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IL-13 is a driver of COVID-19 severity.

ABSTRACT: Immune dysregulation is characteristic of the more severe stages of SARS-CoV-2 infection. Understanding the mechanisms by which the immune system contributes to COVID-19 severity may open new avenues to treatment. Here, we report that elevated IL-13 was associated with the need for mechanical ventilation in 2 independent patient cohorts. In addition, patients who acquired COVID-19 while prescribed Dupilumab, a mAb that blocks IL-13 and IL-4 signaling, had less severe disease. In SARS-CoV-2-infected mice, IL-13 neutralization reduced death and disease severity without affecting viral load, demonstrating an immunopathogenic role for this cytokine. Following anti-IL-13 treatment in infected mice, hyaluronan synthase 1 (Has1) was the most downregulated gene, and accumulation of the hyaluronan (HA) polysaccharide was decreased in the lung. In patients with COVID-19, HA was increased in the lungs and plasma. Blockade of the HA receptor, CD44, reduced mortality in infected mice, supporting the importance of HA as a pathogenic mediator. Finally, HA was directly induced in the lungs of mice by administration of IL-13, indicating a new role for IL-13 in lung disease. Understanding the role of IL-13 and HA has important implications for therapy of COVID-19 and, potentially, other pulmonary diseases. IL-13 levels were elevated in patients with severe COVID-19. In a mouse model of the disease, IL-13 neutralization reduced the disease and decreased lung HA deposition. Administration of IL-13-induced HA in the lung. Blockade of the HA receptor CD44 prevented mortality, highlighting a potentially novel mechanism for IL-13-mediated HA synthesis in pulmonary pathology.

SUBMITTER: Donlan AN

PROVIDER: S-EPMC8410056 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.

Project description:Objective: The increased level of interleukin (IL)-33 is considered as a predictor of severe coronavirus disease 2019 (COVID-19) infection, but its role at different stages of the disease is still unclear. Our goal was to analyze the correlation of IL-33 and other innate immunity cytokines with disease severity. Methods: In this study, 220 patients with COVID-19 were included and divided into two groups, mild/moderate and severe/critical. The value of the cytokines, clinical, biochemical, radiographic data was collected and their correlation with disease severity was analyzed. Results: Most patients in the severe/critical group were male (81.8%) and older (over 64.5 years). We found a statistically significant difference (p < 0.05) in these two groups between clinical features (dyspnea, dry cough, fatigue, and auscultatory findings); laboratory [(neutrophil count, lymphocyte count, monocyte count, hemoglobin, plasma glucose, urea, creatinine, total bilirubin (TBIL), direct bilirubin (DBIL), aspartate aminotransferase (AST), albumin (ALB), lactate dehydrogenase (LDH), creatinine kinase (CK), D-dimer, C-reactive protein (CRP), procalcitonin (PCT), Fe, and Ferritin)], arterial blood gases (oxygen saturation-Sa02, partial pressure of oxygen -p02), and chest X-rays (CXR) lung findings (p = 0.000). We found a significantly higher serum concentration (p < 0.05) of TNF-α, IL-1β, IL-6, IL-12, IL-23, and IL-33 in patients with COVID-19 with severe disease. In the milder stage of COVID-19, a positive correlation was detected between IL-33 and IL-1β, IL-12 and IL-23, while a stronger positive correlation between the serum values of IL-33 and TNF-α, IL-1β, IL-6, and IL-12 and IL-23 was detected in patients with COVID-19 with severe disease. A weak negative correlation (p < 0.05) between pO2 and serum IL-1β, IL-12, and IL-33 and between SaO2 and serum IL-33 was noted. The positive relation (p < 0.05) between the serum values of IL-33 and IL-12, IL-33 and IL-6, and IL-6 and IL-12 is proven. Conclusion: In a more progressive stage of COVID-19, increased IL-33 facilitates lung inflammation by inducing the production of various innate proinflammatory cytokines (IL-1β, IL-6, TNF-α, IL-12, and IL-23) in several target cells leading to the most severe forms of the disease. IL-33 correlates with clinical parameters of COVID-19 and might represent a promising marker as well as a therapeutic target in COVID-19.

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IL-13 is a driver of COVID-19 severity.

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