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Flow cytometric analysis of lymphocyte subsets, monocytes, and HLA-DR expressions on these cells in patients with COVID-19

  • Nurgul Ozcan ORCID logo EMAIL logo , Murat Caglayan ORCID logo , Ali Yalcindag ORCID logo and Oguzhan Ozcan ORCID logo
Published/Copyright: February 14, 2024

Abstract

Objectives

We aimed to investigate the lymphocyte subsets and monocytes by flow cytometry and the correlations between their HLA-DR expressions and inflammatory markers in patients with COVID-19.

Methods

The study included 49 patients with COVID-19 and 42 healthy controls. Blood samples were taken into EDTA tubes. WBC counts were analyzed by the Sysmex/XN-1000i device, and lymphocyte subsets and monocytes were analyzed by flow cytometry. The percentage of HLA-DR expression on cells and median fluorescence intensity (MFI) values were recorded to detect activation. Lymphocyte counts were calculated using the dual-platform method. Correlations between antigen expression and ferritin, CRP, and D-dimer levels were analyzed.

Results

The patient group had lower WBC and lymphocyte counts but significantly higher monocyte counts and neutrophil/lymphocyte ratios compared to controls (p=0.009, p=0.045, respectively). The patient group had significantly lower T lymphocyte counts (p=0.008). B lymphocyte counts and percentages were lower (p<0.001, p=0.004) in the patient group. There was no significant difference between the two groups in terms of NK cells. T helper and T cytotoxic lymphocyte counts were significantly lower, but there was no change in CD4/CD8 ratios. The percentage of HLA-DR expression on T lymphocytes, HLA-DR MFI values of T cytotoxic cells, and HLA-DR MFI values of CD16+ monocytes were significantly increased in the patient group (p=0.001, p=0.004, p<0.001, respectively). CRP was positively correlated with HLA-DR expression on T lymphocytes (r=0.501, p<0.001).

Conclusions

HLA-DR MFI values may be an important marker for demonstrating the function of both T cytotoxic cells and CD16+ monocytes in COVID-19.

Introduction

The novel coronavirus (SARS-CoV-2) infection (COVID-19) was reported to have emerged in Wuhan, China, in December 2019. Since then, it has spread first in China and then all over the world, including our country [1]. The main symptoms have been reported as fever, dry cough, myalgia, and fatigue [2]. Some patients may additionally exhibit headaches, hemoptysis, and diarrhea. The disease may progress from asymptomatic and mild form to pneumonia and acute respiratory distress syndrome (ARDS), resulting in secondary infections and complications such as pneumothorax [3]. Five variants of SARS-CoV-2 designated by the World Health Organization, including Omicron, have been reported, and the disease still leads to deaths despite effective vaccination programs [4].

Monocytic phagocytic cells, lymphocytes, and their subsets play a critical role in maintaining the immune response to COVID-19. Lymphocyte subsets were previously analyzed in patients with SARS-CoV from the same viral family, suggesting that the lymphocyte count may be associated with the severity of the disease [5]. However, the immune response to the disease has not yet been fully elucidated. Previous publications have shown leukopenia and lymphopenia in COVID-19, especially a decrease in T, B, and NK lymphocytes [5, 6]. Studies also investigate alterations in T lymphocyte subsets and the CD4/CD8 ratio, but the results are inconsistent. Some publications have reported decreased CD4 and CD8 subset counts but no change in the CD4/CD8 ratio, while others showed no change in CD4 counts but decreased CD8 counts [5, 7]. However, studies investigating lymphocyte and monocyte activation in COVID-19 have been gaining importance in the literature. Today, multiparametric flow cytometry is considered the gold standard for the detection of lymphocyte subsets and activation of cells using percentages of HLA-DR expression on lymphocytes [8, 9]. The intensity of antigen expression (median fluorescent intensity, MFI) on lymphocytes and the internal complexity of cells (side scatter, SSC) can also be used to evaluate the activation of lymphocytes. However, there are a limited number of studies investigating MFI values of HLA-DR expression but no study about neutrophil SSC/lymphocyte SSC ratio in patients with COVID-19 [10, 11].

In this study, we aimed to investigate the lymphocyte subsets, monocytes, MFI of HLA-DR expression, and SSC of lymphocytes by flow cytometry and to detect any correlations between antigen expressions and inflammatory markers in patients with COVID-19.

