Extracellular Vesicle Protein and MiRNA Signatures as Biomarkers for Post-Infectious ME/CFS Patients, 2026, Seifert et al

[forestglip]

Extracellular Vesicle Protein and MiRNA Signatures as Biomarkers for Post-Infectious ME/CFS Patients

Spoiler: Authors

Seifert, Martina; Schäfers, Johannes; Douglas, Fiona F.; Schwarzburg, Carl; Boristowski, Diana; Birke, Anne; Klein, Oliver; Sotzny, Franziska; Rubarth, Kerstin; Windzio, Lara; Beez, Christien M.; Peters, Claudia Kedor; Wittke, Kirsten; Scheibenbogen, Carmen; Greco, Anna

[Line breaks added]

Abstract
Post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic disease with unresolved pathophysiology and limited diagnostic options. Extracellular vesicles (EVs) carry disease-specific protein and miRNA signatures and may enable improved disease profiling.

We aimed to identify novel protein and miRNA markers as potential biomarkers in plasma EVs from female ME/CFS patients, including post-COVID-19 ME/CFS and post-infectious ME/CFS of other origins, compared with healthy controls. EVs were isolated from plasma by size-exclusion chromatography and characterized for number, size, morphology, and surface marker expression.

Flow cytometry showed that small EVs strongly expressed tetraspanins, with only minor differences between ME/CFS patients and healthy donors. Proteomic profiling of EVs from ME/CFS patients identified altered cargo proteins, including hemoglobin subunit alpha and insulin-like growth factor-binding protein acid labile subunit compared with healthy controls (n ≤ 10/cohort).

Small RNA sequencing followed by qPCR revealed significant downregulation of hsa-let-7b-5p in EVs from post-COVID-19 ME/CFS patients (n = 12) versus healthy controls (n = 15). Reduced hsa-let-7b-5p expression correlated with impaired physical functioning and increased fatigue, pain, and immune activation.

These findings indicate that EV cargo differences, particularly hemoglobin subunit alpha and insulin-like growth factor-binding protein acid labile subunit, as well as hsa-let-7b-5p, represent promising candidates for ME/CFS diagnosis and patient stratification.

Web | DOI | PDF | International Journal of Molecular Sciences | Open Access

 

[Simon M]

I would love to see researchers come together to agree standards for ME/CFS biomarker research. This might include minimum sample sizes, including a validation cohort, at least one disease control group and being clear on the degree of biomarker overlap between patients and others.

We've seen a steady flow of these papers this century, and I'm not aware of any progress in either identifying clinically useful biomarkers or greater understanding of the underlying pathology.

 

[V.R.T.]

I would love to see researchers come together to agree standards for ME/CFS biomarker research. This might include minimum sample sizes, including a validation cohort, at least one disease control group and being clear on the degree of biomarker overlap between patients and others

This sounds like something PRIME could maybe do?

 

[Utsikt]

It seems like they are comparing post-covid HC to post-covid ME/CFS, and precovid HC to precovid post-infection ME/CFS.

2.1. Study Design
Plasma samples were collected from three study groups: post-COVID-19 ME/CFS (pcME/CFS) patients, post-infectious ME/CFS (piME/CFS) patients and the corresponding healthy controls with self-reported SARS-CoV2 infection (pcHC) and pre-pandemic healthy donors (HC), respectively (see Figure 1).

The female patient and control groups in the validation cohorts for protein markers (Table 1) and miRNA markers (Table 2) were similar in their age and body mass index. The piME/CFS group was younger and had a longer disease duration (median 24.45 months vs. 10 months in pcME/CFS). For the HCs, the self-reported time since the last SARS- CoV-2 infection was approximately 10 months. Both patients study groups showed similar disease and symptom severity (Table 1).

Does that mean that the ME/CFS specific signals might be the ones that overlap for both ME/CFS groups?

 

[DMissa]

I would love to see researchers come together to agree standards for ME/CFS biomarker research. This might include minimum sample sizes, including a validation cohort, at least one disease control group and being clear on the degree of biomarker overlap between patients and others.

