#41. Cracking the genetic code of complex chronic illness

Steve Gardner (0:04): We have suddenly built out this landscape from stumbling around in the dark. We switch the light on. We can see all of the major points on the map that we should go and investigate and explore. We've got a really detailed understanding of the disease. We know which patients have problems with particular mechanisms. We may be able to solve by finding a drug that's been studied in another disease that is acting on the same genetic target.

Emily Kate Stephens (0:39): Welcome to Make Visible, the podcast shining a light on complex chronic illness. I am your host, Emily Kate Stephens. Welcome back to our latest episode of Make Visible. We have had a slight hiatus. Welcome to Gez. Hi, Gez.

Gez Medinger (1:03): Hello, Emily. How are you?

Emily Kate Stephens (1:04): I'm good. I was away last week at the International Society of Long COVID and Post-Acute Infection Syndrome conference in Amsterdam, and I was there working with them. I got to meet such a wealth of incredible people in this space. I think there were 300 people there, over 100 presentations given, and it was absolutely remarkable.

Gez Medinger (1:27): What was the emotion that it left you with? Did it lead you with the "Oh God, we've got so far to go" feeling, or did it leave you feeling hopeful and excited?

Emily Kate Stephens (1:35): Look, there is amazing work being done in this space, and within the community, there is huge support, and we are starting to see some of those clinical trials coming through that have the potential to make a difference on a large scale. But actually, I hosted a two and a half hour live stream at the end, which was a patient recap of the whole conference, and I ran polls in that, and the patients that were watching basically said that none of that is still translating to them. And I think that was really great for the panelists that I had there to actually hear in real time, because what we need to do now is disseminate at all levels. So moving it from the lab to the clinic to scalability and moving all of that information then back down through the hospital chains right to your primary care provider, absolutely vital. But yeah, it's really exciting to see the work that's going on. Amazing to see the passion from the people that are involved and actually be there in person with them. But we've we've still got far to go in terms of actually getting the information where it's needed.

Gez Medinger (2:44): I think being a patient with a complex chronic illness is a little bit like sitting in your house, being really hungry, and hearing about all these people who are doing loads of farming and planting loads of potatoes and making cooking shows. And you're like, yeah, but there's nothing in my fridge. And when's that going to turn up in my fridge? I'm really hungry.

Emily Kate Stephens (3:03): Gez, I love your analogies. Yeah, absolutely, it really is. And you could really sense that frustration in this patient recap-the difference between the science that is starting to come and what the patients are even hearing about.

Gez Medinger (3:18): Yeah, but you've got to plant the potatoes before you can eat them, so at least we're planting them, haven't you? Yeah.

Emily Kate Stephens (3:25): How are you?

Gez Medinger (3:26): Looking forward to bedtime. In all honesty, I feel like someone's taken out my eyes and pickled them and put them back into my head, and I'm really excited about getting to 8 o'clock, which is the psychological time where I feel like it's just about acceptable to close the curtains and put my head down. I've just got to get through to something that approximates bedtime.

Emily Kate Stephens (3:43): Okay. Well, this week we actually have an interview with someone that I met, Steve Gardner. He really is doing the high level science in this space. He is the CEO of PrecisionLife, which is an AI health and life sciences company, and they do work into genomics. We had a short clip of him in the episode, which was the overview of where we are in terms of ME/CFS. And here is the rest of the conversation with Steve Gardner. You were part of the Human Genome Project. Good entry point to explain the work that you now do in genomics.

Steve Gardner (4:35): Sure. So back in about 1992, 93, in a company that I was working in, we had Jim Watson on our scientific advisory board, and Jim's thesis was very much that if we could sequence the whole human genome, we would be able to find where the genes were, and we would be able to spot mutations in those genes that were causing disease. And you you have to remember at the time that our conception of a genetic disease was in terms of sickle cell anemia or cystic fibrosis or Huntington's disease, things where one gene goes wrong and it automatically causes this disease. And they were very successful in getting the human genome funded, and we have seen the findings from that study absolutely transform the way that we think about oncology. Back in 1993, if you had breast cancer, you had a tumor in the breast, and that was it. That was what we knew about it. It was anatomically defined. You fast forward to today, and we have hundreds of therapies, a palette of potential therapies, diagnostic tools that get to exactly what are the mutations that are involved in your particular tumor, which inform the clinicians about which therapies are most likely to work for you, and we've seen this result in an ever increasing improvement of survivability across most cancers over the last 25 years, so that's clearly inspirational. But it's also incredibly frustrating that we haven't seen the same level of impact on complex chronic diseases. And just to put this in context, oncology and rare genetic disorders represent about 10% actually a bit less than 10% of healthcare spending. 85% of healthcare spending is in complex chronic conditions, and I'm talking about neurological, inflammatory disorders, women's health, respiratory, cardiovascular, metabolic, those kinds of things, which affect literally billions of patients around the world. They cost trillions of dollars. Many of those diseases have significant genetic components, but the clue is in the name: I call them complex chronic disorders. They are not driven by one gene at a time. They're driven by lots of different genes interacting with one another. You know, we have feedback loops in biology. Some of them inhibit each other. Some of them accelerate each other.

