key: cord-0879770-b3nla9di
authors: Liu, Jing; Li, Sumeng; Liu, Jia; Liang, Boyun; Wang, Xiaobei; Wang, Hua; Li, Wei; Tong, Qiaoxia; Yi, Jianhua; Zhao, Lei; Xiong, Lijuan; Guo, Chunxia; Tian, Jin; Luo, Jinzhuo; Yao, Jinghong; Pang, Ran; Shen, Hui; Peng, Cheng; Liu, Ting; Zhang, Qian; Wu, Jun; Xu, Ling; Lu, Sihong; Wang, Baoju; Weng, Zhihong; Han, Chunrong; Zhu, Huabing; Zhou, Ruxia; Zhou, Helong; Chen, Xiliu; Ye, Pian; Zhu, Bin; Wang, Lu; Zhou, Wenqing; He, Shengsong; He, Yongwen; Jie, Shenghua; Wei, Ping; Zhang, Jianao; Lu, Yinping; Wang, Weixian; Zhang, Li; Li, Ling; Zhou, Fengqin; Wang, Jun; Dittmer, Ulf; Lu, Mengji; Hu, Yu; Yang, Dongliang; Zheng, Xin
title: Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients
date: 2020-04-18
journal: EBioMedicine
DOI: 10.1016/j.ebiom.2020.102763
sha: b5d65ff23de3ee217535620b1f66ddd268d94f20
doc_id: 879770
cord_uid: b3nla9di

Abstract Background The dynamic changes of lymphocyte subsets and cytokines profiles of patients with novel coronavirus disease (COVID-19) and their correlation with the disease severity remain unclear. Methods Peripheral blood samples were longitudinally collected from 40 confirmed COVID-19 patients and examined for lymphocyte subsets by flow cytometry and cytokine profiles by specific immunoassays. Findings Of the 40 COVID-19 patients enrolled, 13 severe cases showed significant and sustained decreases in lymphocyte counts [0•6 (0•6-0•8)] but increases in neutrophil counts [4•7 (3•6-5•8)] than 27 mild cases [1.1 (0•8-1•4); 2•0 (1•5-2•9)]. Further analysis demonstrated significant decreases in the counts of T cells, especially CD8+ T cells, as well as increases in IL-6, IL-10, IL-2 and IFN-γ levels in the peripheral blood in the severe cases compared to those in the mild cases. T cell counts and cytokine levels in severe COVID-19 patients who survived the disease gradually recovered at later time points to levels that were comparable to those of the mild cases. Moreover, the neutrophil-to-lymphocyte ratio (NLR) (AUC=0•93) and neutrophil-to-CD8+ T cell ratio (N8R) (AUC =0•94) were identified as powerful prognostic factors affecting the prognosis for severe COVID-19. Interpretation The degree of lymphopenia and a proinflammatory cytokine storm is higher in severe COVID-19 patients than in mild cases, and is associated with the disease severity. N8R and NLR may serve as a useful prognostic factor for early identification of severe COVID-19 cases. Funding The National Natural Science Foundation of China, the National Science and Technology Major Project, the Health Commission of Hubei Province, Huazhong University of Science and Technology, and the Medical Faculty of the University Hospital Essen, Germany.

Evidence before this study Lymphopenia and inflammatory cytokine storm have been shown in severe acute respiratory syndrome coronavirus (SARS-CoV), the Middle East respiratory syndrome coronavirus (MERS-CoV) infections, and coronavirus disease .

For the first time, the kinetic changes of lymphopenia, lymphocyte subset and cytokine profile were longitudinally characterized. The significant decreases in the count of CD8 + T cell number and increase in inflammatory cytokine levels (e.g. IL-6, IL-10) are dynamically correlated with the severity of COVID-19 patients. T cell counts and cytokine levels in severe COVID-19 patients who survived the disease gradually recovered at later time points to levels that were comparable to those of the mild cases. Neutrophil-to-lymphocyte ratio (NLR) (AUC=0·93) and neutrophil-to-CD8 + T cell ratio (N8R) (AUC =0·94) were identified as powerful prognostic factors affecting the prognosis for severe COVID-19.

