# Identifying Coronavirus B-cell Epitopes Associated with COVID-19 Illness Severity

> **NIH NIH U19** · UNIVERSITY OF WISCONSIN-MADISON · 2020 · $406,048

## Abstract

The new coronavirus outbreak that begin in December 2019 has created a global public health emergency. This
has led to an intense search to identify factors that contribute to the susceptibility and severity of illness. We
recently developed an array to identify antibody-binding epitopes for rhinoviruses. Data from these arrays can
be combined with information about viral protein structure to identify highly immunogenic regions for respiratory
viruses. We propose to expand this array to include linear epitopes that represent the entire proteome of SARSCoV-2 and all other common coronaviruses that infect humans (OC43, NL63, etc.). The study population will
include children from the COAST, WISC and URECA birth cohort studies who are also participating in the
HEROS SARS-CoV-2 surveillance study. As part of routine cohort activities, these children undergo serial
sampling of blood and nasal secretions that we can analyze using the array to determine individual patterns of
antiviral antibody epitope recognition. We hypothesize that the pattern and quantity of antibody specific for
epitopes of common coronaviruses contributes to the susceptibility to SARS-CoV-2 infection and illness. We
propose three specific aims that will utilize sera obtained from children before and after HEROS-confirmed
infection with SARS-CoV-2. First, in specimens obtained pre-infection we will use the array to identify patterns
of antibody epitope recognition to common childhood coronaviruses, assess cross-reactivity with SARS-CoV-2,
and determine whether cross-reactivity is associated with protection against infection or illness. In the second
aim, we will determine whether the diversity of antibody responses to common respiratory viruses is associated
with a reduced risk of infection or illness. Finally, in the third aim we will describe antibody binding patterns before
and after known COVID-19 cases to identify candidate regions that are immunogenic and neutralizing. To
accomplish this aim, we will perform micro-neutralization assays (available in the BSL3 laboratory of Dr. Kristen
Bernard, UW Madison) on convalescent sera or nasal secretions from children who developed symptomatic
infection. This information will be analyzed together with pre- and post-infection array data using machine
learning approaches to identify neutralizing epitopes. Identifying patterns of serologic responses that are crossprotective could help to identify susceptible individuals in the population and direct the design of vaccines to
current and future viruses.

## Key facts

- **NIH application ID:** 10201317
- **Project number:** 3U19AI104317-08S2
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** ANN C. PALMENBERG
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $406,048
- **Award type:** 3
- **Project period:** 2020-07-21 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10201317

## Citation

> US National Institutes of Health, RePORTER application 10201317, Identifying Coronavirus B-cell Epitopes Associated with COVID-19 Illness Severity (3U19AI104317-08S2). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10201317. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*