SARS‐CoV‐2 infected patients show quantitative and qualitative alterations of circulating myeloid cells and plasmacytoid DC. Some of these alterations are typical of all COVID‐19 patients, while some others vary at different stages of the disease and correlate to biochemical parameters of inflammation demonstrating that the myeloid compartment, is severely affected by SARS‐CoV‐2 infection.
Summary
SARS‐CoV‐2 is responsible for a new infectious disease (COVID‐19) in which individuals can either remain asymptomatic or progress from mild to severe clinical conditions including acute respiratory distress syndrome and multiple organ failure. The immune mechanisms that potentially orchestrate the pathology in SARS‐CoV‐2 infection are complex and only partially understood. There is still paucity of data on the features of myeloid cells involved in this viral infection. For this reason, we investigated the different activation status profiles and the subset distribution of myeloid cells and their correlation with disease progression in 40 COVID‐19 patients at different stages of disease. COVID‐19 patients showed a decrease in the absolute number of plasmacytoid and myeloid dendritic cells, different subset distribution of monocytes and different activation patterns of both monocytes and neutrophils, coupled to a significant reduction of HLA‐DR monocyte levels. We found that some of these alterations are typical of all COVID‐19 patients, while some others vary at different stages of the disease and correlate with biochemical parameters of inflammation. Collectively, these data suggest that not only the lymphoid, but also the myeloid compartment, is severely affected by SARS‐CoV‐2 infection.
Introduction
Coronavirus disease‐19 (COVID‐19) is the illness caused by a new coronavirus, identified in December 2019 in China and named SARS‐CoV‐2, able to induce acute respiratory distress syndrome and systemic inflammatory response. 1 , 2 Upon viral infection, relevant numbers of immune cells are mobilized and play different roles in defending the host from the pathogen and in the subsequent inflammatory, humoral and cellular responses. In the context of COVID‐19, an immune dysregulation characterized by lymphopenia and loss of antiviral effects by NK and CD8+ T cells has already been demonstrated. 3 In contrast, there are only few studies focusing on the role of the myeloid cell compartment in COVID‐19. 4
Neutrophils are the most abundant types of leucocyte in humans. They are main players in the innate immune response and major responsible in the effector phase of the host defence against pathogens. In addition, neutrophils play an important role in innate immunity during viral infections: it has recently been hypothesized that neutrophils participate in SARS‐CoV‐2 infection, leading to increase inflammatory status and haemorrhagic lesions in the lungs of infected patients. 5
Monocytes are large mononuclear leucocytes involved in the inflammation and clearance of pathogens. These cells are able to further differentiate into myeloid subsets such as dendritic cells (DCs) and macrophages. Monocytes are a heterogeneous cell population composed by three distinct subsets, which are identified on the basis of their expression of CD14 and CD16 and are characterized by different patrolling, pro‐inflammatory and antigen‐presenting capabilities. The classical monocyte’s subset is characterized by high levels of membrane CD14 and no expression of CD16 (CD14++/CD16−), the intermediate subset is CD14++/CD16+, while the non‐classical one is CD14+/CD16++. 6 CD14++/CD16− classical monocytes are involved in phagocytosis and inflammation. The CD14++/CD16+ intermediate monocyte subset also participates in the inflammatory response, while CD14+/CD16++ non‐classical monocytes have a patrolling function and contribute to the antiviral response. All these monocyte subsets are present with a very well‐defined proportion in the peripheral blood of normal donors; however, significant changes can occur in various pathological conditions. 7 In particular, an expansion of the CD14++/CD16+ fraction has already been described in various inflammatory diseases. 8
