T cell immune status in patients with acute exacerbation of chronic obstructive pulmonary disease: A case-control study

T cell immune status in patients with acute exacerbation of chronic obstructive pulmonary disease: A case-control study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article T cell immune status in patients with acute exacerbation of chronic obstructive pulmonary disease: A case-control study Xiao-feng Xiong, Min Zhu, Hong-xia Wu, Zuo-hong Wu, Li-li Fan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3971739/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Immune inflammatory response plays an important role in chronic obstructive pulmonary disease (COPD). However, the cellular immune status of patients with COPD at different phases is unclear. Herein, we aim to investigate the distribution and functional status of T cell subsets in different phases of COPD (acute exacerbation of COPD [AECOPD] and stable COPD [SCOPD]). Methods This is an observational case-control study undertaken in West China Hospital. The distribution of T cell subsets in peripheral blood of AECOPD, SCOPD, and healthy controls (HCs) was measured using multi-color flow cytometry, and the functional status was analyzed by additional staining of activation markers. Results A total of 43 HCs, 43 SCOPD patients, and 64 AECOPD patients were evaluated. The total number and percentage of lymphocytes and the CD4+/CD8 + T cells ratio were significantly lower in AECOPD patients when compared to HCs. HLA-DR expression in CD3+, CD4+, CD8+, CD8 + TCR aβ, and CD4 + TCR aβ T cells was upregulated in the AECOPD group. Similarly, the expressions of HLA-DR, CD57, and PD-1 were higher in T cell subsets in the AECOPD group. Compared with the SCOPD and HC groups, the AECOPD had a significantly lower proportion of CD4 + CD27 + CD28 + T cells, but opposite results were found for CD4 + CD27-CD28- T cells. In addition, the proportion of CD4 + CD39 + T cells and CD4 + CD25 + FoxP3 + T cells was significantly higher in the AECOPD and SCOPD groups when compared to the HC group ( P < 0.05). Conclusions The distribution of nearly half the T cell subsets in AECOPD patients was significantly different from that in SCOPD patients and HCs. AECOPD patients may have cellular immune suppression, immune dysfunction, abnormal activation, and higher senescence depletion of T cells. Trial Registration: The study has been registered in the China Clinical Trials Registry on September 19, 2018 (ChiCTR1800018452). Chronic obstructive pulmonary disease acute exacerbation T cells immunity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide[ 1 ]. COPD is prevalent in 13.7% of Chinese adults aged over 40 years[ 2 ], and more than 5.4 million people are projected to die from COPD and related diseases by 2060[ 3 , 4 ]. COPD manifests in two distinct phases: stable COPD (SCOPD) and acute exacerbations of COPD (AECOPD). The latter can cause rapid decline in lung function and severely impair patients’ quality of life[ 1 ]. The inflammatory response associated with COPD exhibits notable heterogeneity. This response is characterized by an aberrant activation of the innate immune system, predominantly mediated by neutrophils and macrophages in pulmonary regions, coupled with systemic inflammation. Furthermore, the engagement of T lymphocytes in the adaptive immune response contributes to the chronicity and exacerbation of inflammation, which furthers the development of emphysema and culminates in airway remodeling[ 5 ]. The immune-mediated inflammatory response may be pivotal in the pathogenesis and progression of COPD. However, there is ongoing debate regarding whether disparities exist in the distribution of T cell subsets in the different phases of COPD. The pathogenesis of COPD is yet to be fully elucidated, but the immune inflammatory response is said to play an important role in its occurrence and development. Autoimmune abnormalities have recently been found to promote the development of COPD, providing a new perspective for understanding the pathogenesis of the disease[ 6 – 10 ]. current clinical studies predominantly limit their scope to a primary analysis of peripheral blood T lymphocytes, including CD4 + and CD8 + cells, without an exhaustive and detailed examination of the more nuanced T cell subsets. To date, no clinical research has comprehensively observed the distribution and functional status of T cell subsets in the peripheral blood at different phases of COPD. Thus, this study aimed to investigate the distribution and functional status of T cell subsets in different phases of COPD to provide a clinical and theoretical basis for understanding the immunological mechanism of COPD. Materials and Methods Study design and subjects This observational case-control study was conducted in accordance with the Declaration of Helsinki and was approved by the institutional ethics committees of West China Hospital of Sichuan University (identification no. 2018 [283]). The study was registered in the China Clinical Trials Registry on September 19, 2018 (ChiCTR1800018452). Written informed consent was obtained from all participants. AECOPD and SCOPD patients were recruited in the Department of Respiratory and Critical Care Medicine of West China Hospital from September 2018 to October 2019. All COPD patients were diagnosed according to the 2017 Global initiative for chronic obstructive lung disease (GOLD) guidelines[ 11 ]. Healthy controls (HCs) were matched for age and sex to the patients. The HCs and patients were recruited according to the key inclusion and exclusion criteria (Table 1 ). Subject demographic and clinical characteristics, including age, sex, body mass index, smoking history, and comorbidities, were recorded. The pulmonary function test was performed in all HCs, SCOPD patients, and AECOPD patients with permissible conditions. COPD symptoms were evaluated according to the COPD assessment test (CAT), and the modified British Medical Research Council (mMRC) dyspnea scale[ 12 ] and AECOPD patients were assessed within 48 hours after admission. AECOPD patients received the standardized treatment regimen including (but not limited to) antibiotics, a systemic corticosteroid, a short-acting inhaled β2 agonist, a short-acting anticholinergic, and oxygen therapy. The patient inclusion flowchart is shown in Supplementary Figure S1 . Table 1 Inclusion and exclusion criteria of study Inclusion criteria Exclusion criteria • age ≥ 40 years; 1) Had a history of systemic corticosteroid therapy (prednisone > 0.5 mg/kg or equivalent doses) within 1 month; 2) Had a history of diseases that affect immune cells, such as connective tissue diseases, immunological diseases, hematological diseases, hepar and renal failure; 3) Had a history of asthma, allergic disease, or other clinically significant lung diseases; 4) Had a history of heart failure, arrhythmia, mental disorders, or any malignancy. • SCOPD is defined as respiratory symptoms were stable or mild, and the condition was stable for 3 months. • AECOPD is defined as an acute worsening of respiratory symptoms that results in additional therapy. • HCs: COPD-free individuals with normal pulmonary function. AECOPD, acute exacerbation of chronic obstructive pulmonary disease; SCOPD, stable chronic obstructive pulmonary disease;HCs, healthy controls. Blood collection and flow cytometry The blood, used for routine blood and T cell subsets test, was collected before receiving systemic corticosteroid therapy (prednisone > 0.5 mg/kg or equivalent doses) and tested within 24 hours. The blood routine test was completed by the Clinical Laboratory Department of West China Hospital of Sichuan University. For flow cytometry, flow cytometric fluorescent anti-human monoclonal cell surface antibody (dry powder) tubes (DuraClone IM panels: T cell, TCRs, and Treg subsets) were purchased from Beckman Coulter (Brea, CA, USA). All operations refer to product instructions. The fluorochrome-conjugated antibody, schemes of fluorochrome channel, and compensation controls (each of a single color) are described in Table S1 . All samples were analyzed with a 13-Color CytoFlex Flow Cytometer (Beckman Coulter, Brea, CA, USA) after daily calibration with Flow-Set Pro Beads (Beckman Coulter, Brea, CA, USA). Strategies for T cell subsets gating The classification of T cell subsets is shown in Figure S2, and strategies for T cell subsets gating are shown in Figures S3-5. We used a two-parameter scatter plot composed of CD45 and forward scatter area to gate the lymphocytes. The CD3 + cell population was defined as the total T cells and categorized into seven populations using the human leukocyte antigen-DR (HLA-DR), CD57, programmed death receptor 1(PD-1), TCR, CD8, and CD4 markers as follows: (1) HLA-DR + T cells, (2) CD57 + T cells, (3) PD-1 + T cells. (4) TCR aβ + T cells, (5) TCR γδ + T cells, (6) CD8 + T cells, and (7) CD4 + T cells. CD8 + T cells were divided into 4 subtypes: (1) CD8 + CD57 + T cells, (2) CD8 + PD-1 + T cells, (3) costimulatory molecules (CD8 + CD27 + CD28 + T cells, CD8 + CD27 + CD28- T cells, CD8 + CD27-CD28 + T cells, and CD8 + CD27-CD28- T cells), and (4) CD45RA and CCR7 expressing (CD8 + effector T cells, CD8 + central memory T cells, CD8 + naïve T cells, CD8 + effector memory T cells). Finally, CD4 + T cells were divided into the following 5 subtypes: (1) CD4 + CD57 + T cells, (2) CD4 + PD-1 + T cells, (3) costimulatory molecules (CD4 + CD27 + CD28 + T cells, CD4 + CD27 + CD28- T cells, CD4 + CD27-CD28 + T cells, CD4 + CD27-CD28- T cells), (4) antigen responses (CD4 + effector T cells, CD4 + central memory T cells, CD4 + naïve T cells, CD4 + effector memory T cells), and (5) regulatory T cells (CD4 + CD39 + T cells, CD4 + CD25 + Forkhead box protein 3 (FoxP3) + T cells, CD4 + CD45RA + T cells, CD4 + Helios + T cells, CD4 + FoxP3 + Helios + T cells). Statistical analysis Normally distributed data were described as the mean ± standard deviations (SD), whereas nonnormally distributed data were reported as medians (interquartile range, IQR) unless otherwise indicated. Continuous parametric data, including CAT scores, WBC levels, pulmonary function test indices, and T cell subset percentages, were analyzed using Student’s t-test or one-way analysis of variance (ANOVA), continuous nonparametric data were analyzed using the Mann–Whitney U or Kruskal–Wallis test. Correlation analyses between the proportion of T cell subsets and symptom score and lung function were performed by using the Pearson or Spearman correlation test. All statistical analyses were performed using SPSS 24.0 (IBM, Armonk, NY, USA), and a P value < 0.05 was considered statistically significant. Results Subject baseline characteristics A total of 43 HCs, 43 SCOPD patients, and 64 AECOPD patients were recruited. The clinicodemographic characteristics are summarized in Table 2 and Table S2. Compared with the SCOPD group, the AECOPD group had worse symptom control and pulmonary function. Table 2 Demographic and Clinical characteristics of subjects at baseline Healthy Control SCOPD AECOPD P value Patients(n) 43 43 64 Age, years 63.07 ± 7.87 64.12 ± 9.13 66.78 ± 7.43 0.732 Male, n (%) 30(69.8) 32(74.4) 49(76.6) 0.051 Smoking history 0.103 Current/Ever smoker, n (%) 24(55.8) 33(76.7) 45(70.3) Never smoker, n (%) 19(44.2) 10(23.3) 19(29.7) Pack years smoked ¥ 0(0,350) 740(100,960) 525(0,900) <0.0001 BMI (kg/m 2 ) 22.99 ± 2.66 22.59 ± 3.08 20.04 ± 4.00 0.357 FEV 1 (L) 2.36 ± 0.52 1.57 ± 1.46 # 1.01 ± 0.32 * <0.001 FEV 1 % pred 98.37 ± 14.55 52.49 ± 21.90 # 45.9 ± 15.27 * <0.001 FVC(L) 2.98 ± 0.68 2.60 ± 0.84 # 1.90 ± 0.49 *△ 0.001 FEV 1 /FVC (%) 78.00 ± 5.58 50.34 ± 11.61 # 55.64 ± 19.93 * <0.001 Leukocyte count,10 9 /L 6.91 ± 3.01 5.75 ± 1.69 8.53 ± 3.6 *△ <0.001 Neutrophil count ,10 9 /L 3.44 ± 1.30 3.46 ± 1.27 6.60 ± 3.35 *△ <0.001 Lymphocyte count,10 9 /L 1.65 ± 0.59 1.69 ± 0.54 1.21 ± 0.63 *△ <0.001 Monocyte count,10 9 /L 0.37 ± 0.18 0.40 ± 0.16 0.56 ± 0.28 *△ <0.001 Eosinophil count,10 9 /L 0.11 ± 0.08 0.15 ± 0.12 0.12 ± 0.16 0.264 Neutrophil, % 60.43 ± 8.94 59.37 ± 7.72 72.79 ± 15.84 *△ <0.001 Lymphocyte, % 29.72 ± 9.49 30.29 ± 7.88 15.93 ± 8.54 *△ <0.001 Monocyte, % 6.40 ± 1.82 7.11 ± 1.68 6.92 ± 2.79 0.315 Eosinophil, % 1.85 ± 1.13 2.62 ± 2.12 # 1.62 ± 1.86 △ 0.016 Data presented as mean ± SD unless specified. ¥ median (interquartile range). Pack years smoked, cigarettes per day × smoking years. *: AECOPD vs. Healthy control, p < 0.05, △ : AECOPD vs. SCOPD, p < 0.05, # : SCOPD vs. Healthy control, p < 0.05. AECOPD, Acute exacerbation of chronic obstructive pulmonary disease; SCOPD, Stable chronic obstructive pulmonary disease; BMI, body mass index; FEV 1 , forced expiratory volume in one second, FVC, forced vital capacity; mMRC, modified medical research council dyspnea scale; CAT, COPD assessment test. Distribution of the general T cell subsets The distribution of the T cell subsets detected for CD3 + T cells and their two main subsets (CD8 + and CD4 + T cells) is detailed in