as a more real world example of this. So all of that is to say that scientists such as
00:16:18.940 yourself have some pretty high fidelity tools to measure energy expenditure. But it comes with a
00:16:27.900 caveat, which is it has to be done under this very controlled setting. These people need to be in the
00:16:33.120 hospital and not just in a hospital, but in a metabolic ward and inside a chamber, which is basically a
00:16:38.640 NASA grade gas chamber with how many sensors, by the way, just out of curiosity, how many O2 and CO2
00:16:45.280 sensors would be in a particular chamber? We don't need many because we need to homogenize the air in
00:16:52.240 the room. And what you sample in one corner of the room is the same as the other corners. That's why,
00:16:58.360 but we have to measure humidity. You have to measure temperature because you have to do this
00:17:04.240 correction, what we call STPD, which is standard pressure, et cetera, to calculate the energy
00:17:11.400 generated by this oxygen. But yeah, I mean, it's quite phenomenal, the accuracy of those. And to go
00:17:18.540 back to your question, the accuracy or the precision is about two and a half percent. Now, if you repeat
00:17:25.700 yourself five times or, and myself, there's a little bit more variability because we vary from one day to
00:17:32.580 another one and so on. But I mean, this is quite amazing that we can calculate so precisely your
00:17:40.240 energy expenditure during a day or two days and so on. I wish we had the same system to calculate the
00:17:46.880 energy that we put in. Yeah, that's a great point. Outside of having food prepared in a metabolic
00:17:53.820 kitchen, which of course was also done for this experience, I think at best we're probably plus or
00:17:59.380 minus 10%, right? I mean, it's very difficult to estimate energy intake.
00:18:04.980 When it's in free living, it's worse. When you do that under supervision and you provide all the
00:18:12.320 meals like Kevin Hall is doing, like we're doing, then you have a good estimate and you subtract what
00:18:18.920 is returned on the plate or this kind of things. But it's not normal life. As soon as you go to normal
00:18:25.140 life and free living conditions, things are falling apart. I think that is a really nice intro into
00:18:32.560 kind of a philosophical question that will take us towards some of the experimental work. So
00:18:37.540 I was actually going to launch into the explanation of the energy balance model and talk about the work
00:18:43.580 that you and the other folks that we just talked about did a decade ago. But let's pause for a moment
00:18:49.360 on the statement you just said, which was, look, in the free living environment, we cannot estimate
00:18:54.820 energy intake worth a damn, which is to say that 99% of people out there who aren't weighing every
00:19:02.780 single morsel of food they eat every single time they open their mouth, which again is virtually nobody,
00:19:09.240 are going to have enormous variability in what they're eating. And so I put myself in that category,
00:19:14.500 right? I pay no attention to how much I'm eating in terms of weight. I'm just sort of eating by
00:19:19.320 kind of my appetite. Sometimes I overeat too much. My appetite gets the best of me. I'm surrounded by
00:19:25.580 highly palatable foods that I overeat. And other times, you know, I'm just really busy. Like yesterday,
00:19:30.780 I just didn't get around to eating that much. But here's what's interesting, Eric. My weight lives
00:19:36.400 within about a two pound variation for years. And I don't think I'm unique in that. I would guess
00:19:43.580 that you're pretty similar as well. I think many of us find ourselves in kind of a couple of pounds
00:19:48.380 of variation, most of which is probably water weight varying over years. And yet we're not really
00:19:55.080 paying attention in excruciating detail to how much we eat. So first of all, do you agree with the
00:20:02.240 assessment that that's not an uncommon phenomenon? Yes. But on the other hand, if you take your lifetime
00:20:09.060 history, maybe you're an exception, but I have gained some weight. When I got married in 1975,
00:20:18.420 I weighed 69 kilos. Now I weigh close to 77. Now it's 50 years later, of course, but you have this
00:20:28.000 change. You have also a change in your body composition. And it's very rare that people
00:20:33.660 are staying the same constantly. I mean, you may be an exception. No, no, I would not suggest that
00:20:40.800 I'm an exception. I've had probably more variation in my weight than even what you're describing over
00:20:45.580 the period of time. But I guess the question I'm getting at, Eric, is how does the body regulate
00:20:53.360 energy storage, which is effectively what is determining our weight? It's how much are we storing
00:20:59.400 as fat? How much are we storing as lean tissue? That seems very, very regulated, despite very
00:21:07.540 little control over the input and the output. We're free living animals who live in an environment with
00:21:15.180 endless inputs. So we have to somehow regulate that. And frankly, very little reason to do deliberate
00:21:22.900 outputs, right? Obviously, the majority of our energy expenditure is based on essential function of
00:21:29.080 life, just the necessary ATP production, as you described it for cellular function. But it's not
00:21:35.120 like most of us are out there expending energy deliberately, i.e. exercising and moving necessarily
00:21:42.820 to expend energy. So as we enter this discussion of the energy balance model, let's just talk about
00:21:48.780 energy balance. Why are we so largely able to conserve mass despite very noisy inputs and output
00:21:59.040 into the black box? I think I had an answer. I hope that I had an answer, but I don't. You know,
00:22:05.820 when leptin was discovered, it was a ha-ha moment. We have a signal which comes from the energy storage,
00:22:13.720 and therefore, you know, it seems to regulate food intake, also energy expenditure and all that.
00:22:20.200 I was fortunate to have access to the three Turkish leptin-deficient people that we measured in these
00:22:27.960 chambers in Baton Rouge. We thought that we would have a clue, and it was not the case. We know that
00:22:35.440 leptin is very good to defend against the loss of weight when it becomes extreme, but it doesn't work
00:22:43.200 on the other side of the equation when you creep up with your weight because you become leptin-resistant
00:22:51.620 and your leptin is not telling you stop to eat. I think that we learn a lot about the biology of energy
00:22:59.820 balance thanks to leptin. But then we need to think that we have also signals coming from the fat-free mass.
00:23:09.020 Now, what is the fat-free mass? We measure it as everything but the fat, and we call that fat-free
00:23:16.380 mass, but it's liver, it's skeletal muscle, it's everything but the fat. And I think that there
00:23:22.820 are signals that we are still chasing. John Blundell showed that we eat according to our fat-free mass,
00:23:31.000 which is basically we eat according to our resting metabolic rate, because fat-free mass is the major
00:23:37.040 determinant of your resting metabolic rate. But what are the signals? I don't know. I still don't
00:23:44.020 know. We have to be modest here and say there are still things that we don't understand when it comes
00:23:50.060 to this energy balance. Now, I can understand that why you don't gain five kilograms over this coming
00:23:57.620 year, because in response to creeping up your weight, you burn more energy. If you do the same physical
00:24:05.160 activity, this extra five kilos or 10 pounds is going to cost you more energy. Your resting metabolic
00:24:13.140 rate is creeping up, and basically you offset that. But why are we so good at maintaining, like you said,
00:24:21.980 within a couple of pounds over a year or two years or three years or five years? And I think that we are
00:24:28.240 still missing some signals, but I think that there are signals coming from when FGF21, which is a signal
00:24:35.300 coming from the liver, was discovered. I said, oh, maybe that is. Or when you have some of the
00:24:41.120 myokines coming from the skeletal muscle, I said, maybe this is it. And it's not been it. And I think
00:24:48.100 that we have to be modest and say, hey, we still have things to discover when it comes to this regulation of
00:24:56.040 energy balance. But as a population, we have not been very good. I mean, from the 1980s to 2010,
00:25:03.500 the American population has gained 10 kilograms. It's 22 pounds in 30 years. It means that there is
00:25:13.300 still the major driver is this environment. And the change in the environment has been the trigger
00:25:20.320 of this weight gain. But of course, people, some people are successful, some are less. And this is
00:25:27.800 a problem. And of course, now we have an epidemic of obesity. It has replaced the contagious disease
00:25:34.340 of the past. And now we have all these constellation of conditions which are associated with obesity.
00:25:41.560 Eric, if you were to guess, which I think is the best we can do, although I think it's informed guessing,
00:25:47.260 I don't think we're just guessing in the dark. How much of the regulation do you think is occurring
00:25:54.920 on the appetite side, meaning feedback from whatever is happening in the system? And let's just
00:26:00.460 pause it, as you said, that it's coming from the lean part of the system. So the organs, the skeletal muscles,
00:26:06.560 all but the adipose tissue, and that that is working to feed into the appetitive system.
00:26:13.740 Or do you think the balance is more on the expenditure system, where those signals are
00:26:21.260 feeding to make us move a little bit more? Or simply, as you say, it's the extra weight you have
00:26:27.480 to move around. If you're going to carry, people should pick up what 10 kilos is. That's an awful lot
00:26:32.040 of weight. If you have to carry an extra 10 kilos up a flight of stairs, and every time you get up and
00:26:37.160 move around, you're going to expend more energy. So do you have a sense of the balance of that
00:26:42.820 regulatory pressure?
00:26:45.000 Yeah. Peter, when I first joined the NIH, I did a study in Pima Indians, who are very prone to weight
00:26:53.400 gain, as you know. And we measure in 150 people, the 24-hour energy expenditure, as well as the resting
00:27:02.440 metabolic rate. And we found that there was large variability between people after adjusting for
00:27:09.720 their body size, fat-free mass and fat mass. Now we do better because we have organ size, and we do MRI,
00:27:15.740 MRI, and all these kind of things. But there is variability, and this variability is associated
00:27:22.060 with family membership. In other words, we can say that there is a genetic background to that.
00:27:28.240 But what we found was that those people in the lower tertile of this metabolic rate adjusted for body
00:27:35.880 size were at much higher risk of gaining weight. But when we try to attribute the weight gain either to
00:27:43.720 energy expenditure being low or the other side of the equation, intake was 80%. It reminds me,
00:27:54.220 there are so many systems which are basically regulating energy expenditure and food intake.
00:28:01.540 Take nicotine. Nicotine is a stimulant of energy expenditure. Smokers have higher metabolic rate,
00:28:08.620 but they have less appetite. Take the activity of your sympathetic nervous system. It is also
00:28:15.620 thermogenic, but it cut appetite. And I think that we have to understand better these two systems.
00:28:23.700 But to answer your question, I would say 80% is on the side of the energy intake.
00:28:29.800 That's sort of been my intuition as well. But because I don't keep up with this literature
00:28:34.700 nearly as much as I used to, I wanted to make sure that that was still largely the view of the people
00:28:40.340 at the forefront of this field. And you know, for example, sorry to interrupt, but we know that
00:28:45.580 exercise is pretty bad for weight loss. If you just tell people, okay, go to the gym three times,
00:28:52.260 or you even do under supervision, people don't lose weight. And Donnelly at University of Kansas has done
00:28:59.040 a ton of study like that. And the physical activity for weight loss is a B minus at best in term of
00:29:07.680 evidence that it plays a role.
00:29:10.200 And let's talk about why, because again, it is counterintuitive. I know this, and I preach this
00:29:15.140 to my patients left, right, and center, which is, you probably heard me say, Eric, I will go to my
00:29:19.180 grave maintaining, I suspect, until new evidence emerges that exercise is the single most important
00:29:24.360 thing we need to do for health. But I'm always quick to follow that up if asked with, but it's
00:29:29.340 not the tool you're going to use to regulate body weight. Energy intake, nutrition is the more
00:29:35.720 important tool to regulate body weight. And so explain to people why perhaps, if you could provide
00:29:42.640 a teleologic explanation for why, because it is counterintuitive. If you just look at the human
00:29:48.100 body as a machine, you should have no preference for expenditure of energy versus input of energy,
00:29:55.500 you should say they're equally efficacious. But again, any clinician will tell you that's not true.
