Rhinology
Published: 2022-11-23
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Delineation of T cell subsets in chronic rhinosinusitis with nasal polyps

Department of Clinical Pathology, South Egypt Cancer Institute, Assiut University, Assiut, Egypt
https://orcid.org/0000-0001-8471-6388
Department of Medical Microbiology & Immunology, Faculty of Medicine, Assiut University, Assiut, Egypt
https://orcid.org/0000-0001-8445-711X
Third year Medical student, Faculty of Medicine, Assiut University, Assiut, Egypt
Department of Otorhinolaryngology & Head and Neck Surgery, Faculty of Medicine, Assiut University, Assiut, Egypt
nasal polyps T cell chronic rhinosinusitis

Abstract

Objectives. Detailed characterisation of CD45RA+ and CD45RO+ T cell subsets in both CD4+ and CD8+ cells in blood and tissue of patients with chronic rhinosinusitis with nasal polyps (CRSwNP) is lacking. We aimed to investigate T cell differentiation levels in blood and tissue and correlate this with CT score and white blood cell count.
Methods. This case-control study was conducted on 21 patients with CRSwNP and 20 healthy controls. Lund-Mackay score was used for radiologic staging of chronic rhinosinusitis. T cell subsets were characterised in blood and nasal polyp tissue using CD4, CD8, CCR7, CD45RA, CD45RO, CD27, and CD95 monoclonal antibodies.
Results. Most variations in T cell subsets were detected in tissue rather than blood. A higher level of CD8+ TCM, CD4+ TSCMs and lower level of CD8+ TEM were detected in the blood of CRSwNP patients vs controls. In CRSwNP patients, substantial decrease of tissue CD8+ TNs, CD8+ TCMs, CD4+ TNs, and CD4+TSCMs with marked increase in the percentages of TEMs and TEMRAs were detected among CD4+ and CD8+ T cells compared with levels in blood.
Conclusions. The reduction of TNs, TSCMs, and TCMs and accumulation of TEMs and TEMRAs subsets that function as effector cells in sinonasal mucosa, especially CD8+ T cells, might indicate the role of immunomodulation of memory/effector T-cells in the pathogenesis of CRSwNP.

Introduction

Nasal polyps are believed to arise in the nasal mucosa because of chronic inflammation. Chronic rhinosinusitis with nasal polyps (CRSwNP) is mostly characterised by a moderate to severe T helper type 2 (Th2)-mediated inflammation with hypereosinophilia and increased IgE concentrations 1. CRSwNP is associated with higher colonisation rates with bacteria such as Staphylococcus aureus and fungi like Aspergillus fumigatus and Candida albicans 2. Upper airway colonisation with bacteria may be accompanied by biofilm formation and increasing inflammatory cells in tissue that contribute to nasal tissue damage leading to a recalcitrant disease 3.

Numerous studies have underlined the role of activated memory CD4+ T cells as the primary producer of Th2 cytokines in asthma and other atopic diseases. Th2 cytokines such as IL-4 and IL-13 contribute to many of the pathophysiological features of asthma, including airway inflammation, mucus secretion and airway hyper-responsiveness. The production of Th2 cytokines was initially ascribed to CD4+ T cells. In addition, several studies have provided evidence that CD8+ T cells are able to secrete Th2 cytokines and are essential for allergic inflammation and airway sensitivity 4.

The functional state of T cells is dependent on their degree of differentiation. When naive CD4+ and CD8+ T lymphocytes are challenged with a cognate antigen, they proliferate and differentiate, and acquire specialised migratory and effector capabilities 5. Expression of the lymph node–homing molecules L-selectin (CD62L) and chemokine receptor 7 (CCR7), the activation marker (CD27), and the RA/RO isoforms of the leukocyte common Ag (CD45) distinguishes memory T cells from naïve T cells (TNs) and classifies antigen-experienced T cells into at least four differentiation subsets: stem cell-like memory T cells (TSCMs), central memory T cells (TCMs), effector memory T cells (TEMs) and terminally differentiated effector T cells (TEMRAs) 6,7.

