Circulating endothelial cells transiently increase in peripheral blood after kidney transplantation

The diagnosis of kidney allograft rejection is based on late histological and clinical markers. Early, specific and minimally-invasive biomarkers may improve rejection diagnosis. Endothelial cells (EC) are one of the earliest targets in kidney transplant rejection. We investigated whether circulating EC (cEC) could serve as an earlier and less invasive biomarker for allograft rejection. Blood was collected from a cohort of 51 kidney transplant recipients before and at multiple timepoints after transplantation, including during a for cause biopsy. The number and phenotype of EC was assessed by flow-cytometric analysis. Unbiased selection of EC was done using principal component (PCA) analysis. Paired analysis revealed a transient cEC increase of 2.1-fold on the third day post-transplant, recovering to preoperative levels at seventh day post-transplant and onwards. Analysis of HLA subtype demonstrated that cEC mainly originate from the recipient. cEC levels were not associated with allograft rejection, allograft function or other allograft pathologies. However, cEC in patients with allograft rejection and increased levels of cEC showed elevated levels of KIM-1 (kidney injury marker-1). These findings indicate that cEC numbers and phenotype are affected after kidney transplantation but may not improve rejection diagnosis.

www.nature.com/scientificreports/ EC identification can be performed before and after kidney transplantation. We hypothesized that upon injury, cells within the capillaries are likely to get released from the graft. After organ transplantation, characterization of EC from peripheral blood represents a valuable methodology to avoid invasive diagnostic procedures. Furthermore, understanding the phenotypical determinants of cEC could aid in clinical decision making, developing efficacious strategies for organ repair, and improving long-term graft survival after transplantation.
In the present study we examined whether injury induced by the transplant procedure and rejection episodes is associated with release of EC, with elevated cEC and with phenotypic changes in cEC. To this end, we measured EC numbers in 3 deceased donor kidney machine perfusion perfusates and in the blood of 51 kidney transplant recipients. We additionally examined the cEC phenotype to evaluate their potential as biomarker for transplant status diagnosis. Lastly, we investigated the cEC origin and made correlations with clinical variables related with this biomarker and its relevance in the clinical setting for renal transplantation.

Endothelial cells are present in kidney perfusion solution. Endothelial cells (EC) from deceased
donor kidneys were identified in machine perfusion perfusates by flow cytometry using a non-linear generalization of principal component analysis (PCA) and unsupervised clustering (Fig. 1a). 500 clusters were used to classify cells, based on data set variance, and robustness of detected endothelial cell clusters. Cluster criteria selection was set up to determine EC containing clusters (CD45 -, CD31 + , CD34 + , CD146 + , CD105 + , DRAQ5 + ). For most samples one cluster contained all EC (Fig. 1a). The amount of EC present in perfusates was 0.57 cells/ ml on average and varied between donors from 0.23 to 1.03 cells/ml of perfusate (n = 3). The EC found recorded differences in size and granularity (Fig. 1b). To confirm EC identity, we cultured the cells present in kidney perfusates. The majority of the selected and expanded cells showed a similar expression profile compared to the non-cultured EC in perfusates (Fig. 1c). An angiogenesis assay was carried out to provide evidence that the isolated cells possessed EC functional properties. Culture expanded EC from the perfusate recorded nearly 2.5fold increase in tube length after stimulation with VEGF, confirming they possessed EC functional properties (Fig. 1d). These results indicate that donor kidneys release EC before transplantation. www.nature.com/scientificreports/ Kidney transplant recipients show an increase in cEC number shortly after transplantation. We went on examining whether cEC can be detected in patients after transplantation. We quantified and phenotyped EC in the blood of 51 kidney transplant recipients before and after transplantation. Of these, n = 46 completed the 6-month follow-up. Two patients died before month 6, two had a transplantectomy and one dropped out the study for another reason. These missing patient samples were pairwise deleted from all performed analyses. The same clustering procedure used in perfusates was followed to detect EC in blood. We detected 1.28 ± 0.96 cEC/µl before transplantation. cEC numbers were significantly increased 3 days after transplantation (2.05 fold on average, p < 0.001) (Fig. 2a). At day 7 cEC numbers returned close to preoperative levels (p < 0.001, compared to day 3); 6 months after transplant cEC numbers were similar to pre-transplantation levels (1.29 ± 0.91 cEC/µl). We checked whether the number of cEC in recipients could be indicative of the status of the transplantation and an early biomarker for kidney injury and rejection. Therefore, we compared cEC numbers with patient and donor parameters such as sex, age, creatinine concentration, delayed graft function (DGF), cause of end-stage renal disease, preservation time, donor type, rejection type, dialysis type, induction therapy and other clinical parameters shown in Table 1 (Fig. 2b, Supplementary Fig. S1-2 online). Patient age and the length of the first warm ischemia time were the only substantial and negatively correlated variables with cEC numbers across time points.
