Defining humoral correlates of immunity against COVID-19
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 3R37AI080289-12S1
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Key facts
Disease
COVID-19Start & end year
20202022Known Financial Commitments (USD)
$749,896Funder
National Institutes of Health (NIH)Principal Investigator
Galit AlterResearch Location
United States of AmericaLead Research Institution
N/AResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Immunity
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
Since 2002, several coronaviruses have emerged able to cause severe respiratory disease, however no vaccine is available to prevent these rapidly spreading pathogens. Vaccine design has specifically lagged due to our lack of understanding of the correlates of immunity against these pathogens. Both cellular and humoral immune responses have been implicated in resolution of disease, but to date only the passive transfer of antibodies has been shown to confer complete protection in mice. Interestingly, the transfer of both "neutralizing" and nonneutralizing antibodies have shown protective efficacy, highlighting the role of multiple humoral mechanisms in limiting viral infection/spread. The precise mechanism of action of these antibodies that have the most profound impact on limiting disease is currently unclear, but if elucidated could provide critical insights for the development of effective vaccines against COVID-19 and other coronaviruses. Thus, here we aim to take a systematic approach to dissect and define both the polyclonal and monoclonal mechanisms by which antibodies confer protection against COVID-19. Specifically, samples from DNA- and adenovirus 26 (Ad26)- COVID-19 Spike protein (S) immunized animals, that will be challenged with COVID-19, will be comprehensively profiled using Systems Serology, to define the functional humoral immune responses linked to protection from infection/disease in mice, ferrets, and macaques. Machine learning modeling will be employed to discern key immune response features that translate usefully across these diverse animal contexts. These studies will not only define correlates of immunity across vaccines and species, but also provide mechanistic insights into the precise mechanisms by which antibodies may confer protection in the context of future vaccines.