659 results for ""option,com_discussions"+y+19"

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• COVID-19 Postmortem Lung snRNA-seq

  A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

  Study EGAS00001004689

• ScRNA-seq of PBMC and whole blood samples reveals a dysregulated myeloid cell compartment in severe COVID-19

  In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

  Study EGAS00001004571

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): NIH Digital Health Solutions for COVID-19: IBM Covid19 Contact Tracing and Data Exchange Tools

  The goal of this project is to develop both contact tracing and secure data exchange tools. The contact tracing solution securely combines data from a variety of sources (including manual self-report data and mobile device surveys) to enable tracing of contacts with individuals that have tested positive for COVID-19 or have been exposed to COVID-19. The data exchange solution is a secure mechanism that empowers users to control the data they share in the course of their return to work, including the ability to provide a verifiable health status claim. These tools are being used by an employer to evaluate the risk of allowing individuals to return to normal activities, and also the ability to trace user contact with individuals diagnosed with or suspected of having contracted COVID-19. DOI: https://rapids.ll.mit.edu/10.57895/h0an-m559

  Study phs002516

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): Covidseeker and COVID-19 Citizen Science: Leveraging Citizen Science and Real-Time Geospatial Temporal Mobile Data for Digital Contact Tracing and SARS-CoV-2 Hotspotting

  The Covidseeker and COVID-19 Citizen Science Study integrates a retrospectively-determined geolocation digital program into an established digital infrastructure housed within the NIH-funded Eureka platform to enroll SARS-CoV-2 positive and negative individuals. The solution also leverages the ongoing COVID-19 Citizen Science Study cohort both in-person and remotely to test and implement existing technology to enhance readily accessible contact tracing methods and identify “hot spots” of transmission of SARS-CoV-2. The tools are designed to alert users regarding overlap with SARS-CoV-2 infected individuals, identifying businesses that were visited by someone who later tested positive for COVID-19, and working with those businesses and public health departments on strategies to reduce the spread of the virus. DOI: https://rapids.ll.mit.edu/10.57895/me7r-vp06

  Study phs002519

• Multi-omic single-cell profiling of peripheral blood immune cells from COVID-19 patients and controls.

  The COVID-19 pandemic, caused by SARS coronavirus 2 (SARS-CoV-2), has resulted in excess morbidity and mortality as well as economic decline. To characterise the systemic host immune response to SARS-CoV-2, we performed single-cell RNA-sequencing coupled with analysis of cell surface proteins, providing molecular profiling of over 800,000 peripheral blood mononuclear cells from a cohort of 130 patients with COVID-19. Our cohort, from three UK centres, spans the spectrum of clinical presentations and disease severities ranging from asymptomatic to critical. Three control groups were included: healthy volunteers, patients suffering from a non-COVID-19 severe respiratory illness and healthy individuals administered with intravenous lipopolysaccharide to model an acute inflammatory response. Full single cell transcriptomes are coupled with quantification of 188 cell surface proteins, and T and B lymphocyte antigen receptor repertoires.

  Study EGAS00001005465

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We analyzed pulmonary monocyte and macrophage responses as well as and pulmonary pathology in two cohorts of patients with COVID-19 associated ARDS. Monocyte-derived macrophages accumulated in the lung during ARDS and acquired a profibrotic signature, characterized by high expression of known fibrogenic factors like TGFB1, SPP1 and LGMN. COVID-19 associated macrophages showed highly significant transcriptional similarity with profibrotic macrophage populations identified in idiopathic pulmonary fibrosis (IPF). Notably, overnight exposure to SARS-CoV-2, but not influenza A virus or viral RNA analogues, induced a similar phenotype in human monocytes from healthy volunteers in vitro. Patients with severe COVID-19 associated ARDS showed clear clinical, radiographic and histopathological features of scarring and fibrotic tissue remodeling. In conclusion, SARS-CoV-2 triggers profibrotic macrophage responses, fibroproliferative ARDS, and lung fibrosis

  Study EGAS00001004928

• H3K27ac HiChIP Dataset for 19 T-ALL patients and one normal control sample

  19 H3K27ac HICHIP from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference.

  Dataset EGAD50000000023

• Stability of gut microbiome after COVID-19 vaccination in healthy and immuno-compromised individuals