Emily Kate Stephens (7:06): That's very eye-opening. Bringing it back to that level in terms of the complexity, because I think a lot of the time people view the complexity as being the outward symptoms in terms of the layperson viewers of the symptoms. But you are saying that that genetically they are complex and they are multifaceted.

Steve Gardner (7:23): Yeah, and and in many cases, the clinical label that we use doesn't actually help us very much. So you can think about ME and long COVID, and each of those diseases has, you know, a couple of hundred symptoms that are recognized and that occur across all manner of organs in the body, you know, you you have brain fog, you have fatigue, you have GI issues. You know, there's a variety of different impacts. Actually, in reality, these are not really one disease. There are lots of molecular causes which will lead you to this symptom or that symptom, and a patient may have more than one of them. So what you see is this spectrum of presentation of different symptoms, and and in many ways calling it one disease is responsible for a lot of the enduring complexity that is inhibiting the space. You know, is inhibiting pharma companies from coming in and saying no, it's this target for this type of drug, and really understanding the the complexity of that biology, breaking it down so that we can see what is driving disease within individual patients, linking that to their symptoms, and then finding therapies that are going to be most effective for that patient is the real hope in this space.

Emily Kate Stephens (8:38): And that is your mission at PrecisionLife. To put it simply, and I don't imagine there's anything simple about looking at those genes, what you are intending to do is take this overarching data and use this genomic information to actually filter through to understand what treatments can help people, but very very specifically, and this is one of the huge things that I am told by everyone that I interview is you are hoping to be able to identify which people can respond to which treatments.

Steve Gardner (9:19): Absolutely, yeah. So this is this is precision medicine. We are aiming to get the right drug in the right patient, and in fact, at the right time when it can have an impact on on their disease. And these kind of pictures behind me are different diseases. But the principle is that we can identify genetic signatures. If you take the yellow group above my shoulder here. That is a distinct group of patients within this disease who share a common mechanism that is driving their disease. And because it's that thing that's going wrong, if we fix that thing with a yellow drug, that patient population should respond much more strongly than perhaps red group, who nominally have the same clinical diagnosis, but the cause of their disease is different. The yellow drug doesn't help the red patients, and vice versa would also be true. Understanding that, thinking about the disease in those terms as a collection of causes that actually we can potentially do something about. It is a really important driver of how to think about research in this space. There's a really important point here, which is if you have a great yellow drug that would help those yellow patients, but those yellow patients only make up 20% of your patient population, and you go to a clinical trial just with the ME/CFS label, and you've got everybody in your trial. You're only going to get at best a 20% drug response rate, and that's not enough to put a new drug or a repurposed drug onto the market. So choosing yellow patients to go into that trial means that many more of them will respond to the drug in the first place, and therefore you have a much stronger chance of actually getting a successful trial outcome. This is what holds the field back because there are so many groups here. We've never been able to stratify them and get to that level of resolution of who is actually going to benefit from the therapy that we think will help some patients.

Emily Kate Stephens (11:22): This is potentially what has been so detrimental in studies and trials that have been done to date, because you have not had those subgroups. So you have been putting entire cohorts with multi different, essentially different diseases into the same section and expecting the same response across them, but as you are actually, that's a really great visual. If you've only got the 20% yellow people, that yellow drug is not going to be sufficiently statistically significant in your trial data. This, I believe, is one of your key things that you're aiming to do with the Mello study. Is that right?

Steve Gardner (12:06): Yeah, that's absolutely right. What we did in the Mello study, which was a study based out of Salt Lake City with the Metrodora Institute at the time, it was funded by the Complex Disorders Alliance, was really look at whether we could see the same signals that we had seen in a scientific research population inside patients who were presenting either with a formal diagnosis or indeed just self-reported that they felt that they had ME-like symptoms or long COVID-like symptoms, and we demonstrated that we could the the signals that we were seeing coming out of the research studies from UK Biobank, All of Us, the Sano Genetics GOLD study and DecodeME showed up in that participant population, and that yes, we could distinguish different mechanisms that we believed would be suitable for, in particular drug repurposing studies, where we take existing medications that are safe and well tolerated, and which we believe will give a clinical benefit, they will help the symptoms of some of those patient subgroups and connect the dots between them. So we did the first part of the analysis in the in the Mello study, and we have a new paper coming out on on that, so that that study is going. It has also led us to designing with groups around the world drug repurposing studies, which are targeted. So, if we have an existing drug that we think will help those yellow patients, we can go and we can use the genetic reporting to find patients who would potentially benefit the most from a yellow drug. Design a trial specifically around them and use one of these repurposed medications to see if we actually see that alleviation of their symptoms.

