RESUMO
Cytokine storms and hyperinflammation, potentially controlled by glucocorticoids, occur in COVID-19; the roles of lipid mediators and acetylcholine (ACh) and how glucocorticoid therapy affects their release in Covid-19 remain unclear. Blood and bronchoalveolar lavage (BAL) samples from SARS-CoV-2- and non-SARS-CoV-2-infected subjects were collected for metabolomic/lipidomic, cytokines, soluble CD14 (sCD14), and ACh, and CD14 and CD36-expressing monocyte/macrophage subpopulation analyses. Transcriptome reanalysis of pulmonary biopsies was performed by assessing coexpression, differential expression, and biological networks. Correlations of lipid mediators, sCD14, and ACh with glucocorticoid treatment were evaluated. This study enrolled 190 participants with Covid-19 at different disease stages, 13 hospitalized non-Covid-19 patients, and 39 healthy-participants. SARS-CoV-2 infection increased blood levels of arachidonic acid (AA), 5-HETE, 11-HETE, sCD14, and ACh but decreased monocyte CD14 and CD36 expression. 5-HETE, 11-HETE, cytokines, ACh, and neutrophils were higher in BAL than in circulation (fold-change for 5-HETE 389.0; 11-HETE 13.6; ACh 18.7, neutrophil 177.5, respectively). Only AA was higher in circulation than in BAL samples (fold-change 7.7). Results were considered significant at P<0.05, 95%CI. Transcriptome data revealed a unique gene expression profile associated with AA, 5-HETE, 11-HETE, ACh, and their receptors in Covid-19. Glucocorticoid treatment in severe/critical cases lowered ACh without impacting disease outcome. We first report that pulmonary inflammation and the worst outcomes in Covid-19 are associated with high levels of ACh and lipid mediators. Glucocorticoid therapy only reduced ACh, and we suggest that treatment may be started early, in combination with AA metabolism inhibitors, to better benefit severe/critical patients.
RESUMO
Background: The uncontrolled inflammatory response plays a critical role in the novel coronavirus disease (COVID-19) and triggering receptor expressed on myeloid cells-1 (TREM-1) is thought to be intricate to inflammatory signal amplification. This study aims to investigate the association between soluble TREM-1 (sTREM-1) and COVID-19 as a prognostic biomarker to predict the disease severity, lethality and clinical management.Methods: We enrolled 91 patients with COVID-19 in domiciliary care (44 patients) or in hospital care (47 patients), who were classified after admission into mild, moderate, severe and critical groups according to their clinical scores. As non-COVID-19 control, 30 healthy volunteers were included. Data on demographic, comorbidities and baseline clinical characteristics were obtained from their medical and nurse records. Peripheral blood samples were collected at admission and after hospitalization outcome to assess cytokine profile and sTREM-1 level by specific immunoassays Results: Within COVID-19 patients, the highest severity was associated with the most significant elevated plasma levels sTREM-1. Using receiver operating curve analysis (ROC), sTREM-1 was found to be predictive of disease severity (AUC= 0.988) and the best cut-off value for predicting in-hospital severity was [≥] 116.5 pg/mL with the sensitivity for 93.3% and specificity for 95.8%. We also described the clinical characteristics of these patients and explored the correlation with markers of the disease aggravation. The levels of sTREM-1 were positively correlated with IL-6, IL-10, blood neutrophils counts, and critical disease scoring (r= 0.68, p<0.0001). On the other hand, sTREM-1 level was significantly negative correlated with lymphocytes counting, and mild disease (r= -0.42, p<0.0001). Higher levels of sTREM-1 were related to poor outcome and death, patients who received dexamethasone tended to have lower sTREM-1 levels. Conclusion: Our results indicated that sTREM-1 in COVID-19 is associated with severe disease development and a prognostic marker for mortality. The use of severity biomarkers such as sTREM-1 together with patients clinical scores could improve the early recognition and monitoring of COVID-19 cases with higher risk of disease worsening. Key words: COVID-19; sTREM-1; Inflammation; Biomarker; Severity; Mortality.
