Single-cell RNA-seq of PBMCs from severe COVID-19 patients
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ABSTRACT:
PROVIDER: PRJNA634090 | ENA |
REPOSITORIES: ENA
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Project description:Many clinical risk factors for severe COVID-19, such as diabetes, hypertension, and high body mass index have been reported. However, searching for additional risk factors should be continued to predict the progression of severe COVID-19 more accurately. We suppose that clonal hematopoiesis of indeterminate potential (CHIP) can also be regarded as one of risk factors. To identify the influence of CHIP in COVID-19 pathogenesis, we performed single-cell RNA-seq using peripheral blood mononuclear cells (PBMCs) obtained from severe COVID-19 patient with CHIP and integrate the data with other published COVID-19 scRNA seq data (GSE149689). After clustering and annotating cell types, we compare the expression profiles between CHIP vs non-CHIP COVID-19 severe patient.
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Project description:Lung transplantation can potentially be a life-saving treatment for patients with non-resolving COVID-19-associated respiratory failure. Concerns limiting transplant include recurrence of SARS-CoV-2 infection in the allograft, technical challenges imposed by viral-mediated injury to the native lung, and potential risk for allograft infection by pathogens associated with ventilator-associated pneumonia in the native lung. Most importantly, the native lung might recover, resulting in long-term outcomes preferable to transplant. Here, we report results of the first successful lung transplantation procedures in patients with non-resolving COVID-19-associated respiratory failure in the United States. We performed sm-FISH to detect both positive and negative strands of SARS-CoV-2 RNA in the explanted lung tissue, extracellular matrix imaging using SHIELD tissue clearance, and single cell RNA-Seq on explant and warm post-mortem lung biopsies from patients who died from severe COVID-19 pneumonia. Lungs from patients with prolonged COVID-19 were free of virus but pathology showed extensive evidence of injury and fibrosis which resembled end-stage pulmonary fibrosis. We used a machine learning approach to project single cell RNA-Seq data from patients with late stage COVID-19 onto a single cell atlas of pulmonary fibrosis, revealing similarities across cell lineages. There was no recurrence of SARS-CoV-2 or pathogens associated with pre-transplant ventilator associated pneumonias following transplantation. Our findings suggest that some patients with severe COVID-19 develop fibrotic lung disease for which lung transplantation is the only option for survival.
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Project description:Single cell transcriptomics of PBMCs during severe COVID-19
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel viral pathogen that causes a clinical disease called coronavirus disease 2019 (COVID-19). Approximately 20% of infected patients experience a severe manifestation of the disease, causing bilateral pneumonia and acute respiratory distress syndrome. Severe COVID-19 patients also have a pronounced coagulopathy with approximately 30% of patients experiencing thromboembolic complications. However, the cellular etiology driving the coagulopathy remains unknown. Here, we explore whether the prominent neutrophilia seen in severe COVID-19 patients contributes to inflammation-associated coagulation. We found in severe patients the emergence of a CD16Int low-density inflammatory band (LDIB) neutrophil population that trends over time with changes in disease status. These cells demonstrated spontaneous neutrophil extracellular trap (NET) formation, higher phagocytic capacity, enhanced cytokine production, and associated clinically with D-dimer, ferritin, and systemic IL-6 and TNF-α levels. Strikingly, LDIB neutrophils are the major immune cells within the bronchoalveolar lavage (BAL) fluid with increased CXCR3 and loss of CD44 and CD38 expression. We conclude that the LDIB subset contributes to COVID- 19-associated coagulopathy (CAC) and systemic inflammation and could be used as an adjunct clinical marker to monitor disease status and progression. Identifying patients who are trending towards LDIB crisis and implementing early, appropriate treatment could improve all-cause mortality rates for severe COVID-19 patients.
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