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Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients
Authors:Xiangyu Deng  Yao Zhang  Meiqi Li  Xiaolong Tang  Jing Shen  Yu Chen  Yueshui Zhao  Qinglian Wen  Xu Wu  Mingxing Li  Jing Li  Wenping Xu  Wanping Li  Zhangang Xiao  Deqiang Xian  Fukuan Du
Abstract:During the development of COVID-19 caused by SARS-CoV-2 infection from mild disease to severe disease, it can trigger a series of complications and stimulate a strong cellular and humoral immune response. However, the precise identification of blood immune cell response dynamics and the relevance to disease progression in COVID-19 patients remains unclear. We propose for the first time to use changes in cell numbers to establish new subgroups, which were divided into four groups: first from high to low cell number (H_L_Group), first from low to high (L_H_Group), continuously high (H_Group), and continuously low (L_Group). It was found that in the course of disease development. In the T cell subgroup, the immune response is mainly concentrated in the H_L_Group cell type, and the complications are mainly in the L_H_Group cell type. In the NK cell subgroup, the moderate patients are mainly related to cellular immunity, and the severe patients are mainly caused by the disease, while severe patients are mainly related to complications caused by diseases. Our study provides a dynamic response of immune cells in human blood during SARS-CoV-2 infection and the first subgroup analysis using dynamic changes in cell numbers, providing a new reference for clinical treatment of COVID-19.
Keywords:SARS-CoV-2   COVID-19   T Cells   NK Cells   Single Cell RNA-seq
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