# COVID19: Respiratory SARS-CoV-2 seroprevalence and the association of humoral immune responses with clinical outcomes in veterans and employees in the Cleveland VA Medical Center

> **NIH VA I01** · LOUIS STOKES CLEVELAND VA MEDICAL CENTER · 2021 · —

## Abstract

The global pandemic of SARS-CoV-2 is placing urgent demands on health care workers and researchers.
Between April 3rd and May 1st global cases of COVID19 nearly tripled from approximately 1 million to over 3
million. With the possibility of a reemergence of SARS-CoV-2 in the fall, rapid specific antibody assays are
essential. This application proposes to investigate the humoral immune responses to SARS-CoV-2 in veterans
and employees at the Cleveland VA Medical Center. The proposal has three aims. Aim 1) To develop rapid,
high throughput assays to measure total and functional antibodies to SARS-CoV-2 proteins in COVID19
infected individuals. In aim 1, we will establish a magnet bead-based assay that can detect antibody (Ab)
responses to up to 50 different epitopes of SARS-CoV-2 in one serum sample. This assay will also be able to
detect Abs that interfere with the binding of the receptor binding domain (RBD) of the spike protein of SARS-
CoV-2 to its receptor, ACE2. Antibodies that can block binding between the RBD and ACE2 on lung epithelial
cells will prevent viral entry and will likely be neutralizing. Aim 2) To determine if robust humoral immunity and
higher neutralizing Ab titers protect VA health care employees from clinical COVID19 compared to their
colleagues with low or no SAR2-CoV-2 specific antibodies. In aim 2 we will use a rapid antibody test to screen
Cleveland VA health care employees at high-risk for infection with COVID19 (first responders, emergency
department staff, intensive care unit staff, COVID19 ward staff). We will ask for a serum sample from those
that are Ab positive for COVID19 to examine the SARS-CoV-2 Ab response in more depth. We will examine
general Ab titers, neutralizing Ab titers, and antibody isotypes. If there is a resurgence of COVID19 in the fall,
we will determine if those health care employees with a robust humoral response are better protected from re-
infection than those employees who had a weak or no Ab response. Aim 3) To examine the association of
COVID19-induced lymphopenia with the ability to generate a humoral immune response. Older age, SARS-
CoV-1 and SARS-COV-2 infection are all associated with a decrease of white blood cells or lymphopenia. In
aim 3 we will examine the effect of lymphopenia on the development of the humoral Ab response to COVID19.
We expect that those individuals with severe lymphopenia will have few T follicular helper cells in their lymph
nodes and this will lead to poor Ab affinity maturation, isotype switching, and B cell memory development. In
summary, results from this project will provide a rapid SARS-CoV-2 specific serum assay able to detect
neutralizing Ab that can be used to screen VA healthcare workers for exposure to SARS-CoV-2. We will
investigate the humoral antibody responses of high-risk health care employees that were infected with
COVID19 and try to determine what constitutes protection from re-infection if there is a resurgence of
COVID19 in the fall. Lastly...

## Key facts

- **NIH application ID:** 10160554
- **Project number:** 1I01BX005507-01
- **Recipient organization:** LOUIS STOKES CLEVELAND VA MEDICAL CENTER
- **Principal Investigator:** Carey Lynn Shive
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2021
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2021-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10160554

## Citation

> US National Institutes of Health, RePORTER application 10160554, COVID19: Respiratory SARS-CoV-2 seroprevalence and the association of humoral immune responses with clinical outcomes in veterans and employees in the Cleveland VA Medical Center (1I01BX005507-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10160554. Licensed CC0.

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