Dendritic cells are specialized antigen‐presenting cells that initiate and direct immune responses by presenting pathogen‐derived antigens to naive T cells and by activating them via cytokine production. Two subsets of DCs circulate in the blood, plasmacytoid dendritic cells (pDCs) and myeloid DC (MyDC). Plasmacytoid DCs are specialized to respond to viral infections by their rapid production of high quantities of interferons (I and III) and secretion of other cytokines. Myeloid DCs (referred as ‘classical’ or ‘conventional’ (c) DC and divided into two subsets ‘cDC1’ and ‘cDC2’ based on CD141 and CD1c expression, respectively) act as sentinel cells secreting cytokines: after activation, they effectively stimulate T cells; therefore, they are critical for shaping adaptive immunity. The role of DCs in respiratory viral infection has already been studied. 9 , 10
Antigen expression profiles in the myeloid compartment are correlated with the immune response and disease severity in bacterial and viral infections. HLA‐DR molecules are membrane‐bound molecules that play a role in antigen presentation and T‐cell activation. Several investigators have shown that low levels of HLA‐DR expression in patients with infections and sepsis are linked to the severity of the infection. CD64 (FcgRI) is the high‐affinity receptor for monomeric IgG in immune complexes that can initiate immunological and inflammatory reactions on immune competent cells, including monocytes and joint‐stationed macrophages. 11 , 12 CD66b (CEACAM8, CGM6, NCA‐95) is a GPI‐anchored protein belonging to the carcinoembryonic antigen supergene family. CD66b is an activation marker for human granulocytes involved in adhesion to endothelial cells, degranulation and increased reactive oxygen species production. 13 CD11b is a cell surface receptor important for neutrophil and monocyte migration to sites of infection/ inflammation. Upregulation of CD11b has been demonstrated in leucocytes from peripheral blood of patients suffering from pulmonary diseases. 14 CD64, CD66b and CD11b have been successfully used in other studies to measure neutrophil activation state. 15
To date, little is known about the interplay between SARS‐CoV‐2 and the myeloid compartment, and in particular the role of these cells in the inflammatory responses of COVID‐19 patients. 16 Herein, we report the evaluation and characterization of DC, monocyte and neutrophil subpopulations by standard clinical flow cytometric assays on peripheral blood of COVID‐19 patients.
Materials and methods
Patients
A total of 40 patients presenting to the emergency department (ED) of Careggi University Hospital in Florence with symptoms indicative of SARS‐CoV‐2 infection were consecutively enrolled in the present study. SARS‐CoV‐2 infection was confirmed by nucleic acid testing of nasopharyngeal swab specimens using RT‐PCR (real‐time PCR). Eight blood donors were recruited as healthy donors in the present study. COVID‐19 patients enrolled in the study were firstly analysed together, and then were divided into three groups based on the following criteria. ED patients were identified as those subjects who presented to the ED during the COVID‐19 pandemic because of flu‐like symptoms (i.e. fever, headache, diarrhoea), had a nasopharyngeal swab positive for SARS‐CoV‐2 and were not hospitalized because of their clinical condition, but were discharged home or to an isolation hotel once the diagnosis of SARS‐CoV‐2 infection was made. COVID‐19 patients who were hospitalized in non‐intensive care units (non‐ICU) because of evidence of lower respiratory disease according to clinical assessment or chest imaging and who needed close monitoring were classified as non‐ICU patients. Finally, patients admitted to the intensive care units (ICU) because of the need of invasive or non‐invasive mechanical ventilation were classified as ICU patients. The clinical features of enrolled patients are summarized in Table S1. The procedures followed in the study were approved by the Careggi University Hospital Ethical Committee (protocol 16859). Written informed consent was obtained from recruited patients.
Flow cytometry analysis
Blood specimens were collected using EDTA as anticoagulant. 100 μl of whole blood was stained for surface markers using a stain‐lyse‐and‐then‐wash procedure. The panel of antibodies used in these experiments included the following:
CD45 V‐500 (clone 2D1), HLA‐DR V‐500 (clone L243), CD66b V‐500 (clone G10F5), CD15 FITC (clone MMAC), CD14 FITC (clone MɸP9), CD123 PE (clone 9F5), CD64 PerCp‐cy5 (clone 10.1), CD13 PE‐cy7 (clone L138), CD33 PE‐cy7 (clone P676), CD11b APC (clone D12), CD300 APC clone UP‐H2, CD141 APC‐H7 (clone 1A4), CD16 APC‐H7 (clone 3G8) purchased from Becton‐Dickinson (BD, San Jose, CA) and CD1c (clone AD5‐8E7) purchased from Miltenyi.
