Endogenous IFNβ expression predicts outcome in critical patients with COVID-19.
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ABSTRACT:
SUBMITTER: Menezes SM
PROVIDER: S-EPMC8009614 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: Not available
| S-BSST416 | biostudies-other
Project description:AimsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to angiotensin converting enzyme 2 (ACE2) enabling entrance of the virus into cells and causing the infection termed coronavirus disease of 2019 (COVID-19). Here, we investigate associations between plasma ACE2 and outcome of COVID-19.Methods and resultsThis analysis used data from a large longitudinal study of 306 COVID-19 positive patients and 78 COVID-19 negative patients (MGH Emergency Department COVID-19 Cohort). Comprehensive clinical data were collected on this cohort, including 28-day outcomes. The samples were run on the Olink® Explore 1536 platform which includes measurement of the ACE2 protein. High admission plasma ACE2 in COVID-19 patients was associated with increased maximal illness severity within 28 days with OR = 1.8, 95%-CI: 1.4-2.3 (P < 0.0001). Plasma ACE2 was significantly higher in COVID-19 patients with hypertension compared with patients without hypertension (P = 0.0045). Circulating ACE2 was also significantly higher in COVID-19 patients with pre-existing heart conditions and kidney disease compared with patients without these pre-existing conditions (P = 0.0363 and P = 0.0303, respectively).ConclusionThis study suggests that measuring plasma ACE2 is potentially valuable in predicting COVID-19 outcomes. Further, ACE2 could be a link between COVID-19 illness severity and its established risk factors hypertension, pre-existing heart disease and pre-existing kidney disease.
| S-EPMC8177449 | biostudies-literature
Project description:BackgroundThe immuno-receptor Triggering Expressed on Myeloid cells-1 (TREM-1) is activated during bacterial infectious diseases, where it amplifies the inflammatory response. Small studies suggest that TREM-1 could be involved in viral infections, including COVID-19. We here aim to decipher whether plasma concentration of the soluble form of TREM-1 (sTREM-1) could predict the outcome of hospitalized COVID-19 patients.MethodsWe conducted a multicentre prospective observational study in 3 university hospitals in France. Consecutive hospitalized patients with confirmed infection with SARS-CoV-2 were enrolled. Plasma concentration of sTREM-1 was measured on admission and then at days 4, 6, 8, 14, 21, and 28 in patients admitted into an ICU (ICU cohort: ICUC) or 3 times a week for patients hospitalized in a medical ward (Conventional Cohort: ConvC). Clinical and biological data were prospectively recorded and patients were followed-up for 90 days. For medical ward patients, the outcome was deemed complicated in case of requirement of increased oxygen supply > 5 L/min, transfer to an ICU, or death. For Intensive Care Unit (ICU) patients, complicated outcome was defined by death in the ICU.ResultsPlasma concentration of sTREM-1 at inclusion was higher in ICU patients (n = 269) than in medical ward patients (n = 562) (224 pg/mL (IQR 144-320) vs 147 pg/mL (76-249), p < 0.0001), and higher in patients with a complicated outcome in both cohorts: 178 (94-300) vs 135 pg/mL (70-220), p < 0.0001 in the ward patients, and 342 (288-532) vs 206 pg/mL (134-291), p < 0.0001 in the ICU patients. Elevated sTREM-1 baseline concentration was an independent predictor of complicated outcomes (Hazard Ratio (HR) = 1.5 (1.1-2.1), p = 0.02 in ward patients; HR = 3.8 (1.8-8.0), p = 0.0003 in ICU patients). An sTREM-1 plasma concentration of 224 pg/mL had a sensitivity of 42%, and a specificity of 76% in the ConvC for complicated outcome. In the ICUC, a 287 pg/mL cutoff had a sensitivity of 78%, and a specificity of 74% for death. The sTREM-1 concentrations increased over time in the ConvC patients with a complicated outcome (p = 0.017), but not in the ICUC patients.ConclusionsIn COVID-19 patients, plasma concentration of sTREM-1 is an independent predictor of the outcome, although its positive and negative likelihood ratio are not good enough to guide clinical decision as a standalone marker.
