Background: The immunological background responsible for the severe course of COVID-19 and the immune factors that protect against SARS-CoV-2 infection are still unclear. The aim of this study was to investigate immune system status in persons with high exposure to SARS-CoV-2 infection.
Methods: Seventy-one persons employed in the observation and infectious diseases unit were qualified for the study between November 2020 and October 2021. Symptomatic COVID-19 was diagnosed in 35 persons. Anti-SARS-CoV-2 antibodies were also found in 8 persons. Peripheral blood mononuclear cells subpopulations were analyzed by flow cytometry, and the concentrations of cytokines and anti-SARS-CoV-2 antibodies were determined by ELISA.
Results: The percentages of cytotoxic T lymphocytes (CTLs), CD28 and T helper (Th) cells with invariant T-cell receptors were significantly higher in persons with symptomatic COVID-19 than in those who did not develop COVID-19' symptoms. Conversely, symptomatic COVID-19 persons had significantly lower percentages of: a) CTLs in the late stage of activation (CD8/CD95), b) NK cells, c) regulatory-like Th cells (CD4/CTLA-4), and d) Th17-like cells (CD4/CD161) compared to asymptomatic COVID-19' persons. Additionally, persons with anti-SARS-CoV-2 antibodies had a significantly higher lymphocyte count and IL-6 concentration than persons without these antibodies.
Conclusion: Numerous lymphocyte populations are permanently altered by SARS-CoV-2 infection. High percentages of both populations: NK cells-as a part of the non-specific response, and T helper cells' as those regulating the immune response, could protect against the acute COVID-19 symptoms development. Understanding the immune background of COVID-19 may improve the prevention of this disease by identifying people at risk of a severe course of infection.
Trial Registration: This is a retrospective observational study without a trial registration number.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11348584 | PMC |
http://dx.doi.org/10.1186/s12879-024-09772-5 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!