Data acquisition was performed using a 3‐laser, 8‐colour flow cytometer (FACSCanto TMII, BD Biosciences, San Jose, CA); data were analysed by Infinicyt software (Cytognos SL, Salamanca, Spain). 5 × 105 total leucocytes were acquired for each analysis.
Gating strategy, analysis of cell subset and expression of surface antigens were performed as previously described. 17 , 18
Mean fluorescence intensity (MFI) was collected and tabulated for CD64, HLA‐DR and CD11b for monocytes and CD64, CD11b and CD66b for neutrophils in all patient and healthy donor specimens.
Evaluation of serum clinical parameters
Evaluation of WBC count was performed using a XN 550 haematology analyser (Sysmex Corporation, Kobe, Japan). Serum concentration of C‐reactive protein (CRP), ferritin, lactate dehydrogenase (LDH) and interleukin‐6 (IL‐6) was performed in a Cobas analyser (Roche Diagnostics, Penzberg, Germany). D‐dimer and fibrinogen were measured in a ACLTOP550 system (Instrumentation Laboratory, Werfen Group, Kirchheim bei Munchen, Germany). All these parameters were evaluated on blood specimens collected at the same time of those for flow cytometric analysis.
Statistical analysis
Unpaired Student’s t‐test was used for comparison of clinical and laboratory findings, and for flow cytometric analysis of healthy controls versus COVID‐19 patients. P values ≤0.05 were considered significant. Person’s correlation coefficients were used to calculate the correlations.
Results
COVID‐19 patients show differences in numbers of circulating DCs and in the phenotype of monocytes and neutrophils
In order to characterize the myeloid compartment, we evaluated numerical differences and immunological characteristics of leucocyte subpopulations in peripheral blood cells of 40 COVID‐19 patients. Although total leucocytes showed no differences between healthy donors and COVID‐19 patients (data not shown), we observed a significant decrease in lymphocyte, platelet and eosinophil absolute numbers in SARS‐CoV‐2‐infected subjects (Fig. 1A), in agreement with our previous report. 3 The number of monocytes, neutrophils and basophils showed no significant differences between COVID‐19 patients and healthy subjects (Fig. 1A). Of note, we found that pDCs and cDC2 absolute values significantly decreased in COVID‐19 patients as compared to healthy subjects (Fig. 1B and Fig. S1), whereas cDC1 subset was not detectable in both groups (data not shown).
Figure 1.
Flow cytometric characterization of myeloid cell subsets in COVID‐19 patients. (A) Absolute numbers of platelets (P), neutrophils (N), lymphocytes (L), monocytes (M), basophils (B) and eosinophils (E) in healthy subjects (black dots) and COVID‐19 patients (grey dots). (B) Absolute numbers of plasmacytoid dendritic cells (pDCs) and myeloid dendritic cells cDC2 in healthy subjects (black dots) and COVID‐19 patients (grey dots). (C) CD64, CD11b and HLA‐DR antigen expression on monocytes in healthy subjects (black dots) and COVID‐19 patients (grey dots). (D) Monocyte subset distribution in healthy subjects and COVID‐19 patients. Stacked columns represent means of CD14++/CD16− in orange, CD14++/CD16+ in green and CD14+/CD16++ in violet. *P ≤ 0.05, calculated with Student’s t‐test, referred to CD14+/CD16++ subset. (E) CD64, CD11b and CD66b antigen expression on neutrophils in healthy subjects (black dots) and COVID‐19 patients (grey dots). Data have been obtained from eight healthy controls and 40 COVID‐19 patients. *P ≤ 0.05, calculated with Student’s t‐test.
