Regulatory CD4⁺ and CD8⁺ T cells are negatively correlated with CD4⁺/CD8⁺ T cell ratios in patients acutely infected with SARS-CoV-2

Abstract

Regulatory T cell can protect against severe forms of coronaviral infections attributable to host inflammatory responses. But its role in the pathogenesis of COVID-19 is still unclear. In this study, frequencies of total and multiple subsets of lymphocytes in peripheral blood of COVID-19 patients and discharged individuals were analyzed using a multicolor flow cytometry assay. Plasma concentration of IL-10 was measured using a microsphere-based immunoassay kit. Comparing to healthy controls, the frequencies of total lymphocytes and T cells decreased significantly in both acutely infected COVID-19 patients and discharged individuals. The frequencies of total lymphocytes correlated negatively with the frequencies of CD3⁻CD56⁺ NK cells. The frequencies of regulatory CD8⁺CD25⁺ T cells correlated with CD4⁺/CD8⁺ T cell ratios positively, while the frequencies of regulatory CD4⁺CD25⁺CD127⁻ T cells correlated negatively with CD4⁺/CD8⁺ T cell ratios. Ratios of CD4⁺/CD8⁺ T cells increased significantly in patients beyond age of 45 years. And accordingly, the frequencies of regulatory CD8⁺CD25⁺ T cells were also found significantly increased in these patients. Collectively, the results suggest that regulatory CD4⁺ and CD8⁺ T cells may play distinct roles in the pathogenesis of COVID-19. Moreover, the data indicate that NK cells might contribute to the COVID-19 associated lymphopenia.

Graphical Abstract

Regulatory CD4+ and CD8+ T cells are negatively correlated with CD4+/CD8+ T cell ratios in patients acutely infected with SARS-CoV-2

Introduction

Lymphocytopenia caused by acute virus infections have been suggested to be associated with increased risks of infection-related hospitalization and death.^1–4 Similar observations have also been reported in COVID-19 patients, but not all cell subsets of peripheral blood lymphocytes were reduced.^5–7 Of note, multiple studies observed the decrease of T cells consistently in the peripheral blood of COVID-19 patients.^8–11 Increased inflammatory infiltration in lungs may partially account for the decrease of lymphocytes in peripheral blood,¹² but could not explain the phenomenon completely. To uncover other potential mechanisms, a recent study analyzed the correlations between different cytokines and peripheral blood T cell counts and showed that T cell counts negatively correlated with proinflammatory cytokines, such as IL-6,⁸ suggesting that hyperinflammation might be a cause of lymphopenia in COVID-19 patients.

As a counter-regulation factor of proinflammatory immune responses, regulatory T cell (Treg) has been shown to be able to prevent cytokine storm and reduce tissue damage.^13–15 Hence, we postulated that Tregs may play protective roles against lymphopenia caused by SARS-CoV-2. To test this hypothesis, multi-color flow cytometry analysis of peripheral blood samples was conducted for 69 acutely infected patients (within 10 days after disease onset) and 27 discharged (2 weeks after discharge) individuals.

Materials and Methods

Ethics statement

Informed consents were obtained from all participants. The study was approved by the Research Ethics Review Committee (Ethics Approval Number: 2020-Y025-01) of the Shanghai Public Health Clinical Center Affiliated to Fudan University.

Clinical sample and data collection

Peripheral blood samples were collected from 69 hospitalized COVID-19 patients (within 10 days after disease onset) and 27 discharged individuals (2 weeks post discharge). Demographical characteristics of these individuals were depicted in Table 1. Three milliliters of anti-coagulated fresh peripheral blood was collected from each individual. Flow cytometry assay was performed using 100 µl fresh blood sample per test. Plasma was also freshly isolated from the rest of each sample for the measurement of IL-10. Data of healthy individuals were collected at the health screening clinic of Shanghai Public Health Clinical Center from January 2020 to May 2020. All these individuals reported no epidemiological link with confirmed COVID-19 patients and were confirmed to be free from any chronic or acute disease. vRNA tests confirmed that all these individuals were free from SARS-CoV-2 infection.

TABLE 1.

