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TRANSCRIPT:

*this transcript was mostly generated by AI, please excuse any mistakes

[00:00:00] Amanda Holmes: I have lived a very healthy life. I don’t drink, I don’t smoke, I am a vegetarian by choice, I meditate a ton, but I also run my business like a freight train, right? And I work like nobody’s business, I know how. But I also watched my father die at 55, knowing that he worked himself into his grave. So it’s very important to me to prioritize my health.

So then when I saw this. Test, come back and show me how, on a cellular level, the stress is causing me to age at a rapid rate. It’s a real wake up call, I think, to quantify it and then to know that you can actually do something about it is remarkable. Here is your daily dose of the Ultimate Sales Machine, coming to you from the new edition.

Visit ultimate sales machine. com to get your copy or multiple copies. I am your host, Amanda Holmes, CEO of Chet Holmes International. What you’re about to learn has assisted a quarter of a million businesses to generate billions of dollars working faster, better, smarter. Welcome, everyone, to the CEO Mastery Show, and I’m so excited to have Ryan Smith here.

So, I have to say that I was going through a whole biohacking, understanding what’s going on with my health. I was having some I have some problems with headaches and I wanted to better understand. And one of the things that my functional medicine doctor said was that you should probably think about an epigenetics test.

And I had learned from a client that we had last year, Regenerative Medicine Institute. They are a stem cell clinic, so I learned so much. so much more about this whole thing of biological and chronological age, and I had wanted to know it. So I was so excited, I checked the boxes and said, yes, I have to know about this.

And it was fascinating to get back the data. And I just think it would be stealing from my audiences if I didn’t share how fascinating this is and what the bleeding edge of science has for us to better understand our likelihood And our risk factors for getting disease or even premature death. I mean, what we’ve come up with in the last decade is just absolutely absurd.

So I brought on Ryan! to be able to share a bit more of this for everybody because I think everyone would like to know how to live longer and healthier in that lifespan. So thank you, Ryan.

[00:02:23] Ryan Smith: Yeah, thanks so much for having me. I’m excited to be on. I think I certainly share your enthusiasm. I think for what we can do in this aging field and why now is the perfect time to be having this discussion, due to all the new developments that are happening in the scientific field.

[00:02:37] Amanda Holmes: So how did you get to be the CEO of an epigenetics business?

[00:02:43] Ryan Smith: Yeah. Well, yeah, you know, uh, we’ll talk about my chronologic versus biological age, uh, you know, the other day, but yeah, I know it’s been a long and winding road, you know, my My initial sort of background has always been in science and interest in science.

I was a biochem major, went to medical school at the University of Kentucky, passed my step one, which is really the first two years of the sort of education required, but got to the clinical portion of my third year and just hated it. So I decided to make, The, you know, sort of at the time, very stupid financial decision to quit and explore something else.

So I created a business, a compounding pharmacy that specialized in peptides and proteins. And so we started a little bit of what this peptide revolution had been. We created, you know, we’re the fourth fastest growing company in healthcare. And from me to over 250 employees within three years, that business, it was massive growth, really hitting a niche where I was introduced to this world of integrative medicine and functional medicine, preventative medicine, or, you know, in bioad.

I was so interested. It loves the concept. If I had known that that world of medicine existed, I might’ve stayed in med school, but I think that, you know, I was really introduced to it and it captured my art. But one of the other things is we were doing a lot of really innovative peptide treatments, and I was always looking for a measuring stick.

Stick for those treatments, right? Seeing what actually work and what didn’t. But also realize the big problem there is that we can all do a sort of an end of one analysis, but to really know what’s working for everyone. It’d be great to have a tool where we didn’t have to wait 30 or 40 years to see what was happening with these outcomes.

But if we could predict what was happening in these outcomes, that would be a really, really great tool to use. So I got really familiarized and and the rest of the needs to be. These epigenetic clocks, which are just coming out at the time. Um, and then got really so excited about it. We decided to sell the business and really create you diagnostic in 2020.

We started that process and launched in July of 2020. So now we’re a little over four years old and have learned so much about aging. That’s so much about the DNA methylation as a biomarker. And I think really changing the way that we treat aging or think about aging.

[00:04:38] Amanda Holmes: Wow. So tell me, I am interested in this concept of epigenetics.

What is it? Right? We get blood work done. The doctors look and say, you’re in between these intervals. So you need to look at this. But what is epigenetics actually studying? And how quick can it change?

