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The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

The role of IgG Fc receptors in antibody-dependent enhancement

Open access
Bournazos, Stylianos, Gupta, Aaron, Ravetch, Jeffrey V.·2020·Nature Reviews Immunology

Abstract

Antibody-dependent enhancement (ADE) is a mechanism by which the pathogenesis of certain viral infections is enhanced in the presence of sub-neutralizing or cross-reactive non-neutralizing antiviral antibodies. In vitro modelling of ADE has attributed enhanced pathogenesis to Fcγ receptor (FcγR)-mediated viral entry, rather than canonical viral receptor-mediated entry. However, the putative FcγR-dependent mechanisms of ADE overlap with the role of these receptors in mediating antiviral protection in various viral infections, necessitating a detailed understanding of how this diverse family of receptors functions in protection and pathogenesis. Here, we discuss the diversity of immune responses mediated upon FcγR engagement and review the available experimental evidence supporting the role of FcγRs in antiviral protection and pathogenesis through ADE. We explore FcγR engagement in the context of a range of different viral infections, including dengue virus and SARS-CoV, and consider ADE in the context of the ongoing SARS-CoV-2 pandemic. Antibody-dependent enhancement (ADE) has been described as a mechanism that contributes to the pathogenesis of dengue virus infection. Limited evidence also suggests that it can also occur in other viral infections. Here, the authors explore the history of the ADE phenomenon, discuss the diversity of Fc effector functions and consider its potential relevance in the context of SARS-CoV-2 infection.

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Metadata

Authors
Bournazos, S., Gupta, A., & Ravetch, J. V.
Venue
Nature Reviews Immunology
Published
2020-08-11
Volume
20
Issue
10
Pages
633-643
ISSN
  • 1474-1733 (ISSN-L)
  • 1474-1741
OpenAlex
W3048558989
Cited by
617
References
7
FWCI
15.60
Type
journal article
Language
en
Open access
bronze

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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