Table 3 and Fig. 1 . There was no significant difference in the proportion of CD3 + T cells among the three groups (Fig. 1 A, B). The proportion of CD8 + T cells was significantly higher in the AECOPD group than in the HC and SCOPD groups ( P = 0.004 and P = 0.065, respectively, Fig. 1 C, D). In contrast, the proportion of CD3 + CD4 + T cells and the CD4+/CD8 + T cells ratio were significantly lower in the AECOPD group than in the HC group ( P = 0.042 and P = 0.303, Fig. 1 E, F). Compared with the HC group, the SCOPD group had a higher proportion of CD3 + CD8 + T cells and a lower proportion of CD3 + CD4 + T cells, but the difference was not statistically significant. Table 3 The proportion of T cell subsets in Peripheral Blood of subjects T cell subsets Healthy Control SCOPD AECOPD P value CD3+ (%) 71.87 ± 8.67 67.98 ± 10.58 69.55 ± 13.44 0.286 CD3 + CD8+ (%) 36.88 ± 9.69 39.15 ± 10.86 43.21 ± 12.06 * 0.013 CD3 + CD4+ (%) 56.16 ± 10.03 54.04 ± 11.13 50.33 ± 13.25 * 0.038 CD4+/ CD8+ 1.73 ± 0.87 1.56 ± 0.74 1.35 ± 0.71 * 0.045 CD3 + HLA-DR+ 39.10 ± 13.98 44.97 ± 12.39 48.83 ± 17.26 * 0.006 CD8 + HLA-DR+ 58.92 ± 17.17 64.81 ± 13.04 68.95 ± 15.63 * 0.005 CD4 + HLA-DR+ 24.24 ± 9.70 25.31 ± 10.45 29.23 ± 15.43 * 0.099 CD8 + TCR aβ + HLA-DR+ 58.40 ± 17.55 63.84 ± 13.22 68.59 ± 16.05 * 0.005 CD4 + TCR aβ + HLA-DR+ 24.01 ± 9.70 25.10 ± 10.47 29.03 ± 15.43 * 0.097 CD3 + TCR aβ+ 92.43 ± 6.43 92.61 ± 5.74 93.88 ± 5.83 0.388 CD8 + TCR aβ+ 38.97 ± 12.52 39.36 ± 11.78 30.95 ± 13.53 0.692 CD4 + TCR aβ+ 58.66 ± 12.63 57.86 ± 11.72 55.70 ± 14.53 0.485 CD3 + TCR γδ+ 7.07 ± 6.42 6.91 ± 5.74 5.65 ± 5.78 0.395 CD3 + CD57+ 24.88 ± 11.60 26.48 ± 11.09 30.61 ± 16.70 * 0.090 CD8 + CD57+ 43.58 ± 16.54 47.54 ± 15.07 47.24 ± 17.78 0.455 CD4 + CD57+ 7.43 ± 4.78 8.03 ± 6.47 13.67 ± 13.25 *△ 0.001 CD3 + PD-1+ 37.89 ± 7.50 45.30 ± 11.02 # 54.24 ± 12.31 *△ < 0.0001 CD8 + PD-1+ 34.79 ± 11.57 35.81 ± 11.86 43.84 ± 16.33 *△ 0.001 CD4 + PD-1+ 36.98 ± 8.24 37.84 ± 9.78 47.13 ± 16.68 *△ < 0.0001 CD8 + CD27 + CD28+ 48.10 ± 17.64 44.92 ± 14.96 42.41 ± 18.20 0.246 CD8 + CD27 + CD28- 7.35 ± 3.26 8.17 ± 5.39 9.02 ± 5.36 0.216 CD8 + CD27-CD28+ 4.13 ± 2.22 6.18 ± 5.44 # 4.90 ± 3.24 0.042 CD8 + CD27-CD28- 40.42 ± 16.62 40.73 ± 15.20 43.66 ± 18.50 0.548 CD4 + CD27 + CD28+ 84.70 ± 7.21 84.50 ± 8.23 78.52 ± 16.14 *△ 0.011 CD4 + CD27 + CD28- 0.12 ± 0.29 0.09 ± 0.07 0.14 ± 0.13 0.401 CD4 + CD27-CD28+ 9.15 ± 4.72 8.95 ± 3.92 9.83 ± 6.11 0.652 CD4 + CD27-CD28- 6.02 ± 4.19 6.46 ± 6.03 11.52 ± 12.48 *△ 0.003 CD8 + Effector T 33.44 ± 15.60 33.31 ± 16.20 31.65 ± 17.79 0.880 CD8 + Central Memory T 16.26 ± 8.98 19.31 ± 8.81 14.48 ± 9.43 △ 0.029 CD8 + Naïve T 17.17 ± 11.88 10.45 ± 7.95 # 12.59 ± 12.54 * 0.019 CD8 + Effector Memory T 34.13 ± 13.34 36.93 ± 12.84 41.29 ± 16.18 * 0.040 CD4 + Effector T 1.22 ± 1.95 0.82 ± 0.10 1.68 ± 4.48 0.375 CD4 + Central Memory T 65.00 ± 8.34 67.90 ± 9.41 58.11 ± 15.48 *△ < 0.0001 CD4 + Naïve T 17.50 ± 7.04 13.94 ± 8.82 16.59 ± 13.34 0.268 CD4 + Effector Memory T 16.27 ± 6.59 17.33 ± 8.12 23.61 ± 15.70 *△ 0.002 CD4 + CD39+ 4.99 ± 4.00 7.78 ± 6.48 # 8.31 ± 6.70 * 0.016 CD4 + CD25 + FoxP3+ 5.48 ± 1.70 8.55 ± 1.62 # 9.09 ± 1.91 * < 0.0001 CD4 + CD45RA+ 21.33 ± 8.40 20.43 ± 9.78 19.98 ± 13.77 0.833 CD4 + Helios+ 3.74 ± 3.25 3.95 ± 3.82 3.45 ± 3.42 0.763 CD4 + FoxP3 + Helios+ 2.67 ± 2.63 2.85 ± 2.85 2.49 ± 2.64 0.796 Data presented as mean ± SD. *: AECOPD vs. Healthy control, p < 0.05, △ : AECOPD vs. SCOPD, p < 0.05, # : SCOPD vs. Healthy control, p < 0.05. AECOPD, Acute exacerbation of chronic obstructive pulmonary disease; SCOPD, Stable chronic obstructive pulmonary disease. Distribution of HLA-DR + T cell and TCR cell subsets Compared with the HC group, the AECOPD group showed significantly higher percentages of CD3 + HLA-DR + T cells ( P = 0.001), CD8 + HLA-DR + T cells ( P = 0.001), CD4 + HLA-DR + T cells ( P = 0.047), CD8 + TCR aβ + HLA-DR + T cells ( P = 0.001), and CD4 + TCR aβ + HLA-DR + T cells ( P = 0.046). However, although the distribution of these subsets was higher in the AECOPD group than in the SCOPD group, the difference was not statistically significant (Table 3 and Fig. 2 ). There was also no significant difference in the proportion of CD3 + TCR aβ + T cells, CD3 + TCR γδ + T cells, CD8 + TCR aβ + T cells, and CD4 + TCR aβ + T cells among the three groups (Figure S6). Distribution of the CD57 + and PD1 + T cell subsets The distribution of CD57 + and PD1 + T cell subsets is shown in Table 3 and Fig. 3 . The proportion of CD3 + CD57 + T cells in the peripheral blood was significantly higher in the AECOPD group than in the HC group ( P = 0.038, Fig. 3 A, B). Further, the proportion of CD4 + CD57 + T cells was significantly higher in the AECOPD group than in the SCOPD and HC groups ( P < 0.0001 and P < 0.0001, respectively, Fig. 3 E, F). Meanwhile, there was no significant difference in the proportion of CD8 + CD57 + T cells among the three groups (Fig. 3 C, D). Compared with the HC group, the AECOPD and SCOPD groups had a significantly higher proportion of CD3 + PD-1 + T cells in the peripheral blood ( P < 0.0001 and P = 0.002, respectively; Fig. 3 G, H). Concurrently, the proportions were significantly higher in the AECOPD group than in the SCOPD group ( P < 0.0001). Further analysis showed that the proportions of CD8 + PD-1 + T cells and CD4 + PD-1 + T cells were higher in the AECOPD group than in the SCOPD group ( P = 0.004 and P < 0.0001, respectively) and in the HC group ( P = 0.001 and P < 0.0001, respectively, Fig. 3 I, J, K, L), but there were no significant differences between the SCOPD and the HC groups. Distribution of T cell subsets of costimulatory molecules The distribution of T cell subsets of costimulatory molecules is shown in Table 3 and Fig. 4 . The proportion of CD4 + CD27 + CD28 + T cells was significantly lower in the AECOPD group than in the SCOPD and HC groups ( P = 0.013 and P = 0.010, respectively, Fig. 4 A, B). In contrast, the proportion of CD4 + CD27- CD28- T cells was significantly higher in the AECOPD group than in the SCOPD and HC groups ( P = 0.005 and P = 0.003, respectively, Fig. 4 C, D). There was no significant difference in the proportion of CD8 + CD27 + CD28 + T cells, CD8 + CD27-CD28- T cells, CD8 + CD27 + CD28- T cells, CD4 + CD27 + CD28- T cells, and CD4 + CD27-CD28 + T cells among the three groups (Figure. S7). Distribution of T cell subsets in antigen response The distribution of T cell subsets in antigen response is shown in Table 3 , Fig. 3 , and Figure S8. The proportion of CD4 + central memory T cells was significantly lower in the AECOPD group than in the SCOPD and HC groups ( P < 0.0001 and P = 0.005, respectively, Fig. 3 E, F). In contrast, the proportion of CD4 + effector memory T cells was significantly higher in the AECOPD group than in the SCOPD and HC groups ( P = 0.007 and P = 0.002, respectively, Fig. 3 G, H). Distribution of regulatory T cell subsets The distribution of regulatory T cell subsets is detailed in Table 3 and Fig. 4 . The proportion of CD4 + CD39 + T cells was significantly higher in the AECOPD and SCOPD groups than in the HC group ( P = 0.006 and P = 0.032, Fig. 4 I, J), while there was no significant difference between the AECOPD and SCOPD groups. Similarly, the proportion of CD4 + CD25 + FoxP3 + T cells was significantly higher in the AECOPD and SCOPD groups than in the HC group ( P < 0.0001 and P < 0.0001, Fig. 4 K, L). Correlation Analyses Results of correlation analyses in COPD patients are shown in Fig. 5 and Table S3. The CAT score was positively correlated with the proportion of CD3 + HLA-DR + T cells ( r = 0.191 , P = 0.048 , Fig. 5 A), CD8 + HLA-DR + T cells ( r = 0.207 , P = 0.032 , Fig. 5 B), CD4 + CD57 + T cells (r = 0.223 , P = 0.021 , Fig. 5 C), CD3 + PD-1 + T cells ( r = 0.304 , P = 0.001 , Fig. 5 D), CD8 + PD-1 + T cells ( r = 0.195 , P = 0.044 , Fig. 5 E), CD4 + PD-1 + T cells ( r = 0.319 , P = 0.001 , Fig. 5 F), CD4 + CD27-CD28- T cells ( r = 0.215 , P = 0.005 , Fig. 4 G), and CD4 + Effector Memory T cells ( r = 0.229 , P = 0.018 , Fig. 5 H). On the contrary, the CAT score was negatively correlated with the proportion of CD4 + CD27 + CD28 + T cells ( r = -0.206 , P = 0.033 , Fig. 5 I), CD8 + Central Memory T cells ( r = -0.268 , P = 0.005 , Fig. 5 J), and CD4 + Central Memory T cells ( r = -0.232 , P = 0.016 , Fig. 5 K). The correlation between the proportion of T cell subsets and mMRC score, FVC, and FEV 1 % pred is presented in Table S3. Discussion The distribution and functional status of T cell subsets in the peripheral blood at different phases of COPD are yet to be clarified to date. This study found that the distribution of nearly half the T cell subsets in AECOPD patients was significantly different from that in SCOPD patients and HCs. This study comprehensively detected the distribution and functional status of T cell subsets in the peripheral blood of AECOPD and SCOPD patients and compared them with those in HCs, using multi-color flow cytometry. T cells mainly function as mediators of the cellular immune response [ 13 ]. We found that compared with the HC group, the AECOPD group had a significantly higher proportion of CD8 + T cells and a significantly lower proportion of CD4 + T cells. This is consistent with the results of previous studies and indicates that the cellular immune function is suppressed[ 14 , 15 ]. Further, we found that the number and distribution ratio of peripheral blood T cells in AECOPD patients were significantly different from those in HCs, and there was obvious inhibition of cellular immune function. However, this was not observed in patients with SCOPD, indicating that immune abnormalities differ according to the phase of COPD. The first stage of T cell immune function is the activation of T cells. HLA-DR is a marker of T cell activation, but few studies have focused on HLA-DR and COPD[ 16 , 17 ]. The current study found that HLA-DR expression in CD3+, CD4+, and CD8 + T cells was significantly higher in the AECOPD group than in the HC group. However, there was no significant difference between the SCOPD groups and HC group, consistent with the findings by Pons et al.[ 18 ], who found no significant difference in HLA-DR expression in the peripheral blood between SCOPD patients and healthy non-smokers. In contrast, Ying[ 19 ] found a significantly higher CD4 + HLA-DR expression in patients with SCOPD when compared to normal controls and smokers. However, neither of the above two studies included AECOPD patients. Khalaf et al.[ 20 ] found that HLA-DR expression was upregulated after the alveolar macrophages of COPD patients were infected by Haemophilus influenzae . In summary, the distribution of HLA-DR labeled T cells in stable COPD is still controversial, and the distribution in AECOPD patients has not been reported previously. Our findings suggest higher activated T cells in the peripheral blood in AECOPD patients than in HCs. The abnormal activation of T cells may be related to the acute aggravating factors (such as infection) in AECOPD patients. CD57 + T cells are very minimally expressed in the peripheral blood of newborns; however, it is upregulated in chronic infection and elderly patients[ 21 – 24 ]. Therefore, CD57 + T cells in the peripheral blood are usually regarded as terminally differentiated or senescent T cells. Olloquequi et al.[ 25 ] found a significantly higher density of CD57 + cells in pulmonary lymphoid follicles in COPD patients than in healthy non-smokers and smokers. Compared with moderate COPD patients, extremely severe COPD patients have a significantly higher density of CD57 + cells in the small airways [26] . The status of CD57 + T cells in the peripheral blood in patients with AECOPD has not been reported to date. As such, there is an important implication to our finding that the proportion of CD57 + T cells in the peripheral blood is higher in the AECOPD group than in the SCOPD and HC groups. This finding indicates that there is an increase of T cell senescence in AECOPD patients, further supporting the obvious inhibition of cellular immune function in AECOPD patients. PD-1 is an important member of the CD28 family. Previous studies have shown that PD-1 expression in CD4 + T cells[ 27 , 28 ] and CD8 + T[ 28 ] cells in the peripheral blood is higher in SCOPD patients than in healthy subjects. Contrasting results were observed in the current study, and this could be due to the difference in sample size or methods of sample treatment. However, few studies have focused on PD-1 in AECOPD patients. Only Tan et al.[ 29 ] reported that PD-1 expression in peripheral blood CD4 + T cells is increased in AECOPD patients. Consistently, the current study showed upregulated PD-1 expression in CD3 + and CD8 + T cells in AECOPD patients. Biton et al.[ 30 ] studied the effect of COPD on non-small cell lung cancer and found that upregulated PD-1 expression in tumor-infiltrating CD8 + T cells of lung cancer patients with COPD. McKendry et al.