Journal of Peking University (Health Sciences) ›› 2020, Vol. 52 ›› Issue (6): 1075-1081. doi: 10.19723/j.issn.1671-167X.2020.06.014

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Analysis of the correlation between lymphocyte subsets and severity of corona virus disease 19

Fang BAO1,Wei-li SHI2,Jing HU1,Di ZHANG1,Dong-han GAO3,Yun-xia XIA4,Hong-mei JING1,Xiao-yan KE1,Qing-gang GE5,Ning SHEN3,()   

  1. 1. Department of Hematology
    2. Institute of Sports Medicine
    3. Department of Respiratory and Critical Care Medicine
    4. Department of Rheumatology and Immunology
    5. Department of Critical Care Medicine, Peking University Third Hospital, Beijing 100191, China
  • Received:2020-07-16 Online:2020-12-18 Published:2020-12-13
  • Contact: Ning SHEN E-mail:shengning1972@qq.com

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Abstract:

Objective: To understand the differences in lymphocyte subsets in patients with different clinical classifications of corona virus disease 19 (COVID-19). Methods: Eighty-one patients with COVID-19 who were admitted to the isolation ward under the responsibility of three medical aid teams in the Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, from February 8, 2020 to March 28, 2020, were selected to collect clinical data. According to the relevant diagnostic criteria, the disease status of the patients was classified into moderate cases (n=35), severe cases (n=39) and critical cases (n=7) when lymphocyte subset testing was performed. Their blood routine tests, lymphocyte subsets and other indicators were tested to compare whether there were differences in each indicator between the patients of different clinical classification groups. Results: The differences in the absolute count of total lymphocytes, T-lymphocytes, CD4+T-lymphocytes, CD8+T-lymphocytes and natural killer (NK) cells among the three groups of patients were all statistically significant (P<0.05), and the critical cases were significantly lower than the moderate and severe cases in the above indicators, and the indicators showed a decreasing trend with the severity of the disease. In 22 patients, the six indicators of the absolute count of T-lymphocytes, B-lymphocytes, CD4+T-lymphocytes, CD8+T-lymphocytes and NK cells, CD4+/CD8+ ratio were all within the normal reference range in the first test, and 59 patients had abnormalities of the above indicators, with the absolute count of NK cells and CD8+ T lymphocytes decreasing most frequently (61%, 56%). The patients with the absolute count of NK cells and CD8+ T lymphocytes below the normal reference range were one group, and the remaining abnormal patients were the other group. There were more critical cases in the former group (moderate:severe:critical cases were 4:8:7 vs. 19:21:0, respectively, P=0.001), and all the deaths were in this group (6 cases vs. 0 case, P=0.001). The absolute B lymphocyte count was below the normal reference range in 15 patients, and the remaining 64 cases were within the normal range. The ratio of moderate, severe and critical cases in the reduced group was 4:7:4, and the ratio of critical cases was more in normal group which was 30:31:3, and the difference between the two groups was statistically significant (P=0.043). Conclusion: The more critical the clinical subtype of patients with COVID-19, the lower the absolute count of each subset of lymphocytes.

Key words: Coronavirus infections, Pneumonia, viral, Lymphocyte subsets

CLC Number: 

  • R563.12

Table 1

Basic data of patients in different clinical classifications"

Characteristic Moderate (n=35) Severe (n=39) Critical (n=7) P value
Male:Female 18:17 17:22 4:3 0.856
Age/years, M (P25, P75) 58 (44, 63) 68 (58, 73)* 62 (59, 75) 0.001
Diabetes, n 7 20 4 0.010
Hypertension, n 10 22 2 0.038
Diabetes + Hypertension, n 3 10 0 0.039
Time from onset to test/d, x-±s 36.3±10.0 31.6±8.3 34.3±19.1 0.136

Table 2

Analysis of routine blood test and lymphocyte subsets in patients with different clinical classifications"

