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- [00:01]
A
I'm john strum and this is real talk, mississippi. It's January 20th, and we have a lot to talk about. One of the more confusing aspects of Ms. Is that it can present differently from one person to the next. We can all probably think of examples of two people who have been diagnosed with relapsing remitting ms, yet they seem to experience a very different disease course. A research team at University College London may have uncovered a reason for that when they identified two new and quite different subtypes of Ms. This breakthrough discovery is an important step toward being able to answer the question, why does Ms. Affect different people differently? Joining me today to walk us through this discovery and to explain how it may impact Ms. Clinical care is the study's principal investigator, Dr. Arman Ashagi. But before we get to my conversation with Dr. Ashagi, there are a few other things that you should know about. In 2022, researchers identified the Epstein Barr virus, or EBV, as a trigger for Ms. To say it another way, the Epstein Barr virus isn't considered the cause of ms, but it's a necessary ingredient. The Epstein Barr virus does cause mononucleosis and it's also been shown to cause other non specific childhood illnesses. It's estimated that about 95% of the world's adult population has been infected by the Epstein Barr virus. And for most people, EBV appears to simply lie dormant in our bodies. What hasn't yet been determined is exactly how EBV leads to Ms. And since the great majority of people carrying EBV don't develop ms, the other question to be answered is why? Why do only a very small percentage of the people carrying EBV develop multiple sclerosis. Results of a study by a research team at the University of Zurich may have provided some answers to those questions. The Epstein Barr virus infects B cells in our immune system. Many experts believe that EBV infection can alter B cell activity, making someone more likely to develop Ms. And in this study, the researchers found that an EBV infection can alter the activity of a B cell protein called the human leukocyte antib antigen, or hla. The HLA protein actually displays pieces of infectious bacteria and viruses in the body, allowing our immune system to identify threats and sound the alarm. Now, you should also keep in mind that there are many variants of hla. These variants are referred to as haplotypes. And an individual's genetics determine which HLA haplotype they're carrying. Previous research has shown that people with a specific HLA haplotype known as HLA Dr.15 are at an increased risk of developing Ms. In the study, the researchers found that when B cells with this HLA Dr. -/15 haplotype are infected with the Epstein Barr virus, their HLA molecules begin to display pieces of myelin basic protein, which is a key component of myelin. And just a quick reminder that multiple sclerosis is a demyelinating disease where healthy myelin is attacked by the immune system. Now, in this study, healthy B cells that weren't infected with the Epstein Barr virus did not display this myelin protein on their HLA molecules. In cell experiments using immune cells from Ms. Patients, the researchers demonstrated that T cells, one of the primary types of cells in the immune system, that recognize the proteins displayed by HLA and respond, while the research team showed that T cells can respond to the pieces of myelin protein presented by EBV infected B cells. So what did the research team conclude from this study? Well, they were able to show that in individuals who are genetically predisposed to developing Ms. Because they carry that HLA Dr. -15 haplotype, the Epstein Barr virus can cause their B cells to mistakenly display healthy myelin proteins. And why is that important? Because that display of healthy myelin proteins tells other immune cells, those T cells that healthy myelin is invading the body. And those T cells respond by doing what they're programmed to do, in this case mistakenly attacking the healthy myelin in an individual's central nervous system. So it's this combination of the Epstein Barr virus and the HLA Dr. 15 haplotype that may explain how EBV contributes to someone developing Ms. If you're interested in reviewing the details of this study, you'll find that link in today's show. Notes it's estimated that more than 72,000 former U.S. service members live with Ms. And last week the Paralyzed Veterans of America announced that they're rolling out free online adaptive fitness and wellness classes for veterans with ms, ALS and spinal cord injuries. These expert led classes are powered by Warrior Strong, a non profit organization that's dedicated to improving the physical and mental well being of veterans and their families through free fitness and wellness programs and these classes are being offered to veterans as well as their caregivers. Participants in this new program can access up to nine weekly sessions designed to improve strength, endurance and hand eye coordination. The classes are available for individuals of every level of ability and in addition to adaptive exercise, classes are also being offered in meditation and breath work to help reduce stress and support an individual's mental health. If you're a veteran who's interested in reviewing the schedule of classes or registering for a class, you'll find that link in today's show. Notes. Last week we told you about the launch of Chat GPT Health. That launch was followed just a few days later by an announcement from Anthropic, the company behind the AI large language model Claude, that they were launching Claude for Healthcare, a set of HIPAA compliant tools for healthcare providers, insurance companies, biotech firms and patients. Claude for Healthcare is sort of an AI powered Swiss army knife for the entire healthcare ecosystem. If you're an insurance company or a healthcare provider, it can be used for prior authorizations and patient care coordination. Claude for Healthcare can help pharmaceutical and biotech