The development of severe COVID-19 is the result of imbalanced inflammation and antiviral immune responses. N8R and NLR can serve as useful prognostic factor for early identification of severe COVID-19 cases. This will help physicians to provide timely intervention for COVID-19.

First reported in Wuhan, China, on 31 December 2019, an ongoing outbreak of a viral pneumonia in humans has raised acute and grave global concern, and rapidly spread to 197 countries, areas or territories. 1 The causative pathogen was rapidly identified as a novel β-coronavirus, which has since been formally named as the severe acute patients showing symptoms of fever, dry cough, fatigue, abnormal chest CT findings but with a good prognosis. [3] [4] In contrast, some patients develop severe pneumonia, acute respiratory distress syndrome (ARDS) or multiple organ failure, with death rates ranging from between 4·3% to 15% according to different study reports. 3, 5 Lymphopenia (lymphocyte count <1·0×10⁹/L) 3 and inflammatory cytokine storm are typical laboratory abnormalities observed during highly pathogenic coronavirus infections, such as the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV) infections, and are believed to be associated with disease severities. [6] [7] Recent studies have also reported decreases in the counts of lymphocytes (e.g. CD4 + T cell, CD8 + T cell) in the peripheral blood and increases in serum inflammatory cytokine levels (e.g. IL-6) in COVID-19 patients. 5, [8] [9] [10] However, it has remained largely unclear in the kinetics of lymphocyte subsets and inflammatory cytokines change in the peripheral blood during COVID-19. In this study, we longitudinally characterized the changes of lymphocyte subsets and cytokines profiles in the peripheral blood of COVID-19 patients with distinct disease severities.

A written informed consent was regularly obtained from all patients upon admission into Wuhan Union Hospital, China. The study was approved by the Ethics Committee of Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, in China. The 40 confirmed COVID-19 patients at Wuhan Union Hospital during January 5 to January 24, 2020 were enrolled into this retrospective single-center study. All medical record information including epidemiological, demographic, clinical manifestation, laboratory data, and outcome data were obtained. All data were checked by a team of trained physicians.

Laboratory confirmation of the SARS-CoV-2 was performed by local CDC according to Chinese CDC protocol. Throat-swab specimens were collected from all patients and the samples were maintained in a viral-transport medium for laboratory testing.

An infection with other respiratory viruses including influenza A virus, influenza B virus, coxsackie virus, respiratory syncytial virus, parainfluenza virus and enterovirus was excluded by real-time RT-PCR. Specimens, including sputum or bronchoalveolar lavage fluid, blood, urine, and feces, were cultured to identify pathogenic bacteria or fungi that may be associated with the SARS-CoV-2 infection. The specific IgG and IgM of chlamydia pneumonia and mycoplasma pneumonia were detected by chemiluminescence immunoassay. The lymphocyte test kit (Beckman Coulter Inc., FL, USA) was used for lymphocyte subset analysis. Plasma cytokines (IL2, IL4, IL6, IL10, TNF -α and IFNγ) were detected using the human Th1/2 cytokine kit II (BD Ltd., Franklin lakes, NJ, USA). All tests were performed according to the product manual.

Classification variables are expressed in frequency or percentage, and significance was detected by chi square or Fisher's exact test. The quantized variables of parameters are expressed as mean ± standard deviation, and the significance is tested by t-test. Nonparametric variables are expressed in median and quartile intervals, and significance was tested by Mann Whitney U or Kruskal Wallis test. Data (nonnormal distribution) from repeated measures were compared using the generalized linear 