[ 31 ] also reported higher PD-1 expression in CD4 + T cells and CD8 + T cells in the lung tissue of COPD patients than in HCs. Collectively, these findings support upregulated PD-1 expression in persistent inflammatory immune response. PD-1 is a negative regulatory costimulatory factor on effector T cells, mediating T cell apoptosis by binding to its ligands and playing an important role in cellular immunosuppression and immune tolerance[ 30 , 32 ]. Therefore, PD-1 expression in peripheral T cells is increased in AECOPD patients, suggesting that more effector T cells may be undergoing apoptosis and reversible failure in AECOPD patients. Importantly, these indicate immunosuppression in AECOPD patients. As the second signal, the costimulatory molecules CD27 and CD28 play important roles in the initial complete activation of T cells[ 33 ]. They are also the targets of immunosuppressive therapy. Our results showed that CD27 + CD28+ (double positive costimulatory molecule) CD4 + T cells were decreased while CD27-CD28- (double negative) CD4 + T cells were increased in the peripheral blood of AECOPD patients. Some studies have shown that the proliferation of highly differentiated CD28- T cells related to immune aging is associated with a stronger immunosuppression[ 34 ]. Therefore, the increase in CD4 + CD27-CD28- T cells further supports the view that there is immunosuppression in AECOPD patients. CD39 is an extracellular nucleotidase that hydrolyzes extracellular ATP and ADP into adenosine monophosphate (AMP) and CD73 and converts AMP into adenosine. Tan et al.[ 35 ] reported that CD39 expression in CD4+, CD8+, FoxP3+, and FoxP3- T cells in the peripheral blood are increased in AECOPD patients. Consistent results were obtained in the current study. We also found that the proportion of CD4 + CD25 + FoxP3 + T cells (Tregs) in the peripheral blood is increased in patients with AECOPD and SCOPD. Previous studies have shown that CD39 is highly expressed in Treg cells, which is important for its immunosuppressive function[ 36 , 37 ]. The high expression of CD39 is associated with other markers of T cell depletion or dysfunction, including high expression of PD-1, low expression of CD28, and production of IFN-γ[ 38 ]. CD39 may promote immune failure in patients with COPD and inhibit a protective immune response. Limitations This study has some limitations. First, this was a cross-sectional study and can thus only establish the relationship between AECOPD and immune indicators and cannot suggest causality. However, it provides the basis for further prospective follow-up studies. Second, due to the inclusion of the HC group, it was ethically impossible to further obtain lung tissue samples to understand the situation of immune cells in the airway and lungs. Finally, AECOPD patients had more acute exacerbations and acute hospitalizations over the past year than did SCOPD patients. They also had more severe symptoms, as indicated by higher mMRC and CAT scores. It is speculated that the acute exacerbation and stable phase may also be related to the severity of the disease, and this needs to be confirmed in further subgroup studies with a larger sample size. Conclusion The distribution of nearly half the T cell subsets in AECOPD patients was significantly different from that in SCOPD patients and HCs. Among patients with AECOPD, the total number of lymphocytes, the percentage of lymphocytes, and the CD4+/CD8 + T cells ratio in the peripheral blood were significantly lower, while the proportion of negative regulatory cells (CD4 + CD27-CD28- T cells, CD4 + CD39 + T cells, and CD4 + CD25 + FoxP3 + T cells) was significantly higher, suggesting cellular immune suppression and immune dysfunction in AECOPD. In addition, T cell expressions of HLA-DR, CD57, and PD-1 were significantly upregulated in patients with AECOPD, indicating that there may be abnormal activation and increased senescence depletion of T cells in AECOPD. Abbreviations AECOPD acute exacerbation of chronic obstructive pulmonary disease BMI body mass index CAT COPD assessment test EDTA Ethylene diamine tetraacetate FEV 1 forced expiratory volume in one second FVC forced vital capacity FoxP3 forkhead box protein 3 GOLD Global initiative for chronic obstructive lung disease HLA-DR human leukocyte antigen-DR HCs Healthy controls mMRC modified medical research council dyspnea scale PD-1 Programmed death receptor 1 SCOPD stable chronic obstructive pulmonary disease. Declarations Ethics approval and consent to participate The study was approved by the institutional ethics committees of West China Hospital of Sichuan University (identification no. 2018[283]), and it was registered in the China Clinical Trials Registry on September 19, 2018 (ChiCTR1800018452). All the participants provided written informed consent. Consent for publication Not applicable. Availability of data and material The datasets used and/or analyzed during the current study are available from the corresponding author ( [email protected] ) on reasonable request. Competing interests Authors declare no conflict of interest. Funding This study was supported by the Science and Technology Foundation of Sichuan Province (No.2015SZ0234-3) and National Youth Science Fund Project of National Natural Science Foundation of China (82100045). Authors’ contributions XXF contributed to study design, manuscript writing and data analysis. ZM contributed to data acquisition and analysis. WHX and WZH contributed to study design and data interpretation. FLL contributed to data acquisition and interpretation. CDY contributed to study design and manuscript revision. All authors read and approved the final version of the manuscript. Acknowledgements None References Global strategy for the. diagnosis, management, and prevention of COPD (2024 update). http://wwgoldcopdorg . (accessed 04-Dec-2023). Wang C, Xu J, Yang L, Xu Y, Zhang X, Bai C, Kang J, Ran P, Shen H, Wen F, et al. Prevalence and risk factors of chronic obstructive pulmonary disease in China (the China Pulmonary Health [CPH] study): a national cross-sectional study. Lancet. 2018;391:1706–17. Collaborators GBDCoD. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1736–88. World Health Organization. Projections of mortality and causes of death, 2016 and 2060. http://www.who.int/healthinfo/global_burden_disease/projections/en/ (accessed 14 October 2019). Barnes PJ, Cosio MG. Characterization of T lymphocytes in chronic obstructive pulmonary disease. PLoS Med. 2004;1:e20. Caramori G, Ruggeri P, Di Stefano A, Mumby S, Girbino G, Adcock IM, Kirkham P. Autoimmunity and COPD: Clinical Implications. Chest. 2018;153:1424–31. Nurwidya F, Damayanti T, Yunus F. The Role of Innate and Adaptive Immune Cells in the Immunopathogenesis of Chronic Obstructive Pulmonary Disease. Tuberc Respir Dis (Seoul). 2016;79:5–13. Caramori G, Casolari P, Barczyk A, Durham AL, Di Stefano A, Adcock I. COPD immunopathology. Semin Immunopathol. 2016;38:497–515. Le Guennec L, Pestre V, Mouthon L. Chronic obstructive pulmonary disease: an autoimmune disease? Rev Mal Respir. 2012;29:557–65. Kheradmand F, Shan M, Xu C, Corry DB. Autoimmunity in chronic obstructive pulmonary disease: clinical and experimental evidence. Expert Rev Clin Immunol. 2012;8:285–92. The global initiative for chronic obstructive lung disease.GOLD. 2017 global strategy for the diagnosis, management and prevention of chronic obstructive pulmonary disease 2017 report[EB/OL]. (2016-11-16)[2017-01-03]. i>http://wwwgoldcopdorg. Huang WC, Wu MF, Chen HC, Hsu JY, Group T. Features of COPD patients by comparing CAT with mMRC: a retrospective, cross-sectional study. NPJ Prim Care Respir Med. 2015;25:15063. Zelinskyy G, Werner T, Dittmer U. Natural regulatory T cells inhibit production of cytotoxic molecules in CD8(+) T cells during low-level Friend retrovirus infection. Retrovirology. 2013;10:109. Shirai T, Suda T, Inui N, Chida K. Correlation between Peripheral Blood T-cell Profiles and Clinical and Inflammatory Parameters in Stable COPD. Allergology Int 2010, 59. Fan F, Yufeng W, Yong L. Study on the relationship between T lymphocyte subsets in peripheral blood and acute exacerbation of chronic obstructive pulmonary disease. J Clin Intern Med. 2019;36:412–4. Yang J, Qiao M, Li Y, Hu G, Song C, Xue L, Bai H, Yang J, Yang X. Expansion of a Population of Large Monocytes (Atypical Monocytes) in Peripheral Blood of Patients with Acute Exacerbations of Chronic Obstructive Pulmonary Diseases. Mediators Inflamm 2018, 2018:9031452. Dewhurst JA, Lea S, Hardaker E, Dungwa JV, Ravi AK, Singh D. Characterisation of lung macrophage subpopulations in COPD patients and controls. Sci Rep. 2017;7:7143. Pons AR, Noguera A, Blanquer D, Sauleda J, Pons J, Agusti AG. Phenotypic characterisation of alveolar macrophages and peripheral blood monocytes in COPD. Eur Respir J. 2005;25:647–52. Ying C, Yun S, Yanrong C. Study of T cells activation markers expressing level in peripheral blood of COPD patients. J Clin Experimental Med. 2018;17:485–9. Khalaf RM, Lea SR, Metcalfe HJ, Singh D. Mechanisms of corticosteroid insensitivity in COPD alveolar macrophages exposed to NTHi. Respir Res. 2017;18:61. Onyema OO, Njemini R, Forti LN, Bautmans I, Aerts JL, De Waele M, Mets T. Aging-associated subpopulations of human CD8 + T-lymphocytes identified by their CD28 and CD57 phenotypes. Arch Gerontol Geriatr. 2015;61:494–502. Lee SA, Sinclair E, Hatano H, Hsue PY, Epling L, Hecht FM, Bangsberg DR, Martin JN, McCune JM, Deeks SG, Hunt PW. Impact of HIV on CD8 + T cell CD57 expression is distinct from that of CMV and aging. PLoS ONE. 2014;9:e89444. Aronsson B, Troye-Blomberg M, Smedman L. Increase of circulating CD8 + CD57 + lymphocytes after measles infection but not after measles vaccination. J Clin Lab Immunol. 2004;53:1–12. Fukuda H, Nakamura H, Tominaga N, Teshima H, Hiraoka A, Shibata H, Masaoka T. Marked increase of CD8 + S6F1 + and CD8 + CD57 + cells in patients with graft-versus-host disease after allogeneic bone marrow transplantation. Bone Marrow Transpl. 1994;13:181–5. Olloquequi J, Montes JF, Prats A, Rodriguez E, Montero MA, Garcia-Valero J, Ferrer J. Significant increase of CD57 + cells in pulmonary lymphoid follicles of COPD patients. Eur Respir J. 2011;37:289–98. Olloquequi J, Garcia-Valero J, Rodriguez E, Montero MA, Ferrer J, Montes JF. Lung CD57 + cell density is increased in very severe COPD. Histol Histopathol. 2012;27:39–47. Kalathil SG, Lugade AA, Pradhan V, Miller A, Parameswaran GI, Sethi S, Thanavala Y. T-regulatory cells and programmed death 1 + T cells contribute to effector T-cell dysfunction in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2014;190:40–50. Huang J, Yi H, Zhao C, Zhang Y, Zhu L, Liu B, He P, Zhou M. Glucagon-like peptide-1 receptor (GLP-1R) signaling ameliorates dysfunctional immunity in COPD patients. Int J Chron Obstruct Pulmon Dis. 2018;13:3191–202. Tan DBA, Teo TH, Setiawan AM, Ong NE, Zimmermann M, Hsu AC, Wark PAB, Moodley YP. Impaired Th1 responses in patients with acute exacerbations of COPD are improved with PD-1 blockade. Clin Immunol. 2018;188:64–6. Biton J, Ouakrim H, Dechartres A, Alifano M, Mansuet-Lupo A, Si H, Halpin R, Creasy T, Bantsimba-Malanda C, Arrondeau J, et al. Impaired Tumor-Infiltrating T Cells in Patients with Chronic Obstructive Pulmonary Disease Impact Lung Cancer Response to PD-1 Blockade. Am J Respir Crit Care Med. 2018;198:928–40. McKendry RT, Spalluto CM, Burke H, Nicholas B, Cellura D, Al-Shamkhani A, Staples KJ, Wilkinson TM. Dysregulation of Antiviral Function of CD8(+) T Cells in the Chronic Obstructive Pulmonary Disease Lung. Role of the PD-1-PD-L1 Axis. Am J Respir Crit Care Med. 2016;193:642–51. Festino L, Botti G, Lorigan P, Masucci GV, Hipp JD, Horak CE, Melero I, Ascierto PA. Cancer Treatment with Anti-PD-1/PD-L1 Agents: Is PD-L1 Expression a Biomarker for Patient Selection? Drugs. 2016;76:925–45. Boleto G, Allanore Y, Avouac J. Targeting Costimulatory Pathways in Systemic Sclerosis. Front Immunol. 2018;9:2998. Dedeoglu B, Meijers RW, Klepper M, Hesselink DA, Baan CC, Litjens NH, Betjes MG. Loss of CD28 on Peripheral T Cells Decreases the Risk for Early Acute Rejection after Kidney Transplantation. PLoS ONE. 2016;11:e0150826. Tan DBA, Ong NE, Zimmermann M, Price P, Moodley YP. An evaluation of CD39 as a novel immunoregulatory mechanism invoked by COPD. Hum Immunol. 2016;77:916–20. O'Garra A, Vieira P. Regulatory T cells and mechanisms of immune system control. Nat Med. 2004;10:801–5. Borsellino G, Kleinewietfeld M, Di Mitri D, Sternjak A, Diamantini A, Giometto R, Hopner S, Centonze D, Bernardi G, Dell'Acqua ML, et al. Expression of ectonucleotidase CD39 by Foxp3 + Treg cells: hydrolysis of extracellular ATP and immune suppression. Blood. 2007;110:1225–32. Gupta PK, Godec J, Wolski D, Adland E, Yates K, Pauken KE, Cosgrove C, Ledderose C, Junger WG, Robson SC, et al. CD39 Expression Identifies Terminally Exhausted CD8 + T Cells. PLoS Pathog. 2015;11:e1005177. Additional Declarations No competing interests reported. Supplementary Files SupplementalMaterial.