Demographics of the participants enrolled in this study

Variables	Discharged individuals	Acutely infected patients	P-value
	(N = 27)	(N = 69)
Age (year)	54.63 ± 16.72	33.65 ± 14.21	<0.0001
Gender
Men (%)	15 (55.56)	39 (56.52)	>0.9999
Women (%)	12 (44.44)	30 (43.48)

Antibody staining and flow cytometry assay

Flow cytometry assay was performed as follows: 100 µl of anti-coagulated fresh peripheral blood samples were mixed with the following mouse anti-human Abs: 5 µl BB515-CD25 (catalog no. 546467, BD Bioscience), 20 µl PE-CD28 (catalog no. 555729, BD Bioscience), 5 µl PerCP-CD4 (catalog no. 566321, BD Bioscience), 5 µl PE-CY7-CD56 (catalog no. 557747, BD Bioscience), 20 µl APC-CD152 (catalog no. 555855, BD Bioscience), 5 µl APC-CY7-CD8 (catalog no. 557760, BD Bioscience), 5 µl BV421-CD127 (catalog no. 562436, BD Bioscience), and 5 µl BV510-CD3 (catalog no. 564713, BD Bioscience). The mixtures were incubated at room temperature for 15 min. After staining, 2 ml Red Blood Cell Lysis Buffer (Cat No.349202, BD Bioscience) was added to each sample and incubated at room temperature for 15 min. Then, all samples were centrifuged at 300 × g for 5 min and the supernatant was discarded. Next, the samples were washed once and resuspended with PBS. Finally, prepared samples were subjected to detection using a flow cytometer (Canto II, BD) (Gating strategy shown in Fig. 1). Collected data were analyzed using Flowjo X (TreeStar, United States).

FIGURE 1.

The gating strategy for analysis of flow cytometry data. Lymphocytes were identified base on SSC versus FSC. Total T cells were defined as CD3⁺CD56⁻. NK cells were defined as CD3⁻CD56⁺. Regulatory CD4⁺ T cells were defined as CD3⁺CD56⁻CD4⁺CD25⁺CD127⁻ and regulatory CD8⁺ T cells were defined CD3⁺CD56⁻CD8⁺CD25⁺

Detection of IL-10

Plasma IL-10 concentrations were detected using a microsphere array kit (Raisecare Biotechnology, China). All plasma samples were freshly isolated and detected according to the manufacturer`s manual. Briefly, first, 25 µl of experimental buffer, 25 µl of centrifuged plasma, 25 µl of capture Ab, and 25 µl of detection Ab were added to detection tubes consecutively. Next, all tubes were incubated at room temperature in a shaking incubator for 2 h (400–500 rpm). After that, 25 µl SA-PE (streptavidin labeled with phycoerythrin) was added to each tube and incubated at the same condition as above for 30 min. Then, 500 µl diluted wash buffer was added to each tube. After a brief vortexing, the detection tubes were centrifuged at 300 × g for 5 min. Supernatant was discarded, and the clustered microspheres were suspended with 200 µl diluted washing buffer. Florescence intensity was measured by a flow cytometer (Canto II, BD, USA) and the cytokine concentrations were calculated according manufacturer`s instruction.

Statistical analysis

All statistical analyses were performed using GraphPad Prism 8 (GraphPad Software, Inc., La Jolla, CA, USA). One-factor analysis of variance (ANOVA) was used for comparison among multiple groups. Comparisons between 2 groups were done using t-test. Pearson correlation was used for correlation analysis of normally distributed data and Spearman`s rank correlation was used for analysis of non-normally distributed data. P < 0.05 was considered as statistically significant.

Results

Age-related alterations of lymphocyte frequencies in peripheral blood of COVID-19 patients

Peripheral blood samples were collected from 69 hospitalized COVID-19 patients within 10 days after disease onset (median, 3 days) and 27 discharged individuals at 2 weeks post discharge. The patients and discharged individuals were further divided into sub-groups based on their age: ≤45 years and >45 years. All patients with acute SARS-CoV-2 infection were diagnosed as mild to moderate upon admission and their clinical characteristics are summarized in Table 2. Comorbidities, especially hypertension and diabetes, were more frequently observed in patients older than 45 years. There was 1 patient co-infected with HIV in ≤45 years group. We confirmed that both the CD4⁺ (886 cells/µl) and CD8⁺ (828 cells/µl) T cell counts of this patient fell within the normal range.

