Increased CD64 expression on polymorphonuclear neutrophils indicates infectious complications following solid organ transplantation

Abstract

The aim of this study was to evaluate the diagnostic value of monitoring CD64 antigen upregulation on polymorphonuclear neutrophils (PMN) for the identification of infectious complications in the postoperative course of solid organ transplanted patients. Twenty-five kidney, 13 liver, and four pancreas–kidney transplanted patients were included. Beginning with preoperative values up to postoperative values after 3 months for each patient, the PMN CD64 Index, HLA-DR on monocytes, NKp44⁺ NK and NK/T cells, CXCR3⁺ NK cells, CXCR3⁺ T helper cells, CXCR3⁺ NK/T cells, and CD4/CD8 ratio were measured by flow cytometry. Subsequently they were correlated with confirmed postoperative complications. Measuring the PMN CD64 Index reached a sensitivity of 89% and a specificity of 65% in the detection of infectious complications. Concerning this matter, it was a significantly better marker than all other included parameters except CXCR3⁺ NK/T cells. In contrast, according to our results the PMN CD64 Index has no diagnostic relevance in detection of rejections. The combination of included parameters showed no improved diagnostic value. Due to its high sensitivity and specificity for infectious complications CD64 on PMN could be proven a very good indicator in evaluating suspected infectious complications in the postoperative course of transplanted patients. © 2011 International Society for Advancement of Cytometry.

In Germany, since the first renal transplantation in 1963 and first liver transplantation in 1969, organ substitution by transplantation is an established method of medical treatment, which is performed in about 50 clinical centers. On average, 11 solid organs are transplanted every day. In 2010, there were 2,094 renal, 1,049 liver and 142 combined pancreas–kidney transplantations from postmortem donors in Germany registered by Eurotransplant.

In most cases of terminal organ failure, transplantation seems to be the only way to keep patients alive and preserve their quality of life. Although there are increasing numbers of transplantations, there is still a strong need for transplantable organs.

According to Eurotransplant's yearly statistics, in Germany in December 2010, 7,515 patients were waiting for a kidney, 2,087 for a liver, and 269 for a kidney-pancreas transplantation.

Those facts show clearly the importance of careful pre- and postoperative treatment of the few available organs.

Postoperatively, it is important to avoid organ loss caused by several serious complications especially infections (1) or rejections (2) which can even lead to patient death. Therefore, an early and precise detection of and, furthermore, the discrimination between complications is very important. It is essential for further adjusted treatment, which is comprised of a well balanced course of anti-inflammatory treatment, antibiosis and continuous immunosuppression.

The gold standard in diagnostic evaluation of suspected rejection of a solid organ transplant is organ biopsy (2, 3) and use of the Banff schema (4–6). Due to its invasiveness, this method can cause complications (3, 7).

There remains a lack of specific parameters for non-invasive diagnostic in transplanted patients. Recently, several trials showed potentially valuable conventional markers (ALT, cholesterol, prothrombin time, soluble IL-2R) (7, 8) and cellular markers (eosinophils, lymphocytes) for diagnosing rejection. In particular, the identification and diagnostic use of T cell subtypes is currently a widely discussed approach (7, 9, 10, 11). In clinical practice, a combination of broad panels is necessary to determine complications (7, 8).

Other investigated ways for the recognition of rejection crisis are the detection of anti-HLA antibodies or soluble CD30 (9, 11, 12–14), as well as the detection of the complement split product C4d (15) or monitoring Neopterin (16) or gamma glutamyl transferase (17). Additional explored ways of postoperative transplant monitoring are the sequential monitoring of peripheral blood mononuclear cells (PBMC) to detect changed chemokine receptor/ligand gene expression (18–20) and the measurement of urinary mRNA expression of various immune molecules (21).

Except for virological infections (22, 23), the parameters used to detect infectious complications after transplantation are HLA-DR presented on monocytes (24–26) and procalcitonin (PCT) (27–31). Nevertheless there is still a lack of sensitivity and specificity.

A recently postulated parameter with high sensitivity and specificity for detecting infectious situations is CD64 expression on polymorphonuclear neutrophils (PMN).

In our trial, we ascertained the PMN CD64 Index by using a Leuko64™ kit (32–34), which is based on absolute quantitation of CD64 expression on neutrophils. We correlated the PMN CD64 Index to confirmed complications of transplanted patients.

Until now, CD64 expression on granulocytes has not been examined in solid organ transplanted patients. Due to postoperative iatrogenic immunosuppression and therefore a high risk of infectious complications, they represent a very specific collective with particular challenges related to diagnosis and treatment.

There have been several studies showing the superior diagnostic value of CD64 expression on granulocytes as compared with established markers, such as CRP, leukocyte count [white blood cell (WBC) count], platelet count, ESR, PCT, absolute PMN count, HLA-DR on monocytes, immature/total neutrophil ratio, band percentage, absolute band count, left shift determinations and IL-6, and compared with non-established markers like IL-8, IL-10, CD64⁺ monocytes, total CD2⁺ T cell count, CD4⁺ lymphocytes, CD25⁺ lymphocytes and CD45RO⁺ lymphocytes, as well as CD11b⁺ (CR3⁺) PMN, CD16⁺ PMN, CD18⁺ PMN, CD23⁺ PMN, and CD32⁺ PMN (32, 33, 35–41).

With the objective to evaluate other potentially useful parameters which may lead to a superior diagnostic after transplantation and compare them with the PMN CD64 Index, we screened conventional markers for infection (WBC, CRP, and HLA-DR presented on monocytes) on the one hand, and on the other hand we included parameters following a practice-oriented concept of immunological monitoring after transplantation (42, 43). This monitoring process focuses on the flow cytometric identification of natural killer (NK) cells and natural killer T cells (NK/T cells). In particular these parameters were CD4/CD8 ratio, NKp44⁺ NK and NK/T cells, CXCR3⁺ NK cells, CXCR3⁺ T helper cells, and CXCR3⁺ NK/T cells. In addition to the PMN CD64 Index, they were also correlated with confirmed complications after transplantation.