  Bidirectional interactions between the immune system and the gut microbiota are key contributors to various physiological functions. Immune-associated diseases such as cancer and auto- immunity, and efficacy of immunomodulatory therapies, have been linked to microbiome variation. Although COVID-19 infection has been shown to cause microbial dysbiosis, it remains understudied whether the inflammatory response associated with vaccination also impacts the microbiota. Here, we investigate the temporal impact of COVID-19 vaccination on the gut microbiome in healthy and immuno-compromised individuals; the latter included patients with primary immunodeficiency and cancer patients on immuno- modulating therapies. We find that the gut microbiome remained remarkably stable postvaccination irrespective of diverse immune status, vaccine response, and microbial composition spanned by the cohort. The stability is evident at all evaluated levels including diversity, phylum, species, and functional capacity. Our results in- dicate the resilience of the gut microbiome to host immune changes triggered by COVID-19 vaccination and suggest minimal, if any, impact on microbiome-mediated processes. These findings en- courage vaccine acceptance, particularly when contrasted with the significant microbiome shifts observed during COVID-19 infection.

  Study EGAS50000000179

• Analysis of the co-occurrence of LOY and CHIP in Alzheimer's disease patients and control individuals using whole-exome sequencing (WES)

  We performed deep whole-exome sequencing of FACS-isolated CD4+ T lymphocytes, NK and myeloid cells from men with AD and controls exhibiting either LOY or retention of Y chromosome (ROY). We found 39 sequence variants in known (canonical) myeloid driver genes of clonal hematopoiesis (MD-CH) and known lymphoid driver genes (LD-CH), and maximally 14 (35%) of these could co-exist with LOY within the same clone. We further describe 192 unknown drivers of clonal hematopoiesis (UD-CH), which were markedly enriched in AD-LOY individuals (odds ratio=4.8, Benjamini-Hochberg-adjusted p=0.041), and over 20% of these variants were protein-truncating. In myeloid cells, the total burden of all detected drivers correlated with the percentage of LOY cells (Spearman ρ=0.52, adjusted p=0.00041).

  Study EGAS00001008234

• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  Background Despite advances in identification of genetic markers associated to severe COVID-19, the full genetic characterisation of the disease remains elusive. Imputation of low-coverage whole genome sequencing (lcWGS) has emerged as a competitive method to study such disease-related genetic markers as they enable genotyping of most common genetic variants used for genome wide association studies. This study aims at exploring the potential use of imputation in lcWGS for a highly selected severe COVID-19 patient cohort. Findings We generated an imputed dataset of 79 variant call format (VCF) patient files using the GLIMPSE1 tool, each containing, on average, 9.5 million single nucleotide variants. The validation assessment of imputation accuracy yielded a squared Pearson correlation of approximately 0.97 across sequencing platforms, showing that GLIMPSE1 can be used to confidently impute variants with minor allele frequency up to approximately 2% in Spanish ancestry individuals. We conducted a comprehensive analysis on the patient cohort, examining hospitalisation and intensive care utilisation, sex and age-based differences, and clinical phenotypes using a standardised set of medical terms specifically developed to characterise severe COVID-19 symptoms for this cohort. Conclusion This dataset highlights the utility and accuracy of lcWGS imputation in the study of COVID-19 severity, setting a precedent for other applications in resource-constrained environments. The methods and findings presented here may be leveraged in future genomic projects, providing vital insights for health challenges like COVID-19.

  Study EGAS00001007573

• WGS of primary mediastinal large B-cell lymphoma

  This dataset includes 19 bamfiles of tumor, relapsed tumor and normal samples derived from 7 patients.

  Dataset EGAD50000000494

• Clinical-Epidemiological (CE) dataset from an Erasmus MC COVID-19 cohort

  This dataset comprises of Clinical-Epidemiological (CE) data from an Erasmus MC cohort of 151 individuals who were tested positive for COVID-19.

  Dataset EGAD00001009748

• Dataset for RNA PCNSL

  RNA sequencing of 19 samples from PCNSL tumors. Sequencing was performed on a HiSeq X Ten using Illumina TruSeq Stranded mRNA Kit. Sequencing was always paired.

  Dataset EGAD00001011119

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• COVID_Methyl_scRNA

  DAC for the study of whole-genome enzymatic DNA methylation sequencing and single-cell RNA sequencing of nasal cells from COVID-19 patients. Nasal swabs were collected from COVID-19 patients during the acute phase of infection as well as 3 and 12-months post-infection. Cells isolated from nasal swabs were subjected to whole-genome enzymatic DNA methylation sequencing (n=33) and scRNA-seq (n=24). For n=12 former COVID-19 pateints, follow-up samples were collected at 3 and 12 months post-infection and subjected to scRNA-seq.

