Proteomic profiling of serum small extracellular vesicles predicts post-COVID syndrome development, 2025, Dobra et al.

SNT Gatchaman

Senior Member (Voting Rights)
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Proteomic profiling of serum small extracellular vesicles predicts post-COVID syndrome development
Dobra; Gyukity-Sebestyen; Bukva; Boroczky; Nyiraty; Bordacs; Varkonyi; Kocsis; Szabo; Kecskemeti; Polgar; Szell; Buzas

Post-COVID syndrome affects 10–35 % of COVID-19 patients, and up to 85 % of hospitalized individuals, underscoring the need for early identification of high-risk cases. We hypothesized that the proteomic profile of serum small extracellular vesicles (sEVs) obtained during acute SARS-CoV-2 infection could predict post-COVID syndrome.

Serum samples from 59 patients, stratified as asymptomatic, moderate, or severe, were analyzed. sEVs were isolated, characterized by electron microscopy, nanoparticle tracking, and flow cytometry, then profiled via LC-MS.

Classification models integrating comorbidities, acute symptoms, and sEV proteomics distinguished the three groups, with sEV data outperforming conventional measures. Of 620 identified proteins, 30 showed significant differences between symptomatic and asymptomatic patients, including 12 linked to complement activation. ELISA confirmed LC-MS results that serum sEVs of post-COVID patients had altered C1 inhibitor, C3, and C5 levels.

These results suggest that sEV-based proteomics can enable earlier detection and more targeted follow-up for individuals at risk of post-COVID syndrome.


HIGHLIGHTS
• sEV proteomic profiles during acute COVID-19 can predict the development post-COVID syndrome.

• Alterations in complement proteins (C1 inhibitor, C3, C5) in sEVs are linked to post-COVID syndrome.

• sEV-based models achieve 90.9 % specificity and 84.4 % sensitivity in distinguishing asymptomatic from post-COVID patients.

• Combining clinical data with sEV proteomics using machine learning outperforms traditional metrics in forecasting long-term outcomes

• sEV profiling enables early detection of high-risk individuals for targeted post-hospital care.

Link | PDF (Clinical Immunology)
 
Szeged, Hungary @Wyva

The project received funding from the Hungarian Academy of Sciences under the PC2022-10/2022 project number. The study was also supported by the following research grants: OTKA-K143255 (K.B.), the Szent-Györgyi Albert Research Fundprovided by University of Szeged (K.B.), and the TKP-2021-EGA-09 (K.B.). “Project no. TKP-2021-EGA-09 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund,

There's a paywall, but a few snippets are available. Small EVs are interesting things to study.
Unfortunately, samples were from hospitalised patients, increasing the variety of post-infection problems that they might be suffering from.
 
Yes, I've seen it, thanks. This is one of the studies the Academy funded. The idea behind some of these studies seems worth investigating, however, there are problems with sampling in almost all of these, as you have found in this case for example. Other Hungarian long covid studies recruit people with loss of smell or taste or recruit them exlusively from a pulmonary clinic etc and call the study a post-covid study and generalize the results as if they were applicable in general. I think this reflects the fact that doctors here ignore or are completely unaware of the existence of the kind of post-covid condition that is similar to ME/CFS. Some good ideas, but unfortunately we may learn nothing from them about ME/CFS-like long covid as a consequence.
 
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