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3971739","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":274207305,"identity":"056307ff-c69d-4ddc-99af-aac2bdc0aaf1","order_by":0,"name":"Xiao-feng Xiong","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Xiao-feng","middleName":"","lastName":"Xiong","suffix":""},{"id":274207306,"identity":"9cb1954e-d790-45c7-bb3f-109e5c1b879b","order_by":1,"name":"Min Zhu","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Zhu","suffix":""},{"id":274207307,"identity":"a6218468-8e2e-400f-bccf-674ff26fe24e","order_by":2,"name":"Hong-xia Wu","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Hong-xia","middleName":"","lastName":"Wu","suffix":""},{"id":274207308,"identity":"54beabfe-38e1-4d4e-a69d-ce2913f0dee8","order_by":3,"name":"Zuo-hong Wu","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Zuo-hong","middleName":"","lastName":"Wu","suffix":""},{"id":274207309,"identity":"d65678fd-1f5e-4dd0-b8e2-8c34697f4bdb","order_by":4,"name":"Li-li Fan","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Li-li","middleName":"","lastName":"Fan","suffix":""},{"id":274207310,"identity":"f5cf4aad-c41c-4bb6-9530-77b39e14c7ba","order_by":5,"name":"De-yun Cheng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYDACCRDBBuNVSMjJk6jljIWxYQNJWhjbKhIZDhDQwT+7+djDL2U2iRtutz/8zDtPIoGxgfnhoxv4LLlzLN1Y5lxa4oY7Z4ylebdJ5LEzsBkb5+DRYiCRYyYt2XY4ccONHDZmoJZixgYeNmn8WvK/AbX8B2pJf8bMO0ciseEAQS05bJIf2w4AtSSYMfM2EKFF4kaamTTDuWTjmTdyjCXnHJMwNmwm4Bf+GcnPJH+U2cn23Uh/+OFNTZ2cPHvzw8f4tIAAMw8Dg2MDgktAOQgw/mBgsCdC3SgYBaNgFIxUAADBGUr97WZYxgAAAABJRU5ErkJggg==","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"De-yun","middleName":"","lastName":"Cheng","suffix":""}],"badges":[],"createdAt":"2024-02-20 05:24:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3971739/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3971739/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51568334,"identity":"b227f183-1e46-43b1-ab70-d1da16b241d5","added_by":"auto","created_at":"2024-02-23 20:29:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":373172,"visible":true,"origin":"","legend":"\u003cp\u003eParental proportions of general T cell subsets in peripheral blood among three groups. CD3+ T cells (A, B), CD8+ T cells (C, D), CD4+ T cells (C, E), CD4+ /CD8+ T cells(F). Data are expressed as mean number of each group (mean ± SD).\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3971739/v1/65c42b575d03017e1f96ac57.png"},{"id":51568333,"identity":"22895258-43f4-4dab-be30-8cc327ec7229","added_by":"auto","created_at":"2024-02-23 20:29:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":839559,"visible":true,"origin":"","legend":"\u003cp\u003eParental proportions of HLA-DR+ T cell subsets in peripheral blood among three groups. CD3+HLA-DR+ T cells (A, B), CD8+ HLA-DR+ T cells(C, D), CD4+ HLA-DR+T cells (E, F), CD8+TCR aβ+ HLA-DR+ T cells (G, H), CD4+TCR aβ+ HLA-DR+ cells (I, J). Data are expressed as mean number of each group (mean ± SD).\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3971739/v1/73b36ddb023b81926c227fff.png"},{"id":51568335,"identity":"6393ad97-4a98-4387-8165-a9b1b7d0fab3","added_by":"auto","created_at":"2024-02-23 20:29:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":912789,"visible":true,"origin":"","legend":"\u003cp\u003eParental proportions of CD57+ and PD1+ T cell subsets in peripheral blood among three groups.CD3+ CD57+ T cells (A, B), CD8+ CD57+ T cells (C, D), CD4+ CD57+ T cells (E, F), CD3+ PD-1+ T cells (G, H), CD8+ PD-1+ T cells (I, J), CD4+ PD-1+ T cells (K, L). Data are expressed as mean number of each group (mean ± SD).\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3971739/v1/5deb56c48a55c3007f9e612b.png"},{"id":51568336,"identity":"8a5ab9f8-2861-4a18-bcfc-b4709770ce1b","added_by":"auto","created_at":"2024-02-23 20:29:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1519327,"visible":true,"origin":"","legend":"\u003cp\u003eParental proportions of antigen response T cell subsets, antigen response T cell subsets and regulatory T cell subsets in peripheral blood among three groups.CD4+CD27+CD28+ T cells (A, B), CD4+CD27-CD28- T cells (C, D), CD4+ Central Memory T cells (E, F), CD4+ Effector Memory T cells (G, H), CD4+ CD39+ T cells (I, J), CD4+CD25+Foxp3+ T cells (K, L). Data are expressed as mean number of each group (mean ± SD).\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3971739/v1/3e492f48fbe423e4936870e0.png"},{"id":51568338,"identity":"bd5a7f8b-1037-4a9a-b00b-60ed9c23b4b7","added_by":"auto","created_at":"2024-02-23 20:29:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1247929,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the correlation between the proportion of T cell subsets in peripheral blood and CAT score. CD3+HLA-DR+ T cells (A), CD8+HLA-DR+ T cells(B), CD4+CD57+ T cells(C), CD3+PD-1+ T cells(D), CD8+PD-1+ T cells(E), CD4+PD-1+ T cells(F), CD4+CD27-CD28- T cells (G), CD4+ Effector Memory T cells (H), CD4+CD27+CD28+ T cells (I), CD8+ Central Memory T cells (J), and CD4+ Central Memory T cells (K).\u003c/p\u003e","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3971739/v1/b5ca2407b638262f5bca3591.png"},{"id":51794028,"identity":"13ff377b-014c-4a61-a061-ff27eaa2d6f7","added_by":"auto","created_at":"2024-02-29 06:52:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2239591,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3971739/v1/92377350-b547-4a6d-b88a-bf74a98faa78.pdf"},{"id":51568339,"identity":"2df8bc14-14ff-43d5-9f99-cf95c1d99ad3","added_by":"auto","created_at":"2024-02-23 20:29:46","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":49063424,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalMaterial.doc","url":"https://assets-eu.researchsquare.com/files/rs-3971739/v1/78bb57fbbafb309692364ca8.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"T cell immune status in patients with acute exacerbation of chronic obstructive pulmonary disease: A case-control study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. COPD is prevalent in 13.7% of Chinese adults aged over 40 years[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and more than 5.4\u0026nbsp;million people are projected to die from COPD and related diseases by 2060[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. COPD manifests in two distinct phases: stable COPD (SCOPD) and acute exacerbations of COPD (AECOPD). The latter can cause rapid decline in lung function and severely impair patients\u0026rsquo; quality of life[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe inflammatory response associated with COPD exhibits notable heterogeneity. This response is characterized by an aberrant activation of the innate immune system, predominantly mediated by neutrophils and macrophages in pulmonary regions, coupled with systemic inflammation. Furthermore, the engagement of T lymphocytes in the adaptive immune response contributes to the chronicity and exacerbation of inflammation, which furthers the development of emphysema and culminates in airway remodeling[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The immune-mediated inflammatory response may be pivotal in the pathogenesis and progression of COPD. However, there is ongoing debate regarding whether disparities exist in the distribution of T cell subsets in the different phases of COPD.\u003c/p\u003e \u003cp\u003eThe pathogenesis of COPD is yet to be fully elucidated, but the immune inflammatory response is said to play an important role in its occurrence and development. Autoimmune abnormalities have recently been found to promote the development of COPD, providing a new perspective for understanding the pathogenesis of the disease[\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. current clinical studies predominantly limit their scope to a primary analysis of peripheral blood T lymphocytes, including CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;cells, without an exhaustive and detailed examination of the more nuanced T cell subsets. To date, no clinical research has comprehensively observed the distribution and functional status of T cell subsets in the peripheral blood at different phases of COPD.\u003c/p\u003e \u003cp\u003eThus, this study aimed to investigate the distribution and functional status of T cell subsets in different phases of COPD to provide a clinical and theoretical basis for understanding the immunological mechanism of COPD.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and subjects\u003c/h2\u003e \u003cp\u003e This observational case-control study was conducted in accordance with the Declaration of Helsinki and was approved by the institutional ethics committees of West China Hospital of Sichuan University (identification no. 2018 [283]). The study was registered in the China Clinical Trials Registry on September 19, 2018 (ChiCTR1800018452). Written informed consent was obtained from all participants.\u003c/p\u003e \u003cp\u003e AECOPD and SCOPD patients were recruited in the Department of Respiratory and Critical Care Medicine of West China Hospital from September 2018 to October 2019. All COPD patients were diagnosed according to the 2017 Global initiative for chronic obstructive lung disease (GOLD) guidelines[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Healthy controls (HCs) were matched for age and sex to the patients. The HCs and patients were recruited according to the key inclusion and exclusion criteria (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Subject demographic and clinical characteristics, including age, sex, body mass index, smoking history, and comorbidities, were recorded. The pulmonary function test was performed in all HCs, SCOPD patients, and AECOPD patients with permissible conditions. COPD symptoms were evaluated according to the COPD assessment test (CAT), and the modified British Medical Research Council (mMRC) dyspnea scale[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and AECOPD patients were assessed within 48 hours after admission. AECOPD patients received the standardized treatment regimen including (but not limited to) antibiotics, a systemic corticosteroid, a short-acting inhaled β2 agonist, a short-acting anticholinergic, and oxygen therapy. The patient inclusion flowchart is shown in Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInclusion and exclusion criteria of study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInclusion criteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExclusion criteria\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; age\u0026thinsp;\u0026ge;\u0026thinsp;40 years;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1) Had a history of systemic corticosteroid therapy (prednisone\u0026thinsp;\u0026gt;\u0026thinsp;0.5 mg/kg or equivalent doses) within 1 month;\u003c/p\u003e \u003cp\u003e2) Had a history of diseases that affect immune cells, such as connective tissue diseases, immunological diseases, hematological diseases, hepar and renal failure;\u003c/p\u003e \u003cp\u003e3) Had a history of asthma, allergic disease, or other clinically significant lung diseases;\u003c/p\u003e \u003cp\u003e4) Had a history of heart failure, arrhythmia, mental disorders, or any malignancy.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; SCOPD is defined as respiratory symptoms were stable or mild, and the condition was stable for 3 months.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; AECOPD is defined as an acute worsening of respiratory symptoms that results in additional therapy.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; HCs: COPD-free individuals with normal pulmonary function.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAECOPD, acute exacerbation of chronic obstructive pulmonary disease; SCOPD, stable chronic obstructive pulmonary disease;HCs, healthy controls.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eBlood collection and flow cytometry\u003c/h2\u003e \u003cp\u003eThe blood, used for routine blood and T cell subsets test, was collected before receiving systemic corticosteroid therapy (prednisone\u0026thinsp;\u0026gt;\u0026thinsp;0.5 mg/kg or equivalent doses) and tested within 24 hours. The blood routine test was completed by the Clinical Laboratory Department of West China Hospital of Sichuan University.