ORIGINAL RESEARCH published: 07 January 2022 doi: 10.3389/fmed.2021.780585 A Prospective Multicenter Trial to Evaluate Urinary Metabolomics for Non-invasive Detection of Renal Allograft Rejection (PARASOL): Study Protocol and Patient Recruitment Miriam C. Banas 1*, Georg A. Böhmig 2 , Ondrej Viklicky 3,4 , Lionel P. Rostaing 5,6 , Thomas Jouve 5 , Lluis Guirado 7 , Carme Facundo 7 , Oriol Bestard 8 , Hermann-Josef Gröne 9 , Kazuhiro Kobayashi 10 , Vladimir Hanzal 4 , Franz Josef Putz 1 , Edited by: Daniel Zecher 1 , Tobias Bergler 1 , Sindy Neumann 11 , Victoria Rothe 11 , Tujin Shi, Amauri G. Schwäble Santamaria 11 , Eric Schiffer 11 and Bernhard Banas 1 Pacific Northwest National Laboratory 1 (DOE), United States Department of Nephrology, University Hospital Regensburg, Regensburg, Germany, 2 Division of Nephrology and Dialysis, Department of Medicine III, Medical University of Vienna, Vienna, Austria, 3 Transplant Laboratory, Institute for Clinical and Reviewed by: Experimental Medicine (IKEM), Prague, Czechia, 4 Department of Nephrology, Institute for Clinical and Experimental Medicine Michifumi Yamashita, (IKEM), Prague, Czechia, 5 Nephrology, Hemodialysis, Apheresis and Kidney Transplantation Department, Grenoble University Cedars Sinai Medical Center, Hospital, Grenoble, France, 6 Faculty of Health, Grenoble Alpes University, Grenoble, France, 7 Nephrology Department, United States Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB-Sant Pau), Medicine Department-Universitat Burkhard Tönshoff, Autónoma de Barcelona, REDinREN, Instituto de Investigación Carlos III, Barcelona, Spain, 8 Vall d’Hebron University Hospital Heidelberg University (HUVH), Vall d’Hebron Research Institute (VHIR), Barcelona, Spain, 9 Institute of Pharmacology, Philipps-University, Marburg, Hospital, Germany Germany, 10 Institute of Pharmacology, University of Marburg, Marburg, Germany, 11 numares AG, Regensburg, Germany Rong-Hai Deng, Sun Yat-sen University, China *Correspondence: Background: In an earlier monocentric study, we have developed a novel non-invasive Miriam C. Banas test system for the prediction of renal allograft rejection, based on the detection of a miriam.banas@ukr.de specific urine metabolite constellation. To further validate our results in a large real-world Specialty section: patient cohort, we designed a multicentric observational prospective study (PARASOL) This article was submitted to including six independent European transplant centers. This article describes the study Nephrology, a section of the journal protocol and characteristics of recruited better patients as subjects. Frontiers in Medicine Methods: Within the PARASOL study, urine samples were taken from renal transplant Received: 21 September 2021 recipients when kidney biopsies were performed. According to the Banff classification, Accepted: 01 December 2021 Published: 07 January 2022 urine samples were assigned to a case group (renal allograft rejection), a control group Citation: (normal renal histology), or an additional group (kidney damage other than rejection). Banas MC, Böhmig GA, Viklicky O, Results: Between June 2017 and March 2020, 972 transplant recipients were included Rostaing LP, Jouve T, Guirado L, Facundo C, Bestard O, Gröne H-J, in the trial (1,230 urine samples and matched biopsies, respectively). Overall, 237 Kobayashi K, Hanzal V, Putz FJ, samples (19.3%) were assigned to the case group, 541 (44.0%) to the control group, Zecher D, Bergler T, Neumann S, Rothe V, Schwäble Santamaria AG, and 452 (36.7%) samples to the additional group. About 65.9% were obtained from Schiffer E and Banas B (2022) A male patients, the mean age of transplant recipients participating in the study was 53.7 Prospective Multicenter Trial to ± 13.8 years. The most frequently used immunosuppressive drugs were tacrolimus Evaluate Urinary Metabolomics for Non-invasive Detection of Renal (92.8%), mycophenolate mofetil (88.0%), and steroids (79.3%). Antihypertensives and Allograft Rejection (PARASOL): Study antidiabetics were used in 88.0 and 27.4% of the patients, respectively. Approximately Protocol and Patient Recruitment. Front. Med. 8:780585. 20.9% of patients showed the presence of circulating donor-specific anti-HLA IgG doi: 10.3389/fmed.2021.780585 antibodies at time of biopsy. Most of the samples (51.1%) were collected within the first Frontiers in Medicine | www.frontiersin.org 1 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment 6 months after transplantation, 48.0% were protocol biopsies, followed by event-driven (43.6%), and follow-up biopsies (8.5%). Over time the proportion of biopsies classified into the categories Banff 4 (T-cell-mediated rejection [TCMR]) and Banff 1 (normal tissue) decreased whereas Banff 2 (antibody-mediated rejection [ABMR]) and Banff 5I (mild interstitial fibrosis and tubular atrophy) increased to 84.2 and 74.5%, respectively, after 4 years post transplantation. Patients with rejection showed worse kidney function than patients without rejection. Conclusion: The clinical characteristics of subjects recruited indicate a patient cohort typical for routine renal transplantation all over Europe. A typical shift from T-cellular early rejections episodes to later antibody mediated allograft damage over time after renal transplantation further strengthens the usefulness of our cohort for the evaluation of novel biomarkers for allograft damage. Keywords: kidney transplant rejection, urinary metabolites, biomarker, NMR-spectroscopy, non-invasive test INTRODUCTION value of 0.84 when combining metabolomic analysis and corresponding estimated glomerular filtration rate (eGFR) values Despite a steady improvement of patient and organ survival at time of urine sampling (8). after renal transplantation, allograft rejection continues to pose The subsequently following PARASOL study presented here a risk of graft damage. In the first week and month after is an open, international, multicenter, prospective, observational transplantation, T-cell-mediated rejection (TCMR) in particular study, in which the diagnostic accuracy for the urinary metabolite is more common, while later antibody-mediated rejection constellation initially assessed in the UMBRELLA study will (ABMR) accounts for the majority of immunological graft be validated in an independent cohort resembling the routine damages (1, 2). kidney transplantation programs in six different European Changes in kidney function, a decrease in urine output, or an transplant centers. The study is based on a reasonable number increase in proteinuria may reflect transplant rejection during of patients recruited with their respective urine samples and routine clinical patient care. Kidney biopsies are still current