Standardized single-platform assay for human monocyte subpopulations: Lower CD14+CD16++ monocytes in females

Authors

  • Irene Heimbeck,

    1. KKG Inflammatory Lung Diseases, Helmholtz-Zentrum Muenchen and Asklepios Hospital, Muenchen Gauting and Comprehensive Pneumology Center, Ludwig-Maximilians University Munich, Helmholtz Zentrum München, Germany
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    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.

  • Thomas P. J. Hofer,

    1. KKG Inflammatory Lung Diseases, Helmholtz-Zentrum Muenchen and Asklepios Hospital, Muenchen Gauting and Comprehensive Pneumology Center, Ludwig-Maximilians University Munich, Helmholtz Zentrum München, Germany
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    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.

  • Christiane Eder,

    1. KKG Inflammatory Lung Diseases, Helmholtz-Zentrum Muenchen and Asklepios Hospital, Muenchen Gauting and Comprehensive Pneumology Center, Ludwig-Maximilians University Munich, Helmholtz Zentrum München, Germany
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    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.

  • Adam K. Wright,

    1. Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, United Kingdom
    2. National Institute of Health Research, Biomedical Research Center in Microbial Diseases, Royal Liverpool and Broadgreen University Hospitals Trust, Liverpool, United Kingdom
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    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.

  • Marion Frankenberger,

    1. KKG Inflammatory Lung Diseases, Helmholtz-Zentrum Muenchen and Asklepios Hospital, Muenchen Gauting and Comprehensive Pneumology Center, Ludwig-Maximilians University Munich, Helmholtz Zentrum München, Germany
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    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.

  • Ayman Marei,

    1. Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, United Kingdom
    2. Faculty of Medicine, Department of Microbiology and Immunology, Zagazig University, Egypt
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    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.

  • Ghada Boghdadi,

    1. Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, United Kingdom
    2. Faculty of Medicine, Department of Microbiology and Immunology, Zagazig University, Egypt
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    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.

  • Jürgen Scherberich,

    1. Klinik f. Nephrologie and Klinische Immunologie, Municipal Hospital Harlaching, Ludwig-Maximilians University, Muenchen, Germany
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    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.

  • Loems Ziegler-Heitbrock

    Corresponding author
    1. KKG Inflammatory Lung Diseases, Helmholtz-Zentrum Muenchen and Asklepios Hospital, Muenchen Gauting and Comprehensive Pneumology Center, Ludwig-Maximilians University Munich, Helmholtz Zentrum München, Germany
    2. Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, United Kingdom
    • KKG Inflammatory Lung Diseases, Helmholtz-Zentrum Muenchen, Robert-Koch-Allee 29, 82131 Gauting, Germany
    Search for more papers by this author
    • Irene Heimbeck, Thomas P. J. Hofer, Christiane Eder, Adam Wright, Ayman Marai, and Ghada Boghdadi performed experiments. Marion Frankenberger was involved in the study design and performed experiments. Jürgen Scherberich provided clinical samples. Loems Ziegler-Heitbrock was involved in the study design and wrote the article.


Abstract

We present a novel single-platform assay for determination of the absolute number of human blood monocyte subpopulations, i.e., the CD14++CD16 and the CD14+CD16++ monocytes. A four-color combination of antibodies to CD14, CD16, CD45, and HLA-DR reduces the spill-over of natural killer cells and of granulocytes into the CD14+CD16++ monocyte gate. For these CD14+CD16++ monocytes, the intra-assay coefficient of variation (CV) was 4.1% and the inter-assay CV was 8.5%. Looking at a cohort of 40 donors aged 18–60 years, we found no age dependence. There was however an effect of gender in that females had lower CD14+CD16++ monocytes (45.4 ± 13.5 cells/μl) compared with males (59.1 ± 20.3 cells/μl) (P < 0.02). Using this novel approach, we can confirm that exercise will lead to more than three-fold increase of the CD14+CD16++ monocytes. Also, we show that therapy with low doses of glucocorticoids will deplete these cells. This robust single-platform assay may be a useful tool for monitoring the absolute number of monocyte subpopulations in health and disease. © 2010 International Society for Advancement of Cytometry

