The Peter Attia Drive - #171 - Steve Austad, Ph.D.： The landscape of longevity science： making sense of caloric restriction, biomarkers of aging, and possible geroprotective molecules

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

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

00:00:19.800 into something accessible for everyone. Our goal is to provide the best content in health

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00:00:28.880 If you enjoy this podcast, we've created a membership program that brings you far more

00:00:33.280 in-depth content. If you want to take your knowledge of the space to the next level,

00:00:36.840 at the end of this episode, I'll explain what those benefits are. Or if you want to learn more now,

00:00:41.740 head over to peteratiyahmd.com forward slash subscribe. Now, without further delay, here's

00:00:48.080 today's episode. My guest this week is Steve Austad. Steve is a distinguished professor and

00:00:55.520 chair of the Department of Biology at the University of Alabama, and he's the scientific

00:00:59.700 director of the American Federation for Aging Research. He also directs the University of

00:01:05.720 Alabama's Nathan Schock Center for Excellence in the Basic Biology of Aging, which is only one of six

00:01:11.820 such centers in the United States. Steve's current research seeks to understand the underlying causes

00:01:17.740 of aging specifically with a long-term goal of developing medical interventions that slow

00:01:23.060 the age-related decay in human health. Now, I've known Steve for probably about six or seven years,

00:01:29.460 and in that period of time, I really do consider him to be one of my mentors in this space.

00:01:34.840 Always generous and gracious with his insights and his time, his wisdom, and I was just really excited

00:01:40.620 to have him on the show today. And we talk about his background, which is, as you'll see,

00:01:45.580 very interesting and very unconventional. And we talk about kind of a history of one of the most

00:01:51.980 important discoveries in aging, which is the relationship of caloric restriction and length

00:01:56.660 of life, but also some of the limitations of this research. And we do a very good case study on what

00:02:02.260 is unquestionably the most important experiment ever done on caloric restriction and dietary restriction.

00:02:08.600 We talk about the possible hypotheses for the sex-related differences that exist between men and

00:02:13.740 women. And we talk about some of the most exciting and interesting geroprotective molecules out there,

00:02:19.240 including rapamycin, metformin, and others. So without further delay, please enjoy my conversation

00:02:25.080 with Steve Austin. Hey, Steve, as we were just talking about a minute ago, this has been a long

00:02:35.360 time coming. I am so excited about this discussion today. Good. I'm looking forward to it myself.

00:02:40.980 You're one of those people, and there are a handful of people like you, where anytime we sit down,

00:02:46.180 if it's over a coffee, a meal, or a short phone call, I feel like my learning increases at a

00:02:52.140 geometric rate. So to now be able to do a very long discussion and then share it with so many people is

00:02:59.040 going to be awesome. But frankly, any discussion about longevity, I think, needs to begin with your

00:03:06.340 background. I think people need to understand the curious character that you are. And your journey to

00:03:14.720 where you are today is, you know, it's not common. But yet I think it sort of speaks to the unique

00:03:20.880 lens that you've brought to this space. So give folks a sense of what you did growing up. Like

00:03:26.820 when you were in high school, what were you interested in? You know, it was interesting. In high

00:03:31.080 school, I was a math nerd, and everybody assumed that I was going to be a mathematician, including

00:03:37.460 myself. In fact, I was a math major when I first went to college. But what I really did in my spare

00:03:43.540 time in high school, when I wasn't playing sports, is I liked to kick around in the woods. And this was

00:03:50.500 in Southern California. And I would actually go out into the desert. I actually had a high school

00:03:54.400 biology teacher who would take students out in the desert to catch rattlesnakes. And I still, I'm not

00:04:00.140 sure why he was doing that. I think he was milking them and getting money for the venom or something.

00:04:06.080 But anyway, I had a great time doing that. And at that time, I think I was in 10th grade, he said,

00:04:10.860 you're going to be a biologist. And I thought, that's the most ridiculous thing I've ever heard 0.95

00:04:15.820 of. I know I'm going to be a mathematician. And then after I got to college, I suddenly discovered 0.97

00:04:23.220 after the first year, I didn't really like math all that much. And I wasn't about to spend four

00:04:29.420 years doing something I didn't like. So what I really liked to do was read. And so I switched to

00:04:35.600 an English major. And I actually ended up with an English degree. And my goal at that point was to

00:04:42.080 write the great American novel and become, you know, the Ernest Hemingway of the latter 20th century.

00:04:49.180 And you went to UCLA for undergrad?

00:04:51.440 Yes, I did. So that was really my job. But the one thing I did is I thought, well, to write

00:04:57.440 novels, I've had a pretty traditional upbringing, middle class upbringing, except for the fact

00:05:03.340 that my family traveled all over. I went to 20 different grade schools, at least. I'm not sure

00:05:09.300 how many, really. We would live two months. You know, my dad sold our house and bought a house

00:05:13.940 trailer that we put behind the car. And so for about six years, we would spend three months in

00:05:20.400 this town, four months in that town.

00:05:22.660 Oh, so this wasn't because one of your parents was in the military?

00:05:25.060 No, no. My dad was a newspaper pressman. And his union had something called a traveling card,

00:05:33.360 which meant that if you were a union member, you could go to any big city newspaper and be hired

00:05:38.080 for some short amount of time. And so he must have just had a travel bug. I really regret that I ever

00:05:44.920 asked him, what were you thinking, dad, when you did this? So that's where we went. We went,

00:05:50.700 you know, El Paso, Dallas, Atlanta, Miami, Virginia, New York, Detroit. That was my schooling,

00:05:59.080 except in doing all this traveling every year, I missed probably two months of school. But when we

00:06:05.320 were traveling, my parents just threw these books at me in the backseat of the car and said, there,

00:06:11.000 it's your study time. And so I learned a lot on my own. And that probably influenced somewhat who I am,

00:06:17.940 because that's a pretty unusual upbringing, probably.

00:06:22.760 I can't imagine most kids could thrive in that setting because it's so disruptive. Like I,

00:06:28.200 I actually had a patient once who went to 11 different schools between first and 12th grade.

00:06:37.440 So averaged about a year per school. So at least they didn't have to move during the school year.

00:06:43.640 But I always thought that that was just the social aspect of that, not to mention just the

00:06:49.040 continuity. I mean, when you move from one state to the next, they may have different standards for

00:06:53.700 what you're going to learn in English, math, or science. But what you described takes that to a

00:06:57.780 whole new level. Were you ever behind in school? Did you ever show up at the school that you were in

00:07:02.820 and feel like you're out to lunch? Or was it the opposite? Did you generally feel like you were more

00:07:06.880 than making up for it in the backseat?

00:07:08.180 I felt like I was more than making up for it. But I also think the school systems in Southern

00:07:13.040 California were particularly good at that time. So I usually had had in school a lot of the stuff

00:07:21.100 that I would come across, particularly in the South, which is the first part of this journey

00:07:25.860 where we traveled through. In fact, you know, it was probably made easier for me because I was an

00:07:30.580 only child and I was used to being thrown on my own resources. But one of the things that I

00:07:36.080 quickly figured out because I was always the smallest kid in class, even when I graduated from

00:07:42.060 high school, I was still 105 pounds and about five feet four. And I quickly learned, though, that I could

00:07:51.280 avoid being beaten up by the bigger kids if I helped them with their homework. So I quickly fell into that

00:07:57.340 in every school I went to. I was the guy that would help you figure out what was going on in math or

00:08:02.960 history or whatever. And you're a normal size person. It's not like you're five foot seven today.

00:08:08.780 So what do you attribute such a late growth spurt to? Well, it's kind of interesting given the topic

00:08:14.300 we're going to be talking about. But when I was a sophomore in high school, I was still way behind.

00:08:21.160 I was a wrestler. I was wrestling in the 98 pound division, which is the lowest weight class, but I only

00:08:27.300 weighed 79 pounds. And at some point, my parents took me to the doctor because they were concerned about

00:08:33.380 delayed puberty and me being so small. And I got some sort of injections then. And I don't know if it was

00:08:39.840 growth hormone. I don't know if it was testosterone. But almost immediately after that, I started going

00:08:45.900 through puberty. And then my real growth spurt was after I got into college. It was very unusual. And I still

00:08:52.880 think of myself as being little, you know, even though I know I'm normal size, I still think of

00:08:58.000 myself as being small. Well, that's interesting. That probably speaks to the psychology of our

00:09:03.520 sort of formative years, right? Right, exactly. I really would be curious to know if I got growth

00:09:10.060 hormone when I got those injections or not. So like all good aspiring authors, you somehow wind up

00:09:17.280 in New York. Right. Yeah, I figured that was a place to be if you were going to be a great novelist, because

00:09:24.840 that's where all the publishing was. But the other thing that I figured was that if I'm going to write a great

00:09:30.800 novel, I don't have anything but a sort of typical middle class experience. Because at the time, I didn't

00:09:37.400 realize how unusual my background was. So I went there, but I decided I needed to start accumulating

00:09:44.600 experiences. So I started having adventures. You know, I would, you know, I would hop a train from

00:09:50.560 Southern California to San Francisco and back. I got to New York by hitchhiking to New York. And later

00:09:57.500 on, I hitchhiked back to California again. And when I was in New York, I thought, well, where am I going

00:10:03.300 to get experiences here? So I ended up driving a taxi there because I thought, wow, this looks like you

00:10:09.140 could really accumulate a lot of experiences in a hurry here, which was true. How long did it take you to

00:10:14.180 learn the city? I mean, New York is in some ways a pretty straightforward city to learn because it's

00:10:18.520 on a beautiful grid. But, you know, there's some nuance to it, given the one-way streets and you've

00:10:23.060 got, you know, Broadway is diagonal. And so it's, you know, it's not a trivial city to learn, especially

00:10:28.900 given its size. How long did it take you to be a competent cabbie? Well, I was pretty competent

00:10:34.720 right off because of the logical structure of it. But there are these parts of the city below 14th

00:10:40.020 Street, for instance, that were amazed. And usually what I would do to hide my ignorance

00:10:45.460 is I would just ask the passenger, which way would you like me to take? And so then they would

00:10:50.560 direct me. So I never really felt like I was lost there. And then, of course, if you got to the

00:10:57.000 Outer Burroughs, it was a whole different ballgame. But I didn't go to the Outer Burroughs very much. And

00:11:02.480 when I did, I had to have help getting back because it was challenging. But it was a really

00:11:09.720 unique experience. I drove at night. So I would go to work about four in the afternoon and come home

00:11:14.760 about, you know, somewhere between midnight and 2 a.m., depending on what the fairs were like.

00:11:21.940 And I mean, you know, the experiences I had, I had people who, one person I remember well,

00:11:28.580 wanted me to stop in every bar along the street. And we did this for a while. And he'd say,

00:11:35.700 and he'd go in the bar and he'd say, wait for me. And he'd come out and we'd go to the next one.

00:11:39.740 And I finally said, if you don't mind my asking, because I was afraid he was going to go into the

00:11:44.800 bar and never come back. And I would be, you know, in debt for the taxi fare. He said, oh,

00:11:50.980 I'm looking for my wife. And when I find her, I'm going to shoot her. And so that's the point at 1.00

00:11:55.840 which I said, okay, well, you can pay your fare now. So that's a type of thing that happened to

00:12:02.440 me more than a few times. What years were this? These were in the mid-1970s.

00:12:08.160 In New York, a totally different city from what it is today.

00:12:11.620 Yes. Yes. No, in those days, you could get robbed in daylight in Central Park. And now Central

00:12:19.300 Park is just a wonderful place to go. What was the dodgiest part of the city

00:12:24.740 south of 96th? Probably the extreme west side, 9th and 10th, because there was a lot of abandoned

00:12:32.900 buildings over there. The lighting wasn't good. And then of course, Harlem was not a great place.

00:12:39.480 That's why I said south of 96th. I was like, I took that as a given. Yeah.

00:12:43.300 I figured it was. But the interesting thing is a lot of cab drivers would not take fares to Harlem.

00:12:48.820 And I would. I would take somebody any place they wanted to go. But I did have some dicey

00:12:54.560 experiences there, I have to say. I never was robbed. But I was the only taxi driver in this

00:13:00.360 garage that I knew that was never robbed during that time.

00:13:03.800 Do you attribute that to pure luck or something else?

00:13:07.300 Yeah, I do. The one time I was certain I was going to be robbed, a police car turned a corner

00:13:11.980 and pulled up behind me and couldn't get by because it was a narrow street.

00:13:15.560 So the guys that I could just tell from the vibe, this is not going to be good.

00:13:20.360 They just paid and got out and left. So that was the closest that I had. Although I did pick up

00:13:25.720 two taxi drivers who had been robbed and their cab had been hijacked. And they were on the street

00:13:31.540 and they waved me down. So yeah, it was a pretty adventurous time.

00:13:36.260 So where was it in here, Steve, that you also began a little side hustle training animals?

00:13:41.920 Well, that was after my taxi driving years. What happened is that I moved back to Portland,

00:13:49.140 Oregon. After all of the travel that my family did, we ended up in Portland, Oregon, where we

00:13:54.140 kind of settled down. So I'd spent my first year, sixth through 10th grades there. I really liked it.

00:14:00.960 And after I got out of college, I went to Portland for a short time before I went to New York.

00:14:05.740 So I went back to Portland and there I was taking karate. And my karate teacher had some African 1.00

00:14:13.020 lions at his ranch out in the country. And I used to go out and visit him. And if he was cleaning the

00:14:19.640 cages, you know, he'd say, come on in, let's talk while I'm working. And so I do that. And I guess I

00:14:25.100 wasn't too obviously terrified because he got an offer to use the lions in a movie in Hollywood.

00:14:31.920 And he needed someone to help him drive the lions to Hollywood. So he asked me if I do that.

00:14:38.960 And I was I had a job as a newspaper reporter at the time. So I thought, well, this is going to be

00:14:43.560 a long weekend. So I said, yeah, I'll help you do it. And I went out to his house and I assumed

00:14:50.000 there was going to be like something like a horse trailer that was modified for lions.

00:14:54.660 And what he said was, help me get the backseat out of the car here, Steve. And we're going to put

00:15:00.420 Scherza, which is one of his lions in the back. So we did. We took out the car seat. We put the lion

00:15:05.980 in the backseat and we took off for L.A. And there was nothing between no screen, no window,

00:15:12.140 nothing between the front and the back seat.

00:15:14.500 This is when you're wishing for the New York taxi with the plexiglass.

00:15:17.220 No kidding. Well, actually, I wasn't worried at first because I thought it's his pet. He must

00:15:23.380 know what he's doing. But you weren't worried about the fact that the pet's more familiar with

00:15:27.780 him than you. And if. No, I should have been. I should have been. But here's the weird thing is

00:15:33.020 that he was driving initially. And the way he controlled this lion was with a cattle electric

00:15:38.380 prod. And so he handed me this prod. And it was if you push the button, it buzzes. And he said,

00:15:45.340 the lion's afraid of that. So if he gets restless, just stick that in his face. Don't touch him 0.69

00:15:50.600 with it. Just stick it in his face and buzz it. That worked once. And then the battery ran out. 1.00

00:16:00.520 Then I said, what am I going to do now? He goes, well, just hold it in his face and go

00:16:04.380 with your mouth like that. And I thought again, I thought it's his lion. He must know that his lion

00:16:11.180 is that stupid. And it turned out his lion wasn't that stupid. That worked once. And then the lion 1.00

00:16:17.620 started to get really quite active. And then I realized my friend was scared. And that's when I

00:16:23.900 got scared because I thought he knows what. So we ended up pulling off on a side road in the middle

00:16:29.800 of the night now, getting his lion out on a long leash and walking it down this rural country road for

00:16:36.900 several miles to try to get it tired out. I was driving the car so that he could be in the

00:16:43.160 headlights and see where he was leading the lion. And every time we would go around a corner and the

00:16:47.900 lion would lose sight of the car, we'd come around the corner and the lion would attack the car. It

00:16:52.260 would jump up on the hood. So I was expecting a catastrophe. I thought there's going to be a farm

00:16:57.980 and there's going to be a dog and the dog's going to run out. But none of that happened. So we put

00:17:04.780 the lion in the back of the car. It was tired. It slept all the way until we got to the Bay Area when

00:17:11.460 we had switched drivers and suddenly the police lights came on behind me. And so the policeman pull

00:17:20.820 us over and I jumped out quickly to try to pretend this was just normal. But you know how in the middle

00:17:29.260 of the night, they'll shine their lights into the car ahead of them so they can see what's going on. The

00:17:34.260 lion is now getting up and it's pacing back and forth. And I'm saying, oh, just bringing the lion down from

00:17:40.160 Disney Studios in Washington. Very routine. Was I speeding? Sorry about that. And in the meantime, my friend

00:17:48.640 who owns the lion who owns the lion is in the front seat and he's trying to keep it from coming in the

00:17:52.780 front seat. So you can see him, you know, trying to hit it with his elbow and then the lion goes over

00:17:58.980 and steps on the car horn. And so the car horn just starts shrieking. So at this point, the policeman

00:18:05.820 said, um, just get out of my jurisdiction. He didn't know how to deal with it. So we had a rather

00:18:12.420 uneventful trip down to LA. At some point, did you at least get a new battery for the taser?

