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.

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.

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.

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.

Background/Objectives: While ART effectively suppresses HIV viremia, many PLWH exhibit persistent immune dysfunction. This study aimed to assess immune recovery and immune exhaustion (PD-1/PD-L1 expression) in newly diagnosed versus long-term ART-treated individuals. Methods: We analyzed 79 PLWH: 52 newly diagnosed individuals (12-month follow-up) and 27 long-term-treated patients (Ukrainian refugees). Flow cytometry was used to evaluate CD4+ and CD8+ counts, the CD4+/CD8+ ratio, and PD-1/PD-L1 expression on CD3+, CD4+, and CD19+ lymphocytes. ART regimen and HIV subtype were included as covariates in linear regression models. Results: At 12 months, CD4+ counts were similar between groups (median 596.5 vs. 621 cells/μL, p = 0.22), but newly diagnosed patients had higher CD8+ counts (872 vs. 620 cells/μL, p = 0.028) and a lower CD4+/CD8+ ratio (0.57 vs. 1.05, p = 0.0027). Immune exhaustion markers were significantly elevated in newly diagnosed individuals: CD4+ PD-1+ T cells (24.4% vs. 3.85%, p = 0.0002) and CD3+ PD-1+ T cells (27.3% vs. 12.35%, p < 0.0001). Linear regression confirmed group membership independently predicted higher CD3+ (β = +21.92, p < 0.001), CD4+ (β = +28.87, p < 0.0001), and CD19+ (β = +8.73, p = 0.002) percentages. Lipid parameters and SCORE2 did not differ significantly. Conclusions: Despite virologic suppression and CD4+ recovery, immune exhaustion markers remain elevated in newly diagnosed PLWH, suggesting incomplete immune normalization. Traditional parameters (CD4+ count and CD4+/CD8+ ratio) may not fully capture immune status, warranting broader immunologic profiling in HIV care.

Introduction: The progressive immunological impairment associated with human immunodeficiency virus (HIV) infection is partially mediated by the programmed cell death protein‐1 (PD‐1)/programed death‐ligand 1(PD‐L1) inhibitory pathway. This investigation aims to evaluate the influence of PD‐1 on immune reconstitution in patients undergoing antiretroviral therapy (ART), with data visualized through principal component analysis (PCA). Materials and Methods: Data from 52 ART‐treated individuals achieving viral suppression were analyzed over 12 months. CD4+, CD8+, CD19+, and PD‐1/PD‐L1 expressions were quantified via flow cytometry at baseline and after 12 months, and immune recovery was assessed at CD4+ thresholds of 500 and 800/μL and CD4+/CD8+ ratios of >0.8 and >1.0 using linear and logistic regression. PCA was applied to visualize clustering of immune recovery patterns based on PD‐1/PD‐L1 expression levels and immune cell counts, with statistical significance evaluated using ANOVA. Results: The analyzed group of 52 patients was predominantly male (65.4%; n = 34). PD‐1/PD‐L1 expression showed modest associations with immune recovery. Higher PD‐L1 expression on CD3+ T‐cells at baseline was associated with a reduced likelihood of recovery to CD4+>500/μL (OR: 0.79; 95%CI: 0.62–0.99; p = 0.04). Linear regression demonstrated that increased PD‐L1 on CD4+ T‐cells and PD‐1 on CD19+ B‐cells positively correlated with higher CD4+/CD8+ ratios at follow‐up (coefficient: 0.035 and 0.03, respectively; p < 0.02), while logistic regression indicated that higher PD‐1 on CD3+ T‐cells increased the odds of recovery to CD4+>500/μL (OR: 1.03; 95% CI: 1.0036–1.07); = 0.03). Notably, this weak signal may result from a general increase in the number of lymphocytes during therapy. PCA did not reveal significant clustering of immune recovery patterns. Conclusion: PD‐1 and PD‐L1 expressions on immune cells are weakly associated with immune recovery metrics in individuals undergoing ART. Further research is needed to explore their role in immune reconstitution and potential clinical applications.