Decreased T Cell Levels in Critically Ill Coronavirus Patients: single-center, prospective and observational study

DOI: https://doi.org/10.21203/rs.3.rs-52222/v1

Abstract

Background: Since Dec. 2019, COVID-19 pandemic has been outbreak. T cells play an important role in dealing with various disease-causing pathogens. However, the role of T cells played in COVID-19 patients is still unknown. Our study aimed to describe immunologic state of the critical ill COVID-19 patients.

Methods: 63 patients with confirmed COVID-19 pneumonia admitted Department of Intensive Care Unit of the First Affiliated Hospital of Harbin Medical University. The immunologic characteristics(lymphocyte apoptosis, the expression of PD-1 and HLA-DR in T cells, T cell subset levels, redistribution and the production of inflammatory factors)as well as their laboratory parameters were compared between severe group and critical group.

Results: The level of T cells in peripheral blood was decreased in critical patients compared with that in severe patients, but the expression levels of PD-1 (CD4+: 24.71% VS 30.56%; CD8+: 33.05% VS 32.38%) and HLA-DR (T cells: 36.28% VS 27.44%; monocytes: 20.58% VS 23.83%) in T cells were not significantly changed, and apoptosis and necrosis were not different in lymphocytes (apoptosis: 1.04% VS 1.27%; necrosis: 0.67% VS 1.11%), granulocytes, or monocytes between those two groups.

Conclusions: There is severe immunosuppression in critical ill COVID-19 patients. Redistribution of T cells might be the main reason for lymphocytic decline. Decreasing the infiltration of T lymphocytes in the lung may be beneficial for the treatment of COVID-19.

Trial registration: The study was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University. Code number: kyk2020003. 

Background

Since Dec. 2019, an outbreak of pneumonia cases caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in Wuhan 1,2. As of Jun. 16, the number of confirmed pneumonia cases reached 8112639, and the cumulative number of deaths was 439046. A recent report demonstrated that SARS-CoV-2 infection leads to ICU admission and high mortality3. However, there are few studies on the immunologic function of COVID-19 patients.

T cells play an important role in dealing with various disease-causing pathogens. It differentiate into several subsets of effector cells, including T helper type I (Th1), Th2, Th17, T follicular helper (Tfh), and regulatory T (Treg) cells4. Treg cells inhibit autoimmune responses. Cytokines are the determinant factors for T cell differentiation. For example, the proinflammatory cytokine IL-6, produced by macrophages and T cells, is a critical determinant factor for driving Th17 cell differentiation and inhibiting Treg cell differentiation5-7. In recent studies, T cell level reduction was confirmed in COVID-19 patients8,9. This finding may indicate the presence of immunosuppression in patients with COVID-19. However, the reason for the reduction is still not clear. In our study, we explored the mechanism of immunosuppression in these patients. The immune status of COVID-19 patients will be described by lymphocyte apoptosis, the expression of PD-1 and HLA-DR in T cells, T cell subset levels and the production of inflammatory factors. Our findings will help us understand the immunologic mechanism of COVID-19.

Patients And Methods

The study was approved by the Ethics Committee of the 1st Affiliated Hospital of Harbin Medical University. Written informed consent was regularly obtained from all patients upon admission to department Intensive Care Medicine, the 1st Affiliated Hospital of Harbin Medical University (the intensive care center for severe COVID-19 patients in Harbin, Heilongjiang Province). The 63 confirmed COVID-19 patients in the intensive care unit (ICU) were severe/critical according to the Guidelines of the Diagnosis and Treatment of New Coronavirus Pneumonia (version 6) published by the National Health Commission of China or to the Sequential Organ Failure Assessment(SOFA)score. All the patients enrolled in this retrospective single-center study were admitted to the ICU from Feb. 12th to Mar. 26th, 2020.