Materials and methods

Study population

The study included a total of 91 individuals, including patients who were admitted to Diskapi Yildirim Beyazit Training and Research Hospital with suspicion of COVID-19 and had a positive SARS-CoV-2 PCR test result (n=49) and age- and sex-matched healthy volunteers were selected from those with no symptoms and no history of suspected contact with COVID-19 (not confirmed by PCR test) (n=42). Volunteers with a history of acute infection in the last two months were excluded from the study. The approval for the study was obtained from the Human Ethics Committee of Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital (2020-05/625). Moreover, the required permission was received from the Ministry of Health.

Data collection

The following information for each patient was extracted from the electronic medical records: age, sex, medical history, symptoms, the severity of the disease at the admission, laboratory findings, and chest computed tomography (CT) reports.

Sample collection

All nasal swab samples for PCR testing were collected according to the laboratory testing for the 2019 novel coronavirus (2019-nCoV) in suspected human cases guideline [12]. Venous blood samples were collected into a biochemistry tube. Serum samples were separated by centrifuging at 1,500×g for 10 min. In serum samples, CRP was studied by the turbidimetric method (Roche Diagnostic, Cobas C6000, c501, Japan), the activity levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), and total bilirubin values were detected by the spectrophotometric method (Roche Diagnostic, Cobas 8000, Japan), and ferritin and pro-brain natriuretic peptide (Pro-BNP) levels were measured by the electrochemiluminescence method (Roche Diagnostic, Cobas 8000, C4000 e411, Japan). For coagulation tests, samples were collected into tubes containing citrate. PT, aPTT, and D-dimer levels were studied by the photometric method (Roche Diagnostic, Cobas T711, Japan). Peripheral blood samples (2 mL) anticoagulated with EDTA were collected from patients and healthy controls. Total white blood cells (WBCs), platelet (Plt), and lymphocyte counts were measured using a hematology autoanalyzer (Sysmex XN-1000i, Japan). All samples were tested within 2 h of collection.

Flow cytometry analysis

Flow cytometric analysis of lymphocyte subsets was carried out using the same samples used for the automated blood count autoanalyzer. The lysis no-wash method was performed in accordance with the product manual. In brief, the study tube was labeled with the patient’s name and antibodies inside. After pipetting 10 µL of antibodies (CD3 Allophycocyanin-Alexa Fluor 750 (APC-A750), CD4 Phycoerythrin-Texas Red-X (ECD), CD8 Phycoerythrin-Cyanin 7 (PC7), CD19 Phycoerythrin-Cyanin 5 (PC5), CD56 Allophycocyanin-Alexa Fluor 700, CD16 Phycoerythrin (PE), HLA-DR Pacific Blue (PB), CD45 Krome Orange (KO) Beckman Coulter) according to the manufacturer’s instructions, 100 µL of patient blood sample was added to the labeled tubes. They were incubated in the dark for 15 min at room temperature. At the end of the incubation period, the tubes were vortexed. Then, 2 mL of lysing solution (VersaLyse Lysing Solution, Beckman Coulter) was added to the samples, vortexed, and incubated in the dark for 10 min at room temperature. After vortexing again, data collection was performed on a Beckman Coulter Navios flow cytometer (Brea, CA, USA). At least 10,000 events were collected for each sample, and the results were analyzed using Kaluza software (Treestar, Ashland, OR, USA). The percentage of antigen-expressing cells and MFI values for CD45 and HLA-DR on lymphocytes were recorded. Monocytes were analyzed by gating cells using forward scatter (FSC) and SSC, which were then applied to a CD45 × SSC dot plot. The CD45+ events were gated and applied to a CD4 × SSC dot plot. The CD4 dim+ cell population with low SSC to define the monocytes was gated and applied to a CD16 × CD4 dot plot for the characterization of distinct monocyte subsets and MFI of CD16 (Figure 1).

