Peak Humans Labs Podcast – Dr. Richard Pither on predicting Alzheimer’s Risk with the Polygenic Risk score

In This Article:

Dr Sanjeev Goel recently interviewed Dr Richard Pither from Cytox Ltd, a company that has developed a Polygenic Risk Score tool to determine your risk of Alzheimer’s Disease.   Listen here on Podbean or watch the episode on the Peak Human Podcast Youtube channel.

The Cytox Genoscore Polygenic risk score test will be available shortly.

For Healthcare providers who wish to register for the Genoscore – please go to Genoscore 

A transcript of the interview is below:

Hi, everyone, I’m Dr. Sanjeev Goel and this is the Peak Human labs podcast. And Today my guest is Dr. Richard Pither. From Cytox limited, UK based company has developed a polygenic risk score for Alzheimer’s disease. And I thought this was such an important topic. You know, because we’d really don’t understand how to assess risk for patients who have or who may be at risk for Alzheimer’s. And they’ve developed what looks like a pretty accurate maybe the most accurate test on the market right now. It’s coming soon to US and Canada next month and I thought Dr. Pither would be great to have on to the podcast we can explain how the test works and why you should get it done if you have any concerns about your risk of Alzheimer’s disease. Just something a side note regarding conflict of interest. I don’t have any financial interest in Cytox limited, and not being paid any fee for having Dr. Pither. This is strictly because it’s such an important topic. I hope you enjoyed today’s talk with Dr. Pither.

Sanjeev Goel 0:05
Welcome, Richard, thanks so much for taking the time today. I really appreciate it. Sure. It’s a pleasure to be here. Thanks. Thank you. So, you know, I wanted to just get right into it, I saw your presentation on the on the polygenic risk score that that’s being developed by guess your company. And I thought, you know, this is something that needs to be, you know, brought to people’s awareness. You know, I, myself am eight, but I’m an AP for three. So I, you know, I have a personal kind of vested interest in this. But I know there’s a lot of, you know, the prevalence is quite high of the APR for eliel. And population. So I think it affects a lot of people.

Dr Richard Pither 0:45
And something like 25% of the population carrying one or more copies of e4. That’s right.

Sanjeev Goel 0:50
Yeah. And I think that, you know, generally we only look at that marker. And I thought was really interesting is that there’s more to this story than just looking at e4. Lila, I thought that’s what I thought that the whole idea of polygenic risk scores are so interesting. And I think that’s where it’s going now. So I thought this is such an important topic for viewers to let to hear and then see. So do you want to just go right in and and start the screenshare?

Dr Richard Pither 1:18
Let’s do that. Yeah, let me let me pull up my slides. And we’ll go from there.

Sanjeev Goel 1:22
Yeah, perfect. And then I hope you don’t mind that I may jump in and ask some questions.

Dr Richard Pither 1:27
Just please, please, please do that. Can I just check that you can see the slide? Perfect, elaborate. Okay, great. Well, look, thank thanks again for the invitation to speak about polygenic risk score again. Today, cytoxan has been developing Geno’s score, which is our flavor of a polygenic risk score. And the aim of this product is to identify patients at the earliest stages, who are at the highest risk of cognitive decline due to their inherited Alzheimer disease genetics, and we need a DNA sample for that. And that can come from a simple saliva sample, perhaps even taken from a patient by or a kit in their own home, or indeed, by clinician in the practice. And the the big opportunity here is that by understanding risk, at the very earliest stages, there are things we can go in and do to really mitigate the chances of that risk ever becoming apparent at the level of full blown Alzheimer’s disease. And as we’ll see, that could be pharmacologic intervention, or it could be perhaps more simply a change in lifestyle, and associated risk exposure. So there are really important reasons to understand this risk at the very earliest stages. And, you know, this is really been thrown into highlight recently by the FDA, his decision to approve as you can imagine, which is going to be commercialized, it’s at your home in the US initially. And this is for patients with who are amyloid positive due to their underlying outsider’s condition at the early stages. And importantly, this is the first new drug to be approved since 2003, for the treatment of Alzheimer’s, and the first ever that purports to actually treat the underlying cause of the disease, not just the symptoms. So it’s I think it’s a really important step forward. Despite all the controversy. And despite the limitations of this drug, I think it does point the way forward for for many other therapeutics that will be coming in the future. But what people do forget is that you know, right now on today available to everyone, our lifestyle and risk avoidance factors that can be introduced into a healthy living approach that can prevent or delay up to 40% of dementias. And we should not lose sight of that, because that’s a real prize. I think that’s still to be fully appreciated by the community, and fully implemented. And we’ll talk a little bit more about the specifics of those risk factors that can be addressed today by everyone simply by adopting different lifestyle choices. You

