Determining a reliable set of noninvasive biomarkers for acute rejection (AR), as well as for immunologic unresponsiveness toward the allograft, is a major aim in the field of solid organ transplantation.1,2 Defining such markers may allow for tailor-made immunosuppressive strategies, which will likely result in the prevention of underimmunosuppression and overimmunosuppression. Recently, a biomarker set containing several B-cell features has been associated with the occurrence of operational tolerance in kidney transplant recipients.3,4 This biomarker set included an increased number of peripheral blood B cells, an altered B cell phenotype toward more naive and transitional B cells, a gene expression pattern dominated by B cell–related genes, as well as increased levels of CD20 gene expression in urinary sediments.
The discovery of a B cell–dominated fingerprint of tolerance suggested that B cells may be actively participating in the induction or maintenance of operational tolerance5 and has initiated a quest to delineate the role of B cells as immunoregulatory cells in the transplantation setting. In a seminal study on operationally tolerance kidney transplant recipients by Sagoo and colleagues,3 the B cell–related genes, TCL1A, CD79B and MS4A1 (CD20), were upregulated and among the highest tolerance discriminating genes. How these genes would induce immunologic unresponsiveness is currently unknown.
Tolerance toward the allograft may at least partially be established by regulatory properties of B cells within the transitional B cell compartment. By in vitro studies, it has been shown that (a subset within) transitional B cells, in humans defined as CD19+CD24hiCD38hi, can suppress T cell responses, mediated partially by interleukin (IL)-10 production.6,7 Indeed, of all biomarkers tested, the levels of transitional B cells in operationally tolerant kidney transplant recipients were most predictive for the tolerant state and showed a tendency toward higher levels of IL-10 production on polyclonal stimulation compared to stable patients under immunosuppression.4 Additional B-cell subsets with regulatory properties have recently been described, of which the relevance in clinical transplantation has not yet been addressed.8
Little is known regarding the behavior of tolerance biomarkers in kidney transplant recipients with stable graft function and during AR. Viklicky and colleagues9 recently demonstrated that rejection-free kidney transplant recipients have elevated levels of peripheral B cells compared to patients who experienced an AR episode. Expression levels of the B cell–related genes, MS4A1, TCL1A, and CD79B, were also higher in patients with stable graft function. These data suggest that in addition to discriminating tolerant from nontolerant kidney transplant recipients, this biomarker set might also be used to monitor for AR. Whether this is possible remains elusive because the aforementioned study lacked systematic sampling at the time of AR, and many samples were collected after the AR event. We hypothesized that markers of operational tolerance are differentially expressed at the time of AR compared to stable graft function. To test this hypothesis, we retrospectively determined regulation-associated B-cell phenotypes and tolerance-discriminating B-cell gene expression levels in kidney transplant recipients before transplantation, at discharge and at the time of AR, or a follow-up timepoint in patients without AR.
The Peripheral Transitional B Cell Subset Is Diminished After Transplantation
We selected 21 kidney transplant recipients who experienced a biopsy-proven AR episode within 6 months after transplantation, as well as 22 patients with stable graft course and 20 healthy controls. By flow cytometric analysis, we first determined the relative level of CD3−CD19+ B cells within the lymphocyte population in patients with stable graft function and patients with AR (gating strategy is depicted in Fig. 1A). Similar to the relative level of CD19+ B cells after cardiac transplantation,10 we observed a small, but significant, increase in the percentage of CD3−CD19+ B cells at the time of discharge, both in stable patients (P = 0.001) and in patients who would later develop AR (P = 0.004, Fig. 1B). The percentage of CD3−CD19+ B cells normalized at the follow-up or AR timepoint. We found no differences between the two patient groups. We then looked into the transitional B-cell subset within the CD19+ B-cell population and found that, although pretransplant levels of CD19+CD24hiCD38hi transitional B cells were comparable to those of healthy controls, there was a significant reduction after transplantation in both patient groups (both P < 0.001). The percentage of this subset further declined at the AR timepoint (P < 0.001), but also at matched timepoints in patients with stable graft function (P = 0.02, Fig. 1C). These findings were corroborated by an alternative gating strategy for transitional B cells on the basis of the CD19+IgD+CD38hi phenotype (Fig. 1D).