Rejection events do not influence the number of cEC. Patients with a biopsy-proven rejection (n = 15) recorded heterogeneous cEC concentrations (p = 0.169), comparable to patients who got a biopsy but in whom another diagnosis than rejection was made (n = 11) (Fig. 2c). Similarly, no significant change was observed when cEC levels at the time of rejection were compared to the time point prior to the rejection event (n = 15; p = 0.281) (Fig. 2d). Rejectors were classified regarding their change in cEC during rejection events compared to the previous measured time point (Fig. 2e, Supplementary Table S1 online). Interestingly, rejectors with an increase in cEC reported an increase in KIM-1, while rejectors without an increase in cEC did not show elevated KIM-1 expression. (Fig. 2f).
Progenitor phenotype of cEC relates to recipient age. Within our EC detection panel, we included the endothelial progenitor cell marker CD133 to get insight into the frequency of cEC with potential regenerative characteristics ( Supplementary Fig. S3 online). No significant relationship was found between the expression of CD133 on cEC and graft rejection nor DGF (Fig. 3). Similarly, as with the number of cEC, we found a negative correlation between the age of the recipient and the MFI expression of CD133. The age of the donor did not have an influence on the CD133 expression on cEC (Fig. 3).
cEC are of mixed donor and recipient origin. After corroborating the presence of cEC in patients we investigated cEC origin. We hypothesized that the increase in cEC at day 3 after transplant arose from the kidney, supported by the finding of EC in perfusates. We sought kidney transplant donor-recipient couples with an HLA-A2 mismatch (Supplementary Table S2). We included 14 patients; 7 kidney transplant recipients whose donor expressed HLA-A2, and 7 kidney transplant recipients who expressed HLA-A2 but not the donor, and examined HLA-A2 expression on cEC by flow cytometry. Unbiased clustering was followed to identify the two possible cEC populations ( Supplementary Fig. S4 online). We detected donor kidney derived cEC in 13 out of 14 patients (Fig. 4a,b). The percentage of donor-derived cEC found in patients was in the range of 0.95-18.91% of the total cEC ( Fig. 4c). This demonstrates that the origin of cEC is mixed whereas the majority of cEC is recipient derived.

Discussion
The endothelium is one of the earliest cell types to be affected by ischemia and immunological injury. In the present study we used several markers and an unbiased gating methodology to identify EC in kidney machine perfusion perfusates and in peripheral blood via flow cytometry. Our results demonstrate the presence of kidney transplant-derived EC in machine perfusion solution and suggest that ischemic damage in donor kidneys triggers EC detachment. We found that cEC are mainly of recipient origin and we observed no association between cEC number fluctuations after kidney transplantation and transplant outcome. Machine perfusion is increasingly used to preserve kidneys and it provides an excellent opportunity to examine the kidney before transplantation 20,21 . In the present study, we confirmed that grafts release EC after perfusion. We propose that EC are partly released from the graft through manipulation during the transplantation procedure.
We observed a significant increase in cEC numbers shortly after kidney transplantation. Baseline levels of cEC concentration were recovered for most patients after one week and completely returned to preoperative levels after 6 months. This is a novel finding as other studies have just measured the concentration of cEC at a single time point [22][23][24][25] . The dynamics observed in the level of cEC reflects the disturbance caused to the graft and recipient's endothelium shortly after the transplantation procedure. Nevertheless, the injury caused to the graft during a rejection event had no direct influence in the amount of cEC. We believe changes in cEC concentrations depend on the severity of vascular stress. While a transplantation is a highly invasive procedure with a direct impact on the donor kidney and recipient endothelium due to the procedure itself and donor effects, a rejection event is caused by immunological factors at the interplay of other responses that trigger inflammation and aberrant vasculature responses 26,27 . The later ones appear not to cause substantial EC shedding.
