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

I have been doing more digging and speculating…

So MCTS1 seems to sometimes work in concert with E2F1.

E2F1 is in the area of this peak on LocusZoom for DecodeME which is below the significance threshold but there seems like there could be something going on in this region (you may need to change the filtering and resize the view to see it as there is a lot going on in this area)

We don’t know if there are genetic differences around MCTS1 yet (as above it’s on the X chromosome which we don’t have results for yet) but this study did highlight higher levels of the protein. And transcription factors like E2F1 interact with lots of things so this may not mean anything. However maybe something to dig into a bit more.
 
hotblack said:
So MCTS1 seems to sometimes work in concert with E2F1.
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Reminds me of Plato's cave.

Our appreciation of the real world is merely seeing fleeting shadows on a wall MCTS1, E2F1...
But that doesn't stop physicists ending up making predictions verifiable to 1 in 10^18.

Somewhere in all this is a causal reality. I think we might find it but don't ask me where at the moment.
 
Jonathan Edwards said:
Somewhere in all this is a causal reality. I think we might find it but don't ask me where at the moment.
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Indeed. My general approach is like someone flailing around on a beach picking up pebbles and holding them up to passers-by and saying, in a hopeful tone, ‘is this interesting?’

I think there are lots of interesting pebbles :) If they tell us anything., who knows. Maybe one day they will.
 
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hotblack said:
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.
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Can only speak to what we know other people are doing. I have circulating proteomics on 100 people being done as a small part of one of my studies but it is using olink, not somascan
 
What I do not understand is why on Table 6C there are two entries for the same entity, more specifically the entries "ACRP30" and "Adiponectin". They are the same entity :

https://en.wikipedia.org/wiki/Adiponectin

Interestingly, adiponectin is also related to efferocytosis:

Study in mice :

https://academic.oup.com/jimmunol/a...lement_1/63.1/8001131?redirectedFrom=fulltext

Failure to efficiently clear apoptotic cells (efferocytosis) is associated with autoimmunity. Complement component C1q is required for efferocytosis, and deficiency in C1q leads to development of autoimmunity. We recently identified a novel molecular mechanism for C1q-dependent efferocytosis in mouse macrophages. We found that C1q elicited the expression and function of Mer tyrosine kinase and the Mer ligand, Ga6: a receptor-ligand pair that mediates efferocytosis. To define the signal transduction pathway downstream of C1q, pathway analysis was performed using the transcriptome from C1q-treated macrophages. This analysis revealed that the adiponectin signaling pathway was significantly upregulated with C1q. Adiponectin is a well characterized adipokine with critical roles in glucose and fatty acid metabolism, and it is structurally homologous to C1q. Similar to C1q, adiponectin triggered expression of Mer that correlated with enhanced engulfment of apoptotic cells, and a soluble Mer-Fc fusion protein inhibited adiponectin-dependent efferocytosis.
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More on adiponectin :

https://academic.oup.com/jmcb/article/8/2/120/2459556
 
This seems big. And mostly over my head. But I thought this bit about physical function, steps and deconditioning would be interesting to all on here [from Supplementary Information file]:

Data S1C: Correlation with mean number of steps

In our main analysis, we used SF-36 Physical Functioning (SF-36PF) as a proxy for physical activity, reasoning that lower SF-36PF scores would likely reflect reduced activity and thus potential deconditioning. The broad proteomic changes observed in ME/CFS that were unrelated to SF-36PF therefore suggested that these changes were not driven by reduced activity or deconditioning.

To further address this point, we performed an additional analysis using mean daily step count (per 24h), which provides a more direct measure of physical activity. We found that a large fraction of aptamers correlating with SF-36PF also correlated with mean step count, confirming that SF-36PF is a good surrogate for activity level. Importantly, the main proteomic changes distinguishing ME/CFS from controls remained unrelated to either SF-36PF or step count, supporting that these changes are not primarily driven by deconditioning.

We acknowledge that reduced activity can have negative physiological effects; however, our findings suggest that these effects are largely separate from the disease-specific serum proteome alterations observed in ME/CFS.
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Regarding SF36 physical function (from main paper, formatted with a space between sentences for easier reading):
To further assess potential associations with the metabolic context and physical function, we correlated ME/CFS diagnosis, SF-36 Physical Function (SF-36PF), and metabotype (using metabotype M1 as reference17), adjusting for sex, age, BMI, and fasting (Figures 2B–2D; Supplemental Data S2).

