Elevated CD3^low double negative T lymphocyte is associated with pneumonia and its severity in pediatric patients

Patients and controls

Peripheral blood samples were obtained from 131 pediatric patients and 29 healthy individuals recruited at the Institute of Pediatrics, the First Hospital of Jilin University, Changchun, China, from October 2016 to April 2017. Written informed consent was obtained from all subjects prior to their enrolment. The study was approved by the Human Ethics Committee of the First Hospital of Jilin University (Ethical Approved No. 2016-405). The classification of pneumonia severity was based on the criteria defined by the World Health Organization (WHO) and established in the Brazilian Guidelines for community acquired pneumonia in Pediatrics (WHO, 2013; Sociedade Brasileira de Pneumologia e Tisiologia, 2007). The diagnosis of pneumonia was based on radiological evidence of pulmonary consolidation in combination with increased respiratory rate (respiratory rate ≥ 50 breaths per minute in children aged 2–11 months or ≥ 40 breaths per minute in children aged ≥1 year) (WHO, 2013; Sociedade Brasileira de Pneumologia e Tisiologia, 2007). Severe pneumonia was defined by severe chest indrawing in children with cough or difficult breathing or by the presence of general danger signs in patients with signs of pneumonia (inability to breastfeed or drink, lethargy or reduced level of consciousness, convulsions) (WHO, 2013; Sociedade Brasileira de Pneumologia e Tisiologia, 2007). The pediatric patient population was composed of children aged 0–15 years who were diagnosed with pneumonia (n = 76) or severe pneumonia (n = 55). Peripheral blood samples were collected from patients with pneumonia or severe pneumonia at the time of first clinical diagnosis and prior to receiving any treatment. Patients with recurrent pneumonia, those with a history of chronic pulmonary, renal, or cardiovascular disease, and those with recent surgical intervention were excluded. Data pertaining to demographic, clinical characteristics, and etiology were collected and analyzed. Subjects with immunodeficiency, autoimmune diseases, human immunodeficiency virus (HIV) infection, any infectious diseases or lung disease were excluded from the healthy control group.

Laboratory methods

Specific etiology was determined based on the diagnostic work up at the central laboratory of the hospital using routine methods, such as quantitative-polymerase chain reaction (qPCR) and bacterial culture. Immunophenotyping of peripheral blood lymphocytes was performed using 10-colour/three laser flow cytometer (FACSCanto™; BD Bioscience, San Jose, CA, USA), BD FACSCanto™ software, and BD FACSDiva™ software (BD Bioscience, San Jose, CA, USA). Freshly collected EDTA-anticoagulated whole blood samples were collected usually on the day after the onset of fever (Table 1). Absolute counts and percentage of lymphocyte subsets were determined with a BD Multitest 6-Color TBNK reagent (CD45 PerCP-Cy5.5 clone 2D1/CD3 FITC clone SK7/ CD4 PE-Cy7 clone SK3/CD8 APC-Cy7 clone SK1/CD19 APC clone SJ25C1/CD56 PE clone NCAM 16.2+CD16 PE clone B73) using standard lysis-no-wash procedure and TRUCount tubes (BD Bioscience, San Jose, CA, USA). The lymphocyte subsets were determined by total T cells (CD3⁺), total B cells (CD3⁻CD19⁺), and total natural killer (NK) cells (CD3⁻CD56⁺/CD16⁺). The total T cells were further subdivided into subgroups by CD4 and CD8. The gating strategy for DNT cell subsets is according to the special purpose shown in different figures in the results section. The minimum cell number analyzed in DNT cells (CD3⁺CD4⁻ CD8⁻) gate was 50 cells. The CD3 expression levels on DNT, CD4⁺T, CD8⁺T, and total T cells were determined from MFI analyzed by flow cytometer.