00:18:17.600 Once we got to LA, we did. But by the time it was light, we were close enough that the lion was

00:18:24.340 asleep still. So we never, we never did. It was really pretty interesting. And my intention was

00:18:29.960 as soon as we delivered the lion to fly back to Portland and continue on with my life. But it

00:18:36.800 turned out the movie producer offered me a job on the spot. And, uh, he said, we're doing this movie.

00:18:46.640 We're going to have 25 lions in it. We need lots of lion trainers. I said, you don't understand.

00:18:53.060 I have a job as a reporter. This is the first time I've ever been in close contact with a lion.

00:18:58.640 And frankly, it scared me to death. He said, ah, don't worry about that. He says, I've got lots

00:19:04.540 of professional trainers. Translation, you're the only one dumb enough to do this job. I can't find 1.00

00:19:08.720 anybody in my union willing to do this, but yes, carry on. Exactly. Exactly. So I was still pretty

00:19:15.180 dubious. I have to sell you, but here was the key. He said, well, the way you're going to start

00:19:21.240 is I'm raising some lions at my house. And so I'd like you to live at my house for the next few

00:19:27.040 months and take care of the lions. And the only people that you'll have to deal with is my wife 1.00

00:19:33.800 and my daughter, my wife, Tippi. And I had this crush on this actress named Tippi Hedren since I'd

00:19:42.580 seen her in the birds when I was a kid. And as soon as he said Tippi, I thought, gee, that's a 0.73

00:19:48.480 unusual name. And it turns out he was married to Tippi Hedren. So suddenly I'm thinking of going and

00:19:55.400 living in a house with an actress that I had a crush on since I was 11 years old. So that changed

00:20:01.740 my attitude entirely. So I said, okay, you know, when do I start? I mean, at this point, Steve,

00:20:08.160 you have more than enough substrate to write a fantastic novel, right?

00:20:12.100 Yeah. By that time, I realized that that's not where my talent lay. So I really wasn't thinking

00:20:21.060 anymore of writing a novel. I was trying to think. I loved animals so much. I thought, gosh, this is

00:20:26.480 great. I get to spend my entire day around these animals. And actually for the first year I worked

00:20:33.120 there, I never took a day off on Saturday and Sunday because I just enjoyed it so much. So I'd almost

00:20:39.480 feel like I'd been given this gift of something that I was always meant to do, but just by luck,

00:20:45.800 it had just stumbled into it.

00:20:48.360 So what finally got you to go back to graduate school?

00:20:53.660 Probably a bad encounter with a lion. I was fairly significantly injured by a lion and I had to,

00:21:02.760 I spent a couple of weeks in the hospital and a couple of more months laid up with a lot of time.

00:21:09.480 I jumped me. A lion attacked me under a very bizarre set of circumstances. And there was no

00:21:16.160 one around when this happened. So I was completely helpless, you know, pinned to the ground by this

00:21:21.600 lion expecting that it would start eating me at any point. And again, it's one of these lucky things.

00:21:27.460 The only thing that saved me is it grabbed me and it sunk its teeth into my leg, but it was getting

00:21:34.620 possessive over my leg because they get that way over food. They get, if you've ever seen a group

00:21:39.540 of lions eating, they'll just get their food in front of them and grab onto it very tightly. And

00:21:44.400 that's what it was doing. And so I was just trying to stay conscious and not pass out because I thought

00:21:52.280 then he's going to let go of my leg and start to eat me. And the only reason I'm here today is there

00:21:57.380 were some people that were driving by on the road above the compound. And this was kind of a well-known

00:22:04.320 place that people could pull off the road and they could look down and they might see lions running

00:22:09.220 around or tigers.

00:22:11.720 Where was this, Steve?

00:22:12.920 This is in Acton, California, which is just north of Los Angeles, out in the desert between near Palmdale.

00:22:19.580 And so they saw me with this lion on top of me. So they drove up to the front office and said,

00:22:25.840 there's a guy in the back with a lion on top of him. We don't know if that's supposed to be that

00:22:30.820 way or not. And so they came and rescued me, the, you know, the other trainers that were in the

00:22:36.080 office. So that gave me a lot of time to think about my future. And I really, by that time was kind

00:22:42.600 of disinterested in the Hollywood part of it. I still love the animals, but I really got bored with

00:22:49.380 the movie aspect of it because there's a stereotype that movie people only talk about movies and making

00:22:55.500 movies and movie deals and movie sequels and movie reruns. And I didn't find that very interesting.

00:23:01.500 And so I'd really gotten bored with that part of it. So I thought I've accumulated all this knowledge

00:23:07.600 about animals that's applied. Maybe I should go to graduate school and study it in a formal

00:23:14.300 sort of sense. So I actually went to graduate school with the intention of studying lions in East

00:23:19.080 Africa. And I went to East Africa at that point. There was a long running Serengeti lion project

00:23:25.760 that had just ended. The people that were doing it had just quit. I went to graduate school. My advisor

00:23:32.920 did research in East Africa on monkeys. And he told me, if you get over there, you might be able to take

00:23:39.060 over this project. But I didn't. By the time I got there, someone else had come and taken it over.

00:23:44.980 So it didn't work out. So I ended up doing a PhD that was a very combining my math and my interest

00:23:52.380 in animal behavior. And I did a PhD on sort of theoretical models of animal combat and why animals

00:23:59.020 very seldom fight to the death and under what circumstances they might do that. So I had nothing

00:24:05.120 really to do with lions. At that point, I didn't really know. I thought, well, I've got a PhD. I guess I should be a

00:24:13.720 professor somewhere. But I had no interest in aging. It never even occurred to me. But I did a postdoc

00:24:19.800 in South America at a biological station. Again, unrelated to aging, I was studying these social

00:24:26.960 birds. But a friend of mine there was studying another group of animals. But he kept catching

00:24:32.500 opossums in his traps. And at one point, I said, you know, you're not able to catch the foxes that you

00:24:39.780 want to. You're catching the opossums. You're studying the wrong thing. You should be studying

00:24:43.820 the opossums. So he said, well, what of interest could we do to the opossums? And we put our ads

00:24:52.100 together and came up with something. It still had nothing to do with aging. But in the course of that

00:24:57.560 project, I would capture opossums once a month. And I would weigh them and measure them and look in the

00:25:04.400 pouch. These were all females that were radio collared. And one of the things I discovered 0.88

00:25:09.000 was they aged incredibly quickly. You know, so this is an animal. The South American ones that 1.00

00:25:14.340 we were studying look very much like the North American opossums. Most people would not be able

00:25:19.420 to tell the difference. So they're about the size of a small cat. And I expected they would live 10 or

00:25:25.340 20 years like cats do. And here at 18 months, they would get cataracts. They would lose muscle.

00:25:32.340 They would be able to parasitize. They would just look terrible. Even the same animal that I'd caught

00:25:38.120 three months earlier. And I just became incredibly intrigued with why they would age so much more

00:25:45.000 quickly than a cat. And that really started my interest in aging. In fact, the project that he

00:25:54.140 and I were working on eventually was published in one of the most prestigious scientific journals.

00:25:59.800 And by the time it came out, I completely lost interest. I was interested in aging. And I've

00:26:04.740 been interested in it ever since, you know. So that's kind of the long story about how I got into

00:26:11.940 this.

00:26:13.380 After you finished your postdoc, where did you come back to?

00:26:15.740 When I finished my postdoc, my first faculty position was at Harvard. And it was great because

00:26:20.720 that was the point where I was switching over from what I had done before, which was behavioral

00:26:26.800 evolution to aging. And at Harvard, junior professors, they don't care what you do, really. So I had some

00:26:33.900 time to really gear up and switch fields. It wasn't like I had to get six grants the first year or

00:26:39.920 something. So it was great. So I basically spent some time developing my first aging study, which was a

00:26:47.140 field study of opossums. And these were North American opossums. But I was comparing the way they aged

00:26:55.920 on an island compared to the mainland. And I was interested in that because there were some

00:27:02.540 theories of aging that suggested that animals that had evolved in environments that were low risk,

00:27:10.600 and this island had no predators on it, will evolve slow aging at the same time.

00:27:18.220 So I ended up doing this project where I had a population of opossums on the mainland and another

00:27:23.500 population on the island. And I would track them from birth to death. Because one of the nice things

00:27:28.740 about opossums is that because the babies are born in a pouch, if you catch a mother that's got babies 0.85

00:27:36.000 in the pouch, pouch young, you can mark them at that point. And then if you later catch them, you can put

00:27:41.700 a radio collar on them. So you know the exact birth date, basically, of every animal in a population

00:27:47.340 fairly quickly, which is pretty unusual for wild animals. That was really how my aging career got

00:27:55.140 started at Harvard. And it was a great experience. It was a wonderful place to be. Unfortunately, my wife

00:28:03.540 hated Boston. And so she was really wanting us to go somewhere else.

00:28:09.960 What did you find out about the opossums? And what explained the difference? How much of a difference

00:28:15.700 was there between the groups that grew up in a low stress environment versus the high stress

00:28:21.540 predatory environment? There was about a 20% difference. Okay. So pretty substantial difference.

00:28:27.340 And the next phase to figure this out was to try to work on the mechanism. What is it? And this was

00:28:34.940 cortisol related. Right, exactly. This was in, you know, this by now was in about 1990. And we didn't

00:28:41.720 have genomics, really, at that point. If we did, the first thing I would have done is sequence the

00:28:47.860 genome of the opossums on the island of the mainland. But the only thing I could think of to do next was

00:28:53.520 two things. One, I was interested, is this some genetic thing? Did you do a swap? In other words,

00:29:01.040 did you take the island version and just let them breed? Or, you know, because in one generation,

00:29:07.880 you'd pretty much get your answer, right? That's exactly right. And I submitted a proposal to do

00:29:12.700 that, and it didn't get funded. There was a problem. I could only really do it in one direction.

00:29:18.000 I could take the island of opossums and release them on the mainland and see how they did.

00:29:22.520 I didn't want to do the reverse because I thought, if this is really a unique genetic population...

00:29:27.260 Right, you don't want to contaminate it.

00:29:28.880 Yeah. So I never did that. It was the obvious thing to do, and I thought about it,

00:29:33.060 but I never ended up doing it. And I'm sort of disappointed. What I did, though, is I got

00:29:37.660 a population of opossums that I brought into the laboratory. And my plan was to start off with just

00:29:46.220 some regular opossums. And then once I knew how to manipulate opossums in the laboratory to get some

00:29:52.840 from the island. But opossums are really not easy to keep in the laboratory environment. And my colony

00:29:59.500 ended up getting some flesh-eating infection. And so I basically had to abandon that project.

00:30:09.260 You know, I thought about going back to it subsequently. And in fact, I went back to the

00:30:13.280 island, which is called Sapelo Island, which is off the coast of Georgia, about 10 years later with

00:30:19.700 the film crew to do a film about them. And in the interim, a new species had been introduced to the

00:30:27.860 island. Armadillos had never been there before. And now they were there before. So I suddenly got

00:30:33.380 worried that my population of opossums had also been contaminated. So that discouraged me from going

00:30:41.580 back and working on the genomics of those opossums.

00:30:45.860 So at what point did you start to get interested in the difference between animals in the wild and

00:30:54.300 animals in the lab as far as longevity differences? And of course, where I'm going to go with this,

00:30:59.900 Steve, is two directions just to give you a heads up. Obviously, I want to have a really deep

00:31:05.560 discussion on the largest longevity experiment ever done in animals, which is the Wisconsin NIA

00:31:12.260 experiment, obviously animals in captivity. And I also want to talk about the distinction between

00:31:18.740 mice in the wild and mice in the lab when it comes to all of the literature on CR and DR.

00:31:26.100 Right.

00:31:26.460 So it's really, I mean, and these are discussions you and I have had, and every time we have it,

00:31:30.560 it gets richer and richer. So I guess what I'm really asking at the outset is,

00:31:34.880 when did this subject matter become of great interest to you?

00:31:39.320 Okay. So my background is entirely in field biology at the point when I start doing laboratory

00:31:46.360 biology. So I'm coming from it from a way different perspective than most people.

00:31:51.980 And when I started to learn about the, not just the mice, but the other laboratory animals and how

00:31:59.640 much different they were than the same species in the wild, I started to get very interested in

00:32:08.900 what I call laboratory evolution. How have these things changed in the hundred years or so

00:32:16.240 since they were brought into the laboratory? Because, you know, when I was in the field,

00:32:22.100 I'm always thinking about, well, how is evolution shaping these animals to do whatever? And in the

00:32:28.740 laboratory, I'm thinking, well, the way that we breed them and the way that we inadvertently select

00:32:34.800 them, there's very strong evolutionary pressure on laboratory animals. It's just that most people

00:32:40.900 aren't aware of that. So I started thinking, well, what can we learn? Is there anything to learn?

00:32:46.720 And one of the things right off the bat was this dietary restriction experiment.

00:32:53.020 Now, before we even get to it, Steve, maybe we should explain to people what a laboratory mouse

00:32:59.160 looks like. You know, when you think about the B6 mouse, which is sort of the workhorse of so much of

00:33:05.360 the research that goes into cancer biology, I've had guests on this show before who have made a very

00:33:10.080 compelling case that we simply should never use that mouse model for anything that comes down to

00:33:15.760 cancer therapeutics, because whatever you learn in it almost assuredly is not going to apply later on.

00:33:21.660 But notwithstanding that, help folks understand what a mouse in captivity has been through. What does it

00:33:27.960 mean, for example, to be homozygous at each loci? What is it that we're trying to accomplish? And what's

00:33:34.980 the price we potentially pay for that? Yeah. So let me describe the history of the laboratory mouse.

00:33:41.460 So the laboratory mice came from what were called fancy mice. And these were mice that were bred for

00:33:48.000 bizarre coat colors and coat textures, kinky coats, straight coats, silver coats. And people used to have

00:33:57.760 mouse beauty contests, just like the Westminster Dog Show. There used to be mouse equivalents. And

00:34:04.000 for all that, there probably still are mouse equivalents. So at some point, this is early

00:34:10.820 in the 20th century when they just rediscovered the laws of genetics from Mendel. Some geneticists

00:34:17.900 got looking at all these bizarre coat colors and said, this could be a nice model to see if

00:34:23.900 mammal rules of inheritance are the same as plant rules of inheritance. So they started working with

00:34:30.120 the mice for genetics. And then for reasons of trying to understand the genetics, they started

00:34:36.300 inbreeding them. And when I say inbreeding, I'm not talking about cousin breeding. I'm talking about

00:34:41.620 brother-sister mating. And they did that for now hundreds and hundreds of generations.

00:34:49.020 So the mouse that we currently have in the lab, the typical mice, come from mice that were selected for

00:34:56.120 bizarre coat colors and sizes. Mice that were then inbred for hundreds of generations so that they're

00:35:06.080 absolutely genetically identical to one another. And then over the generations, of course, as we're

00:35:13.000 raising these mice every, you know, once they started being commercially valuable, the companies that

00:35:17.960 produced them would always, the ones that left the most young were the ones that formed the next

00:35:23.400 generation. So you're always getting this selection for bigger and bigger litters and faster growth and

00:35:29.740 more rapid reproduction. So by now you have what a friend of mine calls a mouse-like object.

00:35:36.780 Something that looks like a mouse, but it is, it's not only genetically identical to the other ones,

00:35:42.480 it's now called a strain. Okay. So B6 is a strain. It's now called, it's not only genetically

00:35:47.860 identical, but again, because of the inbreeding, it's, it's homozygous at every locus. That is,

00:35:55.020 it has exactly the same two genetic variants at every single place in the genome. So that makes it

00:36:04.620 very, very different from any kind of, from humans certainly, but from any animal in the wild.