[00:04:56] Ryan Smith: It’s a good question. So first, I’ll go into the definition of epigenetics. Generally, epi, you know, sort of means above the genome, right?

So we’re talking about changes. Which happen to affect your gene expression. So the way I like to generally explain this is that everyone knows about DNA. Everyone knows that every cell in your body has the same DNA and it’s unique to you, right? So if you’re testing your skin or your blood or your brain, it’s all the same DNA sequence.

But it’s obviously very clear that our cells oftentimes behave differently, right? Our brain is behaving very differently than our heart. And the way that it does this is by what genes it actually turns on or off. You know, it, it, they’ve all got the same instructions, but they’re using sort of the same hardware, but different software, right?

Where you have the, the same possible options, but what is actually happening is based on how we, we use those options, right? Or how much we turn, turn them off. And so that’s what epigenetics really is. The regulation of that genomic baseline information, and that can be really informative to us as we’re looking at how cells behave and what they should be doing versus what they are doing.

And to answer your question about how quickly this does this change frequently, we have over 29 million of these methylation locations that we look at in a cell, and every cell is different. So we’re talking about Massive data permutations that can be changed by how much sleep we got, you know, what we’re eating and drinking, you know, our social interactions, there’s a, everything can impact this.

And so what we’re trying to do at our company is to really create with artificial intelligence, ways to read that data pattern and ways to read and interpret it so we can actually use that information to better improve our health.

[00:06:33] Amanda Holmes: Can you give me an example of epigenetics turning on or turning off?

What does that look like in a human being in a real life scenario?

[00:06:42] Ryan Smith: Yeah, so it can be very complicated because you know, we don’t necessarily on or off is not necessarily good or bad But the first ever example that we get is with stem cells, right? We all start off as a stem cell, you know, we can we start as a germline cell And from that cell, we can become any other type of cell, right?

So we’re going from a pluripotent stem cell that can become anything, to an actual cell type that needs to become something to do what we need to do, right? We need skin cells to become and behave like skin cells. And we need our heart cells to behave like heart cells. And so the way that that’s actually done is by what genes are turned on and turned off.

So, it’s like, For instance, you might express, you know, a lot of things for college and cross linking in your skin cells that you don’t want to be in other areas of the body to have that same genotype. So the first thing that happens is, as we’re growing and being born, ourselves are differentiating by the on off switches.

So that’s the first example. But there are also some really good examples for things like oncogenes or cancer versus tumor suppressor genes. So some people might get cancer because their oncogenes, too, that might cause growth. are less methylated. That DNA methylation is what we’re checking, and if it’s less turned off, then that process of growth is accelerated.

That happens in cancer cells all the time. Also, we have protective things like tumor suppressor genes that we really want activated. So we do not want those methylated necessarily. We want our tumors to be suppressed, that gene to always be turned on. But sometimes it can get turned off. Turned off. And if it does, we’re not able to catch or or kill cancers in our own bodies as frequently.

So there’s a lot of different options on how this comes to be. But, you know, we’ve got, like I said, lots of places that this can happen.

[00:08:19] Amanda Holmes: So I know for my own test, in my test, the results came back and said that I was, I had a high likelihood that I could get leukemia. And that was what my father died of.

So obviously your past came with a lot of tears for me. Very upsetting. But, and as I told some people that I love that this happened, they, I saw a divide of people saying, I’d want to know that, or I just wouldn’t even want to know. So what’s your argument for why people should want to know?

[00:08:54] Ryan Smith: Yeah, and that’s the beauty.

That’s the beauty of what we’re doing is that epigenetics is modifiable, right? If you take a genetic test, you know, for instance, you know, I’ve done my genome. Um, I have an APOE4 allele, right? Uh, that makes me at a much higher risk of developing Alzheimer’s. The question is, do I want to know that? And I probably do, but I’m not like everyone.

I want to make sure that I can, you know, try and take as much preparation or care as possible. But unfortunately, I can’t change that. I can only, you know, try and mitigate it. By my lifestyle and other things that I’m doing. The good thing about epigenetics is that it’s changeable. You can actually influence change.

You can control your own destiny. And that’s the beauty of it is that we’re able to just assess your outcomes, risk, and then hopefully help you change that risk for better outcomes.

[00:09:38] Amanda Holmes: So have you seen it? Cause I went online and I was looking at your social media and I saw people saying like, I’ve been taking this test for three years now, and I’m so amazed to see the results.

