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Comparison of Circulating Immune Cells Profiles and Kinetics Between Coronavirus Disease 2019 and Bacterial Sepsis*

de Roquetaillade, Charles MD, MSc1–3; Mansouri, Sehmi MD1–3; Brumpt, Caren MD4; Neuwirth, Marie MD4; Voicu, Sébastian MD3,5; Le Dorze, Matthieu MD, MSc1; Fontaine, Candice MD, MSc6; Barthélémy, Romain MD, MSc1,2; Gayat, Etienne MD, PhD1–3; Megarbane, Bruno MD, PhD3,5; Mebazaa, Alexandre MD, PhD1–3; Chousterman, Benjamin Glenn MD, PhD1–3

Author Information
doi: 10.1097/CCM.0000000000005088


In December 2019, the first pneumonia cases of unknown origin were identified in Wuhan, the capital city of Hubei province. The pathogen was later identified as a novel pathogen from the RNA betacoronavirus family named severe acute respiratory syndrome coronavirus (SARS-CoV) 2. This virus shares phylogenetic similarities with SARS-CoV such as a common entry receptor (angiotensin-converting enzyme 2). The disease triggered by SARS-CoV-2 infection was later named coronavirus disease 2019 (COVID-19). In March 2020, the virus which had spread worldwide was recognized by the World Health Organization (WHO) as a public health emergency and the status of pandemic declared. To date, no specific treatment demonstrated its ability to reduce symptoms and disease severity. However, corticosteroids have gained credence, and their ability to modulate inflammation has been shown beneficial in COVID-19 patients (1).

Although COVID-19 clinical presentation seems well characterized (2–4), several studies reported correlation between clinical severity and alteration in leukocytes count. Recent reports have highlighted marked lymphopenia and elevated neutrophil count as well as reduced human leukocyte antigen D receptor (HLA-DR) expression on CD14+ monocytes (mHLA-DR) (5,6), such modifications could evoke immune suppression similar to this observed in sepsis (7); however, correlation with severity and outcome is poorly described. In particular, it is unknown if COVID-19 immune alterations depict an adaptive mechanism to aggression or a “component” of the aggression itself. In this perspective, analysis of association between observed immune alterations and mortality as well as occurrence of secondary infection (an emerging threat) deserves further investigations (8). Here, we provide a comparative analysis of COVID-19–associated immune alterations and chronologic immune profile with a historical cohort of bacterial sepsis.


Study Design

This is a retrospective single-center study based on case files of patients admitted to Lariboisière Hospital (APHP.Nord, Paris, France) during the first 2020 COVID-19 outbreak. This tertiary-care hospital comprises two distinct ICU and one emergency department (ED). This study was approved by our local ethics committee who waived the need for patients’ consent due to the retrospective observational design of our study (Institutional Review Board 00006477).

Study Population

Case files of COVID-19 patients with confirmed SARS-CoV-2 infection using reverse transcriptase-polymerase chain reaction (RT-PCR), admitted either to the ED, the ICU, or the medical ward with at least one immunophenotyping performed during their hospital stay were included. Patients admitted to the ED/ward were classified as “nonsevere,” whereas patients admitted to the ICU as “severe.”

Severe COVID-19 patients admitted to the ICU were compared with a historical cohort of ICU patients admitted for severe sepsis or septic shock (9) with comparable outcome, referred as “sepsis” patients.

Patient Management

COVID-19 patient were managed according to the international guidelines and local protocols. Utilization of corticosteroids as well as antivirals was left at the physician’s appraisal. For most ICU patients, blood sampling was performed daily and immune profiling twice a week (Monday to Thursday) until discharge or death.


Demographics, comorbidities, chronic medication use, admission and daily clinical measurements, severity scores (including the Simplified Acute Physiology Score II and the Sequential Organ Failure Assessment [SOFA] score), inotrope use, and mechanical ventilation were extracted from the case files and data management systems (ORBIS, Agfa healthcare, Mortsel, Belgium). Viral load refers to cycle threshold (Ct) for RT-PCR positivity assuming that Ct is inversely proportional to viral load (i.e., low Ct value indicates a higher load) (10). “Admission data” referred to the first immune profiling within the 3 first days following admission. Secondary infection was defined using Centers for Disease Control and Prevention definition (11–13) as a new-onset infection starting at least 48 hours after ICU admission and requiring antimicrobial therapy administration or modification. The likelihood of infection motivating the clinical decision to administer an antibiotic was classified retrospectively by three experts (C.d.R., S.M., B.G.C.) as none, possible, probable, and definite.