Figure 1: 
Lymphocyte and monocyte subgroups gating strategy. SS INT/time (A) fluidic system control; SS INT/SS PEAK (B) singlet cells; FS INT/SS INT (C) viable cells; SSC/CD45 (D) debris exclusion; gated lymphocytes (red), monocytes (green) and granulocytes (blue) in SSC/CD45 (E); CD3− CD19+ B lymphocytes (pink) and CD3+ CD19− T lymphocytes (blue) (F); CD4+ and CD8+ T cells at lymphocyte gate (G); CD3− CD19− CD16/56+ NK cells (H); CD3+ 56+ NKT cells (I); CD3− CD4+ monocytes (J, K); CD4+CD16+ monocytes and CD4+CD16− monocytes (L).
Figure 1:

Lymphocyte and monocyte subgroups gating strategy. SS INT/time (A) fluidic system control; SS INT/SS PEAK (B) singlet cells; FS INT/SS INT (C) viable cells; SSC/CD45 (D) debris exclusion; gated lymphocytes (red), monocytes (green) and granulocytes (blue) in SSC/CD45 (E); CD3 CD19+ B lymphocytes (pink) and CD3+ CD19 T lymphocytes (blue) (F); CD4+ and CD8+ T cells at lymphocyte gate (G); CD3 CD19 CD16/56+ NK cells (H); CD3+ 56+ NKT cells (I); CD3 CD4+ monocytes (J, K); CD4+CD16+ monocytes and CD4+CD16 monocytes (L).

Absolute counts of lymphocyte subsets were calculated using the “double platform” method [13]. Accordingly, absolute lymphocyte subset counts were calculated by obtaining the percentage of cells from flow cytometry and the total leukocyte count from the whole blood count analyzer. Absolute values of lymphocyte subsets were calculated by the formula: Absolute number/µL=leucocyte count × % lymphocyte × % antibody positivity/10,000.

Daily flow checks (Beckman Coulter) were used to evaluate the device’s performance. The intra-day and inter-day coefficients of variation were <3 %. Utilizing the UK NEQAS external quality evaluation method, the system’s accuracy was evaluated monthly.

Statistical analysis

The statistical analysis of the study data was carried out using SPSS Version 20.0 software. Numbers, percentages, mean ± standard deviation, median, minimum (min), maximum (max), and interquartile range (IQR 25–75) were used for descriptive statistics. The Mann-Whitney U test was used for the comparison of the demographic characteristics between the two groups. Pearson and Spearman’s rank correlation analysis were used to determine the correlation between parameters according to their distribution. A p-value of <0.05 was considered statistically significant.

Results

Demographic characteristics and laboratory results

A total of 91 individuals, including 49 COVID-19 patients and 42 healthy controls, were included in this study. The median ages of COVID-19 patients and healthy controls were 41 (IQR, 36–53) and 50 (IQR, 37–64) years, respectively. Twenty-nine (59 %) patients were male, and 20 (41 %) were female. There was no significant difference between the patients and healthy controls in terms of age and sex distribution (p>0.05). Twenty-three (47 %) of the patients were asymptomatic (PCR+, no symptom) or had a mild form of the disease (symptomatic, have a sore throat, headache, and congestion, but no evidence of pneumonia or hypoxia), while 26 (53 %) of them had a moderate form of the disease (clinical signs of non-severe pneumonia, febrile, cough, dyspnea, saturation >90 % in air). Severe and critically ill patients were excluded.

A complete blood count and biochemical parameters are presented in Tables 1 and 2, respectively. In blood tests, absolute leukocyte and lymphocyte counts were significantly lower, while monocyte counts and the neutrophil-to-lymphocyte ratio (NLR) were higher compared with healthy controls.

Table 1:

Complete blood count parameters of COVID-19 patients and healthy controls.

