Browse
Submit Data
Databases
API
Help

Dataset Information

16 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell immune profiling reveals distinct immune response in asymptomatic COVID-19 patients.

ABSTRACT: While some individuals infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) present mild-to-severe disease, many SARS-CoV-2-infected individuals are asymptomatic. We sought to identify the distinction of immune response between asymptomatic and moderate patients. We performed single-cell transcriptome and T-cell/B-cell receptor (TCR/BCR) sequencing in 37 longitudinal collected peripheral blood mononuclear cell samples from asymptomatic, moderate, and severe patients with healthy controls. Asymptomatic patients displayed increased CD56^briCD16^- natural killer (NK) cells and upregulation of interferon-gamma in effector CD4⁺ and CD8⁺ T cells and NK cells. They showed more robust TCR clonal expansion, especially in effector CD4⁺ T cells, but lack strong BCR clonal expansion compared to moderate patients. Moreover, asymptomatic patients have lower interferon-stimulated genes (ISGs) expression in general but large interpatient variability, whereas moderate patients showed various magnitude and temporal dynamics of the ISGs expression across multiple cell populations but lower than a patient with severe disease. Our data provide evidence of different immune signatures to SARS-CoV-2 in asymptomatic infections.

SUBMITTER: Zhao XN

PROVIDER: S-EPMC8443960 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Transcriptome analysis of PBMCs reveals distinct immune response in the asymptomatic and re-detectable positive COVID-19 patients

Project description:The existence of asymptomatic and re-detectable positive COVID-19 patients presents the disease control challenges of COVID-19. Most studies on immune response of COVID-19 have focused on the moderately or severely symptomatic patients, however little is known about the immune response in asymptomatic and re-detectable positive patients. Here we performed a comprehensive analysis of the transcriptomic profiles of PBMCs from 48 COVID-19 patients.

2021-07-27 | GSE179627 | GEO

Transcriptome Analysis of Peripheral Blood Mononuclear Cells Reveals Distinct Immune Response in Asymptomatic and Re-Detectable Positive COVID-19 Patients.

Project description:The existence of asymptomatic and re-detectable positive coronavirus disease 2019 (COVID-19) patients presents the disease control challenges of COVID-19. Most studies on immune responses in COVID-19 have focused on moderately or severely symptomatic patients; however, little is known about the immune response in asymptomatic and re-detectable positive (RP) patients. Here we performed a comprehensive analysis of the transcriptomic profiles of peripheral blood mononuclear cells (PBMCs) from 48 COVID-19 patients which included 8 asymptomatic, 13 symptomatic, 15 recovered and 12 RP patients. The weighted gene co-expression network analysis (WGCNA) identified six co-expression modules, of which the turquoise module was positively correlated with the asymptomatic, symptomatic, and recovered COVID-19 patients. The red module positively correlated with symptomatic patients only and the blue and brown modules positively correlated with the RP patients. The analysis by single sample gene set enrichment analysis (ssGSEA) revealed a lower level of IFN response and complement activation in the asymptomatic patients compared with the symptomatic, indicating a weaker immune response of the PBMCs in the asymptomatic patients. In addition, gene set enrichment analysis (GSEA) analysis showed the enrichment of TNFα/NF-κB and influenza infection in the RP patients compared with the recovered patients, indicating a hyper-inflammatory immune response in the PBMC of RP patients. Thus our findings could extend our understanding of host immune response during the progression of COVID-19 disease and assist clinical management and the immunotherapy development for COVID-19.

| S-EPMC8359015 | biostudies-literature

Single-Cell Sequencing of Peripheral Mononuclear Cells Reveals Distinct Immune Response Landscapes of COVID-19 and Influenza Patients.

Project description:The coronavirus disease 2019 (COVID-19) pandemic poses a current world-wide public health threat. However, little is known about its hallmarks compared to other infectious diseases. Here, we report the single-cell transcriptional landscape of longitudinally collected peripheral blood mononuclear cells (PBMCs) in both COVID-19- and influenza A virus (IAV)-infected patients. We observed increase of plasma cells in both COVID-19 and IAV patients and XIAP associated factor 1 (XAF1)-, tumor necrosis factor (TNF)-, and FAS-induced T cell apoptosis in COVID-19 patients. Further analyses revealed distinct signaling pathways activated in COVID-19 (STAT1 and IRF3) versus IAV (STAT3 and NFκB) patients and substantial differences in the expression of key factors. These factors include relatively increase of interleukin (IL)6R and IL6ST expression in COVID-19 patients but similarly increased IL-6 concentrations compared to IAV patients, supporting the clinical observations of increased proinflammatory cytokines in COVID-19 patients. Thus, we provide the landscape of PBMCs and unveil distinct immune response pathways in COVID-19 and IAV patients.

| S-EPMC7368915 | biostudies-literature

Postmortem high-dimensional immune profiling of severe COVID-19 patients reveals distinct patterns of immunosuppression and immunoactivation

Project description: Not available

| S-BIAD170 | bioimages

Postmortem high-dimensional immune profiling of severe COVID-19 patients reveals distinct patterns of immunosuppression and immunoactivation.