companies with regulatory submissions to the FDA and Claude Pro and Claude Max. Subscribers here in the United States can connect their lab results and their personal health records to Claude and Claude can explain test results in plain language. It can detect patterns across an individual's fitness and health metrics, and even provide you with a list of questions for an upcoming medical appointment. With this second major AI entrant into the healthcare ecosystem, make no mistake, a not so quiet revolution is underway and we're here to keep you updated. As artificial intelligence begins to fundamentally impact every area of of Ms. Care. From early stage clinical trials to regulatory submissions to the care you'll receive in the clinic, it's going to be exciting to see these changes as they occur. I want to take a moment to welcome a new sponsor to Real Talk Ms. This episode of Real Talk Ms. Is sponsored by Able Now, a Tax Advantage savings program for people with disabilities. If you're living with multiple sclerosis, this is important news. Expanded federal rules mean more adults with disabilities, including many people with ms, can open an ablenow account. Ablenow lets individuals save and invest money without affecting their eligibility for certain public benefits such as SSI or Medicaid. For many of you, it can be an essential financial tool. To learn more and understand if you're eligible to open an account, visit ablenow.com and you'll find that link in today's show. Notes Talking about how AI is going to impact healthcare feels like a perfect segue to my conversation with Dr. Arman Ashagi, who used artificial intelligence to identify two new subtypes of Ms. That begin to explain why why Ms. Impacts individuals differently. In a moment, we'll meet my guest, Dr. Arman Ashagi. Doctor Arman Ashagi has just published results of a study that combined MRI scans with blood tests for serum neurofilament light chain, which led to the discovery of two new biological subtypes of Ms. Just as a quick review for our listeners, Serum neurofilament light chain is a protein that leaks into the blood when nerve cells are damaged. You can think of it as a smoke detector for the brain. Well, welcome back to the podcast, Dr. Ashagi.
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B
Thank you very much, John, for having me. It's a pleasure.
- [10:31]
A
Your latest research suggests that the way we've been labeling Ms. For decades now as relapsing, remitting or secondary progressive doesn't tell the whole story. You've identified two new biological subtypes. Can you explain what these are and how they differ from the categories we're used to?
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B
You know, the way we categorize Ms. Disease courses is based on symptoms. It's been so since 1950s, so about maybe six, seven decades we have been relying on symptoms alone to. To classify patients. As people listening to a podcast may know better than we do. People living with ms, they are either labeled as relapsing, remitting Ms. Who later may develop a secondary progressive course. And also we have a separate group who may have progressive disease since the onset, patients who are cold and primary proflagellas. This is. It's been known that these sorts of categories have been outdated. We know this because they don't necessarily correspond with what we call biological changes or pathophysiological changes, that is basically changes in the tissues. Why is that important? Because as we move towards better diagnosis of Ms. And potential in the future preventing ms, it becomes important to move away from looking at Ms. Purely based on symptoms. So the idea would be to have a way of what I call biological classification of Ms. To stop the progression before it stops and potentially even prevent Ms. In the future. So that was the idea. And over the past five, six years, many different groups, including myself here in London, but also other groups in Germany, using blood samples, we've been looking at ways, if we can use artificial intelligence or AI to group patients in a way that doesn't necessarily have symptoms. So we asked computers if we could cluster, group or profile people with Ms. In similar groups that have similar trajectories on the data, or biomarkers, what we call biomarkers. So that is, for example, very specifically, as you mentioned, serum neurofilament, I'll use the short name, that is snfl. And what is probably also very available, that is mri, brain mri. So we know this, this is nothing new about dms. And previously we used MRI Alone to classify patients. So we, in that study in 2021, we found three different groups of patients. But now what we've done, we've gone first, we tried to simplify that classification. So in depth study we have patients who had early brain shrinkage, patients who had white matter plaques or white matter lesions, we call them lesion lead, and a third group of patients who had diffused damage in the brain, which we call them normal appearing white matter lead. Now recently, in the past month, the study published in Brain, we tried to simplify that, but the main question we answered is that adding snfl, the serum neurofilament improves that sort of classification, also simplifies that and is a step towards being able to have these source of biological classifications. And what we hope is to improve the classification of Ms. Based on the evidence provided in this study. Patients who had early SNFL elevations, as you mentioned, means patients who probably have a more active disease. Also these were patients who had early active MRI white methodes activity and patients who had late snfl. So patients had later elevation of serum neurofilament with a brain shrinkage later on. So using this source of classification, one would hope in the future to better find treatments or match treatments for specific persons living with ms, preventing disability progression before it happens, and also potentially. So that's a interesting topic, potential to prevent Ms. Before the symptoms emerge.