Human B10 cells, phenotypically defined as CD19+CD27+CD24hi, have been attributed regulatory functions by production of the immunoregulatory cytokine IL-10.8 In patients with stable graft function, the percentage of CD27+CD24hi cells within the CD19+ B-cell population increased on transplantation (P = 0.002), after which the percentage of CD27+CD24hi cells did not significantly change (P=NS, Fig. 1E). The increase of CD27+CD24hi cells on transplantation was also observed in the AR group (P = 0.02). However, at time of AR, we observed a decreased level of CD27+CD24hi cells compared to pretransplant (P = 0.006) and to the discharge timepoint (P < 0.001, Fig. 1E). Despite the difference of the CD19+CD27+CD24hi cell population in time, there was no statistically significant difference between the patients at the time of AR and at follow-up.
Tolerance-Associated B Cell Genes Are Downregulated On AR
We focused on a small set of B cell–related genes that have been described to be upregulated in the context of operational tolerance, namely, MS4A1 (CD20), TCL1A, and CD79B.3,4,9 First, we determined the expression of these genes in PBMC samples and found that MS4A1 gene expression in the AR group and the stable group was lower compared to healthy controls (P = 0.004 and P = 0.01, respectively, Fig. 2A). In stable patients, we observed a slight increase in MS4A1 gene expression levels at the follow-up timepoint compared to pretransplant levels (P = 0.02), whereas in patients with AR, MS4A1 gene expression levels remained stable. We observed no statistical difference between the two patient groups (P=NS). In contrast, gene expression levels of TCL1A behaved differently in the two patient groups (Fig. 2B). In stable patients, we found a gradual increase in TCL1A gene expression levels in time (pretransplantation to discharge: P = 0.03, pretransplantation to follow-up: P = 0.002, and discharge to follow-up: P = 0.03). Gene expression levels of TCL1A in stable patients did not change at the follow-up timepoint but dropped significantly in rejecting patients at the time of AR (P = 0.02), resulting in a significant difference in gene expression levels in stable patients at the time of follow-up compared to patients at the time of AR (P = 0.005). Lastly, CD79B gene expression levels in PBMC remained rather stable in time, only showing a modest, but significant decrease in AR patients at the time of AR (P = 0.02). Despite this decrease, we found no statistically significant differences between the patient groups at any time (Fig. 2C).
Because TCL1A expression is not restricted to B cells, we wanted to know whether the observed changes in TCL1A gene expression during AR were at least partly caused by the changes within the B cell compartment. Therefore, we determined its expression levels on isolated B cells, also including CD79B (exclusively expressed by B cells) to confirm our data on PBMC. Similar to the changes in gene expression levels in PBMC, we observed an increase in TCL1A expression levels on transplantation in patients with stable graft function (pretransplantation to discharge: P = 0.002, pretransplantation to follow-up: P = 0.008, Fig. 3A). In contrast, no increase in TCL1A expression levels was observed in the AR group (P=NS). When we compared the expression of TCL1A at time of AR to samples of stable patients at the follow-up timepoint, we found significantly lower expression levels (P = 0.0004), which was similar to the data obtained from PBMC, albeit more profound. In contrast, differences in CD79B gene expression levels in isolated B cells were much more profound than those found in PBMC (Fig. 3B). On transplantation, CD79B gene expression levels in stable patients increased (P = 0.008) and remained stable afterward, whereas in patients with AR, there was a clear decrease CD79B gene expression levels at time of AR (P = 0.008, compared to discharge timepoint). This resulted in a significant difference in CD79B gene expression levels at the time of AR compared to stable patients at the follow-up timepoint (P = 0.01). Subsequent receiver operating characteristic curve analysis showed a high discriminative capacity for AR by TCL1A (AUC 0.86, P < 0.001) and to a lesser extent by CD79B (AUC 0.76, P = 0.01, Figure S1, SDC,http://links.lww.com/TP/B73).
In both patient groups, there were no active urinary tract infections, wound infections, or other reported infections at the time of measurements. In the control group, one patient had low-grade BK viral load (4.91E+003 copies/mL) and one patient had a low-grade positive cytomegalovirus (CMV) polymerase chain reaction (PCR) (3.50E+002 IU/mL) at the time of immune monitoring. When assessing these patients separately, we found no impact on the markers analyzed in the current study.