TABLE 2.

Clinical characteristics of patients acutely infected with SARS-CoV-2

Age group Clinical variables	≤45 years (n = 54)	>45 years (n = 15)	P-value
Gender, n (%)
Women	23 (42.59%)	7 (46.67%)	0.7780
Men	31 (57.41%)	8 (53.33%)
Comorbidities, n (%)	5 (9.26%)	7 (46.67%)	<0.01
Hypertension	0 (0%)	6 (40.00%)	<0.0001
Diabetes	0 (0%)	3 (20.00%)	<0.01
Hyperlipidemia	0 (0%)	1 (6.67%)	0.2174
bronchial asthma	1 (1.85%)	0 (0%)	>0.9999
Mediterranean anemia	1 (1.85%)	0 (0%)	>0.9999
HIV	1 (1.85%)	0 (0%)	>0.9999
Sleep apnea syndrome	0 (0%)	1 (6.67%)	0.2174
Ankylosing spondylitis	1 (1.85%)	0 (0%)	>0.9999
PaO2 (kPa)	13.76 ± 3.57	12.12 ± 3.99	0.4785
PaCO2 (kPa)	5.53 ± 1.00	5.56 ± 1.95	>0.9999
Length of hospital stay, days	17.22 ± 6.07	20.64 ± 11.36	0.1255

Flow cytometry analyses showed that the frequencies of lymphocytes, total T cells, CD4⁺ T cells, and CD8⁺ T cells decreased significantly in acutely infected patients compared to healthy controls (Fig. 2A and 2B). Unexpectedly, our data showed that the frequencies of these cells in discharged individuals were even lower than those of acutely infected patients (Fig. 2A and 2B). Furthermore, when we divided the acutely infected and discharged individuals into subgroups according to age, we observed that in patients with acute infection over 45 years old, the frequency of CD4⁺ T cells was significantly higher, while the frequency of CD8⁺ T cells was lower (Fig. 2C). The CD4⁺/CD8⁺ T cell ratios were also significantly higher in these patients (Fig. 2D). Similar patterns were also found in discharged individuals (Fig. 2C and 2D), but no significant difference was found.

FIGURE 2.

Frequencies of lymphocytes altered in peripheral blood of COVID-19 patients. Frequencies of total lymphocytes (A) and T cells (B) were compared between acutely infected patients and discharged individuals. Data of healthy individuals generated by health screening were used as controls. (C) Frequencies of CD4⁺ and CD8⁺ T cells were compared between individuals below and beyond age of 45. (D) Comparisons of CD4⁺/CD8⁺ T cell ratios

NK cells and Tregs correlated with lymphocyte frequencies and CD4⁺/CD8⁺ T cell ratios, respectively, in acutely infected COVID-19 patients

To identify the immune correlates of the decreased frequencies of lymphocytes and T cells, we performed correlation analyses among frequencies of lymphocytes and multiple subset cell populations. Our results showed that the frequencies of lymphocytes in peripheral blood of acutely infected COVID-19 patients correlated negatively with the frequencies of NK (CD3⁻CD56⁺) cells (Fig. 3A). Frequencies of regulatory CD8⁺ T (CD3⁺CD56⁻CD8⁺CD25⁺) cells correlated with positively with frequencies of CD4⁺ T cells (P < 0.0001; Fig. 3B) and negatively with frequencies of CD8⁺ T cells (P < 0.0001; Fig. 3C). Consequently, the regulatory CD8⁺ T cell frequencies was associated positively CD4⁺/CD8⁺ T cell ratios (P < 0.0001; Fig. 3D). In contrast, regulatory CD4⁺ T (CD3⁺CD56⁻CD4⁺CD25⁺CD127⁻) cells correlated negatively with CD4⁺ T cell frequencies (P = 0.0333; Fig. 3E) and tended to correlate positively with CD8⁺ T cell frequencies (P = 0.0588; Fig. 3F), which presented a significant negative correlation between regulatory CD4⁺ T cell frequencies and CD4⁺/CD8⁺ T cell ratios (P = 0.0271; Fig. 3G). Moreover, our data showed that there is no significant correlation between frequencies of regulatory CD4⁺ and CD8⁺ T cells (Fig. 3H).

