Identification of Monocytes Associated with Severe COVID-19 in the PBMCs of Severely Infected Patients Through Single-Cell Transcriptome Sequencing.

Abstract

Understanding the immunological characteristics of monocytes-including the characteristics associated with fibrosis-in severe coronavirus disease 2019 (COVID-19) is crucial for understanding the pathogenic mechanism of the disease and preventing disease severity. In this study, we performed single-cell transcriptomic sequencing of peripheral blood samples collected from six healthy controls and 14 COVID-19 samples including severe, moderate, and convalescent samples from three severely/critically ill and four moderately ill patients. We found that the monocytes were strongly remodeled in the severely/critically ill patients with COVID-19, with an increased proportion of monocytes and seriously reduced diversity. In addition, we discovered two novel severe-disease-specific monocyte subsets: Mono 0 and Mono 5. These subsets expressed amphiregulin (AREG), epiregulin (EREG), and cytokine interleukin-18 (IL-18) gene, exhibited an enriched erythroblastic leukemia viral oncogene homolog (ErbB) signaling pathway, and appeared to exhibit pro-fibrogenic and pro-inflammation characteristics. We also found metabolic changes in Mono 0 and Mono 5, including increased glycolysis/gluconeogenesis and an increased hypoxia inducible factor-1 (HIF-1) signaling pathway. Notably, one pre-severe sample displayed a monocyte atlas similar to that of the severe/critical samples. In conclusion, our study discovered two novel severe-disease-specific monocyte subsets as potential predictors and therapeutic targets for severe COVID-19. Overall, this study provides potential predictors for severe disease and therapeutic targets for COVID-19 and thus provides a resource for further studies on COVID-19.

• Authors: Yan Zhang, Shuting Wang, He Xia, Jing Guo, Kangxin He, Chenjie Huang, Rui Luo, Yanfei Chen, Kaijin Xu, Hainv Gao, Jifang Sheng, Lanjuan Li
• Journal: Engineering (Beijing, China) (Engineering (Beijing)) Vol. 17 Pg. 161-169 (Oct 2022) ISSN: 2095-8099 [Print] China
• PMID: 34150352 (Publication Type: Journal Article)
• Copyright: © 2021 THE AUTHORS.