Emily Kate Stephens (13:58): That's fascinating. Let's take it back to the top line of how you do this, because there are multiple strands of PrecisionLife that involve the genetic testing. And interestingly, you are hoping to develop this in in some of these complex diseases to be actually completely non-invasive testing. Is that am I right in thinking?

Steve Gardner (14:20): We're designing genetic reports, which can be used by consumers to become informed more about their health, their wellness, and the impact that they could potentially have on their symptoms.

Emily Kate Stephens (14:34): So that is just one component. Explain to me the multiple arms of the way that you work, the way that you gather data, the way that you analyze it, and the other side that also involves you analyzing pharma and biotech their pipelines to establish then the drugs that are either already on the market or in production that might might help because that kind of umbrella is actually what has the potential to enable us to move forward for the patient, not just in our understanding.

Steve Gardner (15:09): Yeah, absolutely. It stops it being a science exercise and turns it into things that will benefit patients. And it's the quickest and cheapest way I know of getting effective therapies into the hands of patients, which is why we've pursued this. But yeah, to back up, so I mentioned the frustration that we'd had with not being able to get the same level of results as we've seen with oncology in complex diseases. ME and long COVID are complex, really complex diseases. So, unfortunately, to date, there have been very few, and in fact, no really reproduced genetic associations published in either long COVID or ME. There are hints of this through the DecodeME study, the eight loci that were highlighted, but one gene, eight genes-they don't explain the entirety of this disease. So what we wanted to do first off was to map the landscape of all of the different genes that we could see in ME, all the different genes that we could see associated with long COVID. That's two separate studies, and then see whether there was an overlap between those two, and then within those, come through and evaluate which ones were most what we call druggable-the ones where we had a really good sense that we would be able to intervene in that process and fix it. So we started with different datasets. We started with UK Biobank in ME, and then we ultimately the findings of that study we replicated in DecodeME. On the long COVID side, we partnered with Sano Genetics, got access to their Gold dataset long COVID patients, and Sano we we replicated in the All of Us database,

Gez Medinger (17:00): Which is a U.S. based database.

Steve Gardner (17:01): It is U.S. based. A very very diverse ancestry, very diverse socio demographics. This is a series of four major studies over three years or so. What we found were several genes that were associated with long COVID in the first instance. We had something like 80 genes within the highest confidence of long COVID because some patients in that study it was a very early study people didn't really know what long COVID was when the data were collected so it was a little bit noisy but we ended up with about 80 genes in the long COVID side of things and then from the first study in UK Biobank we had 14 genes that we found in ME. Ultimately, we expanded that to 259 using the DecodeME database. So now we've got 260 genes over here. We've got 70 odd genes over here, and we wanted to look at the overlap between them. And the long story short is, we did this three times using three completely different methods, and it appears that about 40% of the genes that confer risk of ME/CFS also confer risk of long COVID. So there is a significant overlap. We see genes like the insulin receptor, which deals with energy production. We see genes like the clock gene, which deals with circadian rhythm, showing up in in both cohorts. But also, 60% of the genes are different, so these aren't the same disease, but they share quite a bit of biology. So then the second piece is, well, what can we do about this? That's great science, as you noted earlier. Lots of papers that we've put out in this, but what can we do about it? And the first thing that we can do, because everything that we're finding in ME and long COVID is a new finding, it hasn't been studied by a pharmaceutical company in the context of ME or long COVID. Now that doesn't mean it hasn't been studied in the context of other diseases, maybe diabetes, maybe obesity, maybe neurological disease, maybe something fibromyalgia, for example, pain-related disorder. And what your listeners may not appreciate is that there are literally tens of thousands of compounds that have been trialed by the pharmaceutical industry, or in the process of development, that are different from the drugs that are actually on market. At the same time, there are also some drugs that were on market have now their patents have expired, and so they become what we call generic. Yeah, ibuprofen, you know, paracetamol, aspirin. These are all great examples of generic drugs. They become cheaper and much more widely available. But we also know, because they've been prescribed for decades, that they're safe, they're well tolerated, and we understand the doses that we can give to have an effect on the body. So now we've got a really detailed understanding of the disease. We know which patients have problems with particular mechanisms that we may be able to solve by finding a drug that's been studied in another disease that is acting on the same genetic target and either amplifying its effect or inhibiting its effect as required. If we can find a match, it's a bit like playing Snap, I suppose. If we can find a match between those two things, we have a really strong scientific hypothesis and the clinical development tools, the biomarkers that we can use to select the patient population that says these people should respond to this medication, and that's phenomenal. That in itself allows us to perform a series of clinical trials, which are much smaller than they would otherwise have to be, and have a much higher chance of reading out with success.

