Abstract: TH-PO799
Urinary Metabolite Constellation Also Detects Very Early Post-transplant Rejection in Living Donor Kidney Recipients
Session Information
- Transplantation: Clinical - 2
October 24, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Transplantation
- 2102 Transplantation: Clinical
Authors
- Banas, Miriam C., Universitatsklinikum Regensburg, Regensburg, Bayern, Germany
- Wiesner, Katharina, Universitatsklinikum Regensburg, Regensburg, Germany
- Banas, Bernhard, Universitatsklinikum Regensburg, Regensburg, Bayern, Germany
- Robertson, Andrew, Numares AG, Regensburg