ABSTRACT
Background: Severe COVID-19 and obesity are characterized by higher inflammation. We aimed to examine early inflammatory patterns in people with (Ob) and without (NOb) obesity and COVID-19 and how they relate to COVID-19 disease severity Methods: Ob (BMI >30 Kg/m2) and NOb with COVID-19 matched for age, sex and WHO disease severity provided blood early after diagnosis. Immunoassays measured 57 plasma biomarkers reflecting innate immune and endothelial activation, systemic inflammation, coagulation, metabolism and microbial translocation (Fig 1). Between-group differences were assessed by Mann- Whitney. Associations between subsequent maximal COVID-19 severity (mild vs moderate/severe/critical) and biomarkers were explored by logistic regression adjusted for age, sex, hypertension (HTN) and diabetes (DM). Data are median pg/mL [IQR] or n [%] unless stated Results: Of 100 subjects (50 Ob and 50 Nob) presenting between April 2020 and March 2021, characteristics (Ob vs Nob) included: age 65 [23-91] vs 65 [21-95];female sex 27 (48%) vs 28 (56%);BMI 33.7 [30.0-71.8] vs 23.3 [15.3-25.9];disease severity mild 22 [48%] vs 23 [46%], moderate 15 [30%] vs 13 [26%], severe 6 [12%] vs 7 [14%];HTN 30 (60%) vs 17 (34%);DM 19 [38%] vs 6 [12%];days from symptom onset 7 [2-17] vs 8 [1-15];vaccinated 3 (6%) vs 0 (0%). Compared to NOb, Ob had higher IFN-alpha (1.8 [0.6;11] vs 0.9 [0.1;4.7]), CRP (10 mAU/mL [9.6;10.2] vs 9.7 [7.2;10]), IL-1RA (197 [122;399] vs 138 [88;253]), IL-4 (288 AU/mL [161;424] vs 205 [82;333]), vWF (252 [166;383] vs 163 [96;318]), Zonulin (114 ng/mL [77;131] vs 57 [18;106]), Resistin (956 [569;1153] vs 727 [712;1525]), Leptin (3482 [1513;5738] vs 848 [249;2114]), and lower Adiponectin (1.12 mg/L [0.09;1.5] vs 1.5 [1.18;1.93]), all p< 0.05. In both groups higher, proinflammatory IL-18 and lower levels of antiinflammatory CCL22 and IL-5 were associated with higher odds of disease severity, and lower E-selectin with higher disease severity only in Ob. However, in NOb higher type 3 interferons (IL-28A), macrophage activation (sCD163, CCL3) and vascular inflammation markers (ICAM-1, VCAM-1), along with higher S100B, GM-CSF and leptin were also associated with disease severity, a pattern not observed in Ob (Fig 1) Conclusion(s): Although Ob had higher overall levels of inflammation than NOb, few biomarkers predicted subsequent COVID-19 severity in Ob. These differential inflammatory patterns suggest dysregulated immune responses in Ob with COVID-19. (Figure Presented).
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
BACKGROUND: Infection caused by SARS-CoV-2 mostly affects the upper and lower respiratory tracts and causes symptoms ranging from the common cold to pneumonia with acute respiratory distress syndrome. Chemokines are deeply involved in the chemoattraction, proliferation, and activation of immune cells within inflammation. It is crucial to consider that mutations within the virion can potentially affect the clinical course of SARS-CoV-2 infection because disease severity and manifestation vary depending on the genetic variant. Our objective was to measure and assess the different concentrations of chemokines involved in COVID-19 caused by different variants of the virus. METHODS: We used the blood plasma of patients infected with different variants of SARS-CoV-2, i.e., the ancestral Wuhan strain and the Alpha, Delta, and Omicron variants. We measured the concentrations of 11 chemokines in the samples: CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1ß, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROα, CXCL8/IL-8, CXCL9/MIG, CXCL10/IP-10, and CX3CL1/Fractalkine. RESULTS: We noted a statistically significant elevation in the concentrations of CCL2/MCP-1, CXCL8/IL-8, and CXCL1/IP-10 independently of the variant, and a drop in the CCL22/MDC concentrations. CONCLUSIONS: The chemokine concentrations varied significantly depending on the viral variant, leading us to infer that mutations in viral proteins play a role in the cellular and molecular mechanisms of immune responses.