Parameters COVID 19 patients Healthy controls p-Value
Median Percentile Median Percentile
25 75 25 75
WBC, 103/µL 5.3 4.9 8.2 7.0 5.5 8.5 0.036
NEUa, 103/µL 3.4 2.4 5.1 4.0 3.2 5.9 0.124
LYMa, 103/µL 1.5 1.1 2.1 2.2 1.7 2.6 <0.001
NLR 1.15 0.50 2.20 0,60 0.20 1.20 0.045
MONa, 103/µL 0.5 0.4 0.6 0.4 0.4 0.5 0.009
EOSa, 103/µL 0.0 0.0 0.1 0.1 0.1 0.2 <0.001
BASa, 103/µL 0.0 0.0 0.1 0.0 0.0 0.0 0.323
NEU, % 62.6 53.8 70.7 61.9 54.9 65.7 0.396
LYM, % 25.4 20.0 33.8 29.4 26.2 35.3 0.044
MON, % 8.4 6.4 11.4 6.3 5.0 7.0 <0.001
EOS, % 0.7 0.2 1.8 1.8 1.3 2.6 <0.001
BAS, % 0.5 0.3 1.1 0.4 0.2 0.5 0.075
RBC, 106/µL 4.7 4.5 5.1 4.7 4.3 5.2 0.956
HGB, g/dL 14.0 12.4 14.9 14.1 13.2 15.5 0.329
HCT, % 43.1 38.8 46.1 42.9 40.0 46.9 0.599
RDW-CV, % 13.8 13.1 14.5 13.2 12.7 14.2 0.039
RDW-SD, fL 44.6 42.7 46.7 43.3 41.9 45.7 0.159
PLT, 103/µL 235.0 188.0 265.0 254.5 229.0 288.0 0.028
  1. aAbsolute number of related parameters; WBC, white blood cell; NEU, neutrophil; LYM, lymphocyte; NLR, neutrophil-to-lymphocyte ratio; MON, monocytes; EOS, eosinophil; BAS, basophil; RBC, red blood cell; HGB, hemoglobin; HCT, hematocrit; RDW, red cell distribution width; PLT, platelet.

Table 2:

The routine biochemical parameters of COVID-19 patients at the time of admission.

Biochemical parameters Median 25th percentile 75th percentile Reference ranges
CRP, mg/L 9.84 5.42 65.7 <5
ALT, U/L 21 18 31 0–33
AST, U/L 22 16 30 0–32
Total bilirubin, mg/dL 0.38 0.31 0.64 0–1.2
LDH, U/L 197 170 224 135–225
Ferritin, µg/L 184 61 445 22.6–383
ProBNP, pg/mL 33.7 7.67 1,597 <192
PT, s 9.53 8.95 9.94 8.4–10.6
aPTT, s 30.8 27.8 33.4 23.9–33.2
D-dimer, µg/mL 0.38 0.20 0.78 0–0.5
  1. CRP, C-reactive protein; ALT, alanine aminotransferases; AST, aspartate aminotransferases; LDH, lactate dehydrogenase; ProBNP, pro-brain natriuretic peptide; PT, prothrombin time; aPTT, activated partial thromboplastin time.

Peripheral lymphocyte subset alteration in COVID-19

The flow cytometric analysis results of lymphocyte subsets are shown in Table 3. Both percentages (%) and absolute counts (#) of total lymphocytes, CD3+ T, and CD19+ B lymphocytes were significantly lower in the patient group compared to the controls. The analysis of T lymphocyte subsets showed significantly lower CD4+ T helper and CD8+ T cytotoxic lymphocyte counts in the patient group (p=0.007, p<0.05) but no change in their percentages or CD4/CD8 ratios. There was no significant difference between the two groups in terms of the count and percentage of NK cells, but a significantly higher percentage of CD3+CD56+ NK-T cells was found in the patient group.

Table 3:

Comparison of immunophenotypic features of lymphocyte subsets by flow cytometry in patients with COVID-19 and healthy controls.