As monocyte and neutrophil absolute numbers showed no significant differences in COVID‐19 patients compared with healthy subjects, we evaluated whether there were any differences in the expression of canonical cell activation markers and/or in the distribution of different functional cell subsets by flow cytometry (see Figs S1 and S2). As shown in Fig. 1C and Fig. S2, the MFI of HLA‐DR expression on monocytes was significantly lower in COVID‐19 patients as compared to healthy subjects. On the other hand, the MFI of CD64 and CD11b expression on monocytes was increased in COVID‐19 patients as compared to healthy donors, even if the latter did not reach statistical significance (Fig. 1C and Fig. S2). Moreover, as shown in Fig. 1D and Fig. S1, we found a significantly lower frequency of CD14+/CD16++ monocytes in peripheral blood of SARS‐CoV‐2‐infected patients as compared to healthy subjects, whereas no differences were detected in the frequencies of CD14++/CD16− and CD14++/CD16+ cells between the two cohorts of subjects. Finally, flow cytometric analysis of neutrophil surface markers showed a significant increase in the MFI of CD66b expression in COVID‐19 patients as compared to healthy subjects, whereas expression of both CD11b and CD64 was comparable between the two groups of subjects (Fig. 1E and Fig. S2).
Figure 2.
Flow cytometric characterization of myeloid cell subsets in COVID‐19 patients at different stages of disease. (A) Absolute numbers of pDCs and cDC2 in ED (black dots), non‐ICU (grey dots) and ICU (white dots) COVID‐19 patients. (B) CD64, CD11b and HLA‐DR antigen expression on monocytes in ED (black dots), non‐ICU (grey dots) and ICU (white dots) COVID‐19 patients. *P ≤ 0.05, calculated with Student’s t‐test. (C) Monocyte subset distribution in ED, non‐ICU and ICU COVID‐19 patients. Stacked columns represent means of CD14++/CD16− in orange, CD14++/CD16+ in green and CD14+/CD16++ in violet. *P < 0.05 between ED and non‐ICU patients, **P < 0.05 between non‐ICU and ICU patients, calculated with Student’s t‐test. (D) CD64, CD11b and CD66b antigen expression on neutrophils in ED (black dots), non‐ICU (grey dots) and ICU (white dots) COVID‐19 patients. Data have been obtained from 9 ED, 20 non‐ICU and 11 ICU COVID‐19 patients. *P ≤ 0.05, calculated with Student’s t‐test.
COVID‐19 patients at different stages of disease show alterations in DC, monocyte and neutrophil compartments
Following admission to the ED for SARS‐CoV‐2 infection, some patients show mild symptoms and can be discharged and cared at home, while some others require hospitalization. Among the last group, a significant fraction of infected individuals develops acute respiratory distress syndrome and requires mechanical ventilation. 2 In this context, we investigated whether there were any significant variations in the previously identified immune parameters between patients who did not require hospitalization (ED), those admitted to the intensive care unit (ICU) and those hospitalized in non‐ICU units (Table S1). As shown in Fig. 2A, the absolute number of pDCs was reduced in both non‐ICU and ICU as compared to ED patients, with the latter being statistically significant. On the other side, cDC2 absolute numbers were significantly reduced in both non‐ICU and ICU patients when compared to ED ones (Fig. 2A). Of note, when comparing with data on healthy subjects, the number of cDC2 was significantly reduced already in ED patients (mean values of healthy versus ED: 0.013 versus 0.0045 cells/μl, P < 0.001). Differently, pDCs were not significantly reduced in ED patients compared with healthy donors (mean values of healthy versus ED: 0.0145 versus 0.0085 cells/μl, P = 0.14) and became significantly reduced only in non‐ICU and ICU patients (P values of healthy versus non‐ICU < 0.002; P values of healthy versus ICU < 0.00). To better elucidate the above‐described distribution of DC and monocyte subsets in the four groups of subjects, we showed in Fig. 3 a representative flow cytometric analysis of pDC, cDC2 and monocyte subpopulations.
Figure 3.
