Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, 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 ICU, requirement for ventilators, or death. Importantly, anti-Ep9 antibodies can be detected within six days post-symptom onset and sometimes within one 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 patients 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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7574261PMC
http://dx.doi.org/10.1101/2020.10.15.341743DOI Listing

Publication Analysis

Top Keywords

anti-ep9 antibodies
12
predicting covid-19
8
disease risk
8
risk factor
8
factor score
8
severe disease
8
disease
6
covid-19 severity
4
severity specific
4
specific nucleocapsid
4

Similar Publications

Evidence for deleterious effects of immunological history in SARS-CoV-2.

PLoS One

August 2022

Department of Molecular Biology & Biochemistry, University of California, Irvine, Irvine, CA, United States of America.

A previous report demonstrated the strong association between the presence of antibodies binding to an epitope region from SARS-CoV-2 nucleocapsid, termed Ep9, and COVID-19 disease severity. Patients with anti-Ep9 antibodies (Abs) had hallmarks of antigenic interference (AIN), including early IgG upregulation and cytokine-associated injury. Thus, the immunological memory of a prior infection was hypothesized to drive formation of suboptimal anti-Ep9 Abs in severe COVID-19 infections.

View Article and Find Full Text PDF

Unlabelled: A previous report demonstrated the strong association between the presence of antibodies binding to an epitope region from SARS-CoV-2 nucleocapsid, termed Ep9, and COVID-19 disease severity. Patients with anti-Ep9 antibodies (Abs) had hallmarks of antigenic imprinting (AIM), including early IgG upregulation and cytokine-associated injury. Thus, the immunological memory of a previous infection was hypothesized to drive formation of suboptimal anti-Ep9 Abs in severe COVID-19 infections.

View Article and Find Full Text PDF
Article Synopsis
  • Researchers developed effective methods to predict COVID-19 outcomes by analyzing patient antibodies and identifying a specific epitope (Ep9) linked to severe disease cases.* -
  • Anti-Ep9 antibodies can be detected quickly after symptom onset and correlate with serious health issues, allowing for a new risk factor score that considers age and comorbidities.* -
  • The study suggests that identifying patients with these antibodies and higher risk scores can help predict severe disease outcomes with high accuracy, aiding in early intervention and treatment.*
View Article and Find Full Text PDF

Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, 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 ICU, requirement for ventilators, or death.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!