Characteristic Moderate (n=35) Severe (n=39) Critical (n=7) P
Leukocyte/(×109/L) 5.69±1.51 5.75±1.53 12.18±2.76 <0.001
Neutrophil/% 54.56±7.07 60.22±8.38 90.73±4.19 <0.001
Neutrophil/(×109/L) 2.95 (2.35, 3.51) 3.36 (2.91, 3.66) 11.49 (9.67, 12.72) <0.001
Lymphocyte/% 32.51±6.64 27.04±7.65 4.74±3.09 <0.001
Lymphocyte/(×109/L) 1.82±0.51 1.52±0.50 0.52±0.19 <0.001
Monocyte/% 9.38±2.14 9.35±2.06 3.87±1.32 <0.001
Monocyte/(×109/L) 0.53±0.16 0.54±0.20 0.46±0.17 0.693
Eosinophil/% 2.8 (1.9, 3.9) 2.1 (1.5, 3.2) 0.1 (0.05, 0.75) <0.001
Eosinophil/(×109/L) 0.17±0.11 0.17±0.17 0.05±0.06 0.010
Basophil/% 0.51±0.25 0.52±0.36 0.21±0.23 0.018
Basophil/(×109/L) 0.03 (0.02, 0.04) 0.03 (0.01, 0.04) 0.01 (0.01, 0.02) 0.173
CD3+CD19-T-cell/% 74.00±7.03 73.72±10.14 64.84±14.87 0.125
CD3+CD19-T-cell/(cells/μL) 1 292±395 1 094±408 295±156 <0.001
CD3-CD19+B-cell/% 12.27±4.96 12.64±7.05 23.77±18.78 0.055
CD3-CD19+B-cell/(cells/μL) 225±126 180±101 110±91 0.033
CD4+T-cell/% 47.61±7.89 45.56±7.70 44.66±16.01 0.501
CD4+T-cell/(cells/μL) 838±304 675±260 212±145 <0.001
CD8+T-cell/% 23.08±6.06 25.73±9.69 18.86±11.80 0.216
CD8+T-cell/(cells/μL) 410±135 383±198 77±39 <0.001
CD3-/CD16+CD56+NK cell/% 12.99±6.85 12.95±6.24 10.13±8.54 0.584
CD3-/CD16+CD56+NK cell/(cells/μL) 212±106 185±101 39±28 <0.001
T+B+NK cell/% 99.25±0.52 99.33±0.51 98.74±0.95 0.054
T+B+NK cell/(cells/μL) 1 729±464 1 435±505 444±182 <0.001
CD4+/CD8+ 2.14±0.76 2.08±1.07 3.35±1.97 0.242

Table 3

Basic information for the first test of lymphocyte subsets in the normal and abnormal groups"

Characteristic Normal (n=22) Abnormal (n=59) P
Male:Female 12:10 27:32 0.618
Age/years, x-±s 52.3±13.3 62.7±12.6 0.002
Clinical classifications (Moderate:Severe:Critical) 12:10:0 23:29:7 0.069
Time from onset to test/d, x-±s 35.1±9.7 33.4±10.7 0.431
Deaths, n 0 6 0.271

Table 4

Basic information on patients with lymphocyte subsets counts in the normal range at the first test"

Characteristic Moderate (n=12) Severe (n=10) P
Male:Female 8:4 4:6 0.412
Age/years, x-±s 49.0±12.1 56.2±14.3 0.107
Time from onset to test/d, x-±s 37.8±10.8 31.8±7.5 0.228

Table 5

Abnormalities in lymphocyte subsets (n=59) n(%)"

Items Below normal range In normal range Above normal range
CD3+CD19-T-cell 27 (46) 32 (54) 0
CD3-CD19+B-cell 15 (25) 42 (71) 2 (3)
CD3-/CD16+CD56+NK cell 36 (61) 23 (39) 0
CD4+T-cell 24 (41) 34 (58) 1 (2)
CD8+T-cell 33 (56) 26 (44) 0
CD4+/CD8+ 1 (2) 41 (69) 17 (29)

Table 6

Basic information of NK & CD8+ T cell both decrease group and other abnormal groups"

Items NK & CD8+ T cell both decrease (n=19) Other index anomaly (n=40) P
Males:Females 8:11 19:21 0.698
Age/years, x-±s 67.1±11.1 60.6±13.0 0.063
Clinical classifications (Moderate:Severe:Critical) 4:8:7 19:21:0 0.001
Time from onset to test/d, x-±s 32.6±13.5 33.8±9.2 0.526
Deaths, n 6 0 0.001