Examples of multiparametric flow cytometry analysis of DC and monocytes subset population frequencies in patients at different stages of disease. (A) Representative examples of flow cytometry dot plots on PB samples from a healthy subject, an ED, a non‐ICU and an ICU COVID‐19 patients (from left to right), frequencies of pDC are shown. (B) Representative examples of flow cytometry dot plots on PB samples from a healthy subject, an ED, a non‐ICU and an ICU COVID‐19 patients (from left to right), frequencies of DC2 are shown. (C) Representative examples of flow cytometry dot plots on PB samples from a healthy subject, an ED, a non‐ICU and an ICU COVID‐19 patients (from left to right), frequencies of the monocytes subsets are shown. Populations were defined as illustrated in gating strategy (Fig. S1).
Moving to surface antigen evaluation, the MFI of HLA‐DR expression on monocytes was remarkably reduced in both non‐ICU and ICU patients versus ED, suggesting a specific association with the need for hospitalization (Fig. 2B and Fig. S2). Of note, no differences were observed in the MFI of HLA‐DR expression on monocytes between ED patients and healthy donors (mean values of healthy versus ED: 17 762·13 versus 18 429·67 MFI, P = 0.82). No differences in CD64 and CD11b MFI expression on monocytes were observed between COVID‐19 groups of patients.
Concerning the distribution of monocyte subsets among the three groups of COVID‐19 patients, we observed that CD14++/CD16− monocytes significantly increased with a consequent significant reduction of CD14++/CD16+ and CD14+/CD16++ monocytes in non‐ICU patients compared with ED ones. Moreover, CD14+/CD16++ monocytes showed a significant small reduction in non‐ICU patients compared with ICU ones (Figs 2C and 3). Of note, CD14+/CD16++ population was significantly reduced in all three groups of patients compared with healthy subjects (mean values of CD14+/CD16++ monocytes in healthy are 7.2%; P values versus ED, non‐ICU and ICU patients are 0.01199, 1 × 10−5 and 3 × 10−5, respectively).
Finally, CD11b and CD66b expression on neutrophils showed no differences between the three groups of COVID‐19 patients, while CD64 was significantly upregulated in ICU compared with non‐ICU patients (Fig. 2D and Fig. S2). Of note, CD64 expression on neutrophils resulted significantly upregulated even when we compared ICU patients with healthy donors (mean values of healthy versus ICU: 1576.3 versus 3185.27 MFI, P = 0.039).
Changes in COVID‐19 patients’ myeloid cells correlate with inflammatory serum biochemical parameters
In order to understand whether the observed alterations in myeloid cells of COVID‐19 patients at different stages of disease might be related to systemic inflammation, we evaluated CRP, ferritin, D‐dimer, fibrinogen, LDH and IL‐6 serum levels in our cohorts of COVID‐19 patients. As shown in Fig. 4A–D, we found that CRP, ferritin, LDH and IL‐6 serum levels progressively increased in COVID‐19 patients with worsening of clinical conditions. Based on these assessments, we investigated whether there were any correlations between the previously described immunological alterations and the biochemical parameters of inflammation. Interestingly, serum levels of CRP inversely correlated with the absolute values of pDC, cDC2 and monocyte HLA‐DR expression (Fig. 4E–G). HLA‐DR expression on monocytes inversely correlated also with serum level of LDH (data not shown). Furthermore, as shown in Fig. 4H,I, we observed a direct correlation between the percentage of CD14++/CD16− monocytes and CRP, while CD14++/CD16+ indirectly correlated with CRP. Finally, we found a direct correlation between CD64 expression on neutrophils and serum levels of IL‐6 (Fig. 4L).
Figure 4.
