Abstract
AbstractMyasthenia gravis (MG) is an autoimmune disease characterized by impaired neuromuscular signaling due to autoantibodies targeting the acetylcholine receptor. Although its auto-antigens and effector mechanisms are well defined, the cellular and molecular drivers underpinning MG remain elusive. Here, we employed high-dimensional single-cell mass and spectral cytometry of blood and thymus samples from MG patients in combination with supervised and unsupervised machine-learning tools to gain insight into the immune dysregulation underlying MG. By creating a comprehensive immune map, we identified two dysregulated subsets of inflammatory circulating memory T helper (Th) cells. These signature ThCD103 and ThGM cells populated the diseased thymus, were reduced in the blood of MG patients, and were inversely correlated with disease severity. Both signature Th subsets rebounded in the blood of MG patients after surgical thymus removal, indicative of their role as cellular markers of disease activity. Together, this in-depth analysis of the immune landscape of MG provides valuable insight into disease pathogenesis, suggests novel biomarkers and identifies new potential therapeutic targets for treatment.
Funder
European Research Council
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Olga Mayenfisch Stiftung
Stiftung für die Erforschung der Muskelkrankheiten
Studienstiftung des Deutschen Volkes
Universität Zürich
Publisher
Springer Science and Business Media LLC
Subject
Cellular and Molecular Neuroscience,Clinical Neurology,Pathology and Forensic Medicine
Cited by
34 articles.
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