00:30:01.360 And any scientist will tell you that's not true. But do we have a reason for why it's not true?
00:30:07.080 I think, first of all, if you try to put calories on your exercise, it's easy on a bicycle,
00:30:14.500 you know, the efficiency, 25%, you know, the workload, and so on. And you can calculate or
00:30:21.900 you can use your mask and measure oxygen consumption. It's very easy like that. And I think
00:30:28.620 that there is a compensation. Now, exercise, very vigorous exercise is anorectic. You don't want to eat
00:30:36.400 after you finish a marathon, or at least I don't.
00:30:40.120 No. And by the way, just to interject, I interviewed George Brooks from Berkeley recently,
00:30:44.100 and he shared with me on the podcast something I didn't know before, which was that lactate
00:30:49.040 specifically is probably partially driving the anorexia we experience following intense exercise
00:30:56.020 that might not be present with low intensity exercise. So I thought that was an interesting
00:31:01.280 way to connect a fact that I think most people appreciate, which is go off and do interval
00:31:06.920 training. The last thing you want to do for the next hour or so is eat.
00:31:10.100 But light exercise has the opposite effect. I think it drives a little bit appetite. And I think
00:31:19.140 Tim Church, who was at Pennington, did a study called eMechanic. And basically, they measured every
00:31:27.300 calorie spent on exercise, on a treadmill, on a bicycle ergometer, and all that, and look at the weight
00:31:35.220 of the people with these different doses of exercise. And there was a compensation. Now,
00:31:41.140 what he didn't measure was to use doubly labeled water. Did they compensate by being less active out
00:31:48.660 of their periods of exercise? You have 90 minutes of exercise, but then, you know, you relax a little bit
00:31:56.100 more rather than fidgeting or moving and so on, or you sleep a little bit longer. This he didn't measure,
00:32:02.740 but there was this compensation with food intake. And I think, first of all, I didn't say that
00:32:09.660 exercise is not good for health. Right. I didn't suggest you were. I was just making sure people
00:32:14.600 knew the distinction. Because I want to make sure, because I'm an aficionado of exercise. I know you
00:32:19.480 are. I know how good it is for health. Yes, yes. But it's not as good for weight control
00:32:24.140 in general. And I think that you have to do the calculation of how many calories are burned
00:32:31.100 when you run a K or a mile and so on versus how quickly you can ingest the calories, the same amount
00:32:40.580 or much more. And I think that there is a difference here that people understand. But exercise and physical
00:32:47.140 activity is the key for weight loss maintenance. And you know, the weight registry from Rena Wing and
00:32:55.100 Jim Hill, they showed that those who were successful at maintaining the weight loss at five years after
00:33:03.240 the intervention were those who engaged in more physical activity. And I still believe that a
00:33:10.320 nutritional approach to weight loss without physical activity or exercise prescribed is not a good
00:33:18.620 strategy. We should implement both and try to have people enjoying the exercise. Most people,
00:33:27.560 I remember one of my colleagues, Richard Mergman, said, I would never exercise. I'd rather be sitting in a
00:33:34.020 cold bathtub to generate some heat rather than exercise. And there are some people who cannot
00:33:41.000 exercise. But I think, again, this is from childhood, that you take the taste of exercise, that you become
00:33:48.640 more physically active in the rest of your life. It's not at the age of 40 because you have too much
00:33:55.700 weight that they can tell you, oh, you have to do your 150 minutes per week of moderate to vigorous
00:34:02.340 activity and all that.
00:34:04.020 It doesn't work in general. But I think physical activity is a key point in metabolic health in
00:34:13.200 general. I agree with that completely. When I look at the data from Jim Hill that you've just cited,
00:34:19.540 I've always found it difficult to infer the direction of causality. And you're correct that
00:34:25.040 the people who are most successful in maintaining weight loss are going to be on balance far more likely
00:34:31.160 to be people who do a lot of exercise than those who don't. And so, of course, it could be that doing
00:34:36.100 a lot of exercise is a valuable tool to drive weight maintenance, i.e. maintenance of energy
00:34:41.900 balance. Alternatively, it could be the people who metabolically get fixed through weight loss are the
00:34:48.400 ones that have an easier time exercising. But I will say this, and I'm curious how robust the data are.
00:34:55.460 I do think one thing that exercise can do for you, and I feel this personally, and I know a lot of my
00:35:01.960 patients do as well, is yes, you could go ride your bike for an hour and you could burn 600 kilocalories
00:35:09.100 and you can eat 600 kilocalories in way less than an hour. But exercise seems to sharpen your appetite
00:35:16.560 to a point that makes you a more responsible eater, if that makes sense. In other words, I think it hones
00:35:23.440 your appetitive signals. And the one thing you as the individual have to do is just be mindful of the
00:35:29.560 speed at which you eat so that you give the brain a moment to recognize what is happening. So let me give
00:35:37.180 you an example of how that works tangibly. If I do a zone two bike ride for an hour, again, that's going
00:35:44.680 to be for me, I know because I measure it, I can measure it exactly. That's going to be about 750 to
00:35:49.760 800 kcal is how much energy I will expend. Above your resting? No, total. Total energy expenditure is
00:35:57.980 750 to 800 kcal in the hour. So call it 800 to make the math about easy. So if I wait an hour before I
00:36:08.320 eat, and I don't eat very quickly, I don't do the usual Peter Atiyah, there's someone who's going to
00:36:14.740 take the plate from me if I don't finish this right away, I won't overeat. And I'll be fine for the rest of
00:36:20.220 the day, I won't have a hyperbolic appetite. Conversely, if I go to eat within 20 minutes, 30 minutes, and I
00:36:28.160 pay no attention to the speed at which I eat, I can easily consume 1000 calories in that one sitting and
00:36:34.840 abrogate the entire energy effect of the exercise. Obviously, I'm still getting all the benefits of the
00:36:40.060 exercise. So first of all, curious if you have seen this, if you have any insight into the effect of exercise on
00:36:48.120 how we subsequently regulate appetite, and how we might sense the hunger hormones, everything from
00:36:55.520 leptin, ghrelin, and even GLP-1? I don't have an answer to that, because it's not my field energy
00:37:02.800 intake. But on the other hand, you just mentioned the GLP-1. I think these gut hormones, I mean, you take
00:37:11.320 GLP-1, GIP, CCK, PYY. Glucagon. Glucagon. If you put glucagon in insulin, I was talking about the gut,
00:37:21.100 the GI hormones. Anyway, I think that there is no question now we start to know more, because they are
00:37:28.040 such good targets for weight management. We start to know more about the physiology of these hormones.
00:37:36.160 And I think that there is no question in my mind that the speed at which you deliver this food in the stomach
00:37:44.940 and it leaves the stomach is very important for the kinetic of these gut hormones, which are important for
00:37:51.820 the regulation of your food intake in general. I think this is one of the things that these GLP-1 and
00:38:00.580 combination of peptides now has shed light on is that they are potent modulators of your intake.
00:38:10.300 Now, the interaction between the exercise that you do before and the meal that you have 20 minutes
00:38:16.660 after and the speed of the meal and all that, I don't know this triangle how it works, but I think
00:38:23.660 it would be a very good topic of research to know the interaction between your physical activity or
00:38:31.300 the bout of exercise, the speed at which you ingest the calories and the delivery of these gut hormones.
00:38:39.880 And again, to make it an even more interesting experiment, but now much more complicated,
00:38:45.400 you introduce a fourth variable, which would be the macronutrient composition of the meal itself at
00:38:53.400 isocaloric substitutions. And maybe that's something we'll talk about now as we go back to the idea of
00:38:59.460 energy balance. So going back to how you and I met and the kind of work that we were interested in,
00:39:05.940 we were interested in a question, a very specific question. And I like specific questions because
00:39:11.200 the more specific the question, the easier it is to design an experiment to test it. And the more
00:39:16.700 likely you are to get an answer that you can interpret as highly probable. Feel free to modify
00:39:21.460 this, Eric. But I think the question we were trying to ask was under isocaloric conditions,
00:39:27.700 does varying the macronutrient composition specifically between carbohydrate and fat while holding
00:39:35.200 protein constant have any bearing on non-deliberate energy expenditure? First of all, would you agree
00:39:42.800 with that statement? And then we can turn it into English, but just scientifically, would you agree
00:39:46.460 that that was the question we were trying to answer? Yes, it was the question. Isocaloric is the
00:39:52.240 important word. That's right. Because now can you do that in the everyday life under not isocaloric
00:40:00.140 condition, but what you want to eat? Which of course, we'll talk about that in spades.
00:40:05.200 But this was a very important question, although truthfully, I think most people felt the answer
00:40:09.740 was known. Well, I guess I should translate what I just said into English. Feel free to interject and
00:40:14.420 help me. What we basically said was, if you give people, a bunch of people, meals, let's just not
00:40:20.660 even use a bunch of people, one individual. You take one individual and you feed them meals on subsequent
00:40:27.560 days or weeks or whatever, where you don't change the total number of calories one iota. You don't even
00:40:34.100 change the amount of protein. You simply manipulate the ratio of carbohydrate and fat, such that
00:40:40.580 obviously when one goes up, the other has to go down, such that you can preserve the total number
00:40:44.760 of calories. And when you feed people meals under those conditions, the null hypothesis should be
00:40:51.300 that their energy expenditure doesn't change. Why would holding a fixed number of calories in
00:40:59.380 to this system change the number of calories that the system expends? Again, it's important that we
00:41:04.860 held protein constant because we know about the thermogenic effect of protein. So that can actually
00:41:10.300 sway things if you change protein a lot. But the alternative hypothesis that was being tested was,
00:41:15.720 no, actually, if you really swing fat and carbohydrate a lot, you could indeed change energy expenditure.
00:41:24.340 Would you add anything to the English version of the question?
00:41:28.060 No, I think it was a question. And we were a little bit skeptical. It was the start of the
00:41:34.420 carbohydrate insulin model. We're used to the energy balance model, but I think it was a good question.
00:41:43.180 And I like the way we debated that with the red team, the blue team, if I recall correctly,
00:41:49.280 and we were arguing about the best design. And at the end, now, if I had to redesign this study,
00:41:56.000 I would do it differently.
00:41:57.860 Tell people how it was done, and then tell people what you would do different. Because
00:42:02.660 this is probably an experiment that might be worth redoing under improved conditions. But I'm very
00:42:08.540 curious, because I haven't given this much thought, but I'm very curious as to what you would do
00:42:12.020 different. Explain to people how this experiment was done.