Naïve T cells, which have not yet encountered an antigen, express CD45RA, CCR7 and CD62L in addition to CD27 and preferentially migrate to secondary lymphoid organs like lymph nodes and spleen. After interaction with its ligand (CD70), CD27 delivers the costimulatory signals needed for expansion of primed T cells and differentiation to effector cells with a fast antigen recall response 8. TCMs lose CD45RA and gain expression of CD45RO during the transition from naive to memory T cells 9. Upon antigenic restimulation, TCMs down-regulate CCR7 and CD27 and differentiate into TEms 8,9 and lastly into TEMRAs, which are considered to be terminally differentiated. TEMRAs lack CCR7 and CD45RO but re-express CD45RA 10. TSCMs represent the least differentiated memory T cell subset and display a naïve-like phenotype (CD45RO-CD45RA+CCR7+) and can be distinguished from TNs by their distinctive expression of CD95 (Fas) 7.

Detailed characterisation of CD45RA+ and CD45RO+ T cell subsets among both CD4+ and CD8+ cells in blood and tissue of patients with CRSwNP is lacking. Hence, we aimed to delineate T cell differentiation level in blood and tissue and correlate it with CT score and white blood cell count.

Materials and methods

This case-control study was conducted on 21 patients with CRSwNP admitted to the Otorhinolaryngology Department, Faculty of Medicine, Assiut University. Twenty age and sex-matched healthy blood donors were enrolled as a control group.

Non-contrast computerised tomography scans were done for all patients, including coronal, axial and sagittal cuts (3 mm thickness) in bone and soft tissue window settings. Lund-Mackay’s radiologic scoring system was used to stage chronic rhinosinusitis 11. Each sinus was given a score of 0, 1, or 2 if it was totally patent, partially opacified, or completely opacified, respectively. The ostiomeatal complex (OMC) was allocated a score of 0 if not occluded or 2 if occluded. The maximum obtainable score for each side is 12, with a total combined score of 24. Lund Mackay scores of 4 or higher largely support a clinical diagnosis of chronic rhinosinusitis, whereas scores less than four are unspecified 12.

Flow cytometry

Two ml of peripheral blood were collected from each participant and polyp biopsy specimens were collected during endoscopic sinus surgery. The polyps were minced finely and passed through a cell strainer in phosphate-buffered saline (PBS) solution. The filtrate was centrifuged, then treated with red blood cell (RBC) lysis buffer and washed twice with PBS. Processed tissue and 100 μl of the whole blood sample were each incubated with 10 μl of fluoroisothiocyanate (FITC)-conjugated anti-CD27, phycoerythrin (PE)-conjugated anti-CD8, PE-cyanine 7 (PE-CY7)-conjugated anti-CD45RO, allophycocyanin (APC)-conjugated anti-CD45RA, APC-H7-conjugated anti-CD4, PerCP-Cy5.5-conjugated anti-CCR7 and V500-conjugated anti-CD95 for 15 minutes at 4°C in the dark. All monoclonal antibodies were purchased from Becton Dickinson (BD, CA, USA). RBCs lysis and washing with PBS were done. An isotype-matched negative control was used to detect background staining signals in each sample.

Data analysis was done by FACSCanto flow cytometer using FACS DIVA 7.0 software (BD, USA). Approximately 100,000 events were acquired for each sample. Lymphocytes were selected based on their light scatter properties. CD4+ and CD8+ T cells were then gated, and five distinct subsets were characterised in each of CD4+ and CD8+ T cells according to CD45RA and CD45RO expression, followed by gating based on CD27, CCR7, and CD95. These subsets include TNs; CD45ROCD45RA+CCR7+CD27+CD95, TSCMs; CD45ROCD45RA+CCR7+CD27+CD95+, TCMs; CD45RO+CD45RA-CCR7+, TEMs; CD45RO+CD45RA-CCR7 and TEMRAs; CD45ROCD45RA+CCR7CD27.

