Abstract
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.
【초록키워드】 COVID-19, Pathogenesis, antibody, cross-sectional, disease severity, immune, COVID-19 disease, cross-sectional study, autoantibodies, Patient, Mild, target, antibody levels, targets, Chemokine receptor, moderate, predict, G protein-coupled receptors, association, Clinical severity, severe disease, autoantibody, the strongest, human biology, G protein-coupled receptor, G protein, Previous studies, healthy control, alteration, COVID-19 disease severity, healthy controls, Mild COVID-19 disease, CXCR3, previous study, component, AGTR1, Systemic autoimmune diseases, chemokine receptor CXCR3, identify, the disease, characterized, individuals, deregulated, 【제목키워드】 severity, with COVID-19,