RESUMO
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.
RESUMO
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 which171 were COVID-19 patients (74 with mild, 65 moderate, and 32 with severe disease) and 77were 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.
RESUMO
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.
RESUMO
Severe COVID-19 patients present a clinical and laboratory overlap with other hyperinflammatory conditions such as hemophagocytic lymphohistiocytosis (HLH). However, the underlying mechanisms of these conditions remain to be explored. Here, we investigated the transcriptome of 1596 individuals, including patients with COVID-19 in comparison to healthy controls, other acute inflammatory states (HLH, multisystem inflammatory syndrome in children [MIS-C], Kawasaky disease [KD]), and different respiratory infections (seasonal coronavirus, influenza, bacterial pneumonia). We observed that COVID-19 and HLH share immunological pathways (cytokine/chemokine signaling and neutrophil-mediated immune responses), including gene signatures that stratify COVID-19 patients admitted to the intensive care unit (ICU) and COVID-19_nonICU patients. Of note, among the common differentially expressed genes (DEG), there is a cluster of neutrophil-associated genes that reflects a generalized hyperinflamatory state since it is also dysregulated in patients with KD and bacterial pneumonia. These genes are dysregulated at protein level across several COVID-19 studies and form an interconnected network with differentially expressed plasma proteins that point to neutrophil hyperactivation in COVID-19 patients admitted to the intensive care unit. scRNAseq analysis indicated that these genes are specifically upregulated across different leukocyte populations, including lymphocyte subsets and immature neutrophils. Artificial intelligence modeling confirmed the strong association of these genes with COVID-19 severity. Thus, our work indicates putative therapeutic pathways for intervention.
RESUMO
The coronavirus disease 2019 (COVID-19) fatality rate varies in different patient groups. However, the underlying mechanisms that explain this variation are poorly understood. Here, we reanalyzed and integrated public RNAseq datasets of nasopharyngeal swabs and peripheral blood leukocytes from patients with SARS-CoV-2, comparing transcription patterns according to sex, age, and viral load. We found that female and young patients infected by SARS-CoV-2 exhibited a similar transcriptomic pattern with a larger number of total (up- and downregulated) differentially expressed genes (DEGs) compared to males and elderly patients. The transcriptional analysis showed a sex-specific profile with a higher transcriptional modulation of immune response-associated genes in female and young subjects against SARS-CoV-2. The functional clustering was characterized by a highly correlated interferome network of cytokine/chemokine- and neutrophil-associated genes that were enriched both in nasopharyngeal cells and peripheral blood of COVID-19 patients. Females exhibited reduced transcriptional levels of key pro-inflammatory/neutrophil-related genes such as CXCL8 receptors (CXCR1/CXCR2), IL-1{beta}, S100A9, ITGAM, and DBNL compared to males, which correlate with a protective gene expression profile against inflammatory damage. Our data indicate specific immune-regulatory pathways associated with sex and age of patients infected with SARS-CoV-2. These results point out therapeutic targets to reduce morbidity and mortality of COVID-19.
