miRNome profiling of extracellular vesicles in severe COVID-19 patients and identification of predictors of mortality.

BACKGROUND: Extracellular vesicles (EVs), containing microRNAs (miRNAs) and other molecules, play a central role in intercellular communication, especially in viral infections caused by SARS-CoV-2. This study explores the miRNA profiles in plasma-derived EVs from severe COVID-19 patients referred to controls, identifying potential mortality miRNA predictors. METHODS: A prospective study was carried out, including 36 severe COVID-19 patients and 33 non-COVID-19 controls. EVs-derived miRNAs were sequenced, and bioinformatics and differential expression analysis between groups were performed. The plasma miRNA profile of an additional cohort of severe COVID-19 patients (n=32) and non-COVID-19 controls (n=12) was used to compare with our data. Survival analysis was used to identify potential mortality predictors among the SDE miRNAs in EVs. RESULTS: Severe COVID-19 patients showed 50 significantly differentially expressed (SDE) miRNAs in plasma-derived EVs. These miRNAs were associated with pathways related to inflammation and cell adhesion. Fifteen of these plasma-derived EVs miRNAs were also SDE in the plasma of severe patients vs controls. Two miRNAs, hsa-miR-1469 and hsa-miR-6124, were identified as strong mortality predictors with an área under the ROC Curve (AUC) of 0.938. CONCLUSION: : This research provides insights into the role of miRNAs found within EVs in severe COVID-19 and their potential as clinical biomarkers for mortality.

The Overlooked Immune State in Candidemia: A Risk Factor for Mortality.

Lymphopenia has been related to increased mortality in septic patients. Nonetheless, the impact of lymphocyte count on candidemia mortality and prognosis has not been addressed. We conducted a retrospective study, including all admitted patients with candidemia from 2007 to 2016. We examined lymphocyte counts during the first 5 days following the diagnosis of candidemia. Multivariable logistic regression analysis was performed to determine the relationship between lymphocyte count and mortality. Classification and Regression Tree analysis was used to identify the best cut-off of lymphocyte count for mortality associated with candidemia. From 296 cases of candidemia, 115 died, (39.8% 30-day mortality). Low lymphocyte count was related to mortality and poor outcome (p < 0.001). Lymphocyte counts <0.703 × 109 cells/L at diagnosis (area under the curve (AUC)-ROC, 0.783 ± 0.042; 95% confidence interval (CI), 0.700-0.867, p < 0.001), and lymphocyte count <1.272 × 109 cells/L five days later (AUC-ROC, 0.791 ± 0.038; 95%CI, 0.716-0.866, p < 0.001) increased the odds of mortality five-fold (odds ratio (OR), 5.01; 95%CI, 2.39-10.93) at time of diagnosis, and three-fold (OR, 3.27; 95%CI, 1.24-8.62) by day 5, respectively. Low lymphocyte count is an independent predictor of mortality in patients with candidemia and might serve as a biomarker for predicting candidemia-associated mortality and poor outcome.