Parameters COVID 19 patients Healthy controls p-Value
Median Percentile Median Percentile
25 75 25 75
LYM, % 25.5 19.5 33.4 29.4 26.4 37.1 0.033
LYMa 1,468.1 1,122.4 1,868.7 2,261.4 1,670.2 2,622.6 <0.001
CD3+%, T cell 75.0 69.2 80.0 70.6 60.8 76.4 0.019
CD3+ a 1,088.4 830.7 1,384.5 1,377.1 1,042.7 1,848.9 0.008
CD3+CD4+% (T helper) 44.7 37.0 48.8 39.7 32.8 47.3 NS
CD3+CD4+ a 602.7 374.7 878.9 818.6 607.0 1,148.8 0.007
CD3+CD8+% (T cytotoxic) 26.6 20.5 35.4 25.4 19.8 31.1 NS
CD3+CD8+ a 395.4 217.3 644.0 481.1 381.6 783.4 0.05
CD4/CD8 ratio 1.7 1.1 2.3 1.6 1.1 2.6 NS
CD3CD16+/CD56+%, NK cell 14.0 9.0 22.6 13.5 8.4 19.4 NS
CD3CD16+/CD56+ a 199.2 110.5 337.1 234.4 179.6 389.3 NS
CD19+%, B cell 9.4 6.7 11.9 12.3 9.7 15.3 0.004
CD19+ a 139.2 88.8 204.5 275.4 181.4 385.6 <0.001
CD3+CD56+ % (NK-T cell) 1.2 0.5 2.2 0.6 0.2 1.2 0.045
CD3+CD56+ a 0.01 0.00 0.03 0.01 0.00 0.02 NS
GRAN CD45 MFI 22,764 20,493 27,552 26,334 20,600 30,359 NS
LYM CD45 MFI 25,446 23,331 27,853 34,848 33,360 36,324 <0.001
GRAN CD45 MFI/LYM CD45 MFI 0.9 0.8 1.1 0.7 0.6 0.9 <0.001
GRAN SSC value 617,472 532,480 712,704 635,904 580,608 668,672 NS
LYM SSC value 72,704 64,512 76,800 62,464 60,416 64,512 <0.001
SSC GRAN/SSC LYM 8.9 7.9 9.9 10.0 8.9 10.9 0.001
  1. aAbsolute number of related parameters calculated by double platform; LYM, lymphocyte; GRAN, granulocyte; MFI, median fluorescence intensity; SSC, side scatter; NS, non significant.

We also found significantly lower CD45 MFI values and higher SCC values for lymphocytes in the patient group compared with controls (p<0.001, p=0.001, respectively). We also detected significantly increased CD45 MFI values of granulocyte/CD45 MFI values of lymphocytes (p<0.001) and decreased SSC of granulocytes/SSC of lymphocytes (p=0.001) (Table 3).

The percentages of HLA-DR expression on T lymphocytes, T helper, and T cytotoxic subsets were found to be significantly higher in the patient group compared with healthy controls (p=0.001, p<0.001, p<0.001, respectively) (Figure 2A). The MFI values of HLA-DR expression on T lymphocytes and the T cytotoxic subset were significantly increased (Figure 2B).

Figure 2: 
Comparison of HLA-DR expression levels in CD3+/CD4+ T helper and CD3+/CD8+ T cytotoxic subsets of the patient and control groups as a percentage (A) and MFI value (B).
Figure 2:

Comparison of HLA-DR expression levels in CD3+/CD4+ T helper and CD3+/CD8+ T cytotoxic subsets of the patient and control groups as a percentage (A) and MFI value (B).

Correlations

The inflammatory indicator C-reactive protein (CRP) was abnormal in 75 % of the patients at admission and was positively correlated with WBC and neutrophil counts and negatively correlated with total lymphocyte, T cell, and T helper counts and the percentage of NK-T cells (Table 4). Similarly, CRP was also positively correlated with the percentage of HLA-DR expression on CD3+ T lymphocytes and the T cytotoxic subset. B cells showed no significant correlation with CRP. There was a significant negative correlation between serum ferritin levels, with total lymphocyte and T helper counts, and percentages of HLA-DR expression on CD3+ T lymphocytes and the T cytotoxic subset. NLR and the percentage of NK-T cells were significantly negatively correlated with D-dimer (Table 4).

Table 4:

Correlations between complete blood count parameters and lymphocyte subsets with biochemical parameters.

Parameters CRP Ferritin D-di̇mer
WBC, 103/µL 0.601a 0.201 0.288
NEUc, 103/µL 0.671a 0.259 0.259
LYMc, 103/µL −0.546a −0.456b 0.147
NLRa −0.282 −0.269 −0.449b
CD3+ c, T cell −0.535a −0.388 0.152
CD3+/CD4+ c (T helper) −0.570a −0.629a 0.181
CD3+/CD8+ c (T cytotoxic) −0.196 0.07 0.155
CD4/CD8 ratio −0.262 −0.396 −0.022
CD3 CD16+/CD56+ c, NK cell −0.337 −0.395 −0.085
CD3+/CD56+,% (NK-T cell)a −0.416b −0.325 −0.383b
CD19+ c, B cell −0.124 −0.305 0.216
CD3+ HLA DR+,% 0.501a 0.426b 0.023
CD3+/CD4+ HLA DR+,% −0.096 −0.042 −0.102
CD3+/CD8+ HLA DR+,% 0.436b 0.437b 0.051
  1. aCorrelation is significant at the 0.01 level; bCorrelation is significant at the 0.05 level. cAbsolute number of related parameters; WBC, white blood cell; NEU, neutrophil; LYM, lymphocyte; NLR, neutrophil-to-lymphocyte ratio;a, Pearson correlation coefficient was used for parameters except for % NK-T cell and NLR.

