Proteomics

Dataset Information

0

Predicting COVID-19 Severity with a Specific Nucleocapsid Antibody plus Disease Risk Factor Score


ABSTRACT: Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, enzyme-linked immunosorbent assay (ELISA) and coronavirus antigen microarray (COVAM) analysis mapped antibody epitopes in the plasma of COVID-19 patients (n = 86) experiencing a wide range of disease states. The experiments identified antibodies to a 21-residue epitope from nucleocapsid (termed Ep9) associated with severe disease, including admission to the intensive care unit (ICU), requirement for ventilators, or death. Importantly, anti-Ep9 antibodies can be detected within 6 days post-symptom onset and sometimes within 1 day. Furthermore, anti-Ep9 antibodies correlate with various comorbidities and hallmarks of immune hyperactivity. We introduce a simple-to-calculate, disease risk factor score to quantitate each patient’s comorbidities and age. For patients with anti-Ep9 antibodies, scores above 3.0 predict more severe disease outcomes with a 13.42 likelihood ratio (96.7% specificity). The results lay the groundwork for a new type of COVID-19 prognostic to allow early identification and triage of high-risk patients. Such information could guide more effective therapeutic intervention.

ORGANISM(S): Human parainfluenza virus 4b Human respirovirus 3 Human adenovirus sp. Severe acute respiratory syndrome coronavirus 2 Human coronavirus 229E Human respirovirus 1 Human coronavirus NL63 Homo sapiens Influenza A virus Human coronavirus HKU1 Severe acute respiratory syndrome-related coronavirus Human respiratory syncytial virus A Human orthorubulavirus 2 human metapneumovirus Human respiratory syncytial virus B Human coronavirus OC43 Influenza B virus Dromedary camel coronavirus

PROVIDER: GSE172471 | GEO | 2021/04/21

REPOSITORIES: GEO

Dataset's files

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

Similar Datasets

2021-04-30 | E-MTAB-10431 | biostudies-arrayexpress
2021-04-15 | GSE168739 | GEO
2021-01-22 | GSE163668 | GEO
2023-07-17 | PXD026510 | Pride
2023-03-15 | E-MTAB-12777 | biostudies-arrayexpress
2023-04-11 | E-MTAB-12779 | biostudies-arrayexpress
2022-08-28 | GSE212041 | GEO
2021-03-26 | MSV000087115 | MassIVE
2021-03-25 | MSV000087099 | MassIVE
2021-03-25 | MSV000087098 | MassIVE