Differences in monocyte subsets are associated with short‐term survival in patients with septic shock

Abstract Sepsis is characterized by dynamic changes of the immune system resulting in deregulated inflammation and failure of homoeostasis and can escalate to septic shock. Circulating monocytes and other innate immune cells are among the first ones to recognize and clear pathogens. Monocytes have an important role in sepsis and septic shock and have been studied as potential diagnostic markers. In total, forty‐two patients with septic shock were recruited and blood samples obtained within first 12 hours of ICU admission. We showed that frequency of classical and intermediate monocytes assessed at the time of admission to the intensive care unit are significantly distinct in patients with septic shock who survived longer that five days from those who died. These parameters correlate significantly with differences in serum levels of inflammatory cytokines MCP‐1, IL‐6, IL‐8, IL‐10, and IL‐18, and with the proportion of helper and cytotoxic T cells. The described changes in frequency of monocyte subsets and their activation status may predict short‐term septic shock survival and help with fast identification of the group of vulnerable patients, who may profit from tailored therapy.

characteristics and laboratory markers equating to a change in the sequential organ failure assessment (SOFA) score of 2 points, or more. 1 Many predictors of poor clinical outcome-such as high SOFA score, refractory course of shock, persistent hyperlactatemia, and hypothermia-have been described. 6 However, no single, standardized predictive marker currently exists to define the group of patients with the worst prognosis.
Monocytes carry the long-term burden of sepsis. 7,8 These cells are activated by pattern recognition receptors (PRRs) and sepsis-associated hypoxia 9,10 ; the hypoxia-inducible factor (HIF-1α) has been identified as having a key role in the functional reprogramming of these cells. 7 Monocytes can be categorized into three major subpopulations: classical (CD14 + CD16 − ), intermediate (CD14 + CD16 + ), and non-classical (CD14 lo CD16 + ) monocytes. 11 Fingerle et al reported that CD16 + cells can represent up to 50% of all monocytes during sepsis. 12 This finding led to studies of functional changes in monocytes during sepsis, although correlations between monocyte counts and sepsis severity have only been reported in the past 2 years. [13][14][15] In the search for diagnostic markers of sepsis progression, promising results have been provided by phenotypic changes in monocytes and the presence of monocyte-produced molecules in plasma. 16 However, studies on the role of monocytes during sepsis have not generally considered the complexity of monocyte biology. 15 The individual mechanistic roles of the three distinct monocyte subsets in sepsis progression remain to be investigated. Moreover, monocyte role in prediction of short-term survival in patients with sepsis has not been studied.
Sepsis affects most of the immune system functions, profound changes indeed impact leucocyte subsets including CD4 + T cells. 17 CD4 + T cells are important for regulation and orchestration of immune response and their impairment leads to loss of functional immune cells and subsequent immunosuppression; characteristic feature very often induced during sepsis. 18,19 In this study, we address whether the differences in monocyte subsets observed in patients with septic shock at the time of admission correlate with the severity of septic shock progression, including cytokine expression, changes in SOFA score, and early mortality.
The diagnosis within the early stages of septic shock is an important factor in patient prognosis.

| Cohort design
In this prospective, observational cohort study, adult patients with early septic shock who were admitted to the intensive care unit (ICU) at St. Anne's University Hospital in Brno, Czech Republic were consecutively enrolled. Patients with chronic immunosuppression and those who had received antibiotic therapy for more than 2 days were excluded. All patients were treated with tailored therapy according to current guidelines. 20 The cohort was divided for study purposes into two groups: those who survived longer than five days after admission and those who died within five days (early deceased).
Written informed consents were obtained from all enrolled patients and all procedures and protocols were approved by the institutional ethic committee (4G/2018).

| Blood sample isolation and preparation
Blood samples were obtained from patients within 12 hours of admission to the ICU and were processed within 2 hours of collection. Peripheral blood mononuclear cells (PBMCs) were isolated from blood by gradient centrifugation using Lymphoprep ® (Alere Technologies AS; Oslo, Norway) (density 1.077 g/mL) following the manufacturer's recommendations. Serum was collected in vials facilitating coagulation, centrifuged and immediately frozen and stored at −80°C.

| Immunophenotyping of samples
To obtain the phenotype of monocytes, PBMCs were labelled using CD3 + T cells were used to distinguish between helper (T h ) CD4 + and cytotoxic (T c ) CD8 + T cells. Sample acquisition was performed using FACSCanto ® (BD Biosciences) and data were analysed using FlowJo ® software (FlowJo, LLC Ltd, Ashland, OR, USA).