Severe COVID-19 patients were defined as those satisfying any of the following criteria: 1. Patients who had hypoxemia at rest; hypoxemia was defined as arterial oxygen tension (PaO2) over inspiratory oxygen fraction (FIO2) of less than 300 mmHg or arterial oxygen saturation of 93% or lower. 2. Patients whose breathing rates were greater than 30 breaths per minute.

Critical patients were defined as COVID-19 patients who required high-flow nasal cannula or higher-level oxygen support measures to correct hypoxemia.

All medical record information, including epidemiological, demographic, clinical manifestation, and laboratory data, were obtained. All data were checked by a team of trained physicians.

Laboratory examination

Laboratory confirmation of COVID-19 was performed by the local CDC according to the Chinese CDC protocol. Throat swab specimens were collected from all patients, and the samples were maintained in viral transport medium for laboratory testing. Specimens, including sputum and blood, were cultured to identify pathogenic bacteria or fungi that may be associated with COVID-19 infection. A lymphocyte test kit (Beckman Coulter Inc., FL, USA) was used for lymphocyte subset analysis. The concentrations of serum cytokines (IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ) were quantitatively determined by a Human Th1/Th2 Cytokine Kit (Saiji Biotec, Hangzhou, China) as described in the instruction manual.

The expression of PD-1 was analyzed using a BD FACSCalibur (BD Biosciences, CA, USA) flow cytometer. Peripheral blood cells were surface stained with mouse anti-human CD8-FITC (BD Biosciences, CA, USA), CD4-PE (BD Biosciences, CA, USA) and CD279 (PD-1)-APC (Biolegend, CA, USA) monoclonal antibodies for 15 minutes in the dark at room temperature. After lysing with 1X BD FACS Lysing Solution(BD Biosciences, CA, USA), cells were then washed two times with PBS. Data were analyzed using Kaluza software (Version 2.1)( Beckman Coulter, IN, USA). The following monoclonal antibody panel was used for surface staining: CD8-FITC (BD Biosciences, CA, USA), CD4-PE (BD Biosciences, CA, USA) and CD279 (PD-1)-APC (Biolegend, CA, USA) for PD-1 expression on lymphocytes; CD14-FITC (BD Biosciences, CA, USA) and HLA-DR-PerCP (Miltenyi, Bergisch Gladbach, Germany) for HLA-DR expression on monocytes; CD4-FITC (Quanto Bio, Beijing, China), CD25-PE (Quanto Bio, Beijing, China) and CD127-APC (Quanto Bio, Beijing, China) for Treg cells. The stained samples were further lysed, washed, and resuspended in 200 µl of PBS before acquisition.

Apoptosis was determined by a FITC Annexin V Apoptosis Detection Kit I (BD Biosciences, CA, USA) after lysing samples with a lysing solution that did not contain a fixative agent. Then, the cells were washed and stained with Annexin V-FITC and PI as described in the instruction manual.

Acquisitions of samples were carried on FACSCalibur flow cytometer (BD Biosciences, CA, USA). Cytokines data were analyzed using FCAP Array™ software (Version 3.0) (BD Biosciences, CA, USA), other data were analyzed using Kaluza software (Version 2.1)( Beckman Coulter, IN, USA).

Figure 1 shows the patient flowchart in this prospective and observational study.

Statistical analyses

The quantized variables of parameters are expressed as the mean ± standard deviation, and the significance was tested by t-test. Nonparametric variables are expressed as median and quartile intervals [M (P25, P75)], and significance was tested by Wilcoxon rank-sum test. P < 0.05 was considered statistically significant in all statistical analyses. The Spearman rank correlation coefficient was used to analyze correlations. All statistical analyses were performed by Statistical Analysis System (SAS) (version 9.1.3, SAS Institute Inc., Cary, NC, USA).

