Dynamic Changes of Lymphocyte Subsets in the Course of COVID-19
- 1 February 2021
- journal article
- research article
- Published by S. Karger AG in International Archives of Allergy and Immunology
- Vol. 182 (3), 254-262
- https://doi.org/10.1159/000514202
Abstract
Background: Although the pathophysiology of coronavirus disease 2019 (COVID-19) is not clearly defined, among the proposed mechanisms, immune system dysfunction is more likely than others. The aim of this study was to clarify the characteristics and clinical significance of dynamic changes of lymphocyte subsets in the course of COVID-19. Methods: In this prospective study, the levels of peripheral lymphocyte subsets including CD4(+), CD8(+), CD4(+)CD25(+)FOXP3(+), CD38(+), CD3(+)HLA-DR+, CD19(+), CD20(+), and CD16(+)CD56(+) cells were measured by flow cytometry in 52 confirmed hospitalized patients with COVID-19 at the day of admission and after 7 days of care. Clinical response was defined as improvement in symptoms (fever, dyspnea, and cough as well as blood oxygen saturation), and patients who met these criteria after 1 week of admission were classified as early responders; others who survived and finally discharged from the hospital were classified as late responders and patients who died were categorized as nonresponders. Immunophenotyping of studied cell changes on the first day of admission and 7 days after treatment were compared. Besides, the correlation between cellular subset variation and clinical response and outcome were analyzed. Results: Total counts of white blood cell, T cells, CD4(+) T cells, CD8(+) T cells, CD38(+) lymphocytes, and CD3(+)HLA-DR+ lymphocytes were significantly increased in both early and late responders. No statistically significant difference was observed in CD4(+)/CD8(+) ratio, B cells, FOXP3(+)T(reg) lymphocytes, and FOXP3 median fluorescence intensity among studied groups. According to the multivariate analysis, an increase in CD4(+) T cells (p = 0.019), CD8(+) T cells (p = 0.001), and administration of interferon (p < 0.001) were independent predictors of clinical response. Conclusion: We found an increasing trend in total T cells, T helpers, cytotoxic T cells, activated lymphocytes, and natural killer cells among responders. This trend was not statistically significant among nonresponders. The findings of this study may enhance our knowledge about the pathogenesis of COVID-19.This publication has 48 references indexed in Scilit:
- Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, ChinaJAMA, 2020
- Clinical features of patients infected with 2019 novel coronavirus in Wuhan, ChinaThe Lancet, 2020
- A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family clusterThe Lancet, 2020
- CRISPR-Cas14 is now part of the artillery for gene editing and molecular diagnosticNanomedicine: Nanotechnology, Biology and Medicine, 2019
- MERS-CoV infection in humans is associated with a pro-inflammatory Th1 and Th17 cytokine profileCytokine, 2018
- Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathologySeminars in Immunopathology, 2017
- T Cell Responses to Whole SARS Coronavirus in HumansThe Journal of Immunology, 2008
- Regulatory T Cells and Immune ToleranceCell, 2008
- Plasma inflammatory cytokines and chemokines in severe acute respiratory syndromeClinical and Experimental Immunology, 2004
- Haematological Effects of Interferon-??-1a (Rebif??) Therapy in Multiple SclerosisDrug Safety, 2004