Statistical analysis

All statistical analyses were performed using SPSS 17.0 software (SPSS Inc, Chicago, IL, USA). Clinical data are expressed as mean ± standard deviation (SD). For quantitative analysis, between-group differences with respect to normally distributed variables were assessed using Student’s t test while those with respect to non-normally distributed variables were assessed using non-parametric Mann–Whitney U test. Differences between three or more groups with respect to continuous variables were assessed using one-way analysis of variance for normally distributed variables and Kruskal–Wallis test for non-normally distributed variables. The Chi-squared test was used for qualitative analysis. A p-value <0.05 was considered statistically significant. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance of the biomarkers. The optimal threshold level for CD3 MFI on DNT was obtained based on the Youden index (defined as the sum of sensitivity and specificity minus one). Based on the maximal Youden index, the sensitivity and specificity were defined.

CD3^low DNT cells were elevated in pediatric patients with pneumonia

During routine test of circulating TBNK subsets by flow cytometry, we noticed variable CD3 levels on DNT lymphocytes. To explore whether the CD3 expression levels on DNT cells were related to infectious disease, we analyzed the data of TBNK subsets from pediatric pneumonia or severe pneumonia patients. The general information of the patients is shown in Table 1. First, we analyzed the numbers of circulating DNT cell subsets by gating for CD45⁺CD3⁺CD4⁻CD8⁻ cells (Fig. 1A) in pneumonia patients and healthy controls; we found that the numbers of DNT cells in healthy controls were not significantly different from those in patients in the pneumonia (p > 0.05) and severe pneumonia (p > 0.05) groups (Fig. 1B). Then, we analyzed the ratios of CD3^low DNT cell subsets in total circulating DNT cells and found that the proportion of CD3^low DNT cells in peripheral blood of patients with pneumonia and severe pneumonia was significantly elevated (p < 0.001) and showed a positive correlation with the severity of pneumonia (p < 0.01) (Fig. 1C). These findings suggest that the frequency of circulating CD3^low DNT cell subsets may predict the severity of infectious disease, such as pneumonia.

Age-related differences of CD3 levels on DNT cell subsets in pediatric pneumonia patients

To assess whether the level of CD3 expression on DNT cell subsets showed differences with the severity of pneumonia, we first analyzed the MFI of CD3 on DNT cell subsets in the different groups. The results showed that the MFI of CD3 on DNT cell subsets in patients with pneumonia or severe pneumonia were significantly lower than that in the healthy control group (p < 0.001 and p < 0.001, respectively). Moreover, the MFI of CD3 on DNT cells from patients with severe pneumonia was significantly lower than that in patients with pneumonia (p < 0.01) (Fig.  2A). These findings indicate a positive correlation between the CD3 levels on DNT cell subsets and the severity of pediatric pneumonia. Then, we further investigated the effect of age on the changes in CD3 expressions levels on DNT by disaggregating the subjects into 3 age-groups: 0–12 months, 66 children (41.2%); 13 months–5 years, 50 children (31.3%); 6–15 years, 44 children (27.5%). As shown in Fig. 2B, the MFI of CD3 on DNT subsets in patients with pneumonia and severe pneumonia aged less than 5 years were significantly lower than that in control group (p < 0.001). Moreover, the MFI of CD3 on DNT subsets in patients with severe pneumonia was significantly lower than that in patients with pneumonia (p < 0.05). However, in the 6–15 year age-group, no significant differences in this respect were observed between the control, pneumonia, and the severe pneumonia groups. These results suggest that CD3 levels on DNT subsets in peripheral blood can only be used as a biomarker of clinical severity of respiratory system infection in patients aged <5 years.

In this study, none of the patients with pneumonia had concomitant diseases. In the severe pneumonia group (n = 55), 25 children had concomitant diseases (heart failure (n = 13), respiratory failure (n = 6), toxic encephalopathy (n = 3), hematuria (n = 2), and gastrointestinal hemorrhage (n = 1)). To explore the impact of concomitant disease on lymphocyte subsets, we analyzed the data of TBNK subsets from patients with severe pneumonia and found that the concomitant diseases did not affect the proportions and numbers of TBNK subsets (Figs. S1A and S1B). During analysis of the MFI of CD3 in DNT cell subsets, we further confirmed that the changes in CD3 expression levels on DNT cell subsets were not affected by concomitant diseases (Figs. S1C).

