Project description:Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit, to identify two clusters that, in spite of no major clinical differences, have different gene expression profiles that reveal different underlying pathogenetic mechanisms and ultimately have different ICU outcome. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding a similar result. These results illustrate the potential of transcriptomic profiles to identify patient endotypes and point to relevant pathogenetic mechanisms in COVID-19.
Project description:Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit, to identify two clusters that, in spite of no major clinical differences, have different gene expression profiles that reveal different underlying pathogenetic mechanisms and ultimately have different ICU outcome. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding a similar result. These results illustrate the potential of transcriptomic profiles to identify patient endotypes and point to relevant pathogenetic mechanisms in COVID-19.
Project description:Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit, to identify two clusters that, in spite of no major clinical differences, have different gene expression profiles that reveal different underlying pathogenetic mechanisms and ultimately have different ICU outcome. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding a similar result. These results illustrate the potential of transcriptomic profiles to identify patient endotypes and point to relevant pathogenetic mechanisms in COVID-19.
Project description:Total plasma IgA glycosylation was compared between healthy volunteers and volunteers suffering fromo infections with either the influenza A virus or the severe acute respiratory syndrome corona virus 2. Data from functional assays of the same plasma samples, such as neutrophil extracellular trap formation is also available.
Project description:Single-cell RNA-sequencing reveals a shift from focused IFN alpha-driven signals in COVID-19 ICU patients who survive to broad pro-inflammatory responses in fatal COVID-19 – a feature not observed in severe influenza. We conclude that fatal COVID-19 infection is driven by uncoordinated inflammatory responses that drive a hierarchy of T cell activation, elements of which can serve as prognostic indicators and potential targets for immune intervention.
Project description:Background: Liver injury commonly occurs in patients with COVID-19. There is limited data describing the course of liver injury occurrence in patients with different disease severity, and the causes and risk factors are unknown. We aim to investigate the incidence, characteristics, risk factors, and clinical outcomes of liver injury in patients with COVID-19. Methods: This retrospective observational study was conducted in three hospitals (Zhejiang, China). From January 19, 2020 to February 20, 2020, patients confirmed with COVID-19 (≥18 years) and without liver injury were enrolled and divided into non-critically ill and critically ill groups. The incidence and characteristics of liver injury were compared between the two groups. Demographics, clinical characteristics, treatments, and treatment outcomes between patients with or without liver injury were compared within each group. The multivariable logistic regression model was used to explore the risk factors for liver injury. Results: The mean age of 131 enrolled patients was 51.2 years (standard deviation [SD]: 16.1 years), and 70 (53.4%) patients were male. A total of 76 patients developed liver injury (mild, 40.5%; moderate, 15.3%; severe, 2.3%) with a median occurrence time of 10.0 days. Critically ill patients had higher and earlier occurrence (81.5 vs. 51.9%, 12.0 vs. 5.0 days; p < 0.001), greater injury severity (p < 0.001), and slower recovery (50.0 vs. 61.1%) of liver function than non-critically ill patients. Multivariable regression showed that the number of concomitant medications (odds ratio [OR]: 1.12, 95% confidence interval [CI]: 1.05-1.21) and the combination treatment of lopinavir/ritonavir and arbidol (OR: 3.58, 95% CI: 1.44-9.52) were risk factors for liver injury in non-critically ill patients. The metabolism of arbidol can be significantly inhibited by lopinavir/ritonavir in vitro (p < 0.005), which may be the underlying cause of drug-related liver injury. Liver injury was related to increased length of hospital stay (mean difference [MD]: 3.2, 95% CI: 1.3-5.2) and viral shedding duration (MD: 3.0, 95% CI: 1.0-4.9). Conclusions: Critically ill patients with COVID-19 suffered earlier occurrence, greater injury severity, and slower recovery from liver injury than non-critically ill patients. Drug factors were related to liver injury in non-critically ill patients. Liver injury was related to prolonged hospital stay and viral shedding duration in patients with COVID-19. Clinical Trial Registration: World Health Organization International Clinical Trials Registry Platform, ChiCTR2000030593. Registered March 8, 2020.
Project description:Background: Outcomes in patients with severe SARS-CoV-2 infection (COVID-19) are conditioned by viral control and regulation of inflammation. Variants in IFIH1, a gene coding the cytoplasmatic RNA sensor MDA5, regulate the response to viral infections. Methods: Patients admitted to an intensive care unit (ICU) with documented COVID-19 were prospectively included and IFIH1 rs1990760 genotypes determined. Peripheral blood gene expression, cell populations and immune mediators were measured during the first day after ICU admission before steroid therapy. Peripheral blood mononuclear cells from healthy volunteers were exposed ex-vivo to an MDA5 agonist and dexamethasone, and changes in gene expression assessed. ICU discharge and hospital death were modelled using rs1990760 variants and dexamethasone therapy as factors. Findings: 237 patients were studied. Patients with the IFIH1 rs1990760 TT variant showed a decrease in expression of inflammation-related pathways, an anti-inflammatory cell profile and a decrease in pro-inflammatory mediators. Cells with TT variant exposed to an MDA5 agonist ex-vivo showed an increase in FOXO3 and IL6 when dexamethasone was added. All patients with the TT variant not treated with steroids (n=14) survived their ICU stay (HR 2.49 95% confidence interval 1.29 – 4.79). Dexamethasone therapy in this subgroup (N=50) delayed ICU discharge and increased hospital mortality (HR 2.19, 95% confidence interval 1.01 – 4.87) and serum IL-6 concentrations. Interpretation: COVID-19 ICU patients with the IFIH1 rs1990760 TT variant show an ameliorated inflammatory response that results in better outcomes than CC/CT variants. Dexamethasone can reverse this anti-inflammatory phenotype, worsening the outcome. Funding: Instituto de Salud Carlos III.
Project description:Background: COVID-19 has revealed novel pathological mechanisms, particularly hypercoagulability leading to increased thrombotic risk in critically ill patients. This study investigates transcriptional signatures associated with thrombosis development in COVID-19 intensive care unit (ICU) patients and evaluates their predictive potential. Methods: We performed whole blood transcriptional profiling of 57 mechanically ventilated COVID-19 patients, comparing those with thrombotic complications (TC, n=36) to those without (non-TC, n=21) using differential gene expression and machine learning approaches. Results: TC patients showed greater transcriptome disruption and 283 differentially expressed genes compared to non-TC patients. Key features included enhanced neutrophil activation, inflammatory responses, and monocyte activation alongside suppressed lymphocyte function. An OPLS-DA model achieved excellent classification performance (AUC=0.961, 95% CI: 0.905-0.997). The maltase-glucoamylase gene (MGAM) was the top discriminatory biomarker outperforming traditional clinical markers like D-dimer and C-reactive protein (AUC=0.94). Conclusions: Thrombotic complications in critically ill COVID-19 patients are characterized by distinct transcriptional signatures reflecting heightened neutrophil activation and inflammatory dysregulation. MGAM represents a novel potential biomarker that outperforms traditional clinical markers for identifying patients at high thrombotic risk, offering new opportunities for personalized risk stratification and management in severe COVID-19.