renal allograft biopsies, such as both protocol and event- gold standard for diagnosing an allograft rejection, but as an driven biopsies. invasive procedure it carries the risk of bleeding and other complications. The latter limits the routine use of serial biopsies, and the diagnosis of rejection is often made at an advanced stage MATERIALS AND METHODS of irreversible tissue injury. At many transplant units, protocol biopsies have been introduced to potentially detect the acute Study Design rejection already in a sub-clinical state (3). However, with serial Urine samples were taken from adult (≥18 years) renal or biopsies, it is unlikely that all rejection episodes will be detected combined renal and pancreas transplant patients prior to a upon onset, not to speak of complications associated with such a kidney biopsy that was performed according to local center costly approach (4). standards as protocol or event-driven biopsies. The target Biomarkers in the urine could help to detect rejections population is thus within the clinical routine and planned early and non-invasively, whereby an appropriate sensitivity and for renal allograft biopsies. The patient population consists of specificity as well as a quick diagnosis are necessary for the patients recruited at least 14 days after transplantation. To clinical routine (5, 6). ensure broad real-world spectrum of biopsy results, all patients Recently, we developed a novel, non-invasive method to scheduled for a renal allograft biopsy were screened for eligibility. detect the graft rejection via a characteristic constellation of the Between June 2017 and March 2020, 972 transplant recipients urine metabolites alanine, citrate, lactate, and urea investigated were included (1,230 urine samples and matched biopsies, by NMR spectroscopy (7). In a first monocentric prospective respectively). According to biopsy results, patients were observational (UMBRELLA) study which included 109 patients, retrospectively assigned to a case group [Banff category 2 the test performance reached an area under the curve (AUCROC ) (ABMR) or 4 (TCMR), either alone or in combination with other findings (other non-rejection changes)], a control group [(no rejection): Banff categories 1 (normal biopsy), 5I (mild Abbreviations: ABMR, antibody-mediated rejection; AUCROC , area under the interstitial fibrosis and atrophy (IFTA)], and an additional group ROC curve, CKD, chronic kidney disease; DSA, donor-specific anti-HLA IgG [Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), antibodies; eGFR, estimated glomerular filtration rate; NMR, nuclear magnetic resonance spectroscopy; ROC, receiver operating characteristic; TCMR, T-cell- 5III (severe IFTA), or 6 (other non-rejection changes)]. Criteria mediated rejection; MFI, mean fluorescene intensity; MMF, mycofenolate mofetil; for subject categorization—based on the rules of the Banff MPA, mycophenolic acid. classification—are detailed in Figure 1. Frontiers in Medicine | www.frontiersin.org 2 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment FIGURE 1 | Study sequence. Patients who received a kidney or kidney and pancreas transplantation ≥14 days prior were selected according to the inclusion criteria of the PARASOL study. After informed consent discussion and signed informed consent form, the clinical data were recorded, the midstream urine sample was collected, and the kidney biopsy was taken within the clinical routine. According to biopsy results, patients were assigned either to a case group [Banff category 2 (antibody-mediated rejection [ABMR]) or 4 (T-cell-mediated rejection [TCMR]), either alone or in combination with other findings (other non-rejection changes)], a control group [(no rejection): Banff categories 1 (normal biopsy), 5I (mild interstitial fibrosis and atrophy (IFTA)], and an additional group [Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes)]. The study was then ended for the participant. Clinical routine shows that patients of the target population the study population. Therefore, a maximum of four biopsies may be biopsied several times. In this context, PARASOL per patient could be included in the study. The patients, collected data on the day of the examination (cross-sectional such as not willing to participate, with a bladder catheter in data), but did not take any data over time (longitudinal place, with a previous biopsy of the transplant within the last data) into account. This resulted in the possibility that some 3 days, already included four times in the study, and after patients were included in the study several times. These multi-organ transplantation other than kidney and pancreas, patients signed the informed consent forms again and new are excluded from the study. Respective clinical data (e.g., patient identification numbers were given (at a maximum date of transplantation, medication, donor-specific anti-HLA of four times). The study sequence is similar to an initial IgG antibodies (DSA), former rejections, and infections) were recruitment (Table 1). collected on the day of the examination and the urine sample To preclude an interaction between the biopsy procedure was taken immediately before the planned biopsy. The report of and the results of the NMR analysis samples were obtained the kidney histopathology analysis, as clinical reference standard, before biopsies and, in case of two or more sequential biopsies, was added to the study documentation after becoming available. a sufficiently large interval between the biopsies was defined Definition of DSA was done individually according to local center in the protocol to prevent possible blood residues in urine standards. The threshold for the positivity was defined as 800– affecting the NMR analysis of the second sample. In addition, 1,000 mean fluorescence intensity (MFI) depending on the local we defined an upper limit for re-recruitment of a patient. protocol and assay used. The centers used mixed and single The goal was to include an adequate number of patients to antigen (SAB) class I and class II bead assays. No follow-up get a representative reflection of the biological variance in appointments were planned for the study participants. Frontiers in Medicine | www.frontiersin.org 3 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment TABLE 1 | Examination matrix. Assessments to be performed On one day of the regular Later time Comment on timing examinations, ≥14 days after kidney transplantation Informed consent X Prior to any study procedure Demography (a) X Anamnesis (b) X Renal transplantation: ≥ 14 days before urine sample collection Last renal transplant biopsy: not within the last 3 days before sample collection. Last serum creatinine, Cystatin-C (optional), eGFR, CMV/ BKV Infection, Urinary tract infection: at day of (or max. 3 days prior to) urine sampling, during regular care (d) Inclusion/ exclusion criteria X Criteria at day of urine sampling Sampling of midstream urine X ≥14 days after renal transplantation, before scheduled transplant biopsy, during regular care Medication (c) X At time of urine sampling Renal transplant biopsy X At same day of urine sampling, at a time point after urine sampling, during regular care Biopsy result X Final status X (a) Age at enrollment (date of signed ICF), ethnicity, and sex. (b) Date of (last) renal transplantation, date of last renal transplant biopsy, last serum creatinine, last cystatin-C (optional), last estimated glomerular filtration rate (eGFR), existence of donor-specific antibodies (DSA), active CMV infection (based on CMV virus detection via PCR at the time of taking the urine sample), active BKV infection (based on polyoma virus detection in the blood of a patient via PCR testing at the time of taking the urine sample and/or direct staining of polyoma virus in the corresponding renal biopsy), active urinary tract infection, diabetes mellitus, hypertension, and underlying renal disease. (c) Immunosuppressants [tacrolimus, cyclosporine, steroids, mycofenolate mofetil (MMF)/mycophenolic acid (MPA), other immunosuppressants], antibiotics, antihypertensives, and antidiabetics. (d) If status was determined >3 days before urine sampling, it is considered as “N/A”. The study was approved by the local Ethics Committees of all measurements were carried out on a Bruker Avance II + 600 participating centers. The written informed consent was received MHz NMR-spectrometer as already described before (7). Using from participants prior to study inclusion. the Axinon R renalTX-SCORE R system, urinary metabolite quantification and test results were generated in a fully automated Kidney Biopsies manner. The resulting score correlates with the probability of The results of morphologic renal allograft evaluation were allograft rejection and ranges between 0 and 100 with low to high documented as the reference standard. The study included probability and is based on an NMR-based pattern encompassing protocol biopsies (as per local center protocol), event-driven the metabolites alanine, citrate, lactate, and urea. biopsies, as well as follow-up biopsies performed for monitoring of treatment responses. Specimens were evaluated in the context of center routine by experienced local renal pathologists Statistical Analysis Strategy following the rules of the 2018 Reference Guide to the Banff Statistical analyses were planned in two ways: a descriptive Classification of Renal Allograft Pathology (9). For analysis in analysis and a performance analysis. The former was to address relation to biomarker results, biopsies were grouped according to the patient data and highlight demographic facts using clinical Banff diagnostic categories as follows: (i) case group (rejection): data derived from the corresponding case report form (CRF). It Banff category 2 (ABMR) or 4 (TCMR), either alone or in was planned that important variables, such as sex, age, ethnicity, combination with other findings (other non-rejection changes) and various disease factors of the patients would be investigated. (ii) control group (no rejection): Banff categories 1 (normal Furthermore, all variables were considered to be used for the biopsy), 5I (mild IFTA) (iii) additional group: [Banff categories 3 performance analysis. (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), It was clear that it may be necessary to exclude patient or 6 (other non-rejection changes)], respectively. data from the performance analysis in case that technically no renalTX-SCORE output could be determined by NMR NMR-Analysis measurement. The performance analysis should use standard Spontaneous mid-stream urine samples were collected and methods and assess conventional parameters for evaluating the measured by NMR spectroscopy at numares AG (Regensburg, quality of the diagnostic patterns developed. Particular attention Germany). For this, a volume of 600 µl of each urine sample to the area under the receiver operating characteristic (ROC) was mixed with 150 µl of Axinon R urine additive solution in curve (AUCROC ), specificity, and sensitivity should be paid. a centrifuge tube. The samples were centrifuged at 20,000 g for In addition, certain subgroup performance analyses should be 10 min at 20◦ C, and 600 µl of the supernatant were transferred obtained in concerns of different cut-off values with regard to to 5 mm NMR tubes and kept at 2–6◦ C until measurement. All specificity and sensitivity. Frontiers in Medicine | www.frontiersin.org 4 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment Sample Size Estimation prove a difference between the AUCROC value of the developed The number of cases was based on the observed values for NMR-based tests and a minimum AUCROC (null hypothesis the AUCROC values of the NMR-based patterns obtained in H0 ) of 0.675 at the level of significance α = 5% with a power the UMBRELLA (8) study for the detection of acute renal of 80%. The percentage of positive biopsy results (prevalence allograft rejection (AUCROC = 0.75). In particular, the number of acute Banff 4 renal allograft rejection) in the UMBRELLA of cases in the multicenter validation should be large enough to collective was 27% (54/203 biopsies). The expected percentage TABLE 2 | Urine sample characteristics collected by the six different study centers. Total Barcelona Bel. Barcelona FP. Grenoble Praha Vienna Regensburg Number of Total 972 21 49 348 150 219 185 patients With one 790/972 (81.3%) 21/21 (100.0%) 47/49 (95.9%) 256/348 (73.6%) 138/150 (92.0%) 209/219 (95.4%) 119/185 (64.3%) urine sample With multiple 182/972 (18.7%) 0/21 (0.0%) 2/49 (4.1%) 92/348 (26.4%) 12/150 (8.0%) 10/219 (5.6%) 66/185 (35.7%) urine samples Number of Total 1,230 21 51 479 164 229 286 urine samples Urine samples Mean 1.3 1.0 1.0 1.4 1.1 1.0 1.5 per patient Status Case 237/1,230 (19.3%) 1/21 (4.8%) 4/51 (7.8%) 73/479 (15.2%) 60/164 (36.6%) 41/229 (17.9%) 58/286 (20.3%) Control 541/1,230 (44.0%) 15/21 (71.4%) 23/51 (45.1%) 260/479 (54.3%) 34/164 (20.7%) 96/229 (41.9%) 113/286 (39.5%) Additional 452/1,230 (36.7%) 5/21 (23.8%) 24/51 (47.1%) 146/479 (30.5%) 70/164 (42.7%) 92/229 (40.2%) 115/286 (40.2%) Age Range 19–84 37–78 26–75 21–84 21–82 20–79 19–84 Mean ± SD 53.7 ± 13.8 58.7 ± 11.1 55.0 ± 13.3 54.2 ± 14.9 53.2 ± 13.2 54.3 ± 12.8 52.3 ± 13.2 Sex Male 810/1,230 (65.9%) 12/21 (57.1%) 26/51 (51.0%) 311/479 (64.9%) 116/164 (70.7%) 151/229 (65.9%) 194/286 (67.8%) Female 420/1,230 (34.1%) 9/21 (42.9%) 25/51 (49.0%) 168/479 (35.1%) 