Genomics

Dataset Information

0

Early Predicting COVID-19 Severity Value with Extracellular Vesicles and Extracellular RNAs


ABSTRACT: The SARS-CoV-2 outbreak started on December 2019 in China and rapidly spread worldwide. Clinical manifestations of Coronavirus-disease 2019 (COVID-19) vary broadly, ranging from asymptomatic infection to acute respiratory failure and death, yet the underlying mechanisms and predictive biomarkers for this high variability are still unknown. Emerging evidence has shown that circulating extracellular vesicles (EVs) and extracellular RNAs (exRNAs) are functionally involved in a number of physiologic and pathologic processes. To test the hypothesis that these extracellular components are a key determinant of severity in COVID-19, we collected 31 serum samples from mild COVID-19 patients at admission in single center. After standard therapy without corticosteroids, 9 of 31 patients became severe COVID-19. We analyzed exRNA profiles from the 31 serums and 10 healthy controls for predicting COVID-19 severity value.

ORGANISM(S): Homo sapiens

PROVIDER: GSE158877 | GEO | 2022/03/31

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

| PRJNA666884 | ENA
2020-05-18 | GSE136243 | GEO
2020-09-29 | GSE158659 | GEO
2018-06-04 | GSE112289 | GEO
2020-04-22 | GSE145926 | GEO
2018-05-04 | GSE113994 | GEO
2023-07-11 | GSE236651 | GEO
2021-05-08 | GSE174072 | GEO
2022-07-22 | GSE180622 | GEO
2018-01-04 | GSE93143 | GEO