Results

1. Patient information

As of Mar. 26th, 2020, a total of 63 hospital-admitted patients with pneumonia were diagnosed with laboratory-confirmed COVID-19 in Harbin Medical University First Affiliated Hospital and were enrolled in our study. Those patients were divided into two groups: patients with SpO2 93%, respiratory rate 30 per min, or oxygenation index (OI) < 300 as the severe group (n=27), whereas patients with the abovementioned signs and needed mechanical ventilation or had organ dysfunction complications as the critical group (n=36). The characteristics of these patients are described, we found that the difference in SOFA scores was statistically significant (p=0.031). The routine blood tests on the 63 COVID-19 patients showed that white blood cell (WBC) and neutrophil counts were normal in the severe group (5.31×10/L and 72.1%) but were slightly increased in the critical group (7.86 ×10/L and 84%). However, lymphocyte counts were significantly lower in the critical group and decreased by almost 60% compared with those in the severe group (Table 1). According to these findings, we hypothesized that there was a relationship between the SOFA score and indicators from routine blood tests. To investigate this relationship, we performed linear correlation analysis between these indicators and the SOFA score.

Table 1. Baseline Characteristics of COVID-19 Patients 

Variables

Total

(n=63)

Severe patients

(n=27)

Critical Patients 

(n=36)

Value

Age (years)

65.33±12.28

67.15±12.29

63.97±12.27

0.314

Gender

 

 

 

0.716

Female

32(50.79)

13(48.15)

19(52.78)

 

Male

31(49.21)

14(551.85)

17(47.22)

 

White blood 

cell count (×109/L)

6.49(5.05-8.75)

5.31(4.09-6.4)

7.86(6.39-10.2)

<0.001

Neutrophil (% )

78.95(63.05-86.65)

72.1(58.8-79.1)

84(71.2-90.3)

0.012

Neutrophil 

count (×109/L)

4.81(2.14-6.86)

3.83(2.01-4.97)

6.53(2.96-8.91)

0.024

Lymphocyte percentage (%)

9.15(4.5-15.55)

14.75(9.9-23.6)

5.9(3.8-9.6)

<0.001

Lymphocyte 

count (×109/L)

0.65(0.39-1.07)

0.71(0.57-1.1)

0.53(0.34-0.84)

0.109

Monocyte percentage (%)

6.45(0.36-11.7)

7.35(0.39-11.8)

1.09(0.32-11.1)

0.414

Monocyte 

count (×109/L)

0.63(0.38-104)

0.57(0.39-0.83)

0.74(0.33-122)

0.467

Platelet 

count (×109/L)

170(113.5-273)

174.5(116-294)

154.5(95-264)

0.541

SOFA

4(2-4)

3(2-4)

4(3-5)

0.031



2. The level of T cells in peripheral blood was decreased in critically ill patients.

Our findings showed that the SOFA score was negatively correlated with lymphocyte counts, WBC counts, and neutrophil counts, especially lymphocyte counts (P<0.0001) (Table 2). This result indicated that lymphocyte counts and lymphocyte ratio were negatively correlated with disease severity in COVID-19 patients; furthermore, lymphocytic decline was an important marker for the outcome of this disease. Then, we tried to explore the reason for lymphocytic decline. We hypothesized that apoptosis was the main reason for lymphocytic decline. To investigate this hypothesis, we tested the apoptosis of CD3+ T lymphocytes in peripheral blood.

Table 2. Linear correlation analysis between these indicators and SOFA score.

Indicators

rs

P

White blood cell count (×109/L)

0.4020

0.0015

Neutrophil (% )

0.2588

0.0478

Neutrophil count (×109/L)

0.2223

0.1248

Lymphocyte percentage (%)

-0.4996

0.0000

Lymphocyte count (×109/L)

-0.3346

0.0090

Monocyte percentage (%)

-0.2489

0.0846

Monocyte count (×109/L)

0.0645

0.7260

Platelet count (×109/L)

