Epigenetic Health Monitoring to Reduce Your Future Illness Risk – EP13: Tom Stubbs (Chronomics)
In this thirteenth episode, Tom Stubbs, Co-Founder/CEO of Chronomics starts with introducing epigenetics. He describes the technology and expertise that he's brought together to create the only company in the world advancing the forefront of epigenetic biomarkers. He explains how their A.I. based health biomarker engine will be used to reduce your risk of future illness.
Lee: Hey, welcome Tom.
Tom: Hey, Lee. Thank you for having me on the show. Pleasure to be here and looking forward to chatting with you.
Lee: What’s the focus of Chronomics?
Tom: We are very much focused on measuring health so people can avoid disease.
Lee: Measuring health so that people can avoid disease, that sounds a little bit cryptic.
Tom: Yeah. I mean, essentially we’re focused on providing people with objective measures that capture the broader definition of health. So not merely health being the absence of disease, but actually as defined by the World Health Organization over 70 years ago, health being the complete physical, mental and social wellbeing of a person. And we think that this is super important, because with the rise of aging populations and the growth in chronic conditions globally, such as heart disease and type two diabetes, there’s a growing need for healthcare to shift towards prevention. And to enable this shift, we need measures to capture the largest risk factors for these conditions ahead of time so that people can prevent through action.
Lee: So I think I was one of the first users of Chronomics. I had contacted yourselves at the end of 2018 and took a whole genome sequence and an epigenetic test.
Tom: Yes. We first were putting the product out 2018, and yes, you were among one of the first users of the product. So, yeah. Pleasure to have had you and still have you as a customer, Lee.
Lee: And I remember yourselves very favorably, because I was a little bit skeptical because Tommy Woods had informed me that the business model of quite a few companies in the OMIC space is to give you a large questionnaire, apply AI to it, and I’ve had it demonstrated now to me that based on a simple questionnaire, AI can derive a lot of information about you on the health front, predictive, way more than the OMICS can in some cases. And these companies are doing this heavy OMICS data acquisition, not so much to give you data at the moment, I mean, information, but in order that may be in 5, 10 years, that vast sum of data that can then do something with. And so, I was skeptical at Chronomics maybe doing that, and I said, please make a special case for me. Give me my results without the questionnaire. Do you remember that?
Tom: Yeah, I do remember this, Lee. I do remember.
Lee: An easy customer. And then I said, hey look, if I’m doing a whole genome sequence, I actually want a copy of it. So send me every letter.
Tom: Yeah.
Lee: And you said, okay, it’s your data, we can ship you a hard disc if you want. So do you also remember that part?
Tom: Yeah. Yeah, absolutely. I mean, the data that we are generating on behalf of our customers under European law and by the values of the company is your data. So, absolutely we make that available for all of our customers.
Lee: So I greatly appreciate that. I think it was a seven gig.
Tom: Yeah. It would have been a fairly large file to get all 6 billion letters, two copies of 3 billion, at 30x depth.
Lee: It was a 30 pass? I never knew that, because I don’t think the site ever said how many passes were getting taken.
Tom: Yeah. On the whole genome and on the epigenetic side, both are 30x minimum passes. We use next-generation sequencing, so we’re not using chips in the sense that we don’t do genotyping, so using technology that you’d see from most genetics providers like Ancestry, 23andMe, etc. where they’re looking at a small fraction of your whole genome, we actually look at the whole genome and we look at it using next-generation sequencing technology. And similarly on the epigenetic side, we’re distinct in that we also use next-generation sequencing there. So we don’t use chips or epigenetic arrays either. The reason being it gives us access to vast amounts more from a data perspective, but also it comes with added benefits around accuracy and additional components of the data that you can understand and use during analysis.
Lee: Chronomics, I understand is the first company to offer epigenetic testing.
Tom: There have been a number of epigenetics companies. So epigenetics as a field has been around for a really long time, and there have been a number of companies that have been really focused on using epigenetics from tissue samples taken from, for instance, cancer patients, to align specific treatments. So for instance, looking at breast cancer, things like that. To my knowledge, we are the first epigenetics company that’s using saliva as a sampling type to provide people with preventive health measures.
Lee: And why is epigenetics good for preventative health measures?
Tom: Epigenetics is really fantastic as a data type for preventive health because of the very nature of what epigenetics is. Epigenetics is really the science of how your DNA is controlled. In any one of yourselves there’s tons of this DNA, and if stretched out it would be kind of two meters long that has to get wrapped, packaged and controlled very, very precisely to enable your cells to function. And that process of controlling packaging and making different bits accessible is managed over long periods of time using epigenetic information. Epigenetics is really a fundamental component of biology, and it’s super useful in a prevention context because it changes in line with health and also over long periods of time. So it isn’t something that necessarily just spikes and tracks acutely, although in certain contexts it does, it also captures long-term risk. And for things like age-related and chronic conditions that happen over years, if not decades, having a data type that can track with the changing health and evolution of health over such long periods of time is super useful. And that’s something that really epigenetics is acutely placed to support within a prevention context.
Lee: Can you differentiate that with genomics? Because I think more people have heard of genomics and genomic testing, and many people test their genomics for health reasons.
Tom: So genomics or your genetic information is the information that you’re born with, that you get from your mother and father, and provides you with a whole host of information about your risk from birth of succumbing to certain diseases. And it’s super useful if you have a rare disease and you want to understand what could be causing you to have that condition and potentially therapeutic options to move forward in improving your health for reducing the burden of the symptoms. Such projects that have kind of been looking at that and using genomics in that way include the 100,000 Genome Project conducted in the UK. Genomics also has other utilities in providing people with information about their personalized pharmaco profiles. So that’s an area of genomics known as pharmacogenomics that provides people with information about the likelihood of certain compounds in their bodies actually working or not.
Tom: And potentially as we move further forward, that will get more granular into dosages, etc. of where epigenetics really comes in and is, to my mind, way more useful than genomics, is around the age-related and chronic conditions that all of us suffer from. So these are things like type two diabetes, heart disease. Conditions where the majority of the risk is not from that genetic layer from birth, but is actually how that genetic information is interacting, and affecting and engaging, I guess if you like, with environmental and lifestyle components of risks. So if we take heart disease, for instance, heart disease is something that genetically you can be predisposed to having a higher risk of from birth due to your genetic information, and that risk could be as high as kind of fourfold more than somebody else.