The problem is that this will never be feasible because of money (even if everybody somehow agreed to a standard which I don't see happening). Different experiments etc will cost differing amounts to do and what might be possible to afford 100 people from the typical philanthropic grants we survive off of might be enough for 10 samples in something else

We've seen a steady flow of these papers this century, and I'm not aware of any progress in either identifying clinically useful biomarkers or greater understanding of the underlying pathology.

My guess is that the right things have not been zoomed in on yet. If somebody thought of the right thing that ended up being a key mediator of symptoms I expect you'd see a promising signal even in a smaller cohort

 

[Murph]

The problem is that this will never be feasible because of money (even if everybody somehow agreed to a standard which I don't see happening). Different experiments etc will cost differing amounts to do and what might be possible to afford 100 people from the typical philanthropic grants we survive off of might be enough for 10 samples in something else

My guess is that the right things have not been zoomed in on yet. If somebody thought of the right thing that ended up being a key mediator of symptoms I expect you'd see a promising signal even in a smaller cohort

Is there evidence of untargeted metabolomics or proteomics revealing answers in other diseases?

I grow less and less excited by -omics studies that have to bundle together a panel of 15 molecules just to get an area under the curve of like .83. And then gesture very broadly in the direction of "immune and neurological markers".

It really genuinely feels, ex-ante, like measuring everything should reveal how the disease works. But so far I haven't seen it, at least not in mecfs.

 

[DMissa]

Is there evidence of untargeted metabolomics or proteomics revealing answers in other diseases?

I have not encountered a clinically used biomarker that was identified using only untargeted omics. Not saying there isn't one or won't be one, and I haven't looked hard for one at all, but yes I have not encountered one. Take this with a huge grain of salt. I'm only saying it because I was asked directly. I'm not confident about it at all.

Really I think it depends on whether it is possible to do high throughput experiments on clean enough cohorts that systematic confounders don't cause problems. This is what people (including us) are trying at the moment in some of our work. Personally I have become generally more interested in more targeted mechanistic work but there is still a place for the high throughput discovery stuff, particularly given recent innovations in proteomics and metabolomics that haven't yet all been fully explored. Also, significant innovations in sampling and recruitment protocols that people like Chris Armstrong and team are doing an impressive job developing

 

[Simon M]

The problem is that this will never be feasible because of money (even if everybody somehow agreed to a standard which I don't see happening). Different experiments etc will cost differing amounts to do and what might be possible to afford 100 people from the typical philanthropic grants we survive off of might be enough for 10 samples in something else

I appreciate the problem, but this approach has got us nowhere in decades, and I'm not sure that things will ever change. We need better science to make progress ,otherwise the list of weak biomarker claims will just grow. I've been ill for over thirty years and am desperate for real progress.

My guess is that the right things have not been zoomed in on yet. If somebody thought of the right thing that ended up being a key mediator of symptoms I expect you'd see a promising signal even in a smaller cohort

I think it's time for a new approach, not simply hoping that a research group will strike lucky, because that hasn't worked. Perhaps a conference would lead to prioritisation based on existing promising work, and fewer bigger studies that would clear answers?

 

[jnmaciuch]

Is there evidence of untargeted metabolomics or proteomics revealing answers in other diseases?

I grow less and less excited by -omics studies that have to bundle together a panel of 15 molecules just to get an area under the curve of like .83. And then gesture very broadly in the direction of "immune and neurological markers".

It really genuinely feels, ex-ante, like measuring everything should reveal how the disease works. But so far I haven't seen it, at least not in mecfs.

I guess I can chime in as someone with experience doing several multi-omics analyses in different contexts. Obviously I’m going to be biased towards thinking that my own contributions were useful. I definitely agree there’s a limitation, though.

One well-powered and well-designed multi-omics study for a context where you don’t even know where to start directing your attention can be very useful for hypothesis generation. I’m doing that right now for a PhD project on severe influenza infection, and I was part of a study that did that for Long COVID (set up early in the pandemic, with a couple hundred participants). Dozens of similar studies that claim to create a clinically useful set of biomarkers and don’t even show the same top features between themselves…I’m 100% with you on being disenchanted.