CD16 and HLA-DR expression on monocytes

Although there was no difference between the patient and healthy control groups in terms of the percentage of HLA-DR expression on monocytes (not shown), the HLA-DR MFI values were significantly higher in the patient group (p<0.001). The patient group had significantly higher percentages and HLA-DR MFI values of CD4+CD16+ monocytes compared to the healthy control group (p<0.001) (Table 5).

Table 5:

The comparison of MFI values of HLA-DR and CD16 expressions on monocytes between groups.

COVID 19 patients Healthy controls p-Value
Median Percentile Median Percentile
25 75 25 75
HLA-DR MFI on CD4+ MON 17,830 14,384 22,328 7,362 6,299 9,791 <0.001
CD4+CD16+ MON, % 23.3 16.0 34.0 11.6 9.7 14.0 <0.001
CD16 MFI on CD4+ MON 12,675 9,159 16,154 22,873 17,999 28,726 <0.001
HLA-DR MFI on CD4+CD16+ MON 33,003 25,548 42,604 16,190 13,809 19,375 <0.001
  1. MFI, mean fluorescence intensity; MON, monocyte.

Discussion

This study examined the complete blood count parameters of patients with mild and moderate COVID-19. T lymphocytes and their subsets, B lymphocytes, and NK cells were analyzed by flow cytometry in patients and compared with the values of healthy controls. Moreover, SSC characteristics and the HLA-DR expressions of lymphocytes and monocytes were measured as percentages and MFI values. In addition, the correlations between antigen expressions and serum CRP, ferritin, and D-dimer values were assessed.

COVID-19 is an acute inflammatory infectious disease. Studies conducted so far have shown alterations in leukocyte and lymphocyte distribution in COVID-19 patients, similar to viral infections such as HIV and SARS. With regard to this, the NLR has been demonstrated to play an important role in the diagnosis and prognosis of viral infections as an inflammatory marker [14, 15]. Similarly, it has been reported that increased NLR is a critical predictor for the assessment of disease severity in COVID-19 patients [16], [17], [18]. While the COVID-19 patients included in the present study had lower absolute leukocyte and lymphocyte counts compared to the healthy controls, there was no significant change in neutrophil counts (Table 1). On the other hand, NLR values were higher in the patient group, which supports the results of other studies. The increased NLR in this study is due to the significant decrease in lymphocyte count. However, no significant correlation was found between NLR, CRP, and ferritin levels. Many publications on COVID-19 have suggested that the progressive reduction of lymphocyte counts in peripheral blood may be a clinical early warning indicator for severe and critical cases in adults [5, 19]. The suppressive effect of cytokines on bone marrow lymphopoiesis has been implicated as a cause of lymphopenia in COVID-19 [20]. In contrast to NLR, the results of this study showed that there was a significant negative correlation between absolute lymphocyte counts and inflammatory markers like CRP and ferritin levels in the patient group (Table 4). Accordingly, it can be suggested that decreasing lymphocyte count may be more useful than NLR because of its negative correlations with inflammatory markers.

