Patients Are the Heart of Our Mission—Every Discovery Starts with Their Voice

Video Transcript:

Danielle Meadows, PhD: So I have with me Dr. Wenzhong Xiao of our Computational Research Center for Complex Diseases to give an update on a project his team worked on that we call the TreatME survey. So this is a survey created and distributed by patient researcher Martha Ecky, which collected information from people with ME/CFS and Long COVID about their experiences with these different treatments.

Dr. Xiao’s team then analyzed the data, which came from almost 4,000 participants and covered over 150 treatments. Dr. Xiao, thanks for coming on to give an update. Could you walk through some of the major findings from your analysis?

Wenzhong Xiao, PhD: Sure. Thank you, Danielle.

So this is one of the main figures that shown the results of the treatment that significantly improved patient conditions as reported by the patients as well as you can see on the right side. Each one of the symptoms that their treatments seem to help. What we see here are the top 20 treatments as well as the conditions.

What we see is that most of the treatments going from fluid and elect electrolytes down to Curcumin seem to help one or two symptoms, but it doesn’t seems like that all the treatments help all the symptoms. So what this showed to us is that perhaps patients can consider individual treatments based on the symptoms that they experience.

So that’s one of the take home messages that we learned. The second is that, some of these treatments have already been recommended by, for example, the clinician’s recommendation in their consensus statements, for example, the fluids and the electrolytes, pacing, and compression stockings,

these are non-pharmaceutical treatments that perhaps patients can consider. Following that we see the treatments like antihistamines and other select mast cell activation treatments that are also among the top treatments. As we know, these are the treatments for mast cell activations.

There are a few other treatments that are also well-recognized. In this field, for example, we get the low dose naltrexone and Mestinon both are under clinical trial here in Boston. In addition, we see a few other types of treatments that are potentially worthwhile for follow up clinical investigations.

This include the nattokinase and lumbrokinase, as well as the anticoagulants, the ADHD stimulants, as well as this maraviroc, which is a CCR5 inhibitor that might be worthwhile for further investigation. Vitamin C is used as a control in this case, and as many patients know graded exercise therapy was reported as the most negative impacting patients’ conditions.

Danielle Meadows, PhD: Yeah, this is great. Thank you. So just kind of, you know, looking at the figure as a whole maybe we can say the more orange you see, the better response there was and the more blue, the worse response. Is that you know kind of a good way to look at the, the colors here?

Wenzhong Xiao, PhD: Yeah, very good point. Patient’s response included seven levels from much better, which the deepest orange color, to much worse which is the darkest blue color. And I think you raised a good point that, you know, some of these treatments seem to have a higher level of either much better or modest better, and you know, for patients as well as the clinicians to consider the treatments

that might be another consideration. One of the other considerations from this result is that some of the types of treatments, for example, ADHD stimulants seem to have a higher percentage of the blue color the response, which means that the side effects, in fact, we find that at least 20% of the patients would have a negative response to drugs like ADHD stimulants, as well as other treatments that affect their central nervous system. So I think that’s one of the considerations for potentially selecting drugs that affect their central nervous system.

Danielle Meadows, PhD: So I think this really you know, highlights some of the heterogeneous nature of these patient populations, right? You know, we’re seeing obviously different people responding differently to the same drug or, or supplement or whatever the treatment may be in this case.

And in some cases, even looking on the right side with the, the darker green showing, you know, I think more patients saying that that particular treatment helps that symptom. Is that what the darker green means in this case?

Wenzhong Xiao, PhD: Yes. Yeah, exactly.

Danielle Meadows, PhD: So I think, you know, it, it really kind of highlights just you know, how different treatment strategies need to be used for different people depending on how they present clinically.

And I think you, you kind of dived a little bit into this with some of this data in this project too. Can you talk a little bit about some of the, the subtyping that you did with this work?

Wenzhong Xiao, PhD: Yeah, the excellent question. So, one of the potential insight that we get from these results is that exactly said the, the response from the patient seems to be quite diverse. So naturally we’re thinking that whether we can utilize the symptoms as well as the comorbidities of the patients to try to predict you know, what might be causing the different type of response to the same drug among the patients.

So what we did was that as you can see from this figure, the left side was the patient’s symptoms, and on the top part, and the patient comorbidities on bottom part. And we just clustered the patients based on their symptoms and the comorbidities. And they seem to fall into four groups.

As you can see here, the number in each entry shows the percentage of patients within that cluster that have that symptom. For example, the leftmost cluster is patients that seems to have most symptoms, as you can see, the color seems to be darker comparing to the other three clusters.

And the rightmost cluster seems to be lighter. That means that the percentage of patients that have that set of symptoms seems to be released. And then we get this second cluster which are dominated by a significant number of patients that have this comorbidity of POTS.

And the third cluster seems to have patients with out, you know, much POTS, but you know, higher percentage of brain fog and pains. You know how to say that this separation seems to be also consistent with the ME/CFS diagnostic criteria set by the Institute of Medicine, you know, where you do have a subset of patients that have mostly POTS related symptoms and the other set seem to have problems with brain fog.

So we then looked at the treatment outcomes within each cluster, and, and that’s shown on the right side. So again, you know, the numbers that higher shows that higher percentage of patients within that cluster would show a positive response.

And what we can see here is that, for example, for patients who have most of the symptoms you know, some of these treatments like, you know, IVIG for example or manual lymphatic drainage seem to be reported as you know, more helpful than some of the other clusters. While for the second cluster where POTS is a dominant symptom you would get some of these other treatments.

For example, low-dose naltrexone and Mestinon to be more effective comparing to, for example, the third cluster where there’s no POTS. But for the third cluster, as we know, brain fog and pain seem to be more dominant. And then in that cluster you get ADHD stimulants that seems to be more effective in that sub cluster of patients comparing to all the other three clusters.

So, we hope that following these lines of research, we can eventually figure out, you know, what patient type of patients might benefit from what type of treatments. Obviously, this is a part of our ongoing analysis, and I hope next time when we talk you know, we can have some more information for us to share with the patient community.

Danielle Meadows, PhD: Excellent. Thank you so much for providing this update, Dr. Xiao. I really appreciate your time. Sure, thank you