| S-EPMC10423708 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic has led to more than 760,000 deaths worldwide (correct as of 16th August 2020). Studies suggest a hyperinflammatory response is a major cause of disease severity and death. Identitfying COVID-19 patients with hyperinflammation may identify subgroups who could benefit from targeted immunomodulatory treatments. Analysis of cytokine levels at the point of diagnosis of SARS-CoV-2 infection can identify patients at risk of deterioration.MethodsWe used a multiplex cytokine assay to measure serum IL-6, IL-8, TNF, IL-1β, GM-CSF, IL-10, IL-33 and IFN-γ in 100 hospitalised patients with confirmed COVID-19 at admission to University Hospital Southampton (UK). Demographic, clinical and outcome data were collected for analysis.ResultsAge > 70 years was the strongest predictor of death (OR 28, 95% CI 5.94, 139.45). IL-6, IL-8, TNF, IL-1β and IL-33 were significantly associated with adverse outcome. Clinical parameters were predictive of poor outcome (AUROC 0.71), addition of a combined cytokine panel significantly improved the predictability (AUROC 0.85). In those ≤70 years, IL-33 and TNF were predictive of poor outcome (AUROC 0.83 and 0.84), addition of a combined cytokine panel demonstrated greater predictability of poor outcome than clinical parameters alone (AUROC 0.92 vs 0.77).ConclusionsA combined cytokine panel improves the accuracy of the predictive value for adverse outcome beyond standard clinical data alone. Identification of specific cytokines may help to stratify patients towards trials of specific immunomodulatory treatments to improve outcomes in COVID-19.
| S-EPMC7506817 | biostudies-literature
Project description: Not available
| S-EPMC8824444 | biostudies-literature
Project description:BackgroundInformation regarding coronavirus disease 2019 (COVID-19) in haemodialysis (HD) patients is limited and early studies suggest a poor outcome. We aimed to identify clinical and biological markers associated with severe forms of COVID-19 in HD patients.MethodsWe conducted a prospective, observational and multicentric study. Sixty-two consecutive adult HD patients with confirmed COVID-19 from four dialysis facilities in Paris, France, from 19 March to 19 May 2020 were included.Blood tests were performed before diagnosis and at Days 7 and 14 after diagnosis. Severe forms of COVID-19 were defined as requiring oxygen therapy, admission in an intensive care unit or death. Cox regression models were used to compute adjusted hazard ratios (aHRs). Kaplan-Meier curves and log-rank tests were used for survival analysis.ResultsTwenty-eight patients (45%) displayed severe forms of COVID-19. Compared with non-severe forms, these patients had more fever (93% versus 56%, P < 0.01), cough (71% versus 38%, P = 0.02) and dyspnoea (43% versus 6%, P < 0.01) at diagnosis. At Day 7 post-diagnosis, neutrophil counts, neutrophil:lymphocyte (N:L) ratio, C-reactive protein, ferritin, fibrinogen and lactate dehydrogenase levels were significantly higher in severe COVID-19 patients. Multivariate analysis revealed an N:L ratio >3.7 was the major marker associated with severe forms, with an aHR of 4.28 (95% confidence interval 1.52-12.0; P = 0.006). After a median follow-up time of 48 days (range 27-61), six patients with severe forms died (10%).ConclusionsHD patients are at increased risk of severe forms of COVID-19. An elevated N:L ratio at Day 7 was highly associated with the severe forms. Assessing the N:L ratio could inform clinicians for early treatment decisions.
| S-EPMC7717182 | biostudies-literature
Project description:In this study, we sought to identify circulating microRNA (miRNA) signatures associated with COVID-19 severity and outcome through small RNA-sequencing of serum samples from 89 COVID-19 patients and 45 healthy controls. As results, a set of miRNAs associated with lung disease, vascular damage and inflammation were upregulated in serum of COVID-19 patients vs controls, while miRNAs that inhibit pro-inflammatory cytokines and chemokines, angiogenesis and stress response were downregulated. In addition, patients with severe COVID-19 vs mild or moderate disease had a circulating miRNA signature associated with sepsis, hearth failure, tissue fibrosis, inflammation, and impairment of type I IFN and antiviral responses. A subset of the differentially expressed miRNAs predicted ICU admission, sequelae and mortality in COVID-19 patients. Investigation of the differentially expressed circulating miRNAs in relevant human cell types in vitro showed that some of these miRNAs were modulated directly by SARS-CoV-2 infection or indirectly by type I IFN stimulation.
