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.

Increased circulating fibronectin, depletion of natural IgM and heightened EBV, HSV-1 reactivation in ME/CFS and long COVID (preprint)

Myalgic Encephalomyelitis/ Chronic Fatigue syndrome (ME/CFS) is a complex, debilitating, long-term illness without a diagnostic biomarker. ME/CFS patients share overlapping symptoms with long COVID patients, an observation which has strengthened the infectious origin hypothesis of ME/CFS. However, the exact sequence of events leading to disease development is largely unknown for both clinical conditions. Here we show antibody response to herpesvirus dUTPases, particularly to that of Epstein-Barr virus (EBV) and HSV-1, increased circulating fibronectin (FN1) levels in serum and depletion of natural IgM against fibronectin ((n)IgM-FN1) are common factors for both severe ME/CFS and long COVID. We provide evidence for herpesvirus dUTPases-mediated alterations in host cell cytoskeleton, mitochondrial dysfunction and OXPHOS. Our data show altered active immune complexes, immunoglobulin-mediated mitochondrial fragmentation as well as adaptive IgM production in ME/CFS patients. Our findings provide mechanistic insight into both ME/CFS and long COVID development. Finding of increased circulating FN1 and depletion of (n)IgM-FN1 as a biomarker for the severity of both ME/CFS and long COVID has an immediate implication in diagnostics and development of treatment modalities.

SARS-CoV-2 infection induces the production of autoantibodies in severe COVID-19 patients in an age-dependent manner (preprint)

Age is a significant risk factor for the coronavirus disease 2019 (COVID-19) outcomes due to immunosenescence and certain age-dependent medical conditions (e.g., obesity, cardiovascular disorder, diabetes, chronic respiratory disease). However, despite the well-known influence of age on autoantibody biology in health & disease, its impact on the risk of developing severe COVID-19 remains poorly explored. Here, we performed a cross-sectional study of autoantibodies directed against 58 targets associated with autoimmune diseases in 159 individuals with different COVID-19 outcomes (with 71 mild, 61 moderate, and 27 severe patients) and 73 healthy controls. We found that the natural production of autoantibodies increases with age and is exacerbated by SARS-CoV-2 infection, mostly in severe COVID-19 patients. Multivariate regression analysis showed that severe COVID-19 patients have a significant age-associated increase of autoantibody levels against 16 targets (e.g., amyloid beta peptide, beta catenin, cardiolipin, claudin, enteric nerve, fibulin, insulin receptor a, and platelet glycoprotein). Principal component analysis with spectrum decomposition based on these autoantibodies indicated an age-dependent stratification of severe COVID-19 patients. Random forest analysis ranked autoantibodies targeting cardiolipin, claudin, and platelet glycoprotein as the three most crucial autoantibodies for the stratification of severe elderly COVID-19 patients. Follow-up analysis using binomial regression found that anti-cardiolipin and anti-platelet glycoprotein autoantibodies indicated a significantly increased likelihood of developing a severe COVID-19 phenotype, presenting a synergistic effect on worsening COVID-19 outcomes. These findings provide new key insights to explain why elderly patients less favorable outcomes have than young individuals, suggesting new associations of distinct autoantibody levels with disease severity.

Determinants of motivated behavior are linked to fatigue and its perturbation by SARS-CoV-2 vaccination (preprint)

Background. Fatigue has an adaptive function and serves as a temporary signal to rest and save energy often in response to immune activation. It may, however, also persist in a pathological condition incurring significant burden. While subjective symptoms and scientific consensus indicate that both physical and mental determinants of motivated behavior are affected in fatigue, the underlying processes are rarely examined using objective, task-based indicators. Methods. In three consecutive studies, including validation (N = 48) and reliability assessments (N = 27), we use an experimental task to jointly objectify reward learning and effort execution as two determinants of behavioral motivation. In addition, we tested how fatigue and its acute perturbation in response to immune activation after SARS-CoV-2 vaccination are linked to these task-based indicators of motivation in a longitudinal cross-over design (N = 55). Results. The validation study showed the utility of the experimental task for simultaneously assessing learning, effort exertion, and its regulation based on subjective confidence. The reliability assessment over a one-week period indicated that symptoms of fatigue and task behavior are highly reliable and that repetition effects have little impact on motivated behavior. Finally, in the vaccination trial, we found significant links between fatigue and task behavior. Baseline levels of fatigue predicted how effort is gauged in dependence of current confidence about reward outcomes, and state perturbations of fatigue in the context of the SARS-CoV-2 vaccination reduced confidence during learning. Importantly, task success was significantly lower in subjects who reported high fatigue at baseline and who additionally experienced stronger increase in fatigue in response to vaccination. Discussion. Our results demonstrate that the experimental task allows to jointly assess determinants of motivated behavior, and to link its constituent processes to subjective fatigue. This suggests that our understanding of fatigue and its perturbation due to acute immune activation can benefit from objective, task-based indicators of the underlying motivational mechanisms. Future studies could build on these findings to further deepen the understanding of neurobehavioral mechanisms underlying fatigue in the context of immune activation.

Autoantibodies linked to autoimmune diseases associate with COVID-19 outcomes (preprint)

The SARS-CoV-2 infection is associated with increased levels of autoantibodies targeting immunological proteins such as cytokines and chemokines. Reports further indicate that COVID-19 patients may develop a wide spectrum of autoimmune diseases due to reasons not fully understood. Even so, the landscape of autoantibodies induced by SARS-CoV-2 infection remains uncharted territory. To gain more insight, we carried out a comprehensive assessment of autoantibodies known to be linked to diverse autoimmune diseases observed in COVID-19 patients, in a cohort of 248 individuals, of which 171 were COVID-19 patients (74 with mild, 65 moderate, and 32 with severe disease) and 77 were healthy controls. Dysregulated autoantibody serum levels, characterized mainly by elevated concentrations, occurred mostly in patients with moderate or severe COVID-19 infection, and was accompanied by a progressive disruption of physiologic IgG and IgA autoantibody signatures. A similar perturbation was found in patients with anosmia. Notably, autoantibody levels often accompanied anti-SARS-CoV-2 antibody concentrations, being both indicated by random forest classification as strong predictors of COVID-19 outcome, together with age. Moreover, higher levels of autoantibodies (mainly IgGs) were seen in the elderly with severe disease compared with young COVID-19 patients with severe disease. These findings suggest that the SARS-CoV-2 infection induces a broader loss of self-tolerance than previously thought, providing new ideas for therapeutic interventions.

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.