-0.3901

0.0021



3. The expression of PD-1 in CD4+ T cells was increased but not significantly altered.

The immune-inhibitory factor PD-1 can activate the apoptosis signaling pathway and induce the apoptosis of immune cells. We tested the expression of PD-1 in CD4+ and CD8+ T cells and found that the expression of PD-1 was only slightly increased in CD4+ T cells, but the difference was not statistically significant (Table 3). Whether Was there truly no difference in T cell apoptosis between the severe and critical groups? For further study, apoptosis of immune cells was determined by a FITC Annexin V Apoptosis Detection Kit I. Our findings showed that apoptosis was not different in lymphocytes, granulocytes, or monocytes between the severe and critical groups (Table 4). Identically, we found that lymphocyte levels were obviously decreased in the critical group compared with those in the severe group (14.82% VS 30.82%). To determine the reason for lymphocytic decline, we also detected cell necrosis by the FITC Annexin V Apoptosis Detection Kit I and found that there were no differences in lymphocytes, granulocytes, or monocytes between the severe and critical groups (Table 4). Then, we detected the inflammatory cytokines IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ and found that  the levels of IL-6 inflammatory were increased in the critical group compared with those in the severe group (4.43pg/mL VS 9.3pg/mL), but the levels of IL-2, IL-4, IL-10, TNF-α, and IFN-γ were no difference between the severe and critical groups.Table 5. There might be another reason for lymphocytic decline that we need to explore.

Table 3. The characteristics of PD-1 expression of COVID-19 patients 

Variables

Total

(n=28)

Severe group

(n=12)

Critical group

(n=16)

t/χ2/Z

P

Age(years)

62.68±11.89

64.42±11.39

61.38±12.46

0.663

0.513

gender

 

 

 

 

0.459

Female

16(57.14)

8(66.67)

8(50.00)

 

 

Male

12(42.86)

4(33.33)

8(50.00)

 

 

CD4+ T (%)

39.14±11.9

46.23±8.89

33.83±11.26

3.144

0.004

PD1+ CD4+ T (%)

28.05±9.35

24.71±5.98

30.56±10.74

-1.694

0.102

CD8+ T (%)

21.35(14.55-28.25)

20.2(15.65-29)

23.05(13.7-28.25)

-0.023

0.982

PD1+ CD8+ T (%)

32.67±11.48

33.05±13.39

32.38±10.27

0.15

0.882

[,M(IQR),n(%)]



Table 4. The characteristics of immune cells apoptosis in COVID-19 patients 

Variables

Total 

(n=14)

Severe group(n=5)

Critical  group(n=9)

t/χ2/Z

P

Age(years)

61.79±7.84

61.2±7.19

62.11±8.58

-0.201

0.844

Gender

 

 

 

 

0.580

Female

9(64.29)

4(80.00)

5(55.56)

 

 

Male

5(35.71)

1(20.00)

4(44.44)

 

 

granulocyte 

 

 

 

 

 

granulocyte (%)

56.53±14.67

34

60.28±11.83

 

 

Necrosis cells (%)

1.06±0.6

0.7

1.12±0.63

 

 

The late apoptosis cells (%)

0.58±0.22

0.79

0.55±0.22

 

 

The early apoptosis cells (%)

2.4±0.97

3.2

2.27±0.99

 

 

Apoptosis cells (%)

2.98±1.14

3.99

2.82±1.16

 

 

Live cells (%)

95.97±1.46

95.3

96.08±1.57

 

 

lymphocyte

 

 

 

 

 

lym  (%)

20.54±11.03

30.82±9.65

14.82±6.96

3.604

0.004

Necrosis cells (%)

1.08(0.76-1.38)

0.67(0.6-1.35)

1.11(0.98-1.38)

-1.200

0.230

The late apoptosis cells (%)

0.33(0.2-0.83)

0.35(0.18-0.83)

0.3(0.21-0.52)

0.000

1.000

The early apoptosis cells (%)

0.9(0.72-2.06)

0.76(0.75-8.23)

0.97(0.72-2.02)

0.400

0.689

Apoptosis cells (%)