48/164 (29.3%) 78/229 (34.1%) 92/286 (32.2%) Ethnicity African 24/1,230 (2.0%) 0/21 (0.0%) 1/51 (2.0%) 21/479 (4.4%) 0/164 (0.0%) 2/229 (0.9%) 0/286 (0.0%) Asian 8/1,230 (0.7%) 0/21 (0.0%) 0/51 (0.0%) 6/479 (1.3%) 1/164 (0.6%) 1/229 (0.4%) 0/286 (0.0%) Caucasian 1,184/1,230 (96.3%) 21/21 (100.0%) 45/51 (88.2%) 450/479 (93.9%) 162/164 (98.8%) 226/229 (98.7%) 280/286 (97.9%) Other 13/1,230 (1.1%) 0/21 (0.0%) 5/51 (9.8%) 2/479 (0.4%) 0/164 (0.0%) 0/229 (0.0%) 6/286 (2.1%) Not specified 1/1,230 (0.1%) 0/21 (0.0%) 0/51 (0.0%) 0/479 (0.0%) 1/164 (0.6%) 0/229 (0.0%) 0/286 (0.0%) Biopsy reason Event-driven 536/1,230 (43.6%) 8/21 (38.1%) 15/51 (29.4%) 164/479 (34.2%) 114/164 (69.5%) 97/229 (42.4%) 138/286 (48.3%) Follow-up 104/1,230 (8.5%) 0/21 (0.0%) 1/51 (2.0%) 67/479 (14.0%) 0/164 (0.0%) 4/229 (1.7%) 32/286 (11.2%) Protocol 590/1,230 (48.0%) 13/21 (61.9%) 35/51 (68.6%) 248/479 (51.8%) 50/164 (30.5%) 128/229 (55.9%) 116/286 (40.6%) Time after TX ≤6 months 628/1,230 (51.1%) 8/21 (38.1%) 20/51 (39.2%) 238/479 (49.7%) 92/164 (56.1%) 113/229 (49.3%) 157/286 (54.9%) [6,12] months 132/1,230 (10.7%) 4/21 (19.0%) 15/51 (29.4%) 60/479 (12.5%) 16/164 (9.8%) 22/229 (9.6%) 15/286 (5.2%) [1,4] years 222/1,230 (18.0%) 6/21 (28.6%) 11/51 (21.6%) 86/479 (18.0%) 29/164 (17.7%) 59/229 (25.8%) 31/286 (10.8%) >4 years 248/1,230 (20.2%) 3/21 (14.3%) 5/51 (9.8%) 95/479 (19.8%) 27/164 (16.5%) 35/229 (15.3%) 83/286 (29.0%) Anamnesis Infections 175/1,230 (14.2%) 1/21 (4.8%) 5/51 (9.8%) 101/479 (21.1%) 16/164 (9.8%) 39/229 (17.0%) 13/286 (4.5%) Diabetes 364/1,230 (29.6%) 8/21 (38.1%) 9/51 (17.6%) 123/479 (25.7%) 56/164 (34.1%) 62/229 (27.1%) 106/286 (37.1%) Hypertension 1,092/1,230 (88.8%) 17/21 (81.0%) 48/51 (94.1%) 389/479 (81.2%) 149/164 (90.9%) 211/229 (92.1%) 278/286 (97.2%) Medication Tacrolimus 1,141/1,230 (92.8%) 20/21 (95.2%) 50/51 (98.0%) 429/479 (89.6%) 152/164 (92.7%) 216/229 (94.3%) 274/286 (95.8%) Cyclosporine 31/1,230 (2.5%) 0/21 (0.0%) 0/51 (0.0%) 8/479 (1.7%) 5/164 (3.0%) 11/229 (4.8%) 7/286 (2.4%) Steroids 975/1,230 (79.3%) 18/21 (85.7%) 51/51 (100.0%) 317/479 (66.2%) 156/164 (95.1%) 224/229 (97.8%) 209/286 (73.1%) MMF/MPA 1,082/1,230 (88.0%) 21/21 (100.0%) 42/51 (82.4%) 389/479 (81.2%) 138/164 (84.1%) 217/229 (94.8%) 275/286 (96.2%) Antibiotics 306/1,230 (24.9%) 4/21 (19.0%) 2/51 (3.9%) 107/479 (22.3%) 31/164 (18.9%) 83/229 (36.2%) 79/286 (27.6%) Antihyper- 1,083/1,230 (88.0%) 17/21 (81.0%) 48/51 (94.1%) 386/479 (80.6%) 147/164 (89.6%) 209/229 (91.3%) 276/286 (96.5%) tensives Antidiabetics 337/1,230 (27.4%) 8/21 (38.1%) 12/51 (23.5%) 123/479 (25.7%) 52/164 (31.7%) 62/229 (27.1%) 80/286 (28.0%) Overall and for each center respectively, the distribution for different subsets is shown. The numbers and relative frequencies in the categories status, age, sex, ethnicity, biopsy type, time after renal transplantation (TX), anamnesis, and medication refer to the number of urine samples. Infections include active CMV (based on CMV virus detection via PCR at the time of taking the urine sample), active BKV (based on polyoma virus detection in the blood of a patient via PCR testing at the time of taking the urine sample and/or direct staining of polyoma virus in the corresponding renal biopsy) and/or active urinary tract infections. Case group: Banff category 2 (ABMR [antibody-mediated rejection]) or 4 (T-cell-mediated rejection [TCMR]), either alone or in combination with other findings (other non-rejection changes); control group [(no rejection): Banff categories 1 (normal biopsy), 5I (mild interstitial fibrosis and atrophy (IFTA)]; additional group [Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes)]. For further clarification: by study design, at day of urine sample collection a biopsy was performed. Frontiers in Medicine | www.frontiersin.org 5 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment of positive biopsy results in the PARASOL study was therefore 90% and the respective specificity at 90% sensitivity and estimated to be 30%. Accordingly, 151 rejections (cases) and sensitivity at 90% specificity including the 95% CI for 334 controls were needed. The indicated number of cases was the exact definition of the NMR-based pattern to detect calculated using the MedCalc v.12.7.7.0-64 bit, observing a two- renal allograft rejection. In addition, for the cut-off values tailed binomial test with a power of 80%. To compensate for determined, the sensitivities and specificities in patients with the losses in recruiting, withdrawal of consent, insufficient urine Banff classification 3, 5II, 5III, and 6 will be determined quantities, losses, etc., a 15% safety margin was calculated so in a subgroup analysis if enough samples are available. that recruiting should include 174 cases: renal allograft rejection Furthermore, the demographic and clinical parameters will Banff 2, 4, either alone or in combination with other findings, be used to examine whether individual parameters or a group e.g., 2 + 6 or 4 + 6, and 384 controls: Banff classification 1 of these parameters are suitable for reliably predicting the and 5I. occurrence of renal allograft rejection in this large, non-stratified The estimated number of cases was exceeded with 237 cases patient group. instead of estimated 174 cases and 541 controls instead of the planned 384. RESULTS Primary Endpoint The primary endpoint of the study is the respective AUCROC In the context of PARASOL (multicenter observational value of the ROC curve for the NMR-based pattern. Acute renal prospective trial including six European transplant centers), allograft rejection is defined according to the Banff classification a total of 1,230 urine samples for metabolite evaluation and and categorized 2 (ABMR), 4 (TCMR), either alone or in corresponding histopathology results (972 patients; 1.3 samples combinations with other findings, e.g., 2 + 6 or 4 + 6. The per patient) were collected (recruitment period between June AUCROC values and their 95% CIs are determined as a measure 2017 and March 2020). of diagnostic accuracy. It should be tested whether the diagnostic Table 2 provides sample and patient characteristics for the accuracy is to be proven with an AUCROC value of at least 0.675 overall cohort and individual centers. Among 1,230 biopsy under the assumption that the observed AUCROC value itself specimens, 237 samples (19.3%) were assigned to the case group, is 0.75. 