\u003c/p\u003e \u003cp\u003eFor flow cytometry, flow cytometric fluorescent anti-human monoclonal cell surface antibody (dry powder) tubes (DuraClone IM panels: T cell, TCRs, and Treg subsets) were purchased from Beckman Coulter (Brea, CA, USA). All operations refer to product instructions. The fluorochrome-conjugated antibody, schemes of fluorochrome channel, and compensation controls (each of a single color) are described in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. All samples were analyzed with a 13-Color CytoFlex Flow Cytometer (Beckman Coulter, Brea, CA, USA) after daily calibration with Flow-Set Pro Beads (Beckman Coulter, Brea, CA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStrategies for T cell subsets gating\u003c/h2\u003e \u003cp\u003eThe classification of T cell subsets is shown in Figure S2, and strategies for T cell subsets gating are shown in Figures S3-5. We used a two-parameter scatter plot composed of CD45 and forward scatter area to gate the lymphocytes. The CD3\u0026thinsp;+\u0026thinsp;cell population was defined as the total T cells and categorized into seven populations using the human leukocyte antigen-DR (HLA-DR), CD57, programmed death receptor 1(PD-1), TCR, CD8, and CD4 markers as follows: (1) HLA-DR\u0026thinsp;+\u0026thinsp;T cells, (2) CD57\u0026thinsp;+\u0026thinsp;T cells, (3) PD-1\u0026thinsp;+\u0026thinsp;T cells. (4) TCR aβ\u0026thinsp;+\u0026thinsp;T cells, (5) TCR γδ\u0026thinsp;+\u0026thinsp;T cells, (6) CD8\u0026thinsp;+\u0026thinsp;T cells, and (7) CD4\u0026thinsp;+\u0026thinsp;T cells. CD8\u0026thinsp;+\u0026thinsp;T cells were divided into 4 subtypes: (1) CD8\u0026thinsp;+\u0026thinsp;CD57\u0026thinsp;+\u0026thinsp;T cells, (2) CD8\u0026thinsp;+\u0026thinsp;PD-1\u0026thinsp;+\u0026thinsp;T cells, (3) costimulatory molecules (CD8\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28- T cells, CD8\u0026thinsp;+\u0026thinsp;CD27-CD28\u0026thinsp;+\u0026thinsp;T cells, and CD8\u0026thinsp;+\u0026thinsp;CD27-CD28- T cells), and (4) CD45RA and CCR7 expressing (CD8\u0026thinsp;+\u0026thinsp;effector T cells, CD8\u0026thinsp;+\u0026thinsp;central memory T cells, CD8\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve T cells, CD8\u0026thinsp;+\u0026thinsp;effector memory T cells). Finally, CD4\u0026thinsp;+\u0026thinsp;T cells were divided into the following 5 subtypes: (1) CD4\u0026thinsp;+\u0026thinsp;CD57\u0026thinsp;+\u0026thinsp;T cells, (2) CD4\u0026thinsp;+\u0026thinsp;PD-1\u0026thinsp;+\u0026thinsp;T cells, (3) costimulatory molecules (CD4\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28\u0026thinsp;+\u0026thinsp;T cells, CD4\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28- T cells, CD4\u0026thinsp;+\u0026thinsp;CD27-CD28\u0026thinsp;+\u0026thinsp;T cells, CD4\u0026thinsp;+\u0026thinsp;CD27-CD28- T cells), (4) antigen responses (CD4\u0026thinsp;+\u0026thinsp;effector T cells, CD4\u0026thinsp;+\u0026thinsp;central memory T cells, CD4\u0026thinsp;+\u0026thinsp;na\u0026iuml;ve T cells, CD4\u0026thinsp;+\u0026thinsp;effector memory T cells), and (5) regulatory T cells (CD4\u0026thinsp;+\u0026thinsp;CD39\u0026thinsp;+\u0026thinsp;T cells, CD4\u0026thinsp;+\u0026thinsp;CD25\u0026thinsp;+\u0026thinsp;Forkhead box protein 3 (FoxP3)\u0026thinsp;+\u0026thinsp;T cells, CD4\u0026thinsp;+\u0026thinsp;CD45RA\u0026thinsp;+\u0026thinsp;T cells, CD4\u0026thinsp;+\u0026thinsp;Helios\u0026thinsp;+\u0026thinsp;T cells, CD4\u0026thinsp;+\u0026thinsp;FoxP3\u0026thinsp;+\u0026thinsp;Helios\u0026thinsp;+\u0026thinsp;T cells).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eNormally distributed data were described as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (SD), whereas nonnormally distributed data were reported as medians (interquartile range, IQR) unless otherwise indicated. Continuous parametric data, including CAT scores, WBC levels, pulmonary function test indices, and T cell subset percentages, were analyzed using Student\u0026rsquo;s t-test or one-way analysis of variance (ANOVA), continuous nonparametric data were analyzed using the Mann\u0026ndash;Whitney U or Kruskal\u0026ndash;Wallis test. Correlation analyses between the proportion of T cell subsets and symptom score and lung function were performed by using the Pearson or Spearman correlation test. All statistical analyses were performed using SPSS 24.0 (IBM, Armonk, NY, USA), and a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSubject baseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 43 HCs, 43 SCOPD patients, and 64 AECOPD patients were recruited. The clinicodemographic characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table S2. Compared with the SCOPD group, the AECOPD group had worse symptom control and pulmonary function.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eDemographic and Clinical characteristics of subjects at baseline\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy Control\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSCOPD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAECOPD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients(n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.07\u0026thinsp;\u0026plusmn;\u0026thinsp;7.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.12\u0026thinsp;\u0026plusmn;\u0026thinsp;9.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.78\u0026thinsp;\u0026plusmn;\u0026thinsp;7.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30(69.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49(76.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent/Ever smoker, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(76.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45(70.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoker, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(29.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePack years smoked \u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0,350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e740(100,960)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e525(0,900)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.99\u0026thinsp;\u0026plusmn;\u0026thinsp;2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.59\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.04\u0026thinsp;\u0026plusmn;\u0026thinsp;4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e(L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e% pred\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.37\u0026thinsp;\u0026plusmn;\u0026thinsp;14.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.49\u0026thinsp;\u0026plusmn;\u0026thinsp;21.90\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.27\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC(L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e/FVC (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.34\u0026thinsp;\u0026plusmn;\u0026thinsp;11.61\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.64\u0026thinsp;\u0026plusmn;\u0026thinsp;19.93\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocyte count,10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.91\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil count ,10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.60\u0026thinsp;\u0026plusmn;\u0026thinsp;3.35\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte count,10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte count,10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophil count,10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.43\u0026thinsp;\u0026plusmn;\u0026thinsp;8.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.37\u0026thinsp;\u0026plusmn;\u0026thinsp;7.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.79\u0026thinsp;\u0026plusmn;\u0026thinsp;15.84\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.72\u0026thinsp;\u0026plusmn;\u0026thinsp;9.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.29\u0026thinsp;\u0026plusmn;\u0026thinsp;7.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.93\u0026thinsp;\u0026plusmn;\u0026thinsp;8.54\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.92\u0026thinsp;\u0026plusmn;\u0026thinsp;2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophil, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003csup\u003e△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD unless specified. \u003csup\u003e\u0026yen;\u003c/sup\u003emedian (interquartile range). Pack years smoked, cigarettes per day \u0026times; smoking years. *: AECOPD vs. Healthy control, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e△\u003c/sup\u003e: AECOPD vs. SCOPD, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e#\u003c/sup\u003e: SCOPD vs. Healthy control, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eAECOPD, Acute exacerbation of chronic obstructive pulmonary disease; SCOPD, Stable chronic obstructive pulmonary disease; BMI, body mass index; FEV\u003csub\u003e1\u003c/sub\u003e, forced expiratory volume in one second, FVC, forced vital capacity; mMRC, modified medical research council dyspnea scale; CAT, COPD assessment test.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of the general T cell subsets\u003c/h2\u003e \u003cp\u003eThe distribution of the T cell subsets detected for CD3\u0026thinsp;+\u0026thinsp;T cells and their two main subsets (CD8\u0026thinsp;+\u0026thinsp;and CD4\u0026thinsp;+\u0026thinsp;T cells) is detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There was no significant difference in the proportion of CD3\u0026thinsp;+\u0026thinsp;T cells among the three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, B). The proportion of CD8\u0026thinsp;+\u0026thinsp;T cells was significantly higher in the AECOPD group than in the HC and SCOPD groups (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.004 and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.065, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, D). In contrast, the proportion of CD3\u0026thinsp;+\u0026thinsp;CD4\u0026thinsp;+\u0026thinsp;T cells and the CD4+/CD8\u0026thinsp;+\u0026thinsp;T cells ratio were significantly lower in the AECOPD group than in the HC group (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.042 and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.303, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE, F). Compared with the HC group, the SCOPD group had a higher proportion of CD3\u0026thinsp;+\u0026thinsp;CD8\u0026thinsp;+\u0026thinsp;T cells and a lower proportion of CD3\u0026thinsp;+\u0026thinsp;CD4\u0026thinsp;+\u0026thinsp;T cells, but the difference was not statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eThe proportion of T cell subsets in Peripheral Blood of subjects\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT cell subsets\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy Control\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSCOPD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAECOPD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3+ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e71.87\u0026thinsp;\u0026plusmn;\u0026thinsp;8.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e67.98\u0026thinsp;\u0026plusmn;\u0026thinsp;10.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e69.55\u0026thinsp;\u0026plusmn;\u0026thinsp;13.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u0026thinsp;+\u0026thinsp;CD8+ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e36.88\u0026thinsp;\u0026plusmn;\u0026thinsp;9.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e39.15\u0026thinsp;\u0026plusmn;\u0026thinsp;10.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e43.21\u0026thinsp;\u0026plusmn;\u0026thinsp;12.06\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u0026thinsp;+\u0026thinsp;CD4+ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e56.16\u0026thinsp;\u0026plusmn;\u0026thinsp;10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e54.04\u0026thinsp;\u0026plusmn;\u0026thinsp;11.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e50.33\u0026thinsp;\u0026plusmn;\u0026thinsp;13.25\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4+/ CD8+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u0026thinsp;+\u0026thinsp;HLA-DR+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e39.10\u0026thinsp;\u0026plusmn;\u0026thinsp;13.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e44.97\u0026thinsp;\u0026plusmn;\u0026thinsp;12.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e48.83\u0026thinsp;\u0026plusmn;\u0026thinsp;17.26\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;HLA-DR+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e58.92\u0026thinsp;\u0026plusmn;\u0026thinsp;17.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e64.81\u0026thinsp;\u0026plusmn;\u0026thinsp;13.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e68.95\u0026thinsp;\u0026plusmn;\u0026thinsp;15.63\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;HLA-DR+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.24\u0026thinsp;\u0026plusmn;\u0026thinsp;9.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e25.31\u0026thinsp;\u0026plusmn;\u0026thinsp;10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e29.23\u0026thinsp;\u0026plusmn;\u0026thinsp;15.43\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;TCR aβ\u0026thinsp;+\u0026thinsp;HLA-DR+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e58.40\u0026thinsp;\u0026plusmn;\u0026thinsp;17.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e63.84\u0026thinsp;\u0026plusmn;\u0026thinsp;13.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e68.59\u0026thinsp;\u0026plusmn;\u0026thinsp;16.05\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;TCR aβ\u0026thinsp;+\u0026thinsp;HLA-DR+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.01\u0026thinsp;\u0026plusmn;\u0026thinsp;9.