Selin Lab

Thank you for sharing this. I read the Health Rising lay summary.

I wonder how the remarkably clean perferin result and T cell exhaustion hypothesis relates to the new Zhang paper that comes at it from the genetics start point. Do the two converge at all?
 
From Facebook


ICYMI: Read the Summary of Our Webinar On Immune Dysfunction & T Cell Exhaustion

Last month we hosted the webinar “Immune Dysfunction & T-Cell Exhaustion via Single Cell Immune Profiling in ME/CFS & Long COVID,” with Solve Ramsay Research Grant Winners Dr. Liisa Selin and Dr. Anna Gil (Selin Lab), Roshan Kumar, PhD (HiFiBiO Therapeutics), and patient advocates Rivka Solomon, MS, and Megan L. Fitzgerald, PhD.

It’s one of our most viewed webinars on YouTube, and it caught the attention of health journalist Cort Johnson. He wrote about it at length in his Health Rising blog here:
https://ow.ly/1pY750VWGqC

The webinar covered complex scientific information and our panelists kindly provided a layperson-friendly summary describing the defects these investigators have found in cells of the immune system from people with ME/CFS and Long COVID -- which they believe are at the core of these conditions.

You can read their summary here:
https://ow.ly/Vchi50VWGqF

and watch the webinar again here:
https://ow.ly/sr7x50VWGqE
 
Dolphin said:
The webinar covered complex scientific information and our panelists kindly provided a layperson-friendly summary describing the defects these investigators have found in cells of the immune system from people with ME/CFS and Long COVID -- which they believe are at the core of these conditions.

You can read their summary here:
https://ow.ly/Vchi50VWGqF
Click to expand...

The written summary is good and actually adds some new information. Here they define T cell exhaustion (@Jonathan Edwards), not necessarily by markers but by function. And they identified increased activation markers in patient CD8+ T cells.
Compared to healthy controls, exhausted CD8+ T cells in patients have decreased production of IFNɣ, TNFɑ, and perforin/granzyme, which are all molecules important in controlling any new or persistent infections present such as EBV or CMV. And, we show increased activation markers in patient CD8+ T cells.
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EDIT: Would decreased production of IFNɣ in lab tests indicate that the T cells have been releasing too much IFNɣ in vivo, perhaps supporting the JE hypothesis?

In the webinar I don't think they mentioned the collaboration with Dr. Dario Ghersi at the University of Nebraska at Omaha, who is an expert in TcR repertoire analysis and target antigen prediction.
By examining the TcR sequences of patients, we can identify groups of T cells that have expanded in response to antigen stimulation. Both the dysfunctional CD4+CD8+ and CD8+ T cell subsets in patients show evidence of clonal expansions to an unknown antigen, which may be a viral or autoantigen. This work is being done in collaboration with Dr. Dario Ghersi at the University of Nebraska at Omaha, who is an expert in TcR repertoire analysis and target antigen prediction. With the combination of single-cell RNA and TcR sequencing data from dysfunctional T cell subsets in patients, we are uniquely positioned to identify the target antigens driving this response which will shed light on underlying disease mechanisms. Altogether, these results suggest that ME/CFS and LC patients have an ongoing, over-activation of CD8+ T cells by some persistent antigen, leading to T cell exhaustion. This is similar to what is observed in a person with chronic viral infections or in tumor environments.
Click to expand...
 
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wigglethemouse said:
In the webinar I don't think they mentioned the collaboration with Dr. Dario Ghersi at the University of Nebraska at Omaha, who is an expert in TcR repertoire analysis and target antigen prediction.
Click to expand...

Does anyone know if Chris Ponting's @Chris Ponting colleagues published their findings anywhere on T cell receptor sequencing in ME/CFS - I seem to remember it was a null result. Perhaps access to the data or a chat with the researcher that did the work could help Dr. Dario Ghersi's work. Or maybe there was never such a project and it was B cell only.

@Simon M Perhaps you can remember?
 
wigglethemouse said:
The written summary is good and actually adds some new information. Here they define T cell exhaustion (@Jonathan Edwards), not necessarily by markers but by function. And they identified increased activation markers in patient CD8+ T cells.
Click to expand...

I have discussed the exhausted T cell idea with Jo Cambridge at length. She agrees that it may well be a red herring. The idea defining 'exhaustion' is that cells fail to respond to standard stimuli because they have some past history of being activated. The markers are supposed to point to this. But this begs a hundred and one questions about how you know that these cells have this past history and whether the 'standard stimuli' are relevant for these particular cells. Maybe the cells that usually respond to 'standard' stimuli are off busy somewhere else and the blood is full of other cells that have other jobs to do. T cells divide into a bewildering array of overlapping, stratified functional subsets which we still do not fully understand.

