¶ Epigenetic Clocks and Longevity Measurement
Welcome back to the Path of Longevity Show , and I'm your host , dr Robert Lufkin , and I've joined by my co-host , dr Steven Sitteroff . I'm excited to announce that our long-awaited book Lies I Taught in Medical School will finally be published by Ben Bella Books and distributed through Penguin Random House .
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And I'm very happy today to invite Ryan Smith , the founder of True Diagnostics , to join us today . He's also one of the founders of the pharmacy tailor-made compounding , which has become one of the fastest growing companies in the healthcare industry . Ryan , welcome to the program .
Yeah , thanks for having me , Dr Siddharath . It's great to be here .
Thank you , thank you . Let's get started by telling the audience a little bit about yourself and how you got into this field .
Yeah , certainly so . True Diagnostic is the company we founded , which really is a health data company and laboratory specializing in epigenetic methylation , biomarkers and diagnostics , and so that sounds obviously like a mouthful , and so my progression here has been really interesting . Biochemistry was my undergrad specialty , really specializing in peptides and proteins .
Then I went to medical school and passed my step one but absolutely hated the clinical portion , so decided to leave and do the entrepreneurial thing where we created tailor-made compounding , which was really a pharmacy that was specializing in this integrative , functional medicine space , looking at a lot of novel interventions , and one of the things we knew about these
novel interventions is they didn't have a lot of data .
So we're always looking for ways that we could look at the impacts of some of these really novel interventions , and really what came up then were these new inventions called these epigenetic clocks , and these were really ways to look at how , I would say , some of the biggest risk factors , which is aging from an individual , and how some of the things we were
using to treat aging in the pharmacy might be able to impact health span and lifespan .
And so I got really fascinated with these clocks so much so that it actually captivated almost my entire attention and decided to sort of sell the pharmacy in order to get to diagnostic and really jump into the world of epigenetic methylation biomarkers and really see how we can interpret those new biomarkers in the space of health , but particularly in the space of
longevity .
That's great and as a psychologist , I really appreciate the notion of measurement . When you start doing measurement in many respects , you really motivate people to pay attention because now they could see the impact of their behavior . So I really appreciate that approach . Ryan , tell us a little bit about your perspective on aging and longevity .
Certainly , and I think it mimics yours a little bit in terms of measuring the process , because most people think about aging as defined entirely by one number , which is their chronological age , and unfortunately , that is just not a great measurement , and I think people know this , or , I should say , have been accustomed to this for several years is everyone knows
people that are in their 50s that look like they're 70 , and then , vice versa , those people who are older and look very , very young . And so this difference , this phenotypic variation , is a good sign to us that we need a better way to measure that process , and not just , I would say , a better way , but also to expand on the reasons why .
One of the most important reasons why is aging itself is the biggest risk factor for almost every chronic disease in death , including chronological age . So if we can improve the measurement , we can also then improve how we treat it or the things that we can learn about treatments for this process .
And so that's really what captivated me with this initial introduction , but beyond that , I think , being able to get a lot of wide scale information on how your genes are actually behaving in the field of longevity and the dysfunction in your genetic expression that occurs with age is really , really fascinating , and so that's really what's grounded me here is we're at
true diagnostic . We've tried to create the best ways to measure that biological aging process through this very unique biomarker , and so I completely agree with you Testing is absolutely necessary so we can actually see change but also then learn what's the best at affecting that change .
So you referred to epigenetic clocks . Can you explain what an epigenetic clock is and perhaps give us a bit of a history of its development ?
Certainly and this has been a relatively complex topic with a lot of twists and turns over these past couple years Really , the first epigenetic clock started in 2013 by actually another UCLA faculty , Steve Horvath , and these clocks we're looking at this biomarker of epigenetic methylation . So before I go into those clocks , I really want to define what that is .
And so epigenetic methylation are basically markers on the DNA , which are essentially the off switch of DNA . By attaching these DNA methylation markers , you're really silencing a lot of gene transcription . So how these genes go from being just genetic information to RNA , which is then expressed into peptides and proteins .
And so the way that I generally explain this to people who are not in the field is every cell in your body has the exact same DNA . Whether we measured your heart or your skin or your hair . The same DNA sequence is found in all those tissues , but they obviously behave very , very differently .