Can you give me examples of people that have been able to suppress or like turn whatever we’re using? Like if they have like a cancer likelihood or an Alzheimer’s likelihood, is there a certain degree of it that they can lessen over time and quantify that?

[00:10:10] Ryan Smith: Yeah, 100%. So many different, I would say, examples.

So, uh, but first I want to maybe take a step back and talk about what we really focus on, Deryn, which is quantifying that biological aging process, right? Yeah, and I think that that’s the best lens to show you some of those trajectories. We focus on biological aging because that’s really one of the The 1st areas that was looked at into these clocks, but it’s also 1 of the most important areas for our health.

And the reason for that is that your age is the number 1 risk factor for every chronic disease and not by a small margin. You know, I will share my screen. Green here just to show you a really quick figure, but I’ll explain it to you when he’s not able to see it on on the podcast or if you’re listening in, but these are the top three causes of death in 2020 COVID 19 is on here because obviously we’re at the height of the pandemic, but heart disease and cancer are always sort of the top two and we all know how bad smoking is, right?

We all know how bad obesity is for our health. We’ve been drilled for years on how those risk factors can increase our risk. But. You can see here that they pale in comparison to the relative risk of aging. Um, you know, uh, even, you know, for Alzheimer’s, for instance, 90 percent of the risk of Alzheimer’s is age.

So, um, and so if we’re really going to have an effect to reduce disease and death, especially In a preventative fashion, we’re helping people before they develop disease or death. One of the most important things we can actually look at is how you’re aging. And unfortunately, we all know that chronological age is not the best way to do this, right?

We know people, for instance, in their 60s who maybe look 40. And we know people in their 40s who maybe look 60. And this is a real phenomenon. And we know that This biological aging process measuring how an individual’s body is aging is much more predictive of that risk than just trying to ask them their birthday.

So we need a way to measure it and that’s really what we focused on first and foremost with a lot of our epigenetic algorithms is quantifying that process.

[00:12:07] Amanda Holmes: I think it’s so fascinating because I am very health conscious and I look much younger. Very often, I get 10 years younger than my age. It’s obnoxious.

You’re running a consulting firm where you’re paid for great hair. But, so I thought that my chronological age would come back saying that I was much younger, but it turned out it was actually the opposite. That I was much older. Interesting, yeah. Yeah, I was six years older than my chronological age. My biological age was six years older.

[00:12:39] Ryan Smith: Yeah.

[00:12:40] Amanda Holmes: Which was, again, shocking. And just for everybody that’s listening here, because I know that probably many of you are not experts in biohacking like Ryan, I mean, this is such a paradigm shift for when we go to the doctor today, we spend an average of 18 minutes with a doctor to determine what What needs to be solved and very often that ends with a prescription and we’re really just treating the disease that has already developed.

Whereas what’s so incredibly mind altering about this process that you’ve just said Ryan is the whole we’re preventing disease before it’s even happened. I mean, that’s just revolutionary if you think about it and that we handle our current medical system. So.

[00:13:27] Ryan Smith: Yeah, exactly. And that’s one of the biggest problems with our medical system is that in, you know, payers, right?

These insurance companies are only into to sort of pay a diagnosis or to reimburse drugs. So it’s sort of like all the money is going to the use case scenario where someone’s already sick. But it’s so much easier to prevent conditions and deterioration than to fix them. Once they’ve occurred, it’s much harder to reverse than it is to prevent in the first place.

So this is what we’re really trying to do by measuring, again, that biggest risk factor of aging. So going back, I think it’s your original question, which is, you know, can you give us some use cases? Um, absolutely. We’ve seen, you know, multiple interventions, reverse biological aging over a short amount of time.

And then as a result, reduce risk, right? Um, because we know that the younger your biological age, the lower your risk of all of these negative outcomes. And so probably the most famous and notable example is one of our users, Brian Johnson. Most people know him as another avid biohacker. He’s doing everything he can in longevity.

Whenever he first took our test, he was at a rate of aging of 1. 04, which means that he was aging basically over a year for every chronological year he aged. And now with his blueprint protocol and intervention, he’s aging at a rate of 0. 64, which means that he’s only aging 0. 64 biological years for every year.

And so he’s had a massive age reversal change, which then should certainly decrease his risk.

