Can You Actually Reverse Aging? What the Science Really Says with Dr. William Mair

What if the way you live today is (scientifically) changing how fast you age? In this episode, Chris Wharton sits down with Dr. William Mair, PhD — Professor at Harvard T.H. Chan School of Public Health — to break down the real science of aging, what actually works, and how to truly live better, longer.

Most of us think of aging as something that just happens to us. Dr. William Mair thinks differently — and after 30 years studying the biology of aging at Harvard, he doesn’t deal in theory – he deals in evidence.

In this conversation, Dr. Mair unpacks why age is the single biggest risk factor for nearly every chronic disease — from Alzheimer's to cancer to cardiovascular disease — and why targeting aging itself may be the most powerful thing we can do for human health and performance. But more importantly, he brings it back to you: what can you actually do, right now, to influence the rate at which your body ages?

You'll walk away understanding: 

• Why your lifestyle choices are actively speeding up or slowing down your biological clock 
• What the science actually says about sleep, nutrition, and exercise, and how to optimize those habits to support healthspan
• How to cut through the longevity noise — supplements, biohacks, and what's real vs. hype
• Why "healthspan" matters more than lifespan — and how to protect it 
• What emerging science could change everything about how we age in the next 10–15 years

Chronological age is fixed. Biological age isn't. This episode gives you the peer-reviewed science to understand the difference — and how to act on it.

Transcript

SPEAKER_02 0:02

By letting us live long enough to get these things, which we've never seen them on evolution. Age is the central risk factor. Every disease you can think of one invitation. You can look at it as a risk factor, you can modulate. Then you can have a kind of one input, which might give it to me. It's all it is. We move ourselves from a really as an environment to a really safe one. Evolution doesn't work anymore because we're revealing this kind of built-in obsolescence. You can modulate a molecular aging. We can do it in a lab with a gene mutation, with a drug, with a geometric change. It's amazing. The idea that we have a limit is true for how our bodies are now, but it doesn't mean it's impossible. It's just that there was no reason. There's never a situation where longevity would have been beneficial for humans until now.

SPEAKER_00 0:54

Welcome to the Living Room podcast. I am super excited for today's conversation because my guest is genuinely one of the most fascinating minds I've had the pleasure of spending time with and an incredible communicator of the nuanced and layered topic that is aging biology. Wilmere is a professor of molecular metabolism at Harvard and director of the Harvard THC Aging Initiative. He's the recipient of the American Federation Breakthrough and Gerontology Award and a recipient of the Glenn Foundation for Medical Research Scholar Award. In this episode, he completely changed the way that I think about how we age. We get into the science of metabolism, what's actually happening inside our bodies as we get older, and how something as simple as when and what we eat can have a profound impact on that process. And most importantly, what we do and don't actually know about what aging truly means. It's one of those conversations that's equal parts mind-blowing and deeply practical. So I hope you enjoy it as much as I do. Let's get into it. Will welcome. Hi, Chris. How are you doing? Good to see you. You have spent your entire career, correct me if I'm wrong, studying the biology of aging. Why pick the biology of aging? What does that even mean? And how does that compare to studying any other of these sort of known diseases, illnesses, um, interventions, and so on?

SPEAKER_02 2:14

Yeah, I have. Honestly, I I've been almost birthed in the field. I started studying aging when I was 18. So sort of 30 years ago, I've been studying this. And I came through quite circuitous roots. So I began to study aging at a when I was doing an undergrad degree from an evolutionary perspective. So why does aging even exist? Right. And that question itself, I think everybody thinks they know the answer to, right? Aging just exists because things break down, because bodies go wrong. We're like machines. But then when you look at nature, some things don't break down. Some organisms age amazingly. You can have something like a naked mole rat can live 30 years, never get cancer, but a similar-sized rat lives two years and gets cancer really quickly. So the my way into it was just like this is a we have this concept of aging as this immutable thing that happens. But in fact, there's huge variety out in the world. And so that's why I got interested in like what's the biology underlying why you get exceptional ages and poor ages in nature. And that extends to people too, right? So some people age incredibly well and some others. The reason why I think it's important why I stayed in that field is actually kind of bang for your buck, right? So when you think about the last century of public health, we added like 30 years to our life expectancy, more probably in the last century. And that was all by targeting things which used to kill us when we were young, right? So didn't do anything about how we age. We got rid of through vaccination, through clean water, through all these things. We got rid of all these things which used to limit our life expectancy, but it created this other problem. It enabled us to live a long time and our bodies just hadn't evolved the capacity to deal with that. So reveal this built in obsolescence, which means in fact, public health gave us Alzheimer's disease, right? By letting us live long enough to get these things which we've never seen in our evolution, we created this incredible new problem for biology, which is that age is the central risk factor for every chronic disease you can think of that's a real killer, it's a huge burden for society and for economies, cardiovascular disease, cancer, Alzheimer's disease, age is the risk factor. And so the reason I stayed in the field is like if you want to do something about, I mean, you've added these years to life expectancy, we want to make them healthily, healthy ones, you've got to actually think about the cause itself, which is aging, not the disease. Because actually what happens is the way you get diseases when you're old is very different than when you're young. So when you're young, you get an infectious disease. If we can cure that, you end up with a healthy kid. When you're old, you begin to get multiple comorbidities at the same time. When you're over 65, you end up with one, two, three, four ailments. So this disease-centric approach, right? If you think there's good data on this, if you cure cancer completely, which would be an incredible thing to do, the numbers of actually healthy individuals you add to the population, the years of life you spend healthy is actually kind of just three, because you're left up with older individuals that have one less comorbidity. So the point of the research of like we think about aging is if you can look at it as a risk factor, you can modulate, then you can have a kind of one input which might give you protection against all those different things. And that's how you really make these healthy years, you know, these years we've added healthy ones. And so we think of aging as something that you can measure, something you can modify. And by doing that, you can change, you know, the way we exist in our old age.

SPEAKER_00 5:19

And do we know what do we know the answers to that? Do we know why we age? Do we have some idea?

SPEAKER_02 5:26

We do. Well, if you think so, why it depends what you've got to get to why versus how, right? So if you ask most people why do we age, they'll say, how do we age actually? Like telomeres get shorter, DNA damage, oxidative species, like why we age, like why aging exists. There's some there's some like theory on that, right? So if you think about an amount of aging is genetic, not all of it, but some percentage of it. There was a paper out a couple of weeks ago saying 50%, we can argue about whether that's true or not. But if aging is generally a negative all around, right? Apart from maybe wealth and knowledge, when you look at biology, everything in a human's body gets worse with time. So if you've got genes which are causing aging effectively, and yet we think about survival of the fittest, right? Everybody's basic level of Darwinian evolution is like, well, then how can you have a gene which is causing this horrific thing to happen? Yeah, right. That doesn't make any sense. And so that's really when you ask most people, they would go, well, aging, there can't be genes which cause aging. And I would say there probably aren't. The reason aging exists is because during our evolution, during the hundreds of thousands of years humans have been evolving, we didn't live very long, right? We didn't die of old age, we died of infectious disease, predation, accidents, right? So if you're dying at 30 during evolution by some catastrophe, there's no reason to evolve capacity to live to 100, right? Natural selection is just a numbers game. The genes which make you more likely to pass on your genes to the next generation will be surviving. So what that means is any gene variant which makes you bigger, stronger, fitter, more reproductive capable, more attractive, whatever it would be, that has a huge selection variant, right? So that's for any any mutation which makes you a bit stronger, whatever, will be selected for because we see the benefit of those genes. But the outcome is if that same intervention causes aging down the line, it doesn't really matter because no one lives long enough to see it. So we have aging because it's the side effect of genes which cause something else beneficial, right? Cause you to be big, to be strong. But now the interesting thing is public health has changed our whole environment we live in. So now we're seeing the side effects of those genes. So you could argue that you know aging is is the is the side effect, it's the byproduct of things which are beneficial when you're young, causes you to age. It never used to matter for us because we didn't see that negative effect. But suddenly because we've got clean water and vaccinations and public health, we're seeing it. So now we that's why it's kind of maintained in the gene pool.

SPEAKER_00 7:53

This might be a naive question, but if that's the case, why does the naked mole rat live longer than normal rat? And why are some whales and sharks and like living for hundreds of years?

SPEAKER_02 8:03

Great question. So when you look at nature and you look at exceptional ages, think about the sort of places they live, right? So you can get a rat running around New York, right? Stressful life, gets eaten by staff, right? Scrapping for pizza in the subway, all these sort of things. It has a really hazardous life. So therefore, its chances of living past two are really low. So its body is optimized. So live fast, die young, grow fast, reproduce fast, get scrappy, get stuff, right? There's no reason for it to evolve capacity. If you look at a bat, same body weight, same metabolic rate, bats live 35 years, right? What's the difference? One can fly. Bats, life is safer, right? They can fly away from predators. So as soon as you move something from one harsh environment, some really kind of dangerous environment, to a safe one, longevity becomes useful. This is true for like I in my lab, we work often to we work on aging real time on a little tiny round worm that lives two weeks in the lab. Lives, ages, dies, skin wrinkles, reproduces, everything goes wrong, can watch age in real time. They live in the soil, right? So their chance of living past two days in the wild is nothing. There's another similar worm which can live 17 years, right? So it's pretty similar biology. That's not chance. Why would one evolve with a capacity to live 17 years and one two weeks? It's because that one that lives 17 years is a parasite, lives in your body, all its nutrients come from the host, super cushy environment, right? So then longevity becomes beneficial for the species. When you look at things that live long, tur tortoises on an island, things that live on islands, really safe environments. That's where you get longevity. Naked mole rats live underground in Africa in very safe environments of these eusocial colonies where suddenly their hazard rate is low. So now for living a long time makes sense. So this is well, same for whales, same for like clams. You can have clams that live 500 years.

SPEAKER_00 9:54

And this is the product of generations and generations.

SPEAKER_02 9:57

Millions of years of evolution, right? Okay. If your hazard is low, it's worth in involve evolving longevity. What humans did is in a hundred years, we moved ourselves from a really hazard environment to a really safe one. Evolution doesn't work that fast. So we can't catch up that fast. So therefore we're seeing our bodies age because we're revealing this kind of built-in obsolescence we have because there's no point to do it.

SPEAKER_00 10:20

So how do we solve for that, given, assuming that we want to, which I think we all do? Yeah, um, if that's a product of millennia of evolution, then how do we speed that process up?

