Monitoring peripheral neutrophil and T-lymphocyte subsets could assist in differentiating the severity and disease progression of coronavirus disease 2019

Basic information and laboratory characteristics of patients with COVID-19

A total of 79 patients were involved in this study, including 41 males and 38 females, and the male patients were significantly younger than the female patients (P = 0.041). The average age had an upward trend with the worsening of COVID-19 (P = 0.004). In the mild and moderate group, condition of four patients (4/56, 7.14%) deteriorated, while in the severe and critically-severe group, that of three patients worsened, and one died (4/23, 17.39%). Additionally, the proportions of exacerbated or fatal cases in mild, moderate, severe, and critically-severe patients were 0%, 9.3%, 16.67%, and 18.18%, respectively. The percentage of improvement within 1 week of admission in mild or moderate COVID-19 patients (22.22%) was twice that in severe or critically-severe patients (11.76%) (Table 1). Table 2 shows that 54.43% (43/79) of COVID-19 patients had a history of going to or living in Wuhan or coming into contact with people from Wuhan. Fever and cough were the most common symptoms in all COVID-19 patients. Over 90% of the severe or critically-severe COVID-19 patients had bilateral pneumonia.

Table 1 demonstrates that 45.76% of COVID-19 patients were characterized by lymphopenia, and among them, the proportion of patients with strikingly decreased T, B, and NK cells was 69.64%, 85.71%, and 73.81%, respectively. About 15-16% of cases also manifested an increase in baseline peripheral neutrophils or monocytes. A marked increase in neutrophils, the neutrophil to lymphocyte ratio (NLR), the neutrophil to monocyte ratio (NMR), the neutrophil to CD3+ T lymphocyte ratio (N3R), the neutrophil to CD3+CD4+ T lymphocyte ratio (N4R), and the neutrophil to CD3+CD8+ T lymphocyte ratio (N8R) and a significant decrease in lymphocytes, the lymphocyte to monocyte ratio (LMR), erythrocytes, hemoglobin, hematocrit (HCT), CD3+ T cells, CD3+CD4+ T cells, and CD3+CD8+ T cells were found in the severe and critically-severe group, compared with the mild and moderate group (all P < 0.05). There was no significant difference in other laboratory indicators between the mild and moderate group and the severe and critically-severe group (all P > 0.05).

Ratio of neutrophil to T lymphocyte and neutrophil to T-lymphocyte subsets could be helpful to differentiate COVID-19 severity

A receiver operating characteristic (ROC) curve analysis showed that the N4R, N3R, NLR, and N8R had potential clinical significance in differentiating severe or critically-severe patients from mild or moderate patients. Their area under ROC curve (AUC) values were 0.933, 0.900, 0.804, and 0.800, respectively (all P < 0.05). The AUCs of neutrophils, lymphocytes, CD3+ T cells, CD3+CD4+ T cells, NMR, LMR, and HCT were all less than 0.8 (all P < 0.05), and the AUC of CD3+CD8+ T cells was less than 0.7 (P < 0.05) (Figure 1). The optimal cut-off value was analyzed using the Youden Index. A diagnostic performance analysis of indicators with the best AUCs (> 0.80) was further made. It showed that under the optimal cut-off, the sensitivity (SEN) of N4R, N3R, NLR, and N8R was >90% for each parameter, and the specificity (SPE) of N4R was the best, at 80.00% (Table 3).

Dynamic characteristics of peripheral T-lymphocyte subsets in COVID-19 patients with different outcomes

According to disease progression, patients with COVID-19 were divided into three groups, including the stable group, improved group, and exacerbated or dead group. This study focused on elucidating the dynamic characteristics of neutrophil, lymphocyte, and T-lymphocyte subsets in COVID-19 patients with different outcomes, and it was observed that the number of lymphocytes, CD3+ T cells, and CD3+CD4+ T cells in the stable and improved groups was significantly more than that in the exacerbated or dead group at baseline, 6-9 days after baseline, and 10-14 days after baseline (P < 0.05, Figure 2). Peripheral total lymphocytes and T-cell subsets in patients with disease exacerbation were all less than the lower limit of their references during the observation period, and those in patients with a stable or improved condition gradually increased after treatment, even surpassing the upper limit of their references at 6-9 days after baseline. No dynamic characteristic of peripheral B cells or NK cells in patients with different outcomes was observed. Figure 3 shows that peripheral CD3+CD4+ or CD3+CD8+ T cells gradually increased during hospitalization, especially 6-9 days after baseline. The period of disease exacerbation could be delayed for more than 2 weeks after admission, while the period of disease improvement was shortened to 1 week after admission. On the contrary, with decreasing peripheral CD3+CD4+ or CD3+CD8+ T cells 6-9 days after baseline, COVID-19 exacerbation quickly occurred within 1 or 2 weeks of admission.