00:42:14.160 The experiment was done to do a isocaloric intake over four weeks, I think. We had the
00:42:22.620 baseline diet, which was the SED diet, the standard American diet. And we had after a low-carbohydrate
00:42:32.580 diet or ketogenic diet for four weeks. And the hypothesis was that, and this was led by
00:42:40.100 the people, we've been bringing up the carbohydrate insulin model, saying that you create a basically
00:42:48.760 uptake of these substrate from the blood into the storage, mostly the adipose tissue and maybe some
00:42:56.820 in the liver. And you deplete from a substrate or energy substrate your circulation, and it puts you
00:43:06.300 in a state of semi-starvation. What is happening when it goes to the brain when you have semi-starvation,
00:43:14.480 you shut down your energy expenditure and you increase your appetite. And this was playing with
00:43:21.480 that, saying that now if we switch to a diet which is going to be less conducive to storage,
00:43:30.500 i.e. less insulin secretion, because it was less than 10% carbohydrate, between 5% and 10%,
00:43:39.480 if I recall correctly, we would cause this, basically this semi-starvation condition in the
00:43:46.300 systemic circulation. And this would basically increase your energy expenditure. And I think
00:43:53.240 that David Ludwig at the time had some data already showing by doubly labeled water that there was an
00:43:59.780 increase. But we are arguing that doubly labeled water is not precise enough. It goes back to our
00:44:05.960 discussion about indirect calorimetry. And we said, why don't we do it in the confinement of a metabolic
00:44:13.440 chamber? And this is what we did. And to my surprise, there was an increase, at least early, because we
00:44:21.040 had couples of, I didn't go back to the papers, but we had measurements every week for two days, if I recall
00:44:28.320 correctly for the four weeks. And the first week and maybe the second week, there was an increase
00:44:34.780 which was significantly higher in sleeping metabolic rate, as well as 24-hour energy expenditure
00:44:41.400 under the ketogenic diet. And boom, yes, there is an increase. Now, was it a significant physiological
00:44:50.660 increase? I mean, we can argue about that. When we talk about metabolic adaptation, because people are
00:44:56.680 talking about that now, we always say we need at least 150 calories. In the study, we achieved
00:45:03.860 statistical significance, but it was just above 100 calories per day. And I was surprised myself of that.
00:45:12.380 Now, we didn't measure the appetite of the people. I mean, were they less hungry under the ketogenic diet?
00:45:19.500 Now, it brings us to all the weight loss studies which have been done either with a low-fat diet or
00:45:26.840 low-carbohydrate diet. If you do a meta-analysis, it seems that there is a slight advantage to the
00:45:33.500 ketogenic diet for the weight loss period. Basically, I was surprised, and I was, as a Swiss, I was kind of a
00:45:42.020 little bit more neutral sometime, rather than the two camps, the red and the blue. I was surprised that
00:45:48.540 there was this effect, but it disappeared at the fourth week or the third and the fourth week.
00:45:55.240 So again, just to make sure people understand that finding. So the finding, and I'm glad you
00:45:59.760 remembered. I forgot the numbers. I didn't think it was 100. For some reason, I thought it was 90. But
00:46:03.980 again, who cares at that point? We had sleeping metabolic rate or 24 hours.
00:46:09.340 That's right. That's right. What the study basically found, and the study was, again,
00:46:13.620 it was a very well-designed study in that there were maybe 16 subjects, which is obviously sounds
00:46:19.380 like a very small number, and it is. But given the complexity and cost of keeping 16 subjects
00:46:24.580 housed in a hospital for a month, and then also putting them in metabolic chambers every few days,
00:46:30.960 this isn't a study that you're going to do with 500 patients. But to increase the statistical power
00:46:36.660 of the study, it was a crossover study, which meant that every patient was their own control,
00:46:41.940 and that's what allows you to get away with having so few subjects. So interestingly, I think it's safe
00:46:47.840 to say that the effect size was large enough that it suggested a signal, but not so large that it
00:46:55.420 dispositively answered the question. And in many ways, it served as fodder for more questions,
00:47:01.980 which I guess is not uncommon in research. It's very rare that one experiment gives you the
00:47:07.520 definitive answer, and rather, it just points you in a slightly different direction and gives you
00:47:12.360 more questions, which then begs the question, which is, if resources were not a limit, what would be
00:47:18.500 the follow-up experiment to that? I wish I had an answer. I mean, I'm tortured between very well
00:47:26.080 controlled studies. We do, like Kevin Hall does, where you basically domicile the people, you feed
00:47:34.840 them whatever you want, you know exactly what you feed them, and you look at outcomes. I mean, I like
00:47:41.380 that, but then how do you transpose that in real life? And one of my mentors was JP Flatt, and JP Flatt
00:47:49.840 says, obesity scientists, they have a tendency to either look at the expenditure side of the equation
00:47:56.780 or the energy intake, but they never put the two together. And he was right, because a lot of studies,
00:48:04.780 you have an outcome which is on this side or on this side, and you maintain the other one.
00:48:09.760 And I think that, to me, designing a study would be, first of all, in free living condition, but it
00:48:16.800 would need a lot of people, because you know you can prescribe all what you want to people. They're
00:48:23.320 going to do whatever they want at the end of the day. Some of them, if you screen them very carefully,
00:48:29.040 are going to be much more compliant and adherent to the instruction. But this is what needs to be done.
00:48:35.960 And by changing here, we changed not the calories, just the composition of the two diets, 10%
00:48:44.680 carbohydrate versus 45% or 50% carbohydrate in the other diet. And that's all what we did. And I think
00:48:54.680 we concentrated only on the energy expenditure, but we even didn't ask very much. They had visual
00:49:02.060 analog scale if they were more hungry or all these kinds of things. But we kind of ignored the food intake
00:49:09.220 that we were clamping. And this is not real life. If you do something, and you know, you talk about
00:49:16.240 engaging on physical activity regimen or exercise and all that, I mean, you have to look at the impact on
00:49:24.620 the other side. And this is the same question that I have. Now, I'm not helping you in designing the perfect
00:49:31.660 study by saying that. But on the other hand, again, we have good tools to measure energy expenditure. We have
00:49:40.080 reasonably good tools to measure where do the calories come from. But we have no tools to measure energy intake. But it's
00:49:50.340 going to come. I bet you that within, I may not be here, but within a couple of decades, we'll have a
00:49:58.300 caller here, which is going to measure your calories coming from fat, carbohydrate, or protein.
00:50:04.500 I think it should be sooner than that, Eric. I mean, I really do think as image recognition gets better
00:50:10.480 and better with AI. To me, I would actually hope that within a decade, if not less, we are at the
00:50:17.700 point where if you can weigh something and take a photograph of it, we should have enough training
00:50:24.820 data that you should be able to know exactly what is in it. Now, that doesn't account for how much of
00:50:30.100 that thing you eat. But assuming you have something that you weigh and you can photograph and you say,
00:50:35.600 I ate all of it or I ate half of it, we should be able to do better than 10%. We should be able to do
00:50:41.360 within 5%. What is the caloric density of that food and the macronutrient breakdown? I wouldn't
00:50:47.660 have said that five years ago. Like five years ago, I would say that's impossible. But given what I'm
00:50:52.140 seeing with image recognition in AI, that to me has to be the future for nutrition research and in a
00:50:59.900 free living environment. I think you put your finger on the exact point. And now I'm the PI of one of the
00:51:06.480 six clinical sites for nutrition for precision health. This is basically a ancillary study of all
00:51:15.200 of us. All of us is a million Americans who are basically providing biosamples, access to the health
00:51:24.240 electronic records and all that. And then this sub study is really to look at the intersection between
00:51:32.040 their health and their nutrition. And there is three modules. One is on 10,000 people. And one of the
00:51:41.380 way to measure is exactly this little camera sitting on your glasses, and also a system which is measuring
00:51:50.600 if you are chewing or not. It's not enough to see the food and going, but is it chewed? And I agree
00:51:58.880 with you. I mean, I was not thinking about that. I was thinking about something much more like a CGM.
00:52:06.020 Who was dreaming of CGM 30 years ago when I was working with the Pima Indians? We were not thinking
00:52:12.500 about that. Now you have CGM and you can measure your, probably your insulin from contact lenses and things
00:52:21.800 like that. And I think this progress are going to help us. Now, are we going to be smarter designing the
00:52:27.860 study? I'm not so sure, but we'll have the tools to be a little bit more real life rather than incarceration
00:52:36.520 in a metabolic ward. Yeah. I mean, I think that, and again, it's, you're so much more thoughtful on
00:52:43.740 this, Eric, because it is your world. It's not my world, but I occasionally will think about it.
00:52:48.440 But as I'm sitting here now reflecting on it with you, my intuition is that the questions are
00:52:53.480 complicated enough that the difference between efficacy and effectiveness have to be separated in
00:52:58.340 studies. And I think if this question of macronutrient composition, isocaloric macronutrient
00:53:06.540 manipulation impacting energy expenditure is to be put to rest, it can only answer that question. It
00:53:14.160 cannot attempt to answer the impact of appetite as a movable variable. It can do it as a swing variable,
00:53:21.640 meaning, as you said, you can force people to eat a clamped amount of food and then measure
00:53:27.640 subjectively or even using PPY and ghrelin and other hormones. So somewhat objectively,
00:53:34.820 somewhat subjectively measure a petitive response to that. I think the biggest mistake of that study
00:53:40.440 was actually not creating a big enough divide in the macronutrients. I think as an efficacy study
00:53:47.120 that was testing a theory, just a theory with, again, you start with a very theoretical response
00:53:54.520 and then you build from there to say, okay, is this theory applicable? In retrospect, I think it should
00:54:00.640 have been more extreme in the carbohydrate and fat differences. I think one should have been, if the
00:54:07.320 carbohydrate insulin model was being tested, one should have been a very, very, very high insulin diet and a
00:54:14.300 very, very low insulin diet that were isocaloric. And by the way, let's assume you do that experiment and
00:54:20.400 you get a difference of 250 kcal a day. Well, you still don't know if a ketogenic diet is a better
00:54:28.060 diet in a free living environment because you're probably not comparing it to somebody who's eating
00:54:33.900 80% carbohydrates. So then you still have to do the next experiment, which is maybe the one we did.
00:54:41.180 And then ultimately you have to be able to do the free living experiment where people make their own
00:54:48.720 choices based on appetite. That has to be sequenced, I think, to answer the questions. These are difficult
00:54:55.740 and costly experiments to do. Also, one thing that I still have in my mind, all the studies which came
00:55:04.500 from Europe about modulating the composition of the diet and look at the impact on the matching of
00:55:14.860 your RQ to the intake. Even Steve Smith that we're working with did this study called ADAPT. He was
00:55:24.100 isocaloric all across, but all of a sudden you continue with more fat. The FQ of the diet,
00:55:32.120 the food quotient, was decreased. And then it takes days to basically have a matching of your RQ to the
00:55:41.820 FQ, which means you oxidize what you eat. Whereas if you do the contrary, you increase carbohydrate,
00:55:50.560 it takes one day. And that's why I still believe. And back in Switzerland, we did this study where we
00:55:58.180 were giving extra fat as LCT, long chain triglyceride or MCT, because the MCTs are oxidized quicker.
00:56:09.460 And we found that against the culprit is always the fat. And we are very good at matching
00:56:18.480 carbohydrate oxidation to carbohydrate intake. Very good. It's very difficult. First of all,
00:56:24.920 you have what? 500 grams of glycogen stores, 100 in the liver, 300 to 500 in the muscle. That's all.
00:56:33.560 It means if you have a lot of carbohydrate, that's a huge signal. And protein, the same thing. You know
00:56:40.580 how difficult it is to build up your muscle mass or your protein mass in the body by just eating more
00:56:48.980 protein. You have to exercise or you have to take anabolic steroids or whatever. But the fat is the
00:56:57.040 one which is not regulated. That's why I still have this problem with the carbohydrate insulin model.