Project description:A complete diagnostic autopsy is the gold-standard to gain insight into Coronavirus disease 2019 (COVID-19) pathogenesis. To delineate the in situ immune responses to SARS-CoV-2 viral infection, here we perform comprehensive high-dimensional transcriptional and spatial immune profiling in 22 COVID-19 decedents from Wuhan, China. We find TIM-3-mediated and PD-1-mediated immunosuppression as a hallmark of severe COVID-19, particularly in men, with PD-1+ cells being proximal rather than distal to TIM-3+ cells. Concurrently, lymphocytes are distal, while activated myeloid cells are proximal, to SARS-CoV-2 viral antigens, consistent with prevalent SARS-CoV-2 infection of myeloid cells in multiple organs. Finally, viral load positively correlates with specific immunosuppression and dendritic cell markers. In summary, our data show that SARS-CoV-2 viral infection induces lymphocyte suppression yet myeloid activation in severe COVID-19, so these two cell types likely have distinct functions in severe COVID-19 disease progression, and should be targeted differently for therapy.

| S-EPMC8755743 | biostudies-literature

Deep immune profiling of COVID-19 patients reveals patient heterogeneity and distinct immunotypes with implications for therapeutic interventions.

Project description:COVID-19 has become a global pandemic. Immune dysregulation has been implicated, but immune responses remain poorly understood. We analyzed 71 COVID-19 patients compared to recovered and healthy subjects using high dimensional cytometry. Integrated analysis of ~200 immune and >30 clinical features revealed activation of T cell and B cell subsets, but only in some patients. A subgroup of patients had T cell activation characteristic of acute viral infection and plasmablast responses could reach >30% of circulating B cells. However, another subgroup had lymphocyte activation comparable to uninfected subjects. Stable versus dynamic immunological signatures were identified and linked to trajectories of disease severity change. These analyses identified three "immunotypes" associated with poor clinical trajectories versus improving health. These immunotypes may have implications for therapeutics and vaccines.

| S-EPMC7263500 | biostudies-literature

Proteomic blood profiling in mild, severe and critical COVID-19 patients

Project description: Not available

| S-BSST416 | biostudies-other

Transcriptomic profiling of peripheral immune cells reveals distinct innate immune signatures associated with disease severity in COVID-19 viremia patients

Project description:SARS-CoV-2 is an emerging mosquito-borne pathogen with increasing public health significance. To characterize interconnected immune responses to SARS-CoV-2, we here examined transcriptional signatures of CD4 and CD8 T cells, B cells, NK cells, monocytes, myeloid dendritic cells (mDCs), and plasmacytoid dendritic cells (pDCs) from three individuals with naturally-acquired SARS-CoV-2 infection. Whole transcriptome analysis demonstrated that all seven immune cells among PBMCs were clustered together with disease severity regardless of cell types. mDCs and pDCs gene signatures distinct disease severity. A distinct phenotype was observed in severe patients with or without plasma viremia, demonstrating a highly impaired induction of Interferon stimulated genes (ISGs) accompanied by imbalanced type I interferon sensing and an excessive inflammatory response. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in seven major immune cells in blood from different disease severe COVID-19 patients.

2022-11-11 | GSE216529 | GEO

Large-scale single-cell analysis reveals critical immune characteristics of COVID-19 patients

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

Clinical Characteristics of Immune Response in Asymptomatic Carriers and Symptomatic Patients With COVID-19.

Project description:The pandemic of coronavirus disease 2019 (COVID-19) has emerged as a major public health challenge worldwide. A comprehensive understanding of clinical characteristics and immune responses in asymptomatic carriers and symptomatic patients with COVID-19 is of great significance to the countermeasures of patients with COVID-19. Herein, we described the clinical information and laboratory findings of 43 individuals from Hunan Province, China, including 13 asymptomatic carriers and 10 symptomatic patients with COVID-19, as well as 20 healthy controls in the period from 25 January to 18 May 2020. The serum samples of these individuals were analyzed to measure the cytokine responses, receptor-binding domain (RBD), and nucleocapsid (N) protein-specific antibody titers, as well as SARS-CoV-2 neutralizing antibodies (nAbs). For cytokines, significantly higher Th1 cytokines including IL-2, IL-8, IL-12p70, IFN-γ, and TNF-α, as well as Th2 cytokines including IL-10 and IL-13 were observed in symptomatic patients compared with asymptomatic carriers. Compared with symptomatic patients, higher N-specific IgG4/IgG1 ratio and RBD-specific/N-specific IgG1 ratio were observed in asymptomatic carriers. Comparable nAbs were detected in both asymptomatic carriers and symptomatic patients with COVID-19. In the symptomatic group, nAbs in patients with underlying diseases were weaker than those of patients without underlying diseases. Our retrospective study will enrich and verify the clinical characteristics and serology diversities in asymptomatic carriers and symptomatic patients with COVID-19.

| S-EPMC9171238 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data