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e25.10\u0026thinsp;\u0026plusmn;\u0026thinsp;10.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e29.03\u0026thinsp;\u0026plusmn;\u0026thinsp;15.43\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u0026thinsp;+\u0026thinsp;TCR aβ+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e92.43\u0026thinsp;\u0026plusmn;\u0026thinsp;6.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e92.61\u0026thinsp;\u0026plusmn;\u0026thinsp;5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e93.88\u0026thinsp;\u0026plusmn;\u0026thinsp;5.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;TCR aβ+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e38.97\u0026thinsp;\u0026plusmn;\u0026thinsp;12.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e39.36\u0026thinsp;\u0026plusmn;\u0026thinsp;11.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e30.95\u0026thinsp;\u0026plusmn;\u0026thinsp;13.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.692\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;TCR aβ+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e58.66\u0026thinsp;\u0026plusmn;\u0026thinsp;12.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e57.86\u0026thinsp;\u0026plusmn;\u0026thinsp;11.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e55.70\u0026thinsp;\u0026plusmn;\u0026thinsp;14.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u0026thinsp;+\u0026thinsp;TCR γδ+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.07\u0026thinsp;\u0026plusmn;\u0026thinsp;6.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.91\u0026thinsp;\u0026plusmn;\u0026thinsp;5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.65\u0026thinsp;\u0026plusmn;\u0026thinsp;5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u0026thinsp;+\u0026thinsp;CD57+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.88\u0026thinsp;\u0026plusmn;\u0026thinsp;11.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e26.48\u0026thinsp;\u0026plusmn;\u0026thinsp;11.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e30.61\u0026thinsp;\u0026plusmn;\u0026thinsp;16.70\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;CD57+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e43.58\u0026thinsp;\u0026plusmn;\u0026thinsp;16.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e47.54\u0026thinsp;\u0026plusmn;\u0026thinsp;15.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e47.24\u0026thinsp;\u0026plusmn;\u0026thinsp;17.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;CD57+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.43\u0026thinsp;\u0026plusmn;\u0026thinsp;4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.03\u0026thinsp;\u0026plusmn;\u0026thinsp;6.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e13.67\u0026thinsp;\u0026plusmn;\u0026thinsp;13.25\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD3\u0026thinsp;+\u0026thinsp;PD-1+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e37.89\u0026thinsp;\u0026plusmn;\u0026thinsp;7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e45.30\u0026thinsp;\u0026plusmn;\u0026thinsp;11.02\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e54.24\u0026thinsp;\u0026plusmn;\u0026thinsp;12.31\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;PD-1+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e34.79\u0026thinsp;\u0026plusmn;\u0026thinsp;11.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e35.81\u0026thinsp;\u0026plusmn;\u0026thinsp;11.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e43.84\u0026thinsp;\u0026plusmn;\u0026thinsp;16.33\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;PD-1+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e36.98\u0026thinsp;\u0026plusmn;\u0026thinsp;8.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e37.84\u0026thinsp;\u0026plusmn;\u0026thinsp;9.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e47.13\u0026thinsp;\u0026plusmn;\u0026thinsp;16.68\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e48.10\u0026thinsp;\u0026plusmn;\u0026thinsp;17.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e44.92\u0026thinsp;\u0026plusmn;\u0026thinsp;14.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e42.41\u0026thinsp;\u0026plusmn;\u0026thinsp;18.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.35\u0026thinsp;\u0026plusmn;\u0026thinsp;3.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.17\u0026thinsp;\u0026plusmn;\u0026thinsp;5.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e9.02\u0026thinsp;\u0026plusmn;\u0026thinsp;5.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;CD27-CD28+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.18\u0026thinsp;\u0026plusmn;\u0026thinsp;5.44\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;CD27-CD28-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e40.42\u0026thinsp;\u0026plusmn;\u0026thinsp;16.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e40.73\u0026thinsp;\u0026plusmn;\u0026thinsp;15.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e43.66\u0026thinsp;\u0026plusmn;\u0026thinsp;18.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.548\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e84.70\u0026thinsp;\u0026plusmn;\u0026thinsp;7.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e84.50\u0026thinsp;\u0026plusmn;\u0026thinsp;8.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e78.52\u0026thinsp;\u0026plusmn;\u0026thinsp;16.14\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;CD27-CD28+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.15\u0026thinsp;\u0026plusmn;\u0026thinsp;4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.95\u0026thinsp;\u0026plusmn;\u0026thinsp;3.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e9.83\u0026thinsp;\u0026plusmn;\u0026thinsp;6.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;CD27-CD28-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.02\u0026thinsp;\u0026plusmn;\u0026thinsp;4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.46\u0026thinsp;\u0026plusmn;\u0026thinsp;6.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e11.52\u0026thinsp;\u0026plusmn;\u0026thinsp;12.48\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;Effector T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e33.44\u0026thinsp;\u0026plusmn;\u0026thinsp;15.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e33.31\u0026thinsp;\u0026plusmn;\u0026thinsp;16.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.65\u0026thinsp;\u0026plusmn;\u0026thinsp;17.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;Central Memory T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e16.26\u0026thinsp;\u0026plusmn;\u0026thinsp;8.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e19.31\u0026thinsp;\u0026plusmn;\u0026thinsp;8.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e14.48\u0026thinsp;\u0026plusmn;\u0026thinsp;9.43\u003csup\u003e△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;Na\u0026iuml;ve T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e17.17\u0026thinsp;\u0026plusmn;\u0026thinsp;11.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.45\u0026thinsp;\u0026plusmn;\u0026thinsp;7.95\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e12.59\u0026thinsp;\u0026plusmn;\u0026thinsp;12.54\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;Effector Memory T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e34.13\u0026thinsp;\u0026plusmn;\u0026thinsp;13.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e36.93\u0026thinsp;\u0026plusmn;\u0026thinsp;12.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e41.29\u0026thinsp;\u0026plusmn;\u0026thinsp;16.18\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;Effector T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.68\u0026thinsp;\u0026plusmn;\u0026thinsp;4.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;Central Memory T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e65.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e67.90\u0026thinsp;\u0026plusmn;\u0026thinsp;9.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e58.11\u0026thinsp;\u0026plusmn;\u0026thinsp;15.48\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;Na\u0026iuml;ve T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e17.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.94\u0026thinsp;\u0026plusmn;\u0026thinsp;8.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e16.59\u0026thinsp;\u0026plusmn;\u0026thinsp;13.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;Effector Memory T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e16.27\u0026thinsp;\u0026plusmn;\u0026thinsp;6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e17.33\u0026thinsp;\u0026plusmn;\u0026thinsp;8.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e23.61\u0026thinsp;\u0026plusmn;\u0026thinsp;15.70\u003csup\u003e*△\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;CD39+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.99\u0026thinsp;\u0026plusmn;\u0026thinsp;4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7.78\u0026thinsp;\u0026plusmn;\u0026thinsp;6.48\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e8.31\u0026thinsp;\u0026plusmn;\u0026thinsp;6.70\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;CD25\u0026thinsp;+\u0026thinsp;FoxP3+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e9.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.91\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;CD45RA+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.33\u0026thinsp;\u0026plusmn;\u0026thinsp;8.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.43\u0026thinsp;\u0026plusmn;\u0026thinsp;9.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e19.98\u0026thinsp;\u0026plusmn;\u0026thinsp;13.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;Helios+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.74\u0026thinsp;\u0026plusmn;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;FoxP3\u0026thinsp;+\u0026thinsp;Helios+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. *: AECOPD vs. Healthy control, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e△\u003c/sup\u003e: AECOPD vs. SCOPD, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e#\u003c/sup\u003e: SCOPD vs. Healthy control, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eAECOPD, Acute exacerbation of chronic obstructive pulmonary disease; SCOPD, Stable chronic obstructive pulmonary disease.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of HLA-DR\u0026thinsp;+\u0026thinsp;T cell and TCR cell subsets\u003c/h2\u003e \u003cp\u003eCompared with the HC group, the AECOPD group showed significantly higher percentages of CD3\u0026thinsp;+\u0026thinsp;HLA-DR\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.001), CD8\u0026thinsp;+\u0026thinsp;HLA-DR\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.001), CD4\u0026thinsp;+\u0026thinsp;HLA-DR\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.047), CD8\u0026thinsp;+\u0026thinsp;TCR aβ\u0026thinsp;+\u0026thinsp;HLA-DR\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.001), and CD4\u0026thinsp;+\u0026thinsp;TCR aβ\u0026thinsp;+\u0026thinsp;HLA-DR\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.046). However, although the distribution of these subsets was higher in the AECOPD group than in the SCOPD group, the difference was not statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). There was also no significant difference in the proportion of CD3\u0026thinsp;+\u0026thinsp;TCR aβ\u0026thinsp;+\u0026thinsp;T cells, CD3\u0026thinsp;+\u0026thinsp;TCR γδ\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;TCR aβ\u0026thinsp;+\u0026thinsp;T cells, and CD4\u0026thinsp;+\u0026thinsp;TCR aβ\u0026thinsp;+\u0026thinsp;T cells among the three groups (Figure S6).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of the CD57\u0026thinsp;+\u0026thinsp;and PD1\u0026thinsp;+\u0026thinsp;T cell subsets\u003c/h2\u003e \u003cp\u003eThe distribution of CD57\u0026thinsp;+\u0026thinsp;and PD1\u0026thinsp;+\u0026thinsp;T cell subsets is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The proportion of CD3\u0026thinsp;+\u0026thinsp;CD57\u0026thinsp;+\u0026thinsp;T cells in the peripheral blood was significantly higher in the AECOPD group than in the HC group (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.038, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B). Further, the proportion of CD4\u0026thinsp;+\u0026thinsp;CD57\u0026thinsp;+\u0026thinsp;T cells was significantly higher in the AECOPD group than in the SCOPD and HC groups (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001 and \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, F). Meanwhile, there was no significant difference in the proportion of CD8\u0026thinsp;+\u0026thinsp;CD57\u0026thinsp;+\u0026thinsp;T cells among the three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, D).