00:57:03.720 It works. Let's say there was a slight increase in energy expenditure. It seems to work for weight
00:57:10.540 loss. It's better with ketogenic diet than with a low fat diet. But in your entire life, I don't think
00:57:19.320 it works. And piling the fat. I mean, you have done some of that. I did it for three years. My intuition
00:57:27.680 is that this always sounds like a cop-out when you say it. And I hate when people say it. But I do think
00:57:34.200 it's kind of true when it comes to nutrition. There's so much heterogeneity between individuals,
00:57:40.740 both genetically and environmentally, that we have to release our agenda from this idea that there is
00:57:49.400 a perfect diet for everybody. Never mind health, even when it comes to weight maintenance. Let's pick
00:57:55.920 a simpler variable, which is nothing but a subset of health. Weight maintenance as one piece of the
00:58:02.740 health puzzle, it strikes me as impossible to suggest that there is a true diet that is good for
00:58:10.720 everybody. I think that, again, based on a person's genetics and their own living evolution, i.e. their
00:58:18.480 epigenetics and their environment and other factors, psychological factors, which of course can be quite
00:58:24.160 genetic, there are either several or few dietary options that are easiest for a person to adhere to
00:58:33.560 to maintain weight balance. I think that carbohydrate restriction, especially extreme
00:58:40.260 carbohydrate restriction, happens to be one of the more efficacious ways for individuals to restrict
00:58:49.620 something in the larger service of restricting calories. Because at the end of the day, whatever
00:58:56.740 you choose to restrict, whether it be certain macronutrients, alcohol, the time during which you allow
00:59:05.220 yourself to eat or just directly the number of calories, some form of restriction is necessary
00:59:13.700 for weight balance in an infinite food environment, which is the one that we have now found ourselves
00:59:21.340 living in for the past 0.01% of our genetic existence as a species. It's a very new problem that we have
00:59:28.660 to be so surrounded by infinite nutrition and therefore it requires some degree of restriction.
00:59:37.020 And you just have to pick your poison. Do you want to directly restrict calories? We're going to talk
00:59:41.420 about that. That's the calorie study. Do you want to restrict the timing in which you eat? We're going
00:59:45.680 to talk about that as well. That's time restriction. Make a smaller and smaller eating window. Or do you just
00:59:51.120 want to pick some boogeymen within the diet and say they're the bad guys? I don't eat fat. I don't eat carbs.
00:59:56.680 I don't eat animal protein. I don't eat whatever. And if I do that enough, I'm going to also restrict
01:00:03.100 energy intake. That's not a very satisfying answer. I think people want to believe that there is one
01:00:09.080 perfect diet, one perfect way, but I just don't buy it. I'm with you. And I think that we are now in the
01:00:18.080 era of precision medicine or personalized medicine. And I think that this is what the NIH is embarking
01:00:26.660 on when they do this nutrition for precision health, when they do this study that I'm also a PI of a
01:00:34.500 clinical site, which is molecular transducers of physical activity, to look at in lieu of your
01:00:42.700 genetic background, your environment, your socioeconomical status, one size does not fit all.
01:00:49.780 We have the dietary guidelines. They are applied for the entire nation. And they tell you, you know,
01:00:57.880 every time it's the Mediterranean diet or the DASH diet, which are the best and all these kind of
01:01:04.160 things, but not for all. And I think that this is where we are going to have a huge development. It's
01:01:11.620 to go, I don't think it's going to be individualized, but at least for groups of people
01:01:17.600 having the same, you know, different strategies and restriction has to be one of that. But now,
01:01:26.160 how do you restrict? Do you restrict by public policies, by taxing things?
01:01:32.880 I feel strongly against that. But of course, I would describe myself as a pretty staunch libertarian
01:01:37.760 when it comes to that kind of stuff, not an extremist. I do believe there's a role for
01:01:42.120 government, but I think long-term compliance and trust on the part of the public will not come
01:01:48.060 through that type of environment. So what I think is really the answer is one is better education.
01:01:54.820 And I don't mean education, like we're going to sit kids down in first grade and teach them this.
01:01:58.980 I just mean public education and better advocacy and education from the scientific and medical
01:02:04.040 community, which says kind of what I just said a few minutes ago, which is, hey, you're not broken,
01:02:08.960 you're not defective, but you might be one of the people for whom the average approach is not going
01:02:14.400 to work. But step one is every one of us needs to accept that in exchange for living in the greatest
01:02:22.660 period of civilization, which is where we all live, none of us would trade places with the king of France
01:02:30.680 or the king of England 500 years ago. You just wouldn't do it. I'd rather be the most average
01:02:36.180 human being in 2024 than the single most important person in 1400. So we just have to accept the fact
01:02:42.800 that we are all so shockingly privileged to be alive at this moment, but that privilege comes with a
01:02:49.460 couple of expenses, comes with some costs. And one of the costs is we live in an environment that has a
01:02:56.820 little bit of toxicity with respect to things like food. And we have to pay a price. We have to pay a
01:03:03.220 price. We're going to have to make a trade-off and a restriction. And I just think people knowing that
01:03:09.040 can take a breath and go, ah, okay, I'm not broken. Now, different people will have to do a greater
01:03:16.060 amount of restriction. That's just the way the cards crumble. Not everybody has the same IQ.
01:03:20.940 Not everybody has the same athleticism. Not everybody has the same emotional intelligence.
01:03:25.760 And not everybody has the same metabolism. So some people are going to have to be not very
01:03:30.980 restrictive. They just have to be somewhat mindful of what they eat and the cards fall into place.
01:03:35.040 That's my wife. Barely thinks about anything and it all works out. And you get people like me in the
01:03:40.460 middle. I have to be thinking about it every day. Not crazy. It doesn't have to occupy my every minute
01:03:46.600 of my life, but I can't eat on autopilot. And of course there are people even further where
01:03:52.480 unfortunately they're going to have to be very mindful and restrictive of what they eat in lieu
01:03:57.860 of potentially using drugs like GLP-1 agonist. So that's step one, Eric, in my view. And then step
01:04:02.900 two is, which goes to your point about personalized precision nutrition. Then what we need are the
01:04:08.400 technological breakthroughs that allow people to become their own laboratory animals and allow people
01:04:14.420 in the real world, in the free living environment to do the empirical stuff that you and I are talking
01:04:22.020 about and will talk about with respect to the experiments to test the hypotheses. How much fat
01:04:27.180 and protein and carbohydrates should I be eating to optimize my appetite, to optimize and regulate my
01:04:33.220 appetite and my energy expenditure? And again, we're sitting here now talking about the fact we can't
01:04:38.320 even give people that tool yet. We don't have the tool that allows the person to do that test
01:04:44.920 with any degree of accuracy. So I know that's not the most optimistic response, but that's kind of my
01:04:50.840 view is like that has to be the direction we go in as opposed to continuing to try to answer the what
01:04:57.860 is the best diet question, which obviously you're not trying to answer because you realize the futility of
01:05:03.480 that as well as I do. But I still think many people in the public view that as the question that's
01:05:08.920 trying to be answered.
01:05:10.400 Yeah, you're correct. And I see that with this new study that we are doing, people, when you say the
01:05:16.220 word diet, they think weight loss, they think something miracle is going to happen. And we tell them,
01:05:23.220 no, no, it's we want to know what you eat in relationship with your health and your genetic makeup and your
01:05:31.720 environment and all these kinds of things. I'm with you on that. Now, I'm a little bit more
01:05:38.040 pessimistic that I always say education is a major cornerstone of that. But we also are going to need
01:05:47.000 to have public health policies. I mean, it's been done with trans fat. It's being done now in South
01:05:54.080 America with black label on dangerous thing in ultra processed food and all this kind of thing.
01:06:00.840 I don't know that I'm opposed to labeling things. I guess I just, I do worry a little bit with excise
01:06:08.260 taxes on things. Although in fairness, if I'm going to be critical of my own point of view,
01:06:12.760 I do support excise taxes on tobacco. I do think alcohol and tobacco should be taxed to cover their
01:06:19.780 consequences on the back end. So maybe I need to revisit my thinking on this, but I do sort of bristle
01:06:25.460 at the idea a little bit of taxing certain foods more than others. Only I think, Eric, because I've
01:06:32.200 lost faith in the government to determine on the margin what's healthy and what's not healthy.
01:06:37.380 Is butter healthy or not healthy? Should butter be taxed disproportionately relative to bread? I mean,
01:06:43.720 that's an area where I simply don't want anybody at the FDA or the USDA or the ATF or anybody else
01:06:50.840 weighing in. But anyway, tell me more of what you think from a policy perspective would be helpful.
01:06:56.840 I think that the government should work very closely with the nutrition companies. And the nutrition
01:07:04.560 companies have been masters at doing two things, to produce very palatable and very cheap food. I
01:07:13.480 remember John Blandell saying, those are the two things that people don't compromise on. It has to be
01:07:20.200 tasty. They need to enjoy it. And it needs to be cheap. And this is what we have now. I mean,
01:07:27.780 a lot of added sugar, a lot of fat, and it's very delicious and all these kind of things. But we have
01:07:33.520 to reverse some of that. And I think that now we know enough about that. And I was at a conference
01:07:41.000 a month ago in Sao Paulo, the International Congress of Obesity, and they have been very, very active in
01:07:48.000 South America when it comes to ultra-processed food. And I was impressed to see even, you know,
01:07:54.340 the protein content of all the ultra-processed food is on the side of 12 to 13 percent. Whereas,
01:08:03.660 you know, we need something between 15 and 18 percent. And if you believe in the protein leverage
01:08:11.200 theory, this is an important factor. Tell folks what that is. I've talked about
01:08:16.920 it a little bit on the podcast, but let's remind people what that theory is. I don't think there's
01:08:21.160 any one theory. I think it's an amalgamation of theories, but I actually think there's some
01:08:25.260 validity to this theory. Tell folks how that works. I mean, in simple words, it's that we eat for a given
01:08:31.500 amount of protein, which is proportional to our body size and all that. And by the way, I remember when I
01:08:37.540 were studying, we were saying during a low-calorie diet, you need 1.2 gram of protein per kilogram
01:08:45.360 of body weight or this kind of things. But the experiment started with insects, and then they
01:08:51.640 went in rodents, and they manipulated the content of protein of the diet. And they found out that
01:09:00.420 basically the intake was all to gravitate around a protein content which was sufficient for the
01:09:10.000 weight of the animal and so on. And this is called the protein leverage theory. And now I'm a little
01:09:18.100 bit more skeptical when Simpson and the two guys in Australia are saying the pandemic of obesity has been
01:09:26.380 parallel by a decrease in the protein content of the diet. And this is what has triggered the
01:09:33.340 increased caloric intake to get the same amount of protein.
01:09:39.160 Yeah, it's basically they're arguing that it's not that total protein has gone down. It's that
01:09:42.860 protein density within food, especially processed food, has gone down. And so people are seeking
01:09:48.420 more calories to subconsciously get more protein. And the data, I mean, I reviewed these data in
01:09:54.640 huge detail for a previous podcast. The data in the rodents is staggeringly compelling. It's
01:10:01.380 unambiguous. A rodent will consume to its level of protein in the studies where this has been tested,
01:10:07.500 even if it means eating way more calories. I do think humans must be more complicated because I
01:10:12.340 don't think the human literature are quite as clear. Do you?
01:10:15.980 No. Once again, with rodents, you can feed them whatever you want. With people, you don't.
01:10:22.180 I remember Dr. George Bray saying, you know, these dietary recall are not worth the paper on which
01:10:28.900 you write the data. Yeah, I couldn't agree more with Dr. Bray on that.
01:10:32.900 This is where we lack tools to know exactly your glasses with the camera or whatever is going to be
01:10:39.600 useful. But I think we need better ways of measuring what people eat and what is the content of their meal
01:10:49.180 and all these kind of things. And that's why it's so easy to do that in rodents, because you feed them
01:10:55.760 with this or these three diets or five diets and you look at how much they eat. You weigh the food and
01:11:02.160 the calories. A little bit more pessimistic.