Myelomonocytic stem cells in bone marrow give rise to monocytes and these are released into blood where they circulate for a few days and then migrate into tissue where they develop into different types of macrophages (1). Monocytes were initially defined based on morphology and cytochemistry. With the advent of monoclonal antibodies and flow cytometry, human monocytes were characterized with antibodies like CD14. This technology also allowed for the definition of two monocyte subsets, i.e., the classical CD14++CD16 and the CD14+CD16++ nonclassical monocytes (2) with the latter cells characterized by higher MHC class II expression and by higher production of the cytokine tumor necrosis factor (3). With the recognition of the potential role of the nonclassical CD14+CD16++ monocytes in disease, many clinical and laboratory studies have been conducted. Increased numbers were found in conditions like sepsis (4–6), erysipelas (7), HUS (8), HIV-infection (9–12), coronary artery disease (CAD) (13), hemophagocytic syndrome (14, 15), rheumatoid arthritis (16–18), Kawasaki disease (19), Sjögren Syndrome (20), and after major hepatectomy (21).

It was also shown that excessive exercise can mobilize the CD14+CD16++ monocytes from the marginal pool, such that the total number of these cells can increase by a factor of 4 (22). On the other hand, glucocorticoid therapy depletes the CD14+CD16++ monocytes in healthy individuals, in multiple sclerosis, in bronchiolitis obliterans, and in rheumatoid arthritis (23–26). A transient depletion of the CD14+CD16++ monocytes was noted during hemodialysis therapy (27).

In many of these studies, percentages of monocyte subsets were reported and when absolute numbers were determined then they were derived from two-platform approaches with its inherent imprecision. For tests in the clinical laboratory, an accurate assay is however an important requirement. We have therefore developed a single-platform assay that reduces at the same time overlap of the CD14+CD16++ monocytes with the CD16+ NK cells and CD16+ granulocytes. We show herein that this assay has a low coefficient of variation and that it can readily detect increases and decreases of the nonclassical CD14+CD16++ monocytes resulting from excessive exercise and from glucocorticoid therapy, respectively. With this test we can demonstrate for the first time that females have a lower absolute count of the nonclassical monocytes when compared with males.

Matterials and Methods

Subjects

Forty nonsmoking healthy subjects between the ages of 18 and 60 years were recruited to determine the normal distribution and any age dependence of monocyte subpopulations. A group of 11 healthy individuals (age 18–30) were studied before and after physical exercise on a home-trainer bike at 200 watts (W) either for 1 min or to exhaustion for 3–10 min. In addition, we analyzed four patients with inflammatory diseases. Two had glomerulonephritis, one polymyalgia, and one bronchiolitis obliterans with organizing pneumonia (BOOP). These patients were studied before and several days after immunosuppressive therapy with oral glucocorticoids during hospitalization (for details on time and dose see legend to Fig. 6). Written informed consent was obtained from each individual. The study was approved by the Ethics Committee of the Medical School of the Ludwig-Maximilians University (Muenchen, Germany).

Monoclonal Antibodies

The following monoclonal antibodies were used to determine monocyte subpopulations: fluorescein isothiocyanate (FITC)-conjugated anti-CD14 clone My4 (No. 6603511, isotype: mouse IgG2b FITC), phycoerythrin (PE)-conjugated anti-CD16 clone 3G8 (No. A07766, isotype: mouse IgG1 PE), PC5-conjugated anti-HLA-DR (No. PM 2659U, isotype: mouse IgG1 PC5), and allophycocyanin (APC)-conjugated CD45 (No. IM2473, isotype: mouse IgG1APC). All antibodies and their respective isotype controls were purchased from Beckman Coulter, Krefeld, Germany.

Blood Sampling and Staining Procedure

Blood samples were taken by peripheral venipuncture. Whole blood was collected in K3E S-Monovettes® (No. 05.1167 Sarstedt, Germany) and specimens were prepared for flow cytometry within 30 min.

About 100 μl of the whole blood was added to a 5 ml polystyrene round-bottom tube (REF 302054 BD Biosciences, Heidelberg, Germany) and 5 μl of each antigen specific fluorochrome-labelled antibody (dilution 1:20) was added. The sample was then incubated for 20 min at 4°C in the dark. Lysis of erythrocytes was performed using a Coulter Q-Prep® lysis instrument. For sample dilution, 2,400 μl of buffer was added and the sample was supplemented with 100 μl of CountBright absolute counting beads® (No. C36950, Invitrogen, Karlsruhe, Germany) for determination of absolute numbers of cells. To ensure maximum viability, stained cells were analyzed promptly.