The role of B cells in allograft rejection and immunologic unresponsiveness in the setting of organ transplantation is becoming increasingly clear. In this study, we showed differential gene expression patterns of the B cell–related genes, TCL1A and CD79B, at time of AR compared to stable graft function in the peripheral blood of kidney transplant recipients. These genes have previously been associated with the occurrence of operational tolerance in kidney transplant recipients.3,4,11 To our knowledge, this is the first study comparing markers of operational tolerance in samples taken at the time of AR, before initiation of antirejection therapy with samples from patients with stable graft function acquired at similar timepoints after transplantation.
The possible involvement of B cells in cellular rejection episodes has previously been suggested in several studies. An important observation came from the Sarwal group12 who showed that the presence of intragraft CD20+ B cells in rejection biopsies was associated with glucocorticoid resistance and graft loss. However, although others have confirmed these findings,13,14 an unfavorable effect of intragraft B cells on graft outcome has not universally been found.15 The exact role of B cells in cellular rejection is still unknown, but it seems likely that B cells act as antigen-presenting cells.16 The importance of B cell antigen presentation was illustrated in a mouse cardiac transplantation model, where the absence of B cell MHC class II expression delayed cellular rejection of allogeneic heart transplants17 A second, yet more hypothetical role of B cells in cellular rejection is a regulatory one, in which cellular rejection may occur when the regulatory capacity of B cells is not sufficient.18
The markers tested in this study have been associated with operational tolerance or immune regulation in kidney transplant recipients.3,4 Whether these markers represent active immune regulation or are a mere result of the tolerant state of the patient is yet unknown. We showed that on transplantation and initiation of standard immunosuppressive therapy, there was a steep decline in the percentage of transitional B cells in the peripheral blood, whereas the percentage of total B cells showed a modest increase. This suggests that transitional B cells may be more susceptible to immunosuppressive drugs than their mature counterparts. Hence, the observation that patients who stopped taking immunosuppressive medication have high levels of transitional B cells (comparable to healthy controls) may be a result of drug cessation, rather than active immunoregulation. In this scenario, an active regulatory role of transitional B cells in operational tolerance is unlikely. Although the susceptibility of total B cells to immunosuppressive drugs has been studied,19,20 more in-depth studies on the susceptibility of B cell subsets to immunosuppressive drugs are needed.
Besides transitional B cells, a subset of CD19+CD27+CD24hi B cells has also been described to have regulatory properties and have been termed B10 cells because of their production of IL-10.8 In an earlier study on operationally tolerant kidney transplant recipients, Pallier et al.21 have shown an increase in peripheral CD19+CD38+/−CD27+IgD− B cells in stable drug-free patients. One may speculate that these include CD19+CD27+CD24hi B10 cells. However, currently, there is no information on B10 cells in operationally tolerant kidney transplant recipients. We wanted to determine the fate of CD19+CD27+CD24hi B cells in our patient cohort and found that these cells behaved differently than the transitional B cells. CD19+CD27+CD24hi B cell levels did not decrease on transplantation, suggesting that this B cell subset is not diminished by immunosuppressive drugs. Because we were unable to determine the IL-10–producing capacity of B cells in this patient cohort, our results lack functional information on the CD19+CD27+CD24hi B cell subset.
The recent study by Viklicky and colleagues9 showed that, when monitoring kidney transplant recipients at fixed timepoints during the first year after transplantation, there was a clear difference in MS4A1, TCL1A, and CD79B gene expression levels between patients who developed an AR episode and patients with stable graft function. We have extended these results by specifically determining the expression levels of these genes at the time of AR. In line with the results from the article by Viklicky et al., we found that TCL1A and CD79B gene expression levels at time of AR were lower than those in patients with stable graft function. By isolating B cells from the peripheral blood, we were able to show that for TCL1A, which is not exclusively expressed by B cells, this effect was at least partially caused by the differential expression in the B-cell compartment. In contrast to the results from Viklicky and colleagues, we did not find any differences in the expression levels of MS4A1 in the PBMC fraction nor in isolated B cells (data not shown).