Emily Kate Stephens (20:53): Are we set up for this yet in terms of the way that clinical trials are designed, either UK, US, within Europe. I don't know which specific authorities you might be able to talk on, but in terms of at the moment, you tend to have to have this the diagnosis for you to register. So you you put it in as ME/CFS. If you are then saying we're taking a subset of ME/CFS patients to treat, not a blanket. Are we set up yet in terms of the approvals for the actual level of science or that level of detail that you're able to offer?

Steve Gardner (21:36): This is where all I think of the major governments and major regulators want to go. They've been encouraging the industry to to go down this path. But if you're talking about the pharma industry, it tends to see an opportunity of a whole disease as being a bigger market.

Emily Kate Stephens (21:54): Almost more is better.

Steve Gardner (21:56): Yeah, yeah, exactly. So take up on that capability has has not necessarily been great when you're thinking about new drug discovery, but here we're talking about repurposing, and so in the UK, NIHR has made money available for a couple of centers in the UK to do precisely this kind of genetically targeted trial design. In Australia, we're working with groups in Melbourne who are wanting to use precisely this, actually across multiple different mechanisms, an adaptive trial design that says you'll go on initially onto the drug that we think will benefit you the most, but we're going to have three drugs in the trial, and we'll then switch you onto a combination therapy to see whether you get additional benefit from one or other of the other medications, Germany is setting itself up to do this. They've got huge amount of federal funding. The Netherlands is doing it, and various centers in the U.S. particularly those affiliated with the Open Medicine Foundation, are also looking to use these kinds of tools. So, yeah, I think it is really it's so essential for the space because again we don't have patient populations of 90% of ME patients who will all respond to one thing. The disease just isn't like that. So in order to be successful at any level, we need to bring this stratification into that design.

Emily Kate Stephens (23:21): Now, from those studies, from the LOCOME and that cross that crossover of the genes, I believe that you found nine safe generic drugs that could potentially help across both.

Steve Gardner (23:38): Yeah,

Emily Kate Stephens (23:39): are those drugs that require prescription.

Steve Gardner (23:42): Some of them are. Some of them are not.

Emily Kate Stephens (23:43): Okay, but they are widely available and safety tested.

Steve Gardner (23:47): Yes, yes. I want to be very careful. However, when we published the paper, we published all of the all of the SNPs, all the mutations, all of the major findings of the results. What I do not want people to go and do is suddenly start googling these things, and you know seeing which of the drugs they can get hold of. They will not work,

Emily Kate Stephens (24:08): you know, because this is the foundation of the work that you're doing

Steve Gardner (24:12): exactly, and that could do a lot more harm than good, both at an individual level and also in terms of the way that we're approaching this. The community needs to get behind responsible science and build the evidence to say yes for these people. These drugs will work. So that's what I want to do. So yes, on LOCOME, we found nine repurposing candidates that we felt would work across both disorders. In the latest publication, the DecodeME analysis, we actually identified 42 repurposing candidates. That's obviously many more than we have clinical centers. One of the things that we said in the paper, we say very openly, is any bona fide research group that's out there, we will be delighted to help them design ethically sound trials that protect the patients don't raise false expectations, but which will go and test the efficacy of these medications in those patient subgroups.

Emily Kate Stephens (25:12): And that is the most important thing: that your work is based on the subgroups and identifying which patients will be suitable for which treatments?

Steve Gardner (25:24): Absolutely.

Emily Kate Stephens (25:26): And yes, there is this genetically shared pathophysiology between ME and long COVID. You're not saying they're the same conditions. I had the conversation with Amy Rochlin , and this very complicated situation of we have these diseases that are being used together, and we almost need to break out the subsets of those diseases, and then look at the components of those subsets, and then potentially group them back together where the ME and long COVID overlaps.

Steve Gardner (25:58): Yeah, if you're a pharmaceutical company, at the end of the day, people are entitled to have their views about commercial research in this. But I think it's pretty undeniable that we would all benefit from having the interest and the R&D budgets of major pharma companies focused on these diseases. So what we've tried to do is to show that there are a series of mechanisms, there are a series of drugs that can affect both populations at the same time. And let's be honest, that's at least 65 million patients around the world, quite possibly more, where there is no competition, and we don't have existing drugs in the same way as we have with the GLP-1s, for example, where there are hundreds of companies trying to play in that space, but these would, for this patient population, this would be a very attractive marketplace if we can get through that complexity of the disease, demonstrate that we can select patients who would benefit from drugs targeting particular mechanisms or genes. If you have that clarity at a mechanism and gene level of what what should I be building a drug against, and if you can also demonstrate that you can select the patients who will benefit from that drug, that is a level of confidence that I think biopharma has been missing, and it's one of the huge reasons why they've ignored this space for so long.