MIFlowCyt Standards

  • 1Experiment Overview 1.1. Purpose To present a novel single platform assay for determination of the absolute number of human blood monocyte subpopulations, i.e., the CD14++CD16 and the CD14+CD16++ monocytes. 1.2. Keywords Human blood monocytes subsets, CD14, and CD16 1.3. Experiment variables Age, gender, exercise, and glucocorticoid therapy.
  • 2Flow Sample 2.1. Sample specimen  2.1.1. Biological samples   2.1.1.1. Human peripheral blood 2.2. Fluorescence reagents FITC-conjugated anti-CD14 clone My4 (No. 6603511, isotype: mouse IgG2b FITC), PE-conjugated anti-CD16 clone 3G8 (No. A07766, isotype: mouse IgG1 PE), PC5-conjugated anti-HLA-DR (No. PM 2659U, isotype: mouse IgG1 PC5), and APC-conjugated CD45 (No. IM2473, isotype: mouse IgG1APC). All antibodies and their respective isotype controls were purchased from Beckman Coulter, Krefeld, Germany.
  • 3Instrument Details All signals were acquired on a FACSCalibur flow cytometer (BD Biosciences, San Jose, CA). The instrument amplifier setting was calibrated monthly using Calibrite™3 beads and Calibrite™APC beads (Nos. 340486 and 340487, BD Biosciences). CellQuest software (version 3.2, 1998) was used to acquire and analyse the data.
  • 4Data Analysis 4.1. List-mode data file Measured parameters: FSC, SSC, FL1=FITC, FL2=PE, FL3=PC5, FL4=APC 4.2. Compensation: software compensation 4.3. Gating: as described below
Table  . 
Detectors/Amps ParamDetectorVoltageAmpGainMode
P1FSCE001.57Lin
P2SSC2651.00Log
P3FL15501.00Log
P4FL24251.00Log
P5FL37001.00Log
P6FL2-A 1.00Lin
P7FL4465 Log
Threshold
 Primary parameter:FSC
 Value:65
 Secondary parameter:FL4
 Value:169
Compensation
 FL1 – 0.6%FL2
 FL2 – 24%FL1
 FL2 – 0.0%FL3
 FL3 – 12.9%FL2
 FL3 – 0.0%FL4
 FL4 – 0.0%FL3

Flow Cytometry Gating Strategy

All signals were acquired on a FACSCalibur flow cytometer (BD Biosciences, San Jose, CA). The instrument amplifier setting was calibrated monthly using Calibrite™3 beads and Calibrite™APC beads (Nos. 340486 and 340487, BD Biosciences). CellQuest software (version 3.2, 1998) was used to acquire data.

First, the CD45-positive leucocytes were visualized in a histogram showing all fluorescence-4 (APC-positive) events. An acquisition threshold was set such that any unwanted events like CD45-negative platelets, dead cells, and debris are not recorded.

The monocytes were then defined by sequential gating on all CD45-positive leukocytes in light scatter plots, CD14 versus HLA-DR-staining and CD14 versus CD16 staining.

Using isotype controls, voltage and compensation the instrument was set such that the cells are adequately positioned in the dot plots. For direct determination of absolute numbers of cells, we used CountBright® absolute counting beads (Invitrogen, Karlsruhe, Germany).

At least 1,000 CD14+CD16++ events were acquired per sample. The number of absolute CD14+CD16++ monocytes were then calculated with reference to the flow count beads according to the following formula:

Absolute CD14+CD16++ monocytes (cells/μl) = absolute beads (beads/μl) × CD14+CD16++ monocyte events recorded bead divided by events recorded.

Statistics

For statistical analysis, we used the parametric paired single-sided Student's T test. For statistical significance the threshold below the calculated P value is chosen at the 0.05 level.

Results

Four-Color Single-Platform Method for Human Blood Monocyte Subsets

As a first step to this novel approach of monocyte subset determination, all CD45-positive leucocytes are visualized in a single color histogram showing all deep-red fluorescence-4 (FL4) events. An acquisition threshold was set such that any unwanted CD45-negative events like platelets, dead cells, and debris are not recorded at all. As shown in Figure 1A, the threshold is at channel 65 for the primary parameter FSC and at channel 169 for the secondary parameter FL4. The various peaks in this histogram represent granulocytes (a), lymphocytes (c), and monocytes (b). Peak “d” represents the absolute counting beads.

