ABSTRACT
In our study, we aimed to evaluate the significance of specific cytokines in blood plasma as predictive markers of COVID-associated mortality. Materials and methods. In plasma samples of 29 patients with PCR-confirmed COVID-19 we measured the concentrations of 47 molecules. These molecules included: interleukins and selected pro-inflammatory cytokines (IL-1alpha, IL-1beta, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-9, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17A/CTLA8, IL-17-E/IL-25, IL-17F, IL-18, IL-22, IL-27, IFNalpha2, IFNgamma, TNFalpha, TNFbeta/Lymphotoxin-alpha(LTA));chemokines (CCL2/MCP-1, CCL3/MIP-1alpha, CCL4/MIP-1beta, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROalpha, CXCL8/IL-8, CXCL9/MIG, CXCL10/IP-10, CX3CL1/Fractalkine);anti-inflammatory cytokines (IL-1Ra, IL-10);growth factors (EGF, FGF-2/FGF-basic, Flt-3 Ligand, G-CSF, M-CSF, GM-CSF, PDGF-AA, PDGFAB/BB, TGFalpha, VEGF-A);and sCD40L. We used multiplex analysis based on xMAP technology (Luminex, USA) using Luminex MagPix. As controls, we used plasma samples of 20 healthy individuals. Based on the results, we applied Receiver Operating Characteristic (ROC) analysis and Area Under Curve (AUC) values to compare two different predictive tests and to choose the optimal division point for disease outcome (survivors/non-survivors). To find optimal biomarker combinations, we as used cytokines concentrations as dependent variables to grow a regression tree using JMP 16 Software.Results. Out of 47 studied cytokines/chemokines/growth factors, we picked four pro-inflammatory cytokines as having high significance in evaluation of COVID-19 outcome: IL-6, IL-8, IL-15, and IL-18. Based on the results received, we assume that the highest significance in terms of predicting the outcome of acute COVID-19 belongs to IL-6 and IL-18. Conclusion. Analyzing concentrations of IL-6 and IL-18 before administering treatment may prove valuable in terms of outcome prognosis. Copyright © Arsentieva N.A. et al., 2022.
ABSTRACT
Introduction: Gut dysbiosis is associated with immune dysfunction and severity in COVID- 191-2. This study aimed to determine targeting dysbiosis as a therapy and its effect on antibody formation, gut dysbiosis and immune profile in patients with COVID-19. Material & Methods: In an open-label study, 25 consecutive hospitalized patients with COVID- 19 received a novel microbiome immunity formula (SIM01) for 28 days;30 patients who did not receive the intervention acted as controls. We collected fecal and blood samples at baseline and week 5 and followed subjects from admission up to five weeks. We performed multi-omics analysis using data from peripheral blood mononuclear cell (PBMC) transcriptome, fecal metagenomic sequencing and fecal metabolomic profiling (Figure 1A). Results: Significantly more COVID-19 patients on SIM01 developed anti-SARS-CoV-2 IgG than the control group at 2 weeks (Figure 1B). Patients on SIM01 (but not controls) showed a significant reduction of plasma levels of interleukin (IL)-6, macrophage colony-stimulating factor (M-CSF), tumour necrosis factor (TNF-a), IL-1RA (Figure 1C) and downregulated COVID-19 related signalling pathway in PBMC at Week 5. Fecal samples of subjects on SIM01 were enriched in commensal bacteria and reduced in opportunistic pathogens at week 4 and 5. Elevated plasma acetic acid in SIM01 group showed a negative correlation with SARS-CoV-2 viral load in nasopharyngeal samples (Figure 2A). Increased relative abundance of Bifidobacteria adolescentis and Coprococcus comes in fecal samples in SIM01 group positively correlated with plasma acetic acid levels (Figure 2B). Conclusion: We showed for the first time a novel microbiome formula SIM01 was effective in hastening antibody formation against SARS-CoV-2, reduced pro-inflammatory immune markers and restored gut dysbiosis in hospitalised COVID-19 patients. References: 1. Zuo T, Zhang F, Lui GCY, et al. Alterations in gut microbiota of patients with COVID-19 during time of hospitalization. Gastroenterology 2020;159:944-955 e8. 2. Yeoh YK, Zuo T, Lui GC, et al. Gut microbiota composition reflects disease severity and dysfunctional immune responses in patients with COVID- 19. Gut 2021;70:698-706. (Figure Presented) (Figure Presented)
ABSTRACT
Rationale: COVID-19 patients present with a number of clinical symptoms ranging from mild, moderate to severe, while only a subgroup of patients, who requires high-dependency critical care resources, accounts for most of the COVID-19 associated health care expenditure and death. A reliable prognostic tool is therefore required to identify patients at risk of developing severe COVID-19 pneumonia. To address this unmet need, we tested a wide range of potentially important peripheral blood biomarkers in a group of clinically risk-stratified COVID-19 patients in order to identify most relevant candidate biomarker(s) predictive of disease progression. Methods: Patients and healthy controls recruited to this study are summarised in Figure 1. Biomarkers levels were analysed using ANOVA across the severity groups. Spearman-correlation coefficients against pairs of average levels from each biomarker within severity-group and healthy controls were assembled into a 76x76 matrix and agglomerative hierarchical clustering was applied to generate the final heatmaps. Linear-discriminant analysis (LDA) was carried out on a reduced optimised set of biomarkers to explore the boundaries between the clinical severity groups.Results: Degree of lymphopaenia, neutrophil levels, TNF-α, INR-levels, and pro-inflammatory cytokines;IL6, IL8, CXCL9 and D-dimers were significantly increased in COVD-19 patients compared to healthy controls (p<0.05, 95% C.I.). C3a and C5 was significantly elevated in all categories of severity compared to healthy controls (p<0.05), C5a levels were significantly different between “moderate” and “severe” categories (p<0.01). sC5b-9 was significantly elevated in the “moderate” and “severe” category of patients compared to healthy controls (p<0.001).Heatmap analysis demonstrated distinct visual differences of biomarker profiles between the clinical severity groups. LDA on the deteriorators, non-deteriorators and healthy volunteers as a combined function of the predictor variables: C3, eosinophil-counts, granulocyte colony-stimulating factor (G-CSF), fractalkine, IL10, IL27, LTB4, lymphocyte count, MIG/CXCL9, M-CSF, platelet count and sC5b-9 showed clear separation between the groups based on biomarker/blood-count levels.Conclusions: Diagnostic and clinical assessments followed by robust statistical and machine learning approaches could identify peripheral blood biomarkers for prognostic stratification of patients in COVID-19. Our results would be helpful for clinicians and supports the use of point of care devices that can quantify multiple analytes. (Lui G, et al., Pointof- care detection of cytokines in cytokine storm management and beyond: Significance and challenges. VIEW. 2021;2: 1-20.). Such would allow for more efficient management and resource allocation. 1 (Figure Presented).
