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.
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:BackgroundAcute kidney injury is common in COVID-19 patients admitted to the ICU. Urinary biomarkers are a non-invasive way of assaying renal damage, and so far, urinary cytokines are not fully investigated. The current study aimed to assess urinary cytokine levels in COVID-19 patients.MethodsUrine was collected from COVID-19 patients (n = 29) in intensive care and compared to a preoperative group of patients (n = 9) with no critical illness. 92 urinary cytokines were analyzed in multiplex using the Olink Target 96 inflammation panel and compared to clinical characteristics, and urinary markers of kidney injury.ResultsThere were strong correlations between proinflammatory cytokines and between urinary cytokines and urinary kidney injury markers in 29 COVID-19 patients. Several cytokines were correlated to kidney injury, 31 cytokines to AKI stage and 19 cytokines correlated to maximal creatinine.ConclusionsUrinary inflammatory cytokines from a wide range of immune cell lineages were significantly upregulated during COVID-19 and the upregulation correlated with acute kidney injury as well as urinary markers of kidney tissue damage.
Project description:Coronavirus disease 2019 (COVID-19) has swept the world, unlike any other pandemic in the last 50 years. Our understanding of the disease has evolved rapidly since the outbreak; disease prognosis is influenced mainly by multi-organ involvement. Acute respiratory distress syndrome, heart failure, renal failure, liver damage, shock and multi-organ failure are strongly associated with morbidity and mortality. The COVID-19 disease pathology is plausibly linked to the hyperinflammatory response of the body characterized by pathological cytokine levels. The term 'cytokine storm syndrome' is perhaps one of the critical hallmarks of COVID-19 disease severity. In this review, we highlight prominent cytokine families and their potential role in COVID-19, the type I and II interferons, tumour necrosis factor and members of the Interleukin family. We address various changes in cellular components of the immune response corroborating with changes in cytokine levels while discussing cytokine sources and biological functions. Finally, we discuss in brief potential therapies attempting to modulate the cytokine storm.