[00:14:48] Amanda Holmes: Wow. I remember when, when I was first taught the Dunedin pace of aging scale, it’s like, is it really just 0. 0 that makes all the difference? But if we think about it for everybody that’s listening, right, if we can actually track, we can now have the ability to track, Oh, a healthy living Can quantifiably prove within your cells, can you break that down just a little bit more of how you actually know whether someone is aging faster or slower?

[00:15:16] Ryan Smith: Well, so we need tools, right? We need tools to come up with a number because we need to, you basically, what we’re measuring in your DNA is So when we take a sample, we’re taking a small drop of blood. We just need it on a blood spot card. Then we’re taking it to our lab here in Kentucky. And what we do is we extract the DNA first.

And then we need to try and quantify how many of those locations in your DNA are methylated and at what percentage. So we’re looking at a big sample. about a million locations in your genome, and we’re getting basically a number between zero and one, right? We’re getting a percentage of methylation. How often is that gene methylated?

But that data needs to be read, right? And in order to read that data, we need a tool. So we create algorithms. I mean, these algorithms are meant to define a purpose. And so, for instance, we can create death predictors that predict time until death. But to do that, we need people who have taken a sample 30 or 40 years and then have proceeded to these outcomes.

Right? Have they proceeded to death? And if so, was it in 10 years or was it in 40 years? Right? And so that way we can signal who is most at risk for things like time until death. So we first have to create these algorithms, and this is a really important process because the true diagnostic, this is something that.

That we really try and emphasize these algorithms need to be published and validated by other people, other universities to make sure they work. Otherwise, it’s just sort of like magic, right? And we’re going to a fortune teller. You can choose to believe us, but it’s better if we show you. How good and accurate we are.

And so we always publish and validate all of our algorithms, but that’s how we create them. We usually are trying to predict a certain variable when we create artificial sort of mathematical formula to read the data input we’re getting from your genome and then outputting the thing that’s most relevant.

And in this case, that’s the rate of aging or biological age. And so, uh, where we’re taking those zeros and ones and then using a mathematical calculation to tell us about that output.

[00:17:05] Amanda Holmes: Well, I do find it really fascinating again, for everybody that’s listening. So, I have lived a very healthy life, I don’t drink, I don’t smoke, I am a vegetarian by choice, I meditate a ton, but I also run my business like a freight train, right, and I work like nobody’s business, I know how.

But I also watched my father die at 55, knowing that he worked himself into his grave. So it’s very important to me to prioritize my health. So then when I saw this test come back and show me how, on a cellular level, the stress is causing me to age at a rapid rate. It’s a real wake up call. I think to quantify it, and then to know that you can actually do something about it, is remarkable.

[00:17:54] Ryan Smith: Yeah, definitely. And now we’re getting resolution. We can even tell you the why you’re aging to some degree as well. So you can actually say what’s driving that process to make really precise recommendations on how to improve it. She even pulled up your report if you’d ever like to go through it, but I’ll give you an example of mine.

So, for instance, we were able to tell you individual resolution of things like your HbA1c or your fasting glucose or your albumin levels. And so we can actually sort of read that data to tell you where. You’re accelerated where you’re not. We also just released a new algorithm with Yale called symphony age and symphony age is able to tell you the age of each organ system.

So we can actually tell you what organ systems are aging well versus what organ systems are not aging as well. That way you can direct intervention to that particular orbit system. So I don’t know if you’ve got that data for yourself, but we can even go into that and say. So whenever I was looking at mine, you know, my inflammation was really high.

And so for me targeting inflammation as much as possible with, you know, the, the thing I tried to do the most, whereas my metabolic age, you know, my HBA1Cs and, and those type of biomarkers look great. So I didn’t need to worry about blood sugar. We might need to worry about those inflammatory processes.

So that are happening in my body and trying to target them. So there’s a lot of examples that, you know, that we could do to break down that individual resolution.

[00:19:04] Amanda Holmes: This is probably off the track a little bit, but I’m curious just from somebody that’s gone through your test, because the test tells you one thing, but it is good to have some kind of expert be able to give you that advice.

So, one thing is just understanding that you need to do these things, and then I’m excited. I have another kit in my fridge that Five months from now, I’m going to do another one to see if the, the protocol that I’m on is helping, but you recommend somebody to read that, right? Because

[00:19:32] Ryan Smith: I

[00:19:34] Amanda Holmes: don’t exactly know, like what you’re saying I think is fascinating and I don’t think that I grasped that from reading the test.

