The CEO of CENTOGENE discussed the recently announced EFRONT study in FTD and the role that rare disease genetic data collection can play in providing insights into disease intervention and treatment.
In early June 2021, Alector and Centogene announced they were collaborating on an observational study, called EFRONT, in an attempt to assess the prevalence of genetic mutations in patients with frontotemporal dementia (FTD). The study will leverage Centogene’s Bio/Databank to do so and aims to enroll and genetically test more than 3000 individuals with FTD at participating centers in Belgium, Germany, Greece, Italy, Portugal, Spain, and Turkey.1
Centogene’s disease platform has built out information on rare diseases with a real-world repository with over 3.9 billion weighted data points from an estimated 600,000 patients from more than 120 countries as of the end of 2020. Alector, meanwhile, has been developing a product candidate for the treatment of FTD, a humanized recombinant monoclonal antibody called AL001, which is in phase 3 testing for FTD with a granulin mutation (FTD-GRN) and phase 2 for with a C9orf72 mutation (FTD-C9orf72).2
To find out more about the EFRONT study, what it will assess, and the goals of the collaboration, NeurologyLive spoke with the company’s chief executive officer, Andrin Oswald, MD, who joined the company in late 2020.
Andrin Oswald, MD: The EFRONT study is being done in partnership with Alector, who is developing therapies against frontotemporal dementia. Now, to do such a study, of course, you need to find the right patients to recruit into the study. It's not that easy to identify those individuals and then also assess which of those are suited to enter to study. And I think that's where we come in. We have very strong network of neurologists in many countries around the world that we have already worked with in the past. And we do have a deep knowledge, and a solid reference lab that can do the respective research. We basically, in that study, together with the neurologists, can identify the patients, do the full genome sequencing, do the assessment, and through that, identify the ones that are eligible and suited to enter the phase 3 study of Alector’s [candidate drug].
The databank serves as the starting point for some of the diseases because we have done a lot of diagnostic work in rare diseases and in neurological diseases. So, for some diseases, when we do a study like this, we already have quite a significant number of patients already sequenced in our database. So that's, of course, low-hanging fruit. If you need to find 50 to 100 patients for a disease, if you already have 30 to 40, part of the job is already done. The second thing, then is that we, based on the data that we have, worked with a company to try to understand what we can learn from our data, and what's the profile of patient that is best suited to enter the study. Once we have that profile, we then go out and we benefit from the physician network that we have, particularly, to recruit and go and analyze and find the patients that we need to complement the numbers that are needed for the study.
The interesting thing is that whenever we do such a study, we also collect all the genomic and sometimes multiomic data, which goes back into our databank. That's the virtual strengthening cycle, which means the more of the studies we do, the stronger the databank and the easier it becomes for the next company to do the next study. In most of these areas, we see rapid growth, more research and development, and several companies developing different modalities and potential therapies for certain rare diseases. Given that we have, with that databank, an ever-increasing amount of data and insights on those patients, our value proposition becomes stronger and stronger.
Given that we have, over the last 15 years, been focused on genetic rare diseases, and many of those, as you may know, have a neurological component—especially infant and childhood diseases. Many of them manifest with neurological symptoms, such as delayed development. This is why our databank is not just about neurology and neuroscience, though neurology is a significant part of it. Many of these diseases, when you look at the origin and the pathway of the biologic cause there is overlap. A nice example is that we had, historically, done a lot of work with Takeda on Gaucher disease. When you look at the patients with Gaucher, and the pathway includes GBA, and it's also found in some forms of genetic Parkinson disease. If you have some of these early childhood rare diseases, the insights you generate are also relevant for late-stage neurodegenerative disorders.
We have also, because of that, done some work in Parkinson, for example. One of which would be that the huge study we have done with Denali, on LRRK2-mediated Parkinson, and there we have done a big study that recruited 10,000 patients. Now we are adding another 2500 to really do the full genome sequencing and the analysis of rare disease Parkinson patients, with LRRK2 being the specific one that we identify for Denali, again, to include in their clinical program. But again, all that data that comes back to us, allows us also to go deeper into Parkinson and find other genetic causes of Parkinson, or even link it back to Gaucher, and come up with new insights that are beneficial to the Parkinson field.
