Humoral signatures of MOG-antibody-associated disease track with age and disease activity
Name
PIIS266637912200492X.pdf
Description
Published version
Size
2.44 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Spatola, Marianna
Chuquisana, Omar
Jung, Wonyeong
Lopez, Joseph A
Wendel, Eva-Maria
Ramanathan, Sudarshini
Keller, Christian W
Hahn, Tim
Meinl, Edgar
Reindl, Markus
Date Issued
January 2023
Journal
Cell Reports Medicine
Publisher
Elsevier BV
Citation
Spatola, Marianna, Chuquisana, Omar, Jung, Wonyeong, Lopez, Joseph A, Wendel, Eva-Maria et al. 2023. "Humoral signatures of MOG-antibody-associated disease track with age and disease activity." Cell Reports Medicine.
Version
Final published version
Abstract
Myelin oligodendrocyte glycoprotein (MOG)-antibody (Ab)-associated disease (MOGAD) is an inflammatory demyelinating disease of the CNS. Although MOG is encephalitogenic in different mammalian species, the mechanisms by which human MOG-specific Abs contribute to MOGAD are poorly understood. Here, we use a systems-level approach combined with high-dimensional characterization of Ab-associated immune features to deeply profile humoral immune responses in 123 patients with MOGAD. We show that age is a major determinant for MOG-antibody-related immune signatures. Unsupervised clustering additionally identifies two dominant immunological endophenotypes of MOGAD. The pro-inflammatory endophenotype characterized by increased binding affinities for activating Fcγ receptors (FcγRs), capacity to activate innate immune cells, and decreased frequencies of galactosylated and sialylated immunoglobulin G (IgG) glycovariants is associated with clinically active disease. Our data support the concept that FcγR-mediated effector functions control the pathogenicity of MOG-specific IgG and suggest that FcγR-targeting therapies should be explored for their therapeutic potential in MOGAD.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/j.xcrm.2022.100913