Tom: But when you take age, you take different components of environment and lifestyle into account, that risk profile actually kind of from lowest risk to highest risk is actually 5,000 fold. So if our greater body of risk is explained by those external factors to the underlying genetics, those components of risk, the actionable components of risk that you can do something about are the components that are explained by epigenetics. And at Chronomics, we’re really focused on providing people with access to way ahead of disease onset so that people can take action to massively reduce their risk independent of what their genetic baseline is.
Lee: So you’re saying genomics is largely a waste of time for the majority of people.
Epigenetics is really fantastic as a data type for preventive health because of the very nature of what epigenetics is.
Tom Stubbs
Tom: The genomics and epigenetics provide complimentary forms of data and they have different utilities, but when it comes to prevention of age-related and chronic conditions, there’s an incredible amount of information that you can get at using this epigenetic data type and paradigm that is completely masked from somebody’s genetic layer.
Lee: It definitely seems to me that genomic testing is not as useful as epigenetic testing is, or at least what epigenetic testing will become. Because I know for myself from genetic testing, it didn’t really help me in any fashion. I did notice I was homozygous from MTHFR, and I think that’s how most people have heard of the word methylation. Could you introduce what methylation is in the context of epigenetics?
Tom: Happy to. Yeah. And I think just going back to the genetics thing, I think genetics provides you with information, but it’s nothing that you can actually change or do anything about in the majority of cases. And to me that is the big distinction with epigenetics, where you can find out about it, take action, remeasure and see the change. Something that’s, yeah, really not possible in a genetic context at all. In the case of methylation, and I know a lot of people will be familiar now with MTHFR as a gene and as a broader concept that’s discussed a lot, in the case of epigenetics, methylation is an integral phenomena within epigenetics. So when people talk about methylation, they’re talking about a methyl group, and this methyl group can be added to proteins, such as histone proteins, which are kind of ball-like protein structures that DNA wraps around in cells, but also the DNA itself can be methylated. And this is a phenomenon known as DNA methylation, unsurprisingly.
Tom: And DNA methylation is actually at Chronomics the mark that we measure. So we measure DNA methylation at millions of positions, tens of millions of positions across the whole of your genome to provide and derive these specific signatures for different components of environment and lifestyle risks, many of the largest risk factors for age and chronic conditions. And yeah, methylation is used in a variety of ways by yourselves. So the dogma, if you like, is that where methylation is present on DNA, it suppresses gene expression, and where it’s absent, genes get expressed.
Lee: It’s interesting you say it’s dogma. I don’t mean to cut you off. I thought that was sort of the general consensus.
Tom: Yeah. Yeah. This is a phenomena that’s true, but it’s true for methylation patterns in specific regions of the genome. And actually when you look at how methylation is used more broadly, methylation being present, for instance, in gene bodies may actually be a function of genes being expressed. So it’s context dependent. And as with all things in biology, it’s often more complicated than it first meets the eye.
Lee: Okay. And, so histone methylation versus DNA methylation.
Tom: So histones, these proteins that your DNA wraps around can have a whole host of different epigenetic modification added to them. Methylation is one component of that. And depending on the type of methylation, because methylation can be added to different amino acids or different building blocks of those histone proteins, that methylation will do different things as well. And it’s also really important to bear in mind that these different epigenetic processes are all interrelated. So been a number of studies actually looking at the ability to predict, for instance, what certain components of histone methylation will look like from DNA methylation and vice versa. But at a really fundamental level, these things are absolutely required for complex life.
Tom: So in the case of DNA methylation, there have been a whole host of studies where people have taken embryonic stem cells. So cells that can become all cells within the body. What they found is that if you remove the ability to methylate, those cells can never differentiate. So those cells can never become skin cells, or liver cells, or blood cells, or any other type of cell without that DNA methylation, profiling. So really showing how fundamental a part of biology epigenetics is and how absolutely required it is for the proper functioning of us as a species and as organisms.
Lee: I appreciate that. And could you kindly introduce what CpG sites, are or islands and dinucleotides?
Tom: So CPG dinucleotide is a fancy way of talking about two specific consecutive letters in the genome. So in our DNA we have four base letters, if you like. We have an A, a C, a G and a T. And when we talk about DNA methylation in mammals, this methylation is pretty much in the majority of cases specifically added to a C letter, so a cytosine, when it’s always followed by a guanine, so G. So when a C is followed by a G, that C has the propensity to get methylated by the enzymes, the proteins in your cells that are known as DNA methyltransferases that add this modification. And for those who don’t know, DNA itself has a directionality. So, CG is not the same as GC. So when we say CpG, it means that along the backbone it has to flow in that order. So GPC would be unlikely to be methylated, whereas CpG is very likely to be methylated. So that’s what CpG dinucleotides are, a fancy way of just referring to a C when it’s followed by a G in the genome. And when we talk about CpG islands, and we also have shores, shelves, seas, oceans, that analogy-
Lee: I wasn’t aware of that.
Tom: Yeah, yeah. So yeah, that analogy in biology probably gets extended further than it actually should. But CpG islands are basically regions of the genome where there’s a really high density of C’s followed by G’s. So these CpG islands can for instance be found in what we call gene promoters, so regions just upstream of genes that control how and when a gene is expressed. But they can also be found in different parts of the genome as well. And CpG islands are a well studied and understood phenomenon because they’re involved in a whole host of different processes through the body, and are also implicated quite heavily in the onset of certain types of cancer as well. So that’s why they’re very well known. And CpG islands are basically the highest density regions of your DNA in terms of CpGs or CG dinucleotides. The regions neighboring CPG islands are known as shores and shelves, and then as you move into lower density CG regions of the genome, you start to get into regions known as seas and oceans, which is where that terminology is coming from.
Lee: Thank you very much for that. And also CpG dense promoters and also talk of hypermethylation and hypomethylation.