The current data confirm the notion that TCL1A and CD79B gene expression levels may serve as markers for the level of immune activation, with high expression levels representing an immunologic quiescent state and low expression levels representing immune activation. Alternatively, high expression levels of these genes may represent immune regulation, and low levels a lack of regulation. How TCL1A and CD79B gene expression levels influence immune responses is subject to future studies. An important feature of a biomarker of AR is that it is capable of detecting successful treatment. Unfortunately, we did not have the availability of routine samples obtained after AR treatment to determine whether TCL1A and CD79B gene expression levels correlated with the resolution of rejection. For two patients, we had PBMC samples, after successful antirejection therapy with steroids, in which we found that gene expression levels of these two genes increased on treatment (Figure S2, SDC,http://links.lww.com/TP/B73). In addition, for use as biomarker, an important next step is to determine whether low levels of TCL1A and CD79B gene expression occur during any form of immune activation, or whether it is specific for alloimmune responses. The patients in the stable graft function group with low-grade positive BKV or CMV PCR results had similar patterns of gene expression compared to stable patients without infection. However, preliminary data on three kidney transplant recipients with biopsy-proven polyomavirus nephropathy suggest that TCL1A and CD79B gene expression levels can decline at time of severe infection (data not shown). Therefore, the validity of these genes as biomarkers for AR should be addressed in future studies.
In conclusion, we show that the B cell–associated genes TCL1A and CD79B are downregulated at the time of acute kidney allograft rejection, indicating that, in addition to being markers for immunologic unresponsiveness, these genes may also identify immune activation in the setting of kidney transplantation.
MATERIALS AND METHODS
Healthy control subjects were age and sex matched to the transplant cohort. All patients received standard triple therapy, consisting of a CD25 blocking antibody (daclizumab or basiliximab), tacrolimus, mycophenolate mofetil, and steroids.22 Patients were treated routinely with oral (tablet) valganciclovir prophylaxis for 3 months, except for a CMV-negative donor recipient status. Patient characteristics are depicted in Table 1. Peripheral blood samples were taken at several timepoints and frozen in liquid nitrogen until further use. For this study, we selected pretransplant samples at the time of hospital discharge, as well as at the time of AR, before the initiation of antirejection therapy. For the patients with stable graft function, follow-up timepoints matching the rejection timepoints were selected. All samples were obtained with informed consent under guidelines issued by the Medical Ethics Committee of the Leiden University Medical Center (Leiden, the Netherlands).
Peripheral blood mononuclear cells (PBMC) were isolated by Ficoll-Paque (LUMC Pharmacy, Leiden, the Netherlands) gradient centrifugation and stored in liquid nitrogen until further use. B cells were isolated by negative selection using the EasySep Human B cell enrichment kit (Stem Cell Technologies, Grenoble, France) according to the manufacturer’s instructions.
Flow cytometry was performed according to standard protocols using the following antibodies (clone): CD19 (SJ25C1), CD24 (ML5), IgD (IA6-2), CD5 (UCHT2), CD3 (UCHT1) (all from BD Biosciences, Breda, the Netherlands), CD1d (51.1) (Biolegend, London, United Kingdom), CD27 (CLB-CD27/1, 9F4) (Sanquin, Amsterdam, the Netherlands) and CD38 (HIT2) (eBioscience, San Diego, CA) or relevant isotype controls.
Gene Expression Analysis
Total RNA from PBMC or isolated B cells was extracted using the NucleoSpin RNA kit (Macherey-Nagel, Düren, Germany). RNA quality was determined on Nano LabChips with the Aligent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). Synthesis of complimentary DNA, primer design, and quantitative PCR analysis were performed according to previously described protocols.23 Primers sequences are depicted in Table 2. Differences in mRNA expression levels were normalized to the geometric mean signal of the reference genes glyceraldehyde-3-phosphate dehydrogenase and β-actin.
Clinical parameters were compared using the Mann-Whitney U test, the Fisher exact test and the chi-square test, where appropriate. Differences between patient groups were analyzed using the Mann-Whitney U test, whereas differences within patient groups at different timepoints were analyzed with the Wilcoxon matched pairs signed rank test with Bonferroni correction for multiple testing. Data were considered statistically significant if P value is less than 0.05. The data are expressed as box plots with error bars showing the 10th to 90th percentile.
The authors thank Geert Haasnoot for statistical advice.
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