Obviously , the skin is behaving much differently than the heart , and that's due to this epigenetic regulation what genes are turned off and turned on in each tissue .
And so by measuring these patterns , particularly in blood in 2013 , they saw a very strong correlation to someone's chronologic age , so much so that they could actually predict relatively closely really within four years someone's actual chronologic age , which was a very , very big development , because this is as I mentioned .
We know that aging is such an important factor in people's health , and this was a way to actually measure it from a diagnostic biomarker perspective in a way that was more accurate than most anything that had to occur to date , and at first this wasn't even used in a health care setting .
It was used to date refugees to see if they were adults or minors and then eligible for asylum , or they were used in forensics to see how old someone was , if they had DNA and a crime scene .
But what they really started to do once they looked at these large-scale meta-analyses is they saw that people who were older , with this testing , than their chronological age were at much more increased risk for negative health outcomes , and vice versa , those people who were younger than anticipated with this testing were protected from these negative health outcomes , and
so this was really exciting , because not only did we have a method to really now detect aging , but it wasn't just your age , it was also a biological age , one that was associated to these health care outcomes , and so that was a really big breakthrough that we could actually now measure the aging process in a biological manner rather than just a simply
chronological one , with very , very high accuracy and so in really high links to disease . And so this field has advanced several times over the last couple of years .
These algorithms have become more and more accurate , and even today we see new algorithms released almost on a six-month basis , which continue to improve the field , to really increase our resolution of what we're able to find in terms of these patterns and associations to disease .
So now , even though Dr Horvath had the first generation clocks , we're already on third generation clocks , which are even better and can even tell you a lot more about your individual aging status .
So what is the evidence that this methylation process of determining biological age actually relates to longevity ?
Certainly so . The way that these algorithms are created are really using computer learning and artificial intelligence , and so one important point to make is that these are not necessarily causal . We don't know if these patterns are a result of aging or if they're causing the aging process themselves , and that is one thing that we really hope to solve .
But once these algorithms are created , we always test them to see if they're effective at predicting aging and disease rates by looking in large cohorts , things like the Frampton-Hartz study cohort , the Nkianti study cohort , the health and retirement cohort and by looking at these we can sort of prove our hypothesis .
By measuring the aging rate , can we see that people who are at advanced aging are having worse outcomes , such as earlier death and more disease . And for those people who are younger than their anticipated age , can we have them be protected or live longer and be more disease-free ?
And the answer is we absolutely have proven that , and actually the way that we do that is by hazard ratios . So what is the likelihood of a particular event ? And then , if you're younger , what is your likelihood versus someone who is the exact same age , and vice versa ?
And with that we see that these hazard ratios , the ability to predict outcomes is better than any other measurement of biological aging . This includes things that are relatively well known , like telomeres , for instance , which have been measured for a long time but generally aren't that predictive of health care outcomes .
It even includes other biomarkers like proteomics or even metabolomic clocks , and so , in terms of all the biomarkers we can measure , it looks like epigenetic methylation is one of the most promising for this measurement process , and it's proven in those large-scale cohorts where we can look at what happened to these patients 50 or 60 years later .
That's great . It's interesting that it predicts better than telomere length .
Yeah , certainly . And actually to expand on this , we actually can turn these epigenetic methylation information into other surrogate predictors . So , for instance , we can actually now even predict telomere length just through the DNA methylation measurements .
And when we do do that , they have double the correlation to age and they're actually more predictive of almost every health care outcome , including time until death , coronary heart disease , et cetera . And so even our surrogate DNA methylation biomarkers can be very , very exciting .
And , as it relates to this inflamaging topic that you all are speaking on , we can actually even use DNA methylation to predict different types of inflammatory markers , like C-reactive protein or IL-6 or TNF-alpha . We can actually create surrogate markers just by reading that information .
And I think that's what's really exciting is that some of those earlier clocks , for instance , didn't have a lot of associations to different hallmarks of aging . So , for instance , the Orvath clock originally wasn't related to cellular senescence , for instance , but with DNA methylation we can actually predict surrogate markers of all of those hallmarks of aging .