The diagnosis of COVID-19 for patients was performed according to the Guidelines Table 1) . Only 3 patients (7·5%) had an exposure history (shopping) to the Huanan seafood market in Wuhan. The medium age of the patients was 48·7 ± 13·9 years old. The ages of the severe patient group (59·7 ± 10·1 years) were older than that of the mild group (43·2 ± 12·3 years). The duration of hospitalization was 12·6 ± (Table 1 ). All severe patients and 85·2% of the mild patients had fever, while no significant difference in the degrees of temperature was observed between the two groups ( Table 1 ). The severe patients showed significantly higher frequencies in the occurrence of sputum production, myalgia and nausea. Three patients in the severe group developed (acute respiratory distress syndrome, ARDS). All patients received antiviral treatment, including interferon α2b (16, 40·0%), ribavirin (24, 60·0%), abidol (18, 45·0%), and/or oseltamivir (17, 42·5%), as well as antibiotic treatment, including moxifloxacin (40, 100%), cephalosporins (20, 50%), penicillin (1, 2·5%), and/or other antibiotics (29, 72·5%).

Seventeen (42·5%) patients received antifungal treatment (13 cases took prophylactic treatment) and 8 (20%) received methylprednisolone therapy (1 mild case and 7 severe cases) ( Table S1 ). The levels of fibrinogen, D-dimer, total bilirubin, aspartate transaminase, alanine transaminase, lactate dehydrogenase, creatine kinase, C-reactive protein (CRP), ferritin and serum amyloid A protein (SAA) in the peripheral blood of the severe patients were significantly higher at admission compared to the mild patients ( Table 2) . No significant differences in the serum levels of immunoglobulins (IgA, IgG and IgM), complement C3 or C4 were observed between the two groups ( Table 2) . We also analyzed the impact of methylprednisolone treatment on the lymphocyte and neutrophil counts, as well as other cytokine levels. The results showed that patients with methylprednisolone treatment had higher lymphocyte counts, lower neutrophil counts, NLR, N8R and serum IL-6 levels than patients without methylprednisolone treatment. However, the differences were not statistically significant (Table S2) .

Lymphopenia was observed in 44·4% (12/27) of mild patients and 84·6% (11/13) of severe patients at the onset of the disease. As shown in Table 2 , the absolute counts of lymphocytes in the peripheral blood of the severe patients was significantly lower, while the absolute counts of total white blood cells (WBCs) and neutrophils were significantly higher than those of the mild patients at the time of hospital admission.

No significant difference in monocyte counts was observed between the two groups (Table 2 ). Next, we analyzed the kinetic changes of WBCs, neutrophils and monocytes as well as different lymphocyte subsets in the peripheral blood of COVID-19 patients from the disease onset to at least 16 days later. The three mortalities in the severe group were excluded from the analysis due to the lack of kinetic data. Significant increases in total WBCs counts in the severe group were only Figure S4b ). In contrast, significant decreases in lymphocyte counts of the severe group were observed at the time point of disease onset and became even greater on 4-6 days later compared to those of the mild patients ( Figure S4c ). No significant differences in monocyte counts were observed between the two groups during the whole observation period ( Figure S4d ).

In order to further determine the kinetic changes of different lymphocyte subsets in the peripheral blood of COVID-19 patients, we performed flow cytometry to stain CD3 + T cells, CD4 + and CD8 + T cell subsets, B cells and NK cells. Similar to the findings for lymphocytes, sustained decreases in CD3 + , CD8 + and CD4 + T cell counts were observed in the severe group compared to those of the mild patients during clinical observation (Figure 2a -c, Figure S1 ). The lowest CD3 + , CD4 + and CD8 + T cell counts were observed at 4-6 days after disease onset (Figure 2a-c) . The differences in CD3 + and CD8 + T cell counts between the two groups were significant at the time point of disease onset and 7-9 days later (Figure 2a and 2c) . However, the differences in CD4 + T cell counts between the two groups did not reach a statistical significance at any time point (Figure 2c ). The T cell counts started to gradually increase in the severe group starting at 7 days after disease onset, and reached comparable levels to those in the mild patients on day 16 after disease onset ( Figure   2a -c). No significant differences in B cell and NK cell counts were observed between the two groups during the whole course of the disease (Figure 2d and 2e) .

