Cargando…

Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19)

BACKGROUND: In December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan City, Hubei Province, China. The coronavirus has spread throughout the world, posing a severe threat to human health. By...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Mingxiang, Wang, Yao, Ye, Jing, Da, Hongqiang, Fang, Sufang, Chen, Lizhou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576080/
https://www.ncbi.nlm.nih.gov/pubmed/33240994
http://dx.doi.org/10.21037/atm-20-5479
_version_ 1783597942718857216
author Huang, Mingxiang
Wang, Yao
Ye, Jing
Da, Hongqiang
Fang, Sufang
Chen, Lizhou
author_facet Huang, Mingxiang
Wang, Yao
Ye, Jing
Da, Hongqiang
Fang, Sufang
Chen, Lizhou
author_sort Huang, Mingxiang
collection PubMed
description BACKGROUND: In December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan City, Hubei Province, China. The coronavirus has spread throughout the world, posing a severe threat to human health. By using flow cytometry, here we observed the dynamic changes of peripheral blood T lymphocyte subsets in COVID-19 patients, with an attempt to explore their roles in the pathogenesis of COVID-19 and their impacts on prognosis. METHODS: Eighty-nine COVID-19 patients were divided into a moderate group (n=70) and the severe/critical group (n=19) according to the disease severity. Furthermore, the severe/critical patients were divided into the improved group (n=14) and unimproved group (n=5) according to the outcomes. The absolute peripheral blood lymphocytes counts and subsets, including CD45+, CD3+, CD4+, and CD8+, in the acute phase, and flow cytometry measured the recovery phase for all patients. Then, the results were compared with those in the normal control group. RESULTS: The absolute counts of lymphocytes, T lymphocytes, and their subsets decreased during the acute phase in COVID-19 patients, especially in the severe/critical group. The T-lymphocyte count reached the lowest point on the 14th day in the severe/critical group. It rose with fluctuations to the normal level in the improved group as the immune function recovered; in the unimproved group, however, the T-lymphocyte count remained at a low level or even continued to decrease. The percentages of CD4+ and CD8+ T lymphocytes showed no visible change in the improved group; however, the percentage of CD8+ T cells dropped in the unimproved group, resulting in higher CD4+/CD8+ ratio. CONCLUSIONS: T lymphocytes count, and their subsets can be used for monitoring the immune functions and predicting the prognosis of COVID-19 patients.
format Online
Article
Text
id pubmed-7576080
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher AME Publishing Company
record_format MEDLINE/PubMed
spelling pubmed-75760802020-11-24 Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19) Huang, Mingxiang Wang, Yao Ye, Jing Da, Hongqiang Fang, Sufang Chen, Lizhou Ann Transl Med Original Article BACKGROUND: In December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan City, Hubei Province, China. The coronavirus has spread throughout the world, posing a severe threat to human health. By using flow cytometry, here we observed the dynamic changes of peripheral blood T lymphocyte subsets in COVID-19 patients, with an attempt to explore their roles in the pathogenesis of COVID-19 and their impacts on prognosis. METHODS: Eighty-nine COVID-19 patients were divided into a moderate group (n=70) and the severe/critical group (n=19) according to the disease severity. Furthermore, the severe/critical patients were divided into the improved group (n=14) and unimproved group (n=5) according to the outcomes. The absolute peripheral blood lymphocytes counts and subsets, including CD45+, CD3+, CD4+, and CD8+, in the acute phase, and flow cytometry measured the recovery phase for all patients. Then, the results were compared with those in the normal control group. RESULTS: The absolute counts of lymphocytes, T lymphocytes, and their subsets decreased during the acute phase in COVID-19 patients, especially in the severe/critical group. The T-lymphocyte count reached the lowest point on the 14th day in the severe/critical group. It rose with fluctuations to the normal level in the improved group as the immune function recovered; in the unimproved group, however, the T-lymphocyte count remained at a low level or even continued to decrease. The percentages of CD4+ and CD8+ T lymphocytes showed no visible change in the improved group; however, the percentage of CD8+ T cells dropped in the unimproved group, resulting in higher CD4+/CD8+ ratio. CONCLUSIONS: T lymphocytes count, and their subsets can be used for monitoring the immune functions and predicting the prognosis of COVID-19 patients. AME Publishing Company 2020-09 /pmc/articles/PMC7576080/ /pubmed/33240994 http://dx.doi.org/10.21037/atm-20-5479 Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Huang, Mingxiang
Wang, Yao
Ye, Jing
Da, Hongqiang
Fang, Sufang
Chen, Lizhou
Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19)
title Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19)
title_full Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19)
title_fullStr Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19)
title_full_unstemmed Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19)
title_short Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19)
title_sort dynamic changes of t-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (covid-19)
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576080/
https://www.ncbi.nlm.nih.gov/pubmed/33240994
http://dx.doi.org/10.21037/atm-20-5479
work_keys_str_mv AT huangmingxiang dynamicchangesoftlymphocytesubsetsandthecorrelationswith89patientswithcoronavirusdisease2019covid19
AT wangyao dynamicchangesoftlymphocytesubsetsandthecorrelationswith89patientswithcoronavirusdisease2019covid19
AT yejing dynamicchangesoftlymphocytesubsetsandthecorrelationswith89patientswithcoronavirusdisease2019covid19
AT dahongqiang dynamicchangesoftlymphocytesubsetsandthecorrelationswith89patientswithcoronavirusdisease2019covid19
AT fangsufang dynamicchangesoftlymphocytesubsetsandthecorrelationswith89patientswithcoronavirusdisease2019covid19
AT chenlizhou dynamicchangesoftlymphocytesubsetsandthecorrelationswith89patientswithcoronavirusdisease2019covid19