So we can look at inflamaging , we can look at cellular senescence , we can look at how proteins are regulated or proteomic dysfunction , and that's really the larger thesis is that as our ability to read these DNA methylation patterns improves , the better that we can get at capturing the entirety of the very , very complex aging process and even create better and better
predictors , and not just that , but predictors of other disease statuses , independently of aging .
So you mentioned measuring inflammation .
¶ Epigenetic Clocks and Biological Age Advancements
Can you say a little bit more about that ?
Yeah , certainly so .
Some of the original clocks that were trained to predict the chronological age of a patient were really completely disassociated from the inflamaging process , and that doesn't really match up , because we know how important those inflammatory markers can be to degradation that we would call this aging process , and so we know that we needed to expand that definition of aging
and do that by improving the things that we're measuring , and so now we've created , by taking both DNA methylation measurements and those inflammatory marker measurements , we've been able to create predictors of those in one data set , and so right now we can read over , for instance , 150 different proteins just from DNA methylation , and I should mention that they're not
exactly quite as precise , they're not going to meet the gold standard of things like mass spectrometry , but the idea is that with all of this epigenetic data that we can get , and maybe even in the future at a very , very low cost , we can read out the functional environment of almost your entire body .
So we can predict your risk of multiple different diseases , multiple inflammatory markers , metabolites , your gut microbiome , all reading the patterns through DNA methylation .
And so now even some of the best aging algorithms , such as GrimmAge , have come out with a version twos , where some of the first steps in that process is to predict things like C-reactive protein or HB1C .
These markers that we know are very related to the health process , and by adding them into this larger biological age consideration we can get even better predictions of health outcomes . And so I'm talking , I think , really about two different processes . I don't want to confuse anyone who's listening .
One is the this idea of DNA methylation to predict biological age , and that is a process that's going to continue to develop .
But the way that we continue to develop is by adding more information to that very complex picture , and to do that we're creating other ways we can read those DNA methylation patterns to more appropriately capture all of those hallmarks of aging , including inflammatory markers .
So I guess this relates to the fact that you're at the third generation . Can you share any more detail about that progression from first , second and third ?
Absolutely , and this is actually one of my favorite topics to talk about right now , because I think that if people have had experience with these epigenic clocks they might have had in the past , especially in the early days , they might have had some experiences which were not quite optimal , and there have been some initial problems with these clocks which have now
been solved . So , for instance , one of the biggest issues has always been precision of these clocks , and the precision of these clocks have , at least originally , been very variable .
So up to 3.9 years of absolute error between a measurement , which means that your age you took it within the course of six months might change by four years , and you might not know if that's real aging related change in your body or if it's just noise of the measurement , and so a lot of times these big fluctuations have led people to be disillusioned with the
applicability of these clocks , and so one of the ways that that has been improved has been this precision of these clocks has been greatly enhanced over these past few years . Now , if we test the exact same sample , we usually have less than a 1% variance on that exact same sample .
So these are now much , much more precise , and and that , although that's not necessarily a generational algorithm perspective , it is definitely an important piece of improvement that's happened with these clocks . The other big improvement has been , as we mentioned , these generational improvements .
So the first generation clocks are defined as clocks that were trained to predict the chronological age of a patient and , as we've talked about we already know , chronological age is not the best way to measure , and so the better that these clocks got the closer to predicting your actual birth date . If we really wanted to know , we could just ask .
Right , we would need to spend several hundred dollars on testing , and so so the second generation of these clocks switch that paradigm and , instead of actually measuring just the chronological age or trying to predict that , they tried to predict a constellation of age related biomarkers , so , for instance , things like T or V , o 2 , max and lung measurements , or even
, you know , functional measurements like frailty , for instance , and those clocks became much , much better , and we know they're better because they were predicting disease better than those previous clocks .
And this leads to one of the other problems with some of those first generation clocks , which is whenever we applied them to known interventions that beneficially affect aging , such as caloric restriction , which has been really well validated in a multitude of animal species .
We actually saw that those first generation clocks went up whenever you applied caloric restriction , and that doesn't make a lot of sense because we know it's so well validated . So the second and third generation clocks the ones that have been trained on biological phenotypes behaved exactly like we would expect .