01:11:05.420 Yeah. You mentioned that George Bray made this funny comment offhand about the role of food frequency
01:11:11.900 questionnaires, which is they're not worth the paper they're written on. And of course,
01:11:15.160 John Ioannidis has famously said that the food frequency questionnaire belongs in the waste
01:11:20.180 basket. I mean, that's basically the only place it belongs. And yet the food frequency
01:11:25.180 questionnaire is the backbone, is the scaffolding of nutritional epidemiology. And so do you as an
01:11:35.220 empirical scientist, an experimental scientist, have concern at how much food policy is being driven
01:11:44.640 by nutritional epidemiology rather than experimental science? When we understand why, why there's an
01:11:52.280 effort around nutritional epidemiology, because these questions are otherwise difficult to answer.
01:11:56.600 But given the fidelity of the data, i.e. the thing you put in the system to calculate isn't worth the
01:12:05.120 paper it's written on, according to basically anybody who understands how it works. So how do we reconcile
01:12:10.580 this problem? Which is, I mean, even things that we're talking about now, which is the role of
01:12:14.900 ultra-processed food. Well, those are determinations from epidemiology. It's epidemiology that's at least
01:12:20.260 telling us or hinting to us that ultra-processed foods on balance are bad. That confirms what I think
01:12:25.840 most people would intuit. But where do we draw the line between what we are letting nutritional
01:12:33.000 epidemiology tell us from a health policy perspective to where maybe it's overstepping and getting things
01:12:39.820 wrong because of the data integrity problem? I think the problem is really jumping from basically
01:12:46.620 nutritional epidemiology to policies or labeling or dietary guidelines. And I think, to me, now we are at a
01:12:57.040 point that the epidemiology should basically provide us with hypotheses to be tested in better control
01:13:07.020 situation. And maybe in domicile with full feeding of people. These studies are expensive, but we are
01:13:15.740 missing a step. And I think, once again, these new studies from NIH, this consortia of nutrition for
01:13:23.740 precision health, are going towards this direction of basically, you are right, the food frequency
01:13:30.540 questionnaire is here every day for 10 days in this module one of the study. But then there are these
01:13:37.740 other ways. There is the remote photography system that you take a picture with your phone of the plates,
01:13:45.260 you have these cameras and all that. And I think that now I hope that we're not going to make policy
01:13:51.900 only or policy or guidelines only based on the nutritional epidemiology, but also on studies,
01:14:00.620 basically testing some hypotheses related to what the nutrition epidemiology has shown.
01:14:07.420 I think all roads, both from a personal health perspective and from a nutrition science perspective,
01:14:13.900 need to point towards AI. Such a cliche thing to say right now. Basically, everybody's saying AI is
01:14:19.420 everything. But when people ask me, how could AI change medicine? It's not by being a better doctor
01:14:26.700 and being better at diagnosing if you have syphilis or not. Sure, that's valuable. A lot of it's in the
01:14:32.700 very unsexy stuff. Image recognition and radiology, insurance, billing, reconciliation, and this. When you
01:14:40.220 want to talk about biomedical research, the thing that gets all the attention is protein folding. And that is
01:14:45.580 truly magnificent. The protein folding predictions from the amino acid sequence is mind-boggling.
01:14:51.260 And that will absolutely shave some time and money off drug discovery. But if AI could solve this
01:14:58.380 quote-unquote simple problem, I say simple in conceptual terms, not technical terms, you change
01:15:04.380 nutrition science. You really start to answer questions that have vexed us for hundreds of years.
01:15:10.620 So anyway, I hope somebody out there who's got serious AI chops is listening to this and thinking
01:15:16.060 this is an area to pursue. Let's pivot a little bit, Eric, to talk about one of the most important
01:15:20.860 parts of your career. I believe you are, if not one of the senior PIs, you might be the single most
01:15:26.860 senior PI on the calorie study. Is that correct? Yeah, I was one of the four PIs. But I was the one who
01:15:34.940 drove the write-up and the design of the study and all that. Calorie was an important study. It was
01:15:42.220 funded by the National Institute on Aging. And it was really the first attempt to look at the impact
01:15:50.940 of caloric restriction on biomarkers of aging. Now, don't ask me what are the biomarkers of aging,
01:15:59.260 because there's still a lot of discussion around that. If I tell you it's your fasting insulin going
01:16:06.060 up with life, it's your VO2 max going down, it's not your gray air or your lack of air or these kind
01:16:13.820 of things. But anyway, you have some more sophisticated protein glycation and production
01:16:20.540 of isoprostane and all that. I want to talk about the details of the study in a moment. But just before I
01:16:25.820 forget, how much banked serum do you still have that is available for analysis in five years or
01:16:33.580 10 years when better and better tools or biomarkers become available? Has it all been spoken for and has
01:16:40.340 it all been tested or are there still some banked samples? It's great that you asked the question
01:16:45.300 because now there is a calorie legacy study, which is to follow up these people. But also there is a
01:16:54.300 biorepository of all the plasma samples, muscle biopsies, fat biopsies at Duke, which was the
01:17:03.740 coordinating center. And these samples are available, of course, with a request. And the PI of that is
01:17:12.580 Bill Krauss. You may know the name. He's a cardiologist, but he's at Duke. And it's interesting that you ask that
01:17:20.580 because one of my colleagues just published a paper in science on a postdoc analysis of adipose tissue
01:17:30.340 in these people before and after caloric restriction. He found a gene of interest. He's an immunologist.
01:17:37.860 Deep Dixit is at Yale. And he really mined these transcriptomes from adipose tissue and found a gene
01:17:48.100 which is related to the immune function and found that if you knock out this gene in mice,
01:17:54.740 they are resistant to weight gain. This is like a calorie restriction mimetic and they improve the
01:18:01.300 immune function and all that. Yeah, your question is very appropriate. There are still
01:18:07.060 samples available. Of course, they become less and less available or more and more difficult. I'm just
01:18:14.980 digging in some of the samples that we had to send to somebody at UT Southwestern because he
01:18:21.620 has a new molecule that he would like to test before and after weight loss in non-obese people.
01:18:27.780 But the goldmine of these studies is really to be able to bank biosamples. We all bank the data
01:18:37.220 and the results, but the biosamples, it's very, very important.
01:18:40.740 That's the treasure trove. So tell folks about the study. So how many subjects? What was the
01:18:45.700 intervention? How were they monitored and tracked? How long were they followed? Let's just start with
01:18:50.980 the basics. First of all, I became interested in caloric restriction because of, I don't know if
01:18:58.100 you remember, Peter, Biosphere 2. I sure do. It was a glass and steel structure southeast of Phoenix,
01:19:07.540 in between Phoenix and Tucson. And eight people went into this biosphere. They had seven different
01:19:16.340 biomes. There was desert, marsh, ocean, agriculture. How big was it? Habitat. It was about three acres.
01:19:26.180 And this was a rich Texan donor who wanted to do that basically for the sake of NASA to know how people
01:19:35.220 can live in otasi. Anyway, eight people entered this Biosphere 2. It's called 2 because Biosphere 1
01:19:45.620 was the Earth. And they decided to call it 2. Among these eight people, there was a faculty from UCLA,
01:19:53.780 Roy Walford, who wrote the textbook with Rick Weindruck on caloric restriction. And while they were in the
01:20:02.580 biosphere and I was in Phoenix, Roy called me and said, we would like to do measurements of energy
01:20:09.700 expenditure. Can we sneak in a delta track or metabolic cart to measure our energy expenditure?
01:20:18.340 And I said, oh, absolutely. And we can also measure your free living energy expenditure using
01:20:24.180 W-label water. And we did that. Anyway.
01:20:27.620 Remind me how long they stayed in the Biosphere 2. Two years.
01:20:31.220 Two years. Yeah, God, Lord.
01:20:32.420 From 1991 to 1993. Roy Walford was a physician of the group, but he was very, very interested in
01:20:41.780 caloric restriction. What he didn't know, things went south. The agriculture, you know, they had pests,
01:20:49.620 they couldn't control some of the insects, they had goats dying, and very quickly they didn't have
01:20:57.300 enough food. And they lost on average 15% of their weight. None of them except one was maybe a BMI of
01:21:04.260 26 or 7. They were all between 20 and 25. And they became calorie restricted. And you had the guy who was
01:21:14.340 writing the textbook on calorie restriction, being the physician in the Biosphere 2. We started to
01:21:21.220 collaborate. And then when this RFA came out in the early 2000, a request for application grant from
01:21:29.940 the NIA, immediately I called Roy and I said, Roy, we have done this study of energy expenditure. And
01:21:37.860 they came and they stayed in the chamber, five of them for one day, right when they came out of the
01:21:44.740 Biosphere. And we need you as a consultant and we want to write a grant which is going to be
01:21:50.180 competitive. I'm not known in aging research. He accepted. By the way, what did you find of their
01:21:57.380 energy expenditure when they were in the chambers? It was low. I mean, very low because of their caloric
01:22:02.980 restriction. We had to compare to a group of 72 people. I mean, it's all published and I can send
01:22:10.020 you some of the papers. They were about 200 calories below what you would expect for their weight and
01:22:16.340 body composition. Interesting. Even correcting for their highly reduced weight and altered body
01:22:22.820 composition, they were still 200 below. Yeah. Three of them said, hey, we have been stuck for two years
01:22:28.980 now in this Biosphere. We don't want to go to the metabolic chamber in Phoenix, but the five who came,
01:22:36.180 they came back six months later and they would regain their weight. They were normal weight,
01:22:41.860 like at the entry. And we published this data. And was their energy expenditure normal as well?
01:22:47.220 Yeah. Normalized. Normalized. Yeah. There's this argument with metabolic adaptation,
01:22:51.780 how long does it last and this kind of things, but it was normal. Roy passed away kind of prematurely,
01:22:58.740 didn't he? Yeah. He blamed it on Biosphere a little bit because they were supposed to be
01:23:04.820 totally independent except for light from the rest of the world. But a few times they had to
01:23:10.980 purge CO2 and in flux O2, but he said there was probably gases, but it was his story. I don't know
01:23:19.300 how true it was, but he said that he was intoxicated by gas in the Biosphere.
01:23:26.100 Yeah. I didn't realize that story, Eric, that it was on the back of Biosphere 2 that your personal
01:23:32.260 interest in this hypothesis emerged and that that's the first thread that pulled towards the
01:23:38.980 calorie study. So I'm glad you shared that story with us. Yeah. Now move almost 10 years later,
01:23:45.620 Roy Walford and I don't remember the name of the investigator in San Antonio came,
01:23:52.020 we brainstorm, what should be the hypothesis. I was very serious. I wanted to have this grant.
01:23:57.940 And we said, what are we going to test? Because if you are Steve Austin, how many theories of
01:24:05.220 behind calorie restriction is going to tell you more than 50 or a hundred and so on.
01:24:10.500 And myself, I was pretty convinced by two things, the rate of living theory, the higher your metabolism,
01:24:19.220 the shorter your life. And the elephant is a very low metabolism per unit of tissue compared to a
01:24:27.140 shrew and all these kinds of things. And the oxidative stress theories.
01:24:31.940 Does that explain the difference between a human and a dog? Is that explained fully the 10x delta
01:24:37.860 in lifespan between a human and a dog or whatever it is? Okay.
01:24:41.140 You can look at the Kleiber book, you have the energy metabolism.