Tom: Yeah. CpG dense promoters would be water termed CpG island promoters, and these are often heavily involved in differentiation. So if you wanted to distinguish one cell type from another cell type, you can look specifically at these regions. If you wanted to know the difference that you’re looking at a liver cell instead of a lung cell, let’s say, and as I mentioned, these things are also heavily involved in cancer phenotypes. When people talk about hypermethylation or hypomethylation, something that’s getting hypermethylated means that that position, when you look across a whole bunch of cells as a population of cells, is getting more methylated. And conversely, hypomethylation means something that’s getting less methylated.
Tom: This is an important concept because it’s distinct from genetics. So in genetics, as we mentioned, all of your cells, or pretty much all of your cells, share the exact same genetic material. So if you have a C followed by a G at one position in your DNA, that’s likely to be across all of the cells in your body, true. Whereas in the case of methylation, what you find is that there’s a probability of a given cell having methylation at a given position. So let’s say you’ve got one copy of your DNA in one cell that’s methylated, that doesn’t necessarily mean that the other 100,000 cells you would looked at in a small subset of cells would also be methylated. And actually what we see when we look in the human genome is that there tends to be a bimodal distribution. So there tends to be positions in the genome that are heavily methylated, so around 80% methylated. So that means 80% of cells will have that methyl group at that position, and 20% of them won’t. And then conversely, you’ll have regions that are really lowly methylated. So this could be anywhere from 0 to 10 or 20% methylated. So very lowly methylated where the converse is true. And yeah, and typically when people look at CpG island promoters, which is where this whole, if methylation is present, then there’s no expression and if the methylation is absent, there is expression comes from. It comes specifically from CpG island promoters-
Lee: I wasn’t aware of that.
Tom: -in the first contexts.
Lee: And what about this link between hypermethylation and promoters and oncogene suppression or silencing.
Tom: Yeah, so there’s a relatively well-studied phenomena when it comes to cancer and CpG island promoters known as CIMP, C-I-M-P, and this basically stands for unimaginatively CpG Island Methylated Phenotype. And basically this is something that seems to happen in a number of different cancers where certain CpG islands that are unmethylated become methylated and that can have adverse outcomes for those cells. And the hypothesis being that can alter cells’ propensities to become cancerous.
Lee: You’re getting me more excited about epigenetics. So it seems Chronomics is taking epigenetic code, making it digital code. What is unique about Chronomics? How did this come about?
Tom: Epigenetics, as we’ve said, is a fantastic data type and this is a huge growing area and there’s clearly a massive need for prevention and reducing the disease burden of age-related and chronic conditions that in the UK but also in, in the US and further afield is having a massive detrimental impact on healthcare budgets and spend.
Tom: In terms of what makes Chronomics unique. So we touched on it at the start around the data type that we use. So we focus in on next-generation sequencing, not arrays. And we’re using saliva rather than other tissue types that are perhaps more invasive to get hold of. But what really sets Chronomics apart is that we have derived a health biomarker engine utilizing the knowledge and experience of our incredible team of scientists and engineers that have worked at the forefront of the field at the University of Cambridge, the European Bioinformatics Institute and other leading institutions in this space to really take this science of epigenetics and these biomarkers that we can derive from this data, and provide it to people.
Tom: So, if you look at some of the other epigenetics companies that are operating in this space, most of them will be utilizing biomarkers for biological age. We’ve already taken that 10 steps further by introducing additional biomarkers for other components of health, or for components of health that also feed into the aging phenomena. So these include biomarkers looking at metabolic health and also exposures that can be detected almost two to five years later using epigenetic signatures for things such as smoke exposures and alcohol consumption.
Lee: Hey, Tom, just so I can be sure that listeners follow, you mentioned earlier arrays, can you differentiate that method from sequencing?
Tom: So this is just more in terms of the ways you can capture epigenetic information, similarly to with genetic information, you can either capture it from a genotyping array that looks at a small fraction of the genome, or epigenome.
Tom: Or you can use sequencing. And sequencing is where you’re basically reading out all of the letters within the genome or the epigenome, and you map that then to a genome and you get to understand, okay, what variants does somebody have across their genome? Or what is the methylation state given this sample across different CG sites in the genome. And the beautiful thing about sequencing data on the epigenetic side is that it provides you with a whole host of other measures that you can’t really get access to with epigenetic arrays.
Tom: So one is looking at your two alleles separately. So with epigenetic array technology, you don’t know which copy you’re looking at in terms of where the one comes from your mother or your father, or to even distinguish the two in the first instance. You also are unable to know and to remove any underlying contamination from the sample, which is a massive issue in the array space. And you also don’t get access to positions surrounding any given epigenetic position you’re looking at. So you mentioned CG sites. Two, a given CG site also has an influence on the methylation state at that site and you lose this sort of information if you’re looking at array data.
Tom: So that really provides us with an edge on the technology side. And then within Chronomics, we have many of the world leaders in this space, both from a scientific advisory board perspective, but also actually in the company doing the stuff to ensure that we stay at the cutting edge of this technology and delivering the advances that are so badly needed in the prevention space.
Lee: Were you suggesting there, just to clarify, that if I go to other companies, I don’t know, pick MyDNAge and order their biological age testing service, which is epigenetic-based, they’re using arrays not next-gen sequencing. Or did I misunderstand?
Epigenetics, as we’ve said, is a fantastic data type and this is a huge growing area and there’s clearly a massive need for prevention and reducing the disease burden of age-related and chronic conditions that in the UK but also in, in the US and further afield is having a massive detrimental impact on healthcare budgets and spend.
Tom Stubbs
Tom: So I guess in the case of MyDNAge, not to get bogged down in what competitors are doing, but in the case of MyDNAge, they’re looking at a very small fraction of your epigenome, looking at a couple of 100 to a couple of 1,000 sites in the genome, to provide you with that one measure of biological age. In the case of Chronomics, we’re looking at pretty much your whole epigenome and we’re providing you with not just the most accurate measure of biological age available from epigenetics, but also a whole host of other epigenetic biomarkers as well.
Lee: And why do you seem to stress saliva? Like, I think you’ve said that a few times now. Has it got some other property than blood?
Tom: So saliva is a really fantastic sampling tissue type for a number of reasons. There’s obviously some practical reasons around the ability for people to take this in the comfort of their own home without having to bleed themselves over a kitchen table, which for those who’ve tried is not a pleasant experience. But it also provides people with access to biomarkers that are not available in blood.