Sanjeev Goel 4:02
think that so that the risk factor just for our viewers to understand will can prevent and delay Alzheimer’s dementia, or just

Dr Richard Pither 4:10
as the evidence Sangiovese, there was a Lancet commission paper that was published last year. I fact I cite that reference later in this slide deck, which identifies those risk factors. And, and this includes not just individuals who are pre symptomatic either very, you know, early, preclinical stages of their disease, but also people with early symptoms as well. But by aggressively addressing some of these lifestyle factors, you can actually hope the decline or indeed reduce the rate of decline of individuals who otherwise would go on to develop full blown Alzheimer’s. So yeah, it applies to Alzheimer’s, it applies to other dementia types as well. And of course, with Alzheimer’s disease, perhaps the most significant concern is the the loss of cognitive function, which actually is how our algorithm is trained and validated. So I think that that’s, again, it’s a very tangible benefit to individuals that’s available today, if we can identify those at risk early enough, and convince them to take the steps necessary to, to adopt those healthy living elements.

Sanjeev Goel 5:17
I just want to ask a question before we get further into this because I normally ask my guests, why did you devote your Why have you devoted your, you know, professional life to this

Dr Richard Pither 5:27
show, I mean, I’ve been working in this field for about 25 years. And I first started working in Alzheimer’s disease when I was a head of r&d for the medical diagnostics division of GE Healthcare General Electric healthcare, huge, multinational company, which I’m sure you know about. And primarily, I was working on the diagnostic imaging elements of this. So in other words, looking for the presence of this amyloid protein that builds up in Alzheimer’s disease and can be linked to future decline and cognitive loss. So I was motivated, you know, by understanding the disease, you know, 2025 years ago, but always understood that those high end imaging solutions were not going to be accessible to many people, due to the high cost of invasive nature. And therefore, we needed something more, we needed something that was more suitable for large scale rollout very early on to identify those at risk. And perhaps then pointing them those high risk individuals in the direction of more invasive, more expensive diagnostic interventions later, in the course of their disease. And also, of course, ultimately directing them to these, these healthy lifestyle and perhaps pharmacological treatments. Perfect, yep. Okay, so we move on. Again, a lot of your listeners will know that there are huge numbers of people, about 46 million people today estimated to be affected by Alzheimer’s disease. And this is likely to double by the end of the decade, primarily driven by the fact that we’re all living longer, because we’re living more healthily and, and that’s sort of a success of modern medicine, if you like. The downside of this, of course, is that we do need tests, therefore, to understand who’s at greatest risk. And the test that we have available today generally have, you know, major problems associated with them, not least the level of accuracy and really predicting cognitive outcome, which is the outcome that most individuals are most concerned by the invasive nature of lumbar puncture, for example, to find amyloid and tau fragments in the cerebral spinal fluid. And the very expensive nature of pet amyloid imaging, for example, to look for this toxic amyloid protein that builds up in the brain in the form of the plaque pathology, so so we were motivated to look for a test that would work was able to be used at the very early preclinical stages, but that maintained a high level of accuracy, and availability, you know, throughout the world. And then that’s where we came upon this polygenic risk component. And that’s where we started academic collaborations in the UK, initially, with the University of Cardiff and University College London, with the leading proponents of academic versions of this test, we then took and validated and modified to enter the product today that we call genius score.