 

[poetinsf]

We've seen a steady flow of these papers this century, and I'm not aware of any progress in either identifying clinically useful biomarkers or greater understanding of the underlying pathology.

I'm sure somebody will follow up if the paper is significant and credible enough regardless of the sample size, etc. The problem is that most papers these days are the product of publish-or-perish culture that get promptly ignored. And this is probably also why certain things come in fashion at certain times when someone makes splash, only to get replaced by something else more fashionable later on.

 

[Murph]

I guess I can chime in as someone with experience doing several multi-omics analyses in different contexts. Obviously I’m going to be biased towards thinking that my own contributions were useful. I definitely agree there’s a limitation, though.

One well-powered and well-designed multi-omics study for a context where you don’t even know where to start directing your attention can be very useful for hypothesis generation. I’m doing that right now for a PhD project on severe influenza infection, and I was part of a study that did that for Long COVID (set up early in the pandemic, with a couple hundred participants). Dozens of similar studies that claim to create a clinically useful set of biomarkers and don’t even show the same top features between themselves…I’m 100% with you on being disenchanted.

At the risk of getting things off-thread I should correct myself and say I know of one hopeful example of untargeted work leading to targeted work, which is this 2011 gene study that surfaced wasf3 as the top candidate and got no attention at the time: https://pubmed.ncbi.nlm.nih.gov/21584188/

It led to Hwang's work in 2024, which appeared to replicate the finding.

WASF3 disrupts mitochondrial respiration and may mediate exercise intolerance in myalgic encephalomyelitis/chronic fatigue syndrome - PubMed

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by various disabling symptoms including exercise intolerance and is diagnosed in the absence of a specific cause, making its clinical management challenging. A better understanding of the molecular mechanism underlying...

pubmed.ncbi.nlm.nih.gov

Close readers of the forum will know I am on team Hwang, because of the nature of his research -
1. he wasn't trying to solve me/cfs, he was just confused by a patient,
2. he carries no baggage or preconceptions,
3. he is backed by the many billions of dollars in cancer funding,
4. He found something that wasn't new, it was a replication.
5. the work elucidates an actual mechanism that makes sense.
6. it's in a domain that hasn't been fully explored: ER stress and in particular mitochondrial-ER contact sites.

Anyway, I realised I was being a bit of a debby downer, but I do carry hope!

 

[SNT Gatchaman]

HBA was the only marker among the identified proteins in our quantitative analyses that could be validated by ELISA, exclusively in the piME/CFS cohort. Moreover, ALS/IGFALS, identified by our qualitative approach, also displayed significantly enhanced levels only in the piME/CFS cohort.

Wikipedia entry for IGFALS —

The protein encoded by this gene is a serum protein that binds insulin-like growth factors, increasing their half-life and their vascular localization.

Small numbers, but interesting comments relating to pathway analysis divergence with the possibility of variance due to duration of illness.

Analyzing the significantly regulated protein candidates from each of the two proteomic datasets in the STRING database for functional enrichment, we found that the majority of proteins belong to the following cellular compartments: blood microparticles, the extracellular space, the extracellular region, and extracellular exosomes. Interestingly, the most strongly enriched Reactome pathways differed between the pcME/CFS and piME/CFS proteomic studies. In the pcME/CFS analysis, the main pathways were fibrin clot formation, regulation of the complement cascade, and hemostasias, whereas in the piME/CFS setting, they included heme degradation, heme signaling, hemostasis, and oxygen uptake and carbon monoxide release by erythrocytes.

It is striking that both proteome analyses revealed distinct proteins associated with different Reactome pathways. These differences may be attributed to the considerably shorter disease duration in the pcME/CFS group (median 12 months) compared to the piME/CFS group (median 78 months). For example, proteins involved in complement activation and clot formation predominate in the pcME/CFS group, whereas proteins and pathways involved in heme binding and the maintenance of homeostasis and erythrocyte function dominated in the piME/CFS group. This divergence could be due to the fact that the pcME/CFS cohort was examined closer to the time of the initial trigger.