Gabriella Dobra , Edina Gyukity-Sebestyen , Matyas Bukva , Timea Boroczky , Szabolcs Nyiraty , Barbara Bordacs , Tamas Varkonyi , Andrea Kocsis , Zoltan Szabo , Gabor Kecskemeti , Tamas Ferenc Polgar , Marta Szell , Krisztina Buzas
{"title":"Proteomic profiling of serum small extracellular vesicles predicts post-COVID syndrome development","authors":"Gabriella Dobra , Edina Gyukity-Sebestyen , Matyas Bukva , Timea Boroczky , Szabolcs Nyiraty , Barbara Bordacs , Tamas Varkonyi , Andrea Kocsis , Zoltan Szabo , Gabor Kecskemeti , Tamas Ferenc Polgar , Marta Szell , Krisztina Buzas","doi":"10.1016/j.clim.2025.110532","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div><div>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.</div><div>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.</div><div>These results suggest that sEV-based proteomics can enable earlier detection and more targeted follow-up for individuals at risk of post-COVID syndrome.</div></div>","PeriodicalId":10392,"journal":{"name":"Clinical immunology","volume":"278 ","pages":"Article 110532"},"PeriodicalIF":4.5000,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical immunology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S152166162500107X","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Clinical Immunology publishes original research delving into the molecular and cellular foundations of immunological diseases. Additionally, the journal includes reviews covering timely subjects in basic immunology, along with case reports and letters to the editor.