In addition to a drop in the number of lymphocytes, changes in the subsets of lymphocytes have been linked to the prognosis of viral diseases and the effectiveness of treatments [1, 5]. A retrospective study showed low CD4+T and CD8+T lymphocyte counts in SARS patients, associated with a poor prognosis [21]. However, the characteristics of lymphocyte subsets in COVID-19 patients are largely unclear. A study showed decreased T, B, and NK counts in COVID-19 patients. The same study reported a simultaneous decrease in CD4+ and CD8+ T lymphocytes but no significant change in the CD4/CD8 ratio [5]. Another study showed a decrease in total T, CD8+T, and NK cell counts in COVID-19 patients compared to healthy controls but no significant difference in CD4+ T and B cell counts between COVID-19 patients and healthy controls [7]. In another study, researchers found decreased T and B cells, monocytes, NK, and NKT cells [22]. The present study analyzed lymphocyte subsets by flow cytometry. The CD3+ T lymphocyte and CD19+ B lymphocyte counts were significantly lower in the patient group compared to the controls. However, there was no significant difference between the groups in terms of the count and percentage of NK cells. Analysis of T lymphocyte subsets showed that the number of CD4+ T helper lymphocytes and CD8+ T cytotoxic lymphocytes was significantly lower in the patient group. However, the decrease in the number of cytotoxic T lymphocytes (17.8 %) was less than the decrease in the number of T helper lymphocytes (26.3 %). There was no significant difference in the CD4/CD8 ratio. In other words, despite no change in ratios of both T helper and cytotoxic cells, it can be stated that both parameters decrease numerically, but cytotoxic T lymphocytes are affected relatively less when compared as a percentage. It is well known that CD4+ and CD8+ T lymphocytes are the basic components of the immune system. Particularly in acute viral infections involving the lung, CD8+ T lymphocytes play a vital role in virus clearance [23]. Activation of CD8+ T cells results in the expression of cytotoxic molecules, which are responsible for killing the target cell [24]. Therefore, in addition to the numerical changes in lymphocytes, activation states should be considered in viral diseases. The HLA-DR antigen is a well-known activation marker found on T lymphocytes [25]. It has also been reported to be associated with acute viral diseases [26]. Kratzer et al. did a study on people with COVID-19 and found that HLA-DR was increasingly expressed on CD3+/CD8+ T cells 10 weeks after the infection [27]. Another study found that COVID-19 patients with mild symptoms had a higher rate of polyfunctional CD8+ T lymphocyte response than those with severe symptoms. This suggests that CD8+ T cells may help reduce the severity of the disease [28]. We measured the expression of HLA-DR on CD8+ T and CD4+ T lymphocytes to understand their activity status. Both T helper lymphocytes and T cytotoxic lymphocytes in the patient group had significantly increased the percentage of HLA-DR expression (Figure 2). In other words, despite the numerical decrease in lymphocytes, there was a significant increase in the expression of HLA-DR, which is used as an activation marker, on both lymphocyte types. We also found a weak but positive correlation between serum CRP levels and HLA-DR expression on T lymphocytes. These results suggest that both T helper and cytotoxic T lymphocytes play a role in the immune response to COVID-19.

The most commonly used statistical criterion for demonstrating antigen expression in the analysis of lymphocyte subsets is the percentage of positive cells. MFI measurements, however, have the potential to demonstrate the average number of antigen molecules per cell approximately. In this respect, it has been said that showing the staining intensities on a lymphocyte population as MFI values may be more informative than showing them as percentages unless there is no fluctuation in measurement [29]. In the present study, HLA-DR MFI values were calculated in addition to the percentage of HLA-DR expressed on the cell surface. In the patient group, HLA-DR MFI values of CD3+/CD4+ T lymphocytes were not changed, but their values in CD3+/CD8+ T cytotoxic cells were significantly higher (Figure 2B). The increase in HLA-DR MFI on the cytotoxic T cell surface indicates that the HLA-DR expression not only increases in percentage but also the amount of protein per cell. This supports the idea that cytotoxic T cells are activated more strongly than T helper cells.

Another molecule associated with lymphocyte activation is CD45 (lymphocyte common antigen) [30]. CD45 is a receptor-linked protein tyrosine phosphatase normally expressed on all leukocytes. It is believed to be essential for maturation, signal transduction, and activation of lymphocytes [30]. CD45 is known to play a role in autoimmune diseases and viral infections, especially HIV [30], [31], [32]. Furthermore, CD45 deficiency results in B and T lymphocyte dysfunction in severe combined immunodeficiency [33]. A previous study showed decreased CD45 expression in patients with COVID-19, suggesting an association with disease severity [33]. The present study supports earlier evidence by showing no difference in CD45 expression of granulocytes but significantly lower CD45 expression of lymphocytes in the patient group compared to the healthy subjects (Table 3). Accordingly, the decrease in CD45 expression in COVID-19 may be another indicator of the deterioration in lymphocyte activity and decrease in maturation.

Side scatter (SSC), which provides information about the internal complexity of cells, such as granularity, is thought to be another indicator of lymphocyte activation [34]. In the present study, the analysis of the SSC characteristics of lymphocytes revealed significantly higher SSC values and a lower ratio of neutrophil SSC to lymphocyte SSC in the patient group compared to the controls. These changes in the light scatter characteristics of lymphocytes indicate increased granularity in their cytoplasm, supporting the increase in cellular activation.