SPEAKER_02 10:33

So there's an intellectual conversation, then as what do we want to do or what do we think is likely? But if the kind of question is, well, given that evolution, right, which is a better biologist than me, only made humans live maximum 120 years, why would we think we could break that limit? So it's start like the real fancy. Why do we think it might be why would anybody think it's possible to biohack a human to live to a thousand? I don't think that's what we want to do here, right? But that's just an intellectual question.

SPEAKER_01 10:56

Yeah.

SPEAKER_02 10:57

The reason is evolution only does, it's a numbers game, it's just stats, right? So it's only created the genome which is optimized for the conditions that that that species evolved in. It doesn't mean it's impossible. So for instance, this is another reason that I got into this field. If you took that tiny little worm that we work in my lab that's been around for millions of years, and you aged every single one of them at room temperature, every single one, they'd live, they'd age, they die in two weeks, over and over and over and over again, right? Because they're optimized for their ecology. So if you look to that, you go, this worm, there's no way its body could ever live past two weeks, right? There's a there's a flat limit. You could ask the same question if you're if you're a worm sitting here, you go like, why we're screwed, guys. We can only live to two weeks.

SPEAKER_00 11:41

Why bother?

SPEAKER_02 11:42

Why bother? But an experiment in 1993, just before I went to college, someone showed you that old. I'm that old. I went to college in 97, 18th grade, right? They did a genetic screen out of conditions this worm evolved in for see if they could find a single gene mutation which would change the way that animal lived. And indeed, they found one gene mutation, could take this animal, which forever, for millennia, had lived and died in two weeks and make it live eight weeks, right? So it broke the whole theory of evolutionary biology of aging. Like what you can do one thing and now, and it doesn't live eight weeks like miserable and decrepit. It looks youthful. It's amazing. And so you can look at this thing and you've completely changed the relationship of that animal with time. It ages completely slowly, it completely revolution. Now, the answer is why didn't evolution make that change? That's the real key. Evolution didn't make that change because there's a difference between longevity and fitness, either either evolutionary fitness or or actual fitness. If you put that mutant long-lived worm out in the wild, or you mix it with the normal wild type worms, it will get out competed, it reproduces less, it's like it's less stress-resistant, different things. It's not the evolutionary optimized ones for its environment. You put that mutated worm in a lab and it'll live for ages, right? And what was even more amazing is like when you take that same mutation, because no one cares about making worms live longer, that same mutation, you do that in a, I mean I do a little bit, you put it in a fruit fly, does the same thing. You put it in a mouse, does the same thing. And now a mouse gets diseases of aging, but you can make that same one gene mutation, slows the way a mouse ages, makes it live three and a half years instead of two and a half years, changes when it gets diseases. And now when we can look at the genetics of centenarians of exceptional ages in humans, they have mutations in those same pathways, right? So the question is, you know, there's a difference between what our bodies evolved to do in our, you know, during the course of evolution, that just because we didn't evolve with sexual longevity, doesn't mean we can't, right? The biology of a whale which lives 200, 300 years, it's not massively different from us, right? I mean, of course, it is at the top level, but it's the way it deals with metabolism, stress, the way it processes these things, the biology is quite similar, right? A naked mole rat isn't that dissimilar from a rat. And actually, you can study it. And one of our scientists, Vera Corvanova, studies the differences between mice and naked mole rats and tries to take the genes that are linked to those naked mole rats and put them in mice and mix around, right? So the question is, it's not hopeless, right? The idea that we have an upper limit is true for how our bodies are now, but it doesn't mean it's impossible. It's just that there was no reason, right? Evolution is not, doesn't have a reason, it's just a blind watchmaker, it's just selection. But there's never a situation where longevity would have been beneficial for humans until now.

SPEAKER_00 14:21

Can can we double-click on that just quickly before we move on? And I think we're almost bombarded with the idea that some tech genius in Silicon Valley somewhere or in some lab um in Boston has figured out a way in which we can do that for humans, and that that this potential to extend lifespan meaningfully by decades, if not more, is a real possibility. And even yesterday I saw a uh uh post about this. Um, I believe that there's just been funding for um human trials on on um epigenetic reprogramming, I think was the term. Can you explain to people listening the difference between us having made that discovery in a mouse or a rat and the leap from there to to humans? Because I don't think it's as simple as we're led to believe.

SPEAKER_02 15:12

I think that's exactly right. And so I'm someone who works with lab models, studies aging. You know, I've done this for 30 years. I didn't do this just because I thought it was going to change how a mouse lives. I really believe in the concept of what we call geroscience, is that, you know, gerontology is studying diseases of aging and trying to treat them. Geroscience is thinking about age as a risk factor for all age-relate conditions that you can modify, right? So I believe in that concept and I believe in that that will have the biggest bang for its buck for therapeutics. There's a long, long process to get from changing the lifespan of a mouse in a lab to a therapeutic, which affects how an older adult ages. Even mice in labs, right? Having a long-lived mouse is not necessarily the most healthy labs. And lots of things that we've extended lifespan in a mouse, it comes with costs. They're immunodeficient, they're small, they're reproductively, you know, delayed. There's lots of things that you definitely wouldn't want for a therapeutic. The trouble is, aging is this real kind of human thing, right? If I go and give a talk on aging to the public, about we're trying to think about diseases of aging, we're thinking about metabolism, why metabolic dysfunction leads to disease. Someone will go, we don't need older people. You're trying to play God. One person will say this is a bad thing to do, someone will say this is great, I want to live forever. Those sort of questions are innately human. They don't come from someone trying to cure cancer, right? If you cure cancer, you end up with more old people. That's exactly the same sort of thing. In fact, you're just going about it from a different way. But this aging thing is a real kind of like gut or human thing. So the problem that we have in the field is that we all experience aging. We don't all experience every disease. Every one of us experiences it or is seeing someone who's suffering the deficits of it. So we're really desperate. And being told to wait is really hard in something which is just this inevitable clock the sky. You know, we're kind of we're brought in this idea that it's just this time is just like against us. And so that means there's a real kind of urgency to be told, what should I do? Which leads to this environment now where people will overinterpret pre-clinical data. They'll tell you things which aren't really scientifically sound. They'll they want to give you kind of like the right advice. And it has led to this huge monetization of like what we can do in the aging field. So I think the thing that I think about is these two things can be true. We can measure biological aging. So we can tell now at a molecular level, pretty well. It's not perfect, but there are good ways to do it in a lab. I don't think they're ready for consumer use. But for I'm 47, there's probably ways that I could, through a series of biomarkers, work out in a test tube whether I'm aging faster or slower than the average 47-year-old. Don't answer that question. I haven't looked. But like you could do it, right? So you can measure it. So that means you can then measure whether an intervention which might affect aging is working or not without having to wait for me to die, which is useful. It's also true that you can modulate biological aging. We can do it in a lab with a gene mutation, with a drug, with a dietary change. It's amazing. And we can then try and study those things. That's what someone like me does is like, how do those things work? What could we translate? Those translations of those kind of moonshot therapies are not here yet. They're not ready for prime time. This is a field that 20 years ago used to be a real fringy field, small field. It's massively underfunded. The NIA, which is the funding body of the government in America that funds aging research, is the least well funded. But in the last five years, 10 years, we've put a lot of investment in. So I think those things are gonna come. I do. Whether they're gonna make us live, you know, to 200, I think that's probably unlikely. But I think there will be therapies that come down the line.

SPEAKER_00 18:49

I think that's unlikely ever.

SPEAKER_02 18:51

Ever is a long time, right? So you always get so I think the complexity of systems gets higher the higher the system, right? So it's always I think you're gonna get a longer return in a nematode worm that's a simple system than a human, right? So I I think, and there's so much more heterogeneity out in the world. So trying to scale these things from a lab where we try to reduce all kinds of variants, right? You just want to do an experiment where you change one thing and everything else is the same, genetics the same, environments the same. To scale that to something really impactful, I think will be very hard. So I think that I don't think it's impossible to break this kind of 120 upper limit. Yeah, that might happen. I also think there will be them, you could argue that maybe GLPs are this already, we can talk about that, but there will be therapeutics who are designed to modify how we age, which have benefits on age-related diseases. I think they'll come in 1015 things. But the truth is now we already know how to do some things, right? So we already know that some people age exceptionally well and others don't. We know that where you're born determines the rate at which your body ages, social advantage, social disadvantage, right? Whether you're poor nutrition, stress, circadian rhythm disruptions, all these things, like lots of things make your where you're born in terms of environmental exposure, make your body age fast, right? And we can measure those things. That's a where you're born in Boston determines how how your body ages, which is wild.

SPEAKER_00 20:16

And and I believe that that can be intra-city, right?

SPEAKER_02 20:19

Like there are different areas of different cities where they're absolutely in New York, you could go to different districts and now, and those data are only just beginning to come out. So we've always known that where you're born determines kind of your health outcomes for disease. But now we can begin to measure aging, you can really show that just luck, right? It's not genetics is different than those things. It's a combination of environmental exposures, behavior, what you can achieve, things you can do, change how your body ages and therefore changes how you succumb to those diseases, right? So if that's true, then we already know we can do something about it, right? So we know that some people who age exceptionally well, it doesn't even have to be a centenarian. But if you think about centenarians, they are incredible people. They obviously live to 100, but they don't kind of live to 100, but that period of decline is stretched more so than we would have. They're like super healthy and independent into their nine, into their mid-90s, right? But that's not chance, right? That's not all genetics for sure. It's a combination of genetics, environment, optimism, whatever it might be. But but basically we tend to in in life, when we don't understand something, we go, well, that bit's just kind of random. That's stochastic kind of chance. Sure. Don't believe that. It's something we can measure. And so we can begin to understand, and we're doing that in the field, like what is it about exceptional ages, whether it's their exercise, their nutrition, their social engagement, the combination of all of these factors, interaction between all these factors, which makes somebody have the fortune of aging really well, we can study those now on a molecular level. And then we can start trying to apply those to the general population. I think that's much more the kind of the Wonder Health mission is like, whilst we wait for these moonshots to come online, whilst we wait for the Scientific rigor to go through where we try to translate, and there are lots of pharma companies doing this, these kind of mechanisms in a lab that work in a mouse to a person. We can't wait for that if you want to, it's it's too late. So, what can we do now? And the things we can do.

SPEAKER_00 22:13

Will I have two questions? Yeah. One, before we talk about what we can do, and we've got a good idea of that, and I think we should unpack that. Just going back to something that you mentioned earlier in that monologue, um, was that I told you I'd more was that the biology of aging research is massively underfunded, right? Or one of the least funded areas of of biology research. Given that, and correct me if I'm wrong, what you were saying earlier in the in the conversation was that the biggest risk factor for all of these um most common diseases and illnesses is aging. Why is that the case? That doesn't make sense.