\u003c/p\u003e \u003cp\u003eCompared with the HC group, the AECOPD and SCOPD groups had a significantly higher proportion of CD3\u0026thinsp;+\u0026thinsp;PD-1\u0026thinsp;+\u0026thinsp;T cells in the peripheral blood (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001 and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.002, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG, H). Concurrently, the proportions were significantly higher in the AECOPD group than in the SCOPD group (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001). Further analysis showed that the proportions of CD8\u0026thinsp;+\u0026thinsp;PD-1\u0026thinsp;+\u0026thinsp;T cells and CD4\u0026thinsp;+\u0026thinsp;PD-1\u0026thinsp;+\u0026thinsp;T cells were higher in the AECOPD group than in the SCOPD group (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.004 and \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001, respectively) and in the HC group (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.001 and \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI, J, K, L), but there were no significant differences between the SCOPD and the HC groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of T cell subsets of costimulatory molecules\u003c/h2\u003e \u003cp\u003eThe distribution of T cell subsets of costimulatory molecules is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The proportion of CD4\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28\u0026thinsp;+\u0026thinsp;T cells was significantly lower in the AECOPD group than in the SCOPD and HC groups (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.013 and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.010, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B). In contrast, the proportion of CD4\u0026thinsp;+\u0026thinsp;CD27-\u003c/p\u003e \u003cp\u003eCD28- T cells was significantly higher in the AECOPD group than in the SCOPD and HC groups (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.005 and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.003, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, D). There was no significant difference in the proportion of CD8\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;CD27-CD28- T cells, CD8\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28- T cells, CD4\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28- T cells, and CD4\u0026thinsp;+\u0026thinsp;CD27-CD28\u0026thinsp;+\u0026thinsp;T cells among the three groups (Figure. S7).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of T cell subsets in antigen response\u003c/h2\u003e \u003cp\u003eThe distribution of T cell subsets in antigen response is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and Figure S8. The proportion of CD4\u0026thinsp;+\u0026thinsp;central memory T cells was significantly lower in the AECOPD group than in the SCOPD and HC groups (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001 and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.005, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, F). In contrast, the proportion of CD4\u0026thinsp;+\u0026thinsp;effector memory T cells was significantly higher in the AECOPD group than in the SCOPD and HC groups (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.007 and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.002, respectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG, H).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of regulatory T cell subsets\u003c/h2\u003e \u003cp\u003eThe distribution of regulatory T cell subsets is detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The proportion of CD4\u0026thinsp;+\u0026thinsp;CD39\u0026thinsp;+\u0026thinsp;T cells was significantly higher in the AECOPD and SCOPD groups than in the HC group (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.006 and \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.032, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI, J), while there was no significant difference between the AECOPD and SCOPD groups. Similarly, the proportion of CD4\u0026thinsp;+\u0026thinsp;CD25\u0026thinsp;+\u0026thinsp;FoxP3\u0026thinsp;+\u0026thinsp;T cells was significantly higher in the AECOPD and SCOPD groups than in the HC group (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001 and \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK, L).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation Analyses\u003c/h2\u003e \u003cp\u003eResults of correlation analyses in COPD patients are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Table S3. The CAT score was positively correlated with the proportion of CD3\u0026thinsp;+\u0026thinsp;HLA-DR\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003er\u0026thinsp;=\u0026thinsp;0.191\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.048\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), CD8\u0026thinsp;+\u0026thinsp;HLA-DR\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003er\u0026thinsp;=\u0026thinsp;0.207\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.032\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB), CD4\u0026thinsp;+\u0026thinsp;CD57\u0026thinsp;+\u0026thinsp;T cells \u003cem\u003e(r\u0026thinsp;=\u0026thinsp;0.223\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.021\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC), CD3\u0026thinsp;+\u0026thinsp;PD-1\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003er\u0026thinsp;=\u0026thinsp;0.304\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.001\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD), CD8\u0026thinsp;+\u0026thinsp;PD-1\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003er\u0026thinsp;=\u0026thinsp;0.195\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.044\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE), CD4\u0026thinsp;+\u0026thinsp;PD-1\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003er\u0026thinsp;=\u0026thinsp;0.319\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.001\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF), CD4\u0026thinsp;+\u0026thinsp;CD27-CD28- T cells (\u003cem\u003er\u0026thinsp;=\u0026thinsp;0.215\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.005\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG), and CD4\u0026thinsp;+\u0026thinsp;Effector Memory T cells (\u003cem\u003er\u0026thinsp;=\u0026thinsp;0.229\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.018\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH). On the contrary, the CAT score was negatively correlated with the proportion of CD4\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28\u0026thinsp;+\u0026thinsp;T cells (\u003cem\u003er = -0.206\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.033\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI), CD8\u0026thinsp;+\u0026thinsp;Central Memory T cells (\u003cem\u003er = -0.268\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.005\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ), and CD4\u0026thinsp;+\u0026thinsp;Central Memory T cells (\u003cem\u003er = -0.232\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.016\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK). The correlation between the proportion of T cell subsets and mMRC score, FVC, and FEV\u003csub\u003e1\u003c/sub\u003e% pred is presented in Table S3.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe distribution and functional status of T cell subsets in the peripheral blood at different phases of COPD are yet to be clarified to date. This study found that the distribution of nearly half the T cell subsets in AECOPD patients was significantly different from that in SCOPD patients and HCs. This study comprehensively detected the distribution and functional status of T cell subsets in the peripheral blood of AECOPD and SCOPD patients and compared them with those in HCs, using multi-color flow cytometry.\u003c/p\u003e \u003cp\u003eT cells mainly function as mediators of the cellular immune response [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. We found that compared with the HC group, the AECOPD group had a significantly higher proportion of CD8\u0026thinsp;+\u0026thinsp;T cells and a significantly lower proportion of CD4\u0026thinsp;+\u0026thinsp;T cells. This is consistent with the results of previous studies and indicates that the cellular immune function is suppressed[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Further, we found that the number and distribution ratio of peripheral blood T cells in AECOPD patients were significantly different from those in HCs, and there was obvious inhibition of cellular immune function. However, this was not observed in patients with SCOPD, indicating that immune abnormalities differ according to the phase of COPD.\u003c/p\u003e \u003cp\u003eThe first stage of T cell immune function is the activation of T cells. HLA-DR is a marker of T cell activation, but few studies have focused on HLA-DR and COPD[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The current study found that HLA-DR expression in CD3+, CD4+, and CD8\u0026thinsp;+\u0026thinsp;T cells was significantly higher in the AECOPD group than in the HC group. However, there was no significant difference between the SCOPD groups and HC group, consistent with the findings by Pons et al.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], who found no significant difference in HLA-DR expression in the peripheral blood between SCOPD patients and healthy non-smokers. In contrast, Ying[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] found a significantly higher CD4\u0026thinsp;+\u0026thinsp;HLA-DR expression in patients with SCOPD when compared to normal controls and smokers. However, neither of the above two studies included AECOPD patients. Khalaf et al.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found that HLA-DR expression was upregulated after the alveolar macrophages of COPD patients were infected by \u003cem\u003eHaemophilus influenzae\u003c/em\u003e. In summary, the distribution of HLA-DR labeled T cells in stable COPD is still controversial, and the distribution in AECOPD patients has not been reported previously. Our findings suggest higher activated T cells in the peripheral blood in AECOPD patients than in HCs. The abnormal activation of T cells may be related to the acute aggravating factors (such as infection) in AECOPD patients.\u003c/p\u003e \u003cp\u003eCD57\u0026thinsp;+\u0026thinsp;T cells are very minimally expressed in the peripheral blood of newborns; however, it is upregulated in chronic infection and elderly patients[\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, CD57\u0026thinsp;+\u0026thinsp;T cells in the peripheral blood are usually regarded as terminally differentiated or senescent T cells. Olloquequi et al.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] found a significantly higher density of CD57\u0026thinsp;+\u0026thinsp;cells in pulmonary lymphoid follicles in COPD patients than in healthy non-smokers and smokers. Compared with moderate COPD patients, extremely severe COPD patients have a significantly higher density of CD57\u0026thinsp;+\u0026thinsp;cells in the small airways\u003csub\u003e[26]\u003c/sub\u003e. The status of CD57\u0026thinsp;+\u0026thinsp;T cells in the peripheral blood in patients with AECOPD has not been reported to date. As such, there is an important implication to our finding that the proportion of CD57\u0026thinsp;+\u0026thinsp;T cells in the peripheral blood is higher in the AECOPD group than in the SCOPD and HC groups. This finding indicates that there is an increase of T cell senescence in AECOPD patients, further supporting the obvious inhibition of cellular immune function in AECOPD patients.\u003c/p\u003e \u003cp\u003ePD-1 is an important member of the CD28 family. Previous studies have shown that PD-1 expression in CD4\u0026thinsp;+\u0026thinsp;T cells[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and CD8\u0026thinsp;+\u0026thinsp;T[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] cells in the peripheral blood is higher in SCOPD patients than in healthy subjects. Contrasting results were observed in the current study, and this could be due to the difference in sample size or methods of sample treatment. However, few studies have focused on PD-1 in AECOPD patients. Only Tan et al.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] reported that PD-1 expression in peripheral blood CD4\u0026thinsp;+\u0026thinsp;T cells is increased in AECOPD patients. Consistently, the current study showed upregulated PD-1 expression in CD3\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells in AECOPD patients. Biton et al.[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] studied the effect of COPD on non-small cell lung cancer and found that upregulated PD-1 expression in tumor-infiltrating CD8\u0026thinsp;+\u0026thinsp;T cells of lung cancer patients with COPD. McKendry et al.