Abstract
The aim of this study is to evaluate the potential of lymphocytes as biomarkers to predict the decline of coronavirus disease 2019 (COVID-19). Lymphocytes were counted in 164 moderate COVID-19 patients in Shenzhen, China. Among the moderate infected patients, 12.2% (20/164) progressed to severe cases after admission. Compared with the stable patients, the counts of lymphocytes, both total T lymphocytes and CD4+ T lymphocytes, in the severe patients, were lower. The aggravation of moderate infected patients was significantly associated with lymphocyte count (hazard ratio [HR] = 0.91; 95% confidence interval [CI]: 0.84–0.99), total T lymphocyte count (HR = 0.91; 95% CI: 0.84–0.99), and CD4+ T lymphocyte count (HR = 0.91; 95% CI: 0.85–0.98). Total T lymphocytes and CD4+ T lymphocytes could be important biomarkers to evaluate the risk of aggravation for moderate infected COVID-19 patients. The patients with low percentages of total T lymphocytes and CD4+ T lymphocytes need more attention.
Keywords: COVID-19, prognosis, T lymphocytes
1. Introduction
An outbreak of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei province, China, in December 2019, and was declared as a pandemic by the World Health Organization on March 11, 2020.[1–3] COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).[4] Clinically, COVID-19 patients are divided into mild, moderate, severe, and critical groups according to disease severity. Unfortunately, a small fraction of the moderate infected patients will develop into severe cases. It is urgent to identify these patients earlier and provide them with appropriate treatments.
Lymphocytes play essential role in host defense against invading viruses. Classically, T lymphocytes are divided into CD4+ T lymphocytes and CD8+ T lymphocytes. Recent studies showed that lymphocyte percentage could be used as a predictor of prognosis in COVID-19 patients.[5–8] Remarkably, the numbers of total T lymphocytes and CD4+ T lymphocytes often reduce in COVID-19 patients who require intensive care unit care.[9,10]
Therefore, the purpose of this study is to evaluate the potential of lymphocytes as biomarkers to predict the deterioration of COVID-19 patients. The counts of T lymphocytes and total lymphocytes in peripheral blood of 164 moderate COVID-19 patients were detected and assessed with the deterioration of the patients.
2. Materials and methods
2.1. Participants and data collection
This study was approved by Ethics Committee of the Third People’s Hospital of Shenzhen (No. 2020-228). All patients provided written consent. Laboratory lymphocytes and T lymphocytes data were collected from the 164 COVID-19 patients from the Third People’s Hospital of Shenzhen, China, and diagnosed as moderate cases on admission from January 15 to February 16, 2020. Clinical outcomes (dismission, improvement, stable, aggravation, and death) were monitored through March 17, 2020, the final date of follow-up. If the patients had outcomes aggravation or death during hospitalization, we assigned them into the aggravated group; otherwise, we assigned them into the stable group.
2.2. Statistical analysis
The Mann–Whitney test was used to access differences between the stable and aggravated groups for some continuous variables non-normally distributed. The χ2 test or Fisher exact test was used to compare differences in categorical variables. Cox model was applied to investigate the association of the aggravation with the lymphocytes and T lymphocytes. Because some patients had multiple measurements during hospitalization, the biomarkers were time-varying. Age was included in the adjusted analysis. Areas under the curve (AUC) applied to assess the diagnostic values of the biomarkers. The Youden index was used to set cutoff values. All analyses were performed using R 3.6.1.
3. Results
3.1. The association of lymphocytes and T lymphocytes with the aggravation of patients
Among 164 moderate patients in our study, 20 (12.2%) patients progressed to severe cases after admission. The demographic characteristics and clinical measurements of the patients were presented in Table 1. We could notice that the aggravated patients were often older. The means of age were 51.5 years for the aggravated patients and 45.3 years for the stable patients (P = .11). However, if we included 170 moderated infected patients without T lymphocyte measurements, their age would be a significant risk factor for disease progression. The mean age was 53.2 years for the aggravated patients and 43.7 years for the stable patients (P < .0001). Compared with the stable patients, the median levels of T lymphocytes, CD4+, and CD8+ T lymphocytes in the aggravated patients were significantly lower.