Summarized, the central questions for our trial have been:

• 1
  Is the PMN CD64 Index measurable after transplantation?
• 2
  Is the predefined cut-off (1.5) for the PMN CD64 Index useful for the detection of infection in transplanted patients?
• 3
  Is an elevated PMN CD64 Index specific for infection in transplanted patients?
• 4
  Is the PMN CD64 Index a more specific and sensitive marker to define infection in the posttransplantation course than conventional markers or other cytometric markers of immune cells?
• 5
  Does a combination of the PMN CD64 Index with another immune marker improve diagnostic value for detection of infection in transplanted patients? Is such a combination reasonable?

MATERIALS AND METHODS

Patients

This study includes 42 patients transplanted in the transplant centre of the Universität Leipzig. The transplants occurred between January and October 2007. The study included 25 kidney transplanted, 13 liver transplanted, and four pancreas–kidney transplanted patients. The age of the patients ranged from 20 to 69 (median 50 years).

Every patient received immediately postoperative an inital dose of 500 mg Urbason i.v., the second day a dose of 250 mg and the third day, 125 mg. The additional immunosuppression was performed by Prednisolon, calcineurin-inhibitor Tacrolimus, and Mycophenolate mofetil.

Postoperatively one patient received instead of Tacrolimus initially Cyclosporin A. This patient was routinely switched to Tacrolimus after 10 days by surgeon. Mycophenolate mofetil was applied in doses of 2 × 0.5–1 g per day. Doses of Tacrolimus and Cyclosporin were applied plasma drug level controlled and adapted in situations of adverse effects of immunosuppression or clinical signs of acute transplant rejection. For induction therapy after liver transplantation, one patient with autoimmune hepatitis received monoclonal antibody Daclizumab additionally to Prednisolon, Tacrolimus and Mycophenolate mofetil.

Definition of Complications

Complications after transplantation were divided into infectious complications, rejections, postischemic transplant-pancreatitis, surgical and cardiac complications. Complications were defined by synopsis of clinical indicators like body temperature (T > 38°C or <36°C), tachycardia (f > 90/min), tachypnoeia (f > 20/min), hyperventilation (PaCO₂ < 4,3 kPa), arterial hypotension (systolic arterial blood pressure < 90 mm Hg), hypoxia (PaO₂ < 10 kPa) and new signs of organ failure (ascites, jaundice, diuresis < 0,5 ml/kg body weight per hour, reduced vigilance, changes of body weight ±3 kg/day).

Infectious complications were confirmed by positive microbiological culture results from blood samples, smears, or urine. Except for two cases, all infectious complications were confirmed by documented positive microbiological culture results. Because of clear clinical signs, massive increased inflammation parameters, and morphologic correlates (abscess), those two complications were also supposed to be by infectious cause. Clinical improvement under appropriate antibiotic treatment showed further evidence that these suspected cases were not misclassified.

Rejections were basically diagnosed by histologic evaluation of graft biopsies, clinical signs (ascites, jaundice) and laboratory tests (ALT, AST, creatinine). Further evidence of suspected rejections was the improvement of symptoms under immunosuppressive treatment. All patients with suspected rejection received a bolus of 500 mg/day Methylprednisolon for 3 days.

Study Design

The study was performed as a prospective study including consecutively all transplanted patients.

The protocol was approved by the Ethics Committee of the Medical Faculty of the Universtiät Leipzig (Permit Number: 361).

The PMN CD64 Index as well as CRP, WBC, HLA-DR on monocytes, CD4/CD8 ratio, NKp44⁺ NK and NK/T cells, CXCR3⁺ NK cells, CXCR3 T helper cells, and CXCR3 NK/T cells were measured directly preoperatively as well as on the first, third, seventh, tenth, and fourteenth day postoperatively. They were measured again after 3 and 4 weeks and after 3 months resulting in a total of 310 blood samples. Afterwards we correlated the diagnostic parameters under examination to clinical signs suggestive of potential complications during posttransplant patient progress.

Laboratory Methods

Referring to total lymphocyte count, NK cells are defined as the CD56⁺CD3^- cell fraction, NK/T cells as the CD56⁺CD3⁺ cell fraction (=large granular lymphocytes = LGL cells) and T helper cells as the CD4⁺CD3⁺ cell fraction. NKp44⁺ NK and NK/T cells are defined as the CD56⁺ cell fraction.

After collecting blood samples, the measurement of CD64 expression on neutrophils was performed by quantitative flow cytometry on FACScalibur (BD Biosciences, San Jose, CA) using a Leuko64™ kit, a whole-blood lysed no-wash method containing internal calibration beads for quantification. The kit is produced by Trillium Diagnostic, LLC, Brewer, Maine.

Briefly, 50 μl of anti-coagulated blood samples were stained with a mixture of CD64-fluorescein-isothiocyanate (FITC, clone 22, clone 32.2) and CD163-phycoerythrin (PE, clone Mac2-158) and incubated for 10 min at room temperature. Erythrocytes were lysed by Trillium Lyse (contains ammonium chloride and purified bovine serum albumin) for 15 min. After adding 5 μl of Leuko64 beads (contains polystyrene beads labeled with StarFire Red and FITC) samples were analyzed on FACScalibur.