00:36:11.880 And I got very interested in how does that affect all of the experiments, not just in aging, but in

00:36:22.440 cancer, in Alzheimer's disease. I mean, we use that one mouse and I used to say to people, this is like

00:36:30.420 if we only tested drugs in the same set of twins time after time, after time, after time, rather than

00:36:38.840 ever going out. So I agree with the people you've had on your show that said, we need to really avoid

00:36:48.460 this kind of reliance on such a bizarre creature. You know, I mean, it's about as bizarre of a creature

00:36:55.380 from a zoological perspective, as you can imagine. They're twice as big as a wild mouse, at least twice

00:37:02.120 as big. They reach sexual maturity about twice as fast. They have much larger litters. They have a

00:37:09.660 bunch of bizarre mutations and some strains become blind in a few months of age. Some become deaf.

00:37:17.220 Some, if they hear a loud noise, start having convulsions. And this is the fundamental basis of

00:37:23.160 our biomedical research enterprise as it applies to mammals. So there's 4,500 species of mammals.

00:37:30.880 The fact that we've had one species and a very bizarre species at that be the substitute for

00:37:38.620 all of the others, including ourselves, is just a very weird approach. And to me, it just shows that

00:37:45.080 the culture of evolutionary biology is never really soaked in to the laboratory biology. And I've kind of

00:37:53.420 made it my goal to try to help with that over my career.

00:37:57.480 Now, some people, of course, have gone to great lengths to avoid this. So I recently had Rich

00:38:02.700 Miller on the podcast, and we talked about the intervention testing program, the ITP.

00:38:07.780 What is it that they do that raises the bar on rigor?

00:38:13.120 Right. So Rich Miller is a good friend of mine, and we've done a bunch of projects together on

00:38:17.500 mice, on different kinds of mice. And what the ITP does is that they create

00:38:23.240 what are called genetically heterogeneous mice. That is, every single mouse is genetically unique,

00:38:29.460 but they're all brothers and sisters, so that you can recreate that population at any time. Not

00:38:36.280 the specific individual, but the population. Now, the interesting thing about those mice

00:38:44.160 is that their ancestors are all these inbred mice. So they've been selected for strange genetic

00:38:51.900 alleles that only work seemingly when they're together with themselves. So I'm a very big fan

00:38:59.940 of that mouse model, I have to say, because I think it's a huge step in the right direction.

00:39:05.520 It's the least bad option, basically.

00:39:08.460 Exactly. And there's one kind of weakness that I'd like to see them work on, and maybe they will,

00:39:15.660 because of the breeding scheme that they use, all of the mice have the same mitochondria. No matter

00:39:23.780 how genetically diverse they are, they all have the same mitochondria. And we now know that the

00:39:30.320 mitochondrial genotype, because it interacts so closely with the nuclear genotype, can have a huge

00:39:37.200 impact. And in fact, someone here at my university, Scott Ballinger, has created these mice that have

00:39:43.580 different mitochondria in the same nuclear background. And they have very different

00:39:49.040 characteristics. The other thing is that because all of the current laboratory mice came from a

00:39:54.540 relatively small number of these fancy mouse ancestors, they all have pretty much the same

00:40:00.160 mitochondria. The only differences are differences that have evolved slowly by drift over the last

00:40:07.080 hundred years. So for instance, my friend that's got the nuclear mitochondrial exchange mice,

00:40:12.840 his two mitochondria, which are very different by mouse standards, only differ at five individual

00:40:18.740 nucleotides in the whole 16 and a half thousand nucleotide mitochondria.

00:40:25.140 How many genes is that again? Is that about 20 genes?

00:40:28.380 Yeah, it's about 17 typical genes, but we're finding new genes. It's interesting. We're finding new

00:40:33.900 genes in the mitochondria. So it's around 20 or 25 genes. So we may be missing out on a huge amount of

00:40:42.560 variability that's due to mitochondria. And humans, of course, have incredibly variable

00:40:48.360 mitochondrial genomes.

00:40:50.460 Now, is it too late, Steve, to sort of say, look, we're going to go into the wild,

00:40:54.720 get a whole bunch of completely wild mice that are so genetically heterogeneous, and we're going to start

00:41:01.140 letting them breed. And we're not going to force them to be inbred. We're just going to let them

00:41:06.080 breed naturally. Is that just too expensive? Or like, why has no one gone about trying to address

00:41:12.460 this? Because it's such an obvious limitation.

00:41:16.020 Right. Well, I think one of the reasons is the lack of genetic control that you would have in that

00:41:21.620 situation. There has been some attempt to do that. That is, people have been working on a genetically

00:41:28.560 diverse population of mice, where they took a whole number of the laboratory mouse strains

00:41:33.920 and mixed in a couple of recent introductions from the wild and mixed them all together to create

00:41:41.080 something. The problem is, in talking to those people, the wild backgrounds don't seem to breed 1.00

00:41:46.380 as well in captivity. So gradually, those genes are lost. But I think there are some reasonable

00:41:53.300 alternatives that are out there that are being developed and have been recently developed.

00:41:58.380 It's just that it's going to take a big change in the culture of the way we do laboratory medicine,

00:42:05.000 I think, before people will accept that. It probably comes back to a point you made earlier,

00:42:10.880 which is for many people who work in the lab using laboratory mice, that's all they've known.

00:42:18.120 And it might not be as apparent to them how genetically far removed they are from their predecessors.

00:42:24.840 Whereas because you came at this from being a field biologist, and also with a much greater lens for

00:42:32.840 comparative gerontology, right? You're looking at this opossum and that opossum, and these are both

00:42:38.900 wild, and yet they have some differences, but they're not totally different. It may simply be a

00:42:44.320 blind spot, right? Yeah, I think it is. And I think that even the best mouse is still a mouse.

00:42:50.840 It's still one species, and it's a very different species than we are. And so even the best mouse

00:42:58.320 model is not going to be enough. We need to know more about general mammalian biology if we're going

00:43:04.780 to understand our own biology better. Well, before we leave the mouse, let's talk a little bit about

00:43:12.160 Clive McKay and kind of the history of caloric restriction. I think most people today are generally

00:43:21.160 well aware of the reported efficacy of caloric restriction in life extension. There are no

00:43:28.760 shortage of people that are now looking at ways to mimic caloric restriction, be it pharmacologically

00:43:35.580 with molecules, or be it using dietary interventions that sort of act like transient periods of caloric

00:43:43.720 restriction, all in search of what we believe CR does. But let's maybe have you explain to people

00:43:52.180 what this history looks like. Sure. Well, the first person to really do this in a formal way was,

00:44:00.140 as you mentioned, Clive McKay, who was a nutritionist at Cornell at the time. And he wasn't

00:44:06.640 interested in aging either. He was interested in growth and how to make animals grow faster,

00:44:12.560 because that has all kinds of agricultural implications. And so in studying growth, he was

00:44:18.380 looking at the effect of restricting the diet on growth rate. And when he did that, he noticed

00:44:25.080 that his animals seemed to be staying healthy longer and living longer when he fed them less.

00:44:31.780 And he did this in fish. He did some stuff in dogs, although he didn't look all the way through

00:44:37.360 their lifespan. And then he finally did this experiment in rats. In that one, he let them live

00:44:43.060 their entire lives and documented very convincingly how dietary restriction made, in this case, only females,

00:44:52.140 males, live longer. And the interesting thing about McKay is that about a decade ago, I was a visiting 1.00

00:45:02.220 scholar in Ithaca, New York for a week. And I went to the Cornell libraries and I looked through all of

00:45:07.880 his old papers. And I don't think he ever really appreciated the significance of what he'd done,

00:45:15.620 because he didn't really follow up on that.

00:45:17.700 This was in the 1930s, if I recall.

00:45:19.940 Yeah, this was in the 1930s. And he was active until the 1960s. But he got into producing high-protein

00:45:28.780 bread and making nutritional food for the military during World War II. And he really kind of dropped

00:45:35.520 this whole thing. So even though he made what, in retrospect, was really, I think, a landmark

00:45:40.840 discovery, I don't think he really appreciated that, because he was never focused, really, on longevity.

00:45:46.560 So what are the ways in which this got validated and repeated throughout time? Who was the next person

00:45:54.060 to pick up that baton?

00:45:56.120 You know, I'm not exactly sure who the next person was. There were a whole bunch of people

00:46:00.860 starting really after World War II that started looking at it more closely in rats and more closely in mice.

00:46:11.080 And there were actually a whole bunch of people working on invertebrates that did this experiment

00:46:15.960 by accident. And I'm one of them, actually. The first paper I published on this topic was some

00:46:22.800 stuff that I did during my PhD. So my PhD was testing all these mathematical models about combat,

00:46:29.640 but I was testing it in a small spider. And as part of that experiment, I had groups of spiders that

00:46:35.760 I was feeding various amounts. And I would keep them until they died, but I wasn't paying any

00:46:41.280 attention to that. Once I discovered all of this work, I went back to my data and I said, well,

00:46:48.320 I wonder what happened when I fed them less. And it turned out the less I fed them, the longer they

00:46:53.120 lived. And so after World War II, people really started getting interested in this. And there were a

00:47:00.880 number of people, there was mouse studies now, rat studies. There was really, I think the next big

00:47:07.260 advance was when Roy Walford got into it, who was very interested, not just in how mice age, but how

00:47:15.680 that might tell him something about human aging. And Ed Masero, another researcher who followed up on

00:47:23.240 rats. And those two, I think, really jumped it to the next level, which is, can we understand why this

00:47:29.780 is happening? There was really very little investigation of that previously. But Walford, who was an

00:47:36.960 immunologist, was very convinced that was doing something to the immune system, and that was at the

00:47:42.440 base of it. And Masero was, didn't really have his own hypotheses, but he thought that it was a great way

00:47:50.400 to test hypotheses about how aging worked. The other big difference between these really fascinating

00:47:56.820 characters. I mean, Walford, probably one of the most interesting and colorful personalities.

00:48:02.280 You must have known him, because he only died, what, maybe 20 years ago, 25 years ago?

00:48:07.520 Oh, yeah. In fact, my first paper, he published the figure out of my spider paper before it was

00:48:13.580 published in a real journal, because he had heard about my work. And he asked that, I'm writing a book,

00:48:19.980 can I put this figure in my book? So, yeah, I knew Roy quite well. He was.

00:48:25.380 Of course, he's famous for the biodome, right?

00:48:27.920 Yeah, the Biosphere 2.

00:48:29.400 A biosphere, yeah, yeah, yeah, yeah.

00:48:30.900 Yeah. And it's pretty interesting, when I was writing my book on, you know, so the Biosphere 2 was

00:48:37.460 this inadvertent experiment on dietary restriction, because these people were sealed in this dome,

00:48:43.640 and they couldn't grow as much food as they thought. And Roy was the doctor in there. And so,

00:48:50.840 this was a great opportunity. You know, he wanted to know how dietary restriction worked in people,

00:48:55.820 and here he had all these people that couldn't make enough. Anyway.

00:49:00.880 How long were they in the Biosphere?

00:49:02.920 Two years.

00:49:04.020 And when you look at pictures of him when he came out, I mean, he looked pretty emaciated.

00:49:08.440 Oh, he looked horrible. He looked absolutely horrible. In fact, they have this famous picture

00:49:14.580 of them all standing on the rafters in the Biosphere when they went in, naked. And they

00:49:23.660 had the same picture that Roy showed at a meeting when they came out. And you've seen pictures of him.

00:49:28.980 He looks like he just emerged from a concentration camp, right? Well, I wanted to use that. And they all 0.72

00:49:34.480 look like that. I wanted to use that picture before and after in my book on aging. And so, I asked Roy

00:49:40.980 about that. And he said, I'd love to give you that picture, but everything's tied up in litigation.

00:49:48.080 It turned out that the people in that experiment had become enemies. And everybody was suing everybody

00:49:53.860 else over everything having to do with the Biosphere. So, psychologically, that wasn't such a great success.

00:50:02.520 People would disagree about whether it was a success scientifically or not. Roy thought it,

00:50:09.100 you know, he looked at it in one way, thought it proved everything that he had seen in mice

00:50:14.000 was true in people. Other people were looking at it and say, oh my gosh, I don't know how you felt,

00:50:20.080 but you just looked terrible. And then he died.

00:50:23.200 Yeah, he died young, right? I mean...

00:50:24.760 Yeah, well, he was at that, I think he was 79 or something.

00:50:27.680 But he was always one of these people that if you knew his age, you'd say, man, that guy looks

00:50:33.460 20 years younger than he is. But after he came out of the Biosphere, he didn't look like that anymore.

00:50:40.140 Now, the other thing, to be fair, that happened in the Biosphere is that the atmosphere got really

00:50:45.920 out of whack. When they ended up, without realizing it, they had so little oxygen, they were living at

00:50:52.380 the equivalent of about 17,000 feet. Yeah. And they'd been doing that for, they didn't know how

00:50:57.820 long. Eventually, so they had to refresh the air and the environment. And he attributed his later

00:51:04.860 health problems to that, not to the dietary restriction.

00:51:08.960 Which is certainly plausible. I mean, we'll never know. But yeah, to spend some portion of two years

00:51:14.340 at Everest Base Camp, if you haven't grown up there, it's one thing if you're a Sherpa, right? But it's

00:51:19.540 another thing if you've spent your whole life at sea level. So going back to the sort of CR insights,

00:51:28.540 sorry, before I do that, what can you tell us about rats versus mice in terms of the genetic

00:51:35.060 diversity and the ability to glean insights that are perhaps more or less interesting?

00:51:41.880 Rats are a lot different to the extent that, as I say, almost all the, well, all of the

00:51:49.380 traditional laboratory mice strains came from this small handful of weird ancestors. Rats have a

00:51:55.160 different history. They were used earlier in biomedical research, actually, but they've been

00:52:00.020 domesticated multiple times in multiple parts of the world. So if you look at all the genetic

00:52:05.680 diversity and the mitochondrial diversity that you have in rats, it's far greater than you have in mice.

00:52:13.160 And so I'm actually working with some other people now trying to bring the rat back more into aging

00:52:20.260 research because we discovered how to manipulate the genes of mice a lot earlier than we discovered

00:52:26.520 anything else. And so they kind of took over. That's really why almost all the focus is now on that

00:52:31.580 one species. We now can do these genetic manipulations in other species just as easily. And I'd like to see

00:52:39.440 something like the rats. For instance, we're working on a rat, which the two mitochondria we're interested

00:52:46.220 in, instead of differing only at five of these nucleotides or DNA letters, differ at a hundred

00:52:52.020 of them. So that's much more similar to the kind of genetic diversity that you find in people's

00:52:58.860 mitochondrial genomes rather than rats. So I'm hoping in the next few years, I would like to see

00:53:05.160 something like Rich Miller's interventions testing program in rats as well, because I think I'd have

00:53:11.900 a lot more confidence that something we found in mice might have relevance to people if we found the

00:53:19.760 same thing in rats. You know, it's not the ideal comparison, but considering because rats and mice

00:53:25.640 are reasonably closely related, they're kind of like we are to a rhesus macaque about that degree of

00:53:33.160 divergence. But still, they're very different. We also can do a lot more sophisticated cognitive

00:53:40.620 studies with rats than we can with mice. They're trainable, you know. And so I'm hoping that over

00:53:48.920 the next few years, we can make an impact and bring the rats back because we might learn something

00:53:55.660 differently. You know, right now, one of the most robust findings in mice is that if you somehow disable

00:54:01.940 growth hormone activity, the mice stay healthy and live a lot longer, there's only been one

00:54:08.600 experiment doing that in rats, and it came to a very different conclusion. It's kind of like the two

00:54:14.980 primate, you know, calorie restriction studies. But again, it's one study against the gazillion

00:54:21.900 studies over here. But I'd like to really look at, are we getting a biased picture of something like

00:54:29.520 growth hormone? Because we only really know a lot about its mechanism in mice.

00:54:35.780 What is your best explanation for why the rats, given growth hormone, fared better?

00:54:41.880 They fared worse. They didn't live any longer. I don't know.

00:54:45.380 No, no, but they fared better than the mice, didn't they?

00:54:47.800 Oh, so we're talking about two different things here. So if you compare dozens and dozens of mouse

00:54:54.040 studies, and you look at how much life extension there was with dietary restriction, and you look

00:54:59.220 at a whole bunch of rat studies, you're right. The effect is bigger in rats. And growth hormone

00:55:05.040 is suppressed by dietary restriction. The experiment I was talking about was one where they had taken a

00:55:11.700 natural genetic mutation that disabled growth hormone in the rats. And that didn't live longer,

00:55:18.560 like the same natural mutations occurred in mice. Now, why is the effect bigger in rats than mice?

