Large-scale single-cell analysis reveals critical immune characteristics of COVID-19 patients
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA663865 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We profiled scRNA-seq of 284 samples collected from 196 individuals, including 22 patients with mild/moderate symptoms, 54 hospitalized patients with severe symptoms, and 95 recovered convalescent persons, as well as 25 healthy controls. The samples were obtained from various tissue types, including human peripheral blood mononuclear cells (249), bronchoalveolar lavage fluid (12) and pleural pleural effusion (1)/sputum (22).
2021-02-04 | GSE158055 | GEO
Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.
2020-08-29 | GSE157103 | GEO
Project description:Large-scale Multi-omic Analysis of COVID-19 Severity
| PRJNA660067 | ENA
Project description:Matched samples from individuals before they contracted COVID-19 and after they were diagnosed with it were used for TMT-based relative quantitation of their plasma proteome and glycoproteome to study the effects of this infectious disease. Twenty one COVID-19 patients whose pre-COVID-19 plasma samples were also available were selected for this study. These patients had varied courses of illness and were classified based on WHO guidelines into outpatients and those with severe and critical illness. 21 matched sample pairs were divided into 3 sets for 3 TMTPro 16-plex-based mass spectrometry experiments with 8 (set01), 8 (set02), and 5 (set03) patients each. Plasma-derived tryptic peptides from each sample were TMT-labeled, and each pooled set was used for separate experiments for total proteomics and glycoproteomics. A pooled aliquot from each set was used to enrich glycopeptides by size exclusion chromatography and another aliquot was used to fractionate all peptides by basic pH reversed phase liquid chromatography. Enriched glycopeptides were analyzed by LC-MS/MS and quantified across samples using TMT reporter ion intensities. Fold changes (intensity of protein or glycopeptide from a patient with COVID-19/that from the same patient before they had COVID-19) for each protein and glycopeptide were calculated for all patients to assess changes in the proteome that may be attributable to this illness. We detected 1,520 proteins, of which 472 were detected in all patients. 3,892 glycopeptides were identified at 1% FDR at peptide, glycan and glycopeptides levels and their reporter ion intensities were quantified. 732 glycopeptides from 232 glycoproteins were detected in all patients.
2022-08-12 | PXD029376 | Pride
Project description:Type I interferon (IFN-I) neutralizing autoantibodies have been found in some critical COVID-19 patients; however, their prevalence and longitudinal dynamics across the disease severity scale, and functional effects on circulating leukocytes remain unknown. Here, in 284 COVID-19 patients, we found IFN-I autoantibodies in 19% of critical, 6% of severe and none of the moderate cases. Longitudinal profiling of over 600,000 peripheral blood mononuclear cells using multiplexed single- cell epitope and transcriptome sequencing from 54 COVID-19 patients, 15 non-COVID-19 patients and 11 non-hospitalized healthy controls, revealed a lack of IFN-I stimulated gene (ISG-I) response in myeloid cells from critical cases, including those producing anti-IFN-I autoantibodies. Moreover, surface protein analysis showed an inverse correlation of the inhibitory receptor LAIR-1 with ISG-I expression response early in the disease course. This aberrant ISG-I response in critical patients with and without IFN-I autoantibodies, supports a unifying model for disease pathogenesis involving ISG-I suppression via convergent mechanisms.
2021-03-09 | GSE168453 | GEO
Project description:We performed RNA-Seq and high-resolution mass spectrometry on 128 blood samples from COVID-19 positive and negative patients with diverse disease severities. Over 17,000 transcripts, proteins, metabolites, and lipids were quantified and associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a comparative analysis with published data and a machine learning approach for prediction of COVID-19 severity.
2020-07-08 | MSV000085703 | MassIVE
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.
2022-02-01 | E-MTAB-10129 | biostudies-arrayexpress
Project description:Introduction: A maladaptive inflammatory response has been implicated in the pathogenesis of severe and critical COVID-19. This study aimed to characterize the temporal dynamics of this response and investigate whether critical disease is associated with distinct gene expression patterns. Methods: We performed microarray analysis of serial whole blood RNA samples from 19 patients with critical COVID-19, 15 patients with severe but non-critical disease and 11 healthy controls. We assessed whole blood gene expression patterns by differential gene expression analysis, gene set enrichment, two clustering methods and estimated relative leukocyte abundance using CIBERSORT. Results: Neutrophils, platelets, cytokine signaling, and the coagulation system were activated in COVID-19, and more pronounced in critical vs. non-critical disease. We observed two different trajectories of neutrophil-associated genes, indicating the emergence of a more immature neutrophil phenotype over time. Interferon-associated genes were strongly enriched in early COVID-19 before falling markedly, with modest severity-associated differences in trajectory. Conclusions: Severe COVID-19 is associated with a broad inflammatory response, which is more pronounced in critical disease. Our data suggest a progressively more immature circulating neutrophil phenotype over time. Interferon signaling is enriched in COVID-19 but does not seem to drive critical disease.
2023-02-13 | GSE213313 | GEO
Project description:Although some studies reported the comprehensive mRNA expression analysis of coronavirus disease 2019 (COVID-19) using blood samples to understand its pathogenesis, the characteristics of RNA expression in COVID-19 and sepsis have not been compared. We compared the transcriptome expression of whole blood samples from patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and patients with sepsis caused by other bacteria who entered the intensive care unit to clarify the COVID-19-specific RNA expression and understand its pathogenesis. Transcriptomes related to mitochondria were upregulated in COVID-19, whereas those related to neutrophils were upregulated in sepsis. However, the transcriptomes related to neutrophils were upregulated in both COVID-19 and sepsis compared to in healthy controls, whereas the mitochondrial transcriptomes were upregulated in COVID-19 and downregulated in sepsis compared to in healthy controls. Moreover, sepsis showed sub-optimal intrinsic apoptotic features compared with COVID-19. The transcriptome expression of COVID-19 has been examined in vitro but has not been widely validated using human specimens. This study improves the understanding of the pathogenesis of COVID-19 and can contribute to the development of treatments.
2022-11-29 | GSE199816 | GEO
Project description:In order to identify differentially abundant proteins, human plasma samples from COVID-19 patients with either a mild or moderate (MM) or a critical or severe (CS) disease course from acute phase of infection were analyzed on antibody microarrays 998 different proteins by 1,425 antibodies.
2023-03-15 | E-MTAB-12777 | biostudies-arrayexpress