- [15:22]
A
Well, I want to get into some of that in a moment, but I'd like to ask you a little bit first about the AI tool you used, a machine learning tool, I believe it's called Sustain, to find these patterns for those of us who aren't tech experts, how did AI see something in these scans and blood tests that human doctors might have missed?
- [15:45]
B
Yeah, so we use the method you mentioned, Sustain. That is what we call unsupervised method. So in machine learning, AR parlance, we have usually two different ways of looking at data, one of which is supervised. Is like having a teacher teaching you what is what, what we call layoffs. For example, if you want to predict, let's say if you want to predict disability, we use supervised learning in the context of Ms. For example, this is unsupervised. That is we somehow, I mean in simple language, we throw data at the model, at the algorithm, and with some constraints, we look at how many clusters can best represent the data. Specifically in this case, the changes we observed was the patterns of change in MRI biomarkers. That includes brain volumes, but also white matter lesions, but also diffuse damage. Using a specific biomarker we call T1, T2 ratio. But without getting to those kinds of details, the idea here is that the AI is able to look at this huge amount of data from. In this case we had more than 600 patients, followed about 2, 3 years, depending on the clinical trial we used. These are changes that are first cannot be detected, especially on mri, cannot be detected by even expert radiologists that require quantification by AI tools. But also in case of SNFL or certain neurofilament on its own is a number. So I think that can be detected easily. But the important point is the pattern, so how it covariates, how it changes with other variables that in this case mri. So the idea is to have a very complex disease such as multiple sclerosis. We hope to be able, and that's what we're doing exactly, to use AI to better understand these changes. And I think the other promises to do so in a way that is unbiased. So it's not really, we don't. We had to select certain variables to input to the model, of course, but other than that, it's kind of, as I said, it's unsupervised. So it's very much, I can say unbiased, but it's less biased compared to manually or cherry picking, for example, certain aspects of the disease or virus.
- [18:23]
A
Your study identified two new subtypes called early SNFL and late snfl. The early SNFL subtype is characterized by high serum neurofilament light chain levels very early on and shows changes in a part of the brain called the corpus callosum. What does this mean for a patient's experience? Could this be considered a more aggressive form of ms?
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B
Potentially, yes. John. So this basically hints to a kind of disease that also was more active, that is, you know, is also more visible. When I say more visible means it shows itself early on as opposed to kind of, you know, Ms. Spectrum where it's more difficult to, to detect changes. As you know, we do have disability worsening or disability accumulation since the very beginning of ms, even in patients with relapsing rheumatic Ms. So that kind of disease, potentially those patients are likely to be in the late SNFL subtype, whereas patients who have relapses more active and also on mri, they're more likely to be in the early SNFL group. We knew about this. We knew some patients are more active than others. But how these two groups, the novelty and what is innovative in this study is really we bring this together. So you kind of what we call multimodal AI, you go above and beyond one aspect of the disease, that is either MRI or blood biomarkers, but you integrate them together to get a more holistic understanding of disease. And again, the idea is to improve whatever we can do. So improve prognosis, for example, improve in the future, potentially prescription of treatments, and as I said many times, potentially also moving forward, looking at how we can use these sorts of changes to prevent disability, worsening and potentially the diagnosis in the future.
- [20:32]
A
I think you've already started to answer my next question a little bit. It's about the late SNFL subtype, which is characterized by lower levels of serum neurofilament light chain early on. But the AI saw quiet shrinkage in the deep gray matter before those SNFL levels went up. And again, as a quick review for our listeners, you can think of that deep gray matter as sort of the mainframe that, that powers the brain. Dr. Ishaki, why is this quiet progression and deep gray matter so important to understand?
