Relationship between cytokine release and stress hyperglycemia in patients hospitalized with COVID-19 infection.

Introduction: Stress hyperglycemia is a frequent finding in patients with COVID-19 infection and could affect the outcome of disease. Cytokines released in response to infection could have adverse effects on insulin sensitivity and pancreatic beta-cell function. The aim of the study was to examine the relationships of stress hyperglycemia with cytokines and clinical outcomes in hospitalized patients with COVID-19. Methods: In a cross-sectional analysis of 150 patients hospitalized for COVID-19 infection who were included in the GIRA-COVID database, we identified patients with stress hyperglycemia by calculation of the Stress Hyperglycemia Ratio (SHR) and use of a cut-off of 1.14. Plasma levels of cytokines principally involved in COVID-19 infection-related cytokine storm were measured. Outcome variables were use of mechanical ventilation and death within 60 days from hospital admission. Results: Patients with SHR > 1.14 had significantly higher plasma insulin, HOMA-index, and levels of interleukin-10 (IL-10), interleukin-10/tumor necrosis factor-a ratio (IL-10/TNF-α), and CXC motif chemokine ligand 10 (CXCL10) than patients with SHR ≤ 1.14. IL-10, IL-10/TNF-α ratio, CXCL10, and IFN-γ were significantly and directly related with SHR in univariate analysis and multivariate logistic regression models showed that IL-10, IL-10/TNF-α ratio, and CXCL10 were independently associated with SHR>1.14. In a multivariate logistic model, stress hyperglycemia predicted use of mechanical ventilation (OR 2.453; CI 1.078-6.012) and death (OR 2.281; CI 1.049-7.369) independently of diabetes and other major confounders. Conclusions: In patients hospitalized for COVID-19 infection, stress hyperglycemia is associated with worse clinical outcomes and is independently related to levels of cytokines that might impair glucose homeostasis.

Combining Deep Phenotyping of Serum Proteomics and Clinical Data via Machine Learning for COVID-19 Biomarker Discovery.

The persistence of long-term coronavirus-induced disease 2019 (COVID-19) sequelae demands better insights into its natural history. Therefore, it is crucial to discover the biomarkers of disease outcome to improve clinical practice. In this study, 160 COVID-19 patients were enrolled, of whom 80 had a "non-severe" and 80 had a "severe" outcome. Sera were analyzed by proximity extension assay (PEA) to assess 274 unique proteins associated with inflammation, cardiometabolic, and neurologic diseases. The main clinical and hematochemical data associated with disease outcome were grouped with serological data to form a dataset for the supervised machine learning techniques. We identified nine proteins (i.e., CD200R1, MCP1, MCP3, IL6, LTBP2, MATN3, TRANCE, α2-MRAP, and KIT) that contributed to the correct classification of COVID-19 disease severity when combined with relative neutrophil and lymphocyte counts. By analyzing PEA, clinical and hematochemical data with statistical methods that were able to handle many variables in the presence of a relatively small sample size, we identified nine potential serum biomarkers of a "severe" outcome. Most of these were confirmed by literature data. Importantly, we found three biomarkers associated with central nervous system pathologies and protective factors, which were downregulated in the most severe cases.

Expansion of plasmablasts and loss of memory B cells in peripheral blood from COVID-19 patients with pneumonia.

Studies on the interactions between SARS-CoV-2 and humoral immunity are fundamental to elaborate effective therapies including vaccines. We used polychromatic flow cytometry, coupled with unsupervised data analysis and principal component analysis (PCA), to interrogate B cells in untreated patients with COVID-19 pneumonia. COVID-19 patients displayed normal plasma levels of the main immunoglobulin classes, of antibodies against common antigens or against antigens present in common vaccines. However, we found a decreased number of total and naïve B cells, along with decreased percentages and numbers of memory switched and unswitched B cells. On the contrary, IgM+ and IgM- plasmablasts were significantly increased. In vitro cell activation revealed that B lymphocytes showed a normal proliferation index and number of dividing cells per cycle. PCA indicated that B-cell number, naive and memory B cells but not plasmablasts clustered with patients who were discharged, while plasma IgM level, C-reactive protein, D-dimer, and SOFA score with those who died. In patients with pneumonia, the derangement of the B-cell compartment could be one of the causes of the immunological failure to control SARS-Cov2, have a relevant influence on several pathways, organs and systems, and must be considered to develop vaccine strategies.