[00:19:41] Ryan Smith: One of the reasons we’ve never been a huge direct consumer company is because there’s so much detail that comes in in these reports that are really important. We tend to be very skeptical of someone who can just say, Hey, I can tell you your age. I can tell you what to do. You know, it’s a hard thing. If you go to these aging conferences and the best aging, you know, people in the world generally agree that we haven’t found the clear single best thing to reduce aging, or that we even can, you know, there’s still a lot of, you know, Uh, argument about can people actually live universally to 120.

And so I think that now we’re getting much more consensus on that in aging itself, which has been a huge focus in development, but it’s probably one of the fastest growing areas of scientific research and development. But with that being said, you need to be really adherent to the science. How are these tools created and what population, then what can they actually tell us?

And, and so it’s always helpful to go through with a medical provider because they can make some recommendations. They can read that data, probably with a little bit better context.

[00:20:37] Amanda Holmes: Okay. Okay. You said that you had some case studies. I would be curious to see what do you got for us?

[00:20:46] Ryan Smith: Yeah, so I think that probably the two most notable case studies are two studies that we’ve done.

One was a study done with Columbia. It’s called a calorie study where they basically did caloric restriction. And by caloric restriction we basically just mean eating fewer calories than you’re expending every day. And the reason that this is such an important study is because generally Everyone agrees that caloric restriction is the best way to improve biological aging process.

And, and so, caloric restriction has been proven now in many animals, and it’s just sort of, I would say, the gold standard in aging interventions. And so, in this calorie study, they did this over the course of two years, and what we were able to see is that actually the only clock, the only DNA methylation clock to measure biological aging, which shows significant reductions was that Dunedin pace clock, that rate of aging clock.

And so we know that it’s the most sensitive to change and really just a great way to measure the impact of things like caloric restriction. If you reduce your calories, you can certainly expect that Dunedin pace to change.

[00:21:44] Amanda Holmes: Wow. Fascinating. So do you normally recommend every six months to get a test to see, is that how quickly your epigenetics can change?

[00:21:55] Ryan Smith: Well, yeah, actually, in the second case study that we looked at, we saw change in as little as eight weeks. And so that study was actually described on sort of a Netflix documentary, which looked at that, the difference between vegan and, and, uh, sort of omnivore diets. And so in that study, we actually took 20 pairs of twins, identical twins.

We’ve got one twin on a vegan diet for eight weeks, and we put the other twin on sort of your standard American omnivore diet over the course of eight weeks. And even within eight weeks, we were able to show that. That, that vegan or omnivore group actually had reversals in that rate of aging, whereas the, the omnivore group continued on the same aging profile and pathway that they were going on.

So that’s certainly another good case example, and as little as eight weeks.

[00:22:36] Amanda Holmes: Okay. Little as eight weeks. Was that like 0. 001 percent difference in the pace of aging? I mean, what are we talking about here? I’m curious.

[00:22:44] Ryan Smith: Yeah. So the absolute change in the rate of aging was 0. 05. So, you know, people go from a rate of aging of one, go down to 0.

9. So basically getting back, you know, a 5 percent of their year, uh, essentially for every one chronological year.

[00:22:59] Amanda Holmes: Fascinating. In eight weeks and imagine what we do for eight weeks now.

[00:23:06] Ryan Smith: Yeah, yeah, certainly. We generally don’t recommend, you know, eight weeks unless you’re testing an intervention, right?

Unless you really want to see how a particular intervention works for you. But, but with that being said, usually we recommend once or twice a year to get an idea of what you’re doing and if you’re on the right trajectory. So it’s usually every six months or a year is what we generally recommend.

[00:23:25] Amanda Holmes: Fascinating. I, one of my clients actually still had productions. I just interviewed her. A few weeks ago, Rhiannon, and she was telling me that she was like nine years younger than her chronological age, and I was so jealous, but she does all the things, all the biohacking things you could possibly think of, so.

It made me feel like proof, like, oh, if I actually get better on track and use the data to quantify that what I’m doing is working, that there is hope for me to not die 62 percent faster than those that are my age, because at the moment, it’s a shocking first page of your document, you know? Like, you’re a little Yeah.

Dying prematurely is 62 percent higher than those of your age demographic. My god.