They actually went down as expected , and so this is important because we don't want people to implement these processes and have the error be so much they can't find out information or that they're measuring the wrong thing and they're getting the wrong information , and so we're actually the only commercial company in the market right now that's doing any second and
third generation clocks , and particularly the one that we pride ourselves on the most is a clock that was developed with with Duke in Columbia , called the Dunedin pace clock , and this doesn't output an age , but it outputs an instantaneous pace of aging , and it is by far the most accurate and the most predictive , and it's actually the only third generation clock
which has been trained on longitudinal samples , and we're looking at a lot of different patients over a lot of different points in their life .
It's actually like the same patients across their aging trajectory , and that's why it is so highly linked to some of these different health care outcomes , and and we're working on some other really exciting things as well but but these improvements have made epigenetic clocks really actually now applicable on an end of one personalized basis , where someone can take this
measurement , get an idea of where they're at , and and and also we can all improve our aging . There's no such thing as too low of a biological age , so we can all try and find what works for us .
You know , we both might take metformin , but my epigenetic aging rate might go up and yours might go down , and so we can get this information on what's actually working for us to reduce the these markers . And by reducing these markers , we know that we're also reducing our risk of disease and death better reliability of these tests is so important .
As you have indicated , you and I are talking about doing some research in looking at the impact of resilience on biological age and if we do , say , an eight week intervention before and after measurement , it's a problem if there's great variability reliability in the data that we get .
So the better we can get at being precise with a reading and a measurement , the more accurately we can determine whether a intervention makes a difference .
Certainly On that topic . I would be remiss if , while having you on the call in a public setting , I didn't emphasize the importance of some of those psychological impacts and things like emotional regulation and stress onto these clocks , and it's been one of the biggest things that I would recommend in terms of treatment .
Intervention is to improve things like your resilience and reduce things like your psychological stress . I was never a big fan of meditation or mindfulness or some of those other things . Before this testing , I was always asking myself is this mindfulness , is this meditation ? Is this right ?
But we've seen drastic reductions and there have been many studies linking resilience and emotional regulation and stress reduction to improvements in these processes . So we might talk about that a little bit later in terms of the interventions , but I'd be remiss if , while on the call with you , I didn't mention that as a point as well .
Well , I appreciate that . Actually , my next question was going to be in your experience , what are some of the factors that influence biological age ?
Yeah , certainly , and this is always a changing topic because , as I mentioned , as we improve these algorithms , we're finding different insights , and so , with that being said , there are a few things that we generally see work for everyone to have an improvement .
I already mentioned stress and improving that sort of emotional regulation and resiliency , which has a strikingly large effect size . It's not just that it's correlated to improvement , it's that the effect size is also very large .
Even people who are working , on average , 40 hours or more per week and the stress that is associated with that , can , on average , have a 1.5 year age increase versus those who don't , and so these lifestyle impacts , and particularly how it affects your psychological status , make an important difference .
¶ Impact of Interventions on Biological Age
Some of the other things we see work for almost everyone are things like caloric restriction , as I already mentioned with some of these newer clocks , and again , as I mentioned earlier , caloric restriction is very well validated to improve health span and lifespan in a lot of animals and even in human measurements , like the calorie study , which was a two year caloric
restriction study , where they ate right around 11% less calories than they were consuming or burning per day , those had really big improvements on all of the ways we can measure biological age , but especially these methylation clocks and we see this again and again again caloric restriction can make a big impact on reversing these markers .
Some of the other supplemental things that we see outside of these epidemiological or diet interventions are things like vitamin D having a major impact and , across a lot of different algorithms , in different populations , some of these studies have shown up to , you know , 1.8 to 2.5 year age reduction in just 16 weeks with 3000 IU of vitamin D , which is , you know
, really , really interesting . Some other supplemental things , like DHEA , tends to have a great impact , and so those , I would say , are really the things we see work in a large majority of people . But right now what we're trying to do is to study some even more , I would say , exotic types of interventions .
Things like Sennilitics , for instance , things like Simcell therapy or , you know , plasma aphoresis or plasma exchange . So we're getting more information about some of these really novel types of therapeutics that are really exciting . But one of my favorites is also rapamycin .