The way that test works is that the saliva sample is sent to a reference lab, under the guidance of a physician is only available through medical professionals. And then the results are sent back to the physician who discusses the concerns of the individual based on that result, outcome and perhaps also, some other tests that may be carried out in parallel, for example, you know, a cognitive test battery, which I’m sure you’ll be familiar with. And it’s together that the cognitive test battery plus the genetics can give an insight into particularly people who have early symptoms, but they’re not sure whether those symptoms may or may not be due to a future risk of developing Alzheimer’s disease. So the so called mild cognitively impaired group who may be a bit more forgetful, they might have a trouble with word word recall, they might be, you know, forgetting where they left their car keys. You know, once too many times. These are the people who have early cognitive concerns that we can help. But of course, there’s a whole bunch of individuals who were much earlier in this process who may have some sort of family history or you know, a relative friends that have been diagnosed with Alzheimer’s disease and they want to understand their own risk. And so this test as we will see later Sir, is very much suitable for those individuals who haven’t yet experienced any symptoms may have concerns based on that family history. And of course, you know, if an individual who’s in that pre symptomatic stage is found to be at high risk, then we might put them onto a monitoring regime using more invasive and expensive tests, such as lumbar puncture, such as pet imaging, or even volumetric MRI scans to look for structural changes in the brain at a later stage, but only focus those efforts on people that have a high risk and therefore need closer attention. So the way the test works is that essentially with scanning for 1000s, actually about 112,000 different DNA variants that we all carry. And some of those variants that are spread across the genes in our genome, can confer a little bit of additional risk for Alzheimer’s disease and others can be protective. So what a polygenic risk test does, it looks in your DNA for the presence of these things, and then adds them together in a weighted algorithm that we call Gini score. And that allows us to then position people into risk categories. So in other words, we can identify those people who are at high risk for developing the disease in the future. And those lower risk those perhaps somewhere in the middle, and then make with a physician, of course, allow that physician to make appropriate choices, perhaps in conjunction with other tests, they may carry out, or certainly to set the kind of benchmark as to where this individual sits within an overall risk distribution across the population.

Sanjeev Goel 11:43
So I want to ask a question about this. Does that does that mean that so you’re saying that you looked at you look at 1000s of these, like SD snips? Right? Is that correct? And that means there has to be enough research on each snip to tell you what the weighted how much actual additional risk that variation has, is that correct? Like all that exists in the literature, and so

Dr Richard Pither 12:07
not Not quite. So these algorithms are actually trained on very large data sets on using something called genome wide association studies. So we’ve got basically databases with 1000s of subjects who went on to develop Alzheimer’s disease, 1000s of subjects, I’m talking 10s of 1000s of subjects in each case, who did not. And then we do a kind of subtractive, look at the sequencing data, which then highlights these different snips or variants, as you said, that link either to increase risk or decrease risk. And then what we do is we take the algorithm based on those weightings. And then we test the performance in a completely independent data set to make sure that the accuracy is maintained, not just in the training data, but in the test data as well.

Sanjeev Goel 12:59
Otherwise, we’re machine learning or AI isn’t very much machine learning on the set, and then you train, then you train it, and then you test it with real data exactly flows and how accurate it is.

Dr Richard Pither 13:13
But that’s exactly right. And and the this is this algorithm in its academic form has been tested in multiple cohorts, including subjects not only who’ve been diagnosed clinically with Alzheimer’s disease, but people who have died clinical diagnosis along with the underlying amyloid and tau pathology, as assessed either by pet or CSF testing. And that’s a kind of gold standard, because it’s the clinical symptomatology plus those underlying pathologies that equals outsiders disease versus some other dementia type. So it’s really important that the testing is done in those incredibly well characterized clinical cohorts that are completely separate from the training set. Otherwise, you risk overfitting, essentially, in statistical terms. Hmm.

Sanjeev Goel 13:59
Is there any concern about like, you know, ethnic, you know, the the type of population was tested on or?

Dr Richard Pither 14:10
Yes, absolutely, there is. I mean, so the, the all the training data, and the test data that’s available to the community at the moment is, is really dominated by Caucasian subjects. And so there’s no reason this test could not be run on any ethnic background, but the validation has been done in a Caucasian population so far. So the claims that we make are really restricted to that Caucasian background at the moment, but we are working on variants of this product that are being validated in other ethnic backgrounds. So we have an in house geneticist working with patient cohorts that we are analyzing at the moment, which will allow us we think in time to be able to offer this test with a greater level of comfort. To non Caucasian subjects as well. So the classic example of this is is what you alluded to earlier with the apple e4 Association to Apple we for association with outside this disease actually does vary across different ethnic groups. So it’s more frequent, for example, in African Americans, but the but the the the circle penetration or the impact of carrying e4 is a bit lower. So we have to modify the impact or the parameters that we use in the algorithm to take account of those ethnic differences. And that takes time. But it also takes access to well validated clinical samples from groups of different ethnic backgrounds.