Emily Kate Stephens (27:27): There are a lot of people, individuals, spending huge amounts of money on unlicensed supplements and unproven techniques. People are desperate, so people are spending their own money on it. There is definitely the appetite, but I absolutely understand what you're saying, and I'm not necessarily condoning them because obviously we would all like to move more quickly. But I understand why there's not the appetite for them to, without that genetic reassurance, to invest money. I've read in one of your papers specifically that you have identified predictive biomarkers and treatment response, but can we say that you have identified biomarkers for these conditions that could be replicable in terms of diagnosis and therefore future treatment?

Steve Gardner (28:21): So this is where it becomes challenging, and we've got to be careful about the language that we use because the word diagnostic has a regulated meaning, and the fundamental problem is that there is no agreement on what ME is or what long COVID is, and certainly not a regulated diagnostic that can say yes, this is that, and this is the other. By the same token, there's no clinical care pathway that we can guide people to, even if we did have such a diagnostic. So the disease is at a very early stage. From a purely science perspective, what we can say is that we have very strong association between the subgroups that we're seeing and the genes and mechanisms that are involved in those, and the symptoms that we see for those patients. Now, I'm being very careful about language here. This is at a science, a research level. We can make those connections. They're statistically significant. They're reproducible across multiple patient populations. They hit all the standards of evidence that are required. But the key experiment to run is to find out whether drugs that have an impact on those targets in a particular direction are going to benefit patients that we can see. So it is these targeted drug repurposing trials that I think are absolutely critical. I think they will take us further and faster than anything else in terms of getting the diseases recognized as having a biological basis, getting clinicians to understand that they can do something for patients, which I think is one of the reasons why there's so much gaslighting out there because clinicians feel helpless in in the face of a complex disease that they don't even know where to start with. I think that'll bring pharma dollars in because they can see something is working in 20% of a 400 million patient market. That's a huge new marketplace for them to work in. And the analogy I draw is if you remember all the way back to the COVID pandemic in the UK, we instituted very very quickly the RECOVERY trial, and this was using the NHS patient population essentially as a big open label, randomized but still open label clinical study to test the impact of drug repurposing candidates, and within six weeks, for less than £2 million, we found dexamethasone. Dexamethasone has saved way more than a million lives now. It became almost overnight the standard of care for severe, yeah, for severe acute COVID-19 patients. There is absolutely no reason why we shouldn't be able to do the same thing in exactly the same way with more targeting in long COVID and ME/CFS, and in fact a whole bunch of other diseases as well.

Emily Kate Stephens (31:10): That description with the dexamethasone definitely gives hope. But you said there that we are in an early stage of the disease. When we're talking about ME, people will say we are 30 years down the line, really in terms of our scientific trying to get some understanding on it. That if we think back also to the Human Genome Project in the early 90s, how far do you feel that we have come as a scientific field in terms of our understanding and what we have the potential to do for ME/CFS patients.

Steve Gardner (31:51): I think we hit a transformational point with the publication of our last paper. It was a collaboration between ourselves, DecodeME and Action for ME. Innovate UK funded the LOCOME project. It's not that we can't find the genes associated with the disease. It's that there are too many genes associated with the disease. This is not one disease. It's technically what we call polygenic, and it's technically what we call heterogeneous. We have now proved that there are hundreds of genes involved in this disease, and therefore our understanding of how we should go about studying this disease, how we should go about designing clinical trials, how we should think about how to impact the disease within patients is fundamentally different from where it was, let's say three, four years ago. Now we understand we have to do stratification, just like we do with cancers these days. We have to do the the genetics. We have to understand the mechanisms at work in individual patients, and we have to design therapies for them at an individual level, out of a combination of medications that are most likely to work for them individually. That is a fundamentally different starting point. We have 260 genes now that we can go after. We have 42 repurposing candidates that we can trial. We have suddenly built out this landscape from stumbling around in the dark, we switch the light on, and now we can see it. We haven't solved it yet, but we can see all of the the major points on the map that we should go and investigate and explore. And I think that is a profound shift in where we are with the disease, and it gives me great hope that we're going to be able to find solutions for patients much quicker.