Of 924 aptamers associated with ME/CFS, 775 were unique to the diagnosis and enriched for intracellular transport/translation.

Metabotype and SF-36PF influenced 1,015 and 726 aptamers, respectively, with distinct enrichments: metabotype-linked proteins involved hormone secretion and smooth-muscle cell regulation, while SF-36PF-linked proteins related to tissue homeostasis and nervous system development.

A subset of 149 aptamers overlapped with both ME/CFS and either metabotype or SF-36PF, highlighting shared immune-metabolic and extracellular matrix pathways, which may link disease status to metabolic context and clinical severity.

Only five proteins showed joint influence by ME/CFS status, SF-36PF, and metabotype (IL-22, HTRA1, OXCT1, ENPP5, and FAS).
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Overall, these results indicate that a substantial proportion of the broad proteomic alterations in ME/CFS cannot be explained by demographic factors or deconditioning, but instead may point to intrinsic disease-associated molecular changes.
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What they say about how their findings compare with those of similar studies (again formatted with a break between sentences for bunched brains):

Comparison with other proteomic studies​

To compare our results with previous work using the same SomaScan platform, we reanalyzed data from Germain et al.29, and Walitt et al.29,30 using a similar analytical pipeline adapted to the available data (STAR Methods; Supplemental Data S7; Document S1: Data S1I, Figures S5 and S6; Tables S10–S13).

In the Germain dataset, 391 aptamers differed between ME/CFS and controls (p < 0.05), of which 122 overlapped with our findings.

In the Walitt dataset, 41 aptamers were altered, with seven overlapping with our data.

While neither dataset demonstrated the broad reduction in intracellular proteins observed here, the Germain data showed a relative increase in membrane and secreted proteins, consistent with our results.

Despite some inter-study variation, likely reflecting differences in ME/CFS case definitions and cohort size, all three studies consistently pointed to immune-related dysregulation.

Our results also align with other independent proteomic investigations showing immune-vascular dysregulation and metabolic involvement, including coagulation and complement pathway changes,47 immune-related differences in plasma and extracellular vesicles,48 mitochondrial and metabolic pathway changes in immune cells,49,50 and aberrant innate/adaptive immune regulation revealed by single-cell and multi-omics analyses.51

Together, these cross-platform findings converge on immune, vascular, and metabolic dysregulation in ME/CFS and strengthen our interpretation of the serum proteome results.
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What they say relating to autoimmunity in the discussion (formatted with a space between each sentence):

Immune system changes and impaired neutrophil function​

Our findings indicate a primarily innate-immune-skewed reduction in granulocyte- and monocyte-associated signatures, contrasting with more variable or elevated lymphoid-cell patterns.

This imbalance may reflect a disturbed immune homeostasis that could contribute to or parallel autoimmune-like mechanisms, although the present data do not directly demonstrate autoimmunity.

Increased pro-inflammatory cytokines associated with T cell dysregulation, together with mixed changes reflecting disturbed immune balance, are hallmarks of many autoimmune conditions.59

The increased inflammatory, coagulation, and complement factors align with previous observations in ME/CFS and long COVID.1,60,61

The substantial reduction of neutrophil-associated proteins may indicate impaired neutrophil maturation or activation.62,63

Elevated complement factors CFD and C6 indicate alternative complement pathway activation, implicated in vasculitis, lupus, dermatomyositis, and autoimmune nephritis.64

Reduced MPO and extracellular histones, which are autoantigens in antineutrophil cytoplasmic antibodies (ANCA)-associated vasculitis, further suggest aberrant neutrophil-complement interplay, although ANCA is not typically reported in ME/CFS.65

Additional evidence includes the presence of autoantibodies and promising studies of antibody-targeting therapies such as immune adsorption and plasma-cell-directed treatments.16,66

Collectively, these findings support a possible autoimmune contribution to ME/CFS pathology.
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Thanks for doing this.

The psycho-behavioural club has never presented any evidence for deconditioning being a significant factor, and indeed have not even made any serious attempt to robustly test that critical assumption.

Instead, all the evidence is pointing in the opposite direction: that deconditioning is not a critical, let alone defining, factor in this disease.

It ain't patients who are irrational and prejudiced and anti-science.
 
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