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.

Public Health Relevance

(from parent grant) The morbidity and cost to society from childhood viral respiratory illnesses (VRI) is staggering, and allergic respiratory disease is rampant. In the search for prevention for these common and high-burden diseases, perhaps the solutions are on the farm. Our main hypothesis is that microbes in farming environments promote immune development in early life, and thereby reduce the severity of VRI and protect against allergies. We will test this hypothesis by expanding studies in the Wisconsin Infant Study Cohort (WISC), a birth cohort in dairy farm country consisting of children and their families who were enrolled before birth and then monitored for farm exposures, development of the immune system, respiratory illnesses and allergies. We hope to identify farm-related exposures, including microbes, that promote healthy immune development, and ultimately, healthy children. Completion of these studies will lead to development of new strategies for raising children who get fewer respiratory illnesses and avoid developing respiratory allergies.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI104317-09
Application #
10221521
Study Section
Special Emphasis Panel (ZAI1)
Program Officer
Minnicozzi, Michael
Project Start
2013-02-01
Project End
2023-01-31
Budget Start
2021-02-01
Budget End
2022-01-31
Support Year
9
Fiscal Year
2021
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Type
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
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