The beads were used for instrument calibration and standardization of the leukocyte CD64 and CD163 expression. The automated proprietary software (Leuko64™ QuantiCALC, contributed by Verity Software House, Topsham, Maine and Trillium Diagnostic, LLC, Brewer, Maine—version number: 1.2) for flow cytometric listmode data analysis uses an iterative cluster finding algorithm to locate lymphocytes, monocytes, and granulocytes depending on SSC Height and CD163 PE FL-2 Height. The assay was kindly provided by IQ Products.

CD64 Index for each population is calculated by dividing median value of CD64 FITC by median value of FITC FL1 Height calibration beads. The granulocyte specific index is called the PMN CD64 Index (33).

The performance and specificity of reagents contained in the Leuko64 kit are tested using Trillium's in-house quality control methods. Manufacturing of this product is done using quality system and manufacturing production guidelines in compliance with FDA QSR and ISO 13485:2003. The manufacturer describes a safe reproducibility (CV < 5%) for the use of the automated software.

Normally, CD64 expression on granulocytes is low with a PMN CD64 Index of lower than 1.5. Monocytes serve as an internal positive control (monocytes normally have moderate levels of CD64 with an index higher than 3.0) and lymphocytes serve as an internal negative control (index lower than 1.0). The gating strategy is shown in Figure 1a. Examples of Fcs-files have been uploaded (Supporting Information).

Figure 1. (a). Dot plot of CD64 expression on PMN. For instrument setup, first, it is necessary to exclude the calibration beads by using StarFireRed (>670 nm)-Height (FL3-H) and CD163 PE (585/42 nm)-Height (FL2-H) (A). Then, the leukocyte subpopulations (lymphocytes, granulocytes and monocytes) must be defined by SSC (488/10 nm)-Height and CD163 PE (585/42nm)-Height (FL2-H) (B). The software relates the median of CD64 FITC (530/30 nm)-Height (FL1-H) expression on granulocytes to the calibration beads, which results in the PMN CD64 Index. Example 1 (C, D, E) and example 2 (F, G, H) show the fluorescence of CD64 FITC on granulocytes, lymphocytes and monocytes in relation to beads of blood sample (light grey area: beads, dark grey area: cells). Example 1 shows a representative sample (from one subject) with a low PMN CD64 Index. Example 2 is representative for a high PMN CD64 Index. Lymphocytes serve as an internal negative control (CD64 negative) (D, G) and the software will alert the user if the lymphocyte gate has a CD64 Index greater than 1.00. Monocytes serve as an internal positive control (monocytes normally have moderate levels of CD64) (E, H) and the software will alert the user if the monocyte gate has a CD64 Index less than 3.00, which may indicate a need for gate adjustment or a failure to add proper antibody volume. (b). Dot plot of NKp44 expression on NK and NK/T cells. Lymphocytes were gated as cells with low side scatter and forward scatter values (A). NK/T cells were defined as lymphocytes and by expression of CD56 and CD3, NK cells show no expression of CD3 (B). C) shows isotype control, and D) NKp44 expression on NK and NK/T cells (UL = 3.76%). (UR = upper right, UL = upper left, LR = lower right, LL = lower left). (c). Gating strategy for CXCR3 expression on NK, NK/T, and T helper cells. NK, NK/T, and T helper cells were defined as lymphocytes which were gated as cells with low side scatter and forward scatter values (A, R1). T helper cells were defined as CD3 and CD4 positive lymphocytes (B, C, R3). NK cells were defined as lymphocytes presenting expression of CD56 (D, R4) and NK/T cells as lymphocytes presenting expression of CD56 and CD3 (D, R5). Isotype controls for T helper cells, NK and NK/T are presented on the left side (E, G, I). CXCR3 is plotted against T helper cells (F, UR = 32.22%). Because of gating strategy (first lymphocytes, then CD3 and then CD4), only T helper cells are shown in this plot. Further, CXCR3 is plotted against NK cells (H, UR = 27.19%) and against NK/T cells (J, UR = 48.28%). (d). Dot plot of gating strategy for HLA-DR expression on monocytes. Monocytes are defined as CD14+ cells with low side scatter (A, R2). Isotype control is presented in the middle dot plot (B). HLA-DR expression is plotted against monocytes (C, UR = 99.74%). (e). Dot plot of gating strategy for CD4/CD8 ratio. Lymphocytes were gated as cells with low side scatter and forward scatter values (A, R1)). T cells were defined as lymphocytes and by expression of CD3 (B, R6). In this gate CD4+ cells were plotted against CD8+ cells (C). Ratio is calculated by dividing CD4 by CD8 (LR /UL). In this example ratio is 2.9 (67.47 /23.19).

Subpopulations of lymphocytes and monocytes were analyzed as relative numbers of lymphocytes and monocytes,respectively, on the FACScalibur flow cytometer after incubation with the respective monoclonal, fluorescent-marked, and anti-human antibodies.

Cells were labeled with antibodies against CD3 (FITC; clone SK7), CD8 (PE; clone SK1), CD45 (Peridinin Chlorophyll Protein Complex (PerCP); clone 2D1), CD4 (allophycocyanin (APC); clone SK3) (5 μl, BD Multitest, BD Biosciences) to estimate T helper cells and cytotoxic T cells (CD8⁺CD3⁺) and against CD3 (FITC; clone SK7), CD16/56 (PE; clone B73.1, clone NCAM16.2), CD45 (PerCP; clone 2D1), CD19 (APC; clone SJ25C1) (5 μl, BD Multitest, BD Biosciences) to estimate NK cells and B cells (CD19⁺).

