A 3-Week Dynamic Differences of Immunological Parameters in Severe and Non-severe COVID-19

Objective We aimed to compare the dynamic differences of immunological parameters in severe and non-severe COVID-19. Methods In this study, the cytokine proles and lymphocyte subsets of 70 patients (31 severe COVID-19 and 39 non-severe COVID-19) were longitudinally analyzed. Results Compared with non-severe cases, severe cases had higher age (64 vs 36 years, p<0.001), more common comorbidities (74.2% vs 15.4%, p<0.001), and more frequently lymphopenia (0.7 vs 1.6×10 9 /L, p<0.001). Severe cases had markedly higher levels of IL-6, IL-8, and IL-10 than non-severe cases from baseline to 3 weeks after admission (p<0.001). No signicant differences were observed in the levels of IL-1β, IL-2, IL-4, IL-5, IL-12P70, IL-17, TNF-α, IFN-α, and IFN-γ between the two groups during the follow-up (p > 0.05). The absolute numbers of CD3+, CD4+, CD8+, and CD45+ T cells were markedly lower in severe cases compared with that in non-severe cases from baseline to 3 weeks after admission (p<0.001). The decrease of T lymphocyte subsets reached its peak from day 1 to 3 after admission, and gradually increased from day 4 to 21 in the non-severe group; however, reached its peak from day 4 to 7 after admission, and sustained at a low levels in the severe group. Conclusion The dynamic changes of cytokine proles and T lymphocyte subsets are related with the disease severity of patients with COVID-19. kit (Shanghai Bio-Germ) with amplication targeting the ORF1a/b and N gene. Conditions for the amplications were 50 °C for 15 minutes, 95 °C for 3 minutes, followed by 45 cycles of 95 °C for 15 seconds and 60 °C for 30 seconds. The lymphocyte test kits (Becton Dickinson and Company, California, USA) were used for the lymphocyte subset analysis. Twelve plasma cytokines (IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12P70, IL-17, TNF-α, IFN-α, and IFN-γ) were detected using the human cytokine kit II (Raisecare Ltd, Qingdao, China). All tests were performed according to the manufacturers’ instructions.


Introduction
Since November 2019, the rapid outbreak of 2019 novel coronavirus disease , which caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global public health emergency. Person-to-person transmission of SARS-CoV-2 has been con rmed in hospital and family settings [1] . The number of con rmed cases and death cases has been quickly growing, and as of June 16th, 2020, there have been 7941, 791 con rmed cases and 434, 796 deaths globally [2] . The clinical characteristics of COVID-19 had been reported in numerous researches, which suggested that most patients with COVID-19 had a good prognosis, but there were still some patients developed to severe cases rapidly, and then resulting in death [3] .
The key point in the disease progression of COVID-19 could be the depletion of antiviral defenses related to innate immune response as well as an elevated production of in ammatory cytokines [4] . Cytokines are a broad category of relatively small proteins (< 40 kDa) that are produced and released with the aim of cell signaling [5] . Recently, more and more data suggest that there are cytokine storms in severe patients with COVID-19, which is an important cause of death [6] . Huang et al analyzed the rst 41 cases with COVID-19, and found that compared with non-ICU patients, ICU patients had higher plasma levels of cytokines, which could be associated with disease severity [7] . Chen et al analyzed 21 cases with COVID- 19, and found that compared with moderate cases, severe cases had markedly higher levels of cytokines, and markedly lower numbers of T lymphocytes, CD4 + T cells, and CD8 + T cells [8] . Ulhaq et al also presented the evidence that circulating IL-6 levels are closely linked to the severity of COVID-19 [9] .
Although there are some reports on the baseline levels of immunological parameters in patients with , the data about the dynamics of cytokines and T lymphocyte subsets in patients with COVID-19 is relatively few. In this study, we performed a 3-week dynamic comparison of immunological parameters between 31 severe and 39 non-severe cases with COVID-19. The results may help us extend our understanding of the risk factors associated with disease severity following the SARS-CoV-2 infection.

Study participants
From January 20th 2020 to June 10th 2020, a total of 31 severe cases with COVID-19 hospitalized in Shanghai Public Health Clinical Center, Shanghai, China, were enrolled into this study. As a comparison group, 39 non-severe cases with COVID-19 hospitalized in Shanghai Public Health Clinical Center from May 1th 2020 to May 14th 2020 were enrolled. All patients were con rmed infected with SARS-CoV-2 by the Chinese Center for Disease Control and Prevention.