Statistical analysis

IBM Statistical Package for the Social Sciences, version 25 (IBM SPSS statistics, USA) was used for statistical analysis of data. Continuous variables were expressed as mean ± standard error (SE), whereas categorical data were presented as numbers (percentages). The Shapiro-Wilk test was employed to determine the normality of data distribution. Independent sample t-test and Mann-Whitney U test were used to compare variables among the different parametric or non-parametric groups, respectively. A Wilcoxon signed-rank test was performed to evaluate the differences in cell frequencies between biopsy and blood samples. Associations between variables were explored using Kendall’s tau and Spearman correlation coefficient. A p-value was considered significant when less than 0.05.

Results

Clinical and laboratory features of patients

As presented in Table I, the average age of patients with CRSwNP was 36.6 ± 4 years and 71% were males. The mean total leukocyte count (TLC) was 7.5 ± 0.5. The neutrophil mean percentage was 52 ± 2, while the eosinophil mean percentage was 3.7 ± 0.6. More than half of patients had a total CT score ≥ 19 and nearly 38% of patients scored 24 by CT.

Changes in CD8+ and CD4+ T cell subsets in CRSwNP patients

Changes in CD8+ and CD4+ T cell subsets in blood and polyp tissue are shown in Figures 1 and 2, respectively. No significant changes were detected in the levels of CD4+ and CD8+ T cells in the blood of CRSwNP patients compared with controls. The percentage of CD4+ T cells in blood was significantly higher than that of CD8+ T cells in CRSwNP patients (p < 0.0001). All but two patients had a CD4/CD8 ratio > 1 in blood.

Similar to controls, blood CD45RA+ T cells were higher than CD45RO+ T cells among both CD8+ and CD4+ T cells of CRSwNP patients (p = 0.03, p < 0.0001, respectively). In addition, no noticeable changes were detected in either blood CD45RA+ T cells or CD45RO+ T cells between patients and controls. Higher levels of CD8+ TCM and lower levels of CD8+ TEM were detected in the blood of CRSwNP patients vs controls (p = 0.01 & p < 0.0001, respectively). CD4+ TSCMs was the only CD4+ T cell subset showing increased frequency in the blood of CRSwNP patients compared with controls (p = 0.01).

CD4+ T cells were lower in polyp tissue than blood of CRSwNP patients (p < 0.0001), whereas tissue and blood levels of CD8+ T cells did not show a significant difference. Also, no significant difference was observed between CD4+ and CD8+ T cells in tissue from CRSwNP patients. However, the CD4/CD8 ratio was substantially lower in tissue than in blood of CRSwNP patients (1 ± 0.09 vs 1.5 ± 0.08, p = 0.004), and 12 had a CD4/CD8 ratio < 1 in tissues.

In comparison with controls, CRSwNP patients showed a significant decrease in the total percentage of CD45RA+ T cells and a significant increase in the total frequency of CD45RO+ T cells among tissue CD8+ (p = 0.004 & p = 0.02, respectively) and CD4+ (p < 0.0001 & p = 0.007, respectively) T cells. Moreover, tissue CD45RO was higher than CD45RA expression by both CD8+ and CD4+ T cells of CRSwNP patients (p < 0.0001, p = 0.001, respectively).

Tissue CD8+ cells showed a substantial decrease of the TNs and TCMs cells (p = 0.001, p = 0.02, respectively), and a marked increase in TEM and TEMRA cells (p < 0.0001, p = 0.001, respectively) in CRSwNP patients compared with controls. Likewise, CD4+ T cells displayed a significant decrease of TNs and TSCMs cells (p = 0.001, p = 0.005, respectively), and a marked increase in TEMs and TEMRAs cells (p < 0.0001, p = 0.02, respectively).

Generally, the percentages of TEMs and TEMRAs were higher among CD8+ than CD4+ T cells in blood (p = 0.047, < 0.0001, respectively) and tissue (p = 0.001, p< 0.0001, respectively). Conversely, the percentages of TNs and TCMs were higher among CD4+ than CD8+ T cells in blood (p = 0.005, p = 0.07, respectively) and tissue (p < 0.0001, p = 0.004, respectively).