A previous study demonstrated changes in inflammatory cytokine levels, such as IL-2, IL-7, IL-10, and TNF-α, in the serum of COVID-19 patients. 3 Therefore, we further characterized the kinetic changes of inflammatory cytokine levels, including IL-2, IL-4, IL-6, IL-10, IFN-γ and TNF-α, in the serum of our patient cohort. Fluctuations in the serum levels of these cytokines in the mild patient group were minor. In contrast, the severe patient group showed more significant fluctuations in the serum levels of these cytokines (Figure 3 ). All examined cytokines, except IL-6, reached their peak levels in the serum at 3-6 days after disease onset (Figure 3 ). Both IL-6 and IL-10 levels showed sustained increases in the severe group compared to the mild group (Figure 3a and 3b) . Reductions in serum IL-6 levels in the severe group started at 16 days after disease onset, and IL-10 levels were lowest at 13 days after disease onset (Figure 3a and 3b ). Significant increases in serum IL-2 and IFN-γ levels in the severe group were only observed at 4-6 days after disease onset (Figure 3c and 3f) .

No significant differences in IL-4 and TNF-α levels were observed between the two groups during the whole course of the disease (Figure 3d and 3e). All examined cytokines reached similar levels between the severe and mild patient groups at 16 days after disease onset (Figure 3 ). We observed higher CRP levels in the severe group than the mild group at most time points; however, the differences were not significant ( Figure S6 ). Moreover, we also performed the analyses by excluding the 4 patients with fungal co-infections from the severe patient group. We observed that both IL-6 and IL-10 levels showed sustained increases in the severe group compared to the mild group ( Figure S3a and S3b). Significant increases in serum IFN-γ levels in the severe group were only observed at 4-6 days after disease onset ( Figure S3f ). No significant differences in IL-2, IL4 and TNF-α levels were observed between the two groups during the whole course of the disease ( Figure S3c, 3d and 3e ).

Next, we examined the possibilities of using above-mentioned parameters as prognostic factors for identifying severe cases in COVID-19 patients. PCA was firstly performed by R package "factoextra" to identify correlated variables for distinguishing severe patients from mild patients (Figure 4a ). Four most contributing variables, neutrophil-to-CD8 + T cell ratio (N8R), neutrophil-to-lymphocyte ratio (NLR), neutrophil counts (NEC) and white blood cells counts (WBCC) were selected as potential prognostic factors for further detailed statistical analysis. To assess the diagnostic value of these four selected parameters, the receiver operating characteristic (ROC) curve and the area under ROC curve (AUC) were calculated by R package "pROC" (Figure 4b) . The results of this analysis identified N8R with a higher AUC (0·94) than NLR (0·93), NE (0·91) and WBC (0·85) (Figure 4b) .

Simultaneously, the cutoff values were calculated from the ROC curves, with a value of 21·9 for N8R (Specificity: 92·6%, Sensitivity: 84·6%), 5·0 for NLR (96·3%, 0·828±0·198. The predictive performances of N8R and NLR were still significant when fungal co-infection cases were excluded from the group ( Figure S2b ).

In this study, we analyzed the clinical features and immunological characteristics of peripheral blood in patients with COVID-19. Although the majority of the patients did not have an exposure history to the Huanan seafood market in Wuhan, the clinical characteristics of these patients are very similar to those reported in previous studies. 3, 5, 11 In severe patients, the ages as well as the proportion of underlying diseases are higher, and co-infection also occurs. Recent reports show that the lymphocyte counts are normal in COVID-19 patients with mild diseases. In contrast, 63%-70·3% of patients with severe diseases have lymphopenia and the lymphocyte counts in patients with a mortal outcome remain at a low level. 5, 11 Our study also confirmed higher rates of developing lymphopenia in severe patients than in mild patients (84·6% vs 44·4%).