Correlations between serum biochemical markers of inflammation with immunophenotypic alterations of the myeloid compartment. (A) CRP serum level in ED (black, n = 9), non‐ICU (grey, n = 20) and ICU (white, n = 11) COVID‐19 patients. (B) Ferritin serum level in ED (black, n = 4), non‐ICU (grey, n = 20) and ICU (white, n = 7) COVID‐19 patients. (C) LDH serum level in ED (black, n = 9), non‐ICU (grey, n = 20) and ICU (white, n = 10) COVID‐19 patients, (D) IL‐6 serum level in ED (black, n = 5), non‐ICU (grey, n = 20) and ICU (white, n = 11) COVID‐19 patients. Correlation of serum levels of CRP with absolute numbers of pDCs (E), cDC2 (F) and MFI of HLA‐DR expression on monocytes (G), frequencies of classical monocytes (CD14++/CD16−) (H) and intermediate monocytes (CD14++/CD16+) (I). Correlation between serum levels of IL‐6 and MFI of CD64 expression on neutrophils (L). Correlation between parameters was calculated with Pearson’s correlation coefficient. Red line represents the trend line, P values are shown in the upper right corner of the plot, and the Pearson correlation coefficient R values are shown below the P value.
Discussion
The role of the myeloid compartment in viral infections and inflammatory diseases has been widely characterized in several studies, demonstrating how these cells are crucial for a successful immune response against viruses and in influencing and regulating the recovery of immune homeostasis. 19 The aim of the present work was to perform a phenotypical characterization of myeloid cell compartment in SARS‐CoV‐2‐infected patients admitted to the Careggi University Hospital and experiencing different types of disease progression.
To this aim, we enrolled 40 COVID‐19 patients and confirmed our previous observations 3 showing marked lymphopenia and eosinopenia in COVID‐19 patients. In addition, we demonstrated a significant reduction of absolute numbers of pDCs and myeloid cDC2 in COVID‐19 patients compared with healthy donors. These observations are in accordance with data from research studies on other viral respiratory infections including MERS‐CoV and SARS‐CoV infections demonstrating a reduction on DC numbers. 10 We then characterized the myeloid compartment evaluating the expression of several functional and activation markers. We observed a downregulation of HLA‐DR and an upregulation of CD64 expression on monocytes while neutrophils showed an upregulation of CD66b expression. The upregulation of membrane activation markers reflects the activation status of monocytes and neutrophils in response to an infection, while the decreased expression of HLA‐DR on monocytes is a phenotypic alteration already reported in several infectious diseases including SARS‐CoV‐2 infection. 11 , 16
We next moved to the evaluation of monocyte subpopulations and observed that the frequency of CD14+/CD16++ was reduced in COVID‐19 patients compared with healthy subjects. Although the role of distinct monocyte subsets in infectious and inflammatory disorders is still debated, our finding is in agreement with the hypothesis of migratory/patrolling function of non‐classical monocytes: their reduction might be explained because of their differentiation and migration to the lung tissue. To further explore whether myeloid cell alterations occur at various stages of COVID‐19, we compared the same immunological parameters between patients who did not require hospitalization (ED), those admitted to the ICU and those hospitalized but not requiring intensive care during the course of the disease (non‐ICU). Intriguingly, we found a different behaviour of the two circulating DC subtypes. In fact, while pDC numbers were nearly unaltered in ED patients when compared to healthy subjects and resulted significantly decreased only in ICU patients, cDC2 were significantly reduced in all the three groups of patients: this suggested a higher susceptibility of cDC2 to SARS‐CoV‐2 infection as compared to pDC. A similar trend was shown by HLA‐DR expression on monocytes that was nearly unaffected in ED patients and markedly reduced in ICU and non‐ICU patients: this was consistent with data reported in SARS‐CoV‐2 and other infections showing the reduced expression of HLA‐DR and its correlation with the severity of the reactions. 