541 to the control group (44.0%), and 452 (36.7%) samples were assigned to the additional group. Overall, 810 samples (65.9%) Secondary Endpoint were obtained from male patients and 420 (34.1%) from female As a secondary endpoint, the recruited collective will patients. The mean recipient age at the time of study inclusion be analyzed with respect to the determination of cut- was 53.7 ± 13.8 years (range 19–84 years) and most of the off values associated with a sensitivity and specificity of patients were Caucasian (96.3%). FIGURE 2 | Distribution of the reasons for biopsy. Relative frequencies are displayed for the total number of samples (irrespective of the group assignment), as well as for each of the status groups. Case group: Banff category 2 (ABMR) or 4 (TCMR), either alone or in combination with other non-rejection changes; Control group: Banff categories 1 (normal biopsy), 5I (mild IFTA); Additional group: Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes). Frontiers in Medicine | www.frontiersin.org 6 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment Tacrolimus (92.8%), mycophenolate mofetil (88.0%), and steroids (79.3%) were the most frequently used immunosuppressive drugs. Antihypertensives and antidiabetics were used in 88.0 and 27.4% of the patients, respectively. About 88.8% of patients suffered from hypertension, 29.6% were diabetics, and 14.2% had any infection (BKV, CMV, or urinary tract infection) at the time of inclusion into the study. Of the 1,230 urine samples, 628 (51.1%) were collected within the first 6 months after transplantation, 132 (10.7%) between 6 and 12 months, 222 (18.0%) between 1 and 4 years, and 248 (20.2%) more than 4 years after transplantation. Most of the samples [590 (48.0%)] were in the context of protocol biopsies, followed by event-driven biopsies [536 (43.6%)], and follow-up biopsies [104 (8.5%)]. The distribution of biopsy types for case, control, and additional group differed in the groups. In the case group, 62.9% event-driven biopsies were noted, 24.1% protocol biopsies, and 13.1% follow-up biopsies. In the control group, 71.3% protocol biopsies, 23.1% event- driven biopsies, and 5.5% follow-up biopsies were seen. The additional group consisted of 58.0% event-driven biopsies, 32.5% protocol biopsies, and 9.5% follow-up FIGURE 3 | Distribution of the status groups. Relative frequencies are derived biopsies (Figure 2 and Supplementary Table S1). Additionally from the total number of samples. Case group: Banff category 2 (ABMR) or 4 Supplementary Figure S1 and Supplementary Table S2 show (TCMR), either alone or in combination with other findings (other non-rejection the distribution of the case, control, and additional groups changes); control group [(no rejection): Banff categories 1 (normal biopsy), 5I (mild IFTA); additional group (Banff categories 3 (suspicious for TCMR), 5II within each of the three biopsy reasons: event-driven, follow-up, (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes)]. and protocol. Distribution of Banff Categories Within Case (Rejection), Control, and Additional a large group of rejections with 42.0% already within the Group first 6 months post transplantation. With increasing time post- Most of the biopsies (44.0%) were assigned to the control transplantation, the proportion of antibody mediated rejection group, corresponding histopathology showed classification into increased up to 84.2% (after 4 years). TCMR (Banff 4 and the Banff categories 1 (normal biopsy) (28.0% out of all biopsies) Banff 4 + x) decreased from 50.7 to 11.8% over time. The and Banff 5I (mild IFTA) (16.0% out of all biopsies) for the largest combination of both stayed stable with 7.3% and 4.0% (Figure 5A proportion of findings, followed by other combinations (15.2%) and Supplementary Table S4). and allograft fibrosis classified as Banff grades 5 II (moderate In the control group within the first 6 months, most biopsy IFTA) and III (severe IFTA) (10.0%) both belonging to the samples were assigned to Banff 1 (70.8%), whereas after 4 years, additional group (Figure 3 and Supplementary Table S3). almost 75% of biopsies of the control group were classified as Within the group of rejection, ABMR (Banff 2) represented Banff 5I (Figure 5B and Supplementary Table S4). the largest proportion (64.6%), followed by TCMR (Banff In the additional group, the proportion of borderline 4: 30.4%). Combined ABMR and TCMR was infrequent rejections (Banff 3) decreased from 21.5 to 2.4% over time, (5.1%) (Figure 4 and Supplementary Table S3). The control whereas the amount of graft fibrosis represented by Banff group showed further a higher proportion of Banff 1 (63.6%) 5II and III findings increased to 33.6% (Figure 5C and than of Banff 5I (36.4%) graded biopsies (Figure 4 and Supplementary Table S4). Supplementary Table S3). In the additional group, the highest proportion of pathology findings belongs to other combinations Detection of Donor-Specific Antibodies (41.4%), Banff 5II and III (27.2%), followed by Banff 6 (17.0%) (DSA) Dependent on Sample Classification and Banff 3 (14.4%) (Figure 4 and Supplementary Table S3). and Banff Categories For 257 of the 1,230 samples, positive corresponding DSA results Type of Renal Allograft Rejections were documented (20.9%) (Table 3). Within the case group for Dependent From Time After 43.5% of the samples (103/237), DSAs were noted. 84 from Transplantation these samples (81.6%) showed ABMR (Banff 2). Simultaneous Within the case group, ABMR classified as Banff 2 category presence of DSA in blood was documented for only 80/541 (either isolated or in combination with other lesions) represented samples (14.8%) from the control group patients. Therein, in Frontiers in Medicine | www.frontiersin.org 7 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment FIGURE 4 | Distribution of Banff categories among the case, control, and additional group. Case group: Banff category 2 (ABMR) or 4 (TCMR), either alone or in combination with other non-rejection changes; Control group: Banff categories 1 (normal biopsy), 5I (mild IFTA); Additional group: Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes). the subgroup associated with Banff 1 findings in the biopsy DISCUSSION 46/80 (57.5%) samples corresponded to patients with DSA, in the subgroup with Banff 5I lesion, the rate was 34/80 (42.5%). For patients with end stage renal disease, kidney transplantation In the additional group, 74/452 (16.4%) samples were associated is the renal replacement therapy of choice as it significantly with DSA. improves the life quality and life expectancy (10). However, by far not all suitable patients can be offered a donor kidney as both post-mortal and living kidney donation are limited. With the observed increase in patients in the majority of countries Distribution of Chronic Kidney Disease worldwide suffering from renal disease, the gap between donor (CKD) Stages Among Status, Time After kidneys available and renal transplantation needed is more and Renal Transplantation, and Recipient Age more widening (11–13). One of