This study is a successor of our previous work concerning changes in the chemokine profile in infection that are associated with different SARS-CoV-2 genetic variants. The goal of our study was to take into account both the virus and the host immune system by assessing concentrations of cytokines in patients infected with different SARS-CoV-2 variants (ancestral Wuhan strain, Alpha, Delta and Omicron). Our study was performed on 340 biological samples taken from COVID-19 patients and healthy donors in the timespan between May 2020 and April 2022. We performed genotyping of the virus in nasopharyngeal swabs, which was followed by assessment of cytokines’ concentration in blood plasma. We noted that out of nearly 30 cytokines, only four showed stable elevation independently of the variant (IL-6, IL-10, IL-18 and IL-27), and we believe them to be ‘constant’ markers for COVID-19 infection. Cytokines that were studied as potential biomarkers lose their diagnostic value as the virus evolves, and the specter of potential targets for predictive models is narrowing. So far, only four cytokines (IL-6, IL-10, IL-18, and IL-27) showed a consistent rise in concentrations independently of the genetic variant of the virus. Although we believe our findings to be of scientific interest, we still consider them inconclusive; further investigation and comparison of immune responses to different variants of SARS-CoV-2 is required.

Background. The adaptive antiviral immune response requires interaction between CD8+ T cells, dendritic cells, and Th1 cells for controlling SARS-CoV-2 infection, but the data regarding the role of CD8+ T cells in the acute phase of COVID-19 and post-COVID-19 syndrome are still limited. Methods.. Peripheral blood samples collected from patients with acute COVID-19 (n = 71), convalescent subjects bearing serum SARS-CoV-2 N-protein-specific IgG antibodies (n = 51), and healthy volunteers with no detectable antibodies to any SARS-CoV-2 proteins (HC, n = 46) were analyzed using 10-color flow cytometry. Results. Patients with acute COVID-19 vs. HC and COVID-19 convalescents showed decreased absolute numbers of CD8+ T cells, whereas the frequency of CM and TEMRA CD8+ T cells in acute COVID-19 vs. HC was elevated. COVID-19 convalescents vs. HC had increased naïve and CM cells, whereas TEMRA cells were decreased compared to HC. Cell-surface CD57 was highly expressed by the majority of CD8+ T cells subsets during acute COVID-19, but convalescents had increased CD57 on ‘naïve’, CM, EM4, and pE1 2–3 months post-symptom onset. CXCR5 expression was altered in acute and convalescent COVID-19 subjects, whereas the frequencies of CXCR3+ and CCR4+ cells were decreased in both patient groups vs. HC. COVID-19 convalescents had increased CCR6-expressing CD8+ T cells. Moreover, CXCR3+CCR6- Tc1 cells were decreased in patients with acute COVID-19 and COVID-19 convalescents, whereas Tc2 and Tc17 levels were increased compared to HC. Finally, IL-27 negatively correlated with the CCR6+ cells in acute COVID-19 patients. Conclusions. We described an abnormal CD8+ T cell profile in COVID-19 convalescents, which resulted in lower frequencies of effector subsets (TEMRA and Tc1), higher senescent state (upregulated CD57 on ‘naïve’ and memory cells), and higher frequencies of CD8+ T cell subsets expressing lung tissue and mucosal tissue homing molecules (Tc2, Tc17, and Tc17.1). Thus, our data indicate that COVID-19 can impact the long-term CD8+ T cell immune response.

The chemokine receptor CXCR3 and its ligands (MIG/CXCL9, IP-10/CXCL10, and I-TAC/CXCL11) play a central role in the generation of cellular inflammation, both in the protective responses to invading pathogens, and in different pathological conditions associated with autoimmunity. It is worth noting that CXCR3 is highly expressed on innate and adaptive lymphocytes, as well as on various cell subsets that are localized in non-immune organs and tissues. Our review focuses exclusively on CXCR3-expressing T cells, including Th1, Th17.1, Tfh17, Tfh17.1, CXCR3+ Treg cells, and Tc1 CD8+ T cells. Currently, numerous studies have highlighted the role of CXCR3-dependent interactions in the coordination of inflammation in the peripheral tissues, both to increase recruitment of CD4+ and CD8+ T cells that upregulate inflammation, and also for recruitment of CXCR3+ T regulatory cells to dampen overexuberant responses. Understanding the role of CXCR3 and its ligands might help to apply them as new and effective therapeutic targets in a wide range of diseases.

IgG is the most prominent marker of post-COVID-19 immunity. Not only does this subtype mark the late stages of infection, but it also stays in the body for a timespan of at least 6 months. However, different IgG subclasses have different properties, and their roles in specific anti-COVID-19 responses have yet to be determined. We assessed the concentrations of IgG1, IgG2, IgG3, and IgG4 against different SARS-CoV-2 antigens (N protein, S protein RBD) using a specifically designed method and samples from 348 COVID-19 patients. We noted a statistically significant association between severity of COVID-19 infection and IgG concentrations (both total and subclasses). When assessing anti-N protein and anti-RBD IgG subclasses, we noted the importance of IgG3 as a subclass. Since it is often associated with early antiviral response, we presumed that the IgG3 subclass is the first high-affinity IgG antibody to be produced during COVID-19 infection.

Background. Infection caused by SARS-CoV-2 mostly affects the upper and lower respiratory tracts and causes symptoms ranging from the common cold to pneumonia with acute respiratory distress syndrome. Chemokines are deeply involved in the chemoattraction, proliferation, and activation of immune cells within inflammation. It is crucial to consider that mutations within the virion can potentially affect the clinical course of SARS-CoV-2 infection because disease severity and manifestation vary depending on the genetic variant. Our objective was to measure and assess the different concentrations of chemokines involved in COVID-19 caused by different variants of the virus. Methods. We used the blood plasma of patients infected with different variants of SARS-CoV-2, i.e., the ancestral Wuhan strain and the Alpha, Delta, and Omicron variants. We measured the concentrations of 11 chemokines in the samples: CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROα, CXCL8/IL-8, CXCL9/MIG, CXCL10/IP-10, and CX3CL1/Fractalkine. Results. We noted a statistically significant elevation in the concentrations of CCL2/MCP-1, CXCL8/IL-8, and CXCL1/IP-10 independently of the variant, and a drop in the CCL22/MDC concentrations. Conclusions. The chemokine concentrations varied significantly depending on the viral variant, leading us to infer that mutations in viral proteins play a role in the cellular and molecular mechanisms of immune responses.

Background. Humoral immunity requires interaction between B cell and T follicular helper cells (Tfh) to produce effective immune response, but the data regarding a role of B cells and Tfh in SARS-CoV-2 defense are still sparse. Methods. Blood samples from patients with acute COVID-19 (n = 64), convalescents patients who had specific IgG to SARS-CoV-2 N-protein (n = 55), and healthy donors with no detectable antibodies to any SARS-CoV-2 proteins (HC, n = 44) were analyses by multicolor flow cytometry. Results. Patients with acute COVID-19 showed decreased levels of memory B cells subsets and increased proportion plasma cell precursors compared to HC and COVID-19 convalescent patients, whereas for the latter the elevated numbers of virgin naïve, Bm2′ and “Bm3+Bm4” was found if compared with HC. During acute COVID-19 CXCR3+CCR6− Tfh1-like cells were decreased and the levels of CXCR3−CCR6+ Tfh17-like were increased then in HC and convalescent patients. Finally, COVID-19 convalescent patients had increased levels of Tfh2-, Tfh17- and DP Tfh-like cells while comparing their amount with HC. Conclusions. Our data indicate that COVID-19 can impact the humoral immunity in the long-term.