Tom: So there’s been a number of studies looking at the correlation between, for instance, the brain methylome and the saliva methylome versus the blood methylome. And in fact the saliva methylome is much better correlated to a brain methylome. And so there’s also the likelihood that additional biomarkers that were previously inconceivable from blood or had never been achieved before, are now possible using this data type. And that’s something that we’re really passionate about exploring and developing the science around. And, Lee, as we’ve spoken before, there are some key advances that we’re making in this space that are super, super exciting that unfortunately we can’t share today. But this is proving to be the case. So watch this space.
Lee: So what you allude to there is someone from Chronomics contacted me I think a few months ago and said, “Hey, we have a new feature, a new epigenetic…” Can I call it an epigenetic biomarker?
Tom: Yeah. Yeah, yeah.
… we have derived a health biomarker engine… to really take this science of epigenetics and these biomarkers that we can derive from this data, and provide it to people.
Tom Stubbs
Lee: So I did actually have a question about that terminology, but I’ll jump ahead. So he contacted me. It was a very pleasant call. He showed me a new feature. So, I can’t mention what the feature is. He told me not to mention it. But I said, “Hey, I’ll be top of the leaderboard for that marker.” And I don’t know if you are able to do any checking or you have any awareness, but he, I don’t know how many others he had looked at. He said, “Yeah, you’re at the top.” So I wasn’t that surprised. And I think what you’re saying there is that, by having such a clean input based on saliva, based on next-gen, you can develop these biomarkers. So I think what you’re saying is possibly without saliva and certainly not with using array technology, you couldn’t develop these epigenetic biomarkers.
Tom: Correct. So, basically saying that saliva as a sampling type provides you with the ability to derive biomarkers that you couldn’t have got access to from another sampling source, potentially like blood. And by using our next-generation sequencing approach, we have access to tens of millions of epigenetic sites in the genome that are completely missed by array technology. And actually many of these sites are the most interesting in the genome when it comes to the epigenome.
Tom: So just to give a bit of historical context on that. So the first epigenetic arrays, going back to cancer and CIMPs and everything we were talking about earlier, were derived initially with a very strong cancer focus. And so what those arrays focused on were regions of the genome from an epigenetic perspective that in the vast majority of cases are pretty static. They only become variable in a disease context. And in a cancer context, in the first iteration of the epigenetic array, more recent iterations have tried to broaden that panel out. But when it comes to looking at the epigenome and from a prevention context, lots of the subtle changes that are happening outside of CpG islands and outside of regions that those arrays focus on. And so by using a much broader next-generation sequencing approach, you get access to the highly variable and much more interesting regions of the genome from an epigenetic context that you can use to derive these biomarkers and that no one else has access to.
Tom: And so that’s what’s super exciting from the Chronomics perspective is that we’ve essentially now got, to use a ski analogy, dry powder to derive novel signatures for these things in a tissue type that’s incredibly versatile to really support people with prevention and getting access to information about their health years, if not decades, before the onset of symptoms.
Lee: Are there other companies using sequencing and saliva for epigenetic biomarkers?
Tom: So to our knowledge, no. That doesn’t mean it may not be happening. It’s just I’m not privy to it. To my knowledge, when we look at many of the companies operating in the epigenetic space, they’re essentially taking biomarkers that are now getting on for kind of four or five years old and just re-purposing them in a blood context or other type of context to provide people with measures of biological age. To my knowledge, we’re the only company at the forefront of deriving novel biomarkers using the scientific expertise that we have internally within the company.
Lee: And these, I’ll call them epigenetic biomarkers, are you publishing papers on these or is this all intellectual property withheld or is it being put into the public domain?
Tom: Absolutely. So as a company, we want to advance the science of epigenetics and part of advancing that science is making our knowledge and understanding available to the academic community to continue the advances that are happening in the epigenetics field. And we’re doing this in a number of ways. One is in publication and we’re working on that for a number of different things that we’ve been developing, in addition to actually making the components of what we’ve developed accessible to researchers as well. So, this is something that we absolutely believe in and are developing. But I think it’s really important to say that when we do any of this stuff for us as a company, the customer comes first and the customer’s data ownership comes first. And so anything that we would ever consider or think about putting out and anyone that’s involved in that would have to have explicit opt-in consent.
Lee: So would you say, Tom, that Chronomics is an epigenetic biomarker development company?
Tom: Yeah, I think that’s one way you can think about what is happening on the back end-
Lee: I would sell on the front end. I find that quite exciting.
Tom: Yeah. That is what we do. And we’re using this technology and this development that we’re doing on the epigenetic side to power preventive solutions that our users and partners can benefit from to support people with improving health and the avoidance of disease. But absolutely, that’s what we’re doing.
Lee: Yeah. So I find that the exciting part and yet you called it “back end”. I mean all… Maybe I mix with a certain niche of people, but we’re very excited at biomarkers and novel biomarkers. And now the first time I’ve heard it from you, you’re developing these unique epigenetic signatures or biomarkers. What I feel from you, the sense I’m getting because I don’t think we… Have we spoke before?
Tom: I don’t think so.
Lee: No, you just seem vaguely familiar. But anyway, jumping back in. I detect from you that you are not such a believer in polygenic risk scoring, as in you far more value this epigenetic side than even polygenic risk scoring. Am I right there?
Tom: I think that the polygenic risk scores have a place and they provide some value. I think there’s some clear issues with them to date. And these are known issues in the academic-
Lee: You are so polite. You are trained in politeness. I think I can detect from you the last thing you want to do is get out of bed and work on polygenic risk scores, rather than epigenetics.
Tom: Yeah, epigenetics is what excites me and to my mind is what’s going to drive people in improving health and the avoidance of chronic conditions. And so, yeah, absolutely. I’m aligned that way, but I do think that genetic information has a value. I just think we’ve got to be cautious around the use of polygenic risk scores because of issues around differences across populations in polygenic risk scores.
Tom: So, to take an example of some data I saw relatively recently, was looking at the polygenic risk score for breast cancer. And this polygenic risk score worked incredibly well in the population that it was tested in. And then when these researchers went on to validate it in different populations or different sets of people globally, they found that it was highly variable in terms of the output of risk for a given population in a way that wasn’t informative of breast cancer risk.
