The Peter Attia Drive - #207 - AMA #35: "Anti-Aging" Drugs — NAD+, metformin, & rapamycin

Episode Date: May 16, 2022

View the Show Notes Page for This Episode Become a Member to Receive Exclusive Content Sign Up to Receive Peter’s Weekly Newsletter In this “Ask Me Anything” (AMA) episode, Peter is joined by special guest, Dr. Matt Kaeberlein. Together they answer many questions around the field of aging with an emphasis on three specific molecules—NAD, metformin, and rapamycin—and their purported geroprotective qualities. They first discuss aging biomarkers and epigenetic clocks before breaking down the advantages and limitations of the most common experimental models being used today to study aging and pharmacological possibilities for extending lifespan. Next they dive deep into NAD and the much-hyped NAD precursors, nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN). They compare data from NAD precursors to studies on metformin and rapamycin, assessing how they stack up against each other and using the comparison as an opportunity to illustrate how to make sense of new experimental data and make smart decisions about how to approach future research. If you’re not a subscriber and listening on a podcast player, you’ll only be able to hear a preview of the AMA. If you’re a subscriber, you can now listen to this full episode on your private RSS feed or on our website at the AMA #35 show notes page. If you are not a subscriber, you can learn more about the subscriber benefits here. We discuss: Logic behind comparing NAD precursors to rapamycin and metformin [3:40]; Aging biomarkers: current state, usefulness, and future promise [7:00]; Epigenetic clocks: definition, use case, and limitations [14:45];   Advantages and limitations of studying aging in non-humans and the strengths and weaknesses of different model systems [26:30]; Aging studies: importance of control lifespans and the problems with reproducibility [34:15]; Intro to NAD, potential role in aging, relationship to sirtuins, and more [48:15]; NAD precursors (NR and NMN): current data [1:10:00]; Human studies with NAD precursors [1:25:45]; Comparing NAD lifespan data to data from metformin and rapamycin [1:28:30]; Defining a “clean drug” and a “dirty drug” [1:38:00]; Reason for the lack of rapamycin studies in humans compared to NAD and metformin [1:41:00]; Ranking the geroprotective molecules in terms of risk and reward [1:48:00]; and More. Connect With Peter on Twitter, Instagram, Facebook and YouTube  

Hey everyone, welcome to a sneak peek, ask me anything, or AMA episode of the Drive Podcast. I'm your host, Peter Atia. At the end of this short episode, I'll explain how you can access the AMA episodes in full, along with a ton of other membership benefits we've created. Or you can learn more now by going to PeterittiaMD.com forward slash subscribe. So without further delay, here's today's sneak peek of the Ask Me Anything episode. Welcome to Ask Me Anything Episode 35. This is a special AMA where, in addition to being joined by Nick Stenson, I'm also joined by a previous guest, Matt Kiberline. Matt's been a previous guest on the podcast, twice actually, with the most recent one being

believe in September of last year. He's a professor of laboratory medicine and pathology, an adjunct professor of genomic science and an adjunct professor of oral health science at the University of Washington. His research interests are focused on the basic mechanisms of aging in order to facilitate translational interventions that promote health span and improve quality of life. I wanted Matt to join for this one because I knew we were going to go into a lot of different subjects where he would provide insight into the questions that many of you have asked. So in this episode, we focus on answering questions around the field of aging, but specifically looking at three-girroprotective molecules.

And these are the three molecules that I get asked about the most. The first is all things that have to do with NAD, and that usually implies its precursors, NR, and NMN, but also sometimes NAD itself. Second being RAPA-MISON and the third being Metformin. Now, if you were to do a search and find out which of those gets asked about the most, it's Metformin ends down the most, and that's followed actually by RAPA-MISON. And I think after that is NR, NAD, and NMN.

But I might have that a little bit backwards. In this podcast, we focus on a number of questions in the field of aging. So it starts with a bit of a discussion around biomarkers of aging. What are they? How good are they? What do they tell us about the field?