01:24:47.460 Yeah. Yeah. I need to go. And it's not 10x. I said 10x.
01:24:49.620 They are all on the same line. They are all on the same line.
01:24:52.820 Got it.
01:24:53.540 We brainstormed for three or four days. I have beautiful memories of this time.
01:24:59.220 And we said, okay, we're going to write a grant. It was a seven-year grant. The first two years,
01:25:05.220 which was you do a study, show us that you can recruit people and maintain them in calorie restriction,
01:25:12.180 and they have to be not obese. They can be overweight. And the second is from the three
01:25:20.180 chosen group. We're going to design one study, and it's going to be a two-year intervention.
01:25:26.420 And the first study we decided was basically to test if caloric restriction decrease your energy
01:25:35.620 metabolism more than what you would expect on the basis of the body weight. And in other words,
01:25:41.700 do you become more efficient? And the answer is yes. And we talk about metabolic adaptation.
01:25:48.020 Now, this is in non-obese people here, but they become more efficient.
01:25:52.500 Which, by the way, always sounds like a good thing, but it's not really a good thing when it
01:25:57.140 comes to weight maintenance, right? It's the exact opposite. Becoming efficient is not what you want.
01:26:02.740 You want to be the most inefficient consumer of calories in an ideal world.
01:26:07.060 You're right. And when I did studies of efficiency of athletes, or do they ever hire
01:26:13.780 a more efficient resting metabolic rate, and therefore can have more energy for the exercise
01:26:21.620 or the tasks that they are doing? You cannot win both sides. Like you said, you are better at
01:26:27.860 controlling your weight when you are a little bit more inefficient, but you are less performant and all
01:26:33.380 these kinds of things. Potentially, energy efficiency can be very good for longevity. And it has been
01:26:41.060 shown in some studies. The Baltimore Longitudinal Study showed that some people with lower metabolic
01:26:48.340 rate were living longer. On the other hand, energy efficiency is a liability for weight gain, for
01:26:56.020 example, because you are more efficient and you are more prone to weight gain. And I think it's a
01:27:01.940 balance between the two. But anyway, I think there is no right answer. But having a high metabolic rate
01:27:09.780 can be a liability because associated with the generation of ATP, you have some what we call
01:27:19.380 production of reactive oxygen species. In other words, the efficiency of the transfer of oxygen into ATP
01:27:30.180 is not perfect. And sometimes you have some reactive oxygen species being generated by the mitochondria,
01:27:39.380 and these reactive oxygen species can damage not only your DNA, but your protein, your lipids, and so on.
01:27:48.980 And this is one of the theory of aging. It is too many reactive oxygen species and therefore a higher degree of oxidative stress.
01:28:00.980 And when we designed the first part of our calorie study, it was a six-month intervention. We had four groups,
01:28:10.580 a ad libitum group, 25% caloric restriction, another group being 25% energy deficient, but half by
01:28:21.700 calorie restriction, 12.5% and half by increasing energy expenditure by exercise. And the last group was
01:28:31.300 weight loss, 10% with very low calorie diet and maintenance of this weight loss. It means you are
01:28:38.020 in calorie restriction compared to that baseline.
01:28:41.300 So just to be clear, the last group, the target was the weight reduction, whereas in the other groups,
01:28:48.340 the target was the energy intake and or energy expenditure.
01:28:51.780 Correct.
01:28:52.500 Now, how did you even do this, Eric? Because in theory, this sounds like a brilliant experiment,
01:28:57.380 right? I mean, those are big enough. Those are seismic changes, right? You take a hundred kilo person
01:29:03.060 down to 90 kilos. I mean, that's a big loss of weight. A 190 pound person is going to be 170 pounds
01:29:10.500 when that experiment is done. That's meaningful. The caloric restriction of 25% is enormous one way
01:29:16.580 or the other. But now the question is, you're doing this in the real world over, in one case,
01:29:22.100 I think months, ultimately over years. How did you think about tools for compliance to see that you
01:29:30.500 could hit even close to those targets? I think it was a lot of work with our psychology group who said,
01:29:38.500 we have to screen the people. We have to screen them for barriers to the intervention,
01:29:44.980 for adherence, and so on. And there was a lot, a lot of screening of our volunteers.
01:29:52.420 Do you remember what your rejection rate was? You know, for every 10 people you screened,
01:29:58.420 how many would pass the psychology test?
01:30:00.500 It is in the console diagram of the publication. I know, if I recall correctly, for the two-year study,
01:30:10.660 we screened more than 5,000 people to enroll 225.
01:30:17.620 Wow. So basically only 5% of people.
01:30:23.140 There was telephone, web screening, telephone screening, in-person screening visit. And there
01:30:29.220 were five screening visits to make sure that they show up. If they don't show up for the screening visit,
01:30:35.460 forget them. And the first study, we published that in JAMA, and we did find that there was metabolic
01:30:41.780 adaptation or you become more efficient. And we had also some indication of less oxidative stress.
01:30:50.580 We did what we call a comet essay. You look at damage of DNA in nucleated blood cells,
01:30:58.660 and we measure isoprostane and all that. After that, the three sites where Washington University with
01:31:06.260 John Holosey was Tufts in Boston with Susan Roberts and us in Baton Rouge. Our study was six months,
01:31:15.620 our preliminary study. Theirs were one year. But after two years, when we analyzed the data and all
01:31:22.900 that, we started to design the study, which was going to be the same for the three sites.
01:31:28.180 And was the only difference in the short study, Eric, the duration of the study and the sample size to
01:31:35.220 just confirm the technical doings of the study? No, they were all different. We insisted to have
01:31:43.140 these four groups ourselves in the preliminary study. Boston had only two groups, low glycemic index
01:31:50.980 versus higher glycemic index in the diet of the caloric restriction. And WashU, I don't remember the
01:31:58.180 details, but there was a component of physical activity in their study. He was John Holosey,
01:32:04.980 was a biochemist of exercise and all that. But after that, we compared our endpoints and our
01:32:14.020 basically intervention, and we designed this study. Now, the RFA was specifying that they have to be
01:32:21.220 non-obese. In our preliminary study, we didn't want to go because of this 10% weight loss. If you start
01:32:29.220 with a BMI of 26, you are 70 kilos and you have to lose seven kilos, you become thin. We decided about
01:32:39.140 the range of BMI and we decided for the study to go from 22 to 27.9 of BMI for admission means normal
01:32:51.540 weight. Yeah, mostly normal weight on the plus or minus side of normal weight. Up to 27.9. We knew that
01:32:59.620 they were going to lose at least 10%. And therefore, you cannot take somebody with a BMI of 20 to start
01:33:07.380 with. You would have problems with bone mineral density. You may have problems with some safety
01:33:15.180 concerns. Men and women or just men? Men and women. Right. So the other thing, you're going to have
01:33:20.440 problems with menstrual cycle and things like that. How long did they have to lose the 10% of body weight?
01:33:27.580 Was they given six months to do this or what were they forced into? We didn't have that in the final
01:33:32.460 protocol, but he now preliminary protocol. He was over three months. He was a low calorie diet. He was
01:33:40.640 like 800 and some calories per day. He was all liquid diet. Provided by Pennington? Yeah. But we could do
01:33:50.000 muffins and things like that from these. It's called a health one diet. And it's still on the market,
01:33:57.620 by the way. The two-year study, then we decided to my surprise that they agreed to do the rate of
01:34:05.980 living slash oxidative stress first endpoint. Let's go back to the subjects. Age 21 to 47 for women
01:34:16.320 and 55 for men. BMI 22 to 28. And then going through a lot of screening to make sure that they were going
01:34:26.700 to stick with us. And I can tell you, we randomized two, two-calorie restriction, 25% for one, two ad
01:34:36.240 libitum. We had 95% completion in the ad libitum group and 85% in the calorie restriction. It's amazing
01:34:47.220 for a two-year study. And the retention was spectacular. They were randomized two, two, one, two,
01:34:55.120 caloric restriction. Unlike the preliminary study we did in which we fed them entirely,
01:35:03.060 they came to Pennington to basically learn how to cook whatever diet they wanted. It could be a low
01:35:10.600 fat diet, a low carbohydrate diet, a med diet. And sorry, Eric, tell me again, it was 25% CR target in
01:35:19.180 the CR group. Yep. It was based on two measurements of doubly labeled water. The average, I just checked
01:35:26.320 that this morning, the average energy requirement was 2,400. It means on average, they were cut by
01:35:34.820 a little bit more than 500, 600 calories. And for two years and the first three months,
01:35:43.060 they could come whenever they wanted to learn to cook. And they were also provided some of the meal
01:35:50.500 if they needed to. I remember one is still our star of the volunteers. His daughter thought he was
01:35:58.080 working at Pennington because he was going every day to Pennington. And his daughter was five when they
01:36:04.120 asked her at the kindergarten, where does your dad work? Oh, he works at Pennington. And he was a
01:36:09.200 volunteer for our study. After that, we had a lot of measurements about resting metabolic rate,
01:36:16.940 about oxidative stress. And the endpoints were really the first RMR, the second Ross formation.
01:36:27.320 And after that, it was CVD markers. It was insulin sensitivity, immune function, neuroendocrine
01:36:34.460 parameters, quality of life, and cognitive function. What was the average percent weight
01:36:41.660 loss of the individuals in the treatment group? One year, the average was 12%. And at two years,
01:36:49.240 it was 10.4%. Now, the caloric restriction that we kind of estimated by doubly labeled water,
01:36:57.480 it's called the intake balance method. You measure energy expenditure, you measure change in body
01:37:04.440 composition. We had about almost 20% of caloric restriction for the first six months. And this
01:37:11.840 is where the weight loss. And after that, it started to decrease to close to 15% at one year. And then at
01:37:21.580 the end of the two years, the overall caloric restriction was 12.5%. Basically, we got half of what we were
01:37:30.460 asking for, which is not bad for, like you said, it's an important cut in your intake. And it was
01:37:38.160 square from day one. It was not a ramping up. And then we did this measurements at six months, 12 months,
01:37:45.940 18 and 24 months.
01:37:48.820 Just for the Pennington part of this, not including the other two sites, what was the budget for
01:37:53.260 everything? Meaning the preparation, planning, the study, the analysis for the first publications,
01:37:58.780 et cetera, not the ongoing, but just the bulk of what you would call that calorie study had a budget
01:38:03.400 of how much?
01:38:04.420 My original grant was 10.4 million and it was in 2003. And after that, because we were recruiting
01:38:13.220 so well, they asked us to boost up our recruitment and they gave us another million and a half.
01:38:20.480 Yeah. Close to 13 million.
01:38:22.240 That was the direct cost or direct plus indirect?
01:38:24.940 No, plus indirect total cost.
01:38:27.280 So let's just apply a little inflation to that and say that that's 20 million in today's dollars
01:38:32.760 conservatively.
01:38:34.400 Yeah. Yeah. Yeah.
01:38:36.020 Again, that sounds like a lot of money, but when you think about the fact that the NIH budget
01:38:41.980 is on the order of $35 billion for both intra and extramural and the extramural budget of which
01:38:50.180 this was part of is on the order of, oh, $28 billion. $20 million on a $28 billion budget
01:39:04.520 is a drop in the bucket. It's less than a tenth of a percent. And yet this is a very important
01:39:10.000 question. I think your success in this study, I think it's the single best study that's ever looked
01:39:15.740 at, even attempted to look at the effects of caloric restriction in a free living environment.