Tom: So for instance, they were finding that one population they tested in every one in the whole population according to this polygenic risk score would fall into the high risk category and getting higher risk there from, which wasn’t meaningful. So, there’s clearly some transformations and things that have to be thought about and normalizations when it comes to the use of polygenic risk scores, that people are still working on. But I think polygenic risk scores versus the use of single nucleotide polymorphisms have a place when it comes to more complex phenotypes that can’t be explained by single changes in somebody’s genome.
Lee: Yeah, I would agree with that last point for sure. So I’m definitely feeling the energy from yourself and the epigenetic side and what I believe I’m picking up is, the values in the epigenetic field, Chronomics is leading it for the reasons that you gave. You’re developing these novel epigenetic biomarkers. It seems you don’t have much competition going on there. So this is all going great in the back end. If we begin to move towards what you would then call the front end, you guys gave me a biological age score. I happen to believe it’s the most accurate biological age score not because it makes me seven years younger. I honestly don’t think I’m so biased. I’m not so attached to such things.
Lee: But I have a number of reasons, I think it’s the most accurate score, which I’ve not shared with yourself and I think I will do in due course, not in this podcast, but over time. I’ve been spending quite a bit of time in the area. So I have I think fairly good reasons to believe it’s the most accurate.
Lee: Now, I’ve just got a couple of questions on that, though. The Horvath clock, you know the epigenetic clock, it was built for arrays, right?
Tom: Correct. Yeah.
Lee: Did it get updated for next-gen sequencing, do you know?
Tom: So we’ve actually been working with Steve on this and what we found, just going to that clock is that it does work. It does work in a sequencing context and it works in saliva, but there’s an offset in saliva and I think that’s down to the predominant tissue types that were involved in the derivation of that predictor. In contrast with Chronomics biological age measure, it works pan-platform as well. So it works from array technology and sequencing technology equivalently well. The, Horvath predictor, as you mentioned, has been solely derived using array platforms and in the case of the Chronomics biomarker, it’s also been derived pan-tissue. So it works equally well in saliva as well as other tissue, tissue sources such as blood.
Lee: Are you saying it’s equal to the standard Horvath clock or did I misunderstand it? It’s just how it sounded, what you said. I don’t know if it’s what you meant.
Tom: No. So our biomarker doesn’t need any transformations or data manipulations to have it align in saliva nor in blood. So for peripheral tissue types that you could sample, our biomarker provides more even coverage across tissues and across a platform types.
Lee: But you would agree it’s better than having array input your biomarker?
Tom: From the array biomarkers for biological age that are out there, they’re derived from a very small subset of sites. The original models, I mean, so if you take for instance the original Horvath predictor that you talked about, that’s been derived from 20 odd thousand sites from an initial starting point. Whereas in the case of the Chronomics biomarkers are derived from millions, so it’s got a much more diverse starting point to derive the biomarker even though the model itself will bring that number down to the hundreds of sites…
Lee: Three hundred and thirty? Or…
Tom: Yeah, exactly. So in the case of the Horvath predictor, you’re talking three hundred and fifty three and in the case of Chronomics biomarker, you’re not talking too much of a dissimilar number either.
Lee: Okay. So Chronomics provide this biological age scoring and, although I’ve covered it on other podcasts, would you briefly cover in your view why we should measure biological age?
Tom: Yeah, sure. So biological age as a phenomena is really moving away from the calendar years to actually understanding, at an internal level how old you are, how healthy you actually are. And in the case of epigenetic age as a readout for biological age, it’s been shown that this measure of biological age is indicative of age-related disease risk and/or cause mortality. And we’ve also shown, kind of prior to Chronomics, that these epigenetic measures of age actually hold across different species.
Tom: So we actually built one of the first, no, THE first biomarker for biological age pan-tissue in a model organism and showed that essentially you could get, as a proportion of lifespan, the same accuracy in that model system, even though the lifespan of that organism was far shorter than it is for a human. Actually the different interventions that accelerate or decelerate that biological age or epigenetic age also impact the life span of that organism. So in a pharmaceutical context and in a research context, that opens up incredible opportunities to accelerate the advances in the aging space by enabling people to understand using these surrogate end points of biological age, how likely a treatment is to impact the aging process over the course of somebody’s life span rather than having to do the study over the actual course of somebody’s life span.
Tom: And for any one of us individuals having an understanding of each of our biological aging rates provides us with information about our likelihoods for age related disease risks and what steps we can take to reduce those risks as well.
Lee: Thank you. I’ll give you a quick example in terms of a biomarker from Chronomics. Today I logged into the Chronomics portal to have a look before we spoke and I looked at my results. And when I received the results, for your interest, it said my alcohol consumption was low, which I posted on social media with a wink because I’m very well known for liking wine. I do have vices. I over-consume coffee by day and I certainly like quality wine by night. I’m very comfortable with that. And I tell you, Slovenia has some very lovely wines. When I logged in today I saw it had put me as, yes, you could do with cutting down on alcohol side. So it had moved. These results are not fixed I presume. The biological age is still where it was, but the alcohol consumption had went up. Was that an error in the system or is this being computed in the back end every time a user logs in?
Tom: In the case of the alcohol consumption biomarker, and in the case of the metabolic state biomarker, we actually advanced the way in which we were calculating this from a scale perspective. So the prior model that we were using was a classification related model, to essentially bin people into buckets related to alcohol content. We’ve since taken that a step further to actually derive a regression based model that can actually provide you with a continuous view of the impact that alcohol is having on your health. And so that would explain the change in the biomarker on that front. In the case of biological age, as you mentioned, it hasn’t changed. That’s because we’ve always been using a regression based approach using an elastic net model similar to the other biological aging models, including the one that I mentioned earlier that we derived in in a mouse as well.
Lee: Thank you. So as a customer, and I simply don’t know this from the website and I would love to know it, is that once I have paid for an epigenetic test, do I somehow get access to novel epigenetic biomarkers in the future that become available?