Rapamycin , which has a mechanism of action very similar to caloric restriction and the fact that it's inhibiting mTOR mTOR 1 , it seems to have a very positive effect on a lot of these markers as well , particularly those newer generation clocks , and I tend to be a little bit .
Although there's been a lot of studies out there on things like growth hormone and metformin , I don't know that we see those same associations in our cohort .
You talking about , or I know you have as part of your toolkit , being able to determine rate of biological aging . Can you explain that and how you're able to get that ?
Yeah , certainly , and so that algorithm , as I mentioned , the Dunedin Pace is definitively our favorite . It has the highest precision , the highest hazard ratio of predictions of disease , and it responds to interventions we know beneficially affect biology . So it really does everything we really want a biological clock to do .
But to create that clock was actually an initiative that took a long time . It really actually started in 1972 with a cohort in New Zealand , which is why it's named Dunedin . It was actually in the town of Dunedin , new Zealand , and this cohort started out with 1,037 children .
From the time they were born , I'd enrolled them into a cohort that tracked their aging process across a lifespan .
So over several years they sort of measured these functional biomarkers to create a pace of aging off of really 21 functional biomarkers , including many of the things I mentioned earlier things like cholesterol , things like telomere length , even gum health was assessed and included into this algorithm , and so it was a really , really unique cohort that really hasn't existed
anywhere else , and as part of that cohort we also added methylation based measurements and from that we were able to take this rate of aging we had calculated from their blood-based biomarkers into an epigenetic survey , and with that this is how we've seen and validated all of these really great interventions .
And so the rate of aging is a more instantaneous pace of aging , but we see that it also increases as we get older . So the idea here is to keep your pace of aging as low as possible for as long as possible , even if you're slightly above a rate of aging of one , which means you're aging more biologically than you are chronologically .
Every year , even if you're at 1.01 , you would increase your risk of death over the next seven years by 56% , and you'd increase your risk of a chronic disease diagnosis by 54% , and so that can be major increases , and so that's really our threshold .
We want everyone to keep this as low as possible , and if you're one standard deviation above this aging average , you would be considered what we call a fast-ager , and in the validation with the Framerton-Hart study cohort , those fast-agers were 62% more likely to die than those people who were aging at an average or slow aging rate , and so this definitely impacts
your risk of disease and your risk of death . But beyond that , I think that some of the most exciting parts of this algorithm have been the correlation to these health span-related metrics , these quality of life-related metrics .
Sometimes , whenever we're talking about this to patients , people ask well , why do I want to live longer if my quality of life is so terrible ? I don't want to live in a nursing home , I don't want to have a poor quality of life as I'm aging quicker .
And I think that's one of the other things that this study really documented , because we basically took everyone at age 45 . And actually right now , terry Moffitt from Duke University is actually in Dunedin doing the 51-year age follow-up of this cohort to create an even another generation of this algorithm , but at 55 years of age .
We also did an analysis , and so we looked at things like retinal imaging , brain MRIs , we did facial imaging scans and what we saw was really really significant Things like grip strength . As you get older at age 45 , as your pace of aging is increased , your grip strength and muscle mass decreases .
We also see this with functional measurements like your ability to balance . The faster your rate of aging at age 45 , the worse you performed on that measurement . Same with actually IQ People who were aging at a rate of two were , on average , 15 IQ points lower than those people who were aging at a rate of one .
We saw this on the brain MRIs as well , with less surface area of the brain , less sort of brain volume , and in everyone's paper we also saw this with facial aging , and this is a really striking image If you look at the paper . You might even see it on our website , where we look at all these people across the line who are the same chronological age .
They're all age 45 . But the people on who are the slowest aging members , measured by this Dunedin pace , look maybe 20 or 30 years younger than those people who were the fastest ages .
And so I always tell people this is not just about how long you're going to live , it's about the quality of life that you're living while you're aging , and so that includes you have better muscle mass and strength and the ability to move about the world , the better your aging rate is .
But you also think about the world , your perceptual reasoning is increased , your IQ is increased and then even aesthetically , you look better . And so I tell people keep doing all the aesthetic things that you want , keep doing your Botox , but also fix the underlying cause of this aging process , which is the reason that you're looking older on a daily basis .
And so I like to mention that all those things that Dunedin pays , because not only is it the most predictive , the most accurate , but it also correlates to all of those quality of life metrics which everyone is very interested in .