The previously described cEC concentration fluctuation was also observed in 11 out of the 15 patients who had biopsy-proven rejections before the 6-month time point. Furthermore, cEC levels were not associated with different types of rejection nor the vascular damage assessed by histological evaluation. Interestingly, we observed www.nature.com/scientificreports/ www.nature.com/scientificreports/ www.nature.com/scientificreports/ that during rejection events with an increase in cEC numbers, cEC elicited a higher expression of KIM-1. It is known that the allograft fate is associated with the degree of the rejection 5 . Nevertheless, the increase in cEC concentration and its KIM-1 expression were not connected with the type of rejection. Although acute rejection leads to vascular damage, we hypothesize the early treatment for rejection added complexity to detect changes in cEC concentrations and its phenotype after transplantation. Beside the correlation between age and the amount of cEC previously reported in renal transplant recipients and healthy subjects 23 , we identified other patient and donor variables that influenced cEC numbers at different stages of transplantation. Shorter warm ischemia times significantly increased the number of cEC 6 months after transplantation. Since we observed no significant correlation between the other time points or ischemia times, we ought to compare the amount of cEC with the total ischemia time, where no significant correlation was observed ( Supplementary Fig. S5 online). Moreover, we found that patients with higher mismatches in HLA (classes A and B), in addition to having a higher chance for a rejection episode 28,29 , also reported a higher cEC number during later time points (Supplementary Fig. S1 online). This suggests that ongoing immune responses against the donor organ may be a factor that stimulates EC release over time. Therefore, we hypothesized that donor cEC could be used as a quality metric after kidney transplantation. Contrary to expectation, the concentration of donor related cEC found within the recipient was not indicative for recipient status. In the present study the methodology used to identify donor/recipient cEC was solely based on the detection of HLA-A2 mismatches. In order to potentiate these findings inclusion of patients with different HLA mismatches is necessary. Nevertheless, this result added evidence that EC shedding is not solely influenced by a rejection event, and that further research is needed to determine the main causes of cEC levels increase.
The use of more sensitive markers for EC characterization in blood may lead to a better classification of EC subpopulations in patients. We included within our EC flow cytometry panel the EPC marker CD133. EPC are involved in repair of various types of vascularized tissues and have shown to be a promising repair tool in animal experiments and clinical trials [30][31][32] . In our study low concentrations of circulating endothelial progenitor cells (cEPC) were only found in young kidney recipients, whereas the donor age did not influence the cEPC concentration in the recipient. Similar results were observed in a mouse model, where EPC mobilization after injury was more robust in the younger animals 33 . As cEPC are a very rare population, cEPC detection by antigens is challenging and may compel the use of different approaches and techniques for EPC identification 34,35 . This would enhance the sensitivity of the assay and give better insight into ongoing organ repair.
Our findings show that donor kidneys release EC during the transplantation procedure. In addition to this initial EC release, recipients show an increase in cEC at day 3 post transplantation. Contrary to reported for other www.nature.com/scientificreports/ vascular damage pathologies 16,[36][37][38] , injury derived from acute rejection episodes did not influence cEC levels. The identified cEC included donor derived cells even after 6 months post transplantation. These data shows that the amount of donor derived cEC in kidney transplant recipients is lower than the ones reported previously 39 .
Our approach for measuring cEC in kidney transplant recipients shows that the endothelium undergoes major changes during early stages of transplantation. On the whole, the concentration of cEC, together with cEC phenotype, give an incomplete figure of the transplant status. This approach of cEC characterization will likely prove effective if expanded with markers that could identify the status of cEC and if those are actively contributing to injury recovery or setting the stage for fibrosis. Blood and perfusate collection. Venous blood of kidney transplant recipients was collected in heparinized blood collecting tubes. Blood was collected at the following time points: before kidney transplantation, 2-4 and 6-8 days after transplantation, and 6 months after transplantation. Additional blood samples were collected at the day a clinically-indicated renal transplant biopsy was taken within the first six months after transplantation. Samples were processed between 1 and 24 h after collection. Samples that were not processed within the first two hours after collection, were stored at 4 °C.