Figure 1.

Gating strategy for determination of CD14+CD16++ monocytes. (A) CD45 single color histogram, (B) dot plot of forward versus side scatter, (C) CD14 versus DR histogram, and (D) CD14 versus CD16 histogram. Whole blood was stained with fluorochrome-conjugated antibodies to CD45, CD14, CD16, and HLA-DR and samples were analyzed by flow cytometry after red cell lysis. (a) granulocytes, (b) monocytes, (c) lymphocytes, (d) beads, (e) HLA-DR-negative lymphocytes, (f) HLA-DR+ cells, (g) CD14+CD16++ monocytes, and (h) CD14++CD16 monocytes. Isotype control staining is shown in Figure S1.

All FL4 positive events in Figure 1A are then given in a forward scatter versus side scatter plot (Fig. 1B). Here gate “b” contains all monocytes and part of the lymphocyte population (c) since some of the monocytes, i.e., the CD14+CD16++ monocytes, which on average are somewhat smaller than the classical monocytes, tend to localize in the lymphocyte area. Gate “a” defines the granulocytes and gate “d” contains the CountBright beads for determination of the absolute count of the cell populations.

Figure 1C gives a dot plot for CD14 and HLA-DR containing all events from gate “b” (Fig. 1B). In Figure 1C, monocytes and some lymphocytes can be seen; there are monocytes strongly positive for CD14 with some expression of HLA-DR as well as cells weakly positive for CD14 with high HLA-DR signal. In addition, there are CD14-negative events that are either DR+ or DR. Gate “f” includes all DR-positive events and this covers the monocytes strongly and weakly positive for CD14 (Fig. 1C).

All events in gate “f” (Fig. 1C) are then displayed in the CD14 CD16 dot plot (Fig. 1D). In this figure, the two monocyte subpopulations can be defined. These are the CD14 weakly positive and CD16 strongly positive (CD14+CD16++) nonclassical monocytes (g) and the CD14 strongly positive and CD16-negative (CD14++CD16) classical monocytes (h).

With reference to the counting beads (d), the absolute number of the monocyte subsets can be determined as described in materials and methods. In this example, the CD14+CD16++ nonclassical monocytes account for 49 cells/μl, while the classical CD14++CD16+ classical monocytes are 274 cells/μl.

Exclusion of Other CD16-Positive Cell Types

The CD16 marker is also expressed by neutrophilic granulocytes and therefore these cells might contaminate the CD14+CD16++ monocytes when they happen to extend into the monocyte scatter gate. There are CD16 antibodies, which typically do not stain granulocytes and therefore such antibodies may be preferred for this assay. However, when granulocytes are activated then they increase their CD16 expression such that they can localize in the CD14+CD16++ gate (data not shown). We have used an antibody against the Fc-binding region of CD16 and this type of reagent strongly stains granulocytes. The expression is much stronger compared with the expression on monocytes. In Figure 2, we have gated on monocytes and in addition on granulocytes (a). These granulocytes are highlighted with a blue oval gate both in the scatter plot (A) and the CD14 CD16 plot (B). As can be seen in the two-color plot, the granulocytes localize above the CD14+CD16++ monocytes and there is minimal overlap of a few granulocytes into this monocyte gate. Therefore with this type of approach and given that the vast majority of granulocytes is excluded from the analysis based on scatter, the contamination by these cells is negligible when using this CD16 antibody.

Figure 2.

Dissection of neutrophils and CD14+CD16++ monocytes. Stained cells were analyzed with scatter gates around monocytes and granulocytes (a and b in A). The CD14 and CD16 histogram (B) demonstrates CD16 positive neutrophils (a) and CD16-negative eosinophils (i). One representative example of three. (a) granulocytes, (b) monocytes, (c) lymphocytes, (d) beads, (g) CD14+CD16++ monocytes, (h) CD14++CD16 monocytes, and (i) eosinophilic granulocytes.

There is another population of cells that becomes apparent when the granulocyte scatter gate is added to the monocyte gate. These events in the red gate “i” represent the CD16-negative eosinophilic granulocytes, which are also clearly separated from the monocytes (Fig. 2B).