In the event of infection, monocytes are responsible for pathogen recognition, the initiation and resolution of inflammation, and the repair of tissue damage [35]. Three main monocyte types have been identified in peripheral blood based on their CD14 and CD16 (FcR III) expression [36, 37]. These monocyte types are known to exhibit different phenotypes and functions. CD16+ monocytes have been shown to express more proinflammatory cytokines with a higher potential for antigen presentation but a reduced ability to perform Fc receptor-mediated phagocytosis [36, 37]. Previous studies have reported an increase in the amount of CD14+/CD16+ (intermediate and non-classical) monocytes in sepsis, tuberculosis, and HIV infection [38, 39]. To date, there have been few reports of peripheral blood monocyte abnormalities in patients with COVID-19 [40], [41], [42], [43]. The results of the present study, similar to previous studies, showed an increased percentage of CD16+ monocytes in COVID-19 patients (Table 5). However, so far, there has been only one study investigating CD16 MFI values in COVID-19 [44]. Measuring CD16 MFI values for the first time in COVID-19, the present study demonstrated significantly lower values compared with healthy controls. In other words, while the percentage of CD16+ monocytes was increased in the patient group, CD16 MFI values were found to be decreased. This may be related to decreased ability to perform Fc receptor-mediated phagocytosis. In other words, it can be suggested that CD16+ monocytes, which have important monocytic functions such as antigen presentation and proinflammatory cytokine production, increase in COVID-19, but the phagocytic capacity of these monocytes decreases.

HLA-DR expression on monocytes plays a major role in the presentation of antigens to immune cells [45]. This study investigated HLA-DR expression on monocytes. Although there was no significant difference in the percentage of monocytes expressing HLA-DR between the patient and healthy control groups, the patient group had significantly higher HLA-DR MFI values. A previous study suggested that CD16+ monocytes express higher levels of HLA-DR in newborns with sepsis and may have higher antigen-presenting cell (APC) activity in these cells [38]. In the present study, COVID-19 patients had significantly increased HLA-DR. MFI values of CD16+ monocytes compared to the control group. It can be concluded that the phagocytic properties of CD16+ monocytes decreased, whereas their APC properties increased. As a matter of fact, a study reported increased HLA-DR bright positive monocytes in patients with mild COVID-19. However, the same study showed decreased HLA-DR expression in severe cases [35, 46]. Eventually, the severity of HLA-DR expression on monocytes seems to be related to the clinical course of the disease.

In conclusion, both lymphocytes count and CD45 expression on lymphocytes were decreased in COVID-19. However, the increase in granularity of lymphocytes, along with the increased HLA-DR expression on T lymphocytes, suggests that lymphocyte activation has an important role in the immune response to the disease. High HLA-DR MFI values of cytotoxic T lymphocytes indicate that these cells remain at the forefront. The detection of both increased counts and increased APC-related HLA-DR MFI of CD16+ monocytes, unlike lymphocytes, supports the hypothesis that these cells play a role in the immune response together with lymphocytes. On the other hand, it can be suggested that the decrease in CD16 MFI values associated with Fc receptor-mediated phagocytosis limits the phagocytic activity of monocytes.


Corresponding author: Nurgul Ozcan, Department of Medical Biochemistry, Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital, Ankara, Türkiye, Fax: + 90 312 334 0352, Mobile: +90 505 314 36 20, E-mail:

Funding source: Beckman Coulter Biyomedikal Ürünler San. ve Tic. Ltd. Şti.

Award Identifier / Grant number: Beckman provides the institution with the products

  1. Research ethics: The approval for the study was obtained from the Human Ethics Committee of Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital (2020-05/625).

  2. Informed consent: Informed consent was obtained from all individuals included in this study.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Competing interests: Authors state no conflict of interest.

  5. Research funding: The flow cytometry reagents used in this study were supported by Beckman Coulter Biyomedikal Ürünler San. ve Tic. Ltd. Şti. (no payment). The funding organization played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

  6. Data availability: Not applicable.

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Received: 2022-04-21
Accepted: 2023-10-17
Published Online: 2024-02-14

© 2023 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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