SPEAKER_02 22:53

I mean, it doesn't make sense to me, but there's there's a few things for it, right? So I I think that for a long time, the concept that aging was something that you could intervene in biologically was seen as a bit fringy. So certainly when I started in this field 25 years ago, it was like, well, that's kind of that will work in a in a small invertebrate in a lab, it'll never work for people. I think that's gone away. But basically, the idea that you could do something that's preventative and that we should spend time investing in that is also a hard burden. So we by nature, like it's much more easy to fund companies which cure disease and to get a drug which which cures disease than one that prevents it. We're changing now a little bit, right? So historically, all the research money has gone into a disease-centric approach. But I also think conceptually, we're taking a long time to steer people around from that idea, right? So I completely agree that that the best, you know, there's a thing we call the longevity dividend, which is really the benefit you would have from changing how people age, even just like giving five years of more youthfulness, right? Not just to human suffering and burden, to the economy, to how people write that it's a massive payoff. Like it is from a financial model, it makes much more sense to try and take the humans that we have and make them healthier for longer than to spend all the money we have on treating end-of-life disease or try and do something about the demographic shift that we're having towards older populations, right? We just don't have enough young people to keep us going. That has been a hard thing to really put into like into even just the people that make policy into the NIH. Like we, this is the way you invest. You have to invest in things which are the biology of prevention, right? The therapeutics of prevention. And up until recently, that was just off the radar. Like when we think about it's certainly true, like Alzheimer's disease and dementia, it's a huge burden to the human population. And we've invested millions and millions and millions of dollars in trying to cure those things. And I am not saying we shouldn't make that investment. But ultimately, what you're trying to do is cure a very complicated disease. And even if you were to cure all the age-related diseases we know of, right, there's going to be ones we don't know that will come later. So essentially, I don't think that this concept of like this disease model, we're a bit addicted to it because it was so successful before. Right? We got rid of polio, we got rid of these diseases because we just went, this is the problem. Let's cure it. It's how we're set up to do it. Aging's just different, and it's taking a long time for this to get kind of mainstream ideas. And this is why when I think about kind of the influencer space and how aging has become this kind of runaway train of like kind of, you know, social media thing. That's there's a good and a bad to that, right? So actually, there's negatives because I think the public gets some misinformation about what they can do, and it feeds into our fears a little bit and it leads us to think we can, you know, we can take one supplement and not do the things that we need to do to make us health eighty. But I do think generally it has moved this concept of aging is not immutable, right? There are things you can do to slow how your body ages that actually we can change and that we might be able to do mechanistically and therapeutically later. And I think, I hope the investment's there, but really when we look at it's another monologue, but when you look at the National Institutes of Health, they're built by Institutes of Disease, right? And then we have the Institute of Aging, which is the least funded, that the most, and it's just like, and that investing in that would affect all the others.

SPEAKER_00 26:08

So do you think a fair takeaway is that there are some extremely exciting developments in this space where you know it's looking promising that there might be some emerging molecules or therapeutics down the line that could help add years, if not decades, of functional years to our lives. But we've all got this bridge to cross, right? And that bridge could be a lot longer, it probably is a lot longer than we're being led to believe on social media.

SPEAKER_02 26:36

I completely agree. So I'm I'm a kind of you know, I'm an optimist, but I'm a cynical optimist. I think you have to be an optimist to be a scientist. You, you know, you have to think that the experiment's going to work. You are you have to think that there's something going to come from this.

SPEAKER_00 26:47

Yeah.

SPEAKER_02 26:48

It is a really recent time period where we've had pharma companies, for-profit pharma companies, set up to think about aging as the problem they're solving, right? That exists now. Five years ago, ten years ago, it really didn't. Those companies are trying to scale and put into humans this basic discovery of foundational research. And I think they'll get success at some point. There's a huge attrition rate between preclinical studies and a mouse and something that works in humans, right? There just is for many reasons. Like mice are not humans, being the most obvious one, but also it's complicated when you put things out into the world, how a drug would work, how you so I think they'll get there, but I think it will take time and it will take a lot more investment than we have, right? We have this kind of investment from Silicon Valley and tech leaders into that concept of like we should target aging. And some of that is because those folks want it for their own personal gain, but also because honestly, they're numbers-driven people.

SPEAKER_01 27:41

Yeah.

SPEAKER_02 27:41

And so the reason Google started a company to fund aging research was because they they were trying to work out where we could make the best bang front park and they listen to to folks like me, not to me, but to folks like me saying aging has more return than a disease, and do it. So that's a certain subset of people that look at data and go, that's a data-generated way. Government funding doesn't work like that. We don't have a lot. So I think they will work, but I think we have to, like you say, bridge that gap. And I think there is a real danger in over-promising early data and try to over-interpret, make guesses about what you do with the human body from a mouse's body.

SPEAKER_00 28:19

Can we dig into that a little? Like this sort of longevity economy, um, it feels like a big cultural shift. And um I think we're all seeing this term longevity more and more and more, I think, is being massively overused. Um why do you think it is that we are exposed to so much misinformation and grandiose claims above and beyond the fact that it could make these huge financial returns? So is that the idea?

SPEAKER_02 28:46

No, I think a lot of it is slightly the fault of the scientists, I have to say. So, like scientists work in probabilities. We're really like, you've known me for a while now. I'm I'm really rarely will speak in definitives, right? So you say, Will this work? You're like maybe, right? Right, but that's how statistic works. It is annoying, but like we work by there's a p-value. What does the P stand for? Probability, right? So we fundamentally don't believe in absolutisms. It's like if I did this over and over again, how many times would I see the same thing? Yeah, humans don't work in probability. We just want to just tell me what to do. For God's sake, just tell me what I should do. Should I do it? Should I not do it? And previously, when we didn't have huge exposure to information in the way we do now in 2027, right? And like 20 years ago, when access to information was lower, I think scientists could take more of a time to work out what they wanted to do. The trouble is, like when I go and give a talk to someone and they say, Well, what should I do? Should I eat this? Should I eat that? Previously, I'll be like, I can't tell you because I don't know what's right for you. Sure. That's not a good enough answer in the moment where someone else will tell you, right? We look to people to tell us something with absolute certainty. And that and that's what generates likes and views and and clicks is like someone who will look down to a camera lens and go, This is what you need to do, Chris. I know what's right for you. And often, and that's monetizable, right? And it's particularly monetizable in the aging space, and it leads to someone starting with it's a slippery slope of like, well, I know this and this domain, this works, and that got a good response. Now I can speak with the same level of certainty, with the same kind of like swagger about this thing and endlessly and ends. And that's just a very human nature. So the problem is, I think, is that scientists haven't found a good way to give a compelling narrative or like what can you do now that is scientifically valid and give someone hope and something they can do without joining this thing. We're kind of like, well, I what do I answer? I can either go, that person's lying to you. No one wants to be the naysayer on social media going, there's nothing you can do. Yeah. Or you get engaged in this thing. And I think for a while we stood back in the aging space and gone, like, this is not our, this is not our world. We're just gonna be in the lab nerding out doing experiments. But time moved on and it's created this huge economy where now it's a mistake. There are different types of aging conferences in the world, right? I go to lots and run academic aging conferences where it's lots of just endless science talks. You have to like get selected to give your talk, and it's like the cutting edge science. There are other ones that are kind of pay-to-play. Someone pays to go, you do it, public code to go. The suit camps of people don't ever meet. So there's no interaction between those people. So it's like, and I think that is, to some extent, slightly on the shoulders of the academics. We've just thought of like, this is not our job. This is not our, and you know, is it our job? I don't know. But meanwhile, the narrative has gone. And it's become very easy to get information about science, like really early, that you couldn't get before. Before most people in the public, or even even clinicians didn't really know all the science was happening. It was at the purview of the researchers. Now everybody gets it instantly. ChatGPT can tell you straight away. So everybody can give you information, just look, I know what to do for you already. And and and they'll give you a load of citations which are true, but they're all based in something. I think this is what's really interesting is that even the weirdest things you've heard on social media, right? The people that are taking blood transfusions from a young kid, right? Or whatever, blood. There used to be like clinics, you can do that, think they were shut down. That didn't come out of nowhere. There were legit scientists, I know many of them, who are doing great science where you can fuse an old mouse and a young mouse together. You can join their circulation systems, right? This is how we discovered leptin, right? This is how we discovered what creates obesity, but but they can do it for aging. You can take a young mouse and an old mouse. They don't love it, right? But you can join them together, and then you can see how that affects the aging of the other. And the the amazing thing is that the old mouse gets a bit younger and the young mouse gets a bit older. So things like stem cells and the muscle, right? You care about muscle regeneration. You can show that quiescence of stem cells, which rejuvenate muscle and able to do repair, get reactivated in the old mouse by joining a young mouse to it, right? That those things are amazing. So that means that these stem cells, which we thought were just kind of old and dormant in an old mouse, they're actually fine. There's just something in the blood that was missing, right? So those studies are great. That's how we begin to learn the biology. It does not mean that you should go and get a blood transfusion of your of your like kid.

SPEAKER_00 33:07

So do you think the main problem is that we are pulling on threads of science, then finding evidence for things we believe in to then commercialize something and then everyone believes it's a thing.

SPEAKER_02 33:17

And and it's it's it really is this idea that everybody, you know, I can ask a hundred people if you could have the pill that would make you live to 200, would you take it or not? And you'll get different answers. But essentially, even the least vain amongst us experience aging, right? Even it's just like, oh, my hangover takes longer than it used to, right? We all care about aging on this, on this real level. The older you get, suddenly things you didn't think about become very important in your life. So it's a very, it's a universal market. It's just a market for everybody. And so that means in this, in this world where you can just, you know, information is is is is marketable. You can get it. And so how do we keep this balance? And I think that's where one thing Wonder Health is trying to do really well is what's real, what's not real, and how instead of just going, well, there's nothing you can do, this is how you can do what you what we what we know works really well. So you optimize it. This is how we can bring online as soon as possible the things that are exciting, the future therapeutics, how we can bring them into your into your circulation, not literally, but like into your world quickly, whilst also letting the scientific process play out.

SPEAKER_00 34:20

So let's talk a little bit about that model and how we think that that is that differs from you know existing setups. Um, you know, we often talk about there being no such thing as a longevity expert, a lone longevity expert. Can you just unpack that a little bit and and explain why you think this instead of one-to-many approach, there's many to many approaches a more suitable way?

