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Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients

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...

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Autores principales: Deng, Xiangyu, Zhang, Yao, Li, Meiqi, Tang, Xiaolong, Shen, Jing, Chen, Yu, Zhao, Yueshui, Wen, Qinglian, Wu, Xu, Li, Mingxing, Li, Jing, Xu, Wenping, Li, Wanping, Xiao, Zhangang, Xian, Deqiang, Du, Fukuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066099/
https://www.ncbi.nlm.nih.gov/pubmed/35541915
http://dx.doi.org/10.7150/ijbs.71163
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author Deng, Xiangyu
Zhang, Yao
Li, Meiqi
Tang, Xiaolong
Shen, Jing
Chen, Yu
Zhao, Yueshui
Wen, Qinglian
Wu, Xu
Li, Mingxing
Li, Jing
Xu, Wenping
Li, Wanping
Xiao, Zhangang
Xian, Deqiang
Du, Fukuan
author_facet Deng, Xiangyu
Zhang, Yao
Li, Meiqi
Tang, Xiaolong
Shen, Jing
Chen, Yu
Zhao, Yueshui
Wen, Qinglian
Wu, Xu
Li, Mingxing
Li, Jing
Xu, Wenping
Li, Wanping
Xiao, Zhangang
Xian, Deqiang
Du, Fukuan
author_sort Deng, Xiangyu
collection PubMed
description 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.
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spelling pubmed-90660992022-05-09 Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients Deng, Xiangyu Zhang, Yao Li, Meiqi Tang, Xiaolong Shen, Jing Chen, Yu Zhao, Yueshui Wen, Qinglian Wu, Xu Li, Mingxing Li, Jing Xu, Wenping Li, Wanping Xiao, Zhangang Xian, Deqiang Du, Fukuan Int J Biol Sci Research Paper 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. Ivyspring International Publisher 2022-04-24 /pmc/articles/PMC9066099/ /pubmed/35541915 http://dx.doi.org/10.7150/ijbs.71163 Text en © The author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Deng, Xiangyu
Zhang, Yao
Li, Meiqi
Tang, Xiaolong
Shen, Jing
Chen, Yu
Zhao, Yueshui
Wen, Qinglian
Wu, Xu
Li, Mingxing
Li, Jing
Xu, Wenping
Li, Wanping
Xiao, Zhangang
Xian, Deqiang
Du, Fukuan
Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients
title Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients
title_full Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients
title_fullStr Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients
title_full_unstemmed Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients
title_short Dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in COVID-19 infected patients
title_sort dynamic response landscape of immune cells identified immune dysfunction which predicts disease progression in covid-19 infected patients
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066099/
https://www.ncbi.nlm.nih.gov/pubmed/35541915
http://dx.doi.org/10.7150/ijbs.71163
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