Table 1.
Demographics and the baseline characteristics of the patients.
| Overall | Stable | Aggravated | P-value | |
|---|---|---|---|---|
| N (%) | 164 | 144 (88.8) | 20 (12.2) | |
| Age (SD)* | 46.0 (16.5) | 45.3 (16.5) | 51.5 (15.5) | .11 |
| Age groups | ||||
| <40 | 64 | 59 (92.2) | 5 (7.8) | .18 |
| 40–59 | 60 | 53 (88.3) | 7 (11.7) | |
| ≥60 | 40 | 32 (80) | 8 (20) | |
| Gender: N (%) | ||||
| Male | 77 | 66 (85.7) | 11 (14.3) | .48 |
| Female | 87 | 78 (89.7) | 9 (10.3) | |
| Median (25%, 75%) | ||||
| Lymphocyte count (cells/nL)† | 1.32 (1.00, 1.77) | 1.4 (1.06, 1.84) | 1.06 (0.92, 1.29) | .0004 |
| T cell count (cells/mm3) | 1040 (703, 1396) | 1060 (728, 1412) | 696 (576, 1187) | .01 |
| CD4+ count (cells/mm3) | 577 (403, 739) | 593 (437, 756) | 392 (333, 646) | .01 |
| CD8+ count (cells/mm3) | 354 (236, 531) | 368 (240, 538) | 277 (168, 390) | .07 |
| T cell (%) | 67.6 (61, 72.9) | 68.8 (61.7, 73.6) | 63.5 (54.4, 67.8) | .006 |
| CD4+ (%) | 37.4 (32.4, 43) | 38.2 (33, 43.2) | 33.2 (30.6, 38.2) | .04 |
| CD8+ (%) | 24.3 (18.3, 29.2) | 24.6 (18.3, 29.5) | 19.8 (18.2, 27.2) | .25 |
| CD4/CD8 | 1.58 (1.19, 2.16) | 1.58 (1.22, 2.1) | 1.54 (1.12, 2.16) | .80 |
The age was significant including 170 moderated infected patients without T cell test. The mean of age was 53.2 for the aggravated versus 43.7 for the stable (P < .0001).
Among 311 patients with lymphocyte test, 269 (86.5%) patients were stable, and 42 (13.5%) patients were aggravated.
The association between disease worsening and T lymphocyte counts is presented in Table 2. Because there were 67 patients with 2 to 7 measurements of T lymphocytes during hospitalization, the total number of measurements was 308 (1280 for lymphocyte). For every 10% increase, the aggravation was associated with lymphocyte count (cells/nL) (hazard ratio [HR] = 0.91; 95% confidence interval [CI]: 0.85, 0.97; P = .0063), T lymphocyte count (HR = 0.91; 95% CI: 0.84, 0.99; P = .0205), CD4+ count (HR = 0.91; 95% CI: 0.85, 0.98; P = .0135). When lymphocyte count increased by 10% (for example, from 1 to 1.1 cells/nL), the risk of aggravation decreased by 9%; when T lymphocyte count increased by 10%, the risk decreased by 9%; when CD4+ count increased by 10%, the risk decreased by 9%. The aggravation was associated with the percentage of total T lymphocytes (HR = 0.95; 95% CI: 0.92, 0.99; P = .01), and CD4+ (HR = 0.94; 95% CI: 0.90, 0.99; P = .0183) for every 1% increase. The higher level of CD8+ was associated with lower risk of aggravation.
Table 2.