Correlations of T cell subsets with Lund-Mackay CT score and blood cell count

Blood CD8+ TCMs had a positive correlation with neutrophil percentage (r = 0.3, p = 0.03), whereas blood CD4+ TEMRAs had a negative correlation with neutrophil count (r = -0.3, p = 0.04). Only blood CD4+ TEMs have shown positive correlation with the total CT score (r = 0.3, p = 0.03). Tissue CD8+ T cells were directly related to the neutrophil count (r = 0.3, p = 0.04), and tissue CD8+ TEMs were positively correlated with eosinophil percentage and absolute count (r = 0.3, p = 0.03, and r = 0.3, p = 0.04, respectively). The relations among demographic data, blood cell count, CT scores and levels of different T cell subsets in blood and polyp tissue specimens of all patients are presented in Figure 3.

Discussion

The abnormal immune system activation in sinonasal mucosa is a key player in the aetiology and pathophysiology of CRS. The recruitment of T cells and elevated T cell inflammatory cytokines, particularly type 2 in the mucosa of CRS patients, emphasises that T cells significantly contribute to the pathogenesis of CRS 1. To better understand the pathophysiologic mechanisms of CRS, characterisation of the immune cells that infiltrate nasal and sinus tissues is critical. Therefore, in this study, we analysed the T cell subset distribution in blood and tissue and assessed their relations with CT score and blood cell count.

Comparable with controls, the percentage of CD4+ T cells in blood was significantly higher than CD8+ T cells in CRSwNP patients. CD4+ T cells were decreased in polyp tissue compared to blood of CRSwNP patients. Even though no noticeable differences were detected in CD8+ T cells in tissue and blood, all but two patients had a CD4/CD8 ratio > 1 in blood, and 12 patients had a CD4/CD8 ratio < 1 in tissues. Also, the CD4/CD8 ratio was substantially lower in tissue than in the blood of CRSwNP patients, which is largely attributable to the decrease in CD4+ T cells.

The distribution of CD4+ and CD8+ T cells in nasal polyps has been broadly discussed in previous studies. Immunohistochemical analysis of sinus mucosal tissue showed elevated levels of CD8+ T cell subset in the nasal mucosa of CRSwNP than controls 13. Several authors also described a predominance of mucosal CD8+ T cells than CD4+ T cells in patients with nasal polyps 14-16 and an inverse median of CD4/CD8 T cell ratio compared with controls 14. However, Pants and coauthors also noted that the mucosa of some patients with chronic inflammation had an excess of CD4+ T cells with a relative decrease of CD8+ T cells 15. In addition, Derycke and colleagues found a rise in CD4/CD8 T cell ratio in nasal polyps 17. Recently, Bartemes et al. found lower levels of both CD8+ and CD4+ T cells in nasal polyp tissue than in peripheral blood 18. On the other hand, Morinaka and Nakamura reported no significant differences in the percentages of CD4+ and CD8+ T lymphocyte subsets and CD4/CD8 ratio between nasal turbinate mucosa and nasal polyps 19. Immunochemical analysis in another study showed higher levels of CD8+ and CD4+ T cells in nasal turbinate mucosa in chronic sinusitis patients vs controls. Additionally CD4+ T cells clustered in lamina propria, whereas CD8+ T cells were scattered in the lamina propria and appeared in the epithelium next to seromucous glands 20.

In line with previous findings 16,17,21, among both CD8+ and CD4+ T cells, there was a shift from naïve phenotype in blood to an effector/memory phenotype in nasal polyp tissues of our CRSwNP patients. However, detailed characterisation of CD45RA+ and CD45RO+ T cell subsets among both CD4+ and CD8+ cells in blood and tissue of CRSwNP patients is lacking. Most of the variations in T cell subsets detected in the current study were in tissue rather than blood. Our results showed a higher level of CD8+ TCM and CD4+ TSCMs with a lower level of CD8+ TEM in the blood of CRSwNP patients compared with controls. In contrast, a substantial decrease of tissue CD8+ TNs, CD8+ TCMs, CD4+ TNs, and CD4+TSCMs with a marked increase in the percentages of TEMs and TEMRAs was detected among CD4+ and CD8+ T cells in CRSwNP patients.