CD14 (FITC; 2.5 μl, clone M5E2) and HLA-DR (APC; 2.5 μl, clone L234, BD Biosciences) were used to describe HLA-DR⁺ monocytes; and CD3 (FITC; 2.5 μl, clone UCHT1, Immunotech), CXCR3 (PE; 2.5 μl, clone 1C6/CXR3, BD Biosciences), CD4 (phycoerythrin-cyanin 5 (PC5); 2.5 μl, clone 13B8.2, Immunotech) and CD56 (APC; 2.5 μl, clone N901, Immunotech) were used to detect CXCR3⁺ NK cells, CXCR3⁺ NK/T cells and CXCR3⁺ T helper cells.

In addition, cells were labeled with CD3 (FITC; 2.5 μl, clone UCHT1), NKp44 (PE; 2.5 μl, clone Z231), CD16 (phycoerythrin-cyanin 7 (PC7); 2.5 μl, clone 3G8), CD56 (APC; 2.5 μl, clone N901, Immunotech) to detect NKp44⁺ NK and NK/T cells (CD56⁺ cells). Iso-type controls (2.5 μl, mouse IgG1-PE, clone 679.1Mc7, Immunotech) were performed for CXCR3⁺ subsets and for NKp44⁺ NK and NK/T cells (CD56⁺ cells).

Cell labeling (100 μl EDTA whole blood) was carried out using monoclonal antibodies at room temperature for 15 min. The monoclonal antibodies were tittered before use and used at a saturating concentration.

After erythrocyte lysis (FACS Lysing Solution, BD Biosciences), samples were washed with PBS and fixed with 1% formaldehyde solution. Isotype-identical monoclonal antibodies served as controls. Flow Cytometry Data Acquisition and Analysis was Performed using CellQuest Pro Software (BD Biosciences, Version 4.02).

Examples of the gating strategy for NKp44 expression on NK and NK/T cells, CXCR3 expression on NK, NK/T, and T helper cells, HLA-DR expression on monocytes and CD4/CD8 ratio are shown in Figures 1b–1e. For gating and visualization of data, partly base-10 log transformation was performed. Optical configuration of FACScalibur flow cytometer is summarized in Tab. 1.

Generally, single lymphocytes have been gated. In a few cases, we found lymphocyte aggregates in low amounts. Those were not excluded.

CRP and WBC count were measured by central laboratory of the Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, Universitätsklinikum Leipzig AöR. CRP was measured by using a particle enhanced turbidimetric immunoassay (PETIA) (800/570 nm) with a Cobas 6000 analyzer (Roche Diagnostics, Mannheim, Germany).

WBC count was measured by electric impedance method using the Sysmex XE-2100 automated blood cell counter (Sysmex, Kobe, Japan).

Statistics

For most immunologic parameters, there is a defined range of normal values. Hence, we analyzed three different pathologic situations for such parameters—below, above, and outside of the normal range. Each pathologic situation serves as a diagnostic test for rejection or infection in the following descriptions. For patients with no event (infection, rejection), the maximum of the PMN CD64 Index measurements was used as the diagnostic criterion while the other tests were treated as (false) positive, if they were positive at least once during the observation period. For events, all measurements taken at most a week before the event were considered. Again, the maximum measurement of the PMN CD64 Index was taken as the diagnostic criterion and the other tests were treated as positive, if positive at least once during this period. The data are presented in box plots (Figs. 2 and 3, Supporting Information Fig. 1)

Figure 2. The course of measured PMN CD64 Indices in patients without complication (a) and patients with complications (b). The lower border of each box indicates the 25th percentile, the line within each box marks the median and the upper line indicates the 75th percentile. Lines (whiskers) over and below box show the 90th and 10th percentiles. The box is only available if there are enough data for a given time point. Points are outliers. In both graphs, the course of the PMN CD64 index after transplantation appears as a chraracteristic kinetic with low PMN CD64 Indices before transplantation (median < 1.0). In both groups, we see a maximum increase on the second postoperative day, followed by decrease in further course. In the group without complications the median PMN CD64 Index never appears higher than the cut-off 1.5.

Figure 3. Organ related early course of the PMN CD64 Index. Liver transplanted patients show a moderate increase during the first postoperative days, renal transplantation leads to a mild increase and after pancreas–kidney transplantation, the PMN CD64 Index strongly increases immediately.

The diagnostic power of the PMN CD64 Index to detect infection or graft rejection was assessed and compared with the other parameters using receiver operating characteristics (ROC), which is visualized in Figure 4.

Figure 4. Receiver Operating Characteristic (ROC) curve for the PMN CD64 Index for detection of infectious complications (a) and rejections (b). The receiver operating characteristic plots sensitivity and 1-specificity of the PMN CD64 Index in dependence on its cut-off value. It is visualized in the receiver operating characteristic curve (+), which illustrates several PMN CD64 Index cut-off values. The used cut-off is marked as a point in the graph. Each point on the ROC plot represents a sensitivity/specificity pair corresponding to a particular decision threshold. A test with perfect discrimination has an ROC plot that passes through the upper left corner or coordinate (0,1) [100% sensitivity (no false negatives), 100% specificity (no false positives)]. Therefore the closer the ROC plot is to the upper left corner, the higher the overall accuracy of the test (44,45). Other tests were presented at the point of the used cut-off, which results in the corresponding sensitivity and specificity. Used cut-offs/ reference ranges: CRP > 5 mg/l, WBC > 9 × 10⁹/l, HLADR+ monocytes <90%, CD4/CD8 ratio 0.9–2.8, CXCR3+ T helper cells 29–50%, CXCR3+ NK/T cells 55–85%, CXCR3+ NK cells 28–52%, NKp44+ NK and NK/T cells 0.7–3.1%. Nonestablished parameters' reference ranges were provided by the laboratory of the Institute of Clinical Immunology, Universitätsklinikum Leipzig. The diagonal line (#) between (0, 0) and (1, 1) (y = x), has an area under the curve (AUC) of less than 0.5, which means that parameters with values situated on the line would result in a completely random guess. With sensitivity of 0.9 and specificity of 0.6 for the detection of infectious complications in transplanted patients, the PMN CD64 Index was superior to other markers except CXCR3+ NK/T cells. These differences were significant. For the detection of rejections, the PMN CD64 Index shows only poor accuracy, the diagnostic value is negligible.