00:55:26.480 That's a good question. I don't think we know why. And I also don't know how far to push that

00:55:35.140 comparison, because there's been a lot fewer rat studies done. We've done mouse studies with a much

00:55:43.660 greater diversity of mice. And so if you look at the biggest effect that we've ever seen in a mouse,

00:55:50.360 and the biggest effect we've ever seen in a rat, those are not that different. So I think it's a

00:55:55.360 little bit premature to conclude that dietary restriction works better in rats generally than

00:56:03.120 it does in mice. That may be true, but I just don't think we know enough yet.

00:56:08.280 Speaking, of course, about big experiments with DR and CR, we have to look no further than,

00:56:15.980 I mean, they have to be the largest experiments done, the Wisconsin NIA experiment, correct?

00:56:20.800 Yes. I mean, certainly the most expensive aging experiments that have been done,

00:56:25.100 that haven't been done in people.

00:56:26.940 Yeah. So gosh, this experiment was probably kicked off in the late 80s?

00:56:33.360 Yeah, exactly. Yeah.

00:56:34.720 Tell folks about the experimental design.

00:56:38.860 Yeah. So it was almost serendipitous that they'd started at the... So two groups,

00:56:44.660 one at the National Institute of Aging, one at the University of Wisconsin, and one person,

00:56:50.660 Rick Weindrick, had actually was involved in both. He was at the NIA when that project got started,

00:56:56.240 then he moved to the University of Wisconsin. And the idea was to see whether the results that we saw

00:57:04.460 in these laboratory rodents could be replicated in something that was a lot closer related to

00:57:09.960 humans, and also something that hadn't gone through these bizarre laboratory inbreeding selection

00:57:15.640 and all that stuff, closer to a real animal, in other words. And of course, these things live

00:57:21.880 up to 40 years. Actually, many people don't know, but there was another study started at the same time

00:57:29.820 on squirrel monkeys, because they were only supposed to live 25 years, and they thought they could do

00:57:35.680 that quicker. But it turned out squirrel monkeys were unusual. You could restrict their diet, but they

00:57:40.800 didn't lose weight. So they ended up abandoning that study. So anyway, because monkeys live so long,

00:57:48.520 and it takes so long to see results, these things went on for years and years, and they would publish,

00:57:53.980 you know, occasional studies about their blood glucose, how it would affect their blood glucose,

00:57:58.900 their body fat, and all these. Eventually, when enough died, over the next few years, they came to

00:58:04.800 very different conclusions. Now, I've got a lot of friends and been involved in both of these studies,

00:58:11.940 and so at the risk of irritating my friends, I'll have to say that I think we learned something

00:58:17.960 very different from each of the studies. So let's explain some of these differences,

00:58:24.280 because I do think there were some interesting differences. And by the way, it's an interesting

00:58:27.740 footnote to, just by total coincidence, that when the first of these papers was published in 2011,

00:58:36.120 I believe it was the same day, so I should say not published as in the scientific publication,

00:58:42.580 but on the day that the New York Times ran the story of the results of the first of them,

00:58:49.900 which I think was Wisconsin, on that same day, they ran the rapamycin ITP result, the first

00:58:56.580 RAPA ITP result. Oh, in 2009.

00:58:59.420 Yeah, 2009, in 2011, you're right. What's interesting is, of course, the monkey study was

00:59:04.480 front page news, the RAPA study was buried in the back, barely got it. Yeah. See, I didn't remember

00:59:11.140 that at all. That's interesting. Yeah. So what was different? Let's talk about what was different

00:59:16.560 between these experiments. Yeah. Well, first of all, let's talk about wild monkeys versus

00:59:21.480 laboratory monkeys. So they haven't been in the laboratory long enough to really have had the kind

00:59:27.080 genetic alterations that mice have. But again, this comes from, you know, I had a long history

00:59:33.440 with studying, you know, lions and tigers and other big cats and bears and elephants in captivity,

00:59:39.480 and then seeing them also in the wild. And one of the things that we know is that virtually all

00:59:47.440 captive animals are obese relative to their wild cousins, including us.

00:59:54.420 Like us captive humans. Exactly. I was just about to say.

00:59:57.880 Exactly. And one, you know, one of the things that I did in the late 80s, early 90s, that I did

01:00:02.740 some research in Papua New Guinea, where we're basically studying people who are still hunting,

01:00:07.820 you know, with spears and arrows. And it's very similar to wild, you know, primates versus captive

01:00:15.300 primates. So, so all of why all captive animals are obese to a degree. Now, there are some that are

01:00:23.300 just frankly obese. And there are some that look okay to us because we've only seen animals like

01:00:29.160 that, but they still have a lot more body fat. So what the Wisconsin study did is they took animals,

01:00:37.020 the control animals that were eating ad libitum. So they, they had food available pretty much all the

01:00:43.000 time. And they restricted each individual animal by 30%. So they tracked individual animals. How much

01:00:51.380 does it eat over a certain amount of time? And they said, okay, it's diet for the rest of its life is

01:00:57.760 going to be 30% less than that. And they did that for the next 35 years.

01:01:03.840 And this was one-to-one randomization, Steve? Yes.

01:01:07.980 So just to be clear, they follow all the animals, get a baseline intake for them. Then they divide

01:01:14.500 them in half randomly. One group gets to continue consuming that amount or gets to continue consuming

01:01:21.420 ad libitum. Yeah. It gets what it wants to eat, ad libitum. Okay. So that's an important distinction.

01:01:26.620 The CR group gets pegged to 70% of what they were eating during the run-in.

01:01:33.300 Right. And so, you know, 35 years later, they report that the animals that are eating less

01:01:40.820 are living longer, substantially longer, and by all kinds of disease metrics are healthier. So

01:01:50.140 pretty much replicating the laboratory experiments. Now, I have to say that up to this time, I really

01:01:58.680 hadn't thought too much about how you would translate the laboratory rodent experiments into human

01:02:05.220 experiments. But suddenly, because I was asked to write something up on these two experiments,

01:02:10.840 I started thinking about, yeah, what are we? I mean, you think about it, a rat or a mouse spends its

01:02:18.520 life in a cage that's no bigger than a jail cell, usually has very little except other animals in

01:02:28.880 the cage. So it has zero opportunity for much physical activity. And needless to say that because

01:02:36.620 they have food available all the time, because they've been selected to reproduce as much as

01:02:41.060 possible, they're going to get really quite big. And I think that that was a perfect replication

01:02:47.520 the Wisconsin study of what goes on in most laboratory rodent experiments, which I think is what

01:02:54.880 they'd intended. I think the philosophy of the National Institute of Aging Study was different. I think

01:03:00.300 they were trying to say, what is the relevance for people? And not for people who are sedentary and obese,

01:03:07.580 but for people generally. So what they did differently, well, let's just talk about the way they did the

01:03:13.300 experiment. What they did is they said, we want our control animals to be at what we consider to be a

01:03:20.460 healthy body weight. So we're not going to feed them ad libitum. We're going to feed them a couple

01:03:25.640 of times a day, and we're only going to feed them enough to keep them at what we think is a healthy

01:03:30.760 body weight. And we're going to restrict our other animals, our restricted animals, 30% from that.

01:03:37.860 So now we're talking the restricted ones are going to be much leaner than the Wisconsin restricted ones.

01:03:45.320 And the controls are also going to be much leaner.

01:03:49.180 So it's a form of pair feeding, but it's a CR pair feed basically.

01:03:53.260 Yeah, exactly. And what they really were saying is, look, if you take a healthy human and you

01:03:57.980 restrict a healthy human, what kind of effect are you likely to see? So almost inadvertently,

01:04:05.480 because I don't really think they had this philosophical difference worked out at the time,

01:04:09.720 but that's really the way I think it ended up happening. And in this case, the animals didn't

01:04:16.800 live any longer. So, and it was, and it was very clear. It wasn't like, well, it's a little bit longer,

01:04:23.100 but not quite enough to be statistically significant. So there's no difference whatsoever,

01:04:28.020 but their controls were also living longer than the Wisconsin controls, which again, not surprising

01:04:35.040 because they're kept at a healthy body weight. And these others are gotten to be frankly obese.

01:04:41.080 And then we get to the difference in the diets.

01:04:43.640 Right.

01:04:44.520 Which is really stark. I mean, that's, that's not a subtle distinction.

01:04:49.440 No. So the difference in the diets is, is, is critical. So if you look at the gross

01:04:54.600 macronutrients, the carbohydrates, the fats, the protein, they're not that different,

01:05:01.180 but here's the critical difference is that they use natural ingredients in the NIA study in the

01:05:09.260 Wisconsin study. They wanted to use what they call purified ingredients because you're complete

01:05:15.440 control of this. You know, you might get a different source of, of, of corn meal and it might differ

01:05:22.000 slightly in nutrients, but if you're just doing specific, if you're just doing albumin, you know,

01:05:27.660 you're always getting the same protein. The trouble is that that wasn't a very palatable diet and to

01:05:34.120 make it more palatable, to do the carbohydrates, they were adding sucrose. And by the end of it,

01:05:41.900 well, I think by the time they figured out the diet, it was a, they were 28%, 28 and a half percent

01:05:47.980 sucrose diet in Wisconsin and you know, very low sucrose, you know, all these natural ingredients.

01:05:55.400 I think it was about 3% sucrose in the Bethesda mice versus, as you said, 28, 29% sucrose there.

01:06:02.720 Bob Kaplan did an analysis for me. We've written about this, I think in a weekly newsletter or

01:06:08.480 something, but the Wisconsin monkeys were effectively eating the equivalent. If they were humans,

01:06:15.200 they were effectively eating three big Macs, two large fries and two jumbo Cokes a day.

01:06:23.520 That was the equivalent of their diet. So you were basically getting a control animal that's eating

01:06:29.160 like three big Macs, two monster fries and two jumbo Cokes a day. And then the CR group was getting 70%

01:06:35.680 of that. In Bethesda, it was basically like a whole foods pescatarian diet with 3% sugar in it.

01:06:45.660 And you know, it's a bit of a shame because it doesn't allow us in my opinion, to appreciate

01:06:52.660 the effect of the weight difference. Because as you said, the controls in each group, there's no

01:06:58.300 comparison, right? The CR group in Bethesda and the control group were the longest lived animals.

01:07:03.440 And they actually lived longer than the CR groups in Wisconsin.

01:07:09.320 Yeah. Yeah. I mean, this isn't, this isn't a surprise when I said, they started off with

01:07:14.560 these squirrel monkeys as well. One of the reasons they abandoned that was they soon realized their

01:07:20.600 squirrel monkeys were living longer than any squirrel monkeys that ever been reported to live

01:07:24.700 before as well. And now their rhesus macaques have been reported to live longer than any macaques

01:07:32.120 had been before. It's interesting because as, as often happens in science, if two groups do what

01:07:38.740 seems to be the same experiment, although with the, I agree with you, this wasn't really the same

01:07:43.680 experiment, but if they seem to do what's superficially the same experiment, they come to

01:07:48.560 different conclusions, they're not happy about it. And so in one of the attempts to reconcile the data,

01:07:56.220 they looked at the weights of the control animals in Wisconsin versus Bethesda, but compared to all

01:08:04.640 of the rhesus monkeys in the country and all of the research facilities in the country. And the

01:08:09.860 Wisconsin ones were about 10% heavier, the controls now, and the Bethesda ones were about 10% lighter.

01:08:16.360 So like I say, I think they're telling us something differently. Someone might want to know if instead

01:08:23.560 of eating two Big Macs and two helpings of fries and two giant Cokes a day, what if I only ate 70%

01:08:31.280 of that? Would I be healthier? Then you as a physician would probably say, yeah, yeah. Eating less of really

01:08:38.260 toxic food is good for you. That's exactly my conclusion from that study is in a still somewhat

01:08:45.840 contrived way. I think what we learned is the worse the diet, the more beneficial the caloric

01:08:52.780 restriction, the better the diet, the less of an impact caloric restriction has. And what that says

01:08:59.940 to me is dietary restriction might be as important, if not more important than caloric restriction by

01:09:05.860 dietary restriction. I mean, manipulating or reducing components of the macro or micronutrient. And in this

01:09:13.020 case, the sucrose was head and shoulders. I mean, to me, this was basically an experiment demonstrating

01:09:18.460 the harm of sucrose. Yeah. Yeah. Because if you looked at what they call glucoregulatory problems

01:09:25.240 and the controls that were massive, and there were zero of those in the restricted animals.

01:09:30.280 And I'm glad you brought that up because it reminds me, the control animals in Bethesda,

01:09:35.480 i.e. the fully fed animals in Bethesda had less diabetes than the calorie restricted animals in

01:09:42.620 Wisconsin. I don't know that that's correct. I don't remember Wisconsin reporting any.

01:09:48.800 No, I think this was an after publication. I'm pretty sure. Yeah. Okay.

01:09:53.400 We'll confirm that for the show notes, but I think this is something that came out much later.

01:09:56.640 But I actually think that the group eating 70% of the high sugar diet had a higher incidence of diabetes

01:10:04.420 than the control in Bethesda. Which again, just speaks to dramatic differences in what you're

01:10:11.700 feeding. Yeah. And I have to say, I don't think we've ever really gone back and worked out the best

01:10:19.520 diets for mice or rats. I think there's a lot still to be done in those. You know, most of those

01:10:28.460 standards were really just developed for keeping them healthy so they could breed. And I think that

01:10:35.600 if we really wanted to understand more about nutrition in those animals, we'd have to go back

01:10:43.220 and do that with modern techniques. If we really wanted to understand nutrition of rats and mice,

01:10:48.380 I don't think we understand it very well. And there's no way to really study monkeys in

01:10:54.260 captivity without limiting their exercise, right? I mean, is it possible?

01:10:59.820 Well, I think it is. I mean, it's possible. I think there are two problems. One is that because

01:11:06.600 you need to control the diet, the animals were kept individually housed. And this is a very social

01:11:14.120 species, just like we are, right? Yeah. And so cognitively, psychologically, these had to be

01:11:23.020 extremely unusual animals. On top of that, because of the size of the cages that they had. Yeah, there

01:11:29.940 was virtually no opportunity for physical activity. That's very similar to the rat and mouse studies,

01:11:36.460 right? But I think for primates... It's probably worse.

01:11:40.060 I think it's, yeah, I think it's much worse. Cognitively, I'd have to think it's terrible.

01:11:46.260 I mean, they were in a room where they could see each other. They could hear each other. They could

01:11:49.880 smell each other, but they couldn't touch each other. So they didn't even get to mingle outside

01:11:55.140 of feeding times? No, no. Probably had to do with captive setup that they had in those two places.

01:12:02.760 It's not easy to get strange monkeys to interact with one another. You might end up with a lot of 1.00

01:12:08.700 fighting. And at least, one of the other differences between the two studies was the Wisconsin animals

01:12:15.120 were all monkeys from India that were born in captivity. And so they knew the precise age. 0.76

01:12:22.360 In the Bethesda study, they sort of added animals of different ages as they got them. Some of them came

01:12:28.220 from the wild. And some of them, they kind of guessed the age at the start. And some of them

01:12:33.020 came from China. So there's some genetic differences as well. So yeah, your basic conclusion

01:12:39.980 that nutrients seem to count, I think, is very valid. And I think that, I think it's also something,

01:12:48.840 you know, I always say that humans are the worst animal to study that you could imagine,

01:12:52.880 because they don't do what you tell them to do, you know, and they'll lie about what they do.

01:12:59.260 But on the other hand, there's certain kinds of studies that I think you have to do in humans.

01:13:04.700 And I think that the idea that the nutrition that works best for a mouse, even if we knew what it was,

01:13:11.960 might not tell us anything. I mean, mice eat seeds and insect larvae in the wild, and we're very

01:13:18.480 different. So I think for these kinds of nutritional studies, I think you really do have to study

01:13:24.560 humans, because humans have their own unique characteristics.

01:13:28.720 Which is a point I'm going to absolutely want to bring us back to as we look to one of the great

01:13:33.460 challenges of studying humans is not only the timescale and the difficulty with interventions,

01:13:38.880 but frankly, the lack of biomarkers that could really help us assess gyroprotection.

01:13:45.100 But I want to go back to kind of what you think would happen to animals calorically restricted in

01:13:51.900 the wild. Imagine this is a thought experiment, although I believe this experiment has also been

01:13:56.520 done in some form or another, where you calorie restrict wild mice. What do we know about that?