CD16 is also expressed by natural killer (NK) cells. These cells may be picked up by the gating strategy in which the scatter gate for monocytes extends into the lymphocytes. To exclude these NK cells, we use staining for HLA-DR and gate on HLA-DR-positive events only as shown in Figure 1C. For demonstration of the necessity of this step, we have in Figure 3 included the HLA-DR-negative events in the CD14 CD16 plot (blue circle in Fig. 3A). As can be seen in the Fig. 3B, the HLA-DR-negative CD16-positive NK-cells now contaminate the CD14+CD16++ population. While the gate for determination of the nonclassical monocytes might be moved further to the right to exclude the NK cells, this would exclude at the same time a portion of the CD14 low monocytes. Therefore the exclusion of the NK cells based on the absence of HLA-DR-expression enables a much more accurate determination of the CD14+CD16++ monocytes.

Figure 3.

Dissection of NK cells and CD14+CD16++ monocytes. Stained cells were analyzed with light scatter gates around monocytes plus the upper right part of lymphocytes. Events in “e” and “f” (A) were gated and shown in the CD14 and CD16 histogram (B). Only when events in “e” are included, then CD16+ NK cells contaminate the CD14+CD16++ monocyte gate. When the cells in “e” are excluded as done in the standard procedure as shown in Figure 1, then the CD14+CD16++ monocytes are not contaminated by NK cells. One representative example of three. (e) HLA-DR-negative lymphocytes including NK cells, (f) HLA-DR+ cells, (g) CD14+CD16++ monocytes, and (h) CD14++CD16 monocytes. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Intra-and Inter-Assay Variation

For determination of intra-assay variation, we obtained blood from a single individual, stained at once and performed 10 acquisitions with 1,000 CD14+CD16++ events per run. This test was done on three independent individuals. The average intra-assay CV of these three samples was 4.1%. For the CD14++ monocytes, the average intra-assay CV of was 3.0%.

The inter-assay variation was studied in blood samples that were split into 10 samples each, which were stained independently and 1,000 CD14+CD16++ monocytes were acquired each. This test was done on blood samples from four individuals and the average inter-assay CV of these was 8.5%. For the CD14++ monocytes, the average inter-assay CV was 7.4%.

Dependence on Age and Gender

To analyze the age dependence of the CD14+CD16++ monocyte numbers, we studied blood samples from healthy volunteers in age groups 18–30, 31–40, 41–50, and 51–60, with 10 individuals per group, each consisting of five males and five females. No age dependence was evident in this analysis (P > 0.72, regression analysis). We noted however a lower average value for the CD14+CD16++ monocytes in females (45.4 ± 13.5 cells/μl) when compared with males (59.1 ± 20.3 cells/μl) (P = 0.017, two-sided test) when all age groups were combined. The mean values per age group for males and females are given in Figure S2. These data show lower numbers for women of all age groups. For total monocytes, females also had significantly lower values (352.0 ± 93.3 cells/μl versus 420.0 ± 111.9 cells/μl, P = 0.044) while for CD14++CD16 classical monocytes, there was a trend towards lower values in females but this was not significant (306.6 ± 89.0 cells/μl versus 360.7 ± 106.9 cells/μl, P = 0.09).

CD14+CD16++ Monocytes and Excessive Exercise

Previous studies have shown that the nonclassical monocytes increase with exercise and this is apparently based on their mobilization from the marginal pool (22). Using the novel four-color assay, we have tried to confirm this finding. One minute of exercise on a home-trainer bike at 400 W did in fact lead to an increase of the CD14+CD16++ monocytes from 41 to 133 cells/μl in the example in Figures 4A and 4B. In Figure 4C, the increase of these cells by exercise is demonstrated for all three cases of this part of the study. The two females performed exercise for 1 min at 200 W only.

Figure 4.

Effect of exercise on CD14+CD16++ monocyte numbers. Dot plot example before (A) and after exercise (B), and summary of all three participants (C). Cells were taken before and immediately after 1 min of exercise at 400 W from a male volunteer (square and solid line, represents the example in A + B) and from two female volunteers before and after 1 min at 200 W (circle). While the classical monocytes increased by about two-fold, the average rise in the CD14+CD16++ monocytes was four fold. (g) CD14+CD16++ monocytes and (h) CD14++CD16 monocytes. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