Diagnostic criteria
Patients with COVID-19 were con rmed by the positive results of SARS-COV-2 nucleotides tests in the nasopharyngeal or throat swab specimens using the real-time polymerase-chain-reaction (RT-PCR) methods [10] . According to the guidelines released by the National Health Commission of China, severe cases with COVID-19 were de ned as at least one of the followings [11] : (1) Respiratory rates ≥ 30/min; (2) Oxygen saturation ≤ 93% in a resting state; (3) Oxygenation index (Pao2/Fio2) ≤ 300 mmHg; (4) Require mechanical ventilation; (5) Shock; (6) Combined with other organ failures and needed treatment in ICU.

Laboratory measurements
The SARS-CoV-2 nucleic acids were detected by RT-PCR methods using automatic magnetic extraction device and accompanying kit (Shanghai Bio-Germ) and screened with a semi-quantitative RT-PCR kit (Shanghai Bio-Germ) with ampli cation targeting the ORF1a/b and N gene. Conditions for the ampli cations were 50 °C for 15 minutes, 95 °C for 3 minutes, followed by 45 cycles of 95 °C for 15 seconds and 60 °C for 30 seconds. The lymphocyte test kits (Becton Dickinson and Company, California, USA) were used for the lymphocyte subset analysis. Twelve plasma cytokines (IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12P70, IL-17, TNF-α, IFN-α, and IFN-γ) were detected using the human cytokine kit II (Raisecare Ltd, Qingdao, China). All tests were performed according to the manufacturers' instructions.

Data collection
We retrospectively evaluated the medical records including clinical charts, nursing records, laboratory ndings, radiological tests, and immunological results obtained from 70 enrolled patients with COVID-19. The data about demographics, epidemiological characteristics, clinical characteristics, laboratory ndings, radiological manifestations, treatment, and clinical outcomes were obtained with data collection forms. The data of cytokine pro les and lymphocyte subsets were obtained from baseline to 3 weeks after admission. The data collection forms were reviewed independently by 2 researchers.

Statistical analyses
The normality test was performed for continuous variables using the Kolmogorov-Smirnov test. Normal distribution variables were expressed as mean ± standard deviation (SD) and compared using the T test. Non-normal distribution continuous variables were presented as medians [interquartile ranges (IQR)], and compared with the Mann-Whitney test. Categorical variables were showed as numbers (percentage), and compared by the chi-square test. All signi cance tests were two-tailed, and p < 0.05 was considered statistically signi cant. All statistical analyses were done using SPSS software version 15.0 (SPSS Inc. USA).

Demographics and clinical characteristics of patients with COVID-19
Demographics and clinical characteristics of patients with COVID-19 are shown in Table 1  The p values indicate differences between severe group and non-severe group. p < 0.05 was considered statistically signi cant.

Dynamic changes of cytokine pro les in patients with COVID-19
In this study, we combined the longitudinal cytokines data of severe group and non-severe group, and plotted their uctuation patterns against the time point after admission (Fig. 1). Fluctuations in the serum levels of cytokines in the non-severe cases were minor. In contrast, the severe group showed more signi cant uctuations in the serum levels of cytokines. Severe cases had markedly higher levels of IL-6, IL-8, and IL-10 than non-severe cases from baseline to 3 weeks after admission (p < 0.001) ( Table 3). No signi cant differences were observed in the levels of IL-1β, IL-2, IL-4, IL-5, IL-12P70, IL-17, TNF-α, IFN-α, and IFN-γ between the two groups during the follow-up (p > 0.05) (Fig. 1). The p values indicate differences between severe group and non-severe group. p < 0.05 was considered statistically signi cant.

Dynamic changes of T lymphocyte subsets in patients with COVID-19
In this study, we analyzed the dynamic changes of T lymphocyte subsets in severe and non-severe COVID-19 (Fig. 2). The absolute numbers of CD3+, CD4+, CD8+, and CD45 + T cells were markedly lower in severe cases compared with that in non-severe cases from baseline to 3 weeks after admission (p < 0.001) ( Table 4). The decrease of T lymphocyte subsets reached its peak from day 1 to 3 after admission, and gradually increased from day 4 to 21 in the non-severe group; however, reached its peak from day 4 to 7 after admission, and sustained at a low levels in the severe group (Fig. 2). The p values indicate differences between severe group and non-severe group. p < 0.05 was considered statistically signi cant.