FIGURE 3.

Correlation analyses among the total and multiple subsets of lymphocytes in acutely infected COVID-19 patients. (A) Frequencies total lymphocytes versus frequencies of NK. (B) Frequencies of CD4⁺ T cells versus frequencies of regulatory CD8⁺ T cell. (C) Frequencies of CD8⁺ T cells versus frequencies of regulatory CD8⁺ T cell. (D) CD4⁺/CD8⁺ T cell ratios versus frequencies of regulatory CD8⁺ T cells. (E) Frequencies of CD4⁺ T cells versus frequencies of regulatory CD4⁺ T cell. (F) Frequencies of CD8⁺ T cells versus frequencies of regulatory CD4⁺ T cell. (G) CD4⁺/CD8⁺ T cell ratios versus frequencies of regulatory CD4⁺ T cell. (H) Frequencies of regulatory CD4⁺ T cell versus frequencies of regulatory CD8⁺ T cell

Similar analyses were performed in discharged individuals either. However, significant correlation was only observed between frequencies of regulatory CD4⁺ and CD8⁺ T cells (Supplementary Fig. 1).

Frequencies of regulatory CD8⁺ T cell increased significantly in acutely infected patients beyond age of 45 years

The frequencies of Tregs were compared between acutely infected COVID-19 patients before and after the age of 45 years. The results showed that the frequencies of regulatory CD4⁺ T cells were slighter lower in patients over 45 years old, but no statistical difference was found (Fig. 4A). The frequencies of regulatory CD8⁺ T cells increased significantly in patients older than 45 years, which held an average frequency nearly 2-fold of that in patients below the age of 45 years (Fig. 4B).

FIGURE 4.

Comparisons of regulatory T cell frequencies between patients before and after age of 45 years. (A) Comparison of regulatory CD4⁺ T cell frequencies between patients before and after age of 45 years. (B) Comparison of regulatory CD8⁺ T cell frequencies between patients before and after age of 45 years

IL-10 concentrations did not correlate with frequencies of CD4⁺, CD8⁺, and Tregs

IL-10 is one of the key factors that mediates the suppressive effect of regulatory T cell. To clarify the role IL-10 in the afore-described correlations between Tregs and CD4⁺/CD8⁺ T cell ratios, we measured the concentrations of IL-10 in plasma samples of COVID-19 patients. Our results showed that there was no statistically significant correlation between IL-10 concentrations and the frequencies of either CD4⁺, CD8⁺ T cells, or CD4⁺, CD8⁺ Tregs (Supplementary Fig. 2).

Discussion

Tregs are subtypes of T cells that can regulate the body’s immune system, maintain autoimmune tolerance, and prevent autoimmune diseases. It is suggested to be able to protect severe forms of coronaviral infections attributable to host inflammatory responses,¹⁶ which has also been suggested to be a leading cause of sever forms of COVID-19.¹⁷ A recent study indicated that the function of Treg might be impaired in COVID-19 patients,¹⁸ however, the influence of Tregs on the pathogenesis of SARS-CoV-2 remains unclear.

To understand the roles of Tregs in COVID-19 associated lymphopenia, in this study, we first analyzed the frequencies of lymphocytes and T cell subsets in peripheral blood of acutely COVID-19 patients and discharged individuals. Our results showed that the frequencies of lymphocyte and CD3⁺ T cell decreased significantly in acutely infected patients compared with healthy control, which were consistent with previous reports.^8–11 Unexpectedly, we observed the lowest frequencies of lymphocytes and CD3⁺ T cells in the discharged group, highlighting that the dysregulation of lymphocytes was long-lasting and profound. Previous studies suggested that the nadir of COVID-19 associated lymphopenia occurred around 2–3 weeks post disease onset.^19,20 While in this study, the frequencies of lymphocytes were measured within 10 days after disease onset (median, 3 days). Hence, we postulate that the frequencies of lymphocytes in acutely infected group did not reach the nadir. Meanwhile, the recovery of immune system might be slow after virus clearance as being suggested by a recent study, which showed that symptoms in some patients persisted even after discharge.²¹ These factors combined may explain the observed lowest frequencies of lymphocytes and T cells in the discharged group.

