Project description:Coronavirus disease 2019 (COVID-19) can be asymptomatic or lead to a wide spectrum of symptoms, ranging from mild upper respiratory system involvement to acute respiratory distress syndrome, multi-organ damage and death. In this study, we explored the potential of microRNAs (miRNA) in delineating patient condition and in predicting clinical outcome. Analysis of the circulating miRNA profile of COVID-19 patients, sampled at different hospitalization intervals after admission, allowed to identify miR-144-3p as a dynamically regulated miRNA in response to COVID-19.
Project description:Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.
Project description:The disease caused by the novel coronavirus of 2019 (COVID-19) has resulted in significant morbidity and mortality world-wide. A systemic hyper-inflammation characterizes the severe COVID-19 disease often associated with acute respiratory distress syndrome (ARDS). Bloodbiomarkers with prognostic relevance are of great importance in effective triage and critical care of severe COVID-19 patients. In the present study we report higher plasma abundance of soluble urokinase-type plasminogen activator receptor (sUPAR), shown to be expressed by an abnormally expanded circulating myeloid cell population, in severe COVID-19 patients with acute respiratory distress syndrome. SUPAR level was found to be linked to a characteristic proteomic signature of plasma. A receiver operator characteristics curve analysis identified a cut-off value of sUPAR at 2000pg/ml, which was linked to characteristic differential expression in the immune transcriptome as well as clinical outcomes in our patient cohort. Thus we identified sUPAR as a biomarker with strong predictive potential for clinical outcomes in severe COVID-19.
Project description:Multi-omics single-cell profiling of surface proteins, gene expression and lymphocyte immune receptors from hospitalised COVID-19 patient peripheral blood immune cells and healthy controls donors. Identification of the coordinated immune cell compositional and state changes in response to SARS-CoV-2 infection or LPS challenge, compared to healthy control immune cells.
Project description:The majority of patients with COVID-19 have a self-limiting upper respiratory tract infection mostly represented by asymptomatic or mild, however a small but relevant proportion of patients develops acute respiratory distress syndrome (ARDS), characterised by an excessive, host immune response with overproduction of proinflammatory cytokines can rapidly lead to multi-organ failure and death. Indeed, immune pathologies are well characterised through deep immune phenotyping, plasma analysis, sc-RNA and chip based methylation analysis, still we lack a molecular understanding of immune pathologies associated with COVID-19 which is urgently needed for new prognostic and therapeutic interventions. In this study, we first time showed a SARS-Cov2 induced severity associated deregulation of immune functions driven through a global reprogramming of immune functions through a epigenetically driven gene regulatory network
Project description:The clinical course of Coronavirus disease 2019 (COVID-19) displays a wide variability, ranging from completely asymptomatic forms to diseases associated with severe clinical outcomes. To reduce the incidence COVID-19 severe outcomes, innovative molecular biomarkers are needed to improve the stratification of patients at the highest risk of mortality and to better customize therapeutic strategies. MicroRNAs associated with COVID-19 outcomes could allow quantifying the risk of severe outcomes and developing models for predicting outcomes, thus helping to customize the most aggressive therapeutic strategies for each patient. Here, we analyzed the circulating miRNA profiles in a set of 12 hospitalized patients with severe COVID-19, with the aim to identify miRNAs associated with in-hospital mortality.
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the ensuing COVID-19 pandemic have caused ∼40 million cases and over 648,000 deaths in the United States alone. Troubling disparities in COVID-19-associated mortality emerged early, with nearly 70% of deaths confined to Black/African-American (AA) patients in some areas, yet targeted studies within this demographic are scant. Multi-omics single-cell analyses of immune profiles from airways and matching blood samples of Black/AA patients revealed low viral load, yet pronounced and persistent pulmonary neutrophilia with advanced features of cytokine release syndrome and acute respiratory distress syndrome (ARDS), including exacerbated production of IL-8, IL-1β, IL-6, and CCL3/4 along with elevated levels of neutrophil elastase and myeloperoxidase. Circulating S100A12+/IFITM2+ mature neutrophils are recruited via the IL-8/CXCR2 axis, which emerges as a potential therapeutic target to reduce pathogenic neutrophilia and constrain ARDS in severe COVID-19.
Project description:Extrapulmonary manifestations of COVID-19 have gained attention, not only due to their links to clinical outcomes, but also due to their potential long-term sequelae1. Recent evidence has shown multi-organ tropism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including heart, kidney and liver2. Previous studies have shown that close to 20% of hospitalized patients with COVID-19 develop liver injury, showing an association to disease severity3. Here, we identified a high frequency of liver enzyme alterations at admission in COVID-19 patients who required hospitalization. Then, we characterized SARS-CoV-2 liver tropism in autopsy samples, based on the expression of cell-entry facilitators in parenchymal cells, clinical polymerase chain reaction (PCR) positivity, subgenomic SARS-CoV-2 identification using RNA sequencing, and viral RNA detection by in situ hybridization. Next, we unraveled the transcriptomic and proteomic landscape of SARS-CoV-2 liver tropism, revealing significant increases in interferon alpha and gamma signaling and compensatory liver-specific metabolic regulation. While these results reflect changes in tissues from patients with severe SARS-CoV-2 infection, these profound molecular alterations raise questions about the potential long-term consequences of COVID-19 infection.
Project description:The amount of SARS-CoV-2 detected in the upper respiratory tract (URT viral load) is a key driver of transmission of infection. Current evidence suggests that mechanisms constraining URT viral load are different from those controlling lower respiratory tract viral load and disease severity. Understanding such mechanisms may help to develop treatments and vaccine strategies to reduce transmission. Combining mathematical modelling of URT viral load dynamics with transcriptome analyses we aimed to identify mechanisms controlling URT viral load. COVID-19 patients were recruited in Spain during the first wave of the pandemic. RNA sequencing of peripheral blood and targeted NanoString nCounter transcriptome analysis of nasal epithelium were performed and gene expression analysed in relation to paired URT viral load samples collected within 15 days of symptom onset. Proportions of major immune cells in blood were estimated from transcriptional data using computational differential estimation. Weighted correlation network analysis (adjusted for cell proportions) and fixed transcriptional repertoire analysis were used to identify associations with URT viral load, quantified as standard deviations (z-scores) from an expected trajectory over time.
Project description:The SARS-CoV-2 has already caused over 523 million COVID-19 cases and 6.27 million deaths worldwide. COVID-19 leads to a severe acute respiratory syndrome, a hyperinflammatory response, and widespread multi-organ damage. Common symptoms of COVID-19 include fever, cough, fatigue, shortness of breath, and loss of taste and smell. Here we offer an in-depth analysis of the transcriptional response to SARS-CoV-2. We performed RNA-seq analysis of lung tissues from three COVID-19 patients.