[00:24:10] Ryan Smith: It’s crazy. Yeah, yeah, definitely. But again, the good news is you can change it, right? That’s, it’s within your power to make those changes to improve it in a positive way. And now we’re really trying to find the toolkit. So going back to those interventional or case study examples, we’re about to release a study with Yale where we’ve actually looked at 75 different interventional studies on DNA methylation with, you know, things taken at a baseline and then then measurements taken at the outcome after a certain study or intervention has been applied.

So we’ve looked at everything from hyperbaric stem cells to exosomes to semalytics, just about everything you can imagine, diet and nutrition, metformin, rapamycin, all of these different interventions that are. You’re in the biohacking lexicon, so to speak. We have now looked at and measured with the same tools across these interventional data sets.

And so we really hope it’ll be, for lack of a better word, a blueprint to what works and what doesn’t and how we’re looking at this data.

[00:25:02] Amanda Holmes: As you were saying that, that also made me think, walking the halls of the biohacking conference, I heard a lot of people throw around the concept of biological and chronological age and getting that tested.

How do you know the test is actually doing? What you wanted to like, I trust yours, but there’s a lot out there that just say that they can do that in a very short period of time. And I don’t really understand the difference between those that maybe are not exactly doing that versus

[00:25:30] Ryan Smith: yeah, it’s a great question.

And one I love to talk about because it’s so important as a consumer. To be able to, I would say, uh, validate or understand these tests, right? Which one’s good, which one it’s bad. Um, but biological age has even been a concept since the 1920s. people were saying your biological age is your chronological age plus one year for every pack per day you smoked.

Right? And so at first it was really crude measurements, but over time we’ve gotten a lot more sophisticated. So I always like to go into the tools we use to tell if a biological age clock is good. The first tool is one I remarked on earlier. It needs to be published and validated, right? What we do with science is we publish these results so that other people can come in and look at them.

And so you want to make sure that 1st of a clock or a measurement of biological age has actually been validated and once it’s been out there, there are 2 other things that we like to look at. 1 is, it goes back to what we would consider about accuracy or precision, right? So, Whenever we’re testing a clock, we actually want to make sure that it’s predictive of outcomes, right?

Because that’s eventually why we’re using it. If it can tell us about what’s going to happen, then we know that it’s a good clock because it’s predicting those outcomes. So we measure those things called through hazard ratios. A hazard ratio is sort of a saying. If we have a baseline and then we have an exposed person, how much more or less at risk is that exposed person?

And so we define sort of a hazard ratio of one as being the standard. And then we, so for instance, and we talk about for every one biological year age increase, right? That would be our exposed. So if you’re one year older, we would be able to compare. What is your risk profile at one year older versus baseline, where your chronological age is the same as your biologic age?

We need to predict outcomes, right? We need to be able to show that we can predict outcomes. And these methylation clocks are definitively the best at predicting biological age outcomes. And in fact, our algorithms are the best in that category. And so I can always show this visually, in case it’s certainly helpful.

But That is really what we try and do is we try and show that it’s predictive. And so, for instance, for, you know, for every one standard deviation you would have, and that didn’t even pace. So if you’re, you know, one state of deviation above what is average, you would increase your risk of death by 64%. And so we know that it’s really, really predictive versus, unfortunately, some of the earlier DNA methylation clocks, like the Horvath clock, that would only be a relative 2 percent increased risk of death.

So which one’s more important? The one that predicts the 64%, right? And so that’s one of our best tools to say how good is a clock is, is it more predictive of outcomes than another? That’s the first piece. The second piece we use to validate these clocks is precision, and this has been a huge problem with these clocks back in the day, where, for instance, you could take a sample, and then we would take that sample and split it into five samples, and we would test that sample, you know, five different times.

In the early days, these biological age clocks could vary by up to 30%, meaning that, let’s just say that you’re, you know, 50 years of age. That is basically 30%. It’s 15 years, right? Um, on the exact same sample, which means that if you’re trying to test within a period of under 15 years, right? How do you know if that’s just noise of the measurement or actual change in your biology?

And the answer is you can’t. So now all of our tests have less than a 0. 5 percent variation on testing the exact same measure. So now they’re really, really precise. They’re accurate. We know we can trust the result, but we can also then trust that result have implications for your outcomes because it’s so predictive.

[00:28:59] Amanda Holmes: When was that, that it was a 15 year difference versus now it’s a 0. 5?

[00:29:04] Ryan Smith: It depends on the clock, but the first clock that ever came out was 2013 by Steve Horvath at UCLA. A lot of people thought that he would win a Nobel Prize for this, but, uh, and that clock is still the most widely validated clock. We know it still has associations with the disease, but much less associations and much less precision than some of the newer clocks.