We talk about how studying aging can be done in various animals, and we get into this specifics, meaning the benefits and disadvantages of studying these in yeast, worms, flies, mice, dogs, and ultimately of course humans, the species of interest. Talk about how to think about the various studies that are being done around the idea of lifespan

and health span, talk about epigenetic clocks. And then from there we really dive into the meat of this, getting into everything that has to do with NAD, and then ultimately it's precursors, NR, and NMN. Smallcules, as I said, I get asked about this a lot, and so we had no shortage of questions and nuances to get into here. After speaking about NAD and detail, we then look at RAPOMICEN and METFORMAN, though probably not in as much detail, because we've spent lots of time talking about those molecules on other podcasts.

However, Matt felt, and I agreed when it was all said and done, that it was going to be beneficial to at least include these other molecules as a means to compare what we know and what we don't know about NAD to molecules for which we have much more data, at least in the case of rapid miceen, as it pertains to longevity,

but in humans, as it pertains to metformin. The goal of this podcast was to help you not only understand these molecules and see how they stack up against each other, but also to help you think about the new information around these and what we might want to expect to see or look to see is we make decisions about the use of these things in the future. If you're a subscriber and you wanna watch the full video

of this podcast, you can find it on the show notes page where of course you also find the show notes. And if you're not a subscriber, you can watch a sneak peek of this video on our YouTube page. So without further delay, I hope you enjoy AMA number 35.

Oh! Oh! Hey Nick, how you doing today? I'm doing good, how you doing? Very well. We're gonna do things a little different today, huh? Yeah, we have a today? I'm doing good. How you doing? Very well. We're going to do things a little different today, huh? Yeah, we have a little different setup for this one.

So what happened was back in February 2021, you and Bob, Deneame, where you looked at one specific topic that was covered on multiple podcasts in particular, the Shulman episode and kind of went back and tried to simplify that conversation around insulin resistance. And what we heard from subscribers was a lot of people really enjoyed that type of podcast, maybe a lot of requests to do more of it. And so what we did for this one is we just kind of been collecting a ton of questions around the science of aging. And in particular three geopolitical molecules that I know we see the most questions come through and I know you hear the most from your patients, which is NAD, Rabbimisin,

Metformin. We have no shortage of podcasts on this with Matt Kable and Steve Austin, Near Bar's Lie, Joan Mannick, Davidson Claire, Lloyd Clixstein, David Sabentini, you kind of name it, we've had a ton of podcasts on it. So what we did is compile all those questions in hopes of having a one-stop shop for people to really understand these topics and how they can think about them just with these molecules, and then also in the future as new information comes out. That's kind of what we're looking at today, which leads us to a little bit of a different thing we're doing, which is in addition to me asking you questions.

We also thought there'd be no better person to ask back on the podcast for the third time then Matt Kaverlin, and we reached out to Matt, and he graciously said yes, and so we're doing a three-person AMA today, which we've never done before. So we'll see how it goes. But thank you, Matt, for joining us for this one. Thanks for having me back, looking forward to it. So this is an ambitious way to go about this. And truthfully, when we first kicked around this idea

a couple of weeks ago, my vote was to talk exclusively about NAD and its precursors. I felt that there was so much information there that to try to do anything beyond that would, frankly, be counterproductive. We just wouldn't be able to cover it in the depth. Now, Matt, you had very strong feelings that as much details we want to go into around NAD and its precursors, NR and NMN, you really felt strongly that we needed to look at RAPMI send metform. and what was your rationale for that? Yeah, well, I mean, I think, as Nick said,

those three molecules often get talked about together in the field and by people who are following the field as certainly three of the leading candidates for Jera protectors. And so I think there's some value in almost a compare and contrast, but between the three and really take a look at the state of the data

that we've got today so that you can really sort of understand what is the evidence for each of these classes of molecules, maybe where some of the challenges as we think about moving from the laboratory into the real world, into the clinic in terms of testing them. So I thought it would be helpful to at least cover those three classes of molecules

