Early Prediction of COVID-19 Severity Using Extracellular Vesicles and Extracellular RNAs

Abstract The clinical manifestations of COVID-19 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-19 severity. To test our hypothesis, we collected serum samples from 31 patients with mild COVID-19 symptoms at the time of their admission. After standard therapy without corticosteroids, 9 of the 31 patients developed severe COVID-19 symptoms. We analyzed EV protein and exRNA profiles to look for correlations between these profiles and COVID-19 severity. Strikingly, we identified three distinct groups of markers (antiviral response-related EV proteins, coagulation-related markers, and liver damage-related exRNAs) with the potential to serve as early predictive biomarkers for COVID-19 severity. Among these markers, EV COPB2 has the best predictive value for severe deterioration of COVID-19 patients in this cohort. This type of information concerning functional extracellular component profiles could have great value for patient stratification and for making early clinical decisions about strategies for COVID-19 therapy..

Medienart:

Preprint

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

bioRxiv.org - (2021) vom: 15. Dez. Zur Gesamtaufnahme - year:2021

Sprache:

Englisch

Beteiligte Personen:

Fujita, Yu [VerfasserIn]
Hoshina, Tokio [VerfasserIn]
Matsuzaki, Juntaro [VerfasserIn]
Kadota, Tsukasa [VerfasserIn]
Fujimoto, Shota [VerfasserIn]
Kawamoto, Hironori [VerfasserIn]
Watanabe, Naoaki [VerfasserIn]
Sawaki, Kenji [VerfasserIn]
Sakamoto, Yohei [VerfasserIn]
Miyajima, Makiko [VerfasserIn]
Lee, Kwangyole [VerfasserIn]
Nakaharai, Kazuhiko [VerfasserIn]
Horino, Tetsuya [VerfasserIn]
Nakagawa, Ryo [VerfasserIn]
Araya, Jun [VerfasserIn]
Miyato, Mitsuru [VerfasserIn]
Yoshida, Masaki [VerfasserIn]
Kuwano, Kazuyoshi [VerfasserIn]
Ochiya, Takahiro [VerfasserIn]

Links:

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doi:

10.1101/2020.10.14.20212340

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI019140177