Sanjeev Goel 15:46
So you know, what the mechanism, what could be the mechanism for why there would be ethnic variations if we’ve already looked at all the various snips already like, which could mean what other factor could? Yeah. Why, why it’s different.

Dr Richard Pither 16:03
The supposition here is that it’s exactly the same set of snips that you would need to describe risk in any ethnic background. But the weightings that you would apply, actually linked to two factors, one of which is so called minor allele frequency. In other words, how often do these snips actually crop up on one particular ethnic group or another? And then and then the so called effect size, which is how much of an impact do they have in that ethnic background. And so the an apple before is a great example where it occurs with a different level of frequency, for example, in African Americans, but the effect size is different. And we think that the the frequency is explained simply by different populations, you know, inheriting slightly different genetics over time. And the effect size is probably due to the fact that these snips in isolation have a very modest impact in in associations with the genes to which they are, you know, they’re co located. And so the impact of any particular snip will be contextualized, based on the other snips that you have or don’t have. So these things often occur, for example, in different signaling pathways. And so if you inherit, you know, one snip, but not another in that pathway, it’s likely to have less of an impact, for example, than someone who inherits multiple snips in that pathway. And this is, you know, this is going to link to ethnicity, simply because of the, you know, the way that genetics work through linkage disick disequilibrium and so cool,

Sanjeev Goel 17:43
but it sounds like it because you’re looking at so many different snips, all of this, the differences between ethnicity should actually cancel out. Yes. In fact, you’re looking at such a broad range that you have already adjusted for the effect of the variation of

difference. But

Dr Richard Pither 17:58
that’s exactly what I think will turn out to be the case, Sanjeev. But we need to prove that and we need to validate it before we can make claims. So I, I would, I wouldn’t want to make any great statements about the likely accuracy or the impact of accuracy in different groups, but But certainly, I think, broadly speaking, the high medium and low risk distribution is probably going to be maintained. But But within, you know, certain, you know, certain sort of, not orders of magnitude difference, that sort of subtle differences if you like,

Sanjeev Goel 18:38
got it. Okay, so thanks. Appreciate that.

Dr Richard Pither 18:42
Sure. And if we look at the details behind this, I mean, this is a so called Manhattan plot, which shows you some of the snips and the genes to which they are associated across the genome. And you can see here on the right hand in chromosome 19, apurvi stands out because as we’ve been discussing Apple, we follow links to increased risk. And there are other Apple we like low side and Gene throughout the genome. And as I said, in order to, to make the most robust product here, we did lots of work with the team at Cardiff University, the Academic Team, and we found that 112,000 gave us the the optimal performance in terms of the productivity of the algorithm. Now let’s just think about APA we for a moment. On the top left of this slide, you can see that again, this is using example an example from the Caucasian population that 25% have one or more copies of before 23% the majority have E three e four, so they would be considered to be increased risk, but in no way is the presence of e4 diagnostic in this context. Conversely, a large port part of the population and This case 61% r e three homozygote. So they have two copies of the Apple II three gene, which is not associated with increased risk. And yet we know that about 40% of Alzheimers disease comes from the so called e three homozygotes. So the question is, can we stratify for the higher and lower risk e4 carriers, that will be a really useful thing to do. And also can we find the high risk non e4 carriers amongst that large e three homozygote population. And if we look on the right hand side, here, we can see that’s the case. So this is looking at a so called apne cohort, which we’ll talk about more in a moment. But we can see that we’ve we’ve, we’ve shown a risk distribution based on polygenic risk score between zero and one on the x axis. And then we can see, we’ve color coded by Apple II genotype, we can see the e4 homozygote. So these individuals with two copies of e4, we know to be at higher risk, or distribute towards the right hand in the high risk and the polygenic risk distribution. Conversely, if we look at the the E three, e four heterozygotes, we can see that there are some very high risk e4, e three heterozygotes. But equally, there are some much lower risk individuals as well. So what we’re showing here is that we can pull out high and low risk individuals even amongst the e4 carriers. And very importantly, to in the E three homozygotes, a large proportion of the population, we can see that despite having no e4, there are still some very high risk individuals. And conversely, there are some very low risk individuals as well. So this is demonstrating very nicely that you can pull apart risk, regardless of APOE e4, carrier status. That’s a really important step forward both for clinicians trying to understand risk with their patients. But of course, also for pharmaceutical companies looking to recruit high risk individuals into clinical trials using more appropriate genetic tools, rather than just the presence or absence of the e4 allele. I thought that was really powerful. Yes.