SPEAKER_02 34:42

Yeah, and I think it's a great question. So, you know, if I if I were to class what type of scientist I am, right, I could say I'm a I'm a biology of aging researcher. That could be applied to any biologist, actually, right? Anything in biology is worse in an old thing. So if I go to an aging conference, someone who studies anything, there's very little, right, which is better in an old thing than a young thing. So I work on aging. So all you've got to think is about, well, I work on this function in a cell. I look at a young thing, I look at an old thing. It's got worse. I want to understand why. So aging is not a scientific discipline like some others that are really, you know, you've got an expert in epigenetics, an expert in whatever you think, physiology, biochemistry. Aging's like a cat all, which means it's because it is literally all of biology can be put in the purview of aging. So that makes those science conferences super cool, really interesting, really diverse research. But it means there isn't one thing which drives the aging process, right? It's different to say, well, maybe we can do one gene mutation and a worm, make it live longer, and everything that goes wrong goes wrong slower. That's true. But it doesn't mean there's one cause of aging. And so there isn't like the world's best aging research. You could probably, in most disciplines of science, you could go to those research and go, like, who are the five best in this thing? They'd all argue and they fight with each other, but you could probably work out ways like I want to find the best biochemist in the world, right? The best metabolism. Subjective something, but you could do it. Similar names. Aging is like, well, which bit are you looking at? It's like, you know, which bit of the elephant are you looking at? Are you talking about the brain? Are you talking about performance? And so that's why I think that there is no one way to say there's the world's best expert. Science, scientists, by definition, we spend years and years and years working in very narrow domains to become the world's best in anything. Like my lab studies a very small area of research, and we get we're pretty good at it. That doesn't mean I'm good at what the next lab does, right? That like to be a real expert in anything, you've got to devote your life to it. Because aging is everything, and like I can't tell you the I'm not an expert on all of aging biology. I might know a bit more than you, I might not, but like we could do it. But like I'm I'm good at what I know, I'm good at what I know. What happens is because the kind of way people are looking for it, someone can just start taking all the data that they're not experts in it and being confident I'm the person who is the decide on whether this is good science or not. And that's just not how the science process works. And so what you really want to do is go, let's find the best people and let's work out and let's get them to talk to each other, to find the best people who work on social engagement and positive psychology, right? That yeah, I work at a school of public health. We have in our school tenured faculty at Harvard who are behavioral economists, who are policy people, who are working nutrition, epidemiology, work in a molecular biology lab, what all these different things. Lots of us study aging from completely different views, right? We're all experts in what we do. Ten years ago, none of us really spoke to each other, actually. We just drilled down our domain and tried to get tenure. Now we're beginning to integrate that science even there. Where someone who wants to really understand why it is that optimism makes someone age better, the people who did those studies, they're not really biologists, right? So they're they're social scientists. So they've they've they've worked out the data. The data are real. If optimism makes you age better, it does something to your biology. Someone like me can study it. So now we can begin to integrate those things. And I think that's what we're trying to do at Wonder Health. We're trying to say, let's get all these scientists, let's get the expert knowledge, the cutting-health knowledge in all of these domains. But beyond that, let's try and get them to talk to each other and work out, you know, the human body is complicated. Like what you do in one domain affects another one. And that's what's amazing about aging, is that it's it's this multifactorial systemic process. So there is just that there cannot be the world's best aging researcher. That doesn't mean anything. Every scientist in the aging domain came in through one route. They started training in one thing. This isn't a field, right? There's no, there's not many undergrad degrees in aging. That's not a thing, right? I did an undergrad degree in genetics. I'm a geneticist. I'm not a biochemist. I happen to be an aging researcher. There's a biochemist who's an aging researcher. We're different.

SPEAKER_00 38:43

So at a very high level, in order to become the world's best in any of these very narrow verticals, you have to forego the opportunity to become the world's best at other ones. Yes. Because of by very definition, it's true.

SPEAKER_02 38:56

When someone goes, you know, to get tenure at Harvard, we go through this incredible laborious process where you have to get external professors you've never met to write 40 letters, say, tell me why this person's the best in the world at this. You can't be the best in the world at two things, right? Unless you're maybe an athlete. But it's possible, it's it's possible in science. And so I think that's really like how that process works. Like you to get, we trust and expertise, we want deep knowledge. You kind of have to shut down everything else. And one thing that's also true is frankly, to have a big social media profile and a big influence, that's a job in itself, right? The people who are speaking the loudest and have the most visibility are not necessarily doing the most research because it's hard to do the most research, right? To really do those things. That's that's your day job. And to create like a huge following, to create these things and to start the companies and to monetize this, you've got to let go of some of those things, right? That doesn't mean you're not knowledgeable, but the people doing the research, the people in the lab doing the research. You need them to continue doing that. They need to keep going, otherwise, the science stands still.

SPEAKER_00 39:56

And I think an interesting observation that I had early on in this journey is that you know a lot of the science exists, but is fragmented across these institutions, is starved of funding.

SPEAKER_01 40:09

Yeah.

SPEAKER_00 40:10

Um, but even at a very high level in high science, understanding how one's vertical impacts another's, we still don't truly know, right? And so we know if you were to do everything right, like you're optimizing the nutrient density of your diet, you're sleeping perfectly every night, your exercise physiology is on point, human connection excellent, it will impact your brain chemistry, your brain function, or your skin health. Right. And those grants are hard to write.

SPEAKER_02 40:41

If you're a scientist, like that study, which would be like, how does the whole thing work, is not a grant you could write. It's not a paper you can write, right? Because we we're trying to go like we're gonna take this one thing and we're gonna move the knowledge forward on that. So scientists have to be kind of myopic to really do it. And this is why I think some of our scientists love Wonder Health, because they begin to think about other stuff, talk to people outside their domain. We don't even go to each other's conferences, right? This idea that you're a scientist, you're you're very in a very small pool of your 500 people that you see all the time in the same domain, reviewing each other's papers, working on the same stuff. We don't go to those other meetings. And so there's very little chance to even begin if we don't know each other or understand each other's science or read each other's papers because there's too much literature out in the world, how can you begin to think how one affects the other? And so I think that's led to a real gap, which is hard for the aging field, is like, okay, we've got a thousand people that know a thousand pieces of information, like who knows all the information. How do we get it? And like, you know, you can just have someone who says, Well, I know, but that's can't be the case.

SPEAKER_00 41:43

Prove it.

SPEAKER_02 41:43

Yeah.

SPEAKER_00 41:44

Let's talk about what we do know. All right. Um, and I think you know, when we talk about longevity this term, we're we're not so much thinking about how do we add decades of years to people's lifespan, the amount of time that they live, right? And we've just discussed there are people doing that. Um, but I think one thing that we all struggle with, and we've all certainly experienced this with our with our family members, is that, yeah, sure, we are surviving some of the things that used to kill us, you know, heart disease, certain cancers, infectious diseases, and so on, but we're seeing this very, very consistent decline in physical and mental health over the age of what, say, mid-60s and sometimes a lot earlier. So I think when our our sort of true North objective collective as a company is how can we help everyone to live like the centenarians that you explained earlier in the conversation? Because I think what we really want, if we're being honest, is to live our best lives for 10 decades and then just fall off a cliff and die, right?

SPEAKER_02 42:48

I think people might make different choices on that. But like, yeah, I mean, I think that's that's the Hellspan mission.

SPEAKER_00 42:53

Yeah. Well, I think when we think, and we discussed this yesterday at lunch, like I think when we think about aging, the only thing that turns people off about the idea of living to 100 is that we associate that with frailty and decrepitude.

SPEAKER_01 43:05

Yeah.

SPEAKER_00 43:05

So really, if we can compress morbidity and stop that happening earlier, then that I think is a is a good true North goal for us as a as a company and as a collective. And I think the the thing I'm optimistic about is a lot of that science exists.

SPEAKER_02 43:21

I think a lot of the science exists because it's things that we can see in the real world, right? So it's uh it's not like every centenarian has been the super optimized human who's been working out every day, right? That you know, there's there's things we don't know. But the human body is now, we had technology has enabled us to study it in ways now at a resolution that we couldn't do 10 years ago, five years ago, right? So now we can begin to understand really on a systems level what is different between someone who's aging really well and what is not, what works, what doesn't. We have AI models which will begin to look at this data and make sense of that noise and put these pieces together. When you think about connecting the dots between different domains, Humans can't do that, but large language models and AI probably can do that to really make sense of like a machine learning approach. This affects that thing. So I think we're at a real stage where we can really do it and we can integrate these different domains. So I think that now more and more, you know, we talked to a kind of um an exercise physiologist yesterday who's also talking about nutrition and time-restricted eating and cognition. Like more and more now, individual domains are beginning to realize that there's links between them. So I think the science is really poised to do really amazing things, and there's never been a better time to do it. I really think what that this is the perfect time to do it, to understand, you know, how do we enable more of us to age exceptionally, right? Whilst we work with these other things that come online, I think the idea about whether we want to be fully functional, like a 20-year-old at 100, that's probably also unlikely. And also that's a pretty scary day every day when you wake up feeling great and you might drop dead tomorrow. Like that's a different thing. Whether those things be completely uncoupled, but what is definitely true is that some of us have this drawn-out period of comorbidities, and others do not experience that. And that is not random chance. That's a combination of the things you've done to yourself, the things that have been done to you, things you didn't do, and then and genetics, right? It's just it's an environment versus genetics interaction. And now we can really begin to make good, good choices and good make good advice about what you can do, really give good advice about how you optimize those things in a way we never could before. That resolution's amazing, but to do that, you've got to understand completely from top to bottom each individual, right? And that's something we're trying to do here. It's like this idea of deep phenotyping is just a fancy word to say, really describe everything that's happening in a person, all those different levels from a molecular level, from a cognitive level. And then when you start to give advice and make recommendations, you can see what moves and what doesn't. And you can really work out what does this person really need. We didn't have capacity to do that 10 years ago, and now we do. It's a master.

SPEAKER_00 45:50

And it's becoming more affordable, right? And I think that's the most exciting element of this is you know, we have been told for so many years exercise more or like consume less calories and you know, get more sleep. And it and it's just a little boring to be told the same thing over and over. And I think this layer of um, you know, uh, the ability to capture data phenotypically across all of our different systems um allows us to get more granularity and then we can approach that with more precision. And then I think one of the best parts of that is that we can hopefully, I mean, we can see this day to day, get a better result in less time.