together so that we can kind of take a look and compare them against each other. Well, you won. I lost. No, I'm kidding. I agree with that logic. We're all winners here. So I think we will do that. So Nick, where do you want to start this thing? Yeah, so as we're thinking about it, I think what we need to do is just answer some general questions around aging and studies of aging because I think that we need to do is just answer some general questions around aging and studies of aging, because I think that's going to be really helpful for people as they hear what you and Matt have to say to break down NAD, rapamice, and metformin. So maybe what we'll start with is just if you can remind people at the highest level, are there any biomarkers

of aging that we can look at when we look at these molecules? level, are there any biomarkers of aging that we can look at when we look at these molecules? Well, certainly what I would say is when you contrast aging with a field like lipidology, our hands are a little bit tight. If your objective is to lower APOB because APOB plays a causative role in atherosclerotic cardiovascular disease, you have the perfect biomarker, it's APOB. So even though you have multiple different ways that drugs can go about lowering that, they can inhibit synthesis primarily, they can increase clearance, they can impute absorption all these things, you have a very clear biomarker that you can track.

And of course that's true for a number of drugs. But when it comes to this field of aging, it really is difficult. I'm guessing Matt that there are going to be some people who will argue that we have remarkable biomarkers for aging. And then you'll have others. And I'm probably more in this camp that would argue, actually, we don't really have any good biomarkers for aging. Where do you sit on this, Matt? I think you're right. And I think one of the things that you have to consider is really what do you want a biomarker to do. We're obviously talking about biomarkers of biological aging. What I think you really want is something you can measure that is predictive at either the individual or the population level of future health outcomes. Mortality certainly, but also functional outcomes, disease risk, things like that.

So at one level, we absolutely have biomarkers. We can look at each other, and to some extent, come up with somewhat of a precise measure of biological age. We can look at two people who are the same chronological age, and humans are actually pretty good at estimating who's in better health. So we've evolved to do that. So there must be these underlying molecular biochemical signatures that we can find that are predictive of that. And I think it's a work in progress. So this has been ongoing

since the 1980s trying to find these molecular biomarkers of aging and it's still a work in progress. It's an interesting time as you suggested where we have some candidates now, and certainly there are people in the field who are very optimistic, some would argue maybe overly optimistic about how well those candidates work. And it's also an interesting time because we're starting to see commercialization of these so-called aging clocks that are being sold to the general public. And again, I think you can have a debate about what the evidence is that these things are actually measuring biological aging. Are they doing it accurately? But certainly, I think I feel like we're closer than we were

15 or 20 years ago, but we're still a ways off from that definition that I gave of having something that you can measure that in a predictive way at either the individual or the population level really tells you with any level of precision what the biological aging trajectory is. I think the example you gave is a pretty good one about the eyeball test. So if you took two people who are 50 years old and looked at them and one had lots of muscle mass and great posture and looked like a physical specimen of health. And the other one was slumped over maybe more bidly obese, take the exact opposite of that. It's probably the case that the fitter person would look younger.

And even if you could look at their face and see the same number of wrinkles and assume that they're, well, they're probably the same age, you would still predict sort of a younger biologic age of that person. So you're right. There's something in the Gestalt that's pretty obvious. But truthfully, at least for me, what would be really valuable would be blood-based biomarkers, potentially more elaborate, but let's start with the blood, where you could do interventions for a short period of time. And if in fact those interventions would, if continued,

lead to better lifespan or health span, and let's just keep it simple and say lifespan, they would show up. So for example, if you took an individual, and you calorie restricted them for three months, took them down to 70% of their weight maintenance, caloric intake. You would like to think that there would be some set of biomarkers that would suggest

an improvement in their lifespan. What do you think about that idea, Matt? Yeah, so I mean, I agree completely with you that from a pragmatic perspective and a usefulness perspective, that's exactly what we want. And I think that's what the field has been searching for for a long time. It's a complicated question that you're asking, though, because it's one thing to hypothesize that there are going to be molecular biomarkers that reflect biological age. Those are not necessarily going to be the same biomarkers that reflect rate of aging.