So the newest way is with really high precision. only came out in a publication from Yale in 2022. So we’re talking about two years of biological aging that have had the precision we need to make sure this is useful.

[00:29:34] Amanda Holmes: And when I kept thinking this, where it said that I was 75 percent older than people of my age group, and I kept thinking, how many people 30s are actually taking this test?

Do you take from a bigger pool than just who have been your clientele? How do you get that data to measure?

[00:29:55] Ryan Smith: That’s a good question. So true diagnostics, we have the biggest DNA methylation data set of all time, bigger than any university, bigger than any government. So we’ve tested now over 100, 000 individuals.

So in addition to that, we’ve also tested in biobank cohorts like the Master General Brigham’s biobank from Harvard or the health and retirement data set. So we have a really University. The most data you could compare it to out of anyone. But with that being said, the cohorts you’re comparing to are also important, right?

Our cohort is a very healthy cohort. They’re all driven to us from positions. We’re We’re proactively preventing their aging or for people like yourselves who are incredibly driven to have the best aging and sort of health lifestyle you can. And so we’re sort of self selecting for the healthiest people right in our cohort.

So we might have the largest data set, but it’s also the healthiest data set comparison and versus, you know, we might go to Harvard biobank data set, which is coming from people who. Are getting their labs done while they’re in clinics, right? So those are people who are coming to clinics for a problem and probably more representative of the traditional population and data set.

And so on our reports, we report the data set population. Most of the time where the algorithm was created that way, the apples to apples comparison. So generally we’ll never compare to anyone less than a 10, 000 person data set, but we’ll sometimes compare you up to over a hundred thousand people.

[00:31:15] Amanda Holmes: Wow.

How fascinating. I’m so impressed. So when people want to go and try this out, where do you recommend they go?

[00:31:23] Ryan Smith: Yeah. So you can certainly ask your physician. So word of this for you and help you interpret it, but we also offer this testing, the direct to consumer as well. So you can always go to our website at True Diagnostic and order a kit.

Takes about two weeks for us to do the analysis, but then you’ll get a lot of information about how you’re aging. And I think that that’s a good start for most people.

[00:31:42] Amanda Holmes: I love it. Ryan, do you think that there’s anything else that needed to be covered that we didn’t CI mean, there’s so much to cover, . Oh

[00:31:50] Ryan Smith: my.

Yeah.

[00:31:52] Amanda Holmes: But if you de wrap it with, this is the last thing that you need to know. For those that don’t know much about biohacking or this whole concept is the first time they’ve ever heard of it.

[00:32:04] Ryan Smith: Yeah, I think that we’ve covered most of everything, but I do want to talk about one of the most exciting things in the space, um, just to get people, you know, really hopeful about what we can do in aging, if that’s okay, and that is, uh, so in 2012, the Nobel Prize was won because they could take any cell in your body and reset it back to a pluripotent stem cell.

It was won by, you know, things are called Yamanaka factors, growth factors, which can basically Turn yourselves back to their embryonic states. We are now starting to see that companies in the space are having incredible results with these factors where basically they can reset the epigenetic age of your cell to zero with some of these and as a result, even restore function that might have been deteriorated with age.

The best example is some work being done by David Sinclair at Harvard, where he’s been able to actually reverse blindness and mice that have had. Their vision lost. And so, you know, a few years ago, Jeff Milner created Altos labs, which actually, you know, hired people like Dr. Yamanaka to work in with the largest startup funding of all time, over 2.

2 billion to try and improve this aging. And so I really do think that aging is the hot topic. It is really exciting. And the developments we’re seeing in this space. Might have major impacts to the lives of us in even just the next few years. So I hope that everyone can get really excited about the work that’s being done here and just also see the importance of treating aging as a primary outcome.

[00:33:30] Amanda Holmes: Thank you so much. It’s so fascinating. I hope that everyone that hears this thing goes, there’s so much I need to learn here. I’m going to dive a bit deeper. Thank you, Ryan.

[00:33:40] Ryan Smith: Yeah. Thanks so much again for having

[00:33:42] Amanda Holmes: me. Make sure to get your copy or copies at theultimatesalesmachine. com there’s a lot of special bonuses that you can’t get going to Amazon.

So make sure you check it out at ultimate sales machine dot com.