1.16(0.93-3.07)

1.04(0.94-9.06)

1.27(0.93-2.54)

0.3337

0.7386

Live cells (%)

97.45(94.3-98.1)

96.9(90.3-98.5)

97.9(96.1-98)

0.000

1.000

monocyte

 

 

 

 

 

Monocyte (%)

5.05(3.21-6.52)

6.26(4.14-6.62)

3.83(3.21-6.32)

0.801

0.423

Necrosis cells (%)

9.95±9.06

3.78±2.27

13.38±9.69

-2.148

0.053

The late apoptosis cells (%)

1.18(0.91-2.31)

0.91(0.56-1.16)

1.25(1.04-2.31)

-1.067

0.286

The early apoptosis cells (%)

3.84±1.52

3.83±1.6

3.84±1.57

-0.018

0.986

Apoptosis cells (%)

5.51±2.58

5.10±2.29

5.74±2.84

-0.43

0.6768

Live cells (%)

84.54±10.01

91.12±2.58

80.89±10.84

2.043

0.064

[,M(IQR),n(%)]



Table 5 Characteristics of cytokines in COVID-19 patients 

Variables

Total (n=27)

Severe (n=10)

Critical (n=17)

t/Z2

P

Age(years)

64.74±11.45

62.9±10.58

65.82±12.11

-0.63

0.5322

Gender

 

 

 

 

0.6831

  Femal

9(33.33)

4(40.00)

5(29.41)

 

 

  Male

18(66.67)

6(60.00)

12(70.59)

 

 

IL-2 (pg/mL)

1.04±0.39

1.14±0.41

0.98±0.38

1.05

0.3054

IL-4 (pg/mL)

1.34±0.59

1.47±0.65

1.27±0.57

0.82

0.4214

IL-6 (pg/mL)

6.11(4.17-15.56)

4.43(2.55-7.15)

9.3(5.2-30.98)

-2.2845

0.0223

IL-10 (pg/mL)

4.44(2.6-7.14)

3.68(3.07-4.5)

4.9(2.53-10.77)

-0.7782

0.4364

TNF (pg/mL)

1.56±0.38

1.7±0.41

1.48±0.36

1.52

0.1415

IFN-γ (pg/mL)

1.01(0.85-1.14)

1.05(0.85-1.17)

1(0.85-1.07)

0.7035

0.4818

[,M(IQR),n(%)]



4. The expression of HLA-DR in T cells and monocytes.

HLA-DR, an indicator of sepsis prognosis, has been shown to be associated with the T cell subset Treg cells. Our findings showed that the expression of HLA-DR in T cells was not different between the severe and critical groups (36.28% VS 27.44%) and that there was no difference between the severe and critical groups regarding monocytes (P= 0.41) (Table 6). Then, we detected the number of Treg cells and found that there was no difference between the severe and critical groups (Table 7). In addition to Treg cells, we also detected CD4+ T cells, CD8+ T cells, B lymphocytes and NK lymphocytes in peripheral blood. Consistently, we obtained a negative result; the levels of those immune cells in peripheral blood did not change between the severe and critical groups (Table 8). Finally, we hypothesized that distribution might be the main reason for lymphocytic decline.

5. Distribution of T cells.

We additionally compared one male critical COVID-19 patient’s T cell subsets (Figure 2) and cytokine levels (Table 9) in peripheral blood, BALF and pleural effusion. There were no differences in the percentage of lymphocytes (T%) or the percentage of NK cells (NK%) in peripheral blood, BALF or pleural effusion. The lymphocyte absolute values (LYM#) in peripheral blood, BALF and pleural effusion were 628, 156, and 299, respectively. T cell absolute values (T#) were 479, 116, and 267, respectively. CD4+ T# were 321, 41, and 132, respectively; CD8+ T# were 155, 70, and 133, respectively; B cell absolute values (B#) were 74, 9, and 7, respectively; NK cell absolute values (NK#) were 42, 13, and 20, respectively; And CD4+CD8+ T cell absolute values were 11, 4, and 24, respectively.