Okay, so let me just come back to the adney cohort for a moment, because this is a really important longitudinal research study that started 15 years ago by Professor Mike Weiner, at the University of San Francisco in California. And Mike has been studying individuals who entered the adney study, either with no symptoms at all, or with early mild cognitive impairment, or perhaps even with early Alzheimer’s disease. And what we’ve shown we’d be able to access data from that cohort to prove the performance. This is the independent data set in which we prove the performance of our Gini score polygenic risk approach. So the first thing we did was we looked at the distribution, our polygenic risk amongst the outside cases here in this pink color on the right hand side at the top. And again, you can see these all have high polygenic risk. And then the age matched cognitively normal controls in blue, are at the lower end of the distributions, we can pull apart these two populations very nicely with an accuracy of over 84%. But what we really want to know is not just a kind of cross sectional look, but we want to see whether we can predict something about the future. And so we use the so called longitudinal analysis whereby we tested individuals who came into the adney study with a diagnosis of mild cognitive impairment. And then we we distributed them or we, we categorize them as low Gini score point six and below hygena score point six and above. And then we asked what happened to those individuals over the next four years from an MCI baseline. And we can see that those individuals with the low Gini score remained cognitively stable using this CDR, some of Bach’s rating composite, whereas those with a Gini score, a point six and above declined significantly over that four year period. A change of 0.5 units in any one year is considered clinically significant. So you can see from his earliest six months, certainly by two years, these two groups are pulling apart very clearly. And that would be a useful information for a physician to have, but obviously also very useful for a pharmaceutical company wanting to stratify subjects at the highest risk of cognitive decline, in order that the company could show that their drug had a meaningful impact in that population. And a little bit more data, we can see that the polygenic risk actually correlates with some of those biomarkers. Because that we were talking about earlier. So amyloid and tau in the cerebral spinal fluid is considered a gold standard for identifying outside subjects at the highest risk of future decline. So we can see here that the outside that this is a kind of heat map distribution, high polygenic risk to the Alzheimer cases in blue have high polygenic risk, and they have a high tau amyloid load in their cerebral spinal fluid, age matched cognitively normal controls, low polygenic risk low tau and amyloid and then the early MCI and in the late MCI, so elite in purple look very outside like they have a high polygenic risk and high amyloid tau and the CSF early MCI is a more distributed, so you’ve got individuals here with a high polygenic risk who are yet to become biomarker positive. So this is showing that you can identify individuals that high risk of future deterioration. And we can see that on the right hand side because what we’ve done here is overlay individuals from that previous study who declined cognitively from an MCI starting point. And we can see here that the individuals who declined have high polygenic risk, high tau amyloid load above the positive cutoff for biomarkers, whereas those who remain cognitively stable, mostly have a low polygenic risk, although there are some individuals with a higher polygenic risk, we’ve yet crossed that biomarker positivity line and therefore become symptomatic. So this is showing that the genetics correlates with known biomarkers. But without the need to go in and take lumbar puncture samples, or even pet amyloid images to identify those at highest risk.

Sanjeev Goel 26:47
And it might be more predictive, it looks like it’s predictive before the actual tau and amyloid starts to deposit.

Dr Richard Pither 26:55
I think it will predict those who are most likely to become tau and amyloid positive, and therefore at highest risk of decline. So I think that’s, that’s a very exciting intervention, because we’re opportunity for intervention because as we’ve seen with the approval of as you can imagine, that’s largely been approved on the basis of biomarker changes rather than over changes to cognition. So I think this is really pointing a good way forward for pharma companies to think about how they stratify populations for for drug development activity at that very early preclinical stage where cognitive endpoints are not useful to power, clinical development studies.