the reasons of this observation Kidney function was seen to be dependent on the status is that renal allograft survival is limited and often shorter as (case/control/additional), time after transplantation, and the the survival of recipient. In consequence, increasing numbers of recipient age. patients with end stage renal disease need more than only one Regarding the severity of CKD of the study population, kidney transplantation and in countries with a very high rate patients with allograft rejections and from the additional of post-mortal organ donors, such as Spain, loss of a previous group showed significantly worse kidney function than controls allograft is nowadays one of the main causes for listing patients (samples 318 corresponding with CKD stage 4 or 5 32.9% in for renal transplantation (14–23)1 . cases vs. 11.4% in controls vs. 32.6% in the additional group; Therefore, one of the major goals in transplant medicine Table 4). Whereas control group samples were associated with is to prolong the time of allograft survival, especially as good allograft function up to 4 years, case group samples more and more allografts with extended donor criteria have and additional group samples corresponded with worse kidney to be used to overcome organ shortage (2, 24–28). Despite function (Table 4). major improvements in transplant patient care and therein With regards to the allograft recipient age, it could be seen immunosuppressive treatment, acute and chronic rejection that controls showed a better renal function within all age groups processes often irreversibly damaging renal allograft tissues are compared with cases and samples from the additional group (Table 5). 1 http://www.registrorenal.es/ Frontiers in Medicine | www.frontiersin.org 8 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment FIGURE 5 | Banff category distribution in concerns of time after renal transplantation (A) in the case group, (B) in the control group, and (C) in the additional group. Case group: Banff category 2 (ABMR) or 4 (TCMR), either alone or in combination with other non-rejection changes; Control group: Banff categories 1 (normal biopsy), 5I (mild IFTA); Additional group: Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes). Frontiers in Medicine | www.frontiersin.org 9 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment TABLE 3 | Existence of donor-specific anti-HLA IgG antibodies (DSA) in the status groups and each of the Banff categories. Total DSA negative DSA positive DSA not specified Number of samples 1,230 802 257 171 Status: case Total 237 106/237 (44.7%) 103/237 (43.5%) 28/237 (11.8%) Banff 2 153/237 (64.6%) 45/153 (29.4%) 84/153 (54.9%) 24/153 (15.7%) Banff 2 + 4 12/237 (5.1%) 5/12 (41.7%) 7/12 (58.3%) 0/12 (0.0%) Banff 4 72/237 (30.4%) 56/72 (77.8%) 12/72 (16.7%) 4/72 (5.6%) Status: control Total 541 395/541 (73.0%) 80/541 (14.8%) 66/541 (12.2%) Banff 1 344/541 (63.6%) 258/344 (75.0%) 46/344 (13.4%) 40/344 (11.6%) Banff 5I 197/541 (36.4%) 137/197 (69.5%) 34/197 (17.3%) 26/197 (13.2%) Status: additional Total 452 301/452 (66.6%) 74/452 (16.4%) 77/452 (17.0%) Banff 3 65/452 (14.4%) 41/65 (63.1%) 15/65 (23.1%) 9/65 (13.8%) Banff 5II, 5III 123/452 (27.2%) 68/123 (55.3%) 27/123 (22.0%) 28/123 (22.8%) Banff 6 77/452 (17.0%) 58/77 (75.3%) 4/77 (5.2%) 15/77 (19.5%) Other 187/452 (41.4%) 134/187 (71.7%) 28/187 (15.0%) 25/187 (13.4%) Relative frequencies are derived from the respective total number of samples in the three status groups. The order of the Banff categories is based on the assignment to case, control, and additional. Case group: Banff category 2 (ABMR) or 4 (TCMR), either alone or in combination with other non-rejection changes; Control group: Banff categories 1 (normal biopsy), 5I (mild IFTA); Additional group: Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes). TABLE 4 | Distribution of chronic kidney disease (CKD) stages among status groups and time after renal transplantation (TX). Total CKD Stage 1 CKD Stage 2 CKD Stage 3A CKD Stage 3B CKD Stage 4 CKD Stage 5 CKD Stage not specified Number of samples 1,230 34 193 253 288 235 52 175 Status: Total 237 2/237 (0.8%) 31/237 (13.1%) 36/237 (15.2%) 62/237 (26.2%) 58/237 (24.5%) 20/237 (8.4%) 28/237 (11.8%) case ≤6 months 69/237 (29.1%) 1/69 (1.4%) 16/69 (23.2%) 9/69 (13.0%) 19/69 (27.5%) 10/69 (14.5%) 7/69 (10.1%) 7/69 (10.1%) [6,12] months 23/237 (9.7%) 1/23 (4.3%) 3/23 (13.0%) 2/23 (8.7%) 7/23 (30.4%) 6/23 (26.1%) 2/23 (8.7%) 2/23 (8.7%) [1,4] years 69/237 (29.1%) 0/69 (0.0%) 9/69 (13.0%) 11/69 (15.9%) 19/69 (27.5%) 20/69 (29.0%) 2/69 (2.9%) 8/69 (11.6%) >4 years 76/237 (32.1%) 0/76 (0.0%) 3/76 (3.9%) 14/76 (18.4%) 17/76 (22.4%) 22/76 (28.9%) 9/76 (11.8%) 11/76 (14.5%) Status: Total 541 22/541 (4.1%) 115/541 (21.3%) 137/541 (25.3%) 116/541 (21.4%) 52/541 (9.6%) 10/541 (1.8%) 89/541 (16.5%) control ≤6 months 373/541 (68.9%) 15/373 (4.0%) 88/373 (23.6%) 110/373 (29.5%) 83/373 (22.3%) 28/373 (7.5%) 7/373 (1.9%) 42/373 (11.3%) [6,12] months 62/541 (11.5%) 4/62 (6.5%) 12/62 (19.4%) 12/62 (19.4%) 12/62 (19.4%) 7/62 (11.3%) 1/62 (1.6%) 14/62 (22.6%) [1,4] years 59/541 (10.9%) 3/59 (5.1%) 10/59 (16.9%) 10/59 (16.9%) 10/59 (16.9%) 6/59 (10.2%) 1/59 (1.7%) 19/59 (32.2%) >4 years 47/541 (8.9%) 0/47 (0.0%) 5/47 (10.6%) 5/47 (10.6%) 11/47 (23.4%) 11/47 (23.4%) 1/47 (2.1%) 14/47 (29.8%) Status: Total 452 10/452 (2.2%) 47/452 (10.4%) 80/452 (17.7%) 110/452 (24.3%) 125/452 (27.7%) 22/452 (4.9%) 58/452 (12.8%) additional ≤ 6 months 186/452 (41.2%) 7/186 (3.8%) 26/186 (14.0%) 35/186 (18.8%) 54/186 (29.0%) 46/186 (24.7%) 9/186 (4.8%) 9/186 (4.8%) [6,12] months 47/452 (10.4%) 3/47 (6.4%) 5/47 (10.6%) 13/47 (27.7%) 7/47 (14.9%) 9/47 (19.1%) 4/47 (8.5%) 6/47 (12.8%) [1,4] years 94/452 (20.8%) 0/94 (0.0%) 7/94 (7.4%) 17/94 (18.1%) 27/94 (28.7%) 25/94 (26.6%) 3/94 (3.2%) 15/94 (16.0%) >4 years 125/452 (27.7%) 0/125 (0.0%) 9/125 (7.2%) 15/125 (12.0%) 22/125 (17.6%) 45/125 (36.0%) 6/125 (4.8%) 28/125 (22.4%) The relative frequencies are derived from the respective total number of samples in each status group. However, the relative frequencies for each time after transplantation category in the respective status groups are computed using the total number of samples in the respective time after transplantation category. Samples that did not have an eGFR value assigned are included in the “CKD not specified” group. Case group: Banff category 2 (ABMR) or 4 (TCMR), either alone or in combination with other non-rejection changes; Control group: Banff categories 1 (normal biopsy), 5I (mild IFTA); Additional group: Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes). still a major risk for premature allograft loss (1, 2, 29). Strategies more important and look very promising to become routine in to