Relationship between increased CD3^low DNT cell subsets and the causative pathogen

To assess any potential relation between CD3^low DNT cell subsets and pathogenic profile of pneumonia, patients with pneumonia and severe pneumonia were further divided into four sub-groups based on the causative pathogen: viral infection (Viral), bacterial infection (Bac), mycoplasma/chlamydia pneumonia infection (Myc), and mixed infection (Mixed). We observed no significant difference between these four sub-groups with respect to the frequency of CD3^low DNT cell subsets in both pneumonia (Fig. 3A) and severe pneumonia (Fig. 3B) groups. Moreover, no significant differences were observed between the four sub-groups with respect to the MFI of CD3 in DNT subsets in both pneumonia (Fig. 3C) and severe pneumonia (Fig. 3D) groups. These findings suggest no relationship between the increased CD3^low DNT cell subsets in pneumonia and the causative pathogens.

Relationship between CD3⁺ CD16/56⁺ NKT cells and CD3^low DNT cells

To clarify whether the increased DNT cell subsets in pneumonia patients were NKT cells, we first analyzed the CD16/56 expression levels on DNT cells. We observed that the MFI of CD16/56 in both CD3^low DNT cells and CD3^high DNT cells in pneumonia patients was significantly lower than that in the control group (Fig. 4A). Subsequently, we determined the ratios of CD3⁺CD16/56⁺ NKT cells in CD3^low DNT cells and CD3^high DNT cells and found no significantly different between the control, pneumonia, and severe pneumonia groups in this respect (Fig. 4B). Finally, we assessed the relationship between NKT and outcomes of pediatric pneumonia. We found similar proportions of NKT cells among total T cells in the healthy control, pneumonia and severe pneumonia groups (Fig. 4C). Moreover, there were no significant differences between the three groups with respect to CD3 expression levels on NKT cells (Fig. 4C). In order to exclude the effect of CD16 expression on the results, we used CD56 monoclonal antibody to detect NKT cells in a part of patients. We found similar proportions of CD3⁺ CD56⁺ NKT cells among CD3^low DNT cells in the healthy control, pneumonia and severe pneumonia groups (Figs. S2A–2C). These results indicate that the increased CD3^low DNT cells were not NKT cells.

Predictive ability of CD3^low DNT cell subsets for clinical severity of pediatric pneumonia

ROC curve analysis was used to assess whether the increased CD3^low DNT cells in circulating lymphocytes may serve as a predictor of the severity of pediatric pneumonia. The dataset of CD3 MFI on DNT cell subsets with or without pneumonia was used to draw ROC curves. In comparing total pneumonia group (pneumonia plus severe pneumonia) and control group, the area under the curve (AUC) was 0.928 and an optimal threshold of 3,435 was associated with 78.6% sensitivity and 96.6% specificity (Fig. 5A). On subgroup analysis, the AUC for CD3 MFIs on DNT cell was 0.896 for pneumonia and 0.970 for severe pneumonia (Fig. 5B). The sensitivity and specificity to differentiate pneumonia from control were 72.4% and 96.6%, respectively, which were lower than that for differentiating severe pneumonia from control (85.5% and 96.6%, respectively). The ROC curve of CD3 MFI on DNT to differentiate severe pneumonia from pneumonia in the 0–5 year age-group had an AUC of 0.775 and the optimal threshold of 2,341.5 was associated with 61% sensitivity and 80.4% specificity (Fig. 5A). These results indicate that CD3 expression levels on DNT cell subsets in peripheral lymphocytes may be a valuable biomarker for assessment of the severity of infectious diseases, such as pneumonia.