CD14+CD16++ Monocytes Mobilization in Males and Females

The lower absolute count of CD14+CD16++ monocytes in females as noted above may be due to a lower total number of these cells in blood or it may be due to a higher degree of sequestration of these cells in the marginal pool. To test this, we studied the response to exercise at 200 W until exhaustion in four females with low CD14+CD16++ monocytes when compared with four males with high CD14+CD16++ monocytes. While the women responded to exercise with a strong increase to 105 ± 11 cells/μl (Fig. 5B), they did not achieve the postexercise level of CD14+CD16++ monocytes found in males (160 ± 51 cells/μl, Fig. 5A). These findings argue that the lower number of nonclassical monocytes in females is not due to a more pronounced sequestration of CD14+CD16++ monocytes to the marginal pool, from which these cells can be mobilized by exercise. They rather support the conclusion that females have lower total numbers of CD14+CD16++ monocytes in blood.

Figure 5.

Effect of exercise on CD14+CD16++ monocyte numbers in males and females. Blood was taken from four males (A) with high CD14+CD16++ monocyte numbers and from four females (B) with low CD14+CD16++ monocyte numbers before and after exercise to exhaustion at 200 W. In males, the absolute number increased from 78 ± 10 cells/μl to 160 ± 51 cells/μl, while in females there was an increase from 46 ± 15 cells/μl to 105 ± 11 cells/μl. The difference between the postexercise levels is significant at P < 0.05.

CD14+CD16++ Monocytes and Glucocorticoid Therapy

Fingerle et al. first demonstrated that high dose glucocorticoid therapy can deplete the CD14+CD16++ nonclassical monocytes (24) and additional studies have shown that this is by induction of apoptosis (23). We have readdressed this issue with the four-color approach in patients treated with different doses of prednisolone for inflammatory diseases. The example in Figures 6A and 6B demonstrates the pronounced depletion from 52 to 5 cells/μl within 6 days of therapy at 40 mg/day. This type of depletion was seen in three additional cases including one case treated with 500 mg/day, one with 90–45 mg/day and another one on 40 mg prednisolone/day (Fig. 6C). These data show that GCs can effectively deplete the CD14+CD16++ monocytes also at low doses of the drug.

Figure 6.

Effect of glucocorticoid therapy on CD14+CD16++ monocyte numbers. An example of a FACS histogram before (A) and after (B) 6 days of therapy with prednisolone at 40 mg/day in a case of bronchiolitis obliterans organizing pneumonia (BOOP). (g) CD14+CD16++ monocytes and (h) CD14++CD16 monocytes. (C) Summary of four cases with prednisolone therapy. Circle dotted line: female age 65, BOOP, therapy 40 mg/d before and on day 6, represents the example in A; square solid line: male, age 87, glomerulonephritis, therapy 40 mg/d before and on day 8; circle dashed line: female, age 71, polymyalgia, therapy 90 mg/d tapered to 45 mg/d before and on day 11; square dashed and dotted line: male, age 68, glomerulosclerosis, therapy 500mg on day 1, 250 mg/d for 2 days, 5mg/d for 2 days, before and on day 5. Classical monocytes showed a 1.3-fold decrease in this study while the nonclassical CD14+CD16++ monocytes decreased eight fold. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Discussion

While monocytes in the early days were defined based on morphology, more recent tests use flow cytometry. This approach revealed the existence of a previously unrecognized population of nonclassical monocytes which account for about 10% of all monocytes (2). The exact determination of the latter cells can be difficult at times because of spill-over of non-monocytes into the scatter and fluorescence gates.

We now describe a four-color approach for determination of the classical and nonclassical monocyte subsets using a single-platform approach. The traditional two-platform approach determines percentages of a given subpopulation in one aliquot of the sample and the absolute numbers of all leukocytes in another aliquot of the sample. The calculation of the absolute number of a leukocyte subpopulation from these values adds an additional element of imprecision and can lead to a higher CV.

The acquisition strategy used herein includes a threshold on CD45 staining such that any nonleukocytes are not recorded at all. The assay takes care to exclude NK cells based on their lack of HLA-DR expression. Also, granulocytes are excluded via scatter and via the strong neutrophil staining with the 3G8 antibody and the lack of eosinophil staining with the same antibody. With these measures, we can demonstrate good reproducibility for determination of the nonclassical monocytes. There is the possibility, however, that a few eosinophils may be picked up in the gate of the nonclassical CD16 positive monocytes under conditions of inflammation since IFNgamma can induce CD16 expression in eosinophils (28) and in allergy these cells may well express CD16 (29).