Recent studies reported that the SARS-CoV-2 infection may primarily affect T lymphocytes particularly CD4 + T and CD8 + T cells, which might be highly involved in the pathological process of COVID-19 . 10 We also found that the development of lymphopenia in severe patients was mainly related to the significantly decreased absolute counts of T cells, especially CD8 + T cells, but not to the absolute counts of B cells and NK cells. The decrease of T cells in the severe patient group reached its peak within the first week during the disease course, and then T cell numbers gradually increased during the second week and recovered to a comparable level to that of the mild patient group in the third week. All the severe patients included in our study survived the disease, and thus we speculate this course is associated with a favorable outcome in severe COVID-19 patients. A recent study in a 61-patient cohort reported that the NLR was the most useful prognostic factor affecting the prognosis for severe COVID-19, 17 and immunological markers (e.g. CD4 + T cell, CD8 + T cell, NLR) tend to be an independent predictor for COVID-19 severity and treatment efficacy. 9, 18 The severity of pathological injury during SARS or MERS correlates with the extensive infiltration of neutrophils in the lung and increased neutrophil numbers in the peripheral blood. 19 Thus, the magnitude of increase in neutrophil counts may suggest the intensity of inflammatory responses in COVID-19 patients. Besides, the magnitude of the decrease in lymphocyte counts also indicates the extent of the impairment of immune system by the viral infection.

Therefore, NLR may serve as a useful factor to reflect the intensity of imbalance of inflammation and immune responses in COVID-19 patients. In this study, we also screened the potential prognostic factors affecting the incidence of severe illness in our patient cohort. Based on our findings with analyzing lymphocyte subsets, we further included the ratio of neutrophils to different lymphocyte subsets as parameters.

Our kinetic analysis revealed that CD8 + T cells are the major lymphocyte subset which decreases in cell numbers during COVID-19. In line with this finding, our results demonstrate that N8R has a comparable performance with NLR in the ROC curve analysis, and both N8R and NLR may serve as powerful factors for predicting the severe illness incidence in COVID patients.

In summary, our study of the immunological characteristics of the peripheral blood in COVID-19 patients shows that the numbers of neutrophils and T cells, especially CD8 + T cells, as well as the levels of inflammatory cytokines in the peripheral blood is dynamically correlated with the severity of the disease. To the best of our knowledge, this is the first work to describe the kinetic changes of lymphocyte subsets and cytokine profiles in COVID-19 patients. Importantly, we identified N8R and NLR as powerful prognostic factors for the early identification of severe COVID-19 cases.

This work may help to achieve a better understanding of immune function disorder as well as immunopathogenesis during SARS-CoV-2 infection, and help physicians to provide timely intervention for COVID-19.

We thank all the doctors, nurses, disease control workers, and researchers who have fought bravely and ceaseless against the virus at the frontline during the SARS-CoV-2 epidemic, some of whom lost their lives in doing so. We thank those who have given great and selfless support to the fight against the virus. We thank Ms. Delia Cosgrove and Ms. Ursula Schrammel for the language correction of this manuscript.

This work is supported by the National Natural Science Foundation of China sources of this study did not play any role in the study design, the collection, analysis and interpretation of the data, in the writing of the manuscript and in the decision to submit the paper for publication.

The authors disclose no conflicts of interest. C3 (g/l) 0·8 ± 0·2 0·8 ± 0·2 0·8 ± 0·1 C4 (g/l) 0·3 ± 0·1 0·3 ± 0·1 0·3 ± 0·1 

Acquisition of data

All authors reviewed and approved the final version of the manuscript

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Figure 4. Prognostic factors of severe COVID-19

Principal component analysis was performed by R package "factoextra" to identify correlated variables for distinguishing severe patients from mild COVID-19 patients. Four mostly contributing variables, neutrophil-to-CD8 + T cell ratio (N8R), neutrophil-to-lymphocyte ratio (NLR), neutrophil counts (NE) and White Blood Cells counts (WBC) were identified. (b) ROC curve and AUC were calculated for these 4 selected parameters by using R package "pROC