And what you're talking about, a short-term readout, almost has to reflect rate of aging, and what you're talking about, a short-term readout, almost has to reflect rate of aging, or even potentially the speculative reversal of biological aging. And so my only point is, those may not actually be the same markers for each of those classes. So I certainly believe that there will be signatures of intervention response that are predictive of efficacy, I'm not sure that it's going to be the same as the signatures of biological age. If you had asked me 15 or 20 years ago when I was really getting started in this field, the kinds of interventions you mentioned caloric restriction, that's kind of the gold standard

that we've been studying for many, many years, are those slowing aging or reversing aging, I would have answered their slowing aging. They are decreasing the rate of decline or damage accumulation. What's been really interesting and I think exciting over the last 10 years or so is the observation that at least some of these interventions reverse many of the molecular changes that go along with aging and in many cases the functional changes that go along with aging. So you talked about blood biomarkers. I agree with you. That would be great if we had blood biomarkers. I'm actually a big fan of functional biomarkers. So looking at organ function, tissue

function, that's harder to do in people than it is in laboratory animals in some ways. But I really feel like those are telling us something fundamental about future health outcomes that you can almost take to the bank. There's still some in some ways, but I really feel like those are telling us something fundamental about future health outcomes that you can almost take to the bank. There's still some stochasticity involved, there's still some luck with staying alive, but if you can make somebody's heart function better, their brain function better, you've got to feel pretty good about that, and if you can make multiple organs and tissues function better with the same intervention, think you can make a case that you are in fact modulating

some underlying biology of aging as opposed to only the biology of that tissue and organ. Yeah, and frankly, Matt, that's exactly what we do in clinical practice. The reality of it is, and we'll talk about these things, but I'm not looking at epigenetic clocks. I'm just not. How do I know if we're moving, or how do I believe? I guess you'll never really know if you're going to talk about this with some humility. But what gives me great confidence that we're moving in the right direction with a patient? It's basically when all of those

functional things improve. So if VO2 max improves, muscle mass improves, strength improves, cardiovascular efficiency improves, phenotypic markers of disease improve. So glucose disposal, insulin signaling, APOB, lipid markers, inflammatory markers. Maybe those are just biomarkers of aging. I mean, there's certainly my crude version of those things. And again, some of those are things you measure in blood. Some of those are things that you measure noninvasively. Some of those things are imaging related. I think until someone comes up with better tools, this is basically how I think about this problem. But let's talk a little bit about epigenetic clocks because they sure are getting a lot of attention. You want to maybe tell folks what they are specifically, how they work, and what they're aspiring to do.

The word epigenetics actually means a lot. It can mean anything that is inherited that's not at the level of your DNA sequence. But mostly when people talk about epigenetic clocks, what they're specifically talking about are chemical modifications either to the DNA or to the histones that pack the DNA. And these chemical modifications control gene expression, so things like methylation and acetylation. What has been observed in laboratory animals and in humans is that there are changes in these epigenetic marks that happen in a predictable way with age, and there are tens of thousands of these marks that can be measured at any given time in a cell.

And you can create algorithms that predict the age-related changes in these epigenetic marks with a pretty high degree of accuracy. So you can sample a subset of these specific chemical changes and come up with an algorithm that within plus or minus five years will predict a person or an animal's chronological age. And that works really well, and that seems to work really well in every organism where people have looked. All the way from very early development up into old age, you can create these predictive algorithms. The idea that has emerged from that is that you can do that at the population level, and then if you identify individuals whose

chronological age doesn't match up really perfectly well with their epigenetic age, in other words, they lie off of that best fit line, that those people may be biologically younger or older than their chronological age. And so that's where this idea of these epigenetic clocks has come from is you then, at least in principle, can predict a person's biological age depending on how well they fit the best fit line for this algorithm. And I think that the evidence in support of that comes mostly from longitudinal studies in humans where you can create a training set, and a test set, and you know what the future

outcomes were for some of these people. They've been sampled, let's say, over 20 years. And indeed, you can see a relationship between the people who's predicted biological epigenetic age, say, is younger than their chronological age. And then when you look at them 20 years later, they have a lower likelihood of developing specific diseases or potentially of dying.