Cytometry Protocol

WBCs count was performed on Hematology Analyzer (Sysmex XN3000, Sysmex, Landskrona, Sweden) (including lymphocytes count) for all patients. Flow cytometry was performed using a FACS Canto II flow cytometer (BD Bioscience, San Jose, CA). In brief, all surface staining was performed on 50 µL of EDTA whole blood. A first antibody panel was used to target the following populations: total CD3+, CD4+ and CD8+ T cells, CD19+ B cells, and CD56+ NK cells (BD MultiTEST four-color Reagents from BD Biosciences) using a BD TrueCOUNT tube. A second antibody panel was used to measure mHLA-DR. Mean fluorescence intensity was later converted to antibody per cell (AB/C) using quantibrite beads from BD Bioscience.

Statistical Analyses

Data are described as numbers and percentages for categorical variables and median (interquartile range) for continuous variables. Comparisons were performed using Fisher exact or chi-square tests for categorical data and Kruskal-Wallis or Wilcoxon tests for continuous data. Analyses of correlation were made using the Pearson correlation coefficient. Leukocytes subset analyzes were performed to compare patients according to severity, viral load, outcome, and secondary infections. Any value of p below 0.05 was considered significant. All statistical analyses were performed using R statistical software version 4.0.0 (R Core Team, 2020, R Foundation for Statistical Computing, Vienna, Austria,


Study Population

Between March and April 2020, 261 patient files with proven SARS-CoV-2 infection and available immune phenotyping were included in the study. The cohort consisted in 94 severe COVID-19 patients requiring ICU admission, 153 patients with nonsevere forms of COVID-19. Those included 118 mild-to-moderate COVID-19 patients hospitalized in ward; 29 hospitalized patients with incidental asymptomatic SARS-CoV-2 infection; and six patients with mild COVID-19 diagnosed in ED and discharged back home (see Flow-Chart in the Supplementary Material, Median delay between admission and baseline immune profile was 2 days (1–3 d). Characteristics of patients are described in Table 1 and Supplementary Table 1 (

TABLE 1. - Comparisons of Severe Coronavirus Disease 2019 and Bacterial Sepsis Patients
Variables Severe Coronavirus Disease 2019 (n = 94) Bacterial Sepsis (n = 108) p
Age, median (IQR) 60 (52–68) 70 (57–84) < 0.01
Male sex, n (%) 75 (79.8) 69 (63.9) 0.02
Comorbid conditions
 Charlson comorbidity score, median (IQR) 2 (1–4) 5 (3–8) < 0.01
 Hypertension, n (%) 47 (50.0) 52 (48.1) 0.90
 Diabetes, n (%) 32 (34.0) 21 (19.4) 0.03
 Tobacco use, n (%) 9 (9.6) 4 (3.7) 0.07
 Chronic heart failure, n (%) 10 (10.6) 34 (31.5) < 0.01
 Chronic kidney disease, n (%) 9 (9.6) 14 (13.0) 0.59
 Obstructive pulmonary disease, n (%) 15 (16.0) 9 (8.3) 0.15
 Immunodepression, n (%) 6 (6.4) 32 (29.6) < 0.01
Clinical characteristic
 ICU 1 61 (64.9) 108 (100)
 ICU 2 33 (35.1) 0 (0)
 Time from onset of symptoms, median (IQR) 7 (4–10)
 Simplified Acute Physiology Score II, median (IQR) 36 (26–47) 56 (46–58) < 0.01
 Sequential Organ Failure Assessment at admission, median (IQR) 7 (3–10) 8 (5–11) < 0.01
 Bacterial coinfection, n (%) 15 (16)
ICU management
 Mechanical ventilation, n (%) 73 (77.7) 25 (23.1) < 0.01
 Catecholamine support, n (%) 61 (65.6) 77 (71.3) 0.47
Specific treatment
 Hydroxychloroquine + azithromycin 44 (46.8)
 Corticosteroids 41 (43.6)
 Tocilizumab/sarilumab 8 (8.5)
 Length of stay (d), median (IQR) 17 (9–31) 9 (5–19) < 0.01
 Secondary infection, n (%) 65 (69.1) 41 (38.0) < 0.01
 ICU mortality, n (%) 33 (35.1) 38 (35.2) 1
IQR = interquartile rage.
p < 0.05 considered statistically significant.
Dashes indicate not applicable.