completely prevent allograft rejection are still missing, the future, however, so far in many countries, this technique is and diagnostic procedures for early detection of rejection are not available due to its costs not routinely covered by medical still suboptimal. insurance companies. Until now, a histopathological evaluation of a renal allograft Several biomarkers have been previously described mainly in biopsy is the gold standard to detect the cause of an allograft blood samples to detect allograft damage without performing malfunction after extra renal problems, such as perfusion renal biopsies, and costs and insufficient proof of usefulness deficits or urinary obstruction could be ruled out (1, 3, 4). under routine conditions are among the reasons for only limited Molecular analyses of renal tissue samples become more and use in daily clinical practice so far (5, 6, 30–35). Frontiers in Medicine | www.frontiersin.org 10 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment TABLE 5 | Distribution of CKD stages in different age groups shown for case, control and additional group. Total 19–29 years 30–39 years 40–49 years 50–59 years 60–69 years 70–79 years 80–84 years Number of samples 1,230 73 141 243 306 297 158 12 Status: Total 237 27/237 (11.4%) 27/237 (11.4%) 66/237 (27.8%) 48/237 (20.3%) 48/237 (20.3%) 18/237 (7.6%) 3/237 (1.3%) case CKD Stage 1 2/237 (0.8%) 0/2 (0.0%) 1/2 (50.0%) 1/2 (50.0%) 0/2 (0.0%) 0/2 (0.0%) 0/2 (0.0%) 0/2 (0.0%) CKD Stage 2 31/237 (13.1%) 9/31 (29.0%) 3/31 (9.7%) 12/31 (38.7%) 4/31 (12.9%) 2/31 (6.5%) 1/31 (3.2%) 0/31 (0.0%) CKD Stage 3A 36/237 (15.2%) 6/36 (16.7%) 6/36 (16.7%) 11/36 (30.6%) 6/36 (16.7%) 6/36 (16.7%) 1/36 (2.8%) 0/36 (0.0%) CKD Stage 3B 62/237 (26.2%) 7/62 (11.3%) 7/62 (11.3%) 14/62 (22.6%) 12/62 (19.4%) 16/62 (25.8%) 5/62 (8.1%) 1/62 (1.6%) CKD Stage 4 58/237 (24.5%) 5/58 (8.6%) 8/58 (13.8%) 12/58 (20.7%) 12/58 (20.7%) 12/58 (20.7%) 7/58 (12.1%) 2/58 (3.4%) CKD Stage 5 20/237 (8.4%) 0/20 (0.0%) 0/20 (0.0%) 8/20 (40.0%) 6/20 (30.0%) 5/20 (25.0%) 1/20 (5.0%) 0/20 (0.0%) CKD Stage not 28/237 (11.8%) 0/28 (0.0%) 2/28 (7.1%) 8/28 (28.6%) 8/28 (28.6%) 7/28 (25.0%) 3/28 (10.7%) 0/28 (0.0%) specified Status: Total 541 22/541 (4.1%) 64/541 (11.8%) 96/541 (17.7%) 140/541 (25.9%) 139/541 (25.7%) 75/541 (13.9%) 5/541 (0.9%) control CKD Stage 1 22/541 (4.1%) 3/22 (13.6%) 7/22 (31.8%) 2/22 (9.1%) 5/22 (22.7%) 5/22 (22.7%) 0/22 (0.0%) 0/22 (0.0%) CKD Stage 2 115/541 (21.3%) 6/115 (5.2%) 22/115 (19.1%) 25/115 (21.7%) 27/115 (23.5%) 23/115 (20.0%) 10/115 (8.7%) 2/115 (1.7%) CKD Stage 3A 137/541 (25.3%) 4/137 (2.9%) 16/137 (11.7%) 22/137 (16.1%) 46/137 (33.6%) 33/137 (24.1%) 15/137 (10.9%) 1/137 (0.7%) CKD Stage 3B 116/541 (21.4%) 5/116 (4.3%) 7/116 (6.0%) 17/116 (14.7%) 25/116 (21.6%) 37/116 (31.9%) 24/116 (20.7%) 1/116 (0.9%) CKD Stage 4 52/541 (9.6%) 2/52 (3.8%) 4/52 (7.7%) 10/52 (19.2%) 10/52 (19.2%) 15/52 (28.8%) 10/52 (19.2%) 1/52 (1.9%) CKD Stage 5 10/541 (1.8%) 0/10 (0.0%) 0/10 (0.0%) 1/10 (10.0%) 2/10 (20.0%) 4/10 (40.0%) 3/10 (30.0%) 0/10 (0.0%) CKD Stage not 89/541 (16.5%) 2/89 (2.2%) 8/89 (9.0%) 19/89 (21.3%) 25/89 (28.1%) 22/89 (24.7%) 13/89 (14.6%) 0/89 (0.0%) specified Status: Total 452 24/452 (5.3%) 50/452 (11.1%) 81/452 (17.9%) 118/452 (26.1%) 110/452 (24.3%) 65/452 (14.4%) 4/452 (0.9%) additional CKD Stage 1 10/452 (2.2%) 3/10 (30.0%) 1/10 (10.0%) 3/10 (30.0%) 2/10 (20.0%) 1/10 (10.0%) 0/10 (0.0%) 0/10 (0.0%) CKD Stage 2 47/452 (10.4%) 4/47 (8.5%) 11/47 (23.4%) 6/47 (12.8%) 16/47 (34.0%) 6/47 (12.8%) 4/47 (8.5%) 0/47 (0.0%) CKD Stage 3A 80/452 (17.7%) 4/80 (5.0%) 10/80 (12.5%) 22/80 (27.5%) 20/80 (25.0%) 13/80 (16.2%) 11/80 (13.8%) 0/80 (0.0%) CKD Stage 3B 110/452 (24.3%) 4/110 (3.6%) 8/110 (7.3%) 19/110 (17.3%) 30/110 (27.3%) 32/110 (29.1%) 17/110 (15.5%) 0/110 (0.0%) CKD Stage 4 125/452 (27.7%) 3/125 (2.4%) 10/125 (8.0%) 20/125 (16.0%) 32/125 (25.6%) 37/125 (29.6%) 20/125 (16.0%) 3/125 (2.4%) CKD Stage 5 22/452 (4.9%) 0/22 (0.0%) 4/22 (18.2%) 3/22 (13.6%) 4/22 (18.2%) 6/22 (27.3%) 4/22 (18.2%) 1/22 (4.5%) CKD Stage not 58/452 (12.8%) 6/58 (10.3%) 6/58 (10.3%) 8/58 (13.8%) 14/58 (24.1%) 15/58 (25.9%) 9/58 (15.5%) 0/58 (0.0%) specified Within each of the status groups, the bold numbers and relative frequencies refer to the total number of samples in that group. However, the relative frequencies for each age group in the respective CKD stages are calculated using the total number of samples in the respective age group within the status group. Samples that did not have an eGFR value assigned are included in the CKD “not specified” group. Case group: Banff category 2 (ABMR) or 4 (TCMR), either alone or in combination with other non-rejection changes; Control group: Banff categories 1 (normal biopsy), 5I (mild IFTA); Additional group: Banff categories 3 (suspicious for TCMR), 5II (moderate IFTA), 5III (severe IFTA), or 6 (other non-rejection changes). A characteristic urinary metabolite constellation for the Additionally, all treatment strategies, i.e., for immunosuppressive detection of TCMR in renal allografts has been previously therapy, concomitant medication, routine follow-up visits, and described by our group (7, 8). In combination with the eGFR renal biopsy, were on purpose not standardized to recruit values of patient, this test was previously proposed as a valuable a study population typical for renal transplant recipients all support in biopsy decision-making and routine follow-up after over Europe. renal transplantation. However, so far two main reasons limit Successful recruitment of the study is described here along the use of this test system in the clinic. The one is that all with an in-depth analysis of the study population, urine samples results generated so far were based on single center studies. The collected and correlation of these with biopsy findings, and second reason is that the original cohort used to develop the analyses for the presence of donor specific antibodies in blood test system was dominated by cellular rejections as these could samples of the allograft recipients at the time of renal biopsies. be easily diagnosed in corresponding kidney biopsies at the time All biopsies were evaluated by experienced renal pathologists of development. according to the Banff classification systematics. Taking clinical To overcome these limitations, the PARASOL study was findings, laboratory values, and histopathological results into initiated as a further completely independent validation study. account, the patients were grouped by the investigators into Major aims of the PARASOL study were evaluation of the test so called “cases,” “controls,” and “additional,” respectively. This system completely under routine conditions in six large, different will allow not only