So I think that's the case that can be made for these epigenetic clocks that they are telling you something about future risk. I think in my view, the limitation to these epigenetic clocks, they're several. One is that there are about two dozen of them, and honestly, I can't tell from the way people argue with each other, which are the best and which aren't. But I think more of what concerns me is nobody has ever done what I would view as the definitive experiment, which is to actually show in the same individual

or in the same population that you can actually predict future health outcomes. Now, some people will argue that the longitudinal data makes that not necessary. I think there are a couple of reasons why I don't agree with that. One big one is that the environment that we live in as humans has changed dramatically over the last three decades. And we know that environment plays a huge role in epigenetic modifications. And so

the epigenetic marks that were most relevant for health outcomes 30 years ago might not be the most relevant today. So that's one. The other is, this is actually a pretty easy experiment to do in mice, and it really bothers me that nobody has done it. I was going to ask you that, Matt. So how many times is someone doing a mouse study that is going to the end of life? Why do we not have the definitive lifespan study for each of these epigenetic clocks. I think that's a legitimate question. I don't know the answer. I mean, people will tell you that the clocks aren't as good in mice. Look, it should be doable and honestly, it should have been done three, four years ago.

So, it's a black hole in the literature that hasn't been filled yet. And just to be explicit, the experiment you want to do, right, is you take a cohort of mice at say 20 months, you measure their epigenetic age and blood, you do a few interventions that we know should extend lifespan, you measure their epigenetic age and blood six months later, and then you see an individual and population level, what the survival is, and you can do end of life pathology. And so, if the clocks are working, you should absolutely be able to detect that signature well in advance of end-of-life.

If somebody did that experiment and it worked, I would be convinced. That would make me really be a believer in the epigenetic clocks, particularly if you could do it at the individual level. But it hasn't been done yet, so it's a little bit unclear. That's a big ask to do it at the individual level. I think it is one thing to do at the population level,

but the question is, how will it port to the individual level? We use this term, and you've already alluded to this, we use this term broadly. Sometimes when a person says, epigenetic clock, they mean literally a set of biomarkers that look at methylation patterns on DNA. And other times when people say epigenetic clock, they mean an algorithm that looks at 15 biomarkers that can include obviously the methylation

pattern on DNA, but can include things like vitamin D level, fasting glucose level, traditional biomarkers. Do you have a point of view on the difference between these? Well, I think what you just said is accurate. They're measuring different things. My personal intuition, so I would call that more of a general aging clock, putative aging clock, I guess I should say, the putative aging clocks that incorporate things beyond epigenetics are much more likely to actually work in a useful way in humans.

And I think one reason to believe that is, if you look at what people call the hallmarks of aging, right? These sort of famous nine things, molecular processes that seem to contribute to aging, only one of them is epigenetics. And so I think you run the risk with the epigenetic clocks that you're only informing on a subset of the biological aging processes. And if you look more broadly, you're much more likely to get a holistic picture at the whole individual level.

I want to come back to something you said though, you said it's kind of a heavy lift or a hard-ass to get these clocks to work at the individual level. That may be true, but I think in order for them to be useful, that's what you want, right? And that's exactly right. The fact that it would be so hard to do speaks to exactly why you would love to see it done. I still come back to what we talked about earlier. I find it hard to believe, I hope I'm wrong because this would be a really efficient way to do

things, but I just have a hard time believing that there's going to be an epigenetic signature that I think will be more valuable than some of the most tried and true phenotypic tests. and true phenotypic tests, VO2 max, zone two threshold, grip strength, muscle mass, fat free mass index, all of these sorts of things that are so highly, and I believe, causally linked to longevity. So I guess if nothing else, it will be interesting to see how tight that association can be. I would agree with you about the epigenetic marks, like methylation, specifically. I'm a little bit more optimistic that you can create the kind of more broad aging clock or aging signature.

