{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T18:53:18Z","timestamp":1790362398844,"version":"4.1.0"},"reference-count":41,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2021,6,2]],"date-time":"2021-06-02T00:00:00Z","timestamp":1622592000000},"content-version":"vor","delay-in-days":1,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J of Extracellular Vesicle"],"published-print":{"date-parts":[[2021,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The clinical manifestations of COVID\u201019 vary broadly, ranging from asymptomatic infection to acute respiratory failure and death. But the predictive biomarkers for characterizing the variability are still lacking. Since emerging evidence indicates that extracellular vesicles (EVs) and extracellular RNAs (exRNAs) are functionally involved in a number of pathological processes, we hypothesize that these extracellular components may be key determinants and\/or predictors of COVID\u201019 severity. To test our hypothesis, we collected serum samples from 31 patients with mild COVID\u201019 symptoms at the time of their admission for discovery cohort. After symptomatic treatment without corticosteroids, 9 of the 31 patients developed severe\/critical COVID\u201019 symptoms. We analyzed EV protein and exRNA profiles to look for correlations between these profiles and COVID\u201019 severity. Strikingly, we identified three distinct groups of markers (antiviral response\u2010related EV proteins, coagulation\u2010related markers, and liver damage\u2010related exRNAs) with the potential to serve as early predictive biomarkers for COVID\u201019 severity. As the best predictive marker, EV COPB2 protein, a subunit of the Golgi coatomer complex, exhibited significantly higher abundance in patients remained mild than developed severe\/critical COVID\u201019 and healthy controls in discovery cohort (AUC 1.00 (95% CI: 1.00\u20101.00)). The validation set included 40 COVID\u201019 patients and 39 healthy controls, and showed exactly the same trend between the three groups with excellent predictive value (AUC 0.85 (95% CI: 0.73\u20100.97)). These findings highlight the potential of EV COPB2 expression for patient stratification and for making early clinical decisions about strategies for COVID\u201019 therapy.<\/jats:p>","DOI":"10.1002\/jev2.12092","type":"journal-article","created":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T04:22:43Z","timestamp":1622780563000},"source":"Crossref","is-referenced-by-count":48,"title":["Early prediction of COVID\u201019 severity using extracellular vesicle COPB2"],"prefix":"10.1002","volume":"10","author":[{"given":"Yu","family":"Fujita","sequence":"first","affiliation":[{"name":"Department of Translational Research for Exosomes The Jikei University School of Medicine  Tokyo Japan"},{"name":"Division of Respiratory Diseases Department of Internal Medicine The Jikei University School of Medicine  Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tokio","family":"Hoshina","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases and 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