| Cytokine detection
Preparation and measurement of samples were performed using a Acquisition of samples was done on FACS Canto (BD Biosciences) and data were analysed using LEGENDplex™ software.

| Statistical analysis
Prism ® (GraphPad Software, LLC, Ltd, La Jolla, CA, USA) software was used for statistical analysis. Data were tested for normal distribution and statistical tests were applied as appropriate. Error bars are represented by SD. Statistical tests used are specified in the figure legends. The level of statistical significance was determined: *(P < 0.05), **(P < 0.01), and ***(P < 0.001). Correlation analysis was performed using Spearman's rank correlation coefficient and visualization was done in R studio by corrplot package. AUC of ROC curves were calculated using Prism ® software.

| Demographic and clinical characteristics of patients
We enrolled a total of 41 patients (all Caucasians), 33 of whom survived longer than five days after admission. The characteristics of the cohort as a whole and by group are shown in Table 1, Figure S1.
The mean age of patients was 71.3 years (range 49-89 years) and mean SOFA score of enrolled patients was 11.46 indicating septic shock. The most frequent comorbidities include ischaemic heart disease, obesity, ischaemic disease of the lower limbs, obesity and diabetes mellitus. The most common cause of septic shock in the cohort, as a whole was pneumonia (n = 17), where all patients survived past day five. Among those who died before day five, the most common origin of septic shock was infection of the urinary tract.
The most frequently detected microbial agents were Staphylococcus Aureus, E Coli, Enterococcus faecalis and Enterobacter Cloacae. In 13 patients the primary aetiological agent was not identified.

| Monocyte population characteristics
We analysed monocytes by immunophenotyping their surface markers. CD45 + and Lin − (CD3, CD19, CD20, CD56, CD66b, CD235a) cells were subsequently categorized to monocyte subsets based on presence of CD14 and CD16. The gating strategy used for monocyte phenotyping is shown in Figure 1A. We analysed the dependence of patient prognosis on the severity of sepsis (SOFA score) ( Figure 1B).
In early deceased patients, the frequency of classical monocytes was significantly decreased (P < 0.05) and the frequency of intermediate monocytes was significantly increased (P < 0.001), compared to patients who survived past day five ( Figure 1C). No differences in non-classical monocytes were observed. Non-significant trend towards decreased expression of human leucocyte antigen-DR isotype (HLA-DR; an indicator of monocyte activation status) was identified across all monocyte subsets in early deceased patients compared with survivors ( Figure 1D). Importantly, the expression of co-stimulatory molecule CD86 was significantly decreased in the classical monocytes of early deceased patients (P < 0.01) and, in the intermediate and non-classical monocyte subsets, CD86 expression tended to be lower in early deceased patients than in those who survived ( Figure 1E). We performed the analysis of HLA-DR low,neg CD86 low,neg and SOFA score was evaluated, revealing close to significant negative correlation (P = 0.069, P = 0.055 respectively; Figure 1G,H). The increased presence of HLA-DR low,neg CD86 low,neg cells in classical monocyte subset revealed significant correlation with sepsis severity represented by SOFA score (P = 0.024) ( Figure 1I).

| Cytokine production and correlation between monocyte characteristics
Differences in cytokine production between survivors and early deceased patients were analysed. The production of MCP-1, IL-6, IL-8, IL-10, and IL-18 was significantly higher in early deceased patients than in those who survived to day 5 (

| T cell immunophenotype and correlation with cytokines levels
T cells were characterized by the presence of CD3, and subsequently, positivity on CD4 (T h ) and CD8 (T c ) was determined. The gating strategy is shown in Figure 3A.
Early deceased patients had significantly fewer CD4 + cells and significantly more CD8 + cells (P < 0.05) compared to patients who survived past day five ( Figure 3B); the ratio of CD4 + and CD8 + populations was calculated ( Figure 3D). No correlations between the frequency of CD4 + or CD8 + cells and the SOFA score were found ( Figure 3D,E).
Correlation analysis was performed using individual parameters for immunophenotyping and cytokine production. The reduced frequency of CD4 + cells strongly negatively correlated with the increasing relative count of CD8 + cells (P < 0.001). The overall decreased frequency of CD4 + T cells was significantly associated with IL-10 production (P < 0.05) (Figure 4, Figure S2.