COVID-19 and Sepsis Baseline Immune Profile

Baseline immune profiles are depicted in Figure 1. Compared with mild-to-moderate forms, patients suffering from severe COVID-19 had higher neutrophil count (p < 0.01) as well as increased basophil count (p < 0.01). Those patients had lower mHLA-DR expression (p < 0.01). They experienced profound lymphopenia affecting CD3+ (p < 0.01), CD4+ (p < 0.01), CD8+ (p < 0.01) T cells, and NK cells (p < 0.01). When compared with patients with septic shock, patients with severe COVID-19 had higher basophil count at baseline (p < 0.01, higher T cells (p < 0.01) and higher B-cell count (p < 0.01). Although severe COVID-19 patients were more prone to be males (p = 0.02), analyses of baseline characteristics and leukocyte subsets as well as mHLA-DR expression retrieved no gender-related differences (Supplementary Table 2, The presence of coinfection at admission was relatively rare among severe COVID-19 patients (n = 15; 16%); among those patients, only mHLA-DR expression was lower when compared with patients without coinfection at admission (6,285 [4,036–9,432] vs 3,964 AB/C [2,983–6,003 AB/C]; p = 0.02) (Supplementary Table 3,

Figure 1.
Figure 1.:
Quantification of major immune subsets and immune suppression markers inpatient cohort. Quantification of key immune variables as well as immune suppression markers within first days of admission (median, 2 d) for patients suffering from nonsevere coronavirus disease (COVID) (green), severe COVID requiring ICU admission (red), and patients with septic shock of bacterial origin (blue). Each dot represent a patient. Usual values are depicted with a green rectangle for each variable. Unless stated otherwise, results are expressed in ×103 cells/mm3. human leukocyte antigen D receptor (HLA-DR) expression on CD14+ monocytes (mHLA-DR) expression is given in antibody per cell (AB/C). Data are compared using the Mann-Whitney U tests; * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. COVID-19 = COVID 2019.

COVID-19 Leukocyte Subsets: Correlation With Severity, Viral Load, and Age

Among severe COVID-19 patients, eosinophil count, mHLA-DR expression as well as NK cells number inversely correlated with SOFA, whereas all the other immune subsets did not vary with SOFA score (Fig. 2). Regarding age, older patients had higher neutrophil count at baseline (R = 0.37; p < 0.01). Older age also correlated with more profound lymphopenia of CD3+, CD4, CD8, NK, and B cells as well as lower mHLA-DR at admission (Supplementary Table 4, Viral load assessment could be obtained from 71 severe COVID-19 patients. Eosinophil count positively correlated with viral load (R = 0.27; p = 0.041), whereas other tested variables were not impacted.

Figure 2.
Figure 2.:
Spearman correlation between initial immune variables and indicated clinical features among patients with severe coronavirus disease 2019 infection. Correlation among patients with the most severe forms (ICU cohort). Comparisons were performed using Pearson’s tests; p < 0.05 was considered as significant. NK = Natural Killer cells, mHLA-DR = human leukocyte antigen D receptor (HLA-DR) expression on CD14+ monocytes, SOFA = Sequential Organ Failure Assessment.

Kinetic Variations of Immune Profiles in Severe COVID-19 and Sepsis

Kinetic variations of CD3, CD4, CD8, monocytes, and NK cells did not differ between severe COVID-19 and sepsis patients with a persistent reduction of cell counts over time (Fig. 3). Neutrophils appeared lowered in severe COVID-19 as compared to sepsis on days 8–12 (p < 0,01). mHLA-DR was higher in severe COVID-19 patients compared with sepsis on days 2–4 (p < 0.01). Strikingly, basophil count remained higher in severe COVID-19 as compared to sepsis during the entire hospital stay (p < 0.01). B cell count and eosinophils were higher in severe COVID-19 compared with sepsis after the second week of ICU admission (days 8–12 and 13–21).

Figure 3.
Figure 3.:
Kinetic analysis of immune alterations in coronavirus disease 2019 (COVID-19) patients in comparison with bacterial sepsis patients. Leukocyte absolute number variations according to the delay from ICU admission between COVID-19 patients (red) and patients with septic shock (blue). Unless stated otherwise, results are expressed in ×103 cells/mm3. human leukocyte antigen D receptor (HLA-DR) expression on CD14+ monocytes (mHLA-DR) expression is given in antibody per cell (AB/C). Data are compared using the Mann-Whitney U tests; * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.

Kinetics of COVID-19 Immune Profile and ICU Mortality

Immune profile of severe COVID-19 patients differed markedly according to their outcome (Fig. 4). Except for CD19+ B cells and neutrophils, immune subsets did not differ on days 0–4 between survivors and nonsurvivors. Differences appeared between survivors and nonsurvivors after day 4, with a trend toward correction of immune cells and phenotype in the survivor group, whereas alterations persisted or worsened in the group of patients who died. Although the two cohorts had a similar mortality rate on day 28 (p = 0.14 log-rank) (Supplementary Fig. 1, These remarkable differences between survivors and deceased patients were not observed among patients with bacterial sepsis (Supplementary Fig. 2,

Figure 4.
Figure 4.:
Kinetic analysis of immune profile according to outcome in patients with severe coronavirus disease 2019 (COVID-19). Longitudinal leukocyte absolute number and immune dysfunction between survivors and non survivors among COVID-19 patients Unless stated otherwise, results are expressed in ×103 cells/mm3. human leukocyte antigen D receptor (HLA-DR) expression on CD14+ monocytes (mHLA-DR) expression is given in antibody per cell (AB/C). Data are compared using the Mann-Whitney U tests; * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.

