COVID-19 vaccine serologic immune response in people with HIV
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 3U01HL146208-03S2
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Key facts
Disease
COVID-19Start & end year
20192026Known Financial Commitments (USD)
$751,032Funder
National Institutes of Health (NIH)Principal Investigator
Charles R RinaldoResearch Location
United States of AmericaLead Research Institution
N/AResearch Priority Alignment
N/A
Research Category
Vaccines research, development and implementation
Research Subcategory
Characterisation of vaccine-induced immunity
Special Interest Tags
N/A
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Other
Occupations of Interest
Unspecified
Abstract
TITLE: COVID-19 vaccine serologic immune response in people with HIV ABSTRACT MWCCS participants are a high-risk group for severe COVID-19 disease in terms of being HIV-infected, predominately of elderly age, and having numerous underlying comorbidities. Therefore, it is imperative that they receive the new COVID-19 vaccines. In Aim 1 we will study the kinetics and immunoglobulin subclasses of COVID-19 vaccine-induced antibody responses in MWCCS male and female people with HIV (PWH) and matched HIV-uninfected controls (HUC) in a 3-year, longitudinal study against a background of HIV infection and cardiovascular comorbidities. We will perform quantitative assays to study anti-S antibody binding, virus neutralization and the capacity of the antigen-specific IgG1, IgG3 and IgA to mediate complement activation. This will be examined via serological levels of C1q, C3, C3a and C5a. MWCCS core longitudinal visit sera will be analyzed to determine COVID-19 infection post-immunization by detecting anti-N antibodies and to quantify the effect of additional immunizations with COVID vaccines. We will also assay sera for soluble immunological pro- and anti-inflammatory and other biomarkers that relate to HIV-1 infection and cardiovascular disease (CVD) to assess the effect of COVID-19 vaccination on these systemic parameters. In Aim 2 we will analyze the multi-omic immune parameter datasets generated in this project to discover, design, and optimize immune responses against the COVID-19 vaccine in PWH. Our hypothesis is that immunological biomarkers that predict COVID-19 vaccine response outcomes are identified by machine learning approaches on the entire set of features quantified in Aim 1. We will identify innate and adaptive immune parameters from Aim 1 that serve as biomarkers of COVID-19 vaccine outcomes in MWCCS participants using machine learning. This includes assessment of plasma HIV virus load and biomarkers of HIV-related immune activation and inflammation associated with chronic cardiovascular disease parameters already documented in MWCCS participants. This study will be a platform for further, targeted use of core samples for an in-depth investigation of vaccine- mediated immune mechanisms of protection. The participants who seroconvert, defined as V101 anti-N negative followed by anti-N positive sample, will be targeted for in-depth investigation of the immune mechanisms of vaccine-mediated protection, the immunologic responses and virologic characteristics of breakthrough SARS-CoV-2 infections in future investigations.