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A Prospective Multicenter Trial to Evaluate Urinary Metabolomics for Non-invasive Detection of Renal Allograft Rejection (PARASOL): Study Protocol and Patient Recruitment

MC. Banas, GA. Böhmig, O. Viklicky, LP. Rostaing, T. Jouve, L. Guirado, C. Facundo, O. Bestard, HJ. Gröne, K. Kobayashi, V. Hanzal, FJ. Putz, D. Zecher, T. Bergler, S. Neumann, V. Rothe, AG. Schwäble Santamaria, E. Schiffer, B. Banas

. 2021 ; 8 (-) : 780585. [pub] 20220107

Language English Country Switzerland

Document type Journal Article

Persistent link   https://www.medvik.cz/link/bmc22010296

Background: In an earlier monocentric study, we have developed a novel non-invasive test system for the prediction of renal allograft rejection, based on the detection of a specific urine metabolite constellation. To further validate our results in a large real-world patient cohort, we designed a multicentric observational prospective study (PARASOL) including six independent European transplant centers. This article describes the study protocol and characteristics of recruited better patients as subjects. Methods: Within the PARASOL study, urine samples were taken from renal transplant recipients when kidney biopsies were performed. According to the Banff classification, urine samples were assigned to a case group (renal allograft rejection), a control group (normal renal histology), or an additional group (kidney damage other than rejection). Results: Between June 2017 and March 2020, 972 transplant recipients were included in the trial (1,230 urine samples and matched biopsies, respectively). Overall, 237 samples (19.3%) were assigned to the case group, 541 (44.0%) to the control group, and 452 (36.7%) samples to the additional group. About 65.9% were obtained from male patients, the mean age of transplant recipients participating in the study was 53.7 ± 13.8 years. The most frequently used immunosuppressive drugs were tacrolimus (92.8%), mycophenolate mofetil (88.0%), and steroids (79.3%). Antihypertensives and antidiabetics were used in 88.0 and 27.4% of the patients, respectively. Approximately 20.9% of patients showed the presence of circulating donor-specific anti-HLA IgG antibodies at time of biopsy. Most of the samples (51.1%) were collected within the first 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.

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$a Background: In an earlier monocentric study, we have developed a novel non-invasive test system for the prediction of renal allograft rejection, based on the detection of a specific urine metabolite constellation. To further validate our results in a large real-world patient cohort, we designed a multicentric observational prospective study (PARASOL) including six independent European transplant centers. This article describes the study protocol and characteristics of recruited better patients as subjects. Methods: Within the PARASOL study, urine samples were taken from renal transplant recipients when kidney biopsies were performed. According to the Banff classification, urine samples were assigned to a case group (renal allograft rejection), a control group (normal renal histology), or an additional group (kidney damage other than rejection). Results: Between June 2017 and March 2020, 972 transplant recipients were included in the trial (1,230 urine samples and matched biopsies, respectively). Overall, 237 samples (19.3%) were assigned to the case group, 541 (44.0%) to the control group, and 452 (36.7%) samples to the additional group. About 65.9% were obtained from male patients, the mean age of transplant recipients participating in the study was 53.7 ± 13.8 years. The most frequently used immunosuppressive drugs were tacrolimus (92.8%), mycophenolate mofetil (88.0%), and steroids (79.3%). Antihypertensives and antidiabetics were used in 88.0 and 27.4% of the patients, respectively. Approximately 20.9% of patients showed the presence of circulating donor-specific anti-HLA IgG antibodies at time of biopsy. Most of the samples (51.1%) were collected within the first 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.
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$a Böhmig, Georg A $u Division of Nephrology and Dialysis, Department of Medicine III, Medical University of Vienna, Vienna, Austria
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$a Viklicky, Ondrej $u Transplant Laboratory, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czechia $u Department of Nephrology, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czechia
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$a Rostaing, Lionel P $u Nephrology, Hemodialysis, Apheresis and Kidney Transplantation Department, Grenoble University Hospital, Grenoble, France $u Faculty of Health, Grenoble Alpes University, Grenoble, France
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$a Jouve, Thomas $u Nephrology, Hemodialysis, Apheresis and Kidney Transplantation Department, Grenoble University Hospital, Grenoble, France
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$a Guirado, Lluis $u Nephrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB-Sant Pau), Medicine Department-Universitat Autónoma de Barcelona, REDinREN, Instituto de Investigación Carlos III, Barcelona, Spain
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$a Facundo, Carme $u Nephrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB-Sant Pau), Medicine Department-Universitat Autónoma de Barcelona, REDinREN, Instituto de Investigación Carlos III, Barcelona, Spain
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$a Bestard, Oriol $u Vall d'Hebron University Hospital (HUVH), Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
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$a Gröne, Hermann-Josef $u Institute of Pharmacology, Philipps-University, Marburg, Germany
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$a Kobayashi, Kazuhiro $u Institute of Pharmacology, University of Marburg, Marburg, Germany
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$a Hanzal, Vladimir $u Department of Nephrology, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czechia
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$a Putz, Franz Josef $u Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
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$a Zecher, Daniel $u Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
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$a Bergler, Tobias $u Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
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$a Banas, Bernhard $u Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
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