Faucher et al. have developed a five-color assay for a white count differential that looks at a broad array of leukocyte populations including monocyte subpopulations (30). This assay also uses the 3G8 antibody to CD16. However, CD36 is used instead of CD14 for definition of monocytes and it appears that there is overlap between the CD36 low CD16+ monocytes and the cytotoxic lymphocytes in that assay. Still, the assay by Faucher et al. may be useful in studies, in which the entire spectrum of leukocytes is to be assessed since the assay is able to determine various lymphocyte subsets at the same time. By contrast, the assay we describe herein focuses on monocytes and can define their subsets with high precision.

Using excessive exercise for 1 min at 400 W on a home-trainer bike, we found a more than three-fold increase in the absolute number of the nonclassical CD14+CD16++ monocytes (Fig. 4). These findings are consistent with earlier work, in which we provided evidence for a role for catecholamines in what appears to be a mobilization from the marginal pool (22). A role for stress hormones in this response is supported by the finding that infusion of adrenaline can also lead to an increase in the nonclassical monocytes (31, 32). These data demonstrate that it is of utmost importance to ensure a period of stress-free rest, if the basal level of CD14+CD16++ monocytes is to be determined correctly.

An important novel finding when using our assay is that there is a clear gender effect, with women having a clearly lower absolute number of the CD14+CD16++ monocytes. Inaddition, there were lower values for the classical CD14++CD16 monocytes, albeit not significant. When adding up the values for the two monocyte subsets, then the absolute number of total monocytes was significantly lower in females in our study. Such a gender effect with respect to monocytes has not been reported before.

Tollerud et al. (33), for instance, found no difference in CD14 monocytes between males and females but that study analyzed the percentage of monocytes among all mononuclear cells only and the cells were first purified by density-gradient separation that may introduce much more variability compared with the direct lyse-no-wash approach used in our study. The study by Ben-Hur et al. (34) using a flow cytometry approach provided some indirect evidence for lower numbers in women, since they reported that menopause increases the absolute number of monocytes and the estrogen replacement therapy will reduce their number. The latter study suggests that the lower number of both monocyte subsets in women as detected in our study may be due to higher estrogen levels compared with men. Some women of the age group 51–60 may be in postmenopause and a rise in the number of CD14+CD16++ monocytes might have occurred. As shown in Figure S2, the average value for the five women in this group still was lower than in men. We have no information on the menopausal status nor on any hormone replacement therapy, but we speculate that sufficient estrogen was available in these women. A separate prospective study is required to study the impact of menopause and estrogen levels on CD14+CD16++ monocyte numbers.

Estrogen may cause an effect on monocyte numbers in blood by various routes including reduced influx into blood or increased sequestration into the marginal pool or increased migration into tissue. We have asked whether in women the low levels in blood at rest may be due to a stronger sequestration of the cells in the marginal pool. We have demonstrated earlier (22) and in this report that excessive exercise will increase the number of CD14+CD16++ monocytes. We therefore have tested whether in women with low counts for the nonclassical monocytes the numbers of these cells reach the level seen in males when both were subjected to exercise. When females mobilized CD14+CD16++ nonclassical monocytes efficiently, they did not reach the postexercise absolute count seen in males. These data are consistent with the concept that women have a lower total number of CD14+CD16++ monocytes in both the central and the marginal pool in blood.

We also can confirm with the novel assay a depletion of the nonclassical monocytes following glucocorticoid therapy. This selective depletion was first demonstrated in patients with multiple sclerosis and then studied in more detail in healthy volunteers infused with repeated doses of methylprednisolone at 250 mg/day (23, 24). A depletion of these cells was also seen in glucocorticoid-treated patients with vasculitis (35) and with rheumatoid arthritis (17). High doses used in the early studies are not required for a pronounced depletion of the nonclassical monocytes since a depletion can be achieved at 30 mg of prednisolone/day (25). Using the novel assay, we can confirm herein the consistent depletion of these cells at low doses of glucocorticoids (Fig. 6).

Taken together, we present a novel approach for determination of human blood monocyte subsets that can define monocyte subsets with high precision and therefore will be useful for analysis of these cells in clinical settings including inflammation and anti-inflammatory therapy.

Acknowledgements

We thank Dr. K. Häußinger, Asklepios-Klinik, Gauting, Germany for provision of patient samples.

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