For the cytokine levels in the three samples, we observed that IL-2 levels were highest in BALF (7.28 pg/mL), lowest in pleural effusion (0.90 pg/mL), and 1.84 in peripheral blood. IL-6 levels were remarkably increased in BALF and pleural effusion (600.38 and 2201.38 pg/mL, respectively) compared with those in peripheral blood (42.84 pg/mL). Moreover, IL-10 levels were higher in pleural effusion (81.64 pg/mL) than in peripheral blood (26.36 pg/mL) and BALF (6.91 pg/mL).

Table 6. The characteristics of HLA-DR expression in COVID-19 patients

Variables

Total

(n=19)

Severe group

(n=4)

Critical group

(n=15)

t/χ2

P

Age(years)

63.74±8.55

68.25±7.8

62.53±8.58

1.203

0.246

Gender

 

 

 

 

1.000

Female

10(52.63)

2(50.00)

8(53.33)

 

 

Male

9(47.37)

2(50.00)

7(46.67)

 

 

T (%)

15.45±8.05

17.09±6.45

15.02±8.57

0.446

0.661

HLA-DR+ (T %)

29.3±10.7

36.28±12.18

27.44±9.9

1.52

0.147

Monocytes (%)

9.5±3.65

10.39±3.13

9.26±3.84

0.539

0.597

HLA-DR+monocyte (%)

23.14±6.79

20.58±2.77

23.83±7.43

-0.845

0.410

[,n(%)]

 

Table 7. The characteristics of CD4+Treg in COVID-19 patients

Variables

Total 

(n=40)

Severe group (n=19)

Critical group

(n=21)

χ2

P

Age(years)

63.48±11.15

64.42±12.94

62.62±9.48

0.010

0.992

Gender

 

 

 

0.002

0.962

Female

17(42.50)

8(42.11)

9(42.86)

 

 

Male

23(57.50)

11(57.89)

12(57.14)

 

 

CD4+Treg (%)

9.49(8.24-11.45)

9.43(8.27-11.09)

9.77(8.2-11.6)

0.000

1.000

[,n(%)]

 

Table 8. The characteristics of T cell subset expression in COVID-19 patients 

variables

total (n=20)

Severe group (n=5)

Critical group (n=15)

t/χ2/Z

P

Age(years)

62.90±9.41

67.4±7.02

61.4±9.83

1.253

0.226

Gender

 

 

 

 

1.000

Female

10(50.00)

3(60.00)

7(46.67)

 

 

Male

10(50.00)

2(40.00)

8(53.33)

 

 

T (%)

74.64±5.69

76.73±4.44

73.94±6.02

0.949

0.355

CD4+/ CD3+ (%)

47.42±6.77

52.25±4.73

45.82±6.69

1.976

0.064

CD8+/ CD3+ (%)

26.56±8.49

23.95±5.88

27.43±9.21

-0.785

0.443

CD19+ (%)

10.59±4.35

9.08±3.01

11.09±4.69

-0.891

0.385

CD16+/ CD3+ (%)

12.89(6.75-15.25)

11.33(6-12.17)

14.33(7.03-15.5)

-0.786

0.432

H/S

1.83(1.37-2.18)

1.97(1.86-2.24)

1.65(1.17-2.11)

1.223

0.222

Lym# (/μL)

979.05±452.4

1296±662.48

873.4±323.3

1.935

0.069

T # (/μL)

732.6±345.22

985.2±498.36

648.4±245.76

2.04

0.056

T4 # (/μL)

455.7±217.85

638.4±287

394.8±158.04

2.429

0.026

T8 # (/μL)

256.75±138.12

299±177.41

242.67±126.68

0.782

0.445

B # (/μL)

100.85±55.51

115.4±61.74

96±54.7

0.667

0.513

NK # (/μL)