The hazard ratio of lymphocytes and T cells.
| Biomarker | Hazard ratio | |
|---|---|---|
| Unadjusted model | Adjusted model† | |
| Count | (every 10% increase) | |
| Lymphocyte count (cells/nL)b | 0.89 (0.84, 0.95)*** | 0.91 (0.85, 0.97)** |
| T cell count (cells/mm3) | 0.9 (0.84, 0.97)** | 0.91 (0.84, 0.99)* |
| CD4+ count (cells/mm3) | 0.9 (0.84, 0.97)** | 0.91 (0.85, 0.98)* |
| CD8+ count (cells/mm3) | 0.94 (0.88, 1.00) | 0.95 (0.88, 1.02) |
| Percentage (%) | (every 1% increase) | |
| T cell | 0.95 (0.92, 0.98)** | 0.95 (0.92, 0.99)* |
| CD4+ | 0.94 (0.89, 0.99)* | 0.94 (0.9, 0.99)* |
| CD8+ | 0.97 (0.91, 1.02) | 0.98 (0.92, 1.04) |
| Percentage ratio | (every 10% increase) | |
| CD4/CD8 | 0.97 (0.89, 1.07) | 0.96 (0.87, 1.05) |
Adjusted for age.
P < .05.
P < .01.
P < .001.
3.2. T lymphocytes as biomarkers to predict high risk of aggravation
Receiver operating characteristic curve analysis was performed to obtain the optimal cut-point by maximizing the Youden index. As shown in Table 3, the total T lymphocyte percentage had the largest AUC of 0.689 (95% CI: 0.574, 0.804). The optimal cut-point value was 68.4% and was associated with a sensitivity of 85% and specificity of 52%. Lymphocyte, total T lymphocyte, and CD4+ had similar AUCs. Because the 95% CI of AUC for CD8+ was 0.5, CD8+ was a poor biomarker to predict the aggravation. The cut points for the total T lymphocyte and CD4+ percentages were close to the lower bound of the normal range, indicating that the lower bound of the normal total T lymphocyte and CD4+ range could be used to identify the patients with high the risk of aggravation.
Table 3.
The optimal cut points obtained by receiver operating characteristic (ROC) curve.
| Biomarker | AUC (95% CI) | Cut point | Sensitivity | Specificity | Normal range |
|---|---|---|---|---|---|
| Lymphocyte count (cells/nL) a | 0.671 (0.587,0.754) | 1.29 | 0.76 | 0.56 | 1.0–4.8 |
| Total T cell count (cells/mm3) | 0.671 (0.542,0.800) | 711 | 0.55 | 0.77 | |
| CD4+ count (cells/mm3) | 0.676 (0.539,0.813) | 409 | 0.60 | 0.78 | 500–1200 |
| CD8+ count (cells/mm3) | 0.626 (0.496,0.755) | 362 | 0.75 | 0.51 | 200–800 |
| T cell (%) | 0.689 (0.574,0.804) | 68.4 | 0.85 | 0.52 | 65–79 |
| CD4+ (%) | 0.640 (0.501,0.779) | 34.7 | 0.65 | 0.66 | 34–52 |
| CD8+ (%) | 0.580 (0.450,0.711) | 20.2 | 0.55 | 0.70 | 21–39 |
The biomarkers were categorized into 2 groups by the cut points. Table 4 presented the hazard ratio of the high-level group to the low-level group. Lymphocyte, total T lymphocyte and CD4+ were significant with HR (95% CI) ranging from 0.20 (0.06, 0.68) to 0.33 (0.16, 0.68). The Kaplan–Meier curves showed that patients with high counts of lymphocyte, total T lymphocyte, and CD4+ had significantly lower risks of aggravation, compared with patients with low counts (Fig. 1). A small fraction of moderate infected patients developed into severe status in the first 2 weeks after admission. The median duration from the first measurement on admission to the severe status was 12 days (range 1–46 days).
Table 4.