SPEAKER_01 46:28

Yeah.

SPEAKER_00 46:28

Because when it when all is said and done, you have to keep doing the thing forever, right? To get the benefit, to get the true benefit.

SPEAKER_02 46:37

Yeah, but the thing, but the thing you do might not be the same thing I do. That's the real thing. So when you're just told, yeah, everybody's known forever, eat well, sleep well, exercise. But that's just this generic recommendation, right? Now we're science is at this resolution of technology. So when I was, as you said, I'm old, when I did my undergrad degree from 97 to 2000, I graduated in 2000, it was at the height of the human genome project, right? To sequence one genome cost hundreds of millions of dollars, took labs across the world, took years and years to do it. Now my lab could do it for 300 bucks, right? So not that long now. We could do it in a machine. So we could have just banked that money, honestly, and just wait for the technology to evolve and done it really quickly and saved all that time and effort. It was a bit depressing, but it's true. That's also true for all the things we're using for deep phenotyping, right? The way we can describe someone's genetics, do metabolomics and proteomics to define these variables, we can do now at scale, lower lower and lower costs every day, so that you can begin to get a full molecular picture of a human, overlay that with all these things we know about their body and cognition, and then go, okay, when we make recommendations, what moves, what doesn't? So I think we can certainly take a much more modern and scientific and compelling approach to those kind of those pillars of you should make these broad suggestions. And then once you've optimized those, bring in extra things. The reality is there is no point in doing something like in taking some supplement if you're sleeping four hours a day and drinking like half a bottle of whiskey every night, it's not going to do anything.

SPEAKER_00 48:03

Yeah, major in the majors first. I learned that. I learned that from you. Thank you. For someone who can't, you know, this all sounds great, right? And we know that it's possible, but we also know that if you want to really collect data across this full picture is expensive. So for for people that can't wait for this cost compression that we know is coming, where do they start?

SPEAKER_02 48:25

Well, I mean, I think this this gets back to either what you recommend behaviorally or how you scale the types of things we're doing. So there's two different answers that make sense. So I think, you know, certainly getting the message through that it that prevention is better than cure, right? That that even if you're feeling great at 45, there's a tsunami of chronic conditions coming for you. And the best you equip yourself for those, that the more healthy you're gonna live, the more you're gonna be able to interact with your family, all those things, the more you'll be. So really getting that world out there that this is not inevitable. Some people even have this idea that just like, you know, my parent did this, it's the same for me. We, you know, this is just gonna happen to me. This is my behavior. Like, that's not true. Aging is malleable, like you we can't optimize everybody and make them perfect human, but you can do things now, which will mean that you're gonna be healthy aging, right? So, like, there's never too late to start. And some of those are just, and really thinking that, you know, exercise is not just about how you look or or nutrition, it's really it's gonna do something about whether you succumb to outside disease. It's gonna do something about whether you someone cancel like that message in itself should be more compelling now than ever. So you can make good choices and things you can do. The other point of like how, whilst we have this kind of like very expensive deep phenotyping we can do for a few people or in a few scientific studies, if no one can get that, what do they do? Well, that's where science comes in, right? You don't the the goal will be if we get all the information about a few people, we can begin to really work out what signal from noise, what are the few pieces of information we might need for a lot of people, right? That's really where AI and computational power comes in to go, you know, we might not have to deep phenotype everybody. And this is what either in scientific studies or or however you want to do it, if we can get enough data from enough people and enough kind of input variation and output variation, right? So it's when you turn on Netflix, right? It knows what you what you've watched and then it guesses what you'll like to watch, right? It's just like this is input variation and output variation. It's making choice. We can do that scientifically. If we can do that, we can reduce the number of measurements we need to scale. So I think that's where I'm really hopeful that this kind of mission can enable us to make recommendations for everybody which might not need deep phenotyping. In the meantime, the there is real science that can tell you, you know, things like if you told me 10 years ago that optimism would make me age better, I would have just kind of grinned and gone, sure, right? Like one, you know, you can't change someone's personality, but there's certain things about stress, about even sleep. Like, you know, when think about like, you know, that 10 years ago when I was chasing tenure, it was like work, work, work, do these things, travel, go to every conference, right? I was like, this is how this is my markers of success. Now, and I, if you just said, well, slow down, you'll live longer, I would have gone, sure. That's just kind of like wishy-washy behavioral science. Now I have changed my mind on those things, right? That there are things we can do behaviorally, which have just as a good effect as some of those kind of the actual real mages that really consider your options. Like, think about do I really, you know, not just do I want to drink this drink or not or eat this food, it's like if my stress levels are so high and my sleep levels are so low that my body's breaking down, that's just not gonna make me tired. That's gonna make me age poorly.

SPEAKER_00 51:37

Yeah.

SPEAKER_02 51:37

Do I want to make those choices? So there are things we can really get out there to really kind of, I think, give proper scientific weight to some of these kind of lower-hanging fruit things to really make, you know, people ultimately are data driven, I think. They really want to know, like, okay, it's like prove it. Like tell me why I should do it. Don't just, don't just go, yeah, you gotta, you gotta sleep eight hours. Like, show me why that does it. Show me really beyond just my how I feel in the morning, how it affects cognitive function, how it affects subsequent disease risk, how, you know, and we have those things now. So I think that's where we're at to make, you know, really compel people to do things. And ultimately, it's always a choice, right? There's this, this is the perfect version of you.

SPEAKER_00 52:17

Yeah, no one's gonna be that. Right, yeah.

SPEAKER_02 52:19

This is what you want to fit in your in your in your kind of lifestyle, and this is like you don't have to be perfect all the time.

SPEAKER_00 52:25

But I think that's the point, like, is giving people agency to make that decision.

SPEAKER_02 52:28

Yeah. So so risk versus benefit, and really that's the whole thing. And you go like, it's okay not to be perfect all the time, but like there is a that there is a way to help your body optimize itself and age as best as it can.

SPEAKER_00 52:40

Like, we know so we know that level of um, you know, resolution is coming, right? We're doing that now. That's what we that's what we do day to day, with the ambition of that being something that you give away, that you make much more affordable and scalable so that people get a much higher yield on their time and they're less confused. Yeah. But right now, today, as someone listening, I think when we hear scientists talk about phenotyping and metabolomics and proteomics and all of these different omics and ologies and things, we are just confused, right? Because I go onto social media and I see a hundred different businesses with a hundred different tests, all claiming to be the test that sort of tips the halo, right? And so whether it is, you know, some at-home blood test or lab work or microbiome or set of supplements, you know, how do we discern signal from noise? Because, like you say, these are promising things, but how do we know what's ready and what's an overreach?

SPEAKER_02 53:35

So I think this is gets back to those what the really difficulties and going just wait for someone to really confirm this is the best one. So if you take an example of that, so you can go online and order a kit which will tell you your biological age, right? You can send it away. I think you've tried some of these to look at the variants, right? So you mail them off, they'll send you spit in a tube, send it back, it'll tell you your biological age. People are desperate to have that. There's two things. What are you going to do with that information? There's only point in having information if you can do something with it. It has to be movable. But also, how robust is that? That is again one of those examples where those kits are not nonsense. They're based on things that have been developed in labs that do work in some settings, but there's like four, fifth generations of those types of things that aren't being used by those companies. So if you were to send your same sample off to 10 of those companies, you get 10 different results. If you were to send the same sample off to the same company 10 different times, you get 10 different results, right? So then the advice has to be that's not useful because obviously that doesn't mean anything. It also doesn't mean that epigenetic age clocks aren't nonsense, right? That's also not true. There are good ones that are being developed. There's a biomarkers of aging consortium which come together to talk about what's the most robust ones of these, which ones scale, which ones don't, which ones have too much variance, so that if I do it in the morning when I'm dehydrated versus the evening, they change, right? If you have something that goes upwards and down all the time, so if I'm hungover, I'm aging faster, that's not useful. But that's coming, right? So actually talking to NIH, NIH just funded RPH, this huge aging study to really begin to get these data. That science will come in five years, I think, and we'll really know this is something that could be useful. So it's like trying to give people hope and that the science is real, whilst not saying, not just go, just you know, just don't order it. So the thing is like you have to think about who are the people selling this thing, what is their background, what what's in it for them, right? And that's really the balance. It gets back to so all those things you see online about about doing oh there's there's good omics and there's bad omics, frankly. There's good data and there's good bad data, and like it's really I don't know. I the answer is you have to find the best people who are really who are who are truly experts in that thing that are the best, the world's best on epigenetic aging clocks who are scaling those things who will solve that problem. Yeah, you know, 10 years ago, not long ago, this is basically just one guy who was doing these, right? And I know him. He would go to conferences and he'd present this stuff, and they were not, they were not clocks of biological age, which is like we could I can tell you if you're 47 or not. And we'd all go, well, my driving license would tell me that. What's the point? And he was kind of like laughed at a little bit. He's laughing now, right? So that science has moved at an incredible rate and it will get to a point where it's precision. And that, for instance, when you think about these aging clocks that go on another tangent, will have huge influences on public health. So if you think about now, you just turned 40, right? As you're getting older, is that so we get older and older at some point How could you? Well, you know, I'm 47. At some point, we screen for diseases based upon age, right? So we start screening for certain cancers based upon age. If age is variable amongst the population, so that your 40 isn't someone else's 40, it's clearly arbitrary to be doing it based on birth certificate, right? Because that doesn't mean the same thing. If you, you know, obese patients also base accelerated aging. This is what we're seeing. All these side effects from GLP1s are because if you if you have a high BMI and you're obese, you're metabolic dysfunctional, you don't just get type 2 diabetes, you get Alzheimer's sooner, cancer sooner, you're an accelerated aging phenotype. So someone of a high BMI is foot 40 is older than someone who's lean 40. That's just true. So therefore, if we could move these aging clocks into a way that they were clinically applicable, that's a use application, right? Then you go, we screen people based upon when they're hitting biological age 40. And then we're going to catch loads of people earlier, and also we're going to save lots of money not getting people later. So those things are coming and we need to get the robustness of the data. The problem is what's robust in a lab and what's robust data to get you a paper in nature with a small sample size is not the robustness that pharma needs. This is, you know, my lots of my friends who who study with me and went off to work in pharma, and endlessly they're taking biomarkers that came out of lab trials and pre-clinical trials, and they fall apart when you scale them. That's that's just known. That's right, right? That's how when you begin to put this in the real world, those markers fall apart. So what we shouldn't do in our urgency to age better is think that that's not going to be true for all these other biomarkers, right? When you scale something to the human population, it's noisy. So if you're basically doing experiments on yourself with biomarkers you got from Amazon, you're falling into this trap of thinking that what worked in a mouse will work in you. And that's not the case.