COVID-19 Immune Profile and Secondary Infections

Patients who experienced at least one secondary infection during their ICU stay had a lower mHLA-DR expression, as well as lower CD8 T cells on days 5–10. At last, basophil count was lower on days 11–21 for those patients (Supplementary Fig. 3, Similar findings were also observed among patients with sepsis with a trend toward correction of CD3, CD4, CD8+, and NK lymphopenia among patients who did not present further secondary infection (Supplementary Fig. 4,


In the present study, we showed that circulating immune cells profiles differs between mild and severe COVID-19 patients. Our results also illustrate that severe COVID-19 is associated with a unique immune profile as compared to sepsis. Several immune features are associated with outcome, and lack of correction of immune alterations during the first 2 weeks of hospitalization is associated with worsened outcome. Thus, immune monitoring of COVID-19 might be of help for patient management.

Our study confirms, in a large population, that immune signature markedly differs between severe and mild-to-moderate COVID-19 patients. Several reports have documented a relationship between circulating immune cells modification and severity during COVID-19 (14). To date, very few studies have reported longitudinal analyses of leukocyte subpopulations evolution over time and their correlation with outcome. As suggested by previous studies, our findings are consistent with persistent and profound depletion in lymphocytes subsets as well as reduction in mHLA-DR expression (15,16).

The pathophysiology and clinical course of COVID-19 is extensively studied and has been compared with “classical” bacterial sepsis (16,17). It appears that such comparison is, at best, naive and no longer supported by recent findings (18). Sepsis is associated with an intense mobilization of the myeloid compartment (neutrophils and monocytes) together with very high levels of circulating cytokines (interleukin [IL]-6, IL-1, tumor necrosis factor-alpha). Initial inflammation process is characterized with a short time course of onset and a resolution within the first days, whereas immune suppression could persist for months (7,19).

During COVID-19, a macrophage—T-cells circuit has recently been described (18). Briefly, SARS-CoV-2 invades and activates alveolar macrophages and recruited inflammatory monocytes in the lung with a subsequent mobilization of T cells that will execute an interferon (INF)–mediated gene expression pattern and cause local tissue damage within a local and progressing alveolitis. This entire process occurs within several days at a much slower pace than the myeloid recruitment observed during sepsis but seems to last for a longer duration.

Distinguishing the features related to the COVID-19 specific immune pathophysiology and nonspecific inflammation related to tissue damage is difficult. Because of tissue lesions and release of damage-associated molecular patterns observed during both sepsis and COVID-19, it is likely that immune similarities between those two syndromes result in part from this nonspecific answer. Systemic elevation of neutrophils and mHLA-DR down-regulation could reflect this aspect of the pathologic process. During COVID-19, the observed depletion in circulating lymphocytes we observe is most likely due to their recruitment in the lung. Indeed, several authors have identified an enrichment of lymphocytes in bronchoalveolar lavage of patients with COVID-19 together with a reduction in circulating pool (18). During sepsis, the observed lymphopenia is mainly the consequence of lymphocyte apoptosis (20). At last, clinical features and cytokine signature markedly differ between the two diseases (21) which should imply different phenotype of circulating leukocyte subsets implied we were not able to provide.

Implications and Perspectives

Our clinical observations support the onset of a strong and durable immune suppression together with an elevated incidence of ICU-acquired infection (60%). Given that, a better characterization of the adverse effects of corticosteroids as well as other anti-inflammatory drugs and their impact on ICU-acquired infections is highly warranted. Conversely, therapy aiming at stopping monocyte-lymphocytes interactions, such as anti–IFNγ therapy (NCT04324021), or etoposide (22), may be of interest in the management of the most severe patients.


Our study has several limitations. First, as retrospective single-center, selection, or center biases may prevent generalization of our findings. Second, the sepsis population we used is not perfectly matched to our COVID-19 patient cohort. However, we selected this cohort because of the similar outcome and hint that COVID-19 is, as sepsis, a disease due to a global activation of the immune system leading to a major increase in circulating cytokines. Third, we did not perform functional testing of immune cells or detailed cell phenotyping. However, our results are based on a large population and include a kinetic analysis that adds to the current knowledge regarding the COVID-19–related impact on immunity.


Circulating immune cells profile differs between mild and severe COVID-19 patients. Severe COVID-19 is associated with a unique immune profile as compared to sepsis. Several immune features are associated with outcome. Immune monitoring might be of help in the management of COVID-19 patients.


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    coronavirus disease 2019; intensive care unit; immune suppression; immunity; sepsis; septic shock

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