We also compared the frequencies of total lymphocytes, CD4⁺ T cells and CD8⁺ T cells among sub-groups of individuals below and beyond the age of 45 years, which showed that the significant differences of CD4⁺ and CD8⁺ T cell frequencies between acutely infected and discharged individuals occurred only in cases aged older than 45 years (Fig. 2C). Moreover, we found that the CD4⁺/CD8⁺ ratios were significantly higher in acutely infected patients over 45 years old compared with infected patients below the age of 45 years. Age associated increase of risk for severe COVID-19 is a major challenge for clinical treatment,²² our results implicated that the age associated alteration of CD4⁺ and CD8⁺ T cell frequencies might contribute to this unresolved enigma.

Next, to characterize the roles of regulatory T cells, we analyzed the correlations among total lymphocytes and multiple cell subsets in both acutely infected patients and discharged individuals. According to previous studies, regulatory CD4⁺ T cell was defined as CD4⁺CD25⁺CD127⁻.²³ and regulatory CD8⁺ T cell was defined as CD8⁺CD25⁺.^24,25 The results showed that the frequencies of regulatory T cells were not associated with the frequencies of lymphocytes or CD3⁺ T cells (data not shown). But very intriguingly, we found that the regulatory CD8⁺ and CD4⁺ T cells correlated oppositely with CD4⁺/CD8⁺ T cell ratios in acutely infected patients. Significantly higher frequencies of regulatory CD8⁺ T cells were observed in patients beyond age of 45 years, which consisted with the observation that the CD4⁺/CD8⁺ T cell ratios were also higher in these patients. In addition to the analyses of Tregs, we also observed that the frequency of CD3^-CD56⁺ NK cells correlated negatively with the lymphocyte percentages in peripheral blood of acutely infected patients. The mechanism underlying this phenomenon is unclear, which is worth of further investigations.

In this study, we did not evaluate the functions of Tregs, therefore, the mechanisms underlying the observed correlations and the roles of regulatory CD8⁺ and CD4⁺ T cells in the pathogenesis of COVID-19 are still not clear. Nonetheless, our data showed that the frequencies of CD8⁺CD25⁺ Tregs tended to correlated positively with the length of hospital stay (P = 0.0575, r = 0.2298, n = 69; Supplementary Fig. 3), implying that Tregs might play some roles in the pathogenesis of COVID-19. Furthermore, we think that the potential effect of Tregs is unlikely mediated by secreting IL-10, because no significant correlation was found between the plasma concentrations of IL-10 and the frequencies T cell subsets (Supplementary Fig. 2). Despite the lack of mechanistical proofs, our study clearly demonstrated that the frequencies of Tregs were associated the dysregulation of CD4⁺ and CD8⁺ T cells, indicating that different subsets of Tregs might have distinct functions in SARS-CoV-2 infection. Further investigations into the underlying mechanisms will deepen our understanding of the COVID-19 associated lymphopenia.

Supplementary Material

jlb10806-sup-0001-figureS1-S3

Supplementary figure 1 Correlation analyses among total lymphocytes and multiple subsets in discharged individuals

Supplementary figure 2 Correlation analyses between plasma IL-10 concentrations and T cell frequencies in acutely infected patients

Supplementary figure 3 Correlation analyses between the length of hospital stay and the frequencies of regulatory T cells in acutely infected patients

Authorship

Z.Z. and Y.W. designed the experiments. M.G., Y.L., M.G., Q.W., and W.Y. performed most experiments and analyses. J.F. and Y.S. helped with sample and patients` information collection. J.H. helped with the flow cytometry assay. M.G. and Z.Z. wrote the initial manuscript, and Y.W. revised it. All authors commented and approved the manuscript. M.G., Y.L., M.G., Q.W., and Y.W. contributed equally to this work.

Dislosure

The authors declare no conflict of interest.