- [21:09]
B
Yeah, so this is probably the most mysterious and less understood part of Ms. And as I said, this happens early on, probably in all patients. So the silent part of disease, it has been coined differently by different people. Some people call it smoldering disease. We know about these days about period progression independent of relapse. This is the activity we used to call this disease progression. So there are lots of different ways of. I think if you look at the. Probably your podcast, but also in the literature, scientific literature, so it's very mysterious. We're starting to better understand it in our study. So we're specifically in this study, we looked at the clinical trial data. It's very short term to a maximum in some patients, three years of data. It's very short. To be able to capture some of these changes, specifically, the silent progression and the slow progression of disease usually requires 5 to 10 years of follow up. So it's very difficult to comment on that using this, you know, specifically this study. But we saw, as you mentioned, so early brain shrinkage, specific deep gray matter. So deep gray matter, as we say deep because it's really deep. If you open up the brain, it's really deep is in the center. And specifically this structure we call thalamus is the part of the brain that very much relates to walking ability and what doctors call motor impairment. You know, it could be thinking about walking, moving our hands and so on. These sorts of functions very much related to deep gray matter, actually. So again, this shows that there is a group of patients that go through this phase and as I said, it's very mysterious. So it's really one of those open questions in the ndms. And when I think about it, so we don't really know exactly what is driving that process and certainly we're not really able to stop it with the existing treatments.
- [23:20]
A
Your study found that people with early SNFL were 144% more likely to develop new lesions. Could knowing which subtype a patient falls under help to predict what their Ms. Might look like 5 or 10 years down the road?
- [23:39]
B
Yeah, so I think the key point exactly as you mentioned, if a. So again these are, you know, we talk about the future. If these were to deploy, for example in a clinical setting, if for example someone is labeled at early snfl, they're likely to be more active. So clearly in the conversations we may have in the future, if this comes into the conversation, it becomes part of the conversation. You will think of potentially prescribing higher efficacy, stronger treatments that can prevent disability before it happens. That's one part of the, the question. The other side is we know that you know, more activity requires, you know, is more aggressive disease, more what we call inflammation requires also a more efficacious treatment. So when you think of, you know, we have 20, 25 treatments depending on the country the audience are based in, but from those then one of the biggest question is, and there's always a risk associated with the treatment, is it worth, for example, starting with a higher efficacy treatment? And potentially we can or we should in the future be able to use AI or in general more information the better in this source of conversation to have this risk benefit ratio and make decisions based on that.
- [25:07]
A
That's exactly what I was wondering. As a matter of fact today with all of those approved treatments, it's not unusual for someone who's living with Ms. To be put on a few different disease modifying therapies before landing on one that seems to work best for them. So could integrating these new subtypes into clinical care help a neurologist find that best medication for a specific patient on day one?
- [25:38]
B
Absolutely, that's the hope. That's the hope to be able to do that. What I see in the future is not necessarily my study, but again the evidence is converging to be able to have algorithmic prediction to feed into the conversations in the future that people living with Ms. And the doctors nursing team and also people who care for people with Ms. Can have to improve that decision Making. That's exactly the idea. But also, as I said, we have treatments, but we are not really able to cure Ms. So in the future for new clinical trials, I think that's also important. If we are able to better profile the underlying biology, you can think about precision clinical trials. So think of clinical trials where we can use AI then to enrich trials with a specific treatment mechanisms that would target that specific biology. So I'm thinking about potential future remyelination trials, trials that look at the restoring, for example, lost myelin. If that happens in the future, you would want to have people who are most likely to respond to treatment. So it's really two aspects to it. One is the clinical care, which I really think it won't be, you know, I think it would be in the future, maybe we think in five, 10 years. It's a lot of work to get these sorts of ideas into the clinic. But also clinical trials probably is easier in terms of regulation to do. What you said in a clinical trial research setting earlier, the clinical care is probably, you know, we're thinking about probably a decade of work before we can get.
- [27:30]
A
It may be a decade out. But I think you've just given us a peek into what the future of Ms. Care is going to look like. And certainly in terms of being able to influence how clinical trials are designed and run, the better the trial design, the better the outcome in terms of developing new treatments faster. I want to congratulate you on this work. It increases our understanding of the biological mechanisms that are driving multiple sclerosis and it truly moves the entire field forward. Thanks so much for talking with me today.
- [28:06]
B
It's a pleasure, John. Thanks very much for having me.
- [28:09]
A
That's going to wrap up this episode of Real Talk Ms. Real Talk Ms. Is powered by the National Ms. Society and you can share this episode of the podcast by letting your friends or family members know that all they have to do is point their web browser@realtalkms.com 438. You'll find that link in today's show Notes, so you can easily copy and paste it right into an email or a text. I'm John Strum. Thanks for listening. Stay safe and make healthy choices.
- [28:49]
B
Sam.