01:14:03.100 Yeah, so I actually did an experiment like this. So I didn't calorie restrict wild mice in the

01:14:08.900 wild, I calorie restricted wild mice in the lab. Yeah, yeah.

01:14:12.120 So I brought them into the lab, because one of the ideas that I had, which turned out not to be

01:14:18.420 correct, was that we have selected, well, partially correct, we have selected these animals to grow as

01:14:24.240 fast and reproduce as fast as possible. So we may have created gluttonous mice, just by laboratory

01:14:31.640 selection over dozens and dozens of generations. Mice after my own heart, basically.

01:14:37.080 Yeah, right. So wild mice, of course, don't have that. So I went out and I caught a bunch of wild

01:14:43.960 mice, and I brought them into the lab, and I let them have babies for a couple of generations to get 0.98

01:14:49.340 rid of all the contaminants of being in the wild. And then I restricted their diet. And what I found was

01:14:56.520 that there was no difference whatsoever in how long they lived. Now, I have to say, I'm watching the

01:15:04.820 animals die, and they're right on top of one another, almost. And I'm just ready to say there's

01:15:10.660 no way that dietary restriction works in wild mice. But then the last few, the last 20% lived longer,

01:15:20.060 the restricted ones were living longer and longer and longer. So all of the longest lived ones

01:15:24.620 were in the restricted group. So what I concluded from that is that these are wild animals,

01:15:31.860 they're genetically diverse. So I thought, well, maybe, because the other part of this I didn't

01:15:37.160 imagine, is very early on when I restricted them, a number of the restricted ones died early in the

01:15:43.160 experiment. So I thought, maybe, depending on your genes, dietary restriction will be good for you,

01:15:51.640 can have very little impact on your health, or can be bad for you.

01:15:54.600 The ones that died early, Steve, when you examined them after death, what were you seeing?

01:16:00.760 You know, I don't think that we did enough necropsies on the early ones that died to know

01:16:06.720 that. It's not very easy to get good necropsy material on mice because their bodies cool off so

01:16:14.440 quickly, and their tissues start to degenerate so quickly. So almost all of what we know about mice

01:16:20.940 pathology is from mice that were euthanized. And I don't think we euthanized any because we didn't

01:16:25.860 expect them to die when they were young like that. So maybe they had some nutritional requirement that

01:16:32.680 we weren't meeting. Like I say, we were using standard laboratory chow, and that's, you know,

01:16:38.580 we don't really know how good that was. 0.94

01:16:41.120 Which, I mean, standard mouse chow is total garbage. That's probably a good reason to be 0.66

01:16:46.760 concerned. At the upper end, Steve, did you see a, I mean, I guess if you didn't euthanize them,

01:16:51.700 you wouldn't know, but you'd expect to see cancer being the biggest difference. Although,

01:16:55.640 do wild mice suffer cancer to a fraction of the extent that inbred mice do?

01:17:00.880 They do to a fraction, but they don't, yeah, we did, for the ones that lived longer,

01:17:05.540 most of those we were watching much more carefully because they were getting to the point where we

01:17:09.560 were expecting them to die. So we have quite a bit, we probably have necropsies on about at least 20

01:17:15.980 mice in each group. And yeah, they still get mice. They still get a lot of cancer because let's face

01:17:22.220 it, mice in the laboratory live on average about two and a half years. And the longest live ones

01:17:28.560 live about three years. In the wild, they live on average about three or four months. And the longest

01:17:33.880 live ones live maybe a year or a little longer. So we're talking about incredibly long live mice.

01:17:41.260 So yes, about half of them had cancer when they died. I don't know if that's what killed them,

01:17:47.620 but they had cancer when they died. But that's a lot lower than live mice.

01:17:51.220 If you bring wild mice into the lab, how long do they live when you take away their predators and

01:17:55.500 you insure them food? They live a little bit longer than your laboratory mice, maybe 20% longer.

01:18:02.480 Okay. So they are a healthier mouse.

01:18:04.960 They're a pretty healthy mouse. Yeah.

01:18:06.240 Despite not being bred for being in a lab. Well, I mean, if I gave a handful of these mice

01:18:12.800 to people that were only familiar with laboratory mice, they wouldn't have any idea. They're looking

01:18:18.160 at the same species. First of all, they bite. Secondly, they can jump. When we change mice from

01:18:25.460 cage to cage, we set the cage down, we take the top off, we pick the mice up, we put them in the new

01:18:30.000 cage. You take my wild mice, you take the top off and you got popcorn, you know, they're, they're all

01:18:36.020 over the place. And there's a common test that we do in laboratory mice for sort of coordination and

01:18:43.460 balance, which is called a rotor rod, which is kind of like log rolling for mice, right? And the idea is

01:18:49.740 that this is probably 18 inches off the ground. So they're afraid to fall. So they'll sit there and

01:18:54.840 try to stay on the circulating rod. Try that on a wild moss and just immediately leap off the thing

01:19:03.080 and leap off to your desk and leap onto the floor and they're gone. There's another one that we call

01:19:09.100 called a wire hang, which is just what it sounds. Take mice and you hang them from a wire, like they're

01:19:14.720 dangling a pushup. And you say, how long can they stay before they fall off? So it's like kind of a grip

01:19:20.100 strength test. Yeah. Yeah. You do this to a wild mouse and it doesn't pull up. It pulls itself up

01:19:26.640 onto the wire and it runs off the wire and that's the end of your test. So when I say there's no

01:19:32.360 comparison between them, I'm really meaning that you could take the most sedentary overweight person

01:19:39.180 you could imagine and say, okay, I'm going to compare you to this trained athlete that, you know,

01:19:45.720 and that's the kind of comparison you get. Cognitively, it would be really interesting to

01:19:51.400 see as well. The trouble is wild mice are not used to being around people. So, you know, they're

01:19:58.960 freaked out when you touch them. And so you can't do the same kinds of cognitive tests, which is

01:20:04.520 unfortunate. But on the other hand, this is what you have with the, the other thing is if a domestic

01:20:10.760 mouse wants to get away from you, it jumps back in its cage and sits there, you know,

01:20:15.500 if a wild mice wants to get away from you, it bites you and then it jumps off the table and onto the

01:20:20.240 floor and it's gone. So if you, if you had to do the thought experiment, which is you're going to

01:20:25.600 take a group of wild mice in their environment, remove the predators. So assume that they can live

01:20:33.300 a little bit longer. One group gets a hundred percent of their necessary nutrition. The other

01:20:41.440 group gets 70% of that. Do you believe that the CR group would live longer? No, no, I don't.

01:20:48.960 Do you think they would live shorter? Quite possible. I think probably yes. And I'll tell you

01:20:54.040 why. So this experiment has not been done because it's, it's, it's hard to do, but the reverse has been

01:21:00.680 done. So there've been a lot of studies where people have supplemented the food of animals in

01:21:06.780 the wild. So they don't have to go out and forage as much because I'm going to give them as much as

01:21:12.580 they need to eat every day. So you would expect, okay, now I'm going to get obese mice that are going 0.81

01:21:18.440 to be short-lived, but that's not what you get. You get mice that live longer and they live longer

01:21:26.560 because they're foraging less. They're exposing themselves to less predation. The reason I think

01:21:33.140 that if you restricted animals in the wild, they would live shorter is that the first thing is they

01:21:40.640 would have to forage longer. They would have to take chances to go after food they don't normally

01:21:47.760 go after. They would possibly eat things that they normally don't eat that might be toxic. So my thought

01:21:57.900 experiment is that the animals, if you did this in the wild, if you could somehow control the available

01:22:03.060 food for them, that they would be shorter-lived. The other thing is that there's a couple of things

01:22:08.260 that calorie restriction does that don't seem compatible with a long life in the wild. One of these

01:22:14.820 is that it slows wound healing. The other thing is that it makes animals more susceptible to certain

01:22:23.300 kinds of pathogens. And those two things in the laboratory are not a big deal because they don't

01:22:30.300 get wounded. And we spend a great deal of time and effort to keep pathogens out of the colonies.

01:22:37.340 But in the wild, those are very important causes of pathology and things that you need to work well.

01:22:44.820 So that would be my guess is that they would probably be shorter-lived.

01:22:50.660 Are there any other studies in the animal literature that you think can shed light on

01:22:56.620 this very important question as it pertains to an extrapolation into humans?

01:23:03.760 Well, I mean, there's the human studies.

01:23:06.080 Yeah, right. Before we get to calorie and cronies and stuff like that.

01:23:09.360 No, I don't think so. I mean, you know, when I first came into this and people

01:23:13.340 told me about this phenomenon, the first question I ask, well, if this is so healthy,

01:23:18.860 why do animals in the wild not eat less? And of course, the answer is that the animals that have

01:23:26.900 the genes that have survived for millions of generations out there are the animals that are

01:23:31.500 the best at reproducing.

01:23:33.160 Right. They're not optimizing for the longest life. They're optimizing for the most reproduction.

01:23:37.660 That's right. And so I said, well, of course. So they probably eat more than is perfectly healthy

01:23:43.680 because that helps them reproduce faster. It made perfect sense. And so I don't find it

01:23:49.720 particularly surprising that you get this kind of health because that's, you know, that's not what

01:23:58.580 nature has designed any of us to live as long as possible. You know, that's kind of up to us to

01:24:04.240 figure out how to stay healthy long. Nature was, nature was fine with us when we were living,

01:24:09.160 you know, 35 years. Yeah. Yeah. There's one experiment that was done where they took mice

01:24:14.760 that had been genetically altered so that they lived longer in the laboratory. And they put those in a

01:24:20.200 field exclosure with some normal mice and just came back 18 months later. And the ones that lived

01:24:30.640 longer in the lab were shorter alive, they were almost all gone in the real world. So there's a

01:24:36.260 slight complication to that experiment, which is a follow-up experiment showed that, well, that same

01:24:41.280 mutation, they don't necessarily live longer in the lab. It was one of these unfortunate false

01:24:47.880 results that couldn't be replicated. But, you know, that's the way science works sometimes.

01:24:52.840 So let's turn to the human studies then, which obviously don't have the luxury of the same

01:24:58.500 duration relative to the lifespan of the animal. But what have we learned there?

01:25:03.260 Right. So there's, I think you have four human studies, five maybe. So the first one, I think,

01:25:11.880 was the Biosphere 2 study. But we don't know much about what happened. Most of the people in that study

01:25:18.040 were pretty young. Roy was a real outlier. Roy Walford was, I think, 66 at the start of that

01:25:24.160 experiment, 68 when he came out. But certainly from their blood analysis, they had very good

01:25:31.500 cardiovascular risk factors. Their blood pressure was extremely low. Their blood glucose was extremely...

01:25:37.020 Of course, those were all exceptionally healthy people when they went in. So this was not a random

01:25:41.800 group. The calorie studies are the two best controlled studies in humans. And there was two

01:25:50.740 of them. There was one that was very short term, six months. And then there was another was slightly

01:25:56.600 longer term, which was two years. How many institutions were a part of these two studies?

01:26:02.700 Three institutions were a part of the study. Pennington was one, right?

01:26:05.840 Pennington, Washington University, and then Tufts. And Tufts didn't publish anything out of the first

01:26:13.780 phase of the study, I don't believe. But in the second one, they did. So to me, I'll just give you

01:26:21.080 my bottom line on those studies is that people can't do calorie restriction in that traditional sense.

01:26:27.820 In all cases, the goal was to reduce calorie intake or energy imbalance by about 25%. And they never came

01:26:39.820 anywhere close to actually getting that. In the longer study, I think ultimately the amount of

01:26:46.880 restriction was about 11% to 12% that people were able to achieve over two years.

01:26:54.420 Because these people were in charge of their own nutrition. It's not like the study could afford

01:27:01.440 to actually give everybody all of their food every single day, which would at least give you some hope

01:27:06.900 of doing that if participants could limit themselves to eating the provided food.

01:27:11.440 Yeah. As I recall, I think they provided meals initially for a short term, but they didn't monitor

01:27:20.780 whether the people went and ate anything else as well. And then they were on their own.

01:27:26.040 So it's quite clear that people can't, normal people, you know, there are people that can,

01:27:32.260 but certainly your average person cannot. So in none of those did they achieve anywhere close to the

01:27:38.820 dietary restriction they had hoped to do. So what did they find with what they did achieve?

01:27:44.160 Cardiovascular risk factors, all improved, certainly. Blood pressure was better, lower insulin, lower

01:27:52.000 glucose, but there were some things, lower bone mineral density as well. So it's a mixed bag. And the

01:28:00.260 main thing is, if you look at a dietary restricted mouse, it's got almost no body fat. Both of these

01:28:09.980 experiments, the thing we struggle with is that most people are overweight or obese in the U.S., where these

01:28:16.680 were both done, right? So your control group is not going to be like the Bethesda monkeys. So what that

01:28:25.840 means is if you can only achieve 10% dietary restriction, you're going to get people that are on the verge of

01:28:32.180 being overweight or obese and getting them down to a healthy body weight. And I don't think it's to surprise

01:28:38.640 anybody that that's good for your health. And that's pretty much what they found. They never got

01:28:44.720 people to that extreme leanness that Roy Walford and the people in the biosphere had, or that the

01:28:53.520 subsequent, the cronies have. So I think you could generally say from the calorie studies that, yes,

01:29:01.840 reducing your food intake had lots of benefits, had some possible negative effects in terms of bone

01:29:11.480 mineral density, had some negative effects in strength loss, although not if corrected for body

01:29:18.300 weight. But yeah, generally beneficial. But again, take somebody that's on borderline overweight,

01:29:25.840 reduce them to a healthy body weight. I don't think any physician, it wouldn't have to be a

01:29:30.960 specialist like yourself. Any physician, I think, would say, yeah, okay, where's the news? So that's

01:29:38.700 what I take away from that. Now, the other study is the study of the cronies. And these are people

01:29:45.360 that belong to a society called the Calorie Restriction Society that have taken the rodent work

01:29:53.660 and assumed that is going to make us healthy longer. And they really have restricted themselves

01:29:59.520 like the, we really do to mice. And they also have good, very good cardiovascular risk factors,

01:30:09.000 less inflammation, they're probably going to get less cancer, but they have low bone mineral density,

01:30:16.540 negligible sex hormones, whole suite of things, no muscle mass to speak of. I've spoken at a couple

01:30:24.420 of their conferences and they're always exhorting one another to exercise more because they have

01:30:30.140 trouble with this degree of restriction, keeping any muscle mass at all. But it's a struggle because

01:30:35.980 they don't really have the energy. They don't have the energy. Yeah. Yeah.

01:30:39.660 And these people typically have what, how much of a BMI, Steve? These are people that are 17,

01:30:44.560 18 BMI at this point? Yeah, I'd say 17 to 20. Yeah. 0.64

01:30:48.700 The interesting thing is in that society, if you look around the room, I would say probably

01:30:53.940 30% of the people are actually doing it like that. The others are maybe aspiring to do it,

01:31:00.380 but not quite making it. They look more like an average person would look. But yeah, that's the

01:31:08.040 problem. And I'm not sure now that all these other diets are starting to come out, how many people are

01:31:12.860 still sticking with that? Because I haven't, I've kind of lost track over the last few years

01:31:17.340 of what's going on with those people. The other thing, they have very low thyroid hormone. So

01:31:24.180 they're cold all the time. So one of the things I noticed at a comfortable room, everybody would be

01:31:29.440 wearing a jacket that was really BMI of 18 or so. And we don't actually know the impact of this on

01:31:37.100 long-term cognition, do we? I think the, on cardiovascular and cancer, it's pretty clear that

01:31:42.320 they will have a benefit. Not clear with respect to dementia, not clear with respect to immune

01:31:47.900 function, and certainly not clear with respect to the diseases of frailty. In fact, I should say it

01:31:54.860 is clear with respect to the diseases of frailty. They're much, much more susceptible.

01:31:59.100 Yeah. I think that's true. The cognitive part, I mean, in the calorie study, they did a little bit of

01:32:05.960 cognitive research. But again, these were people that weren't being restricted to the same extent.

01:32:12.780 And the people in that society are very eager to be studied. The problem is,

01:32:17.640 this is an uncontrolled experiment. My guess is before they started the calorie restriction,

01:32:22.820 they were not your average person with your average person's health habits.

01:32:27.080 Yeah. Yeah. This is the poster child example for healthy user bias in epidemiology. We can learn

01:32:32.940 virtually nothing from that without randomization. In terms of the immune system, though, I will have to

01:32:38.260 say that I did ask a lot of people at the conference, how often do you get colds or the flu?

