Mining for humoral correlates of HIV control and latent reservoir size
Name
ppat.1008868.pdf
Description
Published version
Size
1.49 MB
Format
Unknown
Checksum (MD5)
31dfc807a244459cd8f15a81697676a1
Author(s)
Das, Jishnu
Devadhasan, Anush
Linde, Caitlyn
Broge, Tom
Sassic, Jessica
Mangano, Max
O'Keefe, Sean
Suscovich, Todd
Streeck, Hendrik
Irrinki, Alivelu
Date Issued
October 2020
Journal
PLoS Pathogens
Publisher
Public Library of Science (PLoS)
Version
Final published version
Abstract
© 2020 Das et al. While antiretroviral therapy (ART) has effectively revolutionized HIV care, the virus is never fully eliminated. Instead, immune dysfunction, driven by persistent non-specific immune activation, ensues and progressively leads to premature immunologic aging. Current biomarkers monitoring immunologic changes encompass generic inflammatory biomarkers, that may also change with other infections or disease states, precluding the antigen-specific monitoring of HIV-infection associated changes in disease. Given our growing appreciation of the significant changes in qualitative and quantitative properties of disease-specific antibodies in HIV infection, we used a systems approach to explore humoral profiles associated with HIV control. We found that HIV-specific antibody profiles diverge by spontaneous control of HIV, treatment status, viral load and reservoir size. Specifically, HIV-specific antibody profiles representative of changes in viral load were largely quantitative, reflected by differential HIV-specific antibody levels and Fc-receptor binding. Conversely, HIV-specific antibody features that tracked with reservoir size exhibited a combination of quantitative and qualitative changes marked by more distinct subclass selection profiles and unique HIVspecific Fc-glycans. Our analyses suggest that HIV-specific antibody Fc-profiles provide antigen-specific resolution on both cell free and cell-associated viral loads, pointing to potentially novel biomarkers to monitor reservoir activity.
MIT Department
Ragon Institute of MGH, MIT and Harvard
Massachusetts Institute of Technology. Department of Biological Engineering
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1371/JOURNAL.PPAT.1008868