Emily Kate Stephens (33:43): That is incredible. You wrote that the study reinforces that ME is a complex, multi-systemic condition with a clear genetic basis, and I think it is that clear genetic basis that, for patients, takes it from being something that has been so stigmatized and ignored and blamed on the patient because you have that scientific evidence that there's this genetic basis for it, which is remarkable,

Steve Gardner (34:16): and it's unarguable now. While we were trying to find one SNP or one gene, and nobody was really agreeing with each other. Everybody has their own theory about which things are involved. They're probably all right, but not for the same patient. So different subgroups of patients. Now we have unequivocal, peer-reviewed, multiple times, multiply replicated results that are out there that demonstrate there is really strong biological basis for both diseases.

Emily Kate Stephens (34:46): Actually, how can our audience, who is interested in involvement in the future with PrecisionLife and your data gathering, can you tell us how we can get involved?

Steve Gardner (34:59): Yes, on that side of things, we're designing with key opinion leaders, with research groups around the world, studies that will use a genetic selection as the front entry to the trial. So, if we have three different drugs that we're aiming to trial, we'll test you once, and if you are positive for one of those, you will be recruited into that arm of the trial. We also want to use these with existing trial designs. GLP-1s is one example of that, but there are others where we believe that we will be able to enrich the population who will benefit and therefore increase the probability of success of that trial by pre-selecting patients who have those mechanisms that will respond to those forms of drugs. That's what we're doing in the short term on the research side of things. This is also science that we are in a more consumer-focused sense also aiming to bring forward genetic reports, which can help patients understand their disease, their genetic profile a little bit better, and help them with wellness insights that can support awareness, can support informed conversations about their health as well. All of this is obviously based off similar kinds of underpinning research.

Emily Kate Stephens (36:19): In terms of what you are moving towards in the future in PrecisionLife, you're also hoping to use some of this understanding. As you said, what's the protective biology in some of these people? Why do some people remain healthy? And you are looking potentially. I know that this doesn't help with the people who are already infected, but you are in the future looking. Maybe there are protective vaccines that could be developed.

Steve Gardner (36:47): Yeah, this is really exciting science. We've been able for the first time to almost turn the analysis on its head. Instead of saying which genes show up more in patients than in healthy people. We're asking the question the other way round. We're saying who are the healthy people who have lots of risk genes in their makeup but don't get the disease, even though they may have had repeated viral infections and other disease risk factors. The hypothesis is that they're not getting sick because the background processes in the body are preventing them from from doing that. They're resisting disease pressure. We have found in other diseases such as ALS or motor neurone disease, and in endometriosis that these processes exist and they do indeed actively work to resist the development of the onset of symptoms and the severity of those symptoms. So this is great. Now you could think, what does the COVID mRNA vaccine do, for example? Well, basically, what it does is it turns your muscle cells into a little production factory for certain proteins. In the COVID vaccine, they produced viral spike protein, and we can talk about the pros and cons of having lots of viral spike protein kicking around in the context of a therapeutic vaccine. What they would be producing are more copies of your existing proteins that are the ones that are resisting these disease processes, So you're turning up the volume on this protective signal, and in principle, that benefits pretty much everybody. It's not like a drug that's just fixing one thing that's gone wrong in in a certain set of patients. Everybody would benefit some, some a lot, some less from having more of this protection. Of course, you can also use drug repurposing. So we're also actively looking for compounds that stimulate those same processes, and there are examples of those. And in fact, I referenced one of the studies where we've got three arms. Two of them are for risk genes. One of them is for a protective gene. So I'm really excited about that as a as a way of giving us a better toolkit with which to to deal with the disease.

Emily Kate Stephens (39:08): This is very exciting. It's one of the things that I speak to so many people about is that our healthcare system is not actually a healthcare system. It's not set up for health. It's set up for sickness. So you're suggesting that you might have in this, and I guess to a degree, when they give us vaccines as babies, we do have to a degree the healthcare because we are trying to prevent certain things. But the idea here is that you are helping to prevent people with that known susceptibility from succumbing to the disease, which is remarkable.

Steve Gardner (39:38): And I think this gets really down to how, in the future, we would want to manage the disease. I think if we know that there are people who are particularly at risk, we would want to work harder to ensure that they're vaccinated. We'd want to work harder to make sure that they weren't exposed to disease triggers and particular infections, and we'd want to work harder in terms of augmenting protective processes that they have going on in their body, and all of those measures together, I think would give us a way of preventing many people from experiencing the most debilitating forms of disease. And I think that everything I've said is true in ME. It's true in long COVID, and I think it's true across all complex chronic diseases. There are shared attributes of these diseases that have made them more difficult to study, have made them more difficult to get effective drugs or better diagnostics, and they would all benefit from from similar types of approaches.