01:32:46.160 And they say they don't. And I tend to believe them because I've never met a group of people that are

01:32:52.000 fanatically attentive to their own health. Like if I said, what's your BMI? They could tell me

01:32:58.800 to three decimal points and then say, well, do you mean in the morning or in the afternoon?

01:33:05.180 You know, so when they tell me they haven't gotten a cold in five years, I believe them.

01:33:10.220 Fair, fair enough. So this highlights an important point, right? Which is,

01:33:14.440 one, it's a very, very, very rare subset of the population that is going to be able to adhere to 30%

01:33:21.740 caloric restriction every minute of every day. And I would argue that even if you could,

01:33:31.480 the quality of life might be not justified to try it off. Isn't there a joke that says caloric

01:33:37.600 restriction will lengthen your life and it will feel like it or something to that? Yeah.

01:33:43.100 Yeah. What is it?

01:33:44.240 But I think, you know, for these people, I don't think they perceive it. I don't think they miss it.

01:33:50.100 No, no, no. My point is you couldn't extend, they are the subset who can do that.

01:33:55.200 Yeah.

01:33:55.680 To try to make that the solution for the rest of us who are interested in some form of Giro protection.

01:34:03.120 It's an on-starter. Yeah.

01:34:04.920 Right. Constant caloric restriction isn't the answer. So we now look to other things and

01:34:09.900 you've maybe heard me talk about this, but I kind of have this framework, right? That says,

01:34:13.800 on the one hand, we have this thing called the standard American diet,

01:34:16.880 which is sort of the cesspool of nutrition we all live in. So that's the environment where food is

01:34:22.920 infinitely abundant, infinitely cheap, infinitely palatable, and infinitely transportable. So meaning

01:34:30.240 it's so processed that you can actually take it with you anywhere. And it's hard to escape the

01:34:38.460 gravitational pull of that. So we're all sort of in this orbit around the standard American diet.

01:34:44.620 And there's basically a handful of ways out. So I think one avenue out of that is time-restricted

01:34:53.200 feeding, where you start to say, well, look, I'm not going to restrict what I'm eating. I'm not going

01:34:59.220 to engage in any form of dietary restriction. I'm just going to limit the window in which I expose

01:35:04.740 myself to this toxicity. So I'll not eat for 16 hours, but I will eat for eight hours. And you can

01:35:11.540 obviously make that window narrow and narrow. Then there's what I call dietary restriction. 0.79

01:35:15.200 You and I use these terms a little differently, although I know what you're meaning when you say

01:35:18.240 it. When I refer to dietary restriction, I mean no attempt at reducing the content,

01:35:23.920 but rather changing the mixture or quality. So dietary restriction, which is probably what most

01:35:28.980 people think of when they think of a diet, like a paleo diet, a vegan diet, a keto diet, a low carb diet,

01:35:34.880 they're not explicitly telling you to eat less. They're just telling you to not eat in certain

01:35:39.680 things. So those two become, I think the mainstay of how most people are trying to escape the

01:35:47.080 gravitational pull of the standard American diet. And then you can actually talk about

01:35:51.480 intermittent forms of fasting. And that can be complete, such as, hey, I'm not going to eat

01:35:57.440 anything. I'm just going to have water for three days every month or every quarter. And they can be

01:36:02.440 partial, sort of like the fast mimicking diet where for five days you consume, you know, 750 calories.

01:36:09.780 When you think about that entire landscape, where do you think we have the best insight about the

01:36:15.620 health benefits? Well, first of all, these are all pretty new ideas. And I don't think they've had a

01:36:22.300 lot of empirical testing at this point. And the empirical and testing that they have had has mostly

01:36:29.500 been in people that already had some health issues that were diabetic or pre-diabetic or something

01:36:34.640 like that. However, the logic of it is pretty compelling. And this is something we have learned

01:36:41.640 from the mice. You know, from the mice, in the rapamycin studies, we've learned how suppressing

01:36:49.020 this gene called mTOR can have multiple health benefits. And now we know that it doesn't take

01:36:57.780 that much fasting to also suppress mTOR. So we now kind of have an idea. So, you know,

01:37:06.640 one of the things we should probably mention is that the people that were studying mice and rats

01:37:11.160 years later started noticing, well, wait a second. And I noticed this when we would go to feed these

01:37:16.820 animals, they're right there. They're doing pull-ups on the cage, waiting for you to get

01:37:21.560 the food. And, you know, literally within a half an hour, all their food is gone. And what we never

01:37:28.060 really thought about until recently is, wait a second, maybe it's the timing that's the important

01:37:34.800 thing. The fact that they're fasting for 23 hours a day or 23 and a half hours a day, maybe that more

01:37:42.020 than the total consumption or as much as the total consumption is doing it. And now we kind of have

01:37:47.880 a molecular mechanism for understanding how a period of fasting might have benefits. It might have

01:37:56.120 short-term benefits. I mean, I think that's one of the really interesting things is that these short-term

01:38:01.480 fasts, whether they're in mice or humans, seem to have multiple benefits. I mean, one of the,

01:38:10.180 I think one of the most groundbreaking studies was by Jay Mitchell, unfortunately, who just passed away

01:38:16.280 a year ago. I mean, yeah. Yeah. Yeah. Terrible, terrible bicycle. But he showed that if you fasted

01:38:22.520 a mouse for two or three days, they recovered from surgery so much faster. Well, actually, Steve, I

01:38:28.260 mean, we should double click on that a little bit because it's not just that they recovered from

01:38:31.280 surgery. They recovered from a lethal injury, right? There's one experiment where I think if I'm

01:38:37.700 thinking of the right experiment, it was, they took a group of mice that were constitutively

01:38:43.160 calorically restricted their entire lives. They took another group that were fed ad-lib their whole

01:38:47.900 lives. And then they took another group that were ad-lib fed, but I think three days prior to the

01:38:52.820 surgery were severely calorically restricted. So each of them then had the same procedure, which was

01:38:59.180 a laparotomy with a ligation of the femoral arteries for a period of time and then a reperfusion.

01:39:04.540 So what, you know, for the folks listening, what that means is you clamp off all the blood

01:39:09.500 supply to the lower part of the leg. And then, you know, basically just before the animal's about

01:39:13.700 to die, you let it, you let the blood flow again. But because of all of the ischemic damage to the

01:39:21.360 tissue, all the tissue damage due to no oxygen, you create such an injury to the animal that I believe

01:39:27.420 all of the ad-lib animals died from that. But yet the two groups that were calorically restricted,

01:39:34.000 one its entire life and one just for three days survived. Suggesting that just that period of

01:39:41.660 caloric restriction could produce a similar benefit. Now I could be a little wrong on the numbers,

01:39:46.040 but that was sort of the gist of my memory. Is that correct?

01:39:48.780 Yeah. Well, what he did, it actually cut off blood supply of the kidneys.

01:39:53.400 And then he had another one that they did the liver. Same result though. And you're exactly right.

01:39:59.780 They did these ones that have been calorically restricted their whole lives, the ones that

01:40:03.360 have been, that were ad-lib, and then the ones that have been fasted for, they did some that have

01:40:09.760 been fast, restricted for a few weeks. And then some that had been just fasted, water only fast

01:40:15.040 for two or three days. That's a big fast for a mouse.

01:40:18.760 It is a big fast. That's absolutely right. And they did much better. You're right. I don't remember

01:40:23.720 if all of the controls died, but if not, almost all of them did. And the ones that were restricted

01:40:31.440 lifetime or for two or three days, I think none of them died. So you're right. It's, yeah. When I

01:40:37.520 said a surgery, I guess I was thinking about it from a mouseologist standpoint where a lot of our

01:40:42.800 surgeries don't turn out so well. But yeah, this wasn't a minor surgery that you expected everybody

01:40:49.080 to recover from it. Right. This wasn't a little gallbladder. They really were expecting most of

01:40:52.480 the mice were going to die, and they did. So yeah, I mean, that kind of, I think, it changed my

01:40:58.820 thinking entirely about dietary restriction. And you're right. We use these in different terms.

01:41:04.680 Initially, it was called dietary restriction because they just restricted the amount of diet.

01:41:08.720 But then after they decided it was calories that counted, then they started being called calorie

01:41:14.140 restriction. And now probably not exactly calorie. So I don't know. Food restriction, maybe we should

01:41:21.520 call what they do to the mice at this point. Well, what's your take on the role of the

01:41:26.340 macronutrients here? And I'll pass it to candidates to consider. The first being a subset of amino acids,

01:41:34.120 whether it be methionine, tryptophan, leucine would be candidates to consider. And then other things such

01:41:41.600 as sugar. Again, the Wisconsin half of the monkey experiment certainly suggested that a reduction

01:41:50.160 in sucrose, perhaps independent of calories, could have played a role. But it's difficult because we

01:41:55.580 can't disentangle it from the weight loss and other things. But what do we know about amino acids and

01:42:01.200 their role? We certainly know that mTOR, which you brought up a moment ago, is an amino acid sensor.

01:42:06.420 So how do you think that fits in? Independent of calories, perhaps?

01:42:10.100 Well, I think we need to work that out, you know, because there are these diets around. And there

01:42:15.060 are diets that say, oh, what you want to do is you want to eat as many carbs as you can, and as

01:42:19.300 little protein and fat as you can. And there are others that say the opposite. I don't think the

01:42:25.420 animal work is going to tell us a lot about that. I think we have to try to figure out how to do the

01:42:32.440 experiments in people. We have to do it in healthy people. Because I think if we want to make sick

01:42:40.240 people less sick, that's great. We should be doing that. But a lot of people that are healthy want to

01:42:45.000 know how to stay healthy. And I think that we can't do these things long term, because what if

01:42:50.540 you're in one that's turning out to be really bad for your health? What we need is we need some

01:42:55.480 biomarkers, which you mentioned before. We need something so we can do an experiment of a few

01:43:01.600 weeks or a few months and have the answer long term. And we need to do it in people of different

01:43:07.980 ages as well. You know, the thing that we didn't talk about, the calorie strategy, so those were done

01:43:14.380 on people who were basically in their late 30s. And what's good for them is not necessarily good for

01:43:20.260 what people in their 60s might want to do. You know, one of the things I think that the

01:43:25.760 Interventions Testing Program has demonstrated that's shocking is how late in life you can start

01:43:32.040 some kind of intervention and still have a dramatic improvement in health. And that to me has really

01:43:39.860 major implications for people, right? Just because you're 50 years old and you've never done any

01:43:46.840 exercise and you've eaten a terrible diet, doesn't mean you can't improve your health a lot. Because

01:43:52.380 I think a lot of people feel that. I've done this my whole life, so what's the point in doing it now?

01:43:59.120 I'm curious for you, you know, I get to ask you a question occasionally here. What is the average age

01:44:06.480 of people that come to your clinic? Are they people in their 30s or 40s or 70s or 80s?

01:44:12.640 The median age in our practice is high 30s. Yeah. Would be median and mean is probably a little

01:44:24.980 bit higher. But range is 29 to 79. 29 to 82 maybe is the range. Right. So that makes sense. So that's

01:44:36.780 about the time in life where people start realizing they may not live forever and start making some

01:44:44.080 changes potentially in the way they live their life. You know, I have a dramatic memory of when I

01:44:50.760 first detected aging in myself. What was that? That was, I probably was 30 to 32 maybe, but it was during a

01:45:01.900 basketball game. And I was always the quickest person on the floor. And I was used to blowing by

01:45:10.760 people. And suddenly this person blew by me who was much bigger than me. And I was used to, if anybody

01:45:18.140 was going to be as quick as me, it was going to be somebody as small as me. And I thought, gosh,

01:45:22.280 that had to be an accident. You know, and then he did it again. You know, and then he did it again.

01:45:26.400 And I realized I lost a step. This is what they mean by aging. I have lost a step. There's,

01:45:33.560 you know, and if you're a professional athlete, of course, you're tested much more often. And you

01:45:37.640 probably notice this much earlier than I did in a casual neighborhood basketball game. But it was,

01:45:45.240 it was a shocking moment to me because before then never entered my mind that my body was going to

01:45:51.540 change in a way that would make it less good at things that used to do.

01:45:56.720 Well, speaking of human longevity, Steve, what do you think is the best explanation for the sex

01:46:01.160 difference between men and women? In the United States today and much of the developed world,

01:46:06.440 it probably accounts for about two years of difference, doesn't it?

01:46:10.040 More like five.

01:46:11.420 Is it that much? Wow.

01:46:12.580 Yeah.

01:46:13.600 What's our best attribution?

01:46:15.620 Well, it's a really interesting problem. And let's talk about, I think, some myths about that difference.

01:46:21.000 It's, it's not that women survive better in an old age. They do, but they also survive better when 0.99

01:46:27.560 they're infants. And they also survive better when they're in their twenties and in their thirties and

01:46:32.720 their forties. So they survive better at every age and they survive better when times are good and

01:46:38.380 during epidemics and during famines. And so there's something about their biology that allows

01:46:45.780 them to survive better. And it doesn't seem to depend on conditions. That's very different.

01:46:51.000 It's different from a lot of animals where it depends on the diet. It depends on the circumstances.

01:46:55.560 We don't know any circumstances in which men survive better than, than women, even prematurely 1.00

01:47:02.000 born infants. Being a male infant is a risk factor for dying if you're a preemie. So there's some

01:47:08.700 robust feature of human biology at play here. And unfortunately, we don't really know what it is.

01:47:17.560 We don't know. Is it sex hormones? Is that something that happens before birth that we can't do anything

01:47:25.640 about later? There's, there's a little bit of weak, but I think maybe a provocative evidence. There's at

01:47:33.560 least two studies showing a major increase in longevity for men who were castrated for one reason or

01:47:40.740 another. Is that relevant? These were unique populations and maybe that has no relevance

01:47:46.640 whatsoever, but that was kind of put the onus on sex hormone, right? On the other hand, there's

01:47:55.600 the hormone replacement work in human females, which suggests that, well, maybe replacing those hormones 0.98

01:48:04.220 isn't such a great idea. Although I think we now don't find that to be the case, right? I mean,

01:48:10.040 I think the, I think basically every conclusion of the original women's health initiative has been

01:48:15.180 turned over, right? No, I don't. I would say that's, that's, that's not the case, but the key factor for

01:48:21.760 the women's health initiatives is the women didn't start doing it until 10 years after menopause

01:48:26.320 on average. And so there have been shorter term for women that start replacement therapy earlier

01:48:32.860 and then stop it, that there may be this window in which it's been, but of course it depends on your

01:48:38.880 family history, on all kinds of things. Yeah. But my point is there was no increase in mortality.

01:48:44.920 I think if you really scrutinize the WHI data correctly, even the, the most headline grabbing

01:48:52.140 finding, which was that the women in the progesterone and conjugated equine estrogen group

01:48:58.700 had a greater, 25% greater risk of breast cancer. I mean, I think we now understand that that was a

01:49:05.260 very misleading finding. Yeah. I mean, there were several things that they, they, they were much

01:49:10.020 more, they're more likely to have a stroke, but you're right. The overall mortality rate at the time

01:49:16.140 that they stopped the study because of the blood clots and the strokes, and there was no difference.

01:49:22.140 You're absolutely right about that. There was no difference in mortality and you could have

01:49:26.200 made the case that they shouldn't have stopped it at that point.

01:49:30.760 And it's interesting on the castrated literature, the obvious can one, you know, the first or Occam's

01:49:36.280 razor view of that would be, well, there's something about testosterone. It's not so much that the men

01:49:40.820 who are castrated are getting estrogen and progesterone. If you castrate them, they're actually

01:49:44.620 going to have no estradiol versus the estradiol they would have if they could keep their testosterone.

01:49:48.900 But of course that kind of flies in the face of the testosterone replacement data, which

01:49:54.460 say, well, actually it doesn't seem to impact mortality either way, at least outside of two

01:49:59.140 or three years. But then that comes to a point you made earlier. Maybe it's something that

01:50:03.640 happens early in life with high exposure. And yeah, I mean, to me, the telling data points

01:50:10.300 are that the women survive better from ages zero to five, you know, that suggests to me that there's

01:50:17.580 something already in place and it probably may not have anything to do. I mean, let me point out

01:50:24.300 the two testosterone studies are very weak. They were not done with this in mind. They were done post hoc

01:50:31.460 and there's a lot of complications. So I don't put a great deal of stock in those. It's just

01:50:37.340 provocative. And also the, I mean, the difference in longevity was something like 20 years in both of

01:50:43.060 them. So it wasn't a trivial difference. I can certainly understand why men would have a lower 0.59

01:50:48.420 or a higher all-cause mortality when you factor in a couple of things. One is behaviors.