Sanjeev Goel 27:35
Yeah, it looks like some people who are go on to develop Alzheimer’s may be negative and tau and amyloid at the beginning. So what you’re saying?

Dr Richard Pither 27:44
Yeah, I mean, that’s certainly that’s certainly possible. I mean, of course, if you’re diagnosing on the basis of clinical symptoms, only then differential diagnosis between outsiders, vascular Lewy body dementia, frontal temporal dementia can be problematic. So yeah, this can offer a you know, another level of specificity if you like on top of those, you know, more commonly used clinical parameters. And this is this is really exciting. You do too. So this, you’re the first to see this. Sanjeev This is being presented later this week at the outside Association, International Congress, I’m going to tell you, which is happening in Denver, I would love to be there in person, but but travel restrictions doesn’t allow for that for the moment. So we’re doing, we’re doing this work online and virtual presentation. But this is, this is actually showing the utility of polygenic risk in the presymptomatic at risk individuals. So here we’ve used again, data from acne, but using the so called preclinical Alzheimer cognitive composite, or Pac score, which is sensitive in that transition from basically no symptoms to very early symptoms, rather than in the MCI population, where you’re looking at over clinical symptoms moving into something more substantial associated with early Alzheimer disease. So this is proving that we have utility again, both in the E three, e three homozygous as well as the E three e four heterozygote. So in this case, the lower the pack score, the more cognitively impaired an individual is, and we can see in the E three cognitively normal subjects over a five year period, the individuals who scored the lower at the lower end of the polygenic risk range remain cognitively stable, whereas those in this case with a threshold of point seven or above, after three years started declining cognitively towards MCI. That’s it That’s a very exciting result in the E three you know non e4 carrier group. Equally we can see in the e4 carrier group, we can differentiate between those who remain stable over that period. And again, those who are three years began, you know, begin to decline cognitively. So, regardless of e4 carrier status, we can see our ability here to differentiate high risk from low risk group by setting out threshold. Very exciting. So, of course, age, and genetics are unavoidable. So an age is the biggest risk for developing Alzheimer’s disease along with your inherited genetics. And the point about age is that it’s really a surrogate measure for the accumulation of lifestyle and environmental risk, which together with your genetics add up to the overall risk for developing Alzheimer’s disease. And so the importance of understanding these non variables is that you can then go in and do something about risk factors that you can address successfully. So, two classic examples of CO morbidity associated without some risk would be hypertension,

which in most people is relatively easily treatable, using a combination of pharmacologic and non pharmacologic intervention. And type two diabetes, again, which is you know, is manageable, if caught early in most individuals. So those are two things that if you knew you’re at high risk of Alzheimer’s disease, because of your genetics, you would make sure that you manage aggressively through early detection, and and then treatment as and when those risks became real. But there are all sorts of other things as well, healthy diet, lots of exercise, maintaining a stimulated brain through further education, learning, just social activities, all those things really add up to, you know, highly protective and beneficial activities that again, can be used, even in early symptomatic individuals, but very importantly, in pre symptomatic at risk individuals, so a whole bunch of things that you can do. And we’ve we’ve kind of made those slightly more accessible here on this page by pulling out some of those 12 risk factors which have been identified, both by the Lancet commission review last year, but very importantly, through a series of studies conducted by Mick Beltre and her co colleagues called the finger studies, where again, longitudinal follow up of over 1200 subjects, is shown that changes in nutrition, exercise cognitive training, monitoring, metabolic and cardiovascular risk factors can have a real benefit and measurable benefit in up to 40% of dementia sufferers and some of the specifics associated with exercise, both physical and mental health, eating healthily, stopping smoking, alcohol limits, limited alcohol intake, those sorts of things were shown objectively to have a very major impact, and they’re available to everybody. That’s the important message here. Yeah. So because of all those things, we’re making this polygenic risk score, which we call Gini score available. It’s being managed through our partners in the US and Canada who are infinity biologics. And we’re finishing off the final technical validation work that will allow infinity to introduce this study, or this product with us, as so called laboratory developed test, under the clear, accreditation, and infinity are able to provide that into clinics and to physicians in Canada as well as other parts of the United States. And we expect that launch to be happening very late August, early September, so just over a month time now. And it’s managed through a physician access portal, a web portal, a physician registers, and then orders the test via that portal. And kits are sent out samples collected and then sent back to the reference lab and a report generated that goes back to that physician for them talking through with their patients. And that whole process takes about two to four weeks up to four weeks from the receipt of sample. Okay. Yeah, islands of data. This is a snapshot of a, essentially a three page document that we provide on the left hand side, which reiterates those risks and actions that risks and actions that can be taken. We provide information as to where the individual sits in the overall population with that higher risk or not, and also how that score is likely to evolve with time, based on increasing age. So that’s a very important piece of content of course. But the also want to stress on this page that we are now getting feedback from patients as to how they have found the test and their experience in in dealing with it. So we’ve got one individual here who is known to us, he volunteered to share his experience, he was looking based on family history, a father and uncle had been suffering from dementia before they died. He wanted some reassurance about his own personal risk, very physically and intellectually active, despite being 76 years of age, just taking up canoeing, runs mountain marathons, you know, there’s not much that can be added to his,