  Dac EGAC50000000197

• Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19

  These data correspond to samples used in the following papers: 1. GWAS and meta-analysis identifies 49 genetic variants underlying critical Covid-19 2. Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19. 3. Identification of Genetic Determinants of Transcriptional Response to Metformin in Primary Human Monocytes. They are the raw RNA sequencing files as used in all downstream analysis.

  Dataset EGAD00001010176

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of severe COVID-19. In addition, we performed single-cell RNA-sequencing of SARS-CoV-2 stimulated classical blood monocytes. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001006827

• ATAC Dataset for 19 T-ALL patient samples and 1 normal control sample

  19 ATAC-seq from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference

  Dataset EGAD50000000024

• Targeted sequencing of HGS-EOC samples

  A 19-sample data set containing data from FFPE high grade serous ovarian cancer biopsies. The library was made with a custom hybridization kit (EZ-Cap, Roche) spanning 7 genes.

  Dataset EGAD00001006064

• COVID-19 severity correlates with airway epithelium–immune cell interactions identified by single-cell analysis

  To investigate the immune response and mechanisms associated with severe COVID-19, we performed single-cell RNA-seq on nasopharyngeal and bronchial samples from 19 clinically well-characterized patients with moderate or critical disease and from 5 healthy controls. We identified airway epithelial cell types and states vulnerable to SARS-CoV-2 infection. In COVID-19 patients, epithelial cells showed an average threefold increase in expression of the SARS-CoV-2 entry receptor ACE2, which correlated with interferon signals by immune cells. Compared with moderate cases, critical cases exhibited stronger interactions between epithelial and immune cells, as indicated by ligand–receptor expression profiles, and activated immune cells , including inflammatory macrophages expressing CCL2, CCL3, CCL20, CXCL1, CXCL3, CXCL10, IL8, IL1B and TNF . The transcriptional differences in critical cases compared with moderate cases likely contribute to clinical observations of heightened inflammatory tissue damage, lung injury and respiratory failure. Our data suggest that pharmacologic inhibition of the CCR1 and/or CCR5 pathways may suppress immune hyperactivation in critical COVID-19.

  Dataset EGAD00001006339

• COVID-19 Exome Sequencing DAC policy

  This is the DAC policy for exome sequencing data from COVID-19 patients from EASI genomics and NIMgentics and belonging to the study "Variability in immune response genes and prediction of severe SARS-CoV-2 infection(INMUNGEN-Cov2 project)"

  Dac EGAC50000000065

• Hypoxia acts as an environmental cue for the human TRM differentiation program

  Dataset consists of 19 bam files from RNA sequencing experiments batch1 and batch2.

  Dataset EGAD00001007692

• Single-cell RNA sequencing of 43 BALF samples from CAPA and COVID-19 patients

  Single-cell RNA sequencing of 43 bronchoalveolar lavage fluid (BALF) samples from 15 CAPA and 22 COVID-19 mechanically ventilated patients.

  Dataset EGAD00001011342

• Whole-Genome Sequencing Reveals Complex Genomic Features Underlying Anti-CD19 CAR T-Cell Treatment Failure in Lymphoma

  We performed Whole-Genome Sequencing (WGS) on 100 tumor and matched germline samples from 49 CD19-directed chimeric antigen receptor (CAR-19)-treated diffuse large B cell lymphoma (DLBCL) patients. We found that the presence of complex structural variants, APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide) mutational signatures, and genomic damage from reactive oxygen species predict CAR-19 resistance. BAM files will be available through dbGaP.

  Study phs003023

• Pre-activated anti-viral innate immunity in the upper airways controls early SARS-CoV-2 infection in children

  We investigated 10 female and 14 male SARS-CoV-2 positive children (age range: 0.8 to 18 years). Based on the WHO guidelines, 15 patients were classified as having mild COVID-19, while 7 children were classified as moderate COVID-19 cases. Two children were asymptomatic. 8 female and 10 male SARS-CoV-2 negative children were included as controls (age range: 4 to 16). 12 SARS-CoV-2 positive female and 9 male adults were included ( age range: 27 - 76) together with 13 female and 10 male SARS-CoV-2 negative adult controls (age: 24 - 77). 10 adult COVID-19 patients had mild disease, while 12 had moderate COVID-19. We performed single-cell RNA sequencing experiments.

  Dataset EGAD00001007969