01:50:55.200 I mean, you know, if I compare my sons to my daughter, it's literally like they wake up every

01:51:03.160 day trying to figure out how to hurt each other and hurt themselves. And that, I mean, I'm actually

01:51:08.660 very fascinated by that, Steve, because I don't understand where that is in their genes. Like

01:51:14.460 you would think, well, that has to be sex linked, right? But, you know, when you look at men who are

01:51:20.040 double Ys, so, you know, there are some men who don't get an X chromosome, they get two Ys,

01:51:26.500 they turn out to be no more aggressive than a standard XY. So it's not something as just as 0.51

01:51:33.220 simple as like, well, that Y chromosome has, it's going to be a little bit more nuanced than that. 0.94

01:51:37.580 But, and I think about the dumb things I did growing up. Like there were literally times I was

01:51:42.380 engaging in such stupid behavior, like into my late teens, that it's a miracle I'm sitting here. 1.00

01:51:48.420 At least when you almost died. Well, I guess we could argue that was kind of, 1.00

01:51:52.200 maybe not the wisest behavior, but. Oh, you don't have any clue as to what the

01:51:56.500 really dumbest stuff that I did. We used to, I used to be in a group of friends 0.97

01:52:00.500 that hunted with bows and arrows rabbits when I lived in Florida. And we would take our bows and

01:52:08.100 arrows and go into a vacant lot in the middle of the night when it was dark and shoot them straight

01:52:12.980 up in the air and then stand around to see where they would come down. So they could have come

01:52:17.920 down straight through the top of our heads. And you look back and you go, yeah, what was going on?

01:52:24.600 It's a miracle over here.

01:52:25.860 Yeah. I say that I call this testosterone dementia. And I think probably most men go

01:52:30.520 through it at some point, you know, in their, probably in their adolescent years, right?

01:52:36.420 That's what I did.

01:52:37.580 When I was in high school, one of the things we used to do, there's this huge train in Toronto

01:52:41.820 called the Go Train. And it was the above ground transit train. And we used to play this game. As

01:52:47.540 soon as you got off it, you would dive underneath it and see who could lay the most coins on the track

01:52:53.660 and then get out such that when it started rolling, you'd get whoever had the most flattened coins would

01:52:59.140 win. Yep.

01:53:01.040 Can you believe that for a moment? Like it's just hard to believe that a subset of our species could

01:53:07.820 be so stupid to do something like that. Yeah. We would also shoot arrows at one another on purpose 1.00

01:53:14.720 and dodge them. And that ended because I was the first one that didn't dodge well enough. And I got

01:53:20.460 an arrow stuck in my leg, at which point our parents investigated what we'd been up to. And that was the

01:53:26.440 end of that. Yeah. And like, do you think in the history of the, how many billion people have lived?

01:53:33.440 Like 8 billion? Oh, there's almost 8 billion alive now. Okay. So probably 800 billion. Yeah. Yeah.

01:53:39.480 Yeah. So, so when you think of all the people that have lived, half of them being women, do you think

01:53:44.400 there is one example of a woman doing something so stupid? I don't know. I can't imagine. I can't 1.00

01:53:51.160 imagine. Yeah. Yeah. Yeah. Yeah. But that's not all of it, right? That doesn't explain the infant

01:53:55.720 mortality in the NICU, right? Right. And it doesn't explain the lower influenza deaths. It doesn't

01:54:02.760 explain the lower. I mean, COVID was, you know, if you, if you look at the COVID, so women are dying 1.00

01:54:09.540 at about 45%, men about 55%. That that's pretty much what it looks like for the flu. And I mean,

01:54:16.600 you, if you look at all the major causes of death, women die at a lower rate, even if you adjust for

01:54:23.760 age. So you take age out of the equation than men for all of them with the exception of Alzheimer's

01:54:29.740 disease, which is, is really interesting to me. And it makes me actually, my private hypothesis that

01:54:39.260 I don't think I've ever said publicly before is I think Alzheimer's disease is going to turn out to

01:54:45.060 have an autoimmune component because that's the kind of thing that women seem to be more prone to 1.00

01:54:51.560 than men is some of the autoimmune diseases. So there's a few possibilities here. There's one

01:55:00.340 idea that it has to do with the fact that women have a redundant set of genes on their X, their 1.00

01:55:06.080 second X chromosome, right? So if they have a defective gene or genes on one of the X chromosomes,

01:55:13.580 the other one can compensate for it to a certain extent.

01:55:16.840 If that's true, I don't know if we have enough men with Kleinfelters out there, but 1.00

01:55:21.020 that would be an interesting comparative analysis, right? Just for folks listening,

01:55:25.820 men with Kleinfelters, instead of having X, Y have X, X, Y. So they would also have that same

01:55:31.580 redundancy of genes.

01:55:34.080 Right. But some, some of those redundancies might, might be bad because Kleinfelters don't, 1.00

01:55:39.820 those people don't live long for certain. I don't know how short live they might be,

01:55:43.880 but they're not longer.

01:55:45.020 I didn't realize their lifespan. I mean, they certainly have a unique phenotype,

01:55:48.460 but I didn't realize they lived shorter.

01:55:50.360 Yeah.

01:55:50.820 But that's interesting because women with Turners, right, which is X, which is an aneuploidy of X 1.00

01:55:56.780 only, one X, they definitely live shorter, don't they? 0.91

01:55:59.860 Right. So that's one idea. And a little bit of support for it is if you look at,

01:56:07.720 so one of the X chromosomes typically gets inactivated in each cell and it tends to be random.

01:56:13.320 As people get older, as women get older, there tends to be a bias in one or the other X chromosome.

01:56:21.220 So one is inactivated more than the other.

01:56:25.020 Early in life seems to be random.

01:56:27.380 Half of the cells, your paternal X is inactivated.

01:56:30.520 Half of it is your maternal X. 0.55

01:56:33.020 But over time, you get a kind of a selection for one or the other.

01:56:37.520 Maybe that might be it.

01:56:38.940 The other thing is that there might be an issue of compatibility of the mitochondrial genome

01:56:45.480 and the nuclear genome.

01:56:47.740 Because mitochondrial genomes only get passed from female to female.

01:56:53.220 From female to female is the only way they get passed through generations, right? 0.99

01:56:57.260 So you'd expect there would be a lot of selection for excellent compatibility.

01:57:02.460 Now, the mitochondria that end up in males are at a dead end.

01:57:06.540 So it may be that the male nuclear genome is just not as compatible with the mitochondrial genome

01:57:14.860 as the female genome. 1.00

01:57:16.560 So that's the other possibility.

01:57:18.800 I find both of those really interesting.

01:57:22.120 And what we really need to know about is we need to know a lot more about this NX inactivation.

01:57:28.280 Because it's not total.

01:57:29.480 Not every gene on the second X is inactivated.

01:57:32.740 Only some of them.

01:57:33.680 But the other thing is the Y chromosome is...

01:57:38.000 This has got to be the first time in the history of medicine

01:57:40.800 that men get less attention for anything than women.

01:57:44.500 But we've always assumed the Y chromosome is about sexual characteristics.

01:57:49.500 But we now know there are at least nine genes on the Y chromosome

01:57:52.880 that are expressed in every tissue.

01:57:54.880 We have no idea what they're doing in all those tissues.

01:57:57.780 But maybe they're doing something that's not so good for us in some of those tissues.

01:58:03.900 I find both of those ideas, Steve, incredibly fascinating.

01:58:07.380 I'd never thought of either.

01:58:10.540 The mitochondrial incompatibility is a brilliant one.

01:58:12.880 I'll have to think for a moment about what experiments one could do to test that.

01:58:17.540 But on the other one, on the dominant X, it would be interesting to follow women 0.61

01:58:24.260 and identify ones who partition more into a dominant maternal X

01:58:29.840 and then a dominant paternal X.

01:58:32.360 In the women who have a dominant paternal X, presumably that X is better than the other X. 0.82

01:58:40.020 And then I would like to see if there's a difference in the longevity of that father 0.82

01:58:44.200 versus, and it's not a random experiment, so it sort of sucks,

01:58:49.080 but is that a better surviving male than another male that's otherwise comparable?

01:58:54.740 That's one way I would try to get at that.

01:58:57.160 This is a really intriguing area of research and something that we could do now that we couldn't do a long time ago.

01:59:05.520 The limitation, of course, because it's humans, is that we're kind of stuck with doing that in blood,

01:59:11.460 and we don't know if the same thing might be going on in the brain or the liver.

01:59:16.240 Although, again, I guess from autopsy studies, we could probably figure that out now.

01:59:22.080 But we do have the tools now to do a lot of this.

01:59:26.920 We could do muscle biopsies.

01:59:28.480 Is it the same in the blood and the muscle?

01:59:30.680 That's a possibility.

01:59:32.700 So, you know, my feeling is that we have yet to really explore these sex differences in any depth,

01:59:43.000 and that we may end up having somewhat different therapeutics in women and men

01:59:49.820 once we start looking into exactly how these things work out between the sexes. 1.00

01:59:55.840 Now, the ITP vary consistently, whether you talk about its home-run drugs like rapamycin

02:00:02.360 and other drugs like recently 17-alpha-estradiol.

02:00:06.960 They disproportionately favor the male mice over the female mice.

02:00:10.560 Do you believe that that is simply the result of the fact that they have a higher bar to clear with the females?

02:00:18.080 Possibly, because in the ITP, the female mice live longer. 0.98

02:00:24.500 So it's the longer-life sex that's having no effect, and shorter-life sex is having the bigger effect.

02:00:31.380 A really interesting one is rapamycin, because, you know, in rapamycin,

02:00:35.560 and the sex bias is very, in longevity at least, is very dose-dependent.

02:00:41.920 At the lowest dose they've done, the effect is substantially bigger in females than in males.

02:00:48.560 And that difference gradually goes away as you get it to a higher and higher dose.

02:00:53.700 And in the highest dose that anybody has used, which is not in the ITP but in another study,

02:01:00.060 males had a big effect and females had no effect. 0.87

02:01:04.020 So the idea is maybe you've overdosed the females at that stage.

02:01:08.780 Now, do you recall that in the ITP, the females had a much higher plasma level than the males,

02:01:17.180 despite consuming the same amount?

02:01:19.700 And I don't remember if Rich had an explanation for why that was the case.

02:01:24.000 Do you?

02:01:24.780 No, I don't think they have an explanation.

02:01:26.800 That could explain the difference, right?

02:01:29.060 It could be that it wasn't that at a lower dose, females are living longer because it's a lower dose. 0.99

02:01:35.980 It's because they have a higher plasma concentration.

02:01:38.380 And maybe that's the gap that vanishes at a high enough dose.

02:01:41.180 I don't know, because I don't know what the kinetics were in the other study.

02:01:44.320 In what they've published, it wasn't related to blood levels of rapamycin or its metabolites.

02:01:52.180 Something else is going on.

02:01:54.480 But those things get metabolized very quickly, and there's lots of downstream things that could be.

02:02:01.860 But again, I think that mice are a particularly bad place to look for these sex differences.

02:02:10.040 And that's because, as I said, in the ITP, the females live longer. 1.00

02:02:14.940 But if you look at all the mice studies together, there's mice studies in which males live longer, mouse studies in which there's no difference, mouse studies in which females live longer.

02:02:25.660 And they're all over the place.

02:02:27.040 And it's not a genotype thing.

02:02:29.400 Because I once looked at 30 black six mouse studies, and you found the same range from males living 25% longer to females living 25% longer.

02:02:41.160 And we don't know what that's a result of.

02:02:43.780 Is it something in the diet?

02:02:45.680 Is it something in the bedding?

02:02:47.860 Who knows?

02:02:48.660 But the other thing is that mouse sex chromosomes are quite a bit different than human sex chromosomes.

02:02:57.740 Just to give you an example, some genes on the X chromosome do not get inactivated on the inactive X.

02:03:04.780 About 15%, you know, you get expression in both sexes.

02:03:08.720 In mice, that's about 3% to 4% of the genes on the X chromosome get inactivated.

02:03:15.360 There are also genes on the Y chromosome in humans that are not on the Y chromosome in mice and vice versa.

02:03:23.260 This, again, is one of these things where I think of this as looking at the world through one eye.

02:03:29.080 We have one comparison with humans now.

02:03:31.760 It's mice.

02:03:32.960 And just like you don't have much perspective when you close one eye, I don't think you have much perspective when you have one comparison.

02:03:40.460 And that's kind of what we have now.

02:03:42.800 Why do you think it's been, I don't want to say so difficult because I don't know that we've tried, frankly.

02:03:49.100 But why do you think there hasn't been a greater effort in identifying better biomarkers of aging?

02:03:55.600 Or do you think that there has been an enormous effort and it's just been too difficult?

02:03:59.320 But for example, we don't know how long one as a human needs to fast to achieve a significant inhibition of rapamycin to extract the benefits that we think are there.

02:04:16.320 Why is that?

02:04:17.060 I would say that of your two alternatives that we haven't tried hard enough or maybe we've tried hard enough and haven't found anything, I would say it's the latter.

02:04:27.780 Because in the 1990s, the NIA put, I think, $100 million into developing biomarkers of aging and it came out with nothing.

02:04:35.900 But that may have been that we just didn't have the right tools at that point.

02:04:41.220 I think we're really on the verge of something big here so that we can have biomarkers that will tell us exactly this kind of thing.

02:04:51.460 And do you think these biomarkers will be in the metabolome, in the proteome, in the epigenome, all of the above?

02:04:58.280 Yeah, I think they're likely to be all of the above.

02:05:01.940 And right now, the hottest one is in the epigenome because that's looking better and better.

02:05:08.560 And it seems to work well.

02:05:09.920 Are you optimistic?

02:05:10.440 I mean, I've seen how easy it is to manipulate those and I find it completely uninteresting.

02:05:15.500 And that's going to alienate a lot of people that are listening to this because I'm the naysayer on that.

02:05:20.760 But Steve, when I look at those data, I'm not remotely impressed.

02:05:24.400 And by the way, I've done the experiments on some of my patients, right?

02:05:27.520 You, you know, you measure their epigenetic age on day zero.

02:05:31.980 They do a three-day fast.

02:05:34.080 You measure their epigenetic age.

02:05:35.820 It goes down by 10% or more, frankly.

02:05:39.480 Have you really learned anything?

02:05:41.340 And then a week later, it's back to normal.

02:05:44.580 I don't know what that's telling me.

02:05:46.460 Well, it may be.

02:05:47.220 So I'm actually fairly impressed by the epigenetic data, but maybe it's not going to work in the short term like that.

02:05:53.720 This is maybe something that tells you something over the course of years, but not over the course of weeks or months.

02:06:00.280 My only point there is that it's very sensitive to what's happening in the moment, right?

02:06:05.940 And so when I look at a lot of these aging clocks and I look at the inputs, I think to myself, these are very easy to manipulate.

02:06:15.540 What was your vitamin D level on this day?

02:06:17.740 What was your glucose level at the moment of that blood test?

02:06:20.520 I mean, these things are so easy to manipulate and they have so much volatility over time that I don't find them to be clinically quite useful.

02:06:30.000 Well, they may never turn out to be clinically useful because it may be that they're integrating things over a timescale that's not clinically meaningful.

02:06:40.380 I think the likelihood that we're going to find something in the proteome and the metabolome is higher.

02:06:48.320 I mean, something that's therapeutically useful just because those things really change rapidly, you know.

02:06:57.300 And if we want to know if you fast six hours or you fast 12 hours, I think what you're going to look for there is changes in gene activity.

02:07:07.020 And that's going to be in the proteome or in the metabolome.

02:07:11.800 The thing is, it's going to be computationally complex.

02:07:15.340 Now we have all these tools for doing computationally complex things, but they're not cheap tools.

02:07:21.080 And so I don't know how long before they'll be in the clinic where we can afford to do this in people en masse.

02:07:28.200 If I were czar for a day and could marshal the resources for the Manhattan Project on longevity, this would be one of the departments, right?

02:07:39.740 Like this would be, you know, if you had a billion dollars to put towards a Manhattan Project of longevity, I feel like a quarter of it would go into this problem.

02:07:49.620 Because it, again, if we're interested in longevity, presumably we're interested in human longevity.

02:07:56.040 And if we're interested in human longevity, we don't have a hundred years to come up with the answer.

02:08:01.380 So we have to come up with markers that are better.