Tom: Absolutely. So you know, one of the really exciting things about epigenetics as opposed to genetics is that epigenetics is dynamic. It changes over time. And so we want that longitudinal view of somebody’s epigenetic data to be as versatile and as useful as possible. And to do that, there needs to be some component of backward compatibility. And so as you take another test and another test and as we introduce new biomarkers, as we mentioned, there are some features or biomarkers coming through the pipeline that we can’t discuss on this podcast, then your prior test would get upgraded to align to the future biomarkers coming through so that you can see the dynamics of those things changing over time. Looking backwards as well as moving forwards.
Lee: That’s very cool. If I only paid Chronomics once, would I see any updates over time?
Tom: Absolutely. You’d see updates to the task that you had conducted.
Lee: So you’d see new signatures?
Tom: Yeah. So you’d see the new signatures arriving but obviously we’re not resampling. Use of those signatures will be from a time point when you provided the sample.
Lee: That is right. And do you think there’s a case where you can’t take the old data and derive the new biomarker because you’ve learned something in your [data] acquisition phase? Or can you always think you can go back and apply the new biomarker to the old data?
Tom: So the way we’re looking at the product development and how we think about these things, we think that the backwards compatibility is crucial for our customers. And we’ve had a lot of feedback on that. So anything we do from an acquisition perspective on the data side, we would do to ensure backwards compatibility of new models as they’re made available.
Lee: I appreciate that. When it comes to epigenetics, they are influenced by the environment and lifestyle choices, clearly. And when it comes to environment, more and more I become aware of chemical exposures which are going on all of the time: from your washing powder, residue left in your clothes going transdermally into your bloodstream to the likes of glyphosate. So do you have plans for epigenetic biomarkers for pollution or chemical exposures? Because, trust me, from the functional medicine point of view, I have come to appreciate more and more that chemical exposures in our day to day living play a significant role in our long-term health.
Tom: Absolutely. I mean on the pollution side when we talk about our smoke exposure biomarker, that actually is also capturing a component of pollution as well in an air pollution context. But talking about some of the other more chemical or substance-related things that you’ve just mentioned there, absolutely. These are active areas of interest alongside also deriving information about pharmaceutical products as well. So one thing that we’re seeing happening in the market that we’re also super interested in is around the fact that people more and more now are taking pharmaceutical agents or drugs, not in an acute way as used to be the case, but actually more as a chronic dose of something. So I guess classic examples being; people taking statins or other products of that nature.
Tom: And what we’re really interested in is also understanding the epigenetic footprint of those things. So we’ve seen anecdotally looking at epigenetic profiles, people that have been on products that are known to rejuvenate, actually seeing decelerated or younger epigenetic ages, which is super exciting and worth pursuing, but we’re also really interested in understanding the impact that long-term pharmaceutical use is having on people’s risks for subsequent chronic diseases later on. Because there’s a component of the risk/reward that people aren’t weighing up over the course of their whole lifespan just because they don’t have that information available. And that’s where we think epigenetics is another super powerful tool for supporting people in a prevention context.
Lee: The more we talk, the more I’m getting excited. So now I’m beginning to think of an intervention marketplace, if I can call it that. So first of all, let’s say people are on statins, a long-term drug. Do you think you’ll get to the stage where you can actually say: look the statins, we see a signature? We’ve come to learn that the statins are having an adverse effect on areas of your health?
Tom: Yeah, and this will be at a personalized level. So there’ll be some people where the risk reward is worth taking and others where it isn’t. And you’ll be able to see the signatures for different potential future disease states or risk factors for disease, way ahead of time, to be able to say to somebody, let’s really think about the pros and cons, with your doctor or, or whoever it may be, to ensure that you’re taking the best steps that you as an individual can take to stay as healthy as possible for as long as possible. And one concept that you mentioned there Lee, that we’re really excited about as well is around providing people with a whole host of interventions in a way that they can personalize them to themselves and we can almost provide an understanding of the impact, both positive and negative that various things are having on distinct individuals to support people with areas of health that were previously not measured. And so people were flying blind as to whether things were actually having a positive impact or a negative impact on their health.
Lee: Yeah, intervention marketplaces is most exciting from a sort of business perspective. I suddenly light up with it. So you’ve got this harm your health side, say potentially statins, and you had no visibility and then we can question how you play that. Does a person come to test its genomics [sic: their epigenetics] and then you see that statins are maybe not the best for you? Or do you play where the doctor looks at a past epigenetic history and says “well somehow this might not be good for you”? But what about in a more positive intervention, like you could see that taking nicotinamide riboside for example, is having a positive effect on your epigenome?
Tom: Yeah, absolutely. On the positive side we would completely agree with you in the ability to have an intervention marketplace but to serve it in a way that’s personalized to a person from their molecular data or from their biological data so that you’re serving people interventions that are going to have the biggest impact for them at the doses that make sense for them. And also the ability to then turn off interventions if they’re having any deleterious impact on somebody’s health more than they’d bargain for. This is absolutely the way things are going. And you mentioned with some of the anti-aging therapies that people are working on and these are things that we are integrating and introducing at the moment.
Lee: Because you can act as a bridge to sell it yourselves also these interventions, dozes, therapeutics or you can offer to validate it for third parties and/or the individual and the longevity industry will be a trillion dollar plus industry in 10 years.
Tom: Absolutely.
Lee: If people want to be spending endless amounts of money on anti-aging agents because once they proliferate in the marketplace, you cannot buy everything and you cannot take every therapeutic, etc. So you have to make decisions and it’s very hard to make decisions. It’s extremely hard to make decisions. It’s actually what I’ve been spending some years looking at, and I’m still grappling with, because how do you decide what’s the best spend of your dollar to protect your health, to upgrade your health? This seems a perfect direction to be taking in parallel with the rise of this longevity marketplace.
Tom: Absolutely. And ultimately making decisions goes from being hard to impossible when you don’t have… And the right decisions when you don’t have a molecular data about your own health and an understanding of how that intervention is likely to impact your specific situation. So for sure we have an opportunity here to provide that decision support through helping somebody with their own epigenome.
Lee: It’s great. I hear you, you come across to me as more of a science company at the moment, but it’s very clear the commercial opportunities. It isn’t what I see today on chronomics.com although that’s your first public foray I guess, but it’s clear we’re hearing something much larger. Would you agree with that? I’ve never saw or heard you say anywhere this future vision, but you clearly have a much larger future vision than just a little bit of preventative health advice.