Yeah , well , this is a very fascinating area , particularly the data that you're pointing out , because I know when I , when we look at stress and the impact of stress , we find that . So you talked about a little bit above one and a little bit below one in terms of rate .
Well , what we know about with stress is that it's a there's a snowball effect that when there's some impairment because of stress , it further causes further impairment . For example , there's a mechanism in the hippocampus that causes a breaking system to the stress response .
Well , as people have more impact because of their stress , that breaking mechanism gets impaired as well . So it further impairs ability to manage stress and there's a snowballing effect .
And my hunch is what we're looking at here with rate of growth is something similar that you could be just a little bit faster , but there's something that your organism isn't doing optimally that further perpetuates that correct ?
Yeah , I couldn't agree more , and the way that I generally explain that to patients as well , that same philosophy is likening it to compound interest , but in reverse right , you always want to keep your money in the banks of the interest or in centrist , but in the case here it's damage makes more damage sometimes , and so it's sort of the opposite of that
philosophy where you want to keep this as low as possible for as long as possible in order to , I think , prevent that compounding nature that you mentioned and even to further elaborate on the links of stress and these epigenetic age markers .
The first Horvath pantissue algorithm , which is by far the most widely cited in the literature of the 353 places that we look at on the DNA , 85 of those are located at or near glucocorticoid receptor elements , which I think really emphasizes the impact of stress even more as it relates to that aging process . So I certainly agree .
I think that that rate can certainly compound if it's negative early in life .
Yeah , very interesting . One of the ways that I like to think of this frame is that you want your body as tuned up as possible , which means in a place of balance , and here we're talking about what happens when your body is tuned well versus when it's not tuned well .
Yeah , you can completely agree , and I think that , as these aging definitions continue to expand , a few years ago we had even fewer hallmarks of aging than we do now , but I think that the one unifying definition of aging is this progressive loss of function with age , and I think that it goes exactly to what you're mentioning , which is this dysregulation being
out of the homeostatic step point , or where you should be , leads to worse dysregulation , leading ultimately to worse functioning .
¶ Advancements in Epigenetic Methylation Testing
Yeah , so what is the next step , would you say , Ryan , in epigenetic methylation testing ?
Yeah . So epigenetic methylation testing is . You know , if there's one big takeaway from anyone who's listening , I think it's time to get interested in this testing , because this is really where I would say genetics was 30 years ago .
You know , we're about to see a massive influx of genetic and epigenetic sort of markers for interpretation into a variety of health diseases . You know , I think that last I checked , the genetic market is over 30 billion a year , but you take those tests once in a lifetime . You only take those tests once because your DNA is really stagnant and immutable .
And so now what we're looking at is these epigenetic methylation marks can really bridge that gap . It can tell us a lot about the functional state of a body , particularly in aging .
For us , what we're doing is , since our sort of outset around two and a half years ago , we've really been focused on creating the best in class epigenetic age offering , and to do that we've invested a lot into a large research study that we're doing with Harvard to create a multi-o-mint clock , and so , as I mentioned , you know , aging is a very complex topic
and we wanted to provide as much information to these epigenetic markers as possible . So we've done . You know a lot of participants from a biobank where we've looked at over , you know , 7000 proteins , over 3500 metabolites , to get a good idea of all of the different changes that we can see with age and to create the best aging algorithm .
So we're really excited to launch that and publish on that in the next few weeks even , and so we're really excited about that . We also have some algorithms coming out , as I mentioned , for senescence burden , to be able to predict senescence .
That's a very hard thing to categorize , but we have a really exciting marker that we've done in collaboration with Ohio State and Yale to be able to predict senescence burden and some of those other hallmarks of aging .
With Yale as well , we hope to have their systems clock to be able to report on aging of unique organ systems , all through blood-based methylation , and so there's a lot of developments in epigenetic methylation clocks in age that will again add resolution to not only being able to tell you if you're aging quicker or slower , but also to give you resolution on maybe
why now for the first time , and so we're really excited to roll all those things out . But beyond that , these epigenetic methylation marks can be used in a variety of different ways . Not only can we tell you biological age , but we can actually even predict when you might die .
