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1.
Cells ; 11(12)2022 06 20.
Article in English | MEDLINE | ID: covidwho-1963751

ABSTRACT

Current research proves that immune dysregulation is a common feature of coronavirus disease 2019 (COVID-19), and immune exhaustion is associated with increased disease mortality. Immune checkpoint molecules, including the programmed cell death-1 (PD-1)/PD-1 ligand (PD-L1) axis, may serve as markers of disease severity. Accordingly, in this study, we evaluated the expression of PD-1/PD-L1 in patients with COVID-19. Blood immunophenotypes of hospitalized patients with moderate (n = 17, requiring oxygen support) and severe (n = 35, requiring mechanical ventilation in the intensive care setting) COVID-19 were compared and associated with clinical, laboratory, and survival data. The associations between severity and lymphocyte profiles were analysed at baseline and after 7 and 14 days of in-hospital treatment. Forty patients without COVID-19 infection were used as controls. For PD-1-positive T and B lymphocyte subsets, notable increases were observed between controls and patients with moderate or severe COVID-19 for CD4+PD-1+ T cells, CD8+PD-1+ T and CD19+PD-1+ B cells. Similar trends were observed for PD-L1-positive lymphocytes, namely, CD4+PD-L1+ T cells, CD8+PD-L1+ T cells and CD19+PD-L1+ B cells. Importantly, all markers associated with PD-1 and PD-L1 were stable over time for the analysed time points in the moderate and severe COVID-19 groups. Increased abundances of PD-1+ and PD-L1+ lymphocytes were associated with disease severity and mortality and were stable over time in patients with moderate to severe COVID-19. These immune exhaustion parameters may be attractive biomarkers of COVID-19 severity.


Subject(s)
B7-H1 Antigen , COVID-19 , Antigens, CD19 , Apoptosis , B7-H1 Antigen/genetics , Humans , Ligands , Prognosis , Programmed Cell Death 1 Receptor/metabolism
2.
Cells ; 11(12):1978, 2022.
Article in English | MDPI | ID: covidwho-1894141

ABSTRACT

Current research proves that immune dysregulation is a common feature of coronavirus disease 2019 (COVID-19), and immune exhaustion is associated with increased disease mortality. Immune checkpoint molecules, including the programmed cell death-1 (PD-1)/PD-1 ligand (PD-L1) axis, may serve as markers of disease severity. Accordingly, in this study, we evaluated the expression of PD-1/PD-L1 in patients with COVID-19. Blood immunophenotypes of hospitalized patients with moderate (n = 17, requiring oxygen support) and severe (n = 35, requiring mechanical ventilation in the intensive care setting) COVID-19 were compared and associated with clinical, laboratory, and survival data. The associations between severity and lymphocyte profiles were analysed at baseline and after 7 and 14 days of in-hospital treatment. Forty patients without COVID-19 infection were used as controls. For PD-1-positive T and B lymphocyte subsets, notable increases were observed between controls and patients with moderate or severe COVID-19 for CD4+PD-1+ T cells, CD8+PD-1+ T and CD19+PD-1+ B cells. Similar trends were observed for PD-L1-positive lymphocytes, namely, CD4+PD-L1+ T cells, CD8+PD-L1+ T cells and CD19+PD-L1+ B cells. Importantly, all markers associated with PD-1 and PD-L1 were stable over time for the analysed time points in the moderate and severe COVID-19 groups. Increased abundances of PD-1+ and PD-L1+ lymphocytes were associated with disease severity and mortality and were stable over time in patients with moderate to severe COVID-19. These immune exhaustion parameters may be attractive biomarkers of COVID-19 severity.

3.
Int J Mol Sci ; 23(9)2022 Apr 20.
Article in English | MEDLINE | ID: covidwho-1792658

ABSTRACT

In the beginning of the third year of the fight against COVID-19, the virus remains at least still one step ahead in the pandemic "war". The key reasons are evolving lineages and mutations, resulting in an increase of transmissibility and ability to evade immune system. However, from the immunologic point of view, the cytokine storm (CS) remains a poorly understood and difficult to combat culprit of the extended number of in-hospital admissions and deaths. It is not fully clear whether the cytokine release is a harmful result of suppression of the immune system or a positive reaction necessary to clear the virus. To develop methods of appropriate treatment and therefore decrease the mortality of the so-called COVID-19-CS, we need to look deeply inside its pathogenesis, which is the purpose of this review.


Subject(s)
COVID-19 , Cytokine Release Syndrome , Cytokines , Humans , Pandemics , SARS-CoV-2
4.
Cells ; 10(7)2021 07 19.
Article in English | MEDLINE | ID: covidwho-1323130

ABSTRACT

Since the end of 2019, a new, dangerous virus has caused the deaths of more than 3 million people. Efforts to fight the disease remain multifaceted and include prophylactic strategies (vaccines), the development of antiviral drugs targeting replication, and the mitigation of the damage associated with exacerbated immune responses (e.g., interleukin-6-receptor inhibitors). However, numerous uncertainties remain, making it difficult to lower the mortality rate, especially among critically ill patients. While looking for a new means of understanding the pathomechanisms of the disease, we asked a question-is our immunity key to resolving these uncertainties? In this review, we attempt to answer this question, and summarize, interpret, and discuss the available knowledge concerning the interplay between neutrophils, neutrophil extracellular traps (NETs), and T-cells in COVID-19. These are considered to be the first line of defense against pathogens and, thus, we chose to emphasize their role in SARS-CoV-2 infection. Although immunologic alterations are the subject of constant research, they are poorly understood and often underestimated. This review provides background information for the expansion of research on the novel, immunity-oriented approach to diagnostic and treatment possibilities.


Subject(s)
COVID-19/immunology , Extracellular Traps/immunology , Neutrophils/immunology , SARS-CoV-2/immunology , T-Lymphocytes/immunology , Animals , COVID-19/diagnosis , COVID-19/pathology , COVID-19/therapy , Humans , Immunity, Innate , Neutrophils/pathology , T-Lymphocytes/pathology
5.
Viruses ; 13(7)2021 07 02.
Article in English | MEDLINE | ID: covidwho-1295939

ABSTRACT

The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) evolved into a worldwide outbreak, with the first Polish cases in February/March 2020. This study aimed to investigate the molecular epidemiology of the circulating virus lineages between March 2020 and February 2021. We performed variant identification, spike mutation pattern analysis, and phylogenetic and evolutionary analyses for 1106 high-coverage whole-genome sequences, implementing maximum likelihood, multiple continuous-time Markov chain, and Bayesian birth-death skyline models. For time trends, logistic regression was used. In the dataset, virus B.1.221 lineage was predominant (15.37%), followed by B.1.258 (15.01%) and B.1.1.29 (11.48%) strains. Three clades were identified, being responsible for 74.41% of infections over the analyzed period. Expansion in variant diversity was observed since September 2020 with increasing frequency of the number in spike substitutions, mainly H69V70 deletion, P681H, N439K, and S98F. In population dynamics inferences, three periods with exponential increase in infection were observed, beginning in March, July, and September 2020, respectively, and were driven by different virus clades. Additionally, a notable increase in infections caused by the B.1.1.7 lineage since February 2021 was noted. Over time, the virus accumulated mutations related to optimized transmissibility; therefore, faster dissemination is reflected by the second wave of epidemics in Poland.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , SARS-CoV-2/classification , SARS-CoV-2/genetics , Bayes Theorem , Evolution, Molecular , Genetic Variation , Genome, Viral , Humans , Molecular Epidemiology , Mutation , Phylogeny , Poland/epidemiology , Prevalence , Whole Genome Sequencing
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