Absolutely. When you look at the news of [aducanumab’s approval] recently, I think it's exciting that there is even hope that a certain therapy does work, but it's a small incremental step, I think we can all agree, that is far away from a potential cure for Alzheimer. I still think that there is a lot of argument that there might not be just one simple solution to the problem. When you look at the different underlying context of these diseases, and the genetic differentiation that you see, I think even Alzheimer disease will most likely be stratified, and we will find certain therapies that are very suitable to certain patients with a specific genetic, or sometimes not even genetic, but pathway-mediated conditions. The notion of how we at CENTOGENE approach it is not from the big Alzheimer's studies with lots of patients, and can we throw something at them that will help. We are always starting with identifying patients and in a rare disease.
We are a rare disease company, and I think when we look at needs and insights we can generate with Parkinson, or with Alzheimer, maybe as a next step, it will always start with some rare mutation or some rare condition that we find in neurology or in the neurological cause or disturbance. Then we try to learn and to try to see what can be taken from this for maybe some of the bigger diseases like Alzheimer, or Parkinson, or what have you. I'm pretty convinced that we will find more of those insights that allow us to target a very specific segment of neurological patients, and for that, come up with a much better therapy with a better-detailed understanding of how exactly the pathway or the symptoms of that specific segment of patients emerges.
It's mind-blowing, at least for the less informed, that you can look at the rare disease that is very well-defined with a genetic condition or a mutation that affects a certain gene, find patients who have exactly the same mutation and the same genetic cause, and some of them deteriorate quickly and maybe even have an early death, and others, for whatever reason, live happily and well for decades. That just shows that that the genetic insight is an important thing to know. But even there, you cannot say, “I have found one mutation. Now I know how to treat or deal with patients.” Even then, you have to go deeper into the pathway. That's why we do more and more multiomic assessment to try to understand what's wrong with the cell or with the pathways. We go into proteomics and transcriptomics, and really try to get to what causes the symptoms, because the genetic mutation is just one element of the whole disease pattern within the biology.
Once we have fully analyzed up to 4000 patients with frontotemporal dementia, I would expect for us to be able to come up with great insights on what we learned from the deep biological assessment from the multiomic assessment that we do. That will be very intriguing for the scientific field, in terms of how to look at those patients, and how to potentially treat them with, not just what Alector is doing, but other modalities that we could go after. I do believe that's just the beginning of insight creation that is the journey ahead of us.
The other thing I would say is that I really think that we are at a unique time now where a few things have come together. Twenty years ago, the first genome was developed, and now we can do a full genome sequence for a couple of hundred dollars. It's now where I think the insights can start to take off when we don't have just the genome. Now, when you look at how we can analyze the transcriptome or metabolome—we have so many tools now that really allow us to mine biology in an unprecedented way. We also have artificial intelligence and big data tools that allow us to come up with the right insights. And on the other side, what comes together here in my mind is that we have also made breakthrough progress on therapeutic modalities that you can use for some of these things. The breakthroughs in RNA are really exciting. As always, maybe it's a little bit of hype right now, but there's no doubt in my mind that this technology will deliver for rare diseases, for example. In gene therapy, we have promising vectors, we’ve made progress on that front as well, and we have CRISPR, maybe not as a therapy, but as a tool. When you pack these together, I think we are at a unique time now where we can really go deep into the specific biology of the disease, which you would never do before. With a rare disease, this is absolutely critical because it's rare. If you have millions of patients with cardiovascular disease, or sometimes even with cancer, that's one thing, but here in rare disease, the patient numbers are smaller to start with. Hence, it's more important that we really have a combination of those tools that allow us, even in smaller numbers, to really go through all the data and all the modalities and come up with what's wrong.
I think we're going see more and more of that. I would really encourage scientists or physicians to work with a company like us to actually make sure that data gets collected because we need the patients around the world to actually provide the samples and to participate. The collective nature of those efforts—I find that quite beautiful. If you think about it, there's a democratic element to it because you can't do it—not just in one country, but around the world—without them. If you're able to connect those patients and their biology, you can finally figure out what's wrong and how and how to help them. I find that to be a beautiful mission, and it's something that we have set out to do and I would encourage physicians to join that opportunity for their patients.
Transcript edited for clarity.