But do you think it can be done out of an existing collection of biomarkers, or do you think we're going to have to go deeper into the proteome and metabolism to find things we don't even know exist yet? In other words, find other molecules we don't even know exist yet. In other words, find other molecules that we basically haven't identified yet. I honestly don't know. It wouldn't surprise me if just given the state of knowledge today that there are a subset of the things that people in the field are thinking about that can actually be extremely

predictive at the individual level. It's never going to be perfect. You can always do better. But all of the things you mentioned, all of the functional outcomes that we know are important for health, there is underlying biology that drives that. And I think we've got certainly an incomplete,

but a pretty good idea of what a lot of the processes are that are driving that loss of function and that degeneration. Time will tell, but I feel like the candidates we've got are pretty good, and they may not be as precise as you can get if you can do a full functional workup on a person, but they might be good enough to tell you some information about likely efficacy of lifestyle changes or drug interventions or things that people might want to incorporate to potentially maximize their health spend. Last point on this before we get into the more substantive attempts to answer some questions,

one of the things I'm always mindful of here, and I've seen this a lot with early cancer screening diagnostic companies, is changing the definition of what something means in order to fit a diagnostic test. I've been pitched on these so many times, literally at least three if not four times, where a company comes along and says, hey, we've got a biomarker that is an early detection of cancer. And I say, okay, show me the data. And they say, look at this sample set where we predicted so many cancers in patients. And we have zero false positives and we have zero false negatives. So I look at their test and I say, well, these are a whole bunch of positives in people that don't have cancer. And they said, no, no, no, they have early cancer. I said, what

do you mean by that? Well, they have cancer, but it's only a few thousand cancer cells. And I said, but do you know if those people go on to get cancer? Because clinically relevant cancer is about a billion cells. That's when it would be one square centimeter. And they said, no, it doesn't matter. This person has cancer. And I said, well, look, if a person has a thousand cancer cells in their body, we have no idea if that means they're going to get cancer, or if the immune system is going to come along and mop the floor with that cancer. So to tell me you have no false positives, just because you captured those,

is a little bit like moving the goal post, you shoot the arrow with the side of the barn and you go and draw the target after, right? So I see a little bit of the same thing going on with biologic age clocks, where there's pairing an age clock with a supplement or an intervention and we're tuning them to each other. Does that make sense?

Yep. I agree completely. And I think certainly something I'm concerned about. I think a fair number of scientists in the field are concerned about is the commercialization of these ageing clocks. So you mentioned pairing it with the supplements. That's even a step further. I think even field to the general public and two, it's causing people to make healthy lifestyle choices.

Maybe when you measure your biological age and it tells you your 10 years older than your chronological age, you start exercising or you eat better. Maybe that's true. I don't know that that's necessarily true, but it's still dishonest to claim to people that that that's necessarily true, but it's still dishonest to claim to people that anyone is able to, with any precision, measure your biological age, and there are lots and lots of companies doing that. So to me, that's a problem to begin with. It becomes a bigger problem when the same companies are then also selling a product that they claim will reverse your biological age. That's just snake oil. I don't know any other way to say it. It's just snake oil. Honestly, the FDA should step in and do something about it, in my opinion. I think that was a really good overview kind of around the question of why there's so much complexity around the idea of aging biomarkers.

And so, maybe what would be really helpful for people is knowing all of that. How do we think about that when we look at these studies that look at geopolitical molecules? So people who aren't in the field don't do these studies day in day out aren't always looking at this. A lot of them are going to be wondering, okay, what does that mean as we look at this? So maybe you both can talk about what the takeaway is from everything we just discussed as well as when we look at studies and models and mice and yeast or humans, whoever that may be, maybe run through one of the strengths, the limitations, how to think about those things. Thank you for listening to today's

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