For the analyses, we summarized all types of surgery to obtain a sufficiently high number of events. Measurements at day 1 or 2 after surgery were discarded from the analysis to exclude effects due to postoperative trauma.

Based on these definitions, we determined the ROC for the PMN CD64 Index. The area under the curve and its confidence interval has been estimated using a method of Qin and Hotilovac (46). We compared the diagnostic power of the PMN CD64 Index with the other tests by comparing sensitivity or specificity for specific cut-offs of the PMN CD64 Index using exact Fisher tests. The PMN CD64 Index was considered to be superior in comparison with another test if either the sensitivity is significantly greater with the same specificity or the specificity is significantly greater with the same sensitivity as the other test. Finally, the Youden Index, which is sensitivity+specificity-1, was calculated for the proposed cut-off for the PMN CD64 Index and the other diagnostic tests as well. Furthermore, combinations of the PMN CD64 Index with other tests were analyzed.

RESULTS

In the intra-assay, the Leuko64™ kit used provides a coefficient of variation (CV) of 4.6% for detecting PMN CD64 Index (Supporting Information Table 1). In the observed population of solid organ transplanted patients, the PMN CD64 Index is measurable preoperative as well as postoperative as shown in Figure 2. The preoperative blood samples show organ-specific differences concerning the PMN CD64 Index as illustrated in Figure 3. Statistic significance is shown in the Supporting Information Table 2.

The available values present a kinetic in the course of the PMN CD64 Index which features low values before transplantation and increased values postoperatively, especially on day 1 and day 2. Statistic significance is shown in the Supporting Information Table 3a. In further course, there is again a decrease (Supporting Information Table 3b).

In the group of patients transplanted because of renal shutdown (n = 25), no preoperatively measured value was higher than 1.5. In 91% of these patients, we measured a value lower than or equal to 1.

In the group with hepatic failure (n = 13), we observed only 7 of 13 patients with a preoperative PMN CD64 Index below 1 (53.8%). All values were below 1.5.

In patients designated for a combined transplantation of kidney and pancreas (n = 4), all preoperative values were below the cut-off of <1 (100%).

In each patient group, we noted postoperative increased values for the PMN CD64 Index. With respect to the first two postoperative days, we have to assert that the PMN CD64 Index also presents organ-specific differences in this time period.

Liver transplanted patients show increased values immediately postoperative. Within the first 2 days all blood samples present a PMN CD64 Index higher than 1, five of them are higher than 1.5. The values stayed elevated during next 3 days followed by a descent.

In the kidney transplanted group, the increase of the PMN CD64 Index occurred delayed. Within the first two postoperative days only 37.5% (9 of 24) showed values higher than 1. Five of those 9 were moderately elevated and still beneath 1.5. The highest average values were reached on day 3–5.

All patients with a combined kidney-pancreas transplant showed postoperative values higher than 1.5. For an overview see Table 2. The patient receiving initially Cyclosporin A instead of Tacrolimus suffered renal transplant rejection 7 days after transplantation. PMN CD64 Index was elevated on day 7 (1.91). In further course there was another elevation of PMN CD64 Index on day 28 (2.39) without appearance of any complication, neither infection or rejection.1

Table 1. Optical configuration used for measuring of immunological markers by fluorescence activated cell sorter (FACScalibur; BD Bioscience)

Excitation laser line	Fluorochrome	EXCITATION- maximum (nm)	Emission- maximum (nm)	Filter (nm)	Fluorescence channel
Argon 488 nm	Fluorescein Isothiocyanate (FITC)	495	525	530/30	FL-1/P3
	Phycoerythrin (PE)	488	578	585/42	FL-2/P4
	Phycoerythrin-Cy5 (PC5)	488	674	>670	FL-3/P5
	Peridinin Chlorophyll Protein (PerCP)	470	680	>670	FL-3/P5
	Phycoerythrin-Cy7 (PC7)	488	785	>670	FL-3/P5
HeNe 633 nm	Allophycocyanin (APC)	650	660	661/16	FL-4/P8

Table 2. Organ specific differences of pre- and postoperative PMN CD64 Indices in percentages

	<1		1–1.5		>1.5
	No infection or inflammation		Intermediate		Suspicious for systemic inflammatory reaction
PMN CD64 Index	Pre Tx	Post Tx	Pre Tx	Post Tx	Pre Tx	Post Tx
In patients with kidney and pancreas failure, preoperative PMN CD64 Indices are mostly beneath the cut-off, which implies a lack of infection or inflammation. In patients with liver failure, about half of the patients present intermediate values before transplant. In all organ groups, we find elevated values after transplantation. After kidney-pancreas transplantation all patients present elevated PMN CD64 Indices, after kidney transplantation only 13%.
Kidney	91%	56.5%	9%	30.4%	0%	13%
Liver	53.8%	0%	46.2%	61.5%	0%	38.5%
Kidney-pancreas	100%	0%	0%	0%	0%	100%

The patient who received additionally Daclizumab showed no peculiarities in course after transplantation. There where neither complications nor elevated values for PMN CD64 Index.

It is described that the used diagnostic kit leads to a PMN CD64 Index value below 1 in persons without infectious events and therefore inactivated PMN. The cut-off for patients with immunological response is claimed to be over 1.5 (47).

