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Sen SR, Sanders EC, Gabriel KN, Miller BM, Isoda HM, Salcedo GS, Garrido JE, Dyer RP, Nakajima R, Jain A, Caldaruse AM, Santos AM, Bhuvan K, Tifrea DF, Ricks-Oddie JL, Felgner PL, Edwards RA, Majumdar S, Weiss GA. Predicting COVID-19 Severity with a Specific Nucleocapsid Antibody plus Disease Risk Factor Score. mSphere 2021; 6:e00203-21. [PMID: 33910993 PMCID: PMC8092137 DOI: 10.1128/msphere.00203-21] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 03/19/2021] [Indexed: 12/14/2022] Open
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.IMPORTANCE The COVID-19 pandemic has resulted in over two million deaths worldwide. Despite efforts to fight the virus, the disease continues to overwhelm hospitals with severely ill patients. Diagnosis of COVID-19 is readily accomplished through a multitude of reliable testing platforms; however, prognostic prediction remains elusive. To this end, we identified a short epitope from the SARS-CoV-2 nucleocapsid protein and also a disease risk factor score based upon comorbidities and age. The presence of antibodies specifically binding to this epitope plus a score cutoff can predict severe COVID-19 outcomes with 96.7% specificity.
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Affiliation(s)
- Sanjana R Sen
- Department of Molecular Biology & Biochemistry, University of California Irvine, Irvine, California, USA
| | - Emily C Sanders
- Department of Chemistry, University of California Irvine, Irvine, California, USA
| | - Kristin N Gabriel
- Department of Molecular Biology & Biochemistry, University of California Irvine, Irvine, California, USA
| | - Brian M Miller
- Department of Chemistry, University of California Irvine, Irvine, California, USA
| | - Hariny M Isoda
- Department of Chemistry, University of California Irvine, Irvine, California, USA
| | - Gabriela S Salcedo
- Department of Chemistry, University of California Irvine, Irvine, California, USA
| | - Jason E Garrido
- Department of Molecular Biology & Biochemistry, University of California Irvine, Irvine, California, USA
| | - Rebekah P Dyer
- Department of Molecular Biology & Biochemistry, University of California Irvine, Irvine, California, USA
| | - Rie Nakajima
- Department of Physiology and Biophysics, University of California Irvine, Irvine, California, USA
| | - Aarti Jain
- Department of Physiology and Biophysics, University of California Irvine, Irvine, California, USA
| | - Ana-Maria Caldaruse
- Department of Pharmaceutical Sciences, University of California Irvine, Irvine, California, USA
| | - Alicia M Santos
- Department of Chemistry, University of California Irvine, Irvine, California, USA
| | - Keertna Bhuvan
- Department of Chemistry, University of California Irvine, Irvine, California, USA
| | - Delia F Tifrea
- Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, California, USA
| | - Joni L Ricks-Oddie
- Center for Statistical Consulting, Department of Statistics, University of California Irvine, Irvine, California, USA
- Biostatics, Epidemiology and Research Design Unit, Institute for Clinical and Translational Sciences, University of California Irvine, Irvine, California, USA
| | - Philip L Felgner
- Department of Physiology and Biophysics, University of California Irvine, Irvine, California, USA
| | - Robert A Edwards
- Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, California, USA
| | - Sudipta Majumdar
- Department of Chemistry, University of California Irvine, Irvine, California, USA
| | - Gregory A Weiss
- Department of Molecular Biology & Biochemistry, University of California Irvine, Irvine, California, USA
- Department of Chemistry, University of California Irvine, Irvine, California, USA
- Department of Pharmaceutical Sciences, University of California Irvine, Irvine, California, USA
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