116.95±80.91

150.6±115.01

105.73±67.58

1.078

0.295

CD4+ CD8(%)

2.34(1.8-2.81)

2.64(2.14-2.83)

2.31(1.69-2.78)

0.873

0.383

CD4+ CD8+ # (/μL)

16(11-21.5)

21(16-22)

15(9-21)

1.315

0.188

  [,M(IQR),n(%)]

 


Table 9. The characteristics of cytokines in peripheral blood, BALF and fleural effusion of COVID-19 patient

Cytokines

Patient 

 

Peripheral blood

BALF

Fleural effusion

IL-2 (pg/mL)

1.84

7.28

0.90

IL-4 (pg/mL)

1.21

2.95

2.07

IL-6 (pg/mL)

42.84

600.38

2201.38

IL-10 (pg/mL)

26.36

6.91

81.64

TNF-α (pg/mL)

0.92

51.54

2.54

IFN-γ (pg/mL)

1.62

16.99

2.68



Discussion

This study analyzed severe and critical COVID-19 cases in Heilongjiang, China. This report is the first study to explore the mechanism of immunosuppression in critically ill COVID-19 patients. Recent studies have provided evidence for person-to-person transmission of SARS-CoV-210,11. COVID-19 has become a global problem that needs to be solved immediately. To date, many clinical and epidemiological features of COVID-19 have been reported3,10-12. However, there is little knowledge of immunology in COVID-19. Our study is of great significance for further understanding COVID-19.

T cells play an important role in dealing with various disease-causing pathogens4. A few studies have reported the decreased numbers and function of T cells in COVID-19 patients8,9, but the mechanism of the reduction in T cells is still unclear. Similarly, our study also found that the number of T cells was decreased in routine blood tests, particularly in critical patients. Then, we confirmed the reduction in CD3+ T cell levels by flow cytometry. A study verified T cell exhaustion by measuring the exhaustion markers PD-1 and Tim-39 but did not perform further research. Therefore, we hypothesized that T cell exhaustion might be due to apoptosis. Then, apoptosis and the expression of PD-1 in immune cells were detected. In fact, we confirmed that CD3+ T cell apoptosis and immune cell necrosis in critically ill patients was not more serious than that in severe COVID-19 patients by flow cytometry. They were not significantly different. In contrast, our study found that the expression of PD-1 was not increased significantly in CD4+ and CD8+ T cells in critical patients compared with those in severe patients. Our findings showed that apoptosis and cell necrosis levels were not different in lymphocytes, granulocytes, or monocytes between the two groups. Therefore, we hypothesized that T cell exhaustion might be due to Treg cell proliferation. HLA-DR, an indicator of sepsis prognosis, has been reported to represent a natural T cell subset of CD8+ HLA-DR+ Treg cells, which may play a suppressive effect13. We detected the expression of HLA-DR in T cells and monocytes and tested the level of Treg cells in peripheral blood. Unfortunately, we found that either Treg proliferation or the expression of HLA-DR was not significantly changed in critically ill COVID-19 patients compared with those in severe patients. Our findings indicated that CD3+ T cell apoptosis and Treg proliferation were not the reason for T cell exhaustion, at least not the main reason. Then, we analyzed one patient to detect the distribution of T cells. A surprising discovery was that a large number of T cells infiltrated the lungs in this critical patient, which might be the main reason for the lymphocytic decline in peripheral blood. Our findings were similar to those of Dr. Xu’s autopsy report: inflammatory infiltration occurred in both lungs, especially by lymphocytes14. However, we still need additional patients to detect the distribution of T cells.