By using ROC curve analysis, we could confirm that the cut-off greater than 1.5 for the PMN CD64 Index can be used to detect infectious complications in postoperative course after transplant (Supporting Information Table 4). As an improved cut-off, we would propose 1.71 resulting in a sensitivity of 89% and specificity of 65%. Other diagnostic parameters were used according to internal laboratory standards.

Following the described statistical procedure, we performed a ROC curve analysis including all infectious events (n = 9) and all rejections (n = 5). Other complications were too rare for statistical analysis.

As illustrated in Figure 4, the area below the ROC curve of the PMN CD64 Index was 0.84 for infections (95% confidence interval = 0.679-1, P-value = 4.17e-5).

The comparison of the PMN CD64 Index ROC with the other parameters is illustrated in Table 3. The PMN CD64 Index was a significantly better marker for detecting infectious complications than all other tests except downregulated CXCR3⁺ NK/T cells.

Table 3. Comparison of sensitivity and specificity of tests with the PMN CD64 Index accordingly to ROC curve for infectious complications

	Sensitivity			Specificity
Test	Test	PMN CD64 index	P	Test	PMN CD64 index	P
Accordingly to ROC curve (Fig. 4a +), a cut-off for PMN CD64 Index has been chosen which leads to specificity of analyzed test. With equal specificity, sensitivities of test and of PMN CD64 Index are comparable. Specificity was compared analogously by assuming a cut-off for PMN CD64 Index which results in the sensitivity of the other test.
CRP	0.889	1	1	0.061	0.647	4.22E-07
WBC	0.667	0.889	0.576	0.382	0.941	1.35E-06
HLA-DR on monocytes	0.556	0.889	0.294	0.647	0.941	0.006
CD4/CD8 ratio	0.778	0.889	1	0.382	0.912	7.81E-06
NKp44+ NK and NK/T cells
Out of normal range	0.444	1	0.029	0.059	0.941	2.22E-14
Lower than normal range	0.333	1	0.009	0.294	0.941	3.44E-08
Higher than normal range	0.222	0.889	0.015	0.618	0.971	0.001
CXCR3^+ NK cells
Out of normal range	0.778	1	0.471	0.118	0.912	2.03E-11
Lower than normal range	0.667	1	0.206	0.235	0.941	2.08E-09
Higher than normal range	0.111	0.778	0.015	0.794	1	0.011
CXCR3^+ T helper cells
Out of normal range	0.444	0.889	0.131	0.324	0.941	1.25E-07
Lower than normal range	0.333	0.889	0.050	0.618	0.941	0.00
Higher than normal range	0.111	0.778	0.015	0.706	1	0.001
CXCR3^+ NK/T cells
Out of normal range	1	1	1	0.206	0.294	0.576
Lower than normal range	1	1	1	0.206	0.294	0.576
Higher than normal range	0	0.111	1	1	1	1

As shown in Table 4, the PMN CD64 Index presents the highest Youden Index (0.54) for detection of infectious complications. The combination of tests showed no improved diagnostic value (i.e., no better Youden Index). An example of individual time course of the PMN CD64 Index in a patient with an infectious complication is shown in Figure 5. The PMN CD64 Index is considerably elevated days before the diagnosis of severe complication.

Figure 5. Representative examples of the individual course of the PMN CD64 Index in a patient without any complications (a) and in a patient who had a documented infectious complication (b). Note in both cases the elevated PMN CD64 Indices immediately after transplantation (day 1). In the case of postoperative complication (b), on the fifth day after transplantation (arrow) the patient presents a fulminant pneumonia with need for intubation and intensive care. As a specific marker for infectious complications, the PMN CD64 Index on the third day is considerably elevated.

Table 4. Youden Indices of measured parameters for detection of infectious complications

Test	Sensitivity	Specificity	Youden index
The Youden Index is calculated by summation of sensitivity and specificity minus 1. Immunological parameters were reviewed for whether they present an up- or downregulation out of the normal range. The highest Youden index was calculated for the PMN CD64 Index. Characteristics of meaningful combinations of tests are also provided at the end of the table.
1 = PMN CD64 Index	0.889	0.647	0.536
2 = CXCR3^+ NK/T cells (lower than normal range)	1	0.206	0.206
3 = CXCR3^+ NK/T cells (out of normal range)	1	0.206	0.206
4 = HLA-DR on monocytes	0.556	0.647	0.203
5 = CD4/CD8 ratio	0.778	0.382	0.160
6 = WBC	0.667	0.382	0.049
7 = CXCR3^+ NK/T cells (higher than normal range)	0	1	0
8 = CXCR3^+ T helper cells (lower than normal range)	0.333	0.618	−0.049
9 = CRP	0.889	0.061	−0.050
10 = CXCR3^+ NK cells (higher than normal range)	0.111	0.794	−0.095
11 = CXCR3^+ NK cells (lower than normal range)	0.667	0.235	−0.098
12= CXCR3^+ NK cells (out of normal range)	0.778	0.118	−0.104
13 = NKp44+ NK and NK/T cells (higher than normal range)	0.222	0.618	−0.160
14 = CXCR3^+ T helper cells (higher than normal range)	0.111	0.706	−0.183
15 = CXCR3^+ T helper cells (out of normal range)	0.444	0.324	−0.232
16 = NKp44+ NK and NK/T cells (lower than normal range)	0.333	0.294	−0.373
17 = NKp44+ NK and NK/T cells (out of normal range)	0.444	0.059	−0.497
PMN CD64 and CXCR3^+ NK/T cells (lower than normal or out of normal)	0.889	0.647	0.536
PMN CD64 and HLA-DR on monocytes	0.556	0.853	0.408
PMN CD64 or HLA-DR on monocytes	0.889	0.559	0.448

In contrast, to detect rejections, the PMN CD64 Index resulted in a ROC with an area of 0.463 (95% confidence interval = 0.164-0.763 and a P-value = 0.809) as shown in Figure 4. Hence, the PMN CD64 Index provides no diagnostic value for the detection of rejection events.