Tom: Our vision as a company is to make the unseen actionable and that is providing people with access to molecular level biological data on themselves so that they can make informed decision and take action. And we don’t see ourselves as a company that’s going to provide those actions. As you say, we are, at our core, scientists and that is our foundation. But what we do see we can support with is providing, as you mentioned, validation around interventions and also the personalization of interventions from this molecular data. And, and that is definitely the direction that things are moving, and the space is moving and it’s what people want.
Lee: Tom, if you could see me now, I’m smiling away. That very question, you answered it as a scientist instead of a sales person.
Tom: (Laugh).
Lee: You need a bit of Trump, best in the world, the biggest, the largest, first time in history…
Tom: Yeah. This is going to be huge.
Lee: Stereotypical British sort of understatement.
Tom: Yeah. Maybe it’s the British politeness coming through.
Lee: I see I am running out of time with you here, and I just have a few more questions I must fit in, say three more questions. I might be jumping off a tangent here and please help me out. Folate. What’s the connection between folate intake on epigenetics or a methylation?
Tom: So folate and methylation have a relatively direct link, in that folate is a key constituent chemical in the production of the cofactor for the enzymes that adds methylation to DNA. And that cofactor is called S-adenosyl-methionine and it’s that cofactor that in the enzyme, in DNA methyltransferases, the enzymes that add methylation to DNA, that actually stores that methyl group to transfer it to DNA and folate is a key constituent in that. And this is actually one of the reasons why during pregnancy, mother kind of… yeah, pregnant mothers are often asked to take folate-related supplements to ensure there is no folate deficiency, to ensure that the embryo that’s developing is getting properly methylated. And actually, there’s some evidence now coming out to suggest that… Actually, one of the routes through which fetal alcohol syndrome occurs, so this is a condition when a mother continues to drink alcoholic substances during pregnancy and is specifically heightened at specific moments within pregnancy. Yeah, there’s now links being drawn through this sort of folate pathway and the methylation of DNA which are super interesting as well.
Lee: With the last guest I had, which was Jeff, the CEO of Q Bio. And the reason by the way I wanted you on next is I see overlap or I see you as very complementary in ways I would love to elaborate on but I won’t. I have a suspicion you see the complementary nature of vision. When talking with him, I mentioned the information theory of aging. So, do you agree that epigenetic instability or corruption goes hand in hand with aging? And if so, do you think you can play a role in future interventions to restore the genome back to an earlier state?
Tom: I mean to an extent trying to tease apart and understand the epigenetic mechanism through which aging is occurring was very intertwined to my PhD thesis. Yeah, I completely concur with the view that there is an epigenetic maintenance system and that this is tending towards increased entropy with age. So what you see at an epigenetic level, at a very rudimentary level, what you see is the positions in the genome that had lots of methylations or are highly methylated tend to lose methylation with age. Positions that are lowly methylated tend to gain methylation in age. So they’re tending towards maximal entropy, if you like.
Tom: There’s also a number of interesting phenomena here in that there is the ability that our bodies have or the species has to be immortal. So, if you look at each generation, each generation essentially has a reset that enables humans as a species to not just wear out and age as a species but actually that to be constrained to individuals or to the Soma. So, that I always find is a super interesting phenomenon in that when you take a sperm and an egg that also have epigenetic age and you combine them, you get an epigenetic reset that then allows that newly formed organism to essentially start from zero.
Lee: But when the tags are out, they’re done. They get retagged.
Tom: Yeah, exactly. So during the earlier stages of development, you have a process of a wave of demethylation where pretty much most methylation in the cells gets wiped out. And then that methylation gets put back and as that embryo starts to differentiate, you get different cell types, etc. And those gametes, which are referred to as primordial germ cells at this stage, are set aside at that early point, and they will then form the gametes, the sperms and the eggs, that will fuel that next generation.
Tom: So there’s some really interesting biology intertwined in that kind of development aging axis that basically shows that we do have built in to the process of us existing the ability to be immortal. And there are clear epigenetic phenomena occurring during the reset of that. And this is being backed up by studies that us and others have done around reprogramming experiments. So taking cells, skin cells or other types of cell, from an adult and reprogramming them. So taking them all the way back to induced pluripotent stem cells, which are analogous to embryonic stem cells, and then differentiating them again and seeing that you’ve completely erased age.
Tom: There clearly is something about our ability to retain that immortality across the human existence that is separated from our current existence as any given soma that I find super fascinating. I think there will be a ton of interesting therapeutic and other sorts of development in that space to make use of that system to provide anti-aging therapies and longevity therapies to support people in the very near future.
Lee: You said that in another understated fashion on the immortality front, I appreciate that. I’ll really try and wrap up for you soon. Just to clarify the epigenome, but there is a transgenerational element to it, the classic Dutch Hunger Winter.
Tom: Yeah. So, on the component of epigenetics across generations, there’s definitely a number of phenomena epigenetically whereby the experiences of the environment and lifestyle of one individual can impact future generations. And there’s a number of different ways in which that can happen. Some of which are very well understood and characterized in a research context, others of which we’re still not entirely sure. And you’ve just mentioned one there that we’re more sure about which is the in utero effect.
Tom: So, this is basically that you essentially, through in utero mechanisms, have the ability for a mother’s experience to be passed down two generations. Because if the mother is pregnant with a child, say with a daughter, then the gametes that will develop and go on to become the granddaughter are already present. And so you can have an effect, an epigenetic effect, that lasts two generations due to an in utero effect that the mother feels from the environment. And as you say, that could be dietary related or other sorts of effect.
Tom: Where the evidences is less clear and the jury is still out in the context of humans, it has been demonstrated in other species, is around transgenerational inheritance. And this is essentially where the effect falls outside of that uterine transfer. And there’s a whole host of interesting hypotheses around why it could exist or why it could not exist. And the likelihood of it existing varies from species to species and that’s kind of aligned with the evidence that’s available. But, yeah, the truth of the matter is that the jury is still out on the extent to which there is any transgenerational inheritance in humans of that nature.