Generally, the percentages of TEMs and TEMRAs were higher among CD8+ than CD4+ T cells in blood and tissue. Conversely, the percentages of TNs and TCMs were higher among CD4+ than CD8+ T cells in the blood and tissue of our CRSwNP patients. Tissue accumulation of TEMRAs is enhanced by the presence of persistent infections 22. Altogether these findings indicate that the nasal polyp microenvironment might drive T cell differentiation, especially CD8+ T cells signifying increased activation by long-term exposure to antigens which reflects their likely role in defense against microbes and or suppression of allergic responses.

Previous studies 15,23 suggested recruitment of memory T cells to the inflamed nasal mucosa where reactivation occurs. Pants et al. found that the majority of CD8+ T cells in nasal polyp tissue of CRSwNP patients were TEMRAs. However, they did not detect significant changes in effector memory CD4+ T cells in those patients, indicating that CD8+ T cells are probably the main cells involved in inflammation in nasal polyps. Moreover, they did not detect any differences in CD4 or CD8 T cell subset ratios in nasal mucosa in relation to sinus microbiology or coexisting allergy. In addition, they did not find any alterations in CD8+ and CD4+ T cell subsets between peripheral blood of patients and healthy controls 15.

To date, this is the first study to analyse TSCMs in the nasal polyps microenvironment. TSCMs are considered the least differentiated subset of memory T cells. Staphylococci have been shown to trigger type 2 cytokine release from innate lymphoid cells (ILCs) and T cells 24. Gattinoni and coauthors demonstrated the rapid responsiveness of CD95+ naïve-like CD8+ and CD4+ TSCMs following exposure to staphylococcal enterotoxin B, accompanied by the production of IFN-γ, TNF-α and IL-2, while TNs stayed relatively quiescent. TSCMs have the stem cell-like capabilities of self-renewal and are multipotent progenitors that can generate all memory/effector T-cell subsets in vitro 25.

A multicentre study carried out in Europe, Asia and Oceania revealed that tissues from CRSwNP patients in Western countries were Th2 skewed, while those from Beijing showed mixed Th1/Th2/Th17 pattern 26. Eosinophils are inflammatory cells with a significant role in the pathogenesis of CRSwNP. In addition, levels of peripheral blood eosinophils have been suggested to be a factor of disease severity 27. Moreover, according to recent literature, defining not only the eosinophilic but also the neutrophilic inflammation in CRS patients could lead to prediction of prognosis 28. Eosinophils are involved in the regulation of T cell function with respect to Th1/Th2 polarisation. An earlier study reported a positive correlation of CD8+ T cells with the eosinophil absolute count and percentage 29. Ma et al. evaluated the CD8+ T cell subset distribution in CRSwNP patients and described that the percentage of IL-4+ type-2 cytotoxic T cell (Tc2) subset was directly correlated with absolute eosinophil count, while the frequencies of IFN-γ+ Tc1 and IL-17A+ Tc17 subsets were directly correlated with absolute neutrophil count 30. Along with the previous findings, tissue CD8+ T cells showed significant correlations with eosinophil and neutrophil counts and percentages in our study, proposing that, comparable to CD4+ T cell subsets, accumulation of CD8+ T cells in the tissue of nasal polyps associates with the degree of inflammation in CRS.

Altogether, TNs, TSCMs, and TCMs probably differentiated into effector TEMs and TEMRAs subsets in sinonasal mucosa, especially CD8+ T cells. These changes in memory/effector T-cells may reflect a constant exposure to microbial antigens or allergens. However, our study has some limitations. It was not possible to get healthy tissue from controls which would probably have given wider insight on the alterations in memory/effector T cell subsets in patients with CRSwNP. Also, histopathological examination might yield data on the impact of T cell activity on sinonasal mucosa. It would be of interest to know if changes in T cell subsets and cytokine secretion were present following exposure to microbial antigens.

Conclusions

The reduction of TNs, TSCMs, and TCMs and accumulation of TEMs and TEMRAs subsets that function as effector cells in sinonasal mucosa, especially CD8+ T cells, might indicate the role of immunomodulation of memory/effector T-cells in the pathogenesis of CRSwNP.