| D ISCUSS I ON
Using data from a cohort of 41 patients admitted to the ICU with septic shock, we investigated whether the frequency of different monocyte subsets and their activation status assessed within 12 hours of admission, is associated with a fulminant course of septic shock. In order to identify the immune-phenotype associated with fulminant course of septic shock, the studied cohort was retrospectively divided into two groups; one group contained patients with very short survival (within 5 days) and second was the group of patients, who survived this crucial 5-day period. As we mainly focused to analyse phenotype of the dynamically changing monocytes subsets, the 12 hours time-point of analysis provided an important advantage comparing to other reports focused to monocytes where authors used later sampling (1-5 days after admission to ICU). 13,14,21 The prompt risk stratification of patients with septic shock, is a key information for adjusting the care and later improvement of the therapeutics outcomes remain a key research focus. 5,22 Many different experimental strategies, including single cell expression analysis, 23 have been used to improve our understanding of the immune response in the early phase of sepsis and to identify new therapeutic targets. 24 Here we report shift in frequencies of classical and intermediate gene. 18 We also focused on HLA-DR surface expression levels. Our Interestingly, it is well known that CD86, as a co-stimulatory molecule, has a key role in supporting the development of T cells, therefore we also analysed basic changes in T cells. Considering our search for dynamically changing parameters among monocytes we also assessed some basic information from T cells immune-phenotype, impaired T cells functions, exhaustion and apoptosis are hallmarks of sepsis. 18 Although usually these changes are reported in later time-points of septic shock and also can persist after patient recovery. 36 Our data demonstrate the differences in CD4 + and F I G U R E 3 Changes in T cells frequency of patients with septic shock. A, Gating strategy used for T cell phenotyping. Lymphocytes were gated from an FSC x SSC plot. CD3 + T cells were used to distinguish CD4 + and CD8 + T cells. Singlet and live/dead gating strategy plot not shown. B, Differences in CD4 + and CD8 + cell subsets. There were significantly fewer CD4 + cells and significantly more CD8 + cells in early deceased patients in day 5+ survivors. C, Ratio of CD4 + /CD8 + cells in D5+ survivors in comparison to early deceased patients. D and E, Correlation between frequency of CD4 + and CD8 + T cells and sepsis severity (SOFA score). Data were tested by Mann-Whitney test, error bars are represented by SD. Correlation statistics (Spearman analysis) were performed using Graphpad software. *(P < 0.05), **(P < 0.01), ***(P < 0.001) CD8 + frequency occurred in both observed patient groups with septic shock at the time of their admission to ICU. The differences in CD4 + and CD8 + cell frequency to reduced amount CD4 + cells, probably indicates higher susceptibility to fulminant septic shock. However, validation of our data will be required as our study had several limitations including size (41 patients) recruited from a single centre; the average age of patients was 71.3 years, which limits how our findings can be generalized to other age groups.
Even though we analysed data from cohort with a very broad clinical sources of septic shock including different types of bacterial agents, our results demonstrate that monocyte subset frequency can serve as predictive marker of septic shock survival independent on stimuli, which induced the septic shock. Further analysis in a larger cohort will allow us to determine whether the observed differences in monocyte subsets can be used to predict patient outcome and be used to risk stratify patients and detect those with excessive inflammatory response who may profit from immunomodulatory therapy.
Altogether, we demonstrated that proportional changes in monocyte subsets and their correlation with increased cytokine production and decreased status of activation of these cells, can serve as predictive marker of septic shock prognosis ( Figure 5). Future research should deeply focus on the dynamics of monocytes subsets in progression of septic shock. We have identified markers that have the potential to be used in prognostic tests; the sample may be taken and analysed at the time of admission, and parameters correlating with survival quantified within hours of sample collection. This approach may help to apply more tailored immunotherapy of patients in septic shock.

ACK N OWLED G EM ENTS
We wish to thank Alexandra Roberts of Insight Editing London for critical review of the manuscript. We thank the technical support team of Center of Translational Medicine.

CO N FLI C T O F I NTE R E S T
Authors have no conflicting interests.

DATA AVA I L A B I L I T Y S TAT E M E N T
Data availability is upon the reasonable request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

R E FE R E N C E S F I G U R E 5
The changes in monocyte subset frequency, reduced status of their activation and increased cytokine production can serve as predictive marker of septic shock prognosis