to discriminate rejecting from non-rejecting European transplant centers. All centers were completely allografts. With this strategy, changes in the urine metabolome free in including suitable patients transplanted with donor can be also correlated with pre-existing, i.e., donor-derived organs retrieved as usually done in the respective country. and de novo allograft damages over time and of all types, Frontiers in Medicine | www.frontiersin.org 11 January 2022 | Volume 8 | Article 780585 Banas et al. Parasol Study Design and Recruitment such as cellular and antibody mediated acute and chronic AUTHOR CONTRIBUTIONS allograft lesions. The complete documentation of 1,230 urine samples MB, GB, OV, LR, SN, ES, and BB designed the study. LG, along with corresponding histopathology reports and blood OB, and H-JG gave conceptual advice to the study protocol analyses for donor specific antibodies from 972 different and the enrollment strategy. MB, GB, OV, LR, LG, OB, and patients (approximately one third of them with rebiopsies BB were local principal investigators for the participating during the study), will allow to evaluate the urinary transplant centers and enrolled together with their study metabolite changes for a wide variety of different allograft personnel all participating patients. H-JG and KK gave advice damages alone or in combination and with different severity, on histopathological evaluation and classification of renal biopsy all being representative for typical patient courses after findings. MB, SN, VR, AS, TJ, CF, DZ, TB, FP, VH, and ES renal transplantation. collected study material and data and were responsible for raw Future goals for the test progress are the validation of data controls. SN, VR, AS, and ES supervised and evaluated previous findings in an actual multicenter setting, detection metabolomic analyses and performed statistical evaluations. MB and differentiating antibody-mediated rejection from cellular and BB wrote the manuscript. All authors evaluated study data rejection and recognition of potential disruptive factors other and contributed to the writing of the manuscript. causes of allograft damage. In conclusion, the clinical part of the PARASOL study as an FUNDING international, multicenter study representative for typical renal transplant patients in Europe could be finished successfully. All This study was sponsored by numares AG. urine samples, renal biopsy pathology results, and biographic and clinical patient data are validated and now available for further ACKNOWLEDGMENTS spectroscopic and metabolomic analyses. We would like to thank Lydia Walkowski for her meticulous DATA AVAILABILITY STATEMENT collection of patient data and samples, Stefanie Kühn and Torsten Schramm for their great work in data entry, and Markus The raw data supporting the conclusions of this article will be Fuhrmann and Christiane Kiske from numares for excellent made available by the authors, without undue reservation. technical assistance. We would also like to thank the study coordinators and nurses from all centers who helped with ETHICS STATEMENT sample management. The studies involving human participants were reviewed and SUPPLEMENTARY MATERIAL approved by University Regensburg (principal investigator #16- 315-101) and Local Ethics Committees. The patients/participants The Supplementary Material for this article can be found provided their written informed consent to participate in online at: https://www.frontiersin.org/articles/10.3389/fmed. this study. 2021.780585/full#supplementary-material REFERENCES characteristic for kidney allograft rejection. Metabolomics. (2018) 14:116. doi: 10.1007/s11306-018-1419-8 1. Nankivell BJ, Alexander SI. Rejection of the kidney allograft. N Engl J Med. 8. Banas MC, Neumann S, Pagel P, Putz FJ, Krämer BK, Böhmig GA, et al. A (2010) 363:1451–62. doi: 10.1056/NEJMra0902927 urinary metabolite constellation to detect acute rejection in kidney allografts. 2. Hariharan S, Israni AK, Danovitch G. Long-term survival EBioMedicine. (2019) 48:505–12. doi: 10.1016/j.ebiom.2019.10.007 after kidney transplantation. N Engl J Med. (2021) 385:729– 9. Roufosse C, Simmonds N, Clahsen-van Groningen M, Haas M, 43. doi: 10.1056/NEJMra2014530 Henriksen KJ, Horsfield C, et al. A 2018 Reference guide to the 3. 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Impact of dialysis modality The remaining authors declare that the research was conducted in the absence of on morbimortality of kidney transplant recipients after allograft failure. any commercial or financial relationships that could be construed as a potential Analysis in the presence of competing events. Nefrologia. (2021) 41:200– conflict of interest. 9. doi: 10.1016/j.nefro.2020.12.007 24. Noble J, Jouve T, Malvezzi P, Süsal C, Rostaing L. Transplantation Publisher’s Note: All claims expressed in this article are solely those of the authors of marginal organs: immunological aspects and therapeutic perspectives in kidney transplantation. Front Immunol. (2019) and do not necessarily represent those of their affiliated organizations, or those of 10:3142. doi: 10.3389/fimmu.2019.03142 the publisher, the editors and the reviewers. Any product that may be evaluated in 25. Port FK, Bragg-Gresham JL, Metzger RA, Dykstra DM, Gillespie this article, or claim that may be made by its manufacturer, is not guaranteed or BW, Young EW, et al. Donor characteristics associated with reduced endorsed by the publisher. graft survival: an approach to expanding the pool of kidney donors. Transplantation. (2002) 74:1281–6. doi: 10.1097/00007890-200211150- Copyright © 2022 Banas, Böhmig, Viklicky, Rostaing, Jouve, Guirado, Facundo, 00014 Bestard, Gröne, Kobayashi, Hanzal, Putz, Zecher, Bergler, Neumann, Rothe, 26. Aubert O, Kamar N, Vernerey D, Viglietti D, Martinez F, Duong-Van-Huyen Schwäble Santamaria, Schiffer and Banas. This is an open-access article distributed JP, et al. Long term outcomes of transplantation using kidneys from expanded under the terms of the Creative Commons Attribution License (CC BY). The use, criteria donors: prospective, population based cohort study. BMJ. (2015) distribution or reproduction in other forums is permitted, provided the original 351. doi: 10.1136/bmj.h3557 author(s) and the copyright owner(s) are credited and that the original publication 27. Sung RS, Guidinger MK, Leichtman AB, Lake C, Metzger RA, Port FK, et al. in this journal is cited, in accordance with accepted academic practice. No use, Impact of the expanded criteria donor allocation system on candidates for distribution or reproduction is permitted which does not comply with these terms. Frontiers in Medicine | www.frontiersin.org 13 January 2022 | Volume 8 | Article 780585