ABSTRACT
Analysis of cytokine profile markers in conjunction with the clinical manifestations of coronavirus disease 2019 (COVID-19) can provide valuable information about the pathogenetic manifestations of the disease, and therefore, in the future, determine drugs that affect the cytokine storm and have an anti-inflammatory effect. Aim. To identify correlations between the parameters of the developed cytokine profile and the clinical course in hospitalized patients with COVID-19 of different severity. Material and methods. The study included 70 hospitalized patients with a confirmed diagnosis of COVID-19, with a mean age of 58 [50;69] years, including 40 men (57%) and 30 women (43%). The average lung involvement according to computed tomography (CT) at admission was CT-2 [1;3]. Peripheral venous blood was taken at admission, which averaged 7 [6;8] days from the symptom onset. Standard biochemical parameters were studied, as well as 47 cytokines and chemokines using the Multiplex system (Merck KGaA, Darmstadt, Germany). Results. Correlations was found between the lung involvement degree and the level of IL-8 (r=0,31, p<0,05), IL-15 (r=0,35, p<0,05), IL-18 (r=0,31, p<0,05), MCP-1 (r=0,36, p<0,05), MIG (r=0,50, p<0,05), TNF-α (r=0,41, p<0,05). An inverse correlation was also found in the level of blood oxygen saturation with the same indicators as follows: IL-8 (r=-0,27, p<0,05), IL-15 (r=-0,34, p<0,05), IL-18 (r=-0,31, p<0,05), MCP-1 (r=-0,40, p<0,05), MIG (r=-0,56, p<0,05), TNF-α (r=-0,45, p<0,05). IL-6 levels were significantly elevated in patients with severe COVID-19 (CT3, CT4), while no increase in IL-6 was observed in patients with moderate disease (CT1, CT2). It is noteworthy that in patients with diabetes, the highest values of IL-12, IL-9 were recorded. Conclusion. Hyperinflammatory syndrome in severe COVID-19 is manifested by high levels of IL-6, MIG, MDC, MCP-1, M-CSF, TNF-α, β, IL-8, IL-18, IL-15. With the CT-1 and CT-2, an increase in only the level of IL-18, IL-8 is noted. The identified patterns prove and make it possible to explain a number of systemic inflammatory changes that occur with COVID-19.
ABSTRACT
Today, it has been proven that saliva is the main medium through which the new COVID-19 coronavirus infection spreads. Since the oral cavity is the gateway for the SARS-CoV-2 virus, the degree of change in the physicochemical parameters of the saliva of people who have had coronavirus infection compared to people who have not had COVID-19 is of interest. This study involved dental patients of the first and second health groups with a history of chronic generalized periodontitis of moderate degree in the stage of remission. We studied physicochemical parameters of saliva such as pH, surface tension and base buffering capacity. The results of this stage of the study showed saliva acidification, that is a decrease in pH in people who had had a new coronavirus infection compared to the indicators of people from the control group. The average values of the surface tension of saliva in patients of the control group are 30% less than in those who have had COVID-19. This indicates that the saliva of people who have not been sick with the new coronavirus contains more surface-active agents (surfactants). Surfactants provide rinsing and disinfecting functions of saliva, therefore, it can be concluded that these functions are less pronounced in patients who have recovered from COVID-19. The base buffering capacity of the saliva of patients who have had COVID-19 is, on average, 35% higher than that of people from the control group. Thus, the pH and the base buffering capacity are in correlation: the lower the pH value, the higher the acidity of the saliva and the higher the base buffering capacity is. At the second stage of the study, similar physicochemical parameters of patients’ saliva were measured after the application of an oral spray containing a synthetic peptide (ZP2) of the active center of granulo-cyte-macrophage colony-stimulating factor. This spray was used as an antibacterial therapy for the oral cavity after professional hygiene of patients. In 5 minutes after spray irrigation, an increase in saliva pH was observed in all test subjects within the physiological norm. In patients, regardless of their anamnesis, the surface tension of saliva changed in different ways. In a number of people, it increased, which indicates an increase in the concentration of surfactants in saliva, while in others it decreased, which can be explained by the high rate of penetration of surfactants from saliva through the gums into the blood. After the application of the ZP-2 peptide, the base buffering capacity of saliva decreases or remains unchanged. In patients of the control group, the indicators of the base buffering capacity of saliva change less than in patients who have undergone COVID-19. All the studied physicochemical parameters of saliva in patients who had had uncomplicated COVID-19, three months after receiving two negative results for the SARS-CoV-2 virus, remained within the physiological norm.