[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] also reported higher PD-1 expression in CD4\u0026thinsp;+\u0026thinsp;T cells and CD8\u0026thinsp;+\u0026thinsp;T cells in the lung tissue of COPD patients than in HCs. Collectively, these findings support upregulated PD-1 expression in persistent inflammatory immune response. PD-1 is a negative regulatory costimulatory factor on effector T cells, mediating T cell apoptosis by binding to its ligands and playing an important role in cellular immunosuppression and immune tolerance[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Therefore, PD-1 expression in peripheral T cells is increased in AECOPD patients, suggesting that more effector T cells may be undergoing apoptosis and reversible failure in AECOPD patients. Importantly, these indicate immunosuppression in AECOPD patients.\u003c/p\u003e \u003cp\u003eAs the second signal, the costimulatory molecules CD27 and CD28 play important roles in the initial complete activation of T cells[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. They are also the targets of immunosuppressive therapy. Our results showed that CD27\u0026thinsp;+\u0026thinsp;CD28+ (double positive costimulatory molecule) CD4\u0026thinsp;+\u0026thinsp;T cells were decreased while CD27-CD28- (double negative) CD4\u0026thinsp;+\u0026thinsp;T cells were increased in the peripheral blood of AECOPD patients. Some studies have shown that the proliferation of highly differentiated CD28- T cells related to immune aging is associated with a stronger immunosuppression[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Therefore, the increase in CD4\u0026thinsp;+\u0026thinsp;CD27-CD28- T cells further supports the view that there is immunosuppression in AECOPD patients.\u003c/p\u003e \u003cp\u003eCD39 is an extracellular nucleotidase that hydrolyzes extracellular ATP and ADP into adenosine monophosphate (AMP) and CD73 and converts AMP into adenosine. Tan et al.[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] reported that CD39 expression in CD4+, CD8+, FoxP3+, and FoxP3- T cells in the peripheral blood are increased in AECOPD patients. Consistent results were obtained in the current study. We also found that the proportion of CD4\u0026thinsp;+\u0026thinsp;CD25\u0026thinsp;+\u0026thinsp;FoxP3\u0026thinsp;+\u0026thinsp;T cells (Tregs) in the peripheral blood is increased in patients with AECOPD and SCOPD. Previous studies have shown that CD39 is highly expressed in Treg cells, which is important for its immunosuppressive function[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The high expression of CD39 is associated with other markers of T cell depletion or dysfunction, including high expression of PD-1, low expression of CD28, and production of IFN-γ[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. CD39 may promote immune failure in patients with COPD and inhibit a protective immune response.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has some limitations. First, this was a cross-sectional study and can thus only establish the relationship between AECOPD and immune indicators and cannot suggest causality. However, it provides the basis for further prospective follow-up studies. Second, due to the inclusion of the HC group, it was ethically impossible to further obtain lung tissue samples to understand the situation of immune cells in the airway and lungs. Finally, AECOPD patients had more acute exacerbations and acute hospitalizations over the past year than did SCOPD patients. They also had more severe symptoms, as indicated by higher mMRC and CAT scores. It is speculated that the acute exacerbation and stable phase may also be related to the severity of the disease, and this needs to be confirmed in further subgroup studies with a larger sample size.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe distribution of nearly half the T cell subsets in AECOPD patients was significantly different from that in SCOPD patients and HCs. Among patients with AECOPD, the total number of lymphocytes, the percentage of lymphocytes, and the CD4+/CD8\u0026thinsp;+\u0026thinsp;T cells ratio in the peripheral blood were significantly lower, while the proportion of negative regulatory cells (CD4\u0026thinsp;+\u0026thinsp;CD27-CD28- T cells, CD4\u0026thinsp;+\u0026thinsp;CD39\u0026thinsp;+\u0026thinsp;T cells, and CD4\u0026thinsp;+\u0026thinsp;CD25\u0026thinsp;+\u0026thinsp;FoxP3\u0026thinsp;+\u0026thinsp;T cells) was significantly higher, suggesting cellular immune suppression and immune dysfunction in AECOPD. In addition, T cell expressions of HLA-DR, CD57, and PD-1 were significantly upregulated in patients with AECOPD, indicating that there may be abnormal activation and increased senescence depletion of T cells in AECOPD.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAECOPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eacute exacerbation of chronic obstructive pulmonary disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCOPD assessment test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDTA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEthylene diamine tetraacetate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFEV\u003csub\u003e1\u003c/sub\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eforced expiratory volume in one second\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFVC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eforced vital capacity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFoxP3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eforkhead box protein 3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGOLD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlobal initiative for chronic obstructive lung disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHLA-DR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehuman leukocyte antigen-DR\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealthy controls\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emMRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emodified medical research council dyspnea scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgrammed death receptor 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSCOPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estable chronic obstructive pulmonary disease.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the institutional ethics committees of West China Hospital of Sichuan University (identification no. 2018[283]), and it was registered in the China Clinical Trials Registry on September 19, 2018 (ChiCTR1800018452). All the participants provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author ([email protected]) on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Science and Technology Foundation of Sichuan Province (No.2015SZ0234-3) and National \u0026nbsp; Youth Science Fund Project of National Natural Science Foundation of China (82100045).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXXF contributed to study design, manuscript writing and data analysis. ZM contributed to data acquisition and analysis. WHX and WZH contributed to study design and data interpretation. FLL contributed to data acquisition and interpretation. CDY contributed to study design and manuscript revision. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlobal strategy for the. diagnosis, management, and prevention of COPD (2024 update). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://wwgoldcopdorg\u003c/span\u003e\u003cspan address=\"http://wwgoldcopdorg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. (accessed 04-Dec-2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang C, Xu J, Yang L, Xu Y, Zhang X, Bai C, Kang J, Ran P, Shen H, Wen F, et al. 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Int J Chron Obstruct Pulmon Dis. 2018;13:3191\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan DBA, Teo TH, Setiawan AM, Ong NE, Zimmermann M, Hsu AC, Wark PAB, Moodley YP. Impaired Th1 responses in patients with acute exacerbations of COPD are improved with PD-1 blockade. Clin Immunol. 2018;188:64\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBiton J, Ouakrim H, Dechartres A, Alifano M, Mansuet-Lupo A, Si H, Halpin R, Creasy T, Bantsimba-Malanda C, Arrondeau J, et al. Impaired Tumor-Infiltrating T Cells in Patients with Chronic Obstructive Pulmonary Disease Impact Lung Cancer Response to PD-1 Blockade. Am J Respir Crit Care Med. 2018;198:928\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcKendry RT, Spalluto CM, Burke H, Nicholas B, Cellura D, Al-Shamkhani A, Staples KJ, Wilkinson TM. Dysregulation of Antiviral Function of CD8(+) T Cells in the Chronic Obstructive Pulmonary Disease Lung. 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An evaluation of CD39 as a novel immunoregulatory mechanism invoked by COPD. Hum Immunol. 2016;77:916\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Garra A, Vieira P. Regulatory T cells and mechanisms of immune system control. Nat Med. 2004;10:801\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorsellino G, Kleinewietfeld M, Di Mitri D, Sternjak A, Diamantini A, Giometto R, Hopner S, Centonze D, Bernardi G, Dell'Acqua ML, et al. Expression of ectonucleotidase CD39 by Foxp3\u0026thinsp;+\u0026thinsp;Treg cells: hydrolysis of extracellular ATP and immune suppression. Blood. 2007;110:1225\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta PK, Godec J, Wolski D, Adland E, Yates K, Pauken KE, Cosgrove C, Ledderose C, Junger WG, Robson SC, et al. CD39 Expression Identifies Terminally Exhausted CD8\u0026thinsp;+\u0026thinsp;T Cells. PLoS Pathog. 2015;11:e1005177.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Chronic obstructive pulmonary disease, acute exacerbation, T cells, immunity","lastPublishedDoi":"10.21203/rs.3.rs-3971739/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3971739/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eImmune inflammatory response plays an important role in chronic obstructive pulmonary disease (COPD). However, the cellular immune status of patients with COPD at different phases is unclear. Herein, we aim to investigate the distribution and functional status of T cell subsets in different phases of COPD (acute exacerbation of COPD [AECOPD] and stable COPD [SCOPD]).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis is an observational case-control study undertaken in West China Hospital. The distribution of T cell subsets in peripheral blood of AECOPD, SCOPD, and healthy controls (HCs) was measured using multi-color flow cytometry, and the functional status was analyzed by additional staining of activation markers.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 43 HCs, 43 SCOPD patients, and 64 AECOPD patients were evaluated. The total number and percentage of lymphocytes and the CD4+/CD8\u0026thinsp;+\u0026thinsp;T cells ratio were significantly lower in AECOPD patients when compared to HCs. HLA-DR expression in CD3+, CD4+, CD8+, CD8\u0026thinsp;+\u0026thinsp;TCR aβ, and CD4\u0026thinsp;+\u0026thinsp;TCR aβ T cells was upregulated in the AECOPD group. Similarly, the expressions of HLA-DR, CD57, and PD-1 were higher in T cell subsets in the AECOPD group. Compared with the SCOPD and HC groups, the AECOPD had a significantly lower proportion of CD4\u0026thinsp;+\u0026thinsp;CD27\u0026thinsp;+\u0026thinsp;CD28\u0026thinsp;+\u0026thinsp;T cells, but opposite results were found for CD4\u0026thinsp;+\u0026thinsp;CD27-CD28- T cells. In addition, the proportion of CD4\u0026thinsp;+\u0026thinsp;CD39\u0026thinsp;+\u0026thinsp;T cells and CD4\u0026thinsp;+\u0026thinsp;CD25\u0026thinsp;+\u0026thinsp;FoxP3\u0026thinsp;+\u0026thinsp;T cells was significantly higher in the AECOPD and SCOPD groups when compared to the HC group (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe distribution of nearly half the T cell subsets in AECOPD patients was significantly different from that in SCOPD patients and HCs. AECOPD patients may have cellular immune suppression, immune dysfunction, abnormal activation, and higher senescence depletion of T cells.\u003c/p\u003e\u003ch2\u003eTrial Registration:\u003c/h2\u003e \u003cp\u003eThe study has been registered in the China Clinical Trials Registry on September 19, 2018 (ChiCTR1800018452).\u003c/p\u003e","manuscriptTitle":"T cell immune status in patients with acute exacerbation of chronic obstructive pulmonary disease: A case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-23 20:29:38","doi":"10.21203/rs.3.rs-3971739/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a57e8920-1056-428f-9920-cb6bbe36df34","owner":[],"postedDate":"February 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-29T06:52:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-23 20:29:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3971739","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3971739","identity":"rs-3971739","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}