When the virus invades the body, if the immune system is overactivated or uncontrolled, the infection induces an extreme immune response, releasing large amounts of cytokines that attack the host. This phenomenon is known as an "inflammatory storm." Similar to the case in SARS and Ebola, cytokine storms have become the main cause of death in COVID-1915. Cytokine and chemokine levels are significantly increased in patients with severe infection and are associated with the severity of the disease16, such as sepsis. In our study, we detected the levels of IL-6, IL-10, TNF-α, and IFN-γ in peripheral blood and found that the levels of IL-6 were increased in the critical group compared with those in the severe group. However, according to our previous results, the number of T cells was reduced in the peripheral blood of critically ill patients. These two results seem to be contradictory, but this phenomenon may potentially be due to the activation of T cells. The function of activated T cells producing proinflammatory factors was enhanced in the peripheral blood of critically ill patients. Further study is needed to explore the function of inflammatory factor production in immune cells.

In addition to those findings, we detected cytokines from the alveolar lavage fluid and pleural effusion in one critically ill COVID-19 patient. Our findings showed that the level of IL-6 was significantly increased compared with that in peripheral blood. Our findings indicated that the local extreme immune response in the lungs might be an important cause of death in critical patients. Recently, some studies reported that reducing the level of IL-6 by sarilumab in peripheral blood might be helpful for the treatment of COVID-19 patients17. According to our study, reducing the level of IL-6 in peripheral blood may not be useful for critically ill patients. In summary, our findings indicated that attenuating the concentration of IL-6 or inhibiting the inflammatory response in the lungs might be a significant therapy for critically ill COVID-19 patients.

The limitations of this study were as follows: only 63 ill patients in Heilongjiang Province were enrolled. Heilongjiang Province is a cold region, and almost all patients have chronic bronchial and cardiovascular diseases, which may not represent the global situation for COVID-19. In addition, the results we obtained only described the function of T cells in severely and critically ill COVID-19 patients, and B lymphocytes, granulocytes, and monocytes have yet to be further explored. In addition, the cases we collected lacked continuous observation, and we did not follow up with the patients to obtain biological indicators of the recovery stage. Similarly, we did not collect the relevant data of mild COVID-19 cases and healthy people. There were too many studies reported the levels of PD-1, HLA-DR and Treg in healthy people. The expressions of PD-1 in T cell and the levels of Treg both of severe and critical group were increased compared with healthy people [18-20], and the expressions of HLA-DR in T cell and moncytes were decreased compared with healthy people [21-23], Our findings indicated that the severe immunosuppression in those COVID-19 patients. Finally, further COVID-19 studies at the molecular and gene levels are still needed.

Conclusion

There is severe immunosuppression in critical ill COVID-19 patients. Immune dysfunction may be attributed mainly to T cell redistribution. Decreasing the number of T lymphocytes infiltrating the lung may be beneficial for the treatment of COVID-19.

Declarations

Availability of data and materials

Not applicable

Ethics approval and consent to participate

The study was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University. Code number: kyk2020003.

Consent for publication

All authors have seen and approved the final version of the manuscript.

Competing interests

The authors declare that they have no competing interests.

Funding

This research supported by the National Natural Science Foundation of China (Nos.81571871, 81770276 and 81772045), Nn10 program of Harbin Medical University Cancer Hospital.

Authors’ contributions

Concept and design: Mingyan Zhao, Changsong Wang and Kaijiang Yu

Acquisition, analysis, or interpretation of data:  Haitao Liu, Kai Kang, Zhiyu Liu, Wei Yang, Yunpeng Luo, Dongsheng Fei, Xueting Li, Jingjing Xu

Drafting of the manuscript: Changsong Wang and Jingjing Xu

Critical revision of the manuscript for important intellectual content: Mingyan Zhao, Changsong Wang and Kaijiang Yu

Statistical analysis: Changsong Wang and Xueting Li
Obtained funding:  Mingyan Zhao, Changsong Wang and Kaijiang Yu

Administrative, technical, or material support:  Zhiyu Liu

Acknowledements

 This work was supported by Novel coronavirus pneumonia emergency treatment and diagnosis technology research project of Heilongjiang provincial science and Technology Department.

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