Charting the circulating proteome in ME/CFS using cross-system profiling to uncover mechanistic insights, 2026, Hoel, Fluge, Mella+

Another group is showing that GDF15 is normal in ME/CFS, @Jonathan Edwards. The testing I was part of showed that the most severe patients had the lowest GDF15. Explaining how this could be would go a long way, in my opinion.

I still think it's plausible that, due to poor microvascular diffusion and reduced gradients, blood values might not reflect tissue values. Something similar is seen in mitochondrial diseases, where lactate levels in the blood can be normal.

There could be many other reasons, of course.
Hi Butter,

Interesting that you were tested for that. Was that as part of a study or something available to the public?
 
If you do not mind me asking, you seem to have a vast knowledge of all these studies. How do you keep track and organize these studies?
I try to follow ME/CFS research as closely as I can and sometimes write blogs about them. For example, at the end of the year I write an overview of the most interesting studies of the year, which helps to keep track of the most important ones.
https://mecfsskeptic.com/2024-looking-back-on-a-year-of-me-cfs-research/

I also notice that I tend to ignore the less quality studies more and more. Many papers just aren't worth the time and effort.
 
Peroxidasin is intersting to me, it might help explain POTS

Mammalian Peroxidasin (PXDN): From Physiology to Pathology

PXDN expresses in the endothelial cells and secretes into blood. PXDN exhibits with much higher concentration in plasma than MPO [20]. Therefore, it is reasonable to speculate that PXDN also plays an important role in vascular tone under physiological and pathological conditions.



According to that review it also seems to be involved in extracellular matrix and fibronectin. i don't know too much about extracellular matrix and fibronectin but I do know that these are bits of biology that keep coming up! Collagen-associated functions suggest a possible link to Ehlers Danlos or similar connective tissue issues.
I find PXDN very interesting too.

Here's a link to a post I made about earlier findings:
Myopathy as a cause of fatigue in long-term post-COVID-19 symptoms: Evidence of skeletal muscle histopathology, 2022, Hejbøl et al
 
I also notice that I tend to ignore the less quality studies more and more. Many papers just aren't worth the time and effort.
Was told once by a senior researcher in materials science that when he gets a paper to read he goes straight to the methodology section, and doesn't read the full paper until he knows it is worth reading. Said it saved him a lot of time.
 
HLA-C has the 39th highest fold change out of the 7326 aptamers they tested (logFC = 0.35). Not significant though (p=.19, q=.45).
seq.21797.4-HLA-C_boxplots.png
Here are all the ones they tested that mentioned HLA:
Rank | EntrezGeneSymbol | logFC | adj.P.Val
39 | HLA-C | 0.35 | 0.45
1662 | CD74 | 0.05 | 0.11
2047 | HLA-G | 0.04 | 0.64
2255 | HLA-E | 0.03 | 0.78
3243 | CD74 | 0.01 | 0.83
4309 | HLA-DRB3 | -0.01 | 0.94
5759 | HLA-DQA2 | -0.06 | 0.06

Edit: Mistyped the q-value.
 
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That said it's a ton of work, as you guys found there's a lot of ways to annotate the name of a protein, metabolite or other molecule, and a dozen different numbering systems.
Noticed this thread on Twitter which may be useful to merge data with different names for the same gene ID.


 
https://doi.org/10.1016/j.xcrm.2026.102647

Now published as:
Charting the circulating proteome in ME/CFS using cross-system profiling to uncover mechanistic insights
August Hoel<a>1</a>,<a>2</a>,<a>7</a> ∙ Fredrik Hoel<a>1</a>,<a>7</a> ∙ Sissel Elisabeth Dyrstad<a>1</a> ∙ Henrique Chapola<a>1</a> ∙ Ingrid Gurvin Rekeland<a>3</a> ∙ Kristin Risa<a>3</a> ∙ Kine Alme<a>3</a> ∙ Kari Sørland<a>3</a> ∙ Karl Albert Brokstad<a>4</a> ∙ Hans-Peter Marti<a>2</a>,<a>5</a> ∙ Olav Mella<a>3</a>,<a>6</a> ∙ Øystein Fluge<a>3</a>,<a>6</a> ∙ Karl Johan Tronstad

Highlights​

• Serum proteomics reveals widespread protein changes in ME/CFS patients
• Tissue-linked shifts show reduced intracellular and increased secreted proteins
• Immune signatures show reprogramming with reduced neutrophil-derived proteins
• Regulatory networks link immune, vascular, and metabolic dysfunction

Summary​

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating condition often triggered by infections, with unclear mechanisms and no established biomarkers or treatments.