SPEAKER_00 58:14

Well, I think there's two there's two additional layers with some of the things that we see online. One you've just kind of inferred to, which is like, is there any actual human data for this thing? But the other thing I think we're starting to see a lot of is this like mechanism worship, like where just because something works mechanistically, that is going to work systemically like for me in this moment. And I think, you know, one of the things I'm most excited about in the space is that we're able to capture more data about me in this moment in a way that is fairly cheap now, right? We we weren't using CGMs like these continuous glucose monitors before or wearables even 10 years ago. And now we can capture all of this data about our sleep and our metabolic health and how much we're moving. So we can start applying that transitional layer with the help of some of these AI models. So that, you know, I think the the thing I would love to see, and we're trying to build ultimately is I just want to know when I wake up in the morning, what are the three things that I should do today that are going to be most impactful?

SPEAKER_01 59:20

Yeah.

SPEAKER_00 59:20

I don't want to have to then go into five or six separate apps and track a load of different wearables and monitors and my blood. I just want to know what to do. Right. And I think that is the real challenge for us right now because I I actually think, and curious to hear your perspective here, that the one danger of some of these progressions is that we are just over-optimizing or or over-analyzing, and we're just constantly on a screen or constantly tracking numbers, and then our whole entire sort of mood or um energy levels shift based on a perspective of something.

SPEAKER_02 59:56

I mean, definitely I fall into the trap of you wake up, you're feeling great. I think I slept well. Then I look at one of the barrels and I'm like told I didn't. And then I'm like, well, do I believe me or the or the app, right? And actually, you know, some of our sleep scientists would say the best way to work out if you slept well is self-reporting. It doesn't really matter what those things are. So I think there's definitely an element of, and it's this battle between to get to a point where we can tell you what you should do. We need to know everything about you, which needs data. But constantly looking at the data as if it's tea leaves and panicking about it is not gonna, it's like so it's this complete paradox, right? So it's kind of you're stuck in this catch 22. That gets back to like how we need the data to do this, but we need to then work out how to use it. And honestly, it gets back to that's not up to us as an individual. It's not up to me as a scientist, even to work out all the data for myself. It's up to those domains to do it. We get experts, right? We don't try generally in life, if we need something fixed, we don't need to understand how the TV works. We trust the person who made it was an expert in that, right? We don't try to be our own expert in everything. To give go back a bit to your point about this kind of desperation to scale from mechanism. I'll give you an example that makes me nervous from the research I do in my lab. So I'm very interested in metabolic regulation, metabolic flexibility, how our body sense when we're moving between feeding and fasting, what senses that change, how that can lead to aging, and then how that goes wrong with time, right? And so one of the central nutrient sensors, which you've probably heard about in that domain, is called mTOR, right? MTORC1. So this is what rapamycin turns down. So mTOR is this kinase. That doesn't matter what that is, it's a it's a protein in your body, which whose job is to drive growth in your cells. So when you're eating lots of food, it senses those nutrients, mainly protein and growth factors, and it turns on and it goes, got lots of food, going to turn on, gonna make lots of growth. And then when the food goes away, it turns off, right? So it's a dynamic thing that turns on on and off in response to the environment and it regulates growth. It makes your cells be big or small, your tissues be big and small. It's why it drives anabolism, right? It's an anabolic thing, it drives growth.

SPEAKER_00 1:01:58

Wait, just to explain anabolism.

SPEAKER_02 1:01:59

Anabolism is basically what I thought if from a muscle physical point. So basically you're it's not just me listening to it. That's true, it's true, sorry. I just hear we're in your we're in your fireside chat, it's in your living room. I just told them you. So you're when you're your metabolic state at its most broad is either building something or it's breaking something down, right? So it's either building, storing nutrients and building muscle or putting fat down. That's called anabolic growth, it's building things, or it's using those things and it's taking things apart, and that's catabolic growth, right? So at its most broad, when when you're feeding, you're either using those nutrients for energy or you're not, you're using them to build parts of your body. That's anabolism. MTOR does that. When you're not growing, you either need those fuels, so you break those things down, you break down lipid stores. If you run out of lipids, you'll break down muscle, right? You'll use those that's catabolic and A and BK does that. It's the other thing we work on. But this needs to be regulated at the level so your body knows what do I do with the food I'm getting, right? We've known for ages, for 20 years now, that things like dietary restriction or intermittent fasting can make an animal in a lab age slower and live longer. And we know mechanistically a lot of that works through things like these nutrient sensors. So for instance, you can, with genetics or with a drug in a lab, turn down mTOR, turn down this builder in your cells, and the animal will live longer. You can also, on the converse, you can turn up AMBK, which is the thing that breaks things down, which is turned on when you if you exercise, it turns on if you fast. You can drug that protein, or you can turn it on genetically, and animals will live longer, right? So that's true. And it's kind of amazing. One of the most fundamental results in the aging field was taking this drug rapamycin, which through mechanisms you don't need to know, turns down the mTOR, turns down this builder. You give that to a mouse and they'll live a year longer or so, right? Really profound effects on lifespan. That's amazing. That means we've gone from understanding what dietary restriction does to some point, so how changes to food intake changes aging, to the things that sense the food, changing those directly to a drug we can feed the animal that changes those things and we can change aging. That's like radical. Does it mean we should all be taking rapamycin? The answer to that, I would say. So I'm someone who studies that for a living. This is in my domain of it. Do I take rapamycin? No, because what this thing is supposed to be doing in our bodies, a youthful looking mTOR complex is one which is dynamic. It's turning on and off all the time. You eat, it builds something, it turns on. You stop eating, it turns off, right? It's doing lots of things. If you drug it and just turn it down, that's not making a youthful version of that switch. It's breaking the switch, right? So that doesn't mean you're getting a youthful version of this thing. You've kind of just broken it differently. Just because it made an animal live longer than a mouse in a lab, those mice live longer, but they can't do some other things, right? They they have they get cataracts, they get some diseases. They also have some things they can't do. So to translate that research into humans, to go, could we use this drug to modify the aging process? Like it's amazingly exciting. And there are clinical trials now trying to work out how you do it. If you look at those studies or someone tells you, well, we know that rapamycin makes mice live 40% longer. This is how big a mouse is, this is the dose they gave a mouse. You're a big mouse, I'll give you that thing. Yeah. That's that's just not how it works, right? Because the thing that be many people don't know is what rapamycin is used for in the clinic is an immunosuppressant for people to get transplants, right? So if you get a lung transplant, you might be given rapamycin to suppress your immune system so you don't reject the lungs that you get from the donor, right? That's a very high dose of aging. But that's a side effect of rapamycin. When you start throwing that drug around, even at lower doses in people where one person is not like another, it is impossible to tell you with any certainty one, this is a dose that will work for you. Two, this is a dose that won't do you harm. In those mouse studies, some doses made them live longer, some that gave them cancer.

SPEAKER_00 1:05:58

But the but the headline. Is miracle molecule extended bystand.

SPEAKER_02 1:06:02

So you're stuck in this moment where, like, I'm someone who really works on this kinase. I believe that that is really a route to help healthy aging. I think we can do it. It's we need to understand it more. And if everybody rolls their eyes or a scientist goes, we just need more studies and more data. But that's still true. It like just because it's kind of the boring answer, it takes some more time, takes more investment, doesn't mean, just because that's not the answer you want, doesn't mean it's the actual truth of the answer. Sure. You've got to wait, what can we do in the meantime? There's ways you can maintain metabolic flexibility through diet and exercise. We can do those that don't break the system. This dynamism of metabolism, you can get through behavior, you can get through timing of maybe feeding, all these sort of things. We can do stuff now which is not as synthetic as a drug. So let's do those things well. Do you do time-restricted eating or fasting? You know, I'm I'm uh maybe a bad example. I I don't do stringent time-restricted feeding. I would say of all the kind of like things that are out there, right, in terms of these kind of fad diets, keto, whatever, I'm very interested and I believe in the science of circadian alignment, right? So I'm there are lots of good data now that show for humans that shift workers who like sleep at the wrong time of day, eat at the wrong time of day, get really kind of pathological problems, it's really bad for that for their body. I also really believe we know that when you eat nutrients will determine how well your body processes them, right? So the idea that we've gone from eating all our food in a short space of time, generally as we evolve, to now kind of waking up snacking 14 hours a day is clear, right, all of us. That clearly, I think, induced pathology. So from a conceptual point of view, that time restricted feeding will mean by work, will be beneficial health. I I believe that. So I do think about well, am I gonna like really eat first thing and eat late time? I don't do a stringent eight-hour window, but I'm mindful over letting my body not have nutrients for a good 12 hours of a day, whenever that would be.

SPEAKER_00 1:07:58

I don't do it in the routine I probably should. That feels like the easiest lift.

SPEAKER_02 1:08:01

Yeah, and it's like, and because I'm very interested, like talking, going back to those words anabolism and catabolism, I want my body to go from one to the other. So when you sleep when you're not eating, you want your body to move from burning sugar to burning carbohydrate, to burning fat, right? We can measure that in people, we can measure it in labs, we can show it's called really metabolic flexibility, moving from burning carbohydrates to fat. You want your body to move between those two states and to enable it to know how to do it, right? So your mitochondria, which are the things in your body which burn fat, if they're never doing it, they kind of lose the capacity to do it. So I I don't do it really strictly. I might probably should in many ways. I don't think we're quite, you know, some of our scientists disagree at the moment where we could say there is the best time restrictive feeding diet for everybody we know.

SPEAKER_00 1:08:47

Yeah.

SPEAKER_02 1:08:47

I I would love to do the research. We're trying to write the grant to do it, and maybe we could do something one health two, where we go, if we knew a lot about you, your circadian biology, which is different from just like whether you feel like you're a morning or an evening person, like what is your circadian clock really on?

SPEAKER_03 1:09:01

Yeah.

SPEAKER_02 1:09:02

How can we align what you do with the state that your body's in? And if we did that, would you see better outcomes? That's the research that I want to do, whether we do it here or we do it elsewhere. And I think we're just getting to those things. So I don't do it as well as I should, but I certainly do think that it makes so much sense biologically that having a like, you know, body has to learn what it's being exposed to. So these kind of ideas of sleep roughly at the same time, eat roughly at the same time, don't eat all the time, you know, giving your body a sense to expect what's going to happen to it enables it to do those things better.