02:08:04.960 Well, and now we have the tools to do that.

02:08:07.340 Every year, the tools, the computational tools, the analytic tools, you know, if you can detect, you know, 3,000 different proteins in your blood,

02:08:17.080 then you're much more likely to detect something that's really, really meaningful.

02:08:22.380 And so those things are all happening.

02:08:24.360 Of course, they could happen more if there were more money invested in them.

02:08:28.880 I think that's the big issue, Steve, personally.

02:08:31.100 I think this is not commercially interesting enough.

02:08:33.640 And I think that that's why it hasn't gotten the attention.

02:08:36.480 I mean, I think the diagnostics space is a lousy space, right?

02:08:40.460 Like if you're a venture capitalist and someone comes up to you and says, I've got a new diagnostic test.

02:08:45.100 I mean, that's nowhere near as interesting as I have a new therapeutic model.

02:08:49.320 And that's why I feel like this could only really occur in kind of a Manhattan project or a heavily funded government project.

02:08:56.140 But I just don't.

02:08:57.480 And I use the term Manhattan project, meaning an entity that is so large commercially that they understand that this is an important tool that needs to be developed in research to foster the development of molecules down the line.

02:09:11.620 Yeah, it's an interesting, you know, I mean, Craig Venter tried to do that.

02:09:15.780 And that corporation company went nowhere.

02:09:18.840 Yeah, I have thoughts on that I can't share publicly, but yeah.

02:09:22.880 But you're right.

02:09:24.660 I mean, I think the key's got to be there.

02:09:27.200 This is not magic.

02:09:28.600 You know, there's stuff going on in the body.

02:09:30.240 I think the blood, because it courses through everything in the body, is going to have clues to what's going on everywhere once we learn how to read those clues.

02:09:41.340 And I think part of the problem is that we're not, you know, there's a very small group of people that are interested in making other people live longer.

02:09:49.820 But most of the time, it's trying to prevent them from getting a specific disease.

02:09:53.620 There's a lot more money that goes into obesity, I think, than that goes into longevity.

02:10:00.220 And it's hard to say that it's not well-spent money because obesity is the huge problem.

02:10:06.400 You made a very famous bet with Jay Oshansky 20 years ago, right?

02:10:11.640 21 years ago.

02:10:12.680 Yeah.

02:10:13.000 What was that bet?

02:10:14.320 The bet was about when we would have the first 150-year-old human.

02:10:20.040 Which side of that bet did you fall on?

02:10:21.920 So my part of the bet was I think that person was born already, was born by the year 2000, the person who's already alive, who would ultimately become the first 150-year-old person.

02:10:36.020 And Jay bet the opposite.

02:10:38.880 And the critical thing was the person had to be mentally competent enough to carry on a sensible conversation about something.

02:10:47.600 Yeah, so that was 20 years ago.

02:10:50.600 And nobody's lived as long as the longest live person had lived at that point since then.

02:10:57.360 Which was about 122?

02:10:59.980 Yeah, 122 and a half, roughly.

02:11:02.740 Nobody's even reached 120 since then.

02:11:06.460 And so, yeah, I'm asked quite often if I still think I'm right.

02:11:12.080 And I do because I never thought this was going to happen because we got better at treating cancer or we got better at preventing heart disease.

02:11:24.020 I always thought it was going to happen because we would develop something or some things that would fundamentally change the rate of aging.

02:11:33.620 And we haven't developed that yet.

02:11:37.120 We've got a lot of clues.

02:11:38.920 And I think we're getting closer and closer and closer.

02:11:41.280 But the other reason that I'm still confident that I'm going to win that bet is that one of the things that's come out of the interventions testing program is that things can have this big effect started late in life.

02:11:54.040 So it may be that this doesn't happen until the person that was born in 2001 is 50 years old.

02:12:02.500 But if it happens then, that doesn't mean that they still couldn't live 150 years.

02:12:07.580 Now, it's important to note because this wager gets mischaracterized something.

02:12:12.520 I'm not saying that I think the life expectancy is going to be 150 years.

02:12:17.600 I'm talking about a single person.

02:12:19.480 That's right.

02:12:19.800 Probably a Japanese woman would be my guess if I had to guess right now. 1.00

02:12:25.460 I don't think that 150-year life expectancy is in our future.

02:12:31.200 What do you think is the limit of human life expectancy as we currently exist?

02:12:36.720 Maybe 100 years.

02:12:39.080 I think that's reasonable.

02:12:41.480 Now, if that happens, some people will live 150 years, right?

02:12:45.840 It's like the average is around 80 now and this one person lived 122 years.

02:12:51.520 So I think if we get to 100, that seems conceivable to me.

02:12:56.340 And also something that could be reached by getting better at what we do now.

02:13:02.680 The key thing is getting people to do what we know is better for them.

02:13:07.680 Now, do you understand the math behind Jay's models that say, if we completely eradicated

02:13:13.860 cancer, we would increase life expectancy by X years.

02:13:17.300 If we completely eradicated disease Y, we would increase... 1.00

02:13:20.920 And the numbers are very small in his estimates, but I don't...

02:13:24.180 I've never actually taken the time to look at the models to see where those numbers come from.

02:13:28.360 Those models rely on a number of assumptions.

02:13:31.440 One of the assumptions is that each of these is independent of the other, and I think it's

02:13:36.780 pretty clear.

02:13:37.000 Which is completely untrue.

02:13:38.580 Right.

02:13:38.980 Yeah.

02:13:39.300 Metabolic syndrome tells us that's untrue.

02:13:41.900 Right.

02:13:42.900 And eliminating a single cause of death is not the same as delaying 20 causes of death,

02:13:50.100 right?

02:13:50.780 So I think they're kind of artificial in that respect.

02:13:55.140 So those give me no pause for possibly winning my bet.

02:14:01.140 So when you think about existing molecules, i.e.

02:14:05.980 molecules that are either FDA approved or, you know, like 17 alpha estradiol is not an FDA

02:14:13.720 approved molecule, but it's been tested.

02:14:15.120 And it's had unbelievable success in male mice in the ITP.

02:14:20.440 When you think about canagaflozin, acarbose, of course, rapamycin, metformin, what molecule

02:14:28.720 do you think of the molecules we know about today has the most potential for gyroprotection?

02:14:36.240 Certainly if we go by the mouse data, it would have to be rapamycin.

02:14:39.940 If we go by the human data, it would have to be metformin.

02:14:44.300 Both of those are weak statement.

02:14:46.060 In my qualifications for each of those is a pretty major qualifications.

02:14:51.060 I actually think that what might turn out to be the most helpful is combinations of these

02:14:58.240 things.

02:14:59.500 So rapamycin plus metformin.

02:15:02.620 What I like about metformin is that the most compelling data come from human studies, not

02:15:08.060 from mouse studies.

02:15:08.880 These, the mouse data on metformin are weak.

02:15:12.100 Yeah.

02:15:12.280 It didn't succeed in the ITP, which is, were you surprised by that?

02:15:15.820 No.

02:15:16.960 No, I wasn't surprised by that at all.

02:15:19.120 And I wouldn't be surprised if it didn't work out in humans.

02:15:21.740 It's because, just because most clinical trials don't.

02:15:24.120 I mean, the existing data, which is voluminous and all pretty much points in one direction,

02:15:28.880 which is that it's going to be beneficial.

02:15:32.340 Again, it all comes from people that are taking metformin because they're diabetic.

02:15:36.580 So this could be a lot like the Wisconsin experiment again, where it's not going to work if you

02:15:42.500 do it on people who are healthy.

02:15:44.440 Right.

02:15:45.340 Now, near would argue against that, right?

02:15:47.300 Near would say that there were many benefits that we see in metformin that go far beyond

02:15:51.680 its glucose regulatory benefits that are the obvious benefit that the diabetic patients

02:15:56.980 get.

02:15:57.240 Yeah, no, no, near would be quite emphatic about disagreeing with me on this.

02:16:02.080 I'd love to be wrong about that, but I just, if I had to put my money, it's just because

02:16:06.460 most clinical trials fail.

02:16:08.360 And most clinical trials fail because they were based on mouse data to start off with,

02:16:14.000 at least.

02:16:14.420 So maybe this is, maybe this is something, it's certainly worth figuring out just because

02:16:20.020 the effects are so manifold, you know, it's, it's, it's dementia and cancer and heart disease.

02:16:25.400 And we don't know what else we don't know, for instance, what it might do to muscle function.

02:16:31.240 The best data on that, it's not good for muscle function, but again, that comes from early work.

02:16:37.280 And I think we have a long ways to go because it's so safe.

02:16:41.860 You know, that's the, that's the big thing about metformin is that we know it's extremely

02:16:47.240 safe, been taken by millions of people.

02:16:50.060 We don't know that about rapamycin yet, but I think it ought to be a high priority to find

02:16:55.940 out what low dose rapamycin does.

02:17:00.480 The trouble is it giving drugs of any sort to completely healthy people is something that

02:17:08.120 the FDA is not going to go for.

02:17:10.720 So we're almost going to have to work these things out on people that have some sort of

02:17:15.120 illnesses to start off with.

02:17:17.240 How would you dose rapamycin in a longevity trial, just as a thought experiment, given

02:17:23.260 two pieces of evidence that seem to be at dialectical odds with each other?

02:17:30.740 So they are as follows in the mice studies, in all of the ITP studies, the animals were

02:17:38.600 fed rapamycin in their chow meant, meaning they received rapamycin every day.

02:17:45.100 They were always eating rapamycin.

02:17:47.720 But based on our mechanistic understanding of rapamycin, we believe that the benefits come

02:17:52.920 not from global inhibition of mTOR, but from the inhibition of mTOR complex one and not the

02:18:00.000 inhibition of mTOR complex two.

02:18:01.480 And in fact, the inhibition of mTOR complex two might actually have some negative consequences.

02:18:06.060 And if you were to take constitutively rapamycin as patients do with organ transplants, you

02:18:14.360 were suppressing both.

02:18:16.000 How do you reconcile those two?

02:18:17.880 And how would you design a clinical trial to address this if your stated purpose was increasing

02:18:23.040 longevity?

02:18:23.560 The first thing I would do is I would start off with a dose that's already been tested

02:18:29.300 in human for its effects and enhancing vaccine response to influenza, because they did multiple

02:18:36.100 doses.

02:18:36.760 Now that wasn't rapamycin.

02:18:38.140 No, that was Everolimus.

02:18:39.580 Rapalog.

02:18:40.420 Yeah.

02:18:40.680 And that was, so five milligrams of Everolimus and 20 milligrams of Everolimus given once a

02:18:46.820 week did just that.

02:18:48.780 Right.

02:18:49.300 And the lower dose was just as effective at boosting immune responses, the higher dose.

02:18:54.780 It had fewer side effects.

02:18:56.340 So I would start off with that episodically, like they did, because I think there's some

02:19:02.400 evidence that you're getting just as big a boost from that.

02:19:05.440 Without the side effects.

02:19:07.240 Without the side effects.

02:19:08.380 And also, I think, you know, you can imagine how much the drug companies are working to

02:19:13.160 find a wrap-up log that doesn't inhibit complex two.

02:19:19.560 I mean, that's going to be huge if they can come up with something that works really

02:19:24.400 differentially on complex one.

02:19:27.000 That's really where I would start.

02:19:29.220 And I think those vaccine studies were a great start because they were, those were healthy

02:19:34.940 people.

02:19:35.700 They just were older people.

02:19:37.100 They were people, I think, 65 and older.

02:19:39.000 Or I would like to see those things continued.

02:19:43.680 Now, it's interesting.

02:19:44.800 A number of years ago, we tried to get funding for what I thought was a really good rapamycin

02:19:50.680 study, but we were unsuccessful, which is that there was a NIH clinical trial to look

02:19:55.800 at rapamycin as preventative for the reoccurrence of kidney cancer.

02:20:01.580 So this is people that already had a kidney removed, but were seemingly cured.

02:20:06.140 But they have a higher than an average rate of relapse.

02:20:10.920 They were giving one year of rapamycin to see if it reduced that.

02:20:15.520 And I said, wait a second, why don't we jump in and measure inflammation, muscle strength,

02:20:22.780 you name it, all these things in this experiment that was already ongoing.

02:20:27.640 But unfortunately, that didn't get funded.

02:20:29.840 But on the other hand, it may have been too high a dose.

02:20:31.800 Because this is a therapeutic dose for immunosuppressive purposes, right?

02:20:36.800 So it may not have been the right dose anyway.

02:20:38.580 So we might have come to a conclusion that was misleading.

02:20:42.060 I thought that that vaccination study was a great avenue for starting a longer-term study.

02:20:49.960 And I know they're doing some of that in a private company, you know, spinoff from...

02:20:56.300 Yeah.

02:20:56.800 Are you excited about the SGLT2 inhibitors?

02:20:59.780 I think it's a little early to tell.

02:21:03.040 You know, that and the NAD, various NAD precursors, I think it's a little too early.

02:21:10.440 I typically, you know, this is...

02:21:13.740 So scientists are often, by temperament and training, extremely skeptical.

02:21:19.320 And I think that's why we make boring interviews so often, is we don't ever come down on and

02:21:25.920 make a clean statement.

02:21:27.500 But I really need to see the data before I start to get excited.

02:21:31.840 And I never get excited by a single mouse study.

02:21:35.620 I get intrigued, but I don't get excited.

02:21:38.820 Although the human data on the SGLT2 inhibitors is also remarkable.

02:21:43.260 I mean, I think that's, you know, that's the sort of, that's the theme here, right?

02:21:47.300 Is you have a great ITP outcome.

02:21:50.720 And of course, the human data are not for longevity, but they're, again, they suffer the limitations

02:21:56.700 of all human studies, namely that they're being used in a subset of the population that

02:22:02.220 might not be the subset of interest.

02:22:03.740 But, you know, the impact on kidney failure, all-cause mortality, heart failure is pretty

02:22:09.420 impressive.

02:22:10.540 And I think what's interesting about what the ITPs show us with both kinagaflozin and 0.88

02:22:15.120 acarbose is that the benefits might not have to do anything with reducing, you know, caloric

02:22:21.500 intake, right?

02:22:22.340 Which was the proposed reason for acarbose, but rather has to do with glucose kinetics.

02:22:27.700 And I find that very fascinating, actually.

02:22:30.340 I do too.

02:22:31.360 And I have to say, I'm disappointed in the ITP that they dropped their pair-fed arm of

02:22:38.100 that.

02:22:38.580 When they started off, there was going to be a pair-fed arm and they dropped that.

02:22:43.220 And I'm a bit disappointed because we don't know now.

02:22:47.720 We only have body weight.

02:22:49.500 We don't have food consumption.

02:22:51.560 So we don't know how much of these effects might be due to food consumption and how many

02:22:56.700 might not be.

02:22:58.240 Or changes in the temporal pattern of food consumption.

02:23:04.980 You know, maybe if it makes your stomach feel a little bit queasy, you don't want to eat

02:23:08.860 again for 20 hours.

02:23:10.120 So the human data, I mean, we're going to make real progress when we have human biomarkers.

02:23:17.780 And we can do a five-year study and we can say, we know this is going to decrease dementia,

02:23:25.380 heart disease, cancer, preserve muscle strength, boost immune response, not just immune system,

02:23:32.720 because we have to be careful of that.

02:23:34.080 I think people think, oh yeah, we want to boost the immune system.

02:23:37.180 Well, we don't want autoimmune diseases.

02:23:38.880 We don't want our immune system to go haywire because it mischaracterized something as an

02:23:45.780 invasion.

02:23:46.480 But we want to boost immune responsiveness, certainly.

02:23:49.940 I mean, I think the limiting factor right now is biomarkers.

02:23:55.380 Yeah.

02:23:55.640 You know my feelings on that.

02:23:56.920 So I think we end on the same page there, Steve.

02:23:59.380 This has been a lot of fun.

02:24:00.500 And we're long overdue to share a dinner and continue these discussions.

02:24:04.620 So hopefully the next time it'll be in person.

02:24:07.080 That's great.

02:24:07.880 Next time in New York, Austin, wherever.

02:24:10.440 Perfect.

02:24:11.340 All right.

02:24:11.640 Well, thanks so much, Steve.

02:24:12.620 I'm sure everybody enjoyed this as much as I did.

02:24:15.280 Well, great talking to you, Peter.

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The Peter Attia Drive - August 09, 2021

#171 - Steve Austad, Ph.D.： The landscape of longevity science： making sense of caloric restriction, biomarkers of aging, and possible geroprotective molecules

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