Lee: I appreciate someone with your expertise informing me that because with the materials I’ve read it’s being debated backwards and forwards and I didn’t know if there was a settled position or it was my misunderstanding. And it reminds me just briefly of epigenetic memory. Could you introduce just the notion of epigenetic memory and why that might be particularly useful as a health biomarker?
Tom: Yeah, sure. So, when people talk about epigenetic memory, it can be used in a number of different guises. So, epigenetics at its purest form is the ability for a cell to divide and to maintain its epigenetic profile. So, if you take DNA methylation as a kind of archetypal epigenetic modification and you have two copies of DNA, one from your mom, one from your dad, but each one of those copies of DNA has two strands. And on each strand, you can have methylation. And when a cell divides, those strands get split and they get copied and they end up in different cells.
Tom: And each time a new copy of DNA gets made, DNA methylation needs to get added on it to make sure that that DNA methylation in the next round of division is still present or else you’d have widespread DNA demethylation, something that occurs during development. And that’s actually one of the mechanisms by which demethylation occurs during early development. And so that is known as a memory phenomenon because essentially the new cells are remembering the epigenetic state.
Tom: The other context in which epigenetic memory is used is around differentiated cell types. And the fact that in the majority of cases, your skin cells know that they are skin cell and they sort of stay being a skin cell. They don’t randomly change into a cardiomyocyte or a heart cell.
Lee: Hopefully not.
Tom: Hopefully not. Although, obviously, that’s not always the case. And there are certain instances, particularly around types of cancer, et cetera, where the cell type that’s being played out in a given cell, if you like, the program that’s being run gets changed in a way that’s deleterious for the organism as a whole and their epigenetic memory has failed to lock in a cell fate. And the way that’s, I guess, thought of traditionally in an epigenetic context is from a scientist from back in the 19th century called Conrad Waddington, as essentially every cell starts at the top of a mountain. And there’s different ways that cell, so an embryonic stem cell, and there’s different groups that that cell can flow down the mountain.
Tom: And depending on which epigenetic marks get added to that cell, as it heads down the mountain, will define what that fate of the cell is at the bottom of the mountain. And it’s very hard to go up the mountain. And when we do IPS reprogramming, what we’re essentially doing is forcing a cell, pushing the cell back up the top of the mountain where it doesn’t know which cell fate it is so that we can roll it back down the mountain to become a different cell fate. And so under normal context, you want those cell fates be fixed but under certain context, cancer being one, that those cell fates can be modified and can transition.
Lee: I appreciate that. The only topic I would love to have mentioned that I didn’t is nutrition in the epigenome because I have a strong suspicion if you see people on a highly processed food diet, I think you’re going to see epigenetic signatures.
Tom: Yeah, I mean diet is a super important part of our health. And you see that even if you take something like biological age measured using epigenetics, some of the key areas in which you can approve or decelerate your biological age or slow it down relative to your actual age are through dietary intervention. So absolutely, diet plays a huge part in epigenetics and we kind of mentioned that just with one example in the case of folate. But there’s a whole host of other components to diet that feed into epigenetic phenomena.
Tom: I guess one really interesting one is around whether cells are undergoing oxidative, so it kind of beta oxidation so oxidative metabolism versus glycolysis or sugar-based metabolism. And those two processes amongst other metabolic processes happening in cells results in different levels of different cofactors that feed again into that methylation process that happens and affects how your epigenome is developing and is being maintained. And so diet for sure plays a huge role in the profile of somebody’s epigenome.
Lee: Okay. So, I’ll finish you up because we’ve shot over the allotted time and I don’t want to be rude to you, Tom. Is Chronomics just UK only at the moment?
Tom: No. So, Chronomics, we sell our products globally. We predominantly sell now through partners and distributors. So we’re always looking for new and exciting partners that we can work with and that have, as you mentioned, interventions that they want to benchmark as well. So, yeah, we sell globally.
Lee: So that brings me on another question is when I went to the website today, it didn’t appear that I could order any more direct to consumer.
Tom: Yeah. So, if you are in the US now or anywhere globally actually, other than for existing customers, we currently only sell through partners and channel distributors for the time being, not saying that that’s going to be forever. And depending on the geography or the partner or distributor that you’re purchasing through, the pricing will be reflected in that local currency.
Lee: Okay. So for now, anybody wishing to purchase an epigenetic test needs to go to chronomics.com, fill out the form which sends you a message and then you get back in touch with them to tell them where in their geography, where to go get that test?
Tom: Absolutely. If you get in touch with us through the chat on the website and if you don’t already have a partner or distributor, we can put you in touch with one and ensure that you can get access to your epigenetic health information.
Lee: I didn’t see an offering for whole genome sequencing which you used to have. Do you still do WGS?
Tom: Yeah. So we still do WGS and we work with a number of partners. We sell, sorry, to a number of partners, our whole genome sequencing product as standard. Other partners, they are sold as separate units so you can either purchase your epigenetics test or having purchased your epigenetics test, you can purchase your whole genome test. And also, as an existing customer, you can purchase your whole genome or genomics-related product within your user account.
Lee: So I’d ordered both, epigenetic and the whole genome sequence. And so to be clear, when I log in to the Chronomics portal, I actually see both side by side. There is no major distinction. I mean, it’s the same interface used to investigate my epigenetics and my whole genome sequence.
Tom: Absolutely, absolutely. On the back end, we process that raw data in obviously distinct for the different data types but in the same framework and that is fed back to you through the same user dashboard. And on the whole genome side, you have the functionality should you wish to search across your whole genome as well.
Lee: So my plan, and I’d gotten contact with you a couple of weeks ago, is to redo the test I did last year. As in do an annual epigenetic test. And so, I’m glad we spoke and once I heard Jeff, I knew I really wanted you to come on. And so I’m glad you agreed to come on. I’m very happy you were very gracious with your time and knowledge, so I greatly appreciate that, Tom.
Tom: Pleasure, Lee, pleasure.
Lee: And I’d like to thank you again and take care and I do hope you’ll be back because that was only a tenth of what I felt we should talk about.
Tom: Absolutely. And yeah, we’d love to come back on as well, especially after you’ve done your second test. I think it would be fantastic to come back on the show.
Lee: Thank you very much, Tom.
Tom: Cheers, Lee.
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