SPEAKER_00 1:09:34

And that to me, you know, well, I think that's actually kind of the most exciting thing about capturing data about you in more resolution, is you get to then decide based on information. Right. And I think we we base a lot of the things we do for our health on opinion, and that opinion is easily manipulated by the thing the the media we consume, the people we spend time with, um, our historical perspective on what we've done that's worked in the past.

SPEAKER_01 1:09:59

Yeah.

SPEAKER_00 1:10:00

Whereas very soon, if not already, we can start basing it in data.

SPEAKER_01 1:10:04

Yeah.

SPEAKER_00 1:10:04

And then we get to make the decision. Because we spoke about this with a scientist yesterday. Yeah. Is there an optimal time for you to exercise each day? Probably. Right. But does that mean it's the most practical for you if you're a single mum with two kids that's trying to run a business that has only 20 minutes?

SPEAKER_02 1:10:20

And it's also what's optimal. Is it optimal for the same amount of exercise creates more muscle mass or less, depending on when you do it, which is like, okay, that's one thing. Or is it the cardiovascular effects of both are different?

SPEAKER_00 1:10:30

Like this different answer says, look like to you, yeah.

SPEAKER_02 1:10:32

So it gets back to like the data. So no one data point in isolation means anything, right? So if you were to say your blood sugar is this, it actually means nothing unless you know what you just did, right? So, like, so so when we wear these continuous glucose monitors, right? The idea that they should be completely flat all the time, I think doesn't really make much sense to me. But like you eat sugar, you burn it, you use that fuel, your body needs carbohydrates to do it. It's more how quickly you return to baseline, right? So there's a dynamic range, your your sugar should peak and it should come back down. If you're metabolically fit, it will do that fast. If you're not, it'll go up and it'll stay up for ages. The same we talked about this the other day about stress, right? We talk about cortisol. And you can measure your cortisol maybe in the like apps that you can do it. Again, you could go somewhere, send off your saliva, how much cortisol. Well, how do you know if that's good or bad? If you are, that's kind of fight or flight. If you're if you're in the military or you are someone who's really, you know, has to do something where you have to have a fight or flight response, your cortisol levels peak really fast, like exceptionally high, because it gets what you've all through. You do it, they come straight back down again really fast, right? So, of course, if you would take one level of cortisol for someone who's like trained to like go up and come down, so you stress them, they respond to stress to enable the body to do it, it goes up. But the what's bad for you is that your stress level is going up and it stays up. So cortisol peaks and stays, that leads to inflammation, these things. So the data don't mean anything unless you know the context, unless you know the dynamic range. So you need to have it through the day in many ways. What we're trying to do at Wonder Health is go, okay, we'll measure your cortisol levels now. Then we'll get Sam to stick you on the treadmill and stress the heck out of you and do a VO2 max is really our idea of stress. And then we'll take it and it should go up, and then we'll keep measuring it, see how it comes down again. And that gives you a sense of your body's capacity to respond, right? And that's the dynamic range of your body. And that is something we can get with data. And we can do that across these different methods.

SPEAKER_00 1:12:23

But do you then think that the value isn't just in doing like a deep phenotyping, deep baseline data? It's then doing that more often. Yeah. Right.

SPEAKER_02 1:12:31

And so, you know, what's changing?

SPEAKER_00 1:12:37

Is that like in a silo, like on their own, yeah, they could probably be misleading, right?

SPEAKER_02 1:12:43

Absolutely. And so even these omics, right? We're talking about, you know, come in and we can take a blood draw, we can do all these omics. Is that ideally you'd like a world where you could study those across the course of the day, across right? We're not there yet, but technology will get there with time, where you could really go, some of the things we measure are naturally they have circadian rhythm. They go up and down in response to different things. So that when you capture, what happens to your body before you capture is important data. And then also, if we did that again to you after six months of doing the things we advise, will your body respond differently? Will it respond better? We can begin to get that. And that's what's really exciting about combining these domains, right? So it's really just not isolation that okay, we can assess you in all these different levels in this steady state. Ideally, we could do it in a state where we moved you out of that steady state and see what happens. And then we can say, okay, your body actually has a dynamic range of this and it can move back to baseline normally. That's what homeostasis is. That's what's being being good is is like how quickly you can return back to base level. So it's not the level itself, it's the flux of the thing. It's how quickly you go away from the domain and come back. So we can get there, but it needs again, just gets back to it. It needs a lot of numbers, a lot of a lot of work to do it. And but I think we're so on the threshold of doing that. I mean, you and I have seen things recently about ways you might want to. It's coming. And that's so exciting. And that the, but you never want to be the kind of scientist who goes, like, it's coming, guys, just wait, right? You know, people need to know, well, what do I do now? And I think that's where we can really help give there's really good things you can do now to get you in a better state to take advantage of what's coming later, right? That's right.

SPEAKER_00 1:14:12

Okay, then Lil Mare. Give us three of those things.

SPEAKER_02 1:14:15

Three things you should really do now. Well, this is where you get me in trouble because I'm like, well, I'm not a clinician like that.

SPEAKER_00 1:14:21

So I mean, I so I I think these are three things that you would do for yourself.

SPEAKER_02 1:14:26

There are things that I really do now. So one, I would say I shouldn't say this probably on camera. I work less hard than I used to, probably not to you. What less hard than I used to, right? So I think there was a world where I was just like, I will work all evening, all night, all weekend, and I'm just driving and driving because my definition of success is like winning this race to be whatever the world's best in what domain I want to do. I think about eight years ago, nine years ago, I was just like, is this is is this helping me? Am I doing these things better? Do I want to do it? So I just dialed it back a little bit. So I think one thing I've become better to do, and I think we can all do, is like out is when to push and when not to push. Right. Right. But our bodies, our brains, all these things. So that means, yeah, these boring things. Like sleep is important. Time with your, you know, if you are driven, driven, I mean, you're CEO of a company, right? You're pushing pretty hard to get this company to work. That requires sacrifices in your own life. You can do that for an amount of time, but if you really want to maintain your capacity to do that long term, you have to take a step back, right? So I'm much better now at taking time. I go, I try to put my life a bit in drawers. When I'm working, I'm really working hard, then I close that drawer and then I come back and open another one. Now I'm like with my kid and I'm doing these things. So I'm trying to be much more conscious about moving these things and valuing those in a certain way, which means sleep. Try, try to, I'm not good at really routine. I'm I'm always into change, I'm bad at getting routine, but trying to develop a routine around those things. So I think that's really important. I certainly think being at least cognizant of not just what you're putting in your body, but when you're doing it. And it's very easy, especially when you travel and stuff, to like kind of like constant snack. I'm in an airport, so I should just be eating because I'm here. And you go like, I didn't really need to have this breakfast at 8 a.m. that I never would have eaten normally. So trying to work out like what do I really need? I think I I'm much better now at listening to what I think my body needs, as opposed to just, well, I'm here and I'll do it. So I think that really thinking about not eating over, you know, more than a 10, 12 hour window, which is still quite a lot. You know, there are people in our science board who will say it's eight hours, it should be eight till four, whatever it will be, like great. But certainly it's very easy to go the other way and go, well, I get up at six in the morning, I eat, and then I'm kind of in it's and it I'm taking and then you're then you're eating over like 18 hours, right? So that's really bad. So I think trying to give my body some circadian pattern to know what to expect I do. I also really do kind of listen to data a little bit better, right? I'm a bit of a, you know, I like data from wearables. I move between different ones all the time because I'm always frustrated that none of them are as good as I want. So I'll wear one, I'll wear a different one. I like this app, I don't. So I don't, I'm not consistent what I do, but I do think at some point there are flags where you go, it's time for me to like not push, right? It's time for me to not work out too well, to not push my body because recovery is really important. The older I get, it's thinking, it's trying to do things a bit more strategically and go like, okay, you know, I would like battles. Yeah, I I would love to be someone who from the age of 20 worked out all the time, but I I didn't. I grew up in, you know, I went to college in England in the late 90s. This was not a good time for house.

SPEAKER_00 1:17:32

You weren't raving, weren't you?

SPEAKER_02 1:17:33

I well, you know, I'm not gonna go into what I was doing, but like, wasn't the best time. Doesn't mean I can't do it now, but like, you know, so exercise for me has to like you have to build back up to it. You know, I've got a kid on the way and had a kid six years ago. When that happened, you sacrifice a lot of stuff, your body falls apart, right? You can either then go, right, well, now because I can't run the 10k at the speed I could do before that, I'm not gonna run, or you forgive yourself a little bit and you go, I'm gonna get slowly back up to that thing. And I think that's what I'm much better at doing now is going to be.

SPEAKER_00 1:17:59

You did tell me off camera that you raced your six-year-old and you intentionally won. I didn't like it bothered.

SPEAKER_02 1:18:05

Up until that point, I'd always let him win, and I think that was good for his emotional state. And then I was like, This is time for reality now. This is time when it's my time to tell you the truth about this. I know I haven't told him about Father Christmas yet, but I have told him that I was faster than him. But I also was like, but we can take a bet over when you'll beat me, and I'm I'm a bit nervous it's not going to take that long. Yeah. So, you know, I did I did crush it. Maybe that's a lifestyle, it's crush the hopes and dreams of your six-year-olds and then and then make yourself feel good. Right? The joy I got at beating my six-year-olds in the line. It was, you know, had it been more than hope. No, it was a short distance race. I feel that if it's long distance, he might take me, which is a bit nerve-wracking.

SPEAKER_00 1:18:39

Yeah, but you know, anything over 60 yards, I think you'll touch.

SPEAKER_02 1:18:42

It's probably bad. There's an injury waiting to happen for you right there. But that is also, you know, that's a thing too. Like, you know, you know, when when I joined Wonder Health, I was like, okay, I'm gonna also use this to try and get myself back on a on a more ideal journey in my health. You can't go from zero to a hundred, right? There's things that people go, but you've got to go, well, actually, I've got to take into expect, you know, sometimes I've got to fly around the world, I've got to do these things, I'm gonna ramp this up slowly, I'm gonna be forgiving. I think that's one thing I really am much better at now to myself, is like I'm more forgiving than I used to be. And I used to be like, I've either got to be perfect to this thing. So I'll either do the perfect dive ages, lose loads of weight, and then when I break it, I'll throw it away, or I'll train for a half marathon, I'll do that really well, and then I'll stop, and then I won't do it again. There's a lot of that I think a lot of us have suffer from these things. Like, I've got to be get, I've got to be the best or nothing at my discipline. And it's hard to do function on every level like that. Something has to give. And then you're just like, well, if I wanna be the best in my domain and professionally, I can't also be spending all these.