01:39:20.240 And in large part, I agree. I think your recruiting was exceptional and your hands-on ability to work
01:39:27.280 with the subjects longitudinally is what made the difference. People think that the study is like,
01:39:32.700 you design the study, you recruit the subjects, you go, and then you forget about them, but
01:39:36.180 you would have failed. You did all the unsexy stuff so well, and that's why you got something
01:39:42.780 so remarkable. And as we start to now talk about the results of the study, part of my frustration is
01:39:48.660 I worry that the NIH is funding some stuff that's not that interesting and not that relevant compared
01:39:54.260 to the jugular questions of human health. And this would be a great example of the kind of work that
01:39:58.600 should be getting much more funding in my view. But I'll get off my soapbox now. Let's talk about
01:40:04.140 the findings at the end of two years. What were the most notable findings aside from the obvious,
01:40:09.000 which is weight loss? One amazing was the retention rate. I thought that it was exceptional
01:40:15.220 that between the three sites, and it was much more difficult in Boston, to be honest,
01:40:20.560 than it was in Baton Rouge or even in St. Louis. But anyway, retention was exceptional.
01:40:26.880 Sorry to keep interrupting you, Eric, but what did the subjects tell you? You got to know these people
01:40:31.220 really well. Why did they stay in the study? I mean, it can't be pleasant to be that calorically
01:40:36.260 restricted for two years. Or did they say, actually, you know, guys, it really felt lousy for six
01:40:42.700 months, and then it didn't feel lousy at all. And I came to really enjoy this. I'm very curious as to
01:40:47.860 what their subjective experience was. It's interesting that you are asking, because we have been interested
01:40:53.680 in that. And we are even now following up these people. We're studied from 2005 to 2008. And they are
01:41:03.060 part of this legacy study, Calary legacy study. He was really building a team between the investigators
01:41:10.940 and the study coordinators and study managers and all that, and the people. He was also providing them
01:41:19.340 with some of the results. And we had to fight for that, because normally you don't want to have people
01:41:26.740 having their results. But we said, it's not going to change their behavior if we tell them about their
01:41:32.640 total cholesterol. Right. It's not blinded. Yeah. LDL. And it's not going to change anything or their
01:41:38.840 body composition. They love to see this DEXA. My percent body fat went from 15 to 12 in a guy and so on.
01:41:48.300 And he was kind of building a, we had Mardi Gras with the volunteers. We had every two months,
01:41:57.300 we had a reception and all that, sending postcards for birthdays and all these kinds of things
01:42:03.980 are part of the retention and building a team between the investigators and the study volunteers.
01:42:12.760 And I think we succeeded in that. But again, this was the screening, which was essential.
01:42:20.120 Because you are right. I remember the first person that we randomized, she ended up in the Adlib group.
01:42:28.400 She came to my office and said, I want to do this study because I have read about what it does to your
01:42:36.760 metabolic health, to your cholesterol, to your body composition. And I'm in the control group.
01:42:43.680 She was crying and said, but we're going to give you data. And after we're going to offer you maybe a
01:42:50.900 weight loss or help you for caloric restriction and all these kinds of things. Of course, two years later,
01:42:57.960 we still see them, but not on a regular basis like during the study. It's a lot of investment from the
01:43:05.020 investigative group and also for the study participants because they had so many visits.
01:43:12.740 So talk to me about the lipid changes, the markers of insulin sensitivity, the body composition changes.
01:43:18.600 Let's just kind of run through the list of what improved. I don't think it's a surprise that these
01:43:23.560 things improved, but the magnitude in some cases is interesting. And again, this question of,
01:43:28.580 I'm very curious as to subjective markers of satisfaction in that group, because most people
01:43:37.080 would say, look, if you told me I have to restrict my calories by 20 or 25%, there's no amount of benefit
01:43:44.340 to my health that could justify the unhappiness and unpleasantness of that experience. So where were
01:43:51.180 they psychologically as that trial progressed into its second year? I think, first of all, there was
01:43:57.320 quite a lot of press around the study at the time done at a national level as well as local levels.
01:44:04.720 And they like to know and to know that they are part of an important study. It's like this nutrition
01:44:09.680 for precision health now or motor pack are things which get some press and all that. Most of the people
01:44:17.400 like to be part of a key study. The second thing was really building this relationship between the
01:44:24.300 investigators and the study volunteers, and also the return of results and the sharing of experience
01:44:34.260 with other people. You were asking, you know, how long does it last to have this problem with hunger,
01:44:41.780 suffering, and all that? And it seems that for most people, after one month, he was totally
01:44:48.120 manageable. We taught them also to increase the volume and decrease the fat content to satisfy
01:44:56.400 on a volumetric basis how much food they were eating with less fat and less calorie density in the diet
01:45:04.620 against the ketogenic diet here. And do you have a sense of how their macronutrients shifted? So
01:45:11.620 did the ad lib people effectively mirror the standard American diet of 50 to 55 percent
01:45:19.020 carbohydrate? And did the CR group end up at a higher fraction of carbohydrates because of this
01:45:25.520 attempt to lower caloric density? We have published, I don't remember exactly if there was a clear cut
01:45:33.160 impact of being in the caloric restriction group versus the ad lib group. This I don't know,
01:45:40.420 but I know that quite a few people wanted to make a difference in their diet and they wanted to know
01:45:47.660 more about the med diet, the DASH diet, the low-fat diet and all that. And surprisingly, there are some
01:45:56.340 people, and like I said in this legacy study, and Dr. Redman is the PI now, people are still, a lot of them
01:46:06.200 did not regain all the weight. And now it's more than 15 years after. And they are still using what
01:46:15.260 they have learned during these two years because there was a lot of learning.
01:46:19.220 When was the last time you took blood, gathered any sort of data on those people besides weight?
01:46:23.940 In other words, is there any way to infer whether two years of caloric restriction 20 years ago
01:46:29.540 had any lasting difference relative to the controls?
01:46:33.660 Like I said, this legacy study is targeting all the people. Now, I don't know how many,
01:46:40.340 but I'm pretty sure we're going to get...
01:46:42.300 But we don't have the results yet.
01:46:43.720 No. No, it's ongoing now. But us, we did a six-month follow-up study at Pennington,
01:46:51.540 and here, they were continuing. That's not the thing they said, oh, heck with this study. I go back
01:46:59.500 to my normal life. It was a game changer for their lifestyle for these people.
01:47:05.960 So what do you think, from an anti-aging perspective, were the most important biomarkers
01:47:12.420 that changed? For example, did you do OGTTs or euglycemic clamps? I mean, how much did you
01:47:19.920 scrutinize glucose disposal and insulin sensitivity in these people?
01:47:24.600 We didn't do clamps. Let me tell you, there are two kinds of aging. There's primary aging,
01:47:31.120 which is more like senescence or mitochondrial dysfunction, leaky membrane. And there is secondary
01:47:39.040 aging, which is basically the impact of your environment and your lifestyle. When you ask about
01:47:46.160 insulin sensitivity or cardiovascular factor, it's more secondary aging. And here, we did a lot of
01:47:53.360 measures. Bill Krauss published a quite cited paper five years after the end of the study in JAMA
01:48:01.220 on all the cardiovascular, cardiometabolic risk factors. And everything was tremendously improved,
01:48:09.620 despite the fact that these people were healthy to begin with. BMI 22 to 27.9 and so on. And remarkable
01:48:19.520 improvement in all these markers of secondary aging. Now, when it comes to primary aging, that's a
01:48:27.840 different story because it's much more difficult to measure autophagy, to measure mitochondrial function,
01:48:34.820 to measure leakiness of a cell membrane in these people. And what we ended up to measure was really
01:48:43.160 some of these hallmarks of aging. You have probably seen these papers. There was one in 2012 and one 10
01:48:52.120 years later. We don't have as many data that we would like. But for example, we did measure mitochondrial
01:49:01.460 biogenesis by looking at the relationship between nuclear markers and mitochondrial DNA. And we observed
01:49:13.560 in humans that there was an increased mitochondrial biogenesis. Despite the fact that you use less energy,
01:49:23.040 you become more efficient. You increase your biogenesis of mitochondria, which is quite spectacular
01:49:31.160 because the ROS production of these reactive oxygen species are produced by older mitochondria. The new
01:49:40.260 mitochondria are much more efficient. They don't produce as many ROSs. So let me make sure I
01:49:46.420 understand that, Eric. Sorry. You're saying that the people in the CR group had a greater turnover of
01:49:53.020 their mitochondria. In the muscle, skeletal muscle, it was. It's interesting. And so we would expect
01:50:00.960 that people who are calorically restricted would have lower ROS generation, but we would expect that
01:50:08.860 the reason for that is lower substrate utilization. You're saying, yeah, they had lower ROS generation,
01:50:15.980 but it might actually be just as much from the fact that they had more mitochondrial biogenesis and
01:50:21.220 they were using newer machinery for the substrate utilization. So it could be both of those things
01:50:26.660 are reducing ROS. Is that what you're saying? Absolutely right. I think it's both. When it
01:50:32.180 comes to mitophagy, these old mitochondria, it's been shown in insect, in rodents, that this is improved
01:50:40.220 with caloric restriction. Autophagy, of course, all these organelles in the cells. Did you measure any of
01:50:46.900 the tubules or anything for autophagy? No. No, I'll see too. Okay. But we measured mitochondrial turnover
01:50:52.400 by this method and we found that it was increased with caloric restriction. And I think you are right
01:51:00.740 on the point here. There's both mechanism, less energy requirement, but also more efficient
01:51:08.040 mitochondria. Today, if you were to do this study, for example, I mean, I know the legacy study isn't
01:51:14.260 the same because not as many of the people are going to still be carrying out. But if you could
01:51:19.080 go back and look at the banked samples, are there any other biomarkers you would be able to look at
01:51:24.940 today vis-a-vis the hallmarks of aging? Is there anything we could be doing to better understand
01:51:29.160 senescence? What would you look at in terms of inflammatory markers? I would certainly put that
01:51:33.400 down as primary aging. How much of a suite of the interleukins, TNF, and things of that nature did you
01:51:39.240 look at? Yeah, I mean, we did. We did at 6, 12, 24 months. We didn't do 18 months for that.
01:51:47.200 But we had the whole panel of inflammation and high sensitivities, CRP, and then all the
01:51:54.460 interleukin, TNF-alpha, and all that. Everything improved or just some things?
01:52:00.400 No, everything improved. One thing which was spectacular when it comes to immune function,
01:52:06.660 we did some imaging of the thymus and there was loss of fat.
01:52:13.560 Oh, oh, involution. Okay, fat reduction.
01:52:15.620 There was a reduction of fat in the thymus and our friend Deep Dixit was all excited by that and
01:52:24.360 this is why he pursued all the immune responses from transcriptomics in different tissues and all
01:52:32.700 that. But chronic inflammation, first of all, it was not abnormal to begin with, but there was
01:52:40.000 tremendous improvement. And I think that Bill Krauss in the discussion of his paper, if I recall,
01:52:47.500 he used the Framingham index of cardiometabolic health and there was an improvement in the age.
01:52:57.520 I don't know exactly the index.
01:52:59.220 Yeah, using the Framingham risk calculator, of course, everything would have got better
01:53:03.620 based on the biomarkers. And he was quite spectacular. It was like they were gaining 10
01:53:09.700 years in two years.
01:53:11.500 I mean, again, Eric, I think it's very interesting. And I think it is hands down the best experimental
01:53:18.500 evidence we have that caloric restriction for those who can do it may indeed be a great tool.