2022-05-03 | GSE201790 | GEO
Project description:COVID-19 infections could be complicated by acute respiratory distress syndrome (ARDS), increasing mortality risk. We sought to assess the methylome of peripheral blood mononuclear cells in COVID-19 with ARDS. We recruited 100 COVID-19 patients with ARDS under mechanical ventilation and 33 non-COVID-19 controls between April and July 2020. COVID-19 patients were followed at four time points for 60 days. DNA methylation and immune cell populations were measured at each time point. A multivariate cox proportional risk regression analysis was conducted to identify predictive signatures according to survival. The comparison of COVID-19 to controls at inclusion revealed the presence of a 14.4% difference in promoter-associated CpGs in genes that control immune-related pathways such as interferon-gamma and interferon-alpha responses. On day 60, 24% of patients died. The inter-comparison of baseline DNA methylation to the last recorded time point in both COVID-19 groups or the intra-comparison between inclusion and the end of follow-up in every group showed that most changes occurred as the disease progressed, mainly in the AIM gene, which is associated with an intensified immune response in those who recovered. The multivariate Cox proportional risk regression analysis showed that higher methylation of the "Apoptotic execution Pathway" genes (ROC1, ZNF789, and H1F0) at inclusion increases mortality risk by over twofold. We observed an epigenetic signature of immune-related genes in COVID-19 patients with ARDS. Further, Hypermethylation of the apoptotic execution pathway genes predicts the outcome. IMRPOVIE study, NCT04473131.
| S-EPMC9652914 | biostudies-literature
Project description:BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA loads in patient specimens may act as a clinical outcome predictor in critically ill patients with coronavirus disease 2019 (COVID-19).MethodsWe evaluated the predictive value of viral RNA loads and courses in the blood compared with the upper and lower respiratory tract loads of critically ill COVID-19 patients. Daily specimen collection and viral RNA quantification by reverse transcription quantitative polymerase chain reaction were performed in all consecutive 170 COVID-19 patients between March 2020 and February 2021 during the entire intensive care unit (ICU) stay (4145 samples analyzed). Patients were grouped according to their 90-day outcome as survivors (n=100) or nonsurvivors (n=70).ResultsIn nonsurvivors, blood SARS-CoV-2 RNA loads were significantly higher at the time of admission to the ICU (P=.0009). Failure of blood RNA clearance was observed in 33/50 (66%) of the nonsurvivors compared with 12/64 (19%) survivors (P<.0001). As determined by multivariate analysis, taking sociodemographic and clinical parameters into account, blood SARS-CoV-2 RNA load represents a valid and independent predictor of outcome in critically ill COVID-19 patients (odds ratio [OR; log10], 0.23; 95% CI, 0.12-0.42; P<.0001), with a significantly higher effect for survival compared with respiratory tract SARS-CoV-2 RNA loads (OR [log10], 0.75; 95% CI, 0.66-0.85; P<.0001). Blood RNA loads exceeding 2.51×103 SARS-CoV-2 RNA copies/mL were found to indicate a 50% probability of death. Consistently, 29/33 (88%) nonsurvivors with failure of virus clearance exceeded this cutoff value constantly.ConclusionsBlood SARS-CoV-2 load is an important independent outcome predictor and should be further evaluated for treatment allocation and patient monitoring.
| S-EPMC8522363 | biostudies-literature
Project description:BackgroundDespite the death rate of COVID-19 is less than 3%, the fatality rate of severe/critical cases is high, according to World Health Organization (WHO). Thus, screening the severe/critical cases before symptom occurs effectively saves medical resources.Methods and materialsIn this study, all 336 cases of patients infected COVID-19 in Shanghai to March 12th, were retrospectively enrolled, and divided in to training and test datasets. In addition, 220 clinical and laboratory observations/records were also collected. Clinical indicators were associated with severe/critical symptoms were identified and a model for severe/critical symptom prediction was developed.ResultsTotally, 36 clinical indicators significantly associated with severe/critical symptom were identified. The clinical indicators are mainly thyroxine, immune related cells and products. Support Vector Machine (SVM) and optimized combination of age, GSH, CD3 ratio and total protein has a good performance in discriminating the mild and severe/critical cases. The area under receiving operating curve (AUROC) reached 0.9996 and 0.9757 in the training and testing dataset, respectively. When the using cut-off value as 0.0667, the recall rate was 93.33 % and 100 % in the training and testing datasets, separately. Cox multivariate regression and survival analyses revealed that the model significantly discriminated the severe/critical cases and used the information of the selected clinical indicators.ConclusionThe model was robust and effective in predicting the severe/critical COVID cases.
| S-EPMC7219384 | biostudies-literature