SPEAKER_00 1:19:43

And so now I'm just like, well one big takeaway I'd like people to, you know, get from listening to the podcast in general is to be a bit more forgiving, to not be as hard on yourself because it's complicated and it's nuanced and it's layered, and we're, you know, we're made to feel like we're failing so often when we listen to, you know, social media or any any kind of media when we and as we've touched on, there are so many different ways of approaching this, and everyone's trying to sort of push that silver bullet. And I think that is um, it's difficult to navigate.

SPEAKER_02 1:20:14

Yeah, and I think, you know, that's also sure. I mean, one thing I did, I I thought a lot about, we hear about social connectedness, right? So I think that now we hear more and more being connected, being an optimist is good for your health. But or being optimistic, right? If someone's really pessimistic, you can't just go be an optimist, right? That's the you just can't, yeah, you can't just flip that switch, right? So you can't just tell someone this is what perfect looks like, do it. And even for social engagement, go, well, you should be really socially engaged. Well, if you if you're not, it's hard to just change that. But one thing you can do, this is one thing I did actually a few years ago, is listening to some podcasts around this, is like I think men particularly, as we get older, desert our friend groups, right? We have these friends that we still keep in touch with when we see them, but we but we just kind of whatever, we go to the pub, we watch a football game, we do it, and then we don't ever talk between those times. We put a lot of our social connectedness onto our partners and we don't need it. So I just reached out to some of my best friends from college who I've known for 30 years, about four years ago. I was like, there's things about happening in my life that you don't know, right? I it's been through a divorce, they didn't even really know. Like professionally these things about my health. Like, we don't ever talk to each other about everything. I don't think this is really good. Do you want to just meet on a Zoom? Because we live in different countries, like every few months to chat about stuff. And it was quite vulnerable to do that and go, like, I just want to like, can we just be slightly better friends?

SPEAKER_00 1:21:32

Yeah, we're not very good at that.

SPEAKER_02 1:21:33

No, but they all like, yes, please. And we began to do it and we called it this kind of Maui thing because there's this idea that in Okinawa or people in Japan where people live really long, one of the reasons they live for a long time is social connectedness because they're kind of put into these social groups, like synthetically when they're young with kind of strangers and they meet all the time and they kind of share burdens. And so we tried to do that. And do we keep it all the time? No, does it end up just go we end up talking about fancy football? A little bit, but like to try and go to your friends, actually, which women do much better than guys, actually, you know, my blood pressure's high, and I'm on a you know, those things, or like I'm struggling with this job. And so I've begun to do those in a way which it which again is admitting fallibility, like you know, the vulnerability, like really, actually, it's not all perfect.

SPEAKER_00 1:22:15

Hey, well, if you ever need to zoom call someone, I'm heavy.

SPEAKER_02 1:22:18

I hate Zoom though. Can we do it? We'll do it in person. Okay, you know, I think we'll do another episode. But it is really true, but it gets like when we're making advice to people, yeah, even these like obvious things, like you have to give people tools to also do it. You can't just say like be optimistic or be connected, you've got to go, where are you now? How would you begin to build these bridges? And again, there are expert frameworks of how to do that better, right?

SPEAKER_00 1:22:42

And they're and I think even when you know what those frameworks are, when you pull back the curtain, all of us are struggling with the same problems. Yeah, right. And so, like, it's an it's this is a forever game.

SPEAKER_02 1:22:52

Yeah, and and it's just like, and and what we're doing here is going like, there's no point if you're just if you're focused just on your aerobic capacity, yeah, but you've forgotten all these other things, they're connected, they all pack the same biology. There's no point in doing that. If you are, you know, running two hours a day and do these things, but you're sleeping three hours a night because that's how you crush your job and find time to do all these things, you're losing the benefit. You're adding on one hand, you're taking away with the other, right?

SPEAKER_00 1:23:17

So we're missing out on a lot of upside there.

SPEAKER_02 1:23:20

And some of those things which seemed a bit kind of soft and and like a bit kind of like like connectedness or sleep or just kind of this more wellness, joy. Now where it says that not only is that real science, but we can show that it affects the same things, the same numbers, right? It can affect, and that is incredible. I think that's where the science of kind of healthy aging more generally is now, that it was nowhere near five years ago. And that's what's super cool. So like I like this low-hanging fruit for you.

SPEAKER_00 1:23:45

What time to be alive, Will.

SPEAKER_02 1:23:46

What a time to stay alive.

SPEAKER_00 1:23:48

Hey, I'm gonna ask you some quick fire questions now because I could talk to you for hours, um, and I don't want to take up all your time. That's right. So don't give me a real long monologue for these answers. Okay, and I know that that's gonna be tough because you don't want to oversimplify, but you have to for the purpose of this segment.

SPEAKER_01 1:24:07

Right.

SPEAKER_00 1:24:08

Um, so name one thing that you think we are overhyping in the longevity space.

SPEAKER_01 1:24:18

Peptides.

SPEAKER_00 1:24:20

If you weren't studying the biology of aging, what other domain of of science would you like to study?

SPEAKER_02 1:24:28

None, I'd be a journalist. I I really yeah. I mean, I um I I think to do anything really well, this is this is a long-winded answer. To do anything really well, you've got to love it. Like, I love the stuff that my lab studies. I love I we don't translate stuff to humans in my lab, we're not trying to humans that I love the way we do it. It is an absolute passion project of mine. I still get as excited now as I did when I was 20. You couldn't get me excited about a different bit of biology. I could get excited about lots of different things. I don't want to work in pharma because I don't want to do drug development. So, any advice for generally for life is like find your thing that you love and push on it. Yeah, so the biology of aging to me is so exciting that I only want to study that for a biologist. If I wasn't doing that, I might be doing something in that space around policy or something because I really think it has the biggest capacity to affect human health and suffering of anything almost in things that we're not thinking about really well. Um, and also I'd probably pick something else. So, like, don't make me study something else.

SPEAKER_00 1:25:23

I'm not gonna make you do any of it. Um, that was a long answer though to a quick fire question. Um what do you think we look back on in 20 years' time and say, I can't believe we used to believe that or do that to our bodies?

SPEAKER_02 1:25:37

Um depressingly, I I think it might be alcohol. Like I, you know, and I'm someone who likes a drink, but when I think about where we really go with that, not just how it affects our physiology, but how it affects our metabolism, right? So that we we have just enabled basically this toxin that we've all used and that we love, but has huge effects on our on our metabolic state. I think that might be a thing, but maybe we'll replace some of the joys of it. I'd hope that we found a way to get the benefits without the detriments, but it might be that one, I think.

SPEAKER_00 1:26:09

Sadly, I tend to agree. Yeah. Will if money were no object, you had unlimited resources, what would you research next or study next in the lab?

SPEAKER_02 1:26:19

Um, I would really try to study ways to maintain metabolic flexibility. So really mimic the dynamism of metabolic systems in youthfulness and maintain that in old age. I think that's a kind of a like how you do that is hard, but I really at heart, my quick fire, but my central thesis is that metabolic dysfunction lies at the heart of all of aging and aging-related conditions, and metabolism is a dynamic process. And so trying to find ways to main that di that maintain that dynamism, and I don't think we do that well at all. Sounds expensive. Sounds expensive.

SPEAKER_00 1:26:50

How has studying the biology of aging changed your own perspective on mortality?

SPEAKER_02 1:26:57

It makes me think about it a lot. So I I you know I didn't go into aging too because I was scared of aging or to live forever. I've experienced and met lots of people who do that, right? So what's it's made me really think about how aging is such a um driver of human emotion and fear in different ways for people, I find it fascinating. So for me, it's made me question some of humans' beliefs about aging, right? So I think I I don't believe aging by definition is inevitable, like just it has to be, right? I think it and that concept I'm very comfortable with. It doesn't mean I think we can live to a thousand or be immortal, but it makes me think about aging as this um intersection between biology and health and like the human condition. And I think about that a lot because it could because whenever you uh go out into the world and talk about it, someone has a really strong response. And if I'd worked in a different domain, if I'd worked in a disease, people don't have that sort of response, they just want you to cure it. So, what's been so interesting working in this field and seeing how It's changed and seeing how it moves in is that you can't just go out there and take it out of context with what the people are thinking about, right? Lots of people have for religious reasons or have or just general kind of social reasons have very strong concepts about what aging means, that aging is a good thing, that whatever. And so to begin to have a conversation about the science, you've got to understand the kind of the psychosocial piece about how humans think about it, which is so fascinating to me. So I think that's one thing I didn't really consider when I went into it, that it just generates this gutteral response in people and that makes them challenge them. And often you find people have never really thought about it. Yeah, yeah.

SPEAKER_00 1:28:39

That's it.

SPEAKER_02 1:28:39

They've never, they've never really thought you when you say, like, why does aging exist? They'll just be saying these things off the top of the head. And then when you push, you're like, okay, but like, have you really and we don't. What's amazing to me is like this thing that happens to all of us that actually we on one level we think about all the time. We actually don't think about with any depth, any intellectual depth at all. And like to be able to really, really study it and to really translate that into policy or biology. And I there's lots of people in my field who I think don't fully understand evolutionary biology at all. And so therefore are making incorrect choices about how they study the problem. So to me, it's been a really interesting field because it is just like it always gives you a debating topic, it invokes strong responses either in the science, which has been polarizing from the start, endless fights in the aging fair, whatever stuff. Now in policy, and I think that's so interesting to me. So it's enabled me to be a scientist, but also have this kind of other piece to what you're doing. Yeah.

SPEAKER_00 1:29:35

What's the best bit of advice you've ever been given?

SPEAKER_02 1:29:39

Um I think know when to learn and know when to teach. So know when to kind of like listen to people, like know when you know less than the person that you're listening to and to listen to them and learn from them, and also know in a room, no matter if someone's speaking with confidence, when you know more than them and you should you should teach them.

SPEAKER_00 1:29:56

I love that way.

SPEAKER_02 1:29:57

So judging that.

SPEAKER_00 1:29:58

That's a great mic drop moment, but I'm gonna squeeze out one more question.

SPEAKER_02 1:30:01

Okay, do it.

SPEAKER_00 1:30:02

You have 10 minutes a day to optimize your health. What do you prioritize?

SPEAKER_02 1:30:07

Hanging out with my kid.

SPEAKER_00 1:30:08

Love it. Will Mayor