The hazard ratio of categorized lymphocytes and T cells.
| Biomarker |
Level |
Overall | Stable | Aggravated | Hazard ratio (95% CI) | |
|---|---|---|---|---|---|---|
| N | N(%) | N(%) | Unadjusted | Adjusted† | ||
| Lymphocyte count (cells/nL) | ≤1.29 | 150 | 118 (78.7) | 32 (21.3) | Reference | Reference |
| >1.29 | 161 | 151 (93.8) | 10 (6.2) | 0.28 (0.14, 0.57)*** | 0.33 (0.16, 0.68)** | |
| T cell count (cells/mm3) | ≤711 | 44 | 33 (75) | 11 (25) | Reference | Reference |
| >711 | 120 | 111 (92.5) | 9 (7.5) | 0.29 (0.12, 0.7)** | 0.32 (0.13, 0.82)** | |
| CD4+ count (cells/mm3) | ≤409 | 43 | 31 (72.1) | 12 (27.9) | Reference | Reference |
| >409 | 121 | 113 (93.4) | 8 (6.6) | 0.22 (0.09, 0.54)* | 0.24 (0.1, 0.58)** | |
| CD8+ count (cells/mm3) | ≤362 | 85 | 70 (82.4) | 15 (17.6) | Reference | Reference |
| >362 | 79 | 74 (93.7) | 5 (6.3) | 0.34 (0.13, 0.95)* | 0.4 (0.14, 1.14) | |
| T cell (%) | ≤68.4 | 86 | 69 (80.2) | 17 (19.8) | Reference | Reference |
| >68.4 | 78 | 75 (96.2) | 3 (3.8) | 0.19 (0.05, 0.64)** | 0.20 (0.06, 0.68)* | |
| CD4+ (%) | ≤34.7 | 62 | 49 (79) | 13 (21) | Reference | Reference |
| >34.7 | 102 | 95 (93.1) | 7 (6.9) | 0.31 (0.12, 0.77)*** | 0.29 (0.12, 0.73)** | |
| CD8+ (%) | ≤20.2 | 54 | 43 (79.6) | 11 (20.4) | Reference | Reference |
| >20.2 | 110 | 101 (91.8) | 9 (8.2) | 0.39 (0.16, 0.93)* | 0.44 (0.18, 1.1) | |
Adjusted for age.
P < .05.
P < .01.
P < .001.
Figure 1.
The Kaplan–Meier curves for illness aggravation based on different subsets of lymphocytes.
4. Discussion
T lymphocytes and their subsets play an important role in viral and tumor immunity.[11,12] The counts of T lymphocytes and their subsets that play an important role in viral immunity are often associated with disease severity and prognosis. In this study, we analyzed the correlation between T lymphocytes and the subsets and disease progression in COVID-19 patients.
We found that the counts of T lymphocytes, CD4+ T lymphocytes in the aggravated patients were significantly lower than those in stable patients, while there was no statistical difference in CD8+ T lymphocytes and CD4/CD8 ratio. Jiang et al demonstrated CD4+T and CD8+T lymphocytes as candidate diagnostic markers in the diagnosis of COVID-19 and the prediction of disease severity.[13] Zhang et al also observed that both CD4+T and CD8+T counts significantly reduced in severe COVID-19 group compared with non-severe group. The ratio of CD4/CD8 showed no significant difference between these 2 groups.[11] Furthermore, CD4+and CD8+T lymphocytes counts reflected the severity of infection of SARS and were good markers of disease activity.[14–16] These differences may be caused by insufficient samples or different detection methods, and further verification is needed in the future.
In conclusion, the results showed that compared with the stable patients, the median count of T lymphocytes and CD4+ T lymphocytes in the aggravated patients were significantly decreased. Instead, there were no significant differences in CD8+ T lymphocytes and CD4/CD8 ratio between the 2 groups. These findings could help to develop new biomarkers for the prediction of disease progression in COVID-19 patients.
Acknowledgments
We are grateful to the Shenzhen Third People’s Hospital and Shenzhen Second People’s Hospital in Guangdong Province for providing technical guidance and COVID-19 patients information.
