Dataset Information

Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis.

ABSTRACT:

Background

Evidence has suggested that cytokine storms may be associated with T cell exhaustion (TEX) in COVID-19. However, the interaction mechanism between cytokine storms and TEX remains unclear.

Methods

With the aim of dissecting the molecular relationship of cytokine storms and TEX through single-cell RNA sequencing data analysis, we identified 14 cell types from bronchoalveolar lavage fluid of COVID-19 patients and healthy people. We observed a novel subset of severely exhausted CD8 T cells (Exh T_CD8) that co-expressed multiple inhibitory receptors, and two macrophage subclasses that were the main source of cytokine storms in bronchoalveolar.

Results

Correlation analysis between cytokine storm level and TEX level suggested that cytokine storms likely promoted TEX in severe COVID-19. Cell-cell communication analysis indicated that cytokines (e.g. CXCL10, CXCL11, CXCL2, CCL2, and CCL3) released by macrophages acted as ligands and significantly interacted with inhibitory receptors (e.g. CXCR3, DPP4, CCR1, CCR2, and CCR5) expressed by Exh T_CD8. These interactions formed the cytokine-receptor axes, which were also verified to be significantly correlated with cytokine storms and TEX in lung squamous cell carcinoma.

Conclusions

Cytokine storms may promote TEX through cytokine-receptor axes and be associated with poor prognosis in COVID-19. Blocking cytokine-receptor axes may reverse TEX. Our finding provides novel insights into TEX in COVID-19 and new clues for cytokine-targeted immunotherapy development.

SUBMITTER: Yang M

PROVIDER: S-EPMC9172646 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis.

Yang Minglei M Lin Chenghao C Wang Yanni Y Chen Kang K Han Yutong Y Zhang Haiyue H Li Weizhong W

Precision clinical medicine 20220523 2

<h4>Background</h4>Evidence has suggested that cytokine storms may be associated with T cell exhaustion (TEX) in COVID-19. However, the interaction mechanism between cytokine storms and TEX remains unclear.<h4>Methods</h4>With the aim of dissecting the molecular relationship of cytokine storms and TEX through single-cell RNA sequencing data analysis, we identified 14 cell types from bronchoalveolar lavage fluid of COVID-19 patients and healthy people. We observed a novel subset of severely exhau ...[more]

PMID: 35694714

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Project description:BackgroundSevere acute pancreatitis (SAP) is characterized by inflammation, with inflammatory immune cells playing a pivotal role in disease progression. This study aims to understand variations in specific immune cell subtypes in SAP, uncover their mechanisms of action, and identify potential biological markers for predicting Acute Pancreatitis (AP) severity.MethodsWe collected peripheral blood from 7 untreated SAP patients and employed single-cell RNA sequencing for the first time to construct a transcriptome atlas of peripheral blood mononuclear cells (PBMCs) in SAP. Integrating SAP transcriptomic data with 6 healthy controls from the GEO database facilitated the analysis of immune cell roles in SAP. We obtained comprehensive transcriptomic datasets from AP samples in the GEO database and identified potential biomarkers associated with AP severity using the "Scissor" tool in single-cell transcriptomic data.ResultsThis study presents the inaugural construction of a peripheral blood single-cell atlas for SAP patients, identifying 20 cell subtypes. Notably, there was a significant decrease in effector T cell subsets and a noteworthy increase in monocytes compared to healthy controls. Moreover, we identified a novel monocyte subpopulation expressing high levels of PPBP and PF4 which was significantly elevated in SAP. The proportion of monocyte subpopulations with high CCL3 expression was also markedly increased compared to healthy controls, as verified by flow cytometry. Additionally, cell communication analysis revealed insights into immune and inflammation-related signaling pathways in SAP patient monocytes. Finally, our findings suggest that the subpopulation with high CCL3 expression, along with upregulated pro-inflammatory genes such as S100A12, IL1B, and CCL3, holds promise as biomarkers for predicting AP severity.ConclusionThis study reveals monocytes' crucial role in SAP initiation and progression, characterized by distinct pro-inflammatory features intricately linked to AP severity. A monocyte subpopulation with elevated PPBP and CCL3 levels emerges as a potential biomarker and therapeutic target.

Dataset Information

Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis.

Background

Methods

Results

Conclusions

Publications

Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis.

Similar Datasets

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