Conflict of interest statement

The authors declare no conflict of interest.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author contributions

AMZ, OEB, MM Osman contributed to the study conception and design. MM Osman was responsible for patients’ recruitment. Material preparation and data collection were accomplished by all authors and data analysis was performed by OEB and MMO. The first draft of the manuscript was written by OEB and MMO and AMZ, OEB and MMO commented on previous versions of the manuscript, read and approved the final manuscript.

Ethical consideration

The Faculty of Medicine Ethics Committee, Assiut University, reviewed and accepted the study protocol (IRB. No. 17300596), according to the latest revision of the Declaration of Helsinki. All patients gave written informed consent to participate in the study.

Figures and tables

Figure 1.(A, B, C) plots showing levels of CD4+ and CD8+ cells in patients’ tissue and blood and control blood, respectively; (D,E, F) percentages of CD45RA+CD8+ and CD45RO+CD8+ cells in patients’ tissue and blood and control blood, respectively; (G, H, I) frequencies of CD8+ TNs and CD8+ TSCMs in patients’ tissue and blood and control blood, respectively; (J, K, L) levels of CD8+ TCMs and CD8+ TEMs in patients’ tissue and blood and control blood, respectively; (M, N, O) levels of CD8+ TEMRAs in patients’ tissue and blood and control blood, respectively; (P) comparison of percentages of CD8+ T cell subsets between patients and control blood and (Q) between patients’ blood and tissue. *p < 0.05, **p < 0.01; ***p < 0.0001.

Figure 2.(A, B, C) percentages of CD45RA+CD4+ and CD45RO+CD4+ cells in patients’ tissue and blood and control blood, respectively; (D,E,F) frequencies of CD4+ TNs and CD4+ TSCMs in patients’ tissue and blood and control blood, respectively; (G, H, I) levels of CD4+ TCMs and CD4+ TEMs in patients’ tissue and blood and control blood, respectively; (J, K, L) levels of CD4+ TEMRAs in patients’ tissue and blood and control blood, respectively; (M) comparison of percentages of CD4+ T cell subsets between patients and control blood and (N) between patients’ blood and tissue. *p < 0.05; ** p < 0.01; ***p < 0.0001.

Figure 3.A heat map showing the demographic data, CT scores and laboratory data [total leukocyte count (TLC), neutrophil (neut) count and percentage (%), eosinophil (eosin) count and percentage (%), total CD4+ and CD8+ cells, percentages of TNs, TSCMs, TCMs, TEMs and TEMRAs among CD4+ and CD8+ cells in blood and polyp tissue] of patients. The figure shows a decrease of the tissue CD8+ TNs, CD8+ TCMs, CD4+ TNs, and CD4+TSCMs and an increase in the percentages of TEMs and TEMRAs among CD4+ and CD8+ T cells compared with their levels in blood.

Variables Patients
N = 21
Age (years) 36.6 ± 4
Sex
    Male 15 (71.4%)
    Female 6 (28.6%)
Haematological findings
    TLC (x109/L) 7.5 ± 0.5
    Neutrophil percent/count (x109/L) 52 ± 2/3.8±0.4
    eosinophil percent/count (x109/L) 3.7 ± 0.6/0.3 ± 0.04
Lund-Mackay total score 8 2 (9.5%)
13 1 (4.8%)
15 1 (4.8%)
16 4 (19%)
19 2 (9.5%)
21 1 (4.8%)
22 2 (9.5%)
24 8 (38%)
Table I.Clinical and laboratory features of patients.

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Affiliations

Asmaa M. Zahran

Department of Clinical Pathology, South Egypt Cancer Institute, Assiut University, Assiut, Egypt

Omnia EL-Badaway

Department of Medical Microbiology & Immunology, Faculty of Medicine, Assiut University, Assiut, Egypt

Ibrahim K.I. Elsayh

Third year Medical student, Faculty of Medicine, Assiut University, Assiut, Egypt

Mohamed M. Osman

Department of Otorhinolaryngology & Head and Neck Surgery, Faculty of Medicine, Assiut University, Assiut, Egypt

Copyright

© Società Italiana di Otorinolaringoiatria e chirurgia cervico facciale , 2022

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