Discussion
Both clinical and epidemiological features of patients with COVID-19 have been reported [7,12] . However, only a few study reported the immunological indicators of patients with COVID-19. In this study, we evaluated the immunological characteristics of COVID-19. Serum cytokines increased in the majority of severe cases with COVID-19, suggesting cytokine storms might be associated with the disease progression of COVID-19. Especially, the levels of IL-6, IL-8, and IL-10 were markedly higher in severe COVID-19, compared with non-severe COVID-19, suggesting the serum cytokines could be used as predictors for the prediction of COVID-19 progression. Additionally, we found that a laboratory feature of COVID-19 was lymphocytopenia, particularly in severe cases (initial test result after admission, 0.7 (0.5-0.9) × 10 9 /L). Detailed analysis of T lymphocytes subtypes revealed that CD3+, CD4+, CD8+, and CD45 + T cells were all signi cantly affected. More importantly, compared with non-severe cases, severe cases had markedly lower levels of T lymphocytes subtypes, suggesting that the decrease of CD3+, CD4+, CD8+, and CD45 + T cell counts might be correlated with the disease severity of COVID-19.
Previous studies also reported the correlation between immunological markers and disease severity of COVID-19. Chen et al reported that the SARS-CoV-2 infection may affect T lymphocytes, particularly CD4 + and CD8 + T cells [8] . Wan et al explored the relationships between lymphocyte subsets, cytokines and disease evolution in patients with COVID-19, and found that higher survival rates occurred in those with IL-6 within normal values, and CD4 + T, CD8 + T, IL-6, and IL-10 can be used as indicators for disease progression of COVID-19 [13] . Diao et al reported that the number of CD4 + and CD8 + T cells was dramatically reduced in COVID-19 patients, especially in patients requiring ICU care [14] . However, these studies included a small number of patients, and statistical non-signi cance may not rule out differences between groups. In addition, these studies only reported baseline data. Therefore, we showed the dynamics of cytokines and lymphocytes subsets from baseline to 3 weeks after admission.
Patients with COVID-19 admitted to the ICU have higher expression levels of cytokines, which may indicate patients at risk to develop ARDS and eventually death [7] . This circumstance is called "cytokine storm" [15] . The degree of cytokine storm determines the degree of COVID-19 progression. The more severe the cytokine storm, the more severe the ARDS, which is related to higher mortality. In this study, we found that the degree of increase in serum IL-6, IL-8, and IL-10 is signi cant, but the uctuations in TNF-α, IL-1β, IL-2, IL-4, IL-5, IL-12P70, IL-17, IFN-α, and IFN-γ were minor. The serum levels of IL-6, IL-8 and IL-10 are positively correlated with the severity of COVID-19. The results were consistent with a review, which reported that IL-6 contributes to host defense against infections and tissue injuries, and IL-6 blockade may constitute a novel therapeutic strategy for cytokine storm [16] .
Lymphocytes and the subsets of CD4 + T cells and CD8 + T cells play an important role in the maintenance of immune system function. In 2004, Li et al had reported that a rapid decrease of T cell subsets is a unique characteristic in patients with SARS during acute infection, and a rapid and dramatic restoration of T cell subsets was seen in recovering patients [17] . Wang et al reported that lymphopenia occurred in 70.3% patients with COVID-19, but any alteration in the subsets was still unknown [18] . Wang et al reported that total lymphocytes, CD4 + T cells, and CD8 + T cells decreased in COVID-19 patients, and severe cases had a lower level than mild cases. [19] . In this study, we found that, CD3+, CD4+, CD8+, and CD45 + T cells decreased in patients with COVID-19, and severe cases had a lower level than non-severe cases. We also found the difference in the dynamics of lymphocyte subsets between severe and nonsevere COVID-19. The decrease of T lymphocyte subsets reached its peak from day 1 to 3 after admission, and gradually increased from day 4 to 21 in the non-severe group; however, reached its peak from day 4 to 7 after admission, and sustained at a low levels in the severe group.
This study has some limitations. First, this is a retrospective study. The lymphocyte test kit focused on T cell subsets. We could not provide the dynamics of B cells and NK cells. However, previous study has showed that for B cells and NK cells, no obvious changes were observed among mild and severe cases (p = 0.47) [20] . Second, the data regarding the viral load of SARS-CoV-2 are not available for patients with COVID-19 in this study. Further studies are needed to investigate the correlation between the viral load kinetics and the dynamics of cytokines.

Conclusion
In conclusion, SARS-CoV-2 infection induced cytokine storm and lymphopenia, particularly a decrease in CD3+, CD4+, CD8+, and CD45 + T cell counts, as well as an increase in the levels of IL-6, IL-8, and IL-10.
The decrease of T lymphocyte subsets reached its peak from day 1 to 3 after admission, and gradually increased from day 4 to 21 in the non-severe group; however, reached its peak from day 4 to 7 after admission, and sustained at a low levels in the severe group. This study suggests a strong link between in ammatory cytokines storm and the pathogenesis of SARS-CoV-2 infection, and enhances a deeper understanding of T lymphocyte subnets and their association with the disease severity of patients with COVID-19. Kinetic analysis of cytokines levels in patients with COVID-19.

Figure 2
Kinetic analysis of cell counts of lymphocyte subsets in patients with COVID-19.