Baseline peripheral NK cell number may correlate with SARS-CoV-2 nucleic acid expression after therapy

Among 48 follow-up patients, 19 patients tested negative for SARS-CoV-2 nucleic acid after therapy. Compared with patients positive for SARS-CoV-2 after therapy, more baseline peripheral lymphocytes and NK cells could be observed in SARS-CoV-2-negative patients after therapy (P < 0.05) (Figure 4A). Additionally, there was no significant difference in other laboratory indicators between SARS-CoV-2-negative patients and SARS-CoV-2-positive patients after therapy. An ROC analysis showed that the AUCs of baseline peripheral NK cells and lymphocytes for differentiating the state of SARS-CoV-2 clearance after therapy were 0.800 and 0.673, respectively (P < 0.05) (Figure 4B, 4C). The optimal cut-off value of NK cells, defined by the Youden index, was 105 cells/μL (SEN: 79.2% and SPE; 72.2%), while the optimal cut-off value of lymphocytes was 875 cells/μL (SEN: 95.5% and SPE: 40.5%).

Subjects

Seventy-nine patients (41 males and 38 females) with an average age of 50.50 years hospitalized in the Public Health Clinical Center of Chengdu from January to February 2020 were included in this study. All patients were diagnosed with COVID-19, and disease classifications were made according to the Diagnosis and Treatment Plan of New Coronavirus Pneumonia (Trial Version 6) released by the National Health Commission and National Administration of Traditional Chinese Medicine [4]. Epidemiological history, clinical signs and symptoms, imaging results, and laboratory indicators (especially SARS-CoV-2 nucleic acid-positive) were important diagnostic standards, and for the suspected patients, continuously detecting SARS-CoV-2 nucleic acid within 2 weeks was necessary to exclude false negative results. This diagnostic protocol effectively excluded false-positive and false-negative patients. According to the guideline, patients were categorized into four subtypes: 1) mild: patients with mild symptoms without pneumonia manifestation in imaging; 2) moderate: patients with some symptoms, such as fever, respiratory tract symptoms, etc., with radiological manifestations of pneumonia; 3) severe: patients who fulfill any of the following: respiratory distress, respiratory rate ≥ 30 times/min, oxygen saturation (SpO2) ≤ 93% in resting state, partial pressure of oxygen in arterial blood/fraction of inspired oxygen (PaO2 /FiO2 ratio) ≤ 300 mmHg (1 mmHg = 0.133652 kPa), greater than 50% lesion progression in pulmonary imaging within 24 to 48 h; 4) critically severe: patients who fulfill any of the following: respiratory failure and requiring mechanical ventilation, shock, admission to the ICU with other organ failure. Cure or discharge criteria were as follows: body temperature returned to normal for more than 3 days, respiratory symptoms improved significantly, pulmonary imaging showed a significant improvement in acute exudative lesions, and two consecutive respiratory specimens tested negative for nucleic acid (sampling times were at least 24 h apart). As a retrospective study, this study was performed in accordance with the current revision of the Helsinki Declaration.

All patients were treated with basic therapeutics, including symptomatic management, oxygen inhalation, interferon atomization, antiviral therapy, or antibiotic therapy in patients with suspected bacterial infection, and mechanical ventilation and glucocorticoid treatment were used when necessary. Patients with a peripheral CD3+CD4+ T-cell count less than 350 cells/μL were treated with thymalfasin. Complete blood count and peripheral lymphocyte subsets were determined in all patients and dynamically monitored in 59 cases. The dynamic points included baseline (within 3 days of admission), 3-5 days after baseline, 6-9 days after baseline, 10-14 days after baseline, 16-22 days after baseline, and more than 23 days after baseline. All laboratory results and clinical information are described in Table 1 and Table 2, respectively.

The outcomes of all patients were recorded according to the conclusions of the clinicians from patient medical records, which were mainly dependent on patient symptoms, pulmonary CT imaging, and laboratory results (such as SpO2 and PaO2/FiO2 ratio). Of all 79 patients, 14 were mild cases, 42 were moderate cases, 12 were severe cases, and 11 were critically severe cases. After therapy, 27 patients were in a stable condition, 44 were improved, 7 were exacerbated, and 1 was dead.

Methods

Complete blood count and peripheral lymphocyte count analysis

Whole blood with EDTA-K2 anticoagulant was used for complete blood count analysis, which was conducted on a Mindray BC-6900 automatic blood cell analyzer (Shenzhen Mindray Bio-Medical Electronics Co., Shenzhen, China) with the corresponding reagents. Blood with lithium heparin anticoagulant was used for the peripheral lymphocyte subset count analysis, which was conducted on a Beckman Coulter Dxflex flow cytometer with Cyto-STAT tetraCHROME CD45-FITC/CD4-RD1/CD8-ECD/CD3-PC5 and Cyto-STAT tetraCHROME CD45-FITC/CD56-RD1/CD19-ECD/CD3-PC5 reagents (Beckman Coulter Company, USA). All flow cytometry data were analyzed by CytExpert for Dxflex version 2.0 software. Sample detection and quality control were performed according to the standard operating procedures and requirements of the clinical laboratory.

Statistical analysis

All data were analyzed using the statistical software SPSS 19.0. Normality was analyzed using a Kolmogorov–Smirnov test (K-S test) and a skewness and kurtosis analysis. Data with normal distribution are described as the mean and standard deviation, and comparisons between groups were conducted using the t-test or ANOVA. Data with non-normal distribution are described as the median and interquartile, and comparisons between groups were conducted using the Mann-Whitney test. Chi-square test was used for composition ratio analysis. An ROC analysis was used to assess the clinical significance of tests in differentiating COVID-19 severity. P < 0.05 was considered statistically significant. Graphpad 8.0.1 software was used to construct dynamic graphs.