Integrative Systems Immunology Analysis Reveals Elevated Anti-AGTR1 Levels with Accumulating COVID-19 Symptoms (preprint)

The coronavirus disease 2019 (COVID-19) displays a broad spectrum of symptoms, with the underlying reasons for this variability still not fully elucidated. Our study investigates the potential association between specific autoantibodies (AABs), notably those that targeting G protein-coupled receptors (GPCRs) and renin-angiotensin system (RAS) related molecules, and the diverse clinical manifestations of COVID-19, commonly observed in patients with autoimmune conditions, including rheumatic diseases, such as systemic sclerosis. In a cross-sectional analysis, we explored the relationship between AAB levels and the presence of key COVID-19 symptoms. Hierarchical clustering analysis revealed a robust correlation between certain AABs and symptoms such as fever, muscle ache, anosmia, and dysgeusia, which emerged as significant predictors of disease severity. Specifically, AABs against CHRM5 and CXCR3 were strongly linked to fever, while AABs against CHRM5 and BDKRB1 correlated with muscle ache. Anosmia was predominantly associated with AABs against F2R and AGTR1, while dysgeusia was linked to AABs against BDKRB1 and AGTR1. Furthermore, we observed a rise in AAB levels with the accumulation of these symptoms, with the highest levels detected in patients presenting all four predictors. Multinomial regression analysis identified AABs targeting AGTR1 as a key predictor for one or more of these core symptoms. Additionally, our study indicated that anti-AGTR1 antibodies triggered a concentration-dependent degradation of eGC, which could be mitigated by the AGTR1 antagonist Losartan. This suggests a potential mechanistic connection between eGC degradation, the observed COVID-19 symptoms, and rheumatic diseases. In conclusion, our research underscores a substantial correlation between AABs, particularly those against GPCRs and RAS-related molecules, and the severity of COVID-19 symptoms. These findings open avenues for potential therapeutic interventions in the management of COVID-19.

SARS-CoV-2 Virus-Like Particles (VLPs) specifically detect humoral immune reactions in an ELISA based platform (preprint)

A key in controlling the SARS-CoV-2 pandemic is the assessment of the immune status of the population. We explored the utility of SARS-CoV-2 virus-like particles (VLPs) as antigens to detect specific humoral immune reactions in an enzyme-linked immunosorbent assay (ELISA). For this purpose, SARS-CoV-2 VLPs were produced from an engineered cell line and characterized by western blot, ELISA and nanoparticle tracking analysis. Subsequently, we collected 42 serum samples from before the pandemic (2014), 89 samples from healthy-, and 38 samples from vaccinated subjects. Seventeen samples were collected less than three weeks after infection, and 44 samples more than three weeks after infection. All serum samples were characterized for their reactivity with VLPs and the SARS-CoV-2 N- and S-protein. Finally, we compared the performance of the VLP-based ELISA with a certified in vitro diagnostic device (IVD). In the applied set of samples, we determined a sensitivity of 95.5 % and a specificity of 100 % for the certified IVD. There were 7 samples with an uncertain outcome. Our VLP-ELISA showed superior performance with a sensitivity of 97.5 %, a specificity of 100 %, and only 3 uncertain outcomes. This result warrants further research to develop a certified IVD based on SARS-CoV-2 VLPs as an antigen.

The relationship between autoantibodies targeting GPCRs and the renin-angiotensin system associates with COVID-19 severity (preprint)

The coronavirus disease 2019 (COVID-19) can evolve to clinical manifestations resembling systemic autoimmune diseases, with the presence of autoantibodies that are still poorly characterized. To address this issue, we performed a cross-sectional study of 246 individuals to determine whether autoantibodies targeting G protein-coupled receptors (GPCRs) and renin-angiotensin system (RAS)-related molecules were associated with COVID-19-related clinical outcomes. Moderate and severe patients exhibited the highest autoantibody levels, relative to both healthy controls and patients with mild COVID-19 symptoms. Random Forest, a machine learning model, ranked anti-GPCR autoantibodies targeting downstream molecules in the RAS signaling pathway such as the angiotensin II type 1 and Mas receptor, and the chemokine receptor CXCR3 as the three strongest predictors of severe disease. Moreover, while the autoantibody network signatures were relatively conserved in patients with mild COVID-19 compared to healthy controls, they were disrupted in moderate and most perturbed in severe patients. Our data indicate that the relationship between autoantibodies targeting GPCRs and RAS-related molecules associates with the clinical severity of COVID-19, suggesting novel molecular pathways for therapeutic interventions.