Table 5 illustrates the Youden Index for detection of rejections. The marker with best performance was the CD4/CD8 ratio (Youden Index = 0.42), followed by the PMN CD64 Index (Youden Index = 0.21) and CXCR3⁺ NK cells (higher than norm, Youden Index = 0.19).

Table 5. Youden indices for detection of rejections

Test	Sensitivity	Specificity	Youden index
The CD4/CD8 ratio shows the highest Youden index.
1 = CD4/CD8 ratio	1	0.421	0.421
2= PMN CD64 Index	0.6	0.605	0.205
3 = CXCR3^+ NK cells (higher than normal range)	0.4	0.789	0.189
4 = NKp44+ NK and NK/T cells (lower than normal range)	0.8	0.368	0.168
5 = NKp44+ NK and NK/T cells (out of normal range)	1	0.132	0.132
6 = CRP	1	0.057	0.057
7 = CXCR3^+ NK/T cells (out of normal range)	0.8	0.211	0.011
8 = CXCR3^+ NK/T cells (lower than normal range)	0.8	0.211	0.011
9 = WBC	0.6	0.405	0.005
10 = CXCR3^+ NK/T cells (higher than normal range)	0	1	0
11 = CXCR3^+ NK cells (out of normal range)	0.8	0.158	−0.042
12 = CXCR3^+ T helper cells (higher than normal range)	0.2	0.711	−0.089
13 = HLA-DR on monocytes	0.2	0.684	−0.116
14 = CXCR3^+ T helper cells (lower than normal range)	0.2	0.658	−0.142
15 = NKp44+ NK and NK/T cells (higher than normal range)	0.2	0.632	−0.168
16 = CXCR3^+ T helper cells (out of normal range)	0.4	0.368	−0.232
17 = CXCR3^+ NK cells (lower than normal range)	0.4	0.289	−0.311

DISCUSSION

The aim of this study was to evaluate the diagnostic value of the PMN CD64 Index compared with other markers in the postoperative course of solid organ transplanted patients.

CD64, also called FcγRI, which is a class of plasma membrane receptors in human myeloid cells, exists besides three further classes of Fc receptors: FcγRII (CD32), FcγRIII (CD16), and FcγRIV.

Functionally, there are two different classes of Fc receptors: activatory and inhibitory receptors, which transmit their signals via immunoreceptor tyrosine-based activation (ITAM) or inhibitory motifs (ITIM), respectively (48).

The paired expression of activatory and inhibitory molecules on the same cell is the key for the generation of a balanced immune response. In addition, the IgG Fc receptors show significant differences in their affinity for individual antibody isotypes, rendering certain isotypes more strictly regulated than others (49).

Located on chromosome 1 in humans three distinct genes exist for CD64, called FcγRIA (CD64A), FcγRIB (CD64B) and FcγRIC (CD64C) (50). By alternate splicing these three genes result in six different mRNA transcripts – two from CD64A, three from CD64B, and one from CD64C (51).

CD64 consists of a signal peptide allowing its transport to the cell surface, three extracellular immunoglobulin domains of the C2-type, a hydrophobic transmembrane domain, and a cytoplasmic tail (51, 52).

The three extracellular Ig-like domains bind exclusively to and with high affinity for the Fc portion of IgG2a (51). After binding IgG2a, CD64 interacts with an accessory chain, the common γ chain, which possesses an immunoreceptor tyrosine-based activation motif (ITAM) required for triggering cellular activation (53). The aggregation of activating receptors by immune complexes leads to tyrosine phosphorylation of the ITAM by members of the Src-kinase family and subsequent recruitment of SH2-containing kinases such as members of the Syk-kinase family. These early events ultimately lead to the recruitment of phosphatidylinositol 3-kinase (PI3-K) and phospholipase-Cg (PLCg), which trigger protein kinase C (PKC) activation and sustained calcium elevation (54). CD64 cannot transmit activating signals in the absence of the common γ chain (49).

In healthy individuals, CD64 is constitutively presented at a low level on the cell surface of monocytes, macrophages, eosinophils, and neutrophils, respectively. With about 1500 mean equivalent soluble fluorescence (MESF) units, CD64 expression on neutrophils is negligible in the healthy state. In cases of documented sepsis and/or severe tissue injury, the mean of MESF was up to about 10,000 units (33).

Treatment of polymorphonuclear leukocytes with cytokines like interferon (IFN)γ and G-CSF can induce CD64 expression depending on the intensity of the stimulation of these cells (33, 34, 37, 55, 56).

Given that neutrophils are the major cellular component of acute response to infection, the detection of molecular changes of PMN activation could provide a rapid and sensitive indicator of systemic inflammatory response (32, 33, 36, 41, 57, 58).

CD64 expression on polymorphonuclear leukocytes is mainly induced by bacterial infection (32–34, 36, 39, 41, 58–60) and varies by the type of infection (Gram-negative bacteria inducing higher CD64 expression on neutrophils compared with Gram-positive bacteria) (33). It appears to directly correlate with enhanced bactericidal and antifungal activity (33). The antibody-dependent cross-linking of expressed CD64 (57) contributes to cellular cytotoxicity, phagocytosis and the clearance of immune complexes (34).

In situations of increased inflammatory response like sepsis, SIRS, local infection, or tissue injury, within 4–6 h the cell surface expression of CD64 on granulocytes elevates and already within 1–3 h the detectable mRNA increases and can be measured by Northern Blot analysis (33).