01:53:24.740 Of course, there are other questions that I think can't be answered by this study based on its duration
01:53:31.640 and the age of the subjects. And that is, would those benefits extend into the eighth decade of
01:53:39.260 life, a period of time when sarcopenia becomes a significant driver of not just mortality, but truly
01:53:47.640 morbidity? And would we indeed see a trade-off in lean muscle? Again, the answer is not necessarily
01:53:55.060 that you would. I do think that one could indeed consume fewer calories without any restriction of
01:54:02.160 protein and while doing all of the necessary strength training. So in other words, I think
01:54:06.800 there's a deliberate way to do this. But if one were just to restrict calories and lose lean mass,
01:54:14.000 I mean, I don't remember, Eric, but obviously the subjects got lighter and obviously their body
01:54:18.820 composition improved, meaning they disproportionately lost fat to muscle. But do you recall,
01:54:25.060 if there was also a meaningful reduction in lean tissue independent of the improvement in body
01:54:31.080 composition? I would have to go back to the publication exactly. It was less than a quarter.
01:54:38.200 Less than a quarter. Yep. We like to hold on to that as the gold standard of limit lean body mass to a
01:54:44.180 quarter of total weight loss. We didn't restrict physical activity, but to be enrolled, they had to be
01:54:50.540 screened for not being regular exercises, for example. Do you know the cronies, the calorie
01:54:57.900 restriction optimal nutrition society? I've never interacted with them, but I'm familiar.
01:55:03.780 There is about 200 self-imposed calorie restricted people. They are afraid of exercise. They don't
01:55:11.840 exercise at all because they are afraid that exercise is going to increase...
01:55:16.540 Increase their appetite.
01:55:17.780 Their appetite and their food intake. And they are religious with that. And that's why,
01:55:24.020 I mean, your question about sarcopenia, when you start with people with a BMI of 24 and you
01:55:30.520 lose your 10, 12% and you keep this 12% off and you go in your 70s and 80s, what is happening to
01:55:40.280 your muscle mass and this kind of things? And I don't think we have an answer.
01:55:44.700 I mean, to me, Eric, the experiment that I want to see done is not even an experiment at this point.
01:55:50.520 Frankly, it's literally, it's a much easier experiment, which is your tissue and serum
01:55:55.680 samples provide a very compelling case of you can take healthy people, CR them for a couple of years
01:56:03.780 and make them better across the board by every objective measure of both primary and secondary
01:56:09.440 aging. The secondary stuff's so obvious, it's not even worth talking about. So people that are
01:56:14.500 interested in that can go back and look at the papers and see the lipid profiles and see the
01:56:18.380 insulin sensitivity. But it's really these primary markers of aging. I had forgotten or didn't know
01:56:23.540 about the thymic fat reduction. That's very interesting to me. So now the question is this,
01:56:28.600 well, you were dealing with a very narrow population. You started with 2,500 people and
01:56:33.540 through intensive psychological profiling, you winnowed it down to the 5% of people who were going
01:56:40.340 to be able to most adhere to this. And then on top of that, you provided arguably the most robust
01:56:47.040 support for those people during this journey, the kind of support they couldn't buy outside.
01:56:54.340 Those people as regular people on the outside world couldn't have purchased the level of care and
01:57:01.280 support and encouragement they got for that two-year study. So all of that is not to be a critic of the
01:57:06.380 study. It's to simply say those were the necessary steps to get such exceptional compliance, which is
01:57:11.980 what was necessary to get such a meaningful answer. But if we want to ask the question, how would you
01:57:19.280 help the 99% of people who on their own could not adhere to that? The answer, of course, becomes
01:57:26.140 CR mimetic drugs. This is the question that is on everybody's mind, which is, Eric, you've convinced me
01:57:34.620 that CR to this extent will absolutely help me live a longer, better life, but I just can't do it.
01:57:42.820 I'm not in that percent of the population. But will a GLP-1 agonist give me the same benefit?
01:57:49.920 Will rapamycin give me the same benefit? Will acarbose give me the same benefit? Will an SGLT2 inhibitor
01:57:57.820 give me the same benefit? Will metformin give me the same benefit? And those studies are much easier
01:58:05.340 to do. We can easily put people on those drugs for two years and do the exact same analysis.
01:58:13.140 You've given us the gold standard. You've given us the template. Now we just need to compare
01:58:18.660 every single marker you've measured, plus some you haven't. I really want to see the epigenome
01:58:24.080 in these subjects pre and post. And so is it just me that feels this way, or is that also
01:58:29.340 screaming out to you as the most interesting question to come out of this?
01:58:34.100 It's been a little bit of a roller coaster, the CR mimetics. You remember all the Sirtuin stories.
01:58:42.900 Yes, but notice I picked something very carefully. I only picked drugs, with the exception of GLP-1
01:58:48.880 agonists. I only picked winners of the ITP. And Sirtuins are garbage. Everybody knows they're
01:58:56.140 garbage. I'm sorry to offend people who work on them now, although I don't think anybody's still
01:59:00.380 working on them. But the Sirtuins were a scam story that never materialized. And it never,
01:59:06.860 ever, ever was the mechanism by which CR worked, ever. I've gone back. I have talked to Matt
01:59:13.240 Kaberlin, who did the first study. I have gone through every experiment that was done in that lab.
01:59:18.700 There is zero evidence that Sirtuins' supposed efficacy, which I think is true in yeast, by the
01:59:26.120 way, was mediated through CR. And of course, Sirtuins have had no efficacy post-yeast. So anyway,
01:59:33.740 I'm just being a little pointed in my language to make the point that I'm being particular about
01:59:38.460 which CR mimetics I discuss. Yeah, okay. And you pick metformin, and of course, I'm sure you
01:59:44.120 know neobasili. Of course. My hypothesis, by the way, is that metformin is not a CR mimetic,
01:59:50.440 but I just think we should include it. There's a reasonable enough probability that all of those
01:59:55.180 molecules I suggested, I think should be tested. I mean, the GLP-1 are so potent when it comes to
02:00:03.580 weight loss, metabolic health, and all that. I mean, there's not a week without a new paper on GLP-1.
02:00:09.600 I know. I just read a blood pressure one today on trisepatide.
02:00:13.760 Why would that be? Because when you calorie restrict yourself, you eat less,
02:00:19.560 and therefore you stimulate less these GI peptides.
02:00:24.720 None of it makes sense. None of it makes sense.
02:00:28.040 If you tell me, I mean, are they true caloric restriction mimetics, and do they decrease oxidative
02:00:36.760 stress? Do they improve insulin sensitivity and all that? Among the one you cited, there's a lot of
02:00:43.840 those. Now, the question is, how do you go about to test that? Of course, there is all these failed
02:00:51.940 drugs and things which have been tested for toxicity and safety and all that, that some people want to
02:01:00.320 recycle in aging, and I'm not sure where it's going to be. To me, the secondary aging, which is the impact
02:01:08.980 of your lifestyle and your environment, is what we should target first. The primary aging,
02:01:16.420 I like to hear David Clark talking about autophagy or the people on the East Coast and all that,
02:01:24.100 but what do you do to have more autophagy or more mitophagy and all that? I don't know.
02:01:32.720 I mean, we know exercise does it. I mean, we know that autophagy is not just fueled by caloric
02:01:37.980 restriction, but exercise is an incredibly potent driver of that for similar mechanisms, right? You could
02:01:44.220 argue that it's basically a substrate utilization problem. It's the input, it's the output. And when
02:01:49.420 you transiently deprive the output, if you drive more output and you transiently create a deficit
02:01:55.740 of energy, I don't think at the cellular level, the body is particularly concerned with, am I short on
02:02:01.740 what's coming in or am I short because too much is going out? And again, this doesn't have to be an
02:02:07.000 either or. That's the beauty of biology is we can look for accretive solutions. So I think that
02:02:13.160 those particular gyroprotective agents, Eric, are probably not going to be as impressive
02:02:18.080 on the secondary markers of aging with the exception of the GLP-1 agonist because of the obvious weight
02:02:24.320 loss. I don't think metformin, RAPA, SGLT2s, acarbose are going to result in weight loss. And
02:02:29.640 even in the ITPs, they did not result in weight loss. Remember the hypothesis of David Allison who
02:02:35.160 proposed acarbose is this is going to be a CR memetic that induces weight loss because of bad
02:02:41.380 absorption. Well, guess what? Those mice weighed the exact same amount. They just lived a heck of
02:02:46.380 a lot longer, suggesting it was actually the glucose metabolism that gave the benefit. But
02:02:51.720 I don't know. I just think, Eric, what you've done is amazing. And I know it just wasn't you.
02:02:56.240 Of course it wasn't you. I mean, you had an incredible team. I've been to Pennington on many
02:03:01.140 occasions. It's a wonderful place. I think it's dedication. It's the little stuff that matters,
02:03:06.580 Eric. It's like, I know what your staff is like. I remember working with Courtney and the entire team
02:03:11.960 of nutritionists there. I mean, that's the stuff that's not sexy, but that's what's necessary to do
02:03:17.920 this kind of work. I hope that through this podcast, we're giving people an appreciation for
02:03:22.400 how hard it is to do nutrition science. If you're an experimentalist, anybody can do epidemiology.
02:03:29.180 And I kind of share the view of George and John and the people who think that it is a very,
02:03:36.480 very limited use, not of no use. There is a case, but we over-index on that stuff when what we really,
02:03:44.420 in my mind, need to be doing is doubling down on the kind of work you do, because that's the only
02:03:49.700 place I think we're going to get causal information and information that we could make people's lives
02:03:55.900 better with. So thank you for what you're doing. My pleasure. Stay tuned, because you mentioned
02:04:01.960 time-restricted eating, and now there is a study which is going to be implemented in a year or two,
02:04:09.480 a five-year intervention, calorie restriction versus time-restricted eating. What's the time
02:04:15.740 window of restriction going to be? I don't know the details. The protocol is not finalized. It's one of
02:04:21.660 these exercise where we were part of one of the study, and now you put all your brain together,
02:04:27.940 but it's going to be probably eight hours a day. My vote, if you give me a vote, Eric, make it more
02:04:33.880 restrictive. The first study we did was six hours. Yeah. If you really want to see if there's a signal
02:04:40.060 independent of calorie restriction, because I think the goal has to be, you're going to have to match
02:04:44.840 their calories. This is the isocaloric difference between CR and time-restricted feeding. In my experience,
02:04:51.220 eight hours will give you a null answer. I bet a million dollars you'll get a null answer if you
02:04:56.500 compare eight hours, but four to six is interesting, and I'd be very curious. Yep. Interesting you bring
02:05:03.840 that up, but our study was the first in humans, and this was Courtney Peterson who did that,
02:05:11.480 and we had six hours, and people said it would be easier with eight hours and all that, but
02:05:17.960 after, if I recall correctly, after two weeks anyway, they were perfectly fine with six hours.
02:05:24.220 Even if at the end, the exit interview, they said it would be easier for eight hours, but I think it
02:05:29.660 was at the start, and you can maybe ramp it down from eight to six hours. Yeah, yeah. Well, Eric,
02:05:38.560 great to spend time with you today. Thank you. I know you're in Europe, so that obviously you've had
02:05:42.620 to stay up a little bit later, but hopefully the next time we do this, we're talking about this study
02:05:46.640 and maybe the follow-up studies that I'd like to see done on some of these CR memetics, and we're
02:05:50.800 doing it in person. All right. Thank you very much, Peter. My pleasure. Thanks, Eric.
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