Emily Kate Stephens (40:38): Can I ask a question that, for you who works in genetics, might seem very obvious, but if we are talking about some people having the genetic code to actually suggest that they could develop these conditions, does that give a suggestion that there is a potential hereditary inherited element of that genetic code?

Steve Gardner (41:00): Family history remains one of the strongest predictors for many complex diseases. That is also true to some degree in long COVID and ME. Most of the studies that you see, the level of genetics that we can say definitively are associated with the disease actually don't explain all of that heritability. I remember the figure for endometriosis, so forgive me for using a different one. But endometriosis is about 50% heritable, but the genetics that we found using those tools that were developed originally for cancer only explain about 5% of the disease. 90% of the genetic signal we're just not seeing, so we've developed a different methodology that allows us to find more of that signal in the first place. But the second piece of that is it goes back to this clinical label question: Did those people actually have the disease? Were they diagnosed correctly? And were people who were dismissed out of the clinic

Emily Kate Stephens (42:00): not diagnosed?

Steve Gardner (42:01): Probably, yeah, not diagnosed. They were missed as opposed to misdiagnosed, and I think there's a there's a lot of that going on inside these diseases. As we get better at understanding the genetics of these disorders, that will give us better diagnostic tools, and those better diagnostic tools will in turn allow us to define much more specifically the patient populations that we're dealing with, and that has absolutely been the the experience in oncology. We now know HER2 positive breast cancer, we know hormone responsive breast cancer, we know triple negative breast cancer, and they're defined much more narrowly and much more accurately than previously, and that it has led, as I said, to sustained improvement in survivability of those those tumor types.

Emily Kate Stephens (42:49): It's amazing. I think it's very hopeful, but I also like your caveating. The research is there, but warning our audience that because we have this information doesn't mean that they can.

Steve Gardner (43:01): It doesn't mean that it will work for them. Unfortunately, we still need to do the science. We still need to do the clinical trials. I would say two things. Number one, if if your listeners want to read up about this, they're very welcome to go to the PrecisionLife website. We have a link through precisionlife.com/mecfs.

Emily Kate Stephens (43:23): I'll include that in the show notes.

Steve Gardner (43:24): Thank you. All of those studies are referenced there, plus some talks, podcasts, etc. The second thing I would ask, if your listeners are are interested, we are trying to understand the appetite of the community for a consumer-facing genetic report and trying to understand how best to structure that and how best to bring it to market. So on that page as well, there is a button to take a very short survey, a two-three minute survey that we would like to hear from the community whether this would be valuable to them, how it should be reported, and how best we can essentially bring this to patients with these diseases. So the help would be very gratefully received on that.

Emily Kate Stephens (44:13): I've signed up. It's really, really very simple, very straightforward. So I encourage people to go and do it because if it enhances your understanding of what the community needs when you have access or you have the ability to do this very very wide ranging research, then I really really would encourage people to take part.

Steve Gardner (44:30): I'm being very careful what I say. This is a consumer facing wellness test. However, in the fullness of time, what we would like to do to address the question that you raised earlier, we would like to be able to bring this into a more diagnostic test. We're not there yet. This isn't. This test is not that test. There's more science to be done. There's more research and validation work to be done. But these are stepping stones that we need to make with the disease in order to be able to understand it better and to have those tools that we could then use in the clinic once we do have some medicines that work to guide people towards things that are actually going to be effective for them.

Emily Kate Stephens (45:09): For them, and that is the key to what you're trying to do. Thank you so so much for your time today. It has been an absolutely brilliant conversation. I've so much enjoyed it.

Steve Gardner (45:20): It's been a pleasure, and thank you for your advocacy and the awareness that you bring, and the information that you bring for the patient community. It really is appreciated.

Emily Kate Stephens (45:35): So, Gez, tell me your thoughts.

