Abstract
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 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 (96.72% 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.
Competing Interest Statement
The authors declare the following competing financial interest(s): P.L.F., R.N., and A.J. have a financial interest in a company, Nanommune Inc., that is commercializing the COVAM technology. Nanommune partners with Sino Biological Inc. (Beijing, China) for expression and purification of COVAM antigens used in this study. The terms of this arrangement have been reviewed and approved by the University of California, Irvine in accordance with its conflict of interest policies.
Footnotes
One Sentence Summary: Antibodies targeting a specific spot within a SARS-CoV-2 structural protein and calculating patient disease risk factor can predict COVID-19 outcomes.