Author contributions
Conceptualization: Lu Tang, Shengkun Zhang.
Funding acquisition: Lanlan Wei.
Investigation: Lanlan Wei.
Methodology: Xiaobao Zhao, Siwei Zhang, Shengkun Zhang, Dongdong Huang.
Project administration: Shengkun Zhang.
Software: Siwei Zhang, Dongdong Huang.
Supervision: Siwei Zhang, Ming Chu.
Visualization: Xiaobao Zhao, Lu Tang.
Writing – original draft: Xiaobao Zhao.
Writing – review & editing: Fuxiang Wang, Ming Chu.
Abbreviations:
- AUC
- areas under the curve
- CI
- confidence interval
- COVID-19
- coronavirus disease 2019
- HR
- hazard ratio
This study was supported by Shenzhen Science and Technology R&D Fund, Grant No. JCYJ20200109144203815.
The authors have no conflicts of interest to disclose.
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
How to cite this article: Chu M, Zhao X, Tang L, Zhang S, Zhang S, Huang D, Wang F, Wei L. The correlation of lymphocytes with disease progression of COVID-19. Medicine 2023;102:48(e36244).
Contributor Information
Ming Chu, Email: chuming120@163.com.
Xiaobao Zhao, Email: 12133177@mail.sustech.edu.cn.
Lu Tang, Email: T15377182437@163.com.
Siwei Zhang, Email: 807892157@qq.com.
Shengkun Zhang, Email: 807892157@qq.com.
Dongdong Huang, Email: hs98777@163.com.
Fuxiang Wang, Email: 13927486077@163.com.
References
- [1].Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382:727–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [2].Lu H, Stratton CW, Tang YW. Outbreak of pneumonia of unknown etiology in Wuhan, China: the mystery and the miracle. J Med Virol. 2020;92:401–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [3].Hui DS, Azhar EI, Madani TA, et al. The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health – The latest 2019 novel coronavirus outbreak in Wuhan, China. Int J Infect Dis. 2020;91:264–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [4].Wu Y, Ho W, Huang Y, et al. SARS-CoV-2 is an appropriate name for the new coronavirus. Lancet. 2020;395:949–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Tan L, Wang Q, Zhang D, et al. Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study. Signal Transduct Target Ther 2020;5:33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497–506. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395:507–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [8].Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323:1061–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].Diao B, Wang C, Tan Y, et al. Reduction and functional exhaustion of T cells in patients with coronavirus disease 2019 (COVID-19). Front Immunol. 2020;11:827. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [10].Liu Z, Long W, Tu M, et al. Lymphocyte subset (CD4+, CD8+) counts reflect the severity of infection and predict the clinical outcomes in patients with COVID-19. J Infect. 2020;81:318–56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].Zhang H, Wu T. CD4+T, CD8+T counts and severe COVID-19: A meta-analysis. J Infect. 2020;81:e82–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [12].Feng M, Wang F, Liu X, et al. Neutrophils as key regulators of tumor immunity that restrict immune checkpoint blockade in liver cancer. Cancer Biol Med 2023;20:421–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Jiang M, Guo Y, Luo Q, et al. T-cell subset counts in peripheral blood can be used as discriminatory biomarkers for diagnosis and severity prediction of coronavirus disease 2019. J Infect Dis. 2020;222:198–202. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [14].Wong RS, Wu A, To KF, et al. Haematological manifestations in patients with severe acute respiratory syndrome: retrospective analysis. BMJ 2003;326:1358–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [15].Luo M, Ni K, Sun Y, et al. Toward an optimized strategy of using various airway mucus clearance techniques to treat critically ill COVID-19 patients. Biocell. 2022;46:855–71. [Google Scholar]
- [16].Ozturk A, Kara M. Diagnostic and prognostic significance of the lymphocyte/C-reactive protein ratio, neutrophil/lymphocyte ratio, and D-dimer values in patients with COVID-19. Biocell. 2022;46:2625–35. [Google Scholar]