Gez Medinger (45:38): Well, first of all, just so pleased to hear someone banging the same drum that I've just been banging, feeling like I've just been waving my fist at clouds. I loved the way that Steve put it, which is: let's say we've got ME, or let's say we've got long COVID, or any complex chronic condition. Inside those, we've got a rainbow of colors, which are essentially the phenotypes of people inside those conditions. And what we need to do is to test the drugs that might work on the yellow people with the yellow drugs, right? Put those people into a trial together, and don't put the yellow drugs into a trial with the whole rainbow, because you're only going to get a small amount of people responding to it, and then it won't be statistically significant, and you've got a null result. This might well have been, or this is what rumor has it was the problem with trials like the BC007 one, and again, there's some word on the street that some of the antiviral trials that are happening at the moment are having similar responses. That is to say, some people respond incredibly well and are marvelously better than they were, and other people don't respond at all. But when that's 15% of your group, that's not enough for that treatment to go on and reach the next phase of a trial. So having the right tests that we don't have to argue about. This is the dream, right? I think there is still a little bit of argument about exactly what these biomarkers should be and just how much we can read into these genetic results. But fundamentally, if we have a set of things that we can just do a blood test and go, great. These are your genes. These are the ones that are at high risk. These are the drugs that you should consider taking because they've all been through RCTs and they have X percent efficacy. Now that we can see you're in the green group, here are the green green drugs. And what's what's really interesting is how what we might find is that whilst long COVID and ME/CFS have different rainbows or different shades in all of them, we might find that the yellow group in long COVID is actually the same as the yellow group in ME/CFS or the green group in ME/CFS. However, you want to use the metaphor, but fundamentally, if we've got this 40% crossover with the genetic results they're seeing between ME/CFS and long COVID, what's really interesting to me is that that's about the proportion of people 40 to 50% of people who have long COVID who fit an ME/CFS diagnosis, who fit the criteria. I'm one of those people. It's about labeling is so important as well, right? And are we going to go on to a place where we have eight different labels for subtypes of long COVID, and are they going to be eight for ME/CFS or 20 or or who knows? And as Steve said, there's so many genes. The problem they've got at the moment is actually too many results rather than not enough results. And how do you make sense of those?

Emily Kate Stephens (48:13): We've spoken to people before about this comparison with autoimmune. Initially, it was kind of classified as one umbrella term, and now it's been broken out. If you have the ability to break it out in terms of the genetics and operate on this can fix the yellow, this can fix the green genetics. Then you have a far greater chance of people actually yielding the results. But I think that is fascinating if we reflect back on those trials that have proved inconclusive, or that haven't worked, despite very positive indications before entering the trial phase.

Gez Medinger (48:47): Very positive indications in the trial phase, but just not on enough scale. You know, like with BC007, we had a bunch of people coming out saying, "I'm better," and still, it wasn't enough to make the whole trial work. But the sheer mechanics of making trials work is half the battle, and we've just got to get the groundwork right. And it sounds like we're finally in the position to be able to do that. And that's what's really exciting about this. But again, this is planting the seeds in the fields. It's going to be a while before the potatoes turn up in our fridge, sadly.

Emily Kate Stephens (49:15): Absolutely. The other exciting thing about this is though that PrecisionLife are working with a huge number of the other groups in this space, so the the way in which different groups are collaborating, and he had a call to action for researchers who want to actually start doing some of the trials with them. The other thing that has come out in the past week in terms of PrecisionLife is that they have announced that they now have a US partner to launch and deliver that DNA wellness report that he spoke about right at the end, which is going to include DNA home testing and the idea of being able to do that kind of testing to understand your genetic makeup without having to go into a lab is going to make such difference for all of those people who have not been able to be involved in certain trials or not been able to establish certain things about their bodies because they're unable to travel. So the way in which they are designing really, really is with the limitations of the community in mind.

Gez Medinger (50:21): Yeah, absolutely. There was just one other point that I, I guess, I would just like to point out, or clarify, and also just point out my own confusion on, and that is the what is genetics, right? It's an incredibly confusing subject, and we all know that we have genes. That's why you look a bit like your brothers and sisters and your parents and the rest of it. But the genes I think that are being talked about here are the myriad number of genes that you have in your body that have a function, and they can switch on and they can switch off. And what we're talking about when we talk about therapeutics here is about modifying the function of that gene. We're not turning you into some sort of mutant superhero by changing what your fundamental genetics are. We are simply affecting, but at a very fundamental level, what switches on or switches off certain processes in your body, and by modulating those, we can change everything that's downstream of those. So it has the potential to be really very effective, and potentially far more effective than trying to treat symptoms, which is treating from the bottom up. This is trying to look at the top to try and treat from the top down,

Emily Kate Stephens (51:21): Yeah, I think he used the word augmenting, didn't he?

Gez Medinger (51:24): Yeah.

Emily Kate Stephens (51:24): You're trying to augment the behavior, I think, of those genes. So it's an exciting space. And if you want to know more about the work into genetics and genomics that PrecisionLife are doing, Steve and his co-founder Rowan have a fantastic podcast that delves deeper, and I highly recommend checking it out. Gez, this has been fantastic. Thank you so much for gracing me with your time.

Gez Medinger (51:50): You too.

Emily Kate Stephens (52:00): Thank you for listening to Make Visible. Please do like, follow, or subscribe to listen to our next episode, where we'll be uncovering more insights into complex chronic illness. This was brought to you by the team at Visible, a group of scientists and engineers whose lives have been affected by energy-limiting health conditions. We're building wearable technology that's helping 100,000 people measure and manage their complex chronic illness. To find out more about what we're working on and how Visible could help you, visit our website at makevisible.com.