16 , 20 In addition, the reduced HLA‐DR expression may suggest a reduced antigen presentation capacity, thus leading to impaired CD4+ T‐cell activation. Comparing the frequencies of monocyte subsets among the three groups of patients, we observed an increase in CD14++/CD16+ subset in ED patients compared with non‐ICU patients: this observation is in agreement with findings by Ahout et al., 11 demonstrating that intermediate monocyte subpopulation increased in the acute phase of respiratory syncytial virus infections. All together, these data support the hypothesis that pDCs, cDC2 and CD14+/CD16++ monocytes may be recruited from the bloodstream to the site of infection where they can either directly contribute to the host virus defence or supply the inflamed tissue with differentiated macrophages and DC cells to target the virus. This hypothesis is in agreement with findings by Sanchez‐Cerillo et al., 4 which show that CD14++/CD16+ and CD14+/CD16++ accumulate in the lungs of COVID‐19 patients. Another data emerged by the subgroup analysis of COVID‐19 patients are the significant upregulation of neutrophil expression of CD64 in ICU patients compared with healthy and non‐ICU subjects. The upregulation of this activation marker has already been described and is considered as an indicator of complication development during infectious diseases. 15
In addition, the correlation analysis showed that absolute values of pDCs', cDC2 and monocytes’ HLA‐DR expression significantly and inversely correlated with serum level of CRP (LDH also correlated with HLA‐DR MFI). These findings suggest that systemic inflammation may impair the myeloid cell functionality, as already demonstrated with lymphoid cells. 3 Supporting this hypothesis, the neutralization of IL‐6 axis via tocilizumab restores HLA‐DR expression on monocytes. 16
Finally, we found that frequencies of circulating CD14++/CD16− monocytes positively correlated with CRP, while CD14++/CD16+ monocytes negatively correlated with CRP. Collectively, these data support the hypothesis of a CD14++/CD16+ cell recruitment to infected tissues to face the viral infection with the consequent reduction of their frequencies in the periphery. In COVID‐19 patients at different stages of disease, we did not find any correlation between CD64 and CD11b expressions on monocytes and CD66b on neutrophils with inflammatory markers. This observation suggests that the upregulation of monocyte and neutrophil activation markers occurs at first stages of the infection, in parallel to the increase in pro‐inflammatory markers, and it is maintained over the course of the disease independently of the clinical severity. Only CD64 expression on neutrophils positively correlated with serum levels of IL‐6: this is in accordance with the observed higher expression of CD64 on neutrophils only in ICU patients and supports the hypothesis that its expression reflects the abnormal neutrophil activation status leading to a systemic inflammatory response as represented by IL‐6 upregulation. 21
In conclusion, our study demonstrates that circulating neutrophils, monocytes and DCs are altered in COVID‐19 patients. Moreover, we provide the first evidence that myeloid cell subsets important for antigen presentation are significantly affected in COVID‐19 patients as evidenced by the dramatic reduction in absolute numbers of circulating DCs and the reduced expression of HLA‐DR by monocytes. All these data, coupled with the impaired lymphoid cell functions, reflect the crucial role of inflammation in the immune dysregulation occurring in COVID‐19 patients.
Funding
This work was supported by the funds of Italian Ministry of Education, University and Research, 'Excellence Departments 2018–2022 Project', to the Department of Experimental and Clinical Medicine, University of Florence.
Disclosures
The authors declare that no conflict of interest exists.
Author contributions
PB, BS, CM, MA, ML, SL, VA, OC and CR performed experiments. NC, MoA, PL, PF, PA, BA and AMV recruited patients. LF, CL and AF designed the study. PB, CM and AF wrote the manuscript.
Supporting information
Figure S1. Gating strategy for the identification of granulocytes, different subsets of circulating monocytes and dendritic cells (DCs) in a representative peripheral blood (PB) sample from a COVID‐19 patient.
Figure S2. Examples of activation markers MFI in monocytes and granulocytes of COVID‐19 patients at different stage of disease.
Table S1. Clinical features of COVID‐19 patients.
Acknowledgements
We thank Dr. Carraresi Alessia (AOU Careggi), Dr. Statello Marinella (AOU Careggi) and Dr. Stefanelli Stefania (AOU Careggi) for technical support throughout the study.
Data availability statement
Data are available on request due to privacy/ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1. Gating strategy for the identification of granulocytes, different subsets of circulating monocytes and dendritic cells (DCs) in a representative peripheral blood (PB) sample from a COVID‐19 patient.
Figure S2. Examples of activation markers MFI in monocytes and granulocytes of COVID‐19 patients at different stage of disease.
Table S1. Clinical features of COVID‐19 patients.
Data Availability Statement
Data are available on request due to privacy/ethical restrictions.