Compared with other haematological indices, CD64 expression on granulocytes shows a biphasic response to lipopolysaccharide (LPS) administration in humans. Peak values of pro-inflammatory cytokines, but not the anti-inflammatory IL-10, correlate with CD64 expression on granuloycytes after LPS administration. This illustrates that CD64-on-granulocyte expression is a parameter of innate immunity (61).

By using a quantitative flow cytometric assay, the PMN CD64 Index as an in vitro indicator of neutrophil activation seems to be a valuable marker in the evaluation of patients with suspected acute inflammation or infection (32).

In laboratory diagnostics, interpretation of findings depends on reference values in adequate controls. In our case, transplanted patients without complications served as control group. In the literature concerning the PMN CD64 Index, a cut-off value of 1.5 is proposed to detect infectious complications (47). In our study, we confirmed that this cut-off is appropriate, but the cut-off 1.71 had a higher Youden Index. No evidence was found that the cut-off should be different for different types of graft. However, further investigations with a higher count of case numbers are necessary to answer this question definitely.

In patients with liver failure, we could detect higher preoperative values than in cases with kidney or pancreas failure which seems to be caused by a higher basic stimulation of the immune system in cases of hepatic shutdown. Furthermore, we found highly elevated PMN CD64 Index values immediately after pancreas–kidney transplantation which most likely is caused by a high operative trauma, which leads immediately to immunological response.

We showed that for transplanted patients under immunosuppression, the same cut-off for the PMN CD64 Index is usable as for nontransplanted patients (47). However, recent studies have reported a downregulation of CD64 expression on granulocytes by hydrocortisone treatment (33, 62). Following our results, it seems that this fact does not influence the cut-off and diagnostic usability of this marker in transplanted persons.

Related to the other analyzed parameters, the PMN CD64 Index showed the best performance in detecting infectious postoperative complications. Exemplary courses of PMN CD64 Indices in cases of inconspicuous course (a) and with infectious complication (b) are shown in Figure 5. In particular, the early increase of PMN CD64 Index before infectious complication should be mentioned.

Compared with the other parameters PMN CD64 Index reached a better specificity with the same sensitivity or a better sensitivity with the same specificity. It was not significantly better than downregulation of CXCR3⁺ NK/T cells. Hence, the PMN CD64 Index seems to be a useful marker for diagnostic of postoperative infections in solid organ transplanted patients. Due to the direct correlation between acute inflammatory processes and CD64 upregulation on polymorphonuclear granulocytes, the preoperative assessment of the PMN CD64 Index is not useful for the prediction of complications in further course.

In contrast, according to our results the PMN CD64 Index has no diagnostic value for the detection of rejections. If immunosuppression by Cyclosporin A instead of Tacrolimus has an effect to diagnostic value of PMN CD64 Index can not be said closing, because in this study such constellation was a singular case.

It has already been shown that CD64 expression on granulocytes can be initially and transiently elevated in patients with sepsis (32, 59). Early decrease of CD64 expression on granulocytes did not appear to be detrimental.

Initial elevated values seem to be caused by a general postoperative IFN-γ upregulation by Th1 cells after contact with antigen-presenting cells (APC) which leads to a stimulation of PMN, T cells, NK cells, macrophages, and endothelial cells. A second peak of expression of CD64 on granulocytes in a survivor might indicate an adequate response to a recurrent invasion of microorganisms, avoiding a relapse into septic shock (59).

The PMN CD64 Index is a valuable marker to detect infectious complications occurring more than two days after surgery. A cut-off value of 1.71 resulted in the highest Youden Index, but the optimal cut-off must be defined on the basis of a larger cohort. However, it should be noted that the Youden Index is only a summary measure of test performance. For future diagnostic applications, cost-benefit analyses regarding false-positive and false-negative diagnoses are necessary to define clinically useful cut-off values.

Results for other parameters show consistency with the literature base for this patient group. CRP presents high sensitivity with poor specificity for infectious complication and rejection. (63–67). Elevated WBC count and low HLA-DR on monocytes are useful parameters for the detection of infectious complications (26, 68), but not for the detection of rejection (26, 69). In the literature, an association between leukocytopenia and rejection is declared (70), which was not examined in this study.

According to our results, the CD4/CD8 ratio seems to be a valuable marker for the detection of rejection. This is consistent to other studies' results (71, 72).

CXCR3⁺ NK/T cells demonstrated good sensitivity for infectious complications, but low specificity. Other immunologic monitoring parameters show no advantage for the detection of infection. NKp44⁺ NK and NK/T cells present diagnostic value for the detection of rejection.

A combination of immunologic parameters may be useful. In our trial, a combination showed no diagnostic advantage, probably due to low case number.

CONCLUSION

We conclude that the measurement of CD64 on PMN, by ascertainment of the PMN CD64 Index, results in a useful parameter for the diagnostic evaluation of suspected postoperative infectious complications in transplanted patients. Its diagnostic value for infectious complications shown in other studies has been confirmed for the cohort of transplanted patients and their special clinical characteristics.

In accordance with other studies including different patient collectives, our results suggest that the use of the PMN CD64 Index as a marker of postoperative infections allows early and quick predictions of critical events which could be accompanied by prophylactic or ameliorative interventions before definitive microbiologic culture results (58).

Measurement of the PMN CD64 Index is fast to perform. Davis and Bigelow (73) demonstrated a superior sensitivity, specificity, and positive predictive likelihood ratio for neutrophil CD64 expression, compared with neutrophil counts, band counts, and myeloid immaturity fraction. An anticipated benefit is that cytometric measurement of CD64 on PMN could make the need for performing subjective and laborious manual microscopic differential counts for the determination of band counts and immature-to-total myeloid ratios superfluous, in particular, if it would be integrated into routine laboratory procedure. Whether this kit is better than the polychromatic flow cytometry assay recently presented by Roussel et al. (74) needs to be answered in further trials.