Meta-analysis of single-cell RNA-seq data reveals phenotypic switching of immune cells in severe COVID-19 patients. (October 2021)

• Record Type: Journal Article
• Authors: Hasan, Md Zobaer; Islam, Syful; Matsumoto, Kenichi; Kawai, Taro
• Is Part Of: Computers in biology and medicine. Volume 137(2021)
• Publication Date: 2021-10
• Subjects: COVID-19 patients -- Single-cell RNA-Seq -- Meta-analysis -- Immune cell landscape -- Phenotypic switching; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2021.104792
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in the global coronavirus disease 2019 (COVID-19) pandemic. Despite several single-cell RNA sequencing (RNA-seq) studies, conclusions cannot be reached owing to the small number of available samples and the differences in technology and tissue types used in the studies. To better understand the cellular landscape and disease severity in COVID-19, we performed a meta-analysis of publicly available single-cell RNA-seq data from peripheral blood and lung samples of COVID-19 patients with varying degrees of severity. Patients with severe disease showed increased numbers of M1 macrophages in lung tissue, while the number of M2 macrophages was depleted. Cellular profiling of the peripheral blood showed a marked increase of CD14 +, CD16 + monocytes and a concomitant depletion of overall B cells and CD4 +, CD8 + T cells in severe patients when compared with moderate patients. Our analysis indicates the presence of faulty innate-to-adaptive switching, marked by a prolonged innate immune response and a dysregulated adaptive immune response in severe COVID-19 patients. Furthermore, we identified cell types with a transcriptome signature that can be used as a prognostic biomarker for disease state prediction and the effective therapeutic management of COVID-19 patients. Graphical abstract: Differential cellular landscape based on disease severity observed in COVID-19 patients. Healthy controls had high numbers of B-cells and T-cells. Moderate COVID-19 patients also had high numbers of some T-cell and B-cell subsets, with a slight increase in monocytes. Severe and deceased patients had significantly fewer T-cells and B-cells and had an abundant presence of inflammatory monocytes and macrophages in their blood and lung, respectively. Thus, innate-to-adaptive switching may be key in determining COVID-19 outcomes, and the lymphoid-to-myeloid cell ratio can be an early biomarker for predicting outcomes and designing effective therapeutic regimens. Image 1 Highlights: Severe cases had fewer B and T cells in blood than controls and moderate cases. The immune landscape in the lung of severe cases had increased M1 macrophages. Severe and fatal cases had impaired surfactant function of airway secretory cells. Severe and fatal cases had aberrant switching between innate and adaptive response.