Table 7

Comparison of B-lymphocyte decrease with normal group"

Items B-lymphocyte decrease (n=15) B-lymphocyte normal (n=64) P
Males:Females 8:7 30:34 0.652
Age/years, x-±s 63.5±10.9 59.5±13.7 0.381
Clinical classifications (Moderate:Severe:Critical) 4:7:4 30:31:3 0.043

Table 8

Comparison of B-lymphocyte decrease with normal group who underwent antibody testing"

Items B-lymphocyte decrease (n=5) B-lymphocyte normal (n=33) P
Time from onset to test/d, M(P25, P75) 45.0 (28.5, 51.0) 39.0 (32.0, 43.0) 0.585
IgM/(AU/mL), M(P25, P75) 59.47 (42.79, 76.05) 39.42 (14.29, 106.21) 0.449
IgG/(AU/mL), M(P25, P75) 209.03 (92.91, 329.47) 173.70 (149.15, 207.09) 0.645
[1] Luo Y, Xie YL, Zhang WJ, et al. Combination of lymphocyte number and function in evaluating host immunity[J]. Aging (Albany NY), 2019,11(24):12685-12707.
[2] Qin C, Zhou LQ, Hu ZW, et al. Dysregulation of immune response in patients with COVID-19 in Wuhan, China[J]. Clin Infect Dis, 2020,71(15):762-768.
pmid: 32161940
[3] Zhou P, Yang XL, Wang XG, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin[J]. Nature, 2020,579(7798):270-273.
doi: 10.1038/s41586-020-2012-7 pmid: 32015507
[4] Wang DW, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China[J]. JAMA, 2020,323(11):1061-1069.
doi: 10.1001/jama.2020.1585 pmid: 32031570
[5] Tan L, Wang Q, Zhang DY, et al. Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study[J]. Signal Transduct Target Ther, 2020,5(1):33.
pmid: 32296069
[6] 董庆鸣, 何忠平, 庄辉, 等. SARS患者外周血B淋巴细胞和自然杀伤细胞动态变化[J]. 中华流行病学杂志, 2004,25(8):695-697.
[7] He ZP, Zhao CH, Dong QM, et al. Effects of severe acute respi-ratory syndrome (SARS) coronavirus infection on peripheral blood lymphocytes and their subsets[J]. Int J Infect Dis, 2005,9(6):323-330.
pmid: 16095942
[8] Chen MH, Wong VW, Wong CK, et al. Serum LD1 isoenzyme and blood lymphocyte subsets as prognostic indicators for severe acute respiratory syndrome[J]. J Inter Med, 2004,255(4):512-518.
[9] 贺莉, 丁彦青, 王蔚, 等. 免疫细胞在SARS病变组织中的表达及其作用[J]. 第一军医大学学报, 2003,23(8):774-776, 780.
[10] Glass WG, Subbarao K, Murphy B, et al. Mechanisms of host defense following severe acute respiratory syndrome-coronavirus (SARS-CoV) pulmonary infection of mice[J]. J Immunol, 2004,173(6):4030-4039.
pmid: 15356152
[11] Maloir Q, Ghysen K, von Frenckell C, et al. Détresse respiratoire aiguё révélatrice d’un syndrome des antisynthétases[J]. Rev Med Liege, 2018,73(7-8):370-375.
pmid: 30113776
[12] Chen J, Lau YF, Lamirande E W, et al. Cellular immune responses to severe acute respiratory syndrome coronavirus (SARS-CoV) infection in senescent BALB/c mice: CD4+ T cells are important in control of SARS-CoV infection[J]. J Virol, 2010,84(3):1289-1301.
pmid: 19906920
[13] Wang F, Nie JY, Wang HZ, et al. Characteristics of peripheral lymphocyte subset alteration in COVID-19 pneumonia[J]. J Infect Dis, 2020,221(11):1762-1769.
pmid: 32227123
[14] Zhang Z, Xu DP, Li YG, et al. Longitudinal alteration of circulating dendritic cell subsets and its correlation with steroid treatment in patients with severe acute respiratory syndrome[J]. Clin Immunol, 2005,116(3):225-235.
doi: 10.1016/j.clim.2005.04.015 pmid: 15964242
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