you know, physical regime, I suspect and mentally still a very active engineer, he scored in the sort of 50th percentile, which means that he’s not at increased risk, he’s not above average risk. And for him that lady’s concerns, he had actually already worked out personal action plans, in the event that your score came back in the at risk category, he was prepared to adopt, you know, further changes to his lifestyle, if he thought that would help. And importantly, of course, he wanted to get all his future plans in place as well. So that was something he saw as a real benefit from understanding his likely trajectory in the future. And I think this all kind of adds into this picture that we’re seeing, not just in Alzheimer’s, but in many other conditions that test like these need to be, in order to for the patient to benefit the information has to be well understood and meaningful to those patients. And if necessary, actionable, you know, it’s all very well knowing you have a certain risk profile, but also, but most importantly, you want to know there’s something you can do to modify the outcome, the likely outcome. And of course, having that reinforced by a clinical professional, is really important. And I think that’s been seen time and time again, in across multiple disease types.

So

just a word to finish. If I hadn’t said it already, this test is coming to Canada, and to the US soon. If you’re a physician, and you would like to register your interest, you can go to the web portal, www dot Jena score, hyphen lab.com, forward slash register. And that will then allow us to put you on our list and get in touch and talk you through the process for for signing up. If you want to know more, more detail behind the test and have a more in depth discussion, then I would encourage you to contact our commercial partners in the US at Alzheimer’s at Vanguard pharma.com. And we’d be more than happy working with Vanguard to set up a call to go into as much detail and answer as many questions as you may have. So that you’re well prepared to to offer this test to your patients at the earliest possible opportunity. And I think you know, we all need to be aware that with the approval by the FDA of the Agile kanima product from Biogen, there’s likely to be an increased level of interest in understanding risk so that patients can begin to know whether they might be eligible for that treatment in due course. So I think being being prepared now for that wave of interest is a really important thing that we can that we can all do. Thanks very much for your attention.

Sanjeev Goel 38:43
Now. That’s excellent. Thank you so much for sharing this. couple of quick questions. I had the you said about a month that’s coming to US and Canada. Is that correct?

Dr Richard Pither 38:53
Yeah, I can’t give you an absolute date yet. But it’ll be right at the end of August or very early. September is the the Labor Day holiday, I think in September is something like the sixth of September in the US. So it’s gonna be around that sort of date, I think Sanjeev to be confirmed, but that’s what we’re working towards at the moment. Okay, and what’s the cost looking like? So, that depends that we work on a practice by practice basis, depending on, you know, the the likely volumes and, you know, you know, we can we can come to, you know, arrangements based on, you know, those sorts of projections. So, again, that’s why I would encourage individual physicians to come come talk to us.

Sanjeev Goel 39:37
These they would they would be buying it from you and then potentially charging the patient. That’s how it would work.

Dr Richard Pither 39:43
Yeah, at the moment, there’s no direct reimbursement associated with this test. We’re working on those sorts of access studies so that you know, reimbursement through insurance or national healthcare schemes ultimately, to cover the cost of that but that takes time in the field. instance, we’re making this available through private pay practices where individual patients are willing to pay for this test. And of course, you know, we will, we will agree a price to charge the clinician and the practice and it’s up to them, what they charge the patient. But this is a discussion that we will have on a case by case basis.

Transcribed by https://otter.ai

 

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