Dissecting the common and compartment-specific features of COVID-19 severity in the lung and periphery with single-cell resolution

biorxiv(2020)

引用 6|浏览2
暂无评分
摘要
As the global COVID-19 pandemic continues to escalate, no effective treatment has yet been developed for the severe respiratory complications of this disease. This may be due in large part to the unclear immunopathological basis for the development of immune dysregulation and acute respiratory distress syndrome (ARDS) in severe and critical patients. Specifically, it remains unknown whether the immunological features of the disease that have been identified so far are compartment-specific responses or general features of COVID-19. Additionally, readily detectable biological markers correlated with strata of disease severity that could be used to triage patients and inform treatment options have not yet been identified. Here, we leveraged publicly available single-cell RNA sequencing data to elucidate the common and compartment-specific immunological features of clinically severe COVID-19. We identified a number of transcriptional programs that are altered across the spectrum of disease severity, few of which are common between the lung and peripheral immune environments. In the lung, comparing severe and moderate patients revealed severity-specific responses of enhanced interferon, A20/I魏B, IL-2, and IL-6 pathway signatures along with broad signaling activity of IFNG, SPP1, CCL3, CCL8, and IL18 across cell types. These signatures contrasted with features unique to ARDS observed in the blood compartment, which included depletion of interferon and A20/I魏B signatures and a lack of IL-6 response. The cell surface marker S1PR1 was strongly upregulated in patients diagnosed with ARDS compared to non-ARDS patients in 纬未 T cells of the blood compartment, and we nominate S1PR1 as a potential marker for immunophenotyping ARDS in COVID-19 patients using flow cytometry.
更多
查看译文
关键词
COVID-19,SARS-CoV-2,single-cell RNA sequencing,re-analysis,BALF,PBMC,cell surface marker,immunophenotyping
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要