It is interesting if a group has found some functional differences in a blood population of CD8 cells but worth remembering that there have been at least a score of papers in the past looking at lymphocyte populations in blood in ME/CFS and pretty much every study finds something different which may just be a chance finding.

I would hope that there are some differences to find, using techniques like short term co-culture perhaps, but I am a bit sceptical that this lab suddenly joining the party is going to strike gold with a few preliminary experiments.
 
wigglethemouse said:
Does anyone know if Chris Ponting's @Chris Ponting colleagues published their findings anywhere on T cell receptor sequencing in ME/CFS - I seem to remember it was a null result. Perhaps access to the data or a chat with the researcher that did the work could help Dr. Dario Ghersi's work. Or maybe there was never such a project and it was B cell only.
Click to expand...

There was certainly a null result from Chris's group on T cell clonal expansion. I would be very sceptical that anyone will find antigen specific clones here. This is a very standard tunnel vision T cell immunology approach that by and large never pans out to anything. About the only disease where I think it might work is tuberculosis, and for good reason.
 
wigglethemouse said:
Does anyone know if Chris Ponting's @Chris Ponting colleagues published their findings anywhere on T cell receptor sequencing in ME/CFS - I seem to remember it was a null result. Perhaps access to the data or a chat with the researcher that did the work could help Dr. Dario Ghersi's work. Or maybe there was never such a project and it was B cell only.

@Simon M Perhaps you can remember?
Click to expand...

Comparison of T-cell Receptor Diversity of people with Myalgic Encephalomyelitis versus controls, 2023, Dibble, Ponting et al
 
The Selin lab has a Solve grant to take forward its work on t-cell receptors.

solvecfs.org

New Catalyst Awards to Accelerate ME/CFS and Long Covid Breakthroughs - Solve ME/CFS Initiative

Solve announces ME/CFS Catalyst Awards for two new groundbreaking studies to advance urgently needed treatment and diagnostic research for ME/CFS and Long Covid.
solvecfs.org solvecfs.org

They have roped in a Harvard scientist called Kohlgruber who is quite confidence-inspiring to hear speak.



The upside of this research would be that in each patient, by looking at the t-cell receptors, they can infer what the immune system believes is hanging around, and thereby tailor treatments. (E.g. if the immune system is casing Borellia bacteria, consider antibiotics; if it is chasing a virus that hides in b-cells, consider b-cell depletion; if it is chasing another virus, consider antivirals; if it is chasing self, consider car-t cells, etc.)

The absolute dream would be, huh, 90% of patients have the same target their t-cells are chasing. This is highly unlikely ... but not impossible.

Even if the research doesn't transfer immediately to treatments it could guide research: we can't find any evidence of virus X in the blood, but the expanded t-cell clones seem to imply it is still present in this group of patients, perhaps we should do a deeper dive on places it could have reservoirs /be latent.
 
I'm not well across the papers from the Selin lab, so I don't know if this PCA has been published yet. If it has, this comment probably would be better on the thread for the paper.

Screenshot 2026-05-04 at 10.27.33 PM.png

It looks to me as though PC2 is highly influenced by age. The researchers must have realised that themselves, given that they have given the colour legend for age and have coded each participant by their age. So, at this point, without seeing more detailed data, I rather doubt the vertical factors in the second figure (i.e. presumably the ones contributing to the PC2 separation relate to disease.

The two disease clusters that are claimed to separate largely along sex lines actually seem to relate to older and younger age, with a similar pattern also seen in the healthy controls. It just so happens that all of their older disease participants were female.

The CD4+CD8+ factor seems to be mostly affecting the y axis/ PC2, so might just be a confounding of age.

But the separation of disease participants from healthy participants on the x axis/PC1 looks impressive. So, some of those factors with more horizontal lines in the second figure look interesting. Most of them seem to have to do with perforin and granzyme, also some IFNg.
 
Kitty said:
Principal component?
Click to expand...
Yes

Edit: High-dimensional spaces are difficult to visualise, so it helps to explore the data in a reduced space. That's the plot on the left. Each dimension is a linear combination of the original features. In the case of PCA, those dimensions have maximal variance: PC1 is the direction (in the space of original features) along which the variance of the data is maximal. PC2 is the direction, orthogonal to PC1, with the second largest variance.

Each PC is a linear combination of the original features. The plot on the right shows the contribution of the original features to each of the two first principal components. As Hutan points out, age has a large weight in PC2.
 
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