TY - JOUR
T1 - Autoantibodies targeting GPCRs and RAS-related molecules associate with COVID-19 severity
AU - Cabral-Marques, Otavio
AU - Halpert, Gilad
AU - Schimke, Lena F.
AU - Ostrinski, Yuri
AU - Vojdani, Aristo
AU - Baiocchi, Gabriela Crispim
AU - Freire, Paula Paccielli
AU - Filgueiras, Igor Salerno
AU - Zyskind, Israel
AU - Lattin, Miriam T.
AU - Tran, Florian
AU - Schreiber, Stefan
AU - Marques, Alexandre H.C.
AU - Plaça, Desirée Rodrigues
AU - Fonseca, Dennyson Leandro M.
AU - Humrich, Jens Y.
AU - Müller, Antje
AU - Giil, Lasse M.
AU - Graßhoff, Hanna
AU - Schumann, Anja
AU - Hackel, Alexander
AU - Junker, Juliane
AU - Meyer, Carlotta
AU - Ochs, Hans D.
AU - Lavi, Yael Bublil
AU - Scheibenbogen, Carmen
AU - Dechend, Ralf
AU - Jurisica, Igor
AU - Schulze-Forster, Kai
AU - Silverberg, Jonathan I.
AU - Amital, Howard
AU - Zimmerman, Jason
AU - Heidecke, Harry
AU - Rosenberg, Avi Z.
AU - Riemekasten, Gabriela
AU - Shoenfeld, Yehuda
N1 - Funding Information:
We acknowledge the patients for participation in this study. We also thank the São Paulo Research Foundation (FAPESP grants: 2018/18886-9, 2020/01688-0, and 2020/07069-0 to O.C.M.; 2020/09146-1 to P.P.F.; 2020/16246-2 to D.L.M.F.; 2020/07972-1 to G.C.B., 2020/11710-2 to D.R.P.), and the Coordination for the Improvement of Higher Education Personnel (CAPES) Financial Code 001 (grant to ISF) for financial support. We acknowledge the Ontario Research Fund (grant #34876), Natural Sciences Research Council (NSERC #203475), Canada Foundation for Innovation (CFI #29272, #225404, #33536), and IBM. This work was also supported by the Deutsche Forschungsgemeinschaft (DFG) founding the Excellence Cluster Precision Medicine in Inflammation, project TI4 and CD1, by the COVID fund of Schleswig-Holstein as well as by DFG project RI 1056 11-1/2. This work was supported by the Bundesministerium für Bildung und Forschung [01EC1901D (MESINFLAME)]. We thank Prof. Dr. med. Tanja Lange from the Department of Rheumatology and Clinical Immunology at the University of Lübeck, Germany for her advice to measure autoantibodies targeting the angiotensin-(1-7) receptor MAS1. We would like to acknowledge the contributions of Lev Rochel Bikur Cholim of Lakewood (led by Rabbi Yehuda Kasirer and Mrs. Leeba Prager) and their hundreds of volunteers who participated in collecting samples for this research.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity.
AB - COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity.
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UR - http://www.scopus.com/inward/citedby.url?scp=85126081158&partnerID=8YFLogxK
U2 - 10.1038/s41467-022-28905-5
DO - 10.1038/s41467-022-28905-5
M3 - Article
C2 - 35264564
AN - SCOPUS:85126081158
SN - 2041-1723
VL - 13
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 1220
ER -