Dynamic Changes Of T-Iymphocyte Subsets And The Correlations With 89 Patients With Coronavirus Disease 2019 (Covid-19)

Annals of Translational Medicine(2020)

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Abstract
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.
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Key words
Coronavirus disease 2019 (COVID-19),CD3,CD4,CD8
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