Methods
UW machine perfusion perfusate samples were collected from kidneys of deceased after circulatory death donors (DCD; n = 3). These samples arose from kidneys that were perfused using hypothermic perfusion. Subsequently, the samples were stored at 4 °C. Perfusates were processed between half an hour and eight hours after collection. Collected volume was 0.1 L. Perfusates, collected from these deceased donor kidneys, are considered as left over material. Therefore, no specific informed consent was necessary from the deceased donors.
Endothelial cell culturing from perfusates. Kidney perfusates were centrifuged at 800 RCF for 5 min.
Angiogenesis 3D gel assay. A tube formation assay was performed to evaluate the angiogenic potential of EC. Geltrex LDEV-Free Reduced Growth Factor Basement Membrane Matrix (Thermo Fisher Scientific-Gibco, Rockford IL, USA) was kept at 4° C overnight prior to the experiment to allow complete thawing. 50 µl Geltrex was added to each well of an ice-cold 96-well plate using cold pipette tips to avoid premature Geltrex solidification. Cells were stimulated with 25 ng/ml of VEGF (R&D Systems, Abingdon, UK). Plates were incubated for 30 min at 37 °C to allow Geltrex solidification. Cells were added to the wells in a concentration of 2 × 10 4 cells per well. After 6 h, pictures were taken to evaluate the formation of tube-like structures (i.e. angiogenic capacity). The total length of the tubes formed during the assay was measured. Images were analyzed using ImageJ (version 1.52p). www.nature.com/scientificreports/ before analysis by flow cytometry. Data acquisition was done at a low flow rate (10 µL min -1 ). At least 1.5·10 6 cells were recorded on BD FACS Canto II (BD Bioscience). Measurements were performed in a blindfolded fashion. The same procedure was followed with perfusion solutions, with the difference of a shorter lysis time (10 min) due to a lower amount of red blood cells in the perfusion samples.
To distinguish between donor/recipient derived endothelial cells, patients with an HLA(A2)-mismatch with their donor were identified. HLA(A2) antigen was used in this study because it is one of the most common mismatching antigens among donor/recipients 11 . Cells from these patients were labelled with anti-human antibody HLA(A2)-BV421 (BD Bioscience) together with the other antibodies used to phenotype endothelial cells, except for CD133-BV421. Two patients without HLA-A2 were used as negative control for this patient subgroup. Statistical and data analysis. All bioinformatics analyses were performed in R (version 3.6.2) 43 . Flow cytometry data was analyzed using the flowCore package 44 . Data was compensated using a spill over matrix generated with single labeled cells. Data quality was checked for anomalies regarding flow rate, signal acquisition and dynamic range using the flow_auto_qc function from flowAI 45 . Thresholds were set on FSC and SSC to remove non-single cells from the data. Fluorescence signal data were transformed to Logicle scale. Unbiased and unsupervised data clustering was performed using a non-linear generalization of principal component analysis (PCA) using flowSOM 46 . EC are a rare population, therefore, multiple clustering numbers and random seeds were used to determine the robustness of detected endothelial cell clusters between samples. Data set size and variance were also taken into consideration; 500 clusters were used for all patient data samples. Clusters were then displayed using t-SNE. A query was implemented to identify EC containing clusters and later those were manually inspected for all samples.
One-way ANOVA or Mann-Whitney U-test was used for statistical analysis wherever it was appropriate and described in the figure legend. A Bayesian Mann-Whitney U-test was also used to provide a more trustworthy perspective than the traditional frequentist analysis for the associations between cEC and rejection. Data shown are means ± SEM. P-value ≤ 0.05 was considered significant. Correction of p-values for multiple comparisons was done using the Benjamini and Hochberg procedure for controlling the false discovery rate (FDR).

Data availability
The data that support the findings of this study are available on request from the corresponding author. www.nature.com/scientificreports/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.