We apply aptamer-based serum proteomics to 50 ME/CFS patients and 29 healthy controls, analyzing 7,326 protein targets.
We identify 1,823 aptamers with significant differences between the groups (845 after false discovery rate [FDR] correction).

Distinct patterns of tissue- and process-specific changes are seen.
There is a broad increase in secreted proteins, while intracellular proteins, e.g., from skeletal muscle, particularly show reduction. Immune cell-associated signatures indicate immune reprogramming, including a distinct reduction in proteins secreted by activated neutrophils.
Focused secretome analysis supports intensified regulatory interactions related to immune activity, inflammation, vasculature, and metabolism.
Validation of measurements using antibody-based methods confirms findings for a selection of proteins.

The uncovered serum proteome patterns in ME/CFS patients may contribute to understanding the pathophysiology and inform future biomarker research and therapeutic development.
 
I just want to heap some praise onto the authors of this study.

Every time I see proteomics from biofluids I always wonder "okay but what tissue specific information can this tell us if any?"

They have made great efforts to address this in the paper. The intracellular stuff is noted to be limited in its interpretability by being so and later they do a bunch of things with different gene expression atluses. Extremely impressive
 
I was going to ask those more knowledgeable and experienced in this field (like @DMissa ) what the chances are of someone else looking at ME/CFS proteomics would be of reproducing this. It looks like the Rosetta Stone study is using the same kit at least, I wonder if they're aware of this paper?

From this paper
Serum protein concentrations for 50 ME/CFS patients and 29 HCs were measured using aptamer-based technology (SomaScan v.4.1 7 k).
From the Rosetta Stone funding document
The study will also investigate several important biological questions, including whether:

• Proteins in the blood (measured using SomaScan proteomics) reveal shared disease patterns or underlying mechanisms in LC and ME/CFS.
The UCL study is using a different platform and more focussed on immune/neurological so perhaps isn’t such a good fit, from their funding document
The project will use ALAMAR Bioscience’s NULISA platform, a next generation technology with extremely high sensitivity. It can detect more than 300 proteins involved in immune function and central nervous system processes — including many that cannot be measured using standard immunoassays (a simple test that used antibodies to detect something present in a sample, such as a protein).
 
Sorry to be the same broken record: obligatory mention that JAK2 is not exclusive to interferon gamma
I just noticed that revisiting this paper, my JAK-STAT pathway senses started tingling. So elevated MCTS1 leading to increased JAK2 protein so hypersensitive JAK-STAT? Maybe something here with the interleukins and complement to to keep a bit of an IFN loop going too?
 
I just noticed that revisiting this paper, my JAK-STAT pathway senses started tingling. So elevated MCTS1 leading to increased JAK2 protein so hypersensitive JAK-STAT? Maybe something here with the interleukins and complement to to keep a bit of an IFN loop going too?
Maybe! I think in general when genes come up in an untargeted study like this, they tend to be upregulated somewhere downstream of an abnormal disease process
 
Followed up on the link between MCTS1 and IFN-g, seems to come from this paper:


What they found was that an MCTS1 loss-of-function mutation caused a deficiency of the JAK2 protein (not mRNA) because JAK2 requires a specific MCTS1-dependent process to be fully translated. The initial hypothesis was that this would impair the cellular response to IFN-g (JAK2 is attached to the IFN-g receptor and is involved in the signaling cascade) but that actually didn’t seem to be the case. What was impaired was response to IL-23, which does influence production of IFN-g by T cells.

Either way, MCTS1 is a pretty ubiquitously expressed protein. More MCTS1 probably wouldn’t mean more JAK2, because it doesn’t seem like the limiting factor in that direction. So I think it supports the idea that if MCTS1 is related to interferons at all, it would be something farther downstream.
 
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