We can predict how much you've smoked across an entire lifetime , how much you're currently drinking , we can tell you if you're likely to , if you have diabetes , not just what you have diabetes , but what subtype of diabetes you have , where we might be able to recommend different interventions .
Or we might be able to recommend , or I should say , project , different risks for your individual profile . So really , epigenetics is a bridge to this personalized medicine movement that we've seen for a long time , where we're actually able to get a really unique signature about you as an individual and then interpret that in ways that can really improve your health .
And so definitely , aging has been what has started it , and aging is a massive problem . We continue to hope to lead the way on and help fix . But beyond that , epigenetic methylation as a biomarker is going to change the way that health care is practiced and we hope to be leading the way there too .
Well , that's great , brian . Let me just ask you a question about the kind of results that people get when they give you a sample . I imagine you get your biological age , but do you also get the different biomarkers that go into creating that biological age ? And so you get ?
You can see biomarkers that are perhaps really good and then biomarkers that are needing improvement on . Do you get sort of like a profile of biomarkers with that biological age ?
Certainly , and we're adding new reports , you know , every four to six weeks , so we continue to be able to extract more information from this , and I think that's . Another great thing about our platform is that as our information and knowledge of this process grows , the reports also grow . But currently , right now , we do things like giving you your biological age .
We give you your immune age , also with your immune cell subset , so we can actually tell you your relative percentage of different immune cells in your body , like your naive versus exhausted CD4 or your naive and exhausted CD8 T cells . We can , even , beyond that , give you your pace of aging .
We also do telomere length , as we mentioned earlier , and , as I mentioned , we have some other really exciting age related things coming out , like the systems clock age , the death predictor and the senescence burden predictors .
But we also do other disease related quantification , especially if you're doing this through a physician , where we'll do things like your diabetes risk , your 10-year cardiovascular disease risk . We'll be able to do things like how likely are you to lose weight if you implement caloric restrictions ?
Some people might lose a lot of weight , other people might lose significantly less and , as I mentioned as well , we also do things like how much are you currently drinking just to keep you honest , and how much have you smoked across an entire lifetime to get an idea of maybe how much damage has been accumulated as a result of that process ?
We even do things like mitotic clock rates to look at the number of stem cell proliferations you're having per year , which can be a big risk factor for cancer , and so we'll continue to expand this as time goes along .
Many people might be familiar with these things called polygenic risk scores , which look at all your genes and predict how likely you are to get a certain type of risk . But one of the really big movements in methylation is to create methylation-based risk scores .
So very , very similar concept , but the idea is that these are changeable as a result of environment and history and protocols and generally these have been shown in .
Actually , another study at UCLA where we can actually improve prediction over polygenic risk scores by a substantial amount and so that is really what's coming is by doing one blood test we'll be able to give approximate estimations of a lot of other biomarkers , but even these functional outputs .
So we're also coming out with things like VO2 max prediction , grip strength prediction , walking speed prediction and again , as these things continue to scale , we'll have more insights , but the costs will remain the same .
So the idea is that we'll be able to read out a lot of different value in the future , but right now , that's almost everything you can get on our platform as it currently stands .
That's an unbelievable wealth of information that one can get from that and if they're really working on their health and wanting to improve , it gives them a lot of data to put their teeth into and identify where they need to make their effort . So that's tremendous .
I wasn't aware that there were so many points of data that are available out of that one sample , yeah , and it's really incredible that the majority of those things that I mentioned have really happened in the past year and a half to two years .
This is still incredibly new , really exciting , but the amount of growth that we'll see over the next year , two years or even five years will be substantial .
That's fantastic and I know you're engaged in a number of research studies with a number of universities and researchers . Can you give us a heads up on some of the current and newest findings in terms of what you've discovered has an impact ?
Certainly so . You know , I like to classify this research into two ways . One is these epidemiological associations these are all the things that we know in really large cohorts that have been effected .
And then there's a separate group that I would call the interventional data sets , where we look at an individual , an intervention and then an outcome , and unfortunately , those interventional data sets are much more limited , especially because , you know , the way that we measure or interpret these things change all the time .
So sometimes , for instance , the gene pays , which is now what I would consider the best measurement , only came out in 2021 . So we're still not even , you know , a year and a half away from when it first came out . So again , I think that , from an interventional perspective , most of the things that I've talked about already are what we would recommend
¶ Synolytics, Immune System, Slowing Biological Age
. But there's some other surprising findings , for instance , like synolytics .
We did a study on disatnipic course with Dr Edwin Lee from Orlando and found that synolytics don't necessarily have an age reduction effect and in fact , sometimes they might even increase , you know , some of those aging markers , while we still see reductions in the senescence associated secretory phenotype inflammation markers , and so that , I think , is an interesting
study that's coming out here very soon .
One of the other things that I think is a really important study , which is where we'll probably be publishing on by the end of January , at least as a preprint , and something that Eric Verdin from the Buck Institute is also working on at the moment , is separating these biological age signals from changes in immune cell subsets , so , as our immune system changes ,
that's the DNA that we're measuring and we really need to control for what types of cells we're actually testing to make sure that we're not confounded by different cellular proportion changes and I know that might be a complicated way of just saying .
The immune system effects matter in terms of how we read these results , and whenever we take out those factors of immune cells , we get some really strange associations that we didn't see in previous clocks , and so I would say definitely look out for some of those papers about how the immune system changes can affect the biological aging process , and definitely look
out for some papers that explore things like senescence or synolytics and how they may not be impacting our health like we imagine .
Interesting , very interesting . So in the last couple of questions here , Ryan , based on this information , what would you say are some things that the audience could do right now to help reverse or slow their biological age ?
Yeah , and this is going to sound a little self-serving , but I would want to highlight that people should get first tested to see where they're at . Even if you're not using our platform , there are other platforms out there that you can look into . Always , make sure that those algorithms are published .
So you know you're not just going to a fortune teller and make sure they have some data , but go out there and see your baseline . It's not always intuitive . Some of the world's best athletes that we've measured have extensively higher biological ages , even though you probably wouldn't expect that , and so it's not always as intuitive as you might imagine .
So establishing a baseline is a great way to actually see what works for you . So that would be my first recommendation . But then , beyond that , from an epidemiological perspective , do the things that you think you probably should do already . You know , one of the great things about this testing is it's reinforced a lot of our beliefs and knowledge of behaviors .
Things like Mediterranean diets are great , you know . Things like beta carotines are great for you in terms of aging . Stress reduction is great .
Physical activity is great , but maybe not too much , and so , and in addition to that , chloroconstriction , limiting calories if you have a physician that you can go to think about having a conversation about some really new and exciting things , like rapamycin , making sure that your DHEA is normalized .
Start thinking about even things that might be even more exotic , like plasma apheresis or , you know , diluting your plasma by giving blood . Those are all things we see work almost in everybody and really I would say at the moment , relatively low risk strategies which could have a really long term effect .
So you mentioned reducing caloric intake , but do you have data on intermittent fasting ?
So we don't have a controlled study , unfortunately . But , with that being said , we do ask almost every participant who takes our test about their dietary behaviors , and so we do have a cohort that is more like an epidemiological study . And we don't necessarily see that intermittent fasting improves the biological ages , unless it's also included with chloroconstriction .
So I think that if you're eating the same amount of calories in a day , no matter when you eat them , I think that we don't necessarily see an effect , but if you are reducing calories , we certainly do .
Very interesting . And finally , how can people reach you , Ryan , if they want to get some more information , more information about your products ?
Yeah , so it's a fast growing area and so we love to distribute information and knowledge , and so if anyone would like to reach out to us , they can reach out on our website at true that's trudiagnosticcom , and they can reach out to support at True Diagnostic or Ryan at True Diagnostic . If you have any questions .
We love to answer and share your data wherever we can at the moment , and hopefully we'll be doing another sort of Ask Me Anything with you , dr Siddharath , in the future , and so hopefully people will continue into some of those things as well .
Yeah , thank you so much , and , yes , we certainly will stay in touch because , again , measurement is so important . Wherever anybody is in their lives , getting the baseline so that they know , whatever they do subsequently , what the actual impact is is always very important . So I think it's a very important service that you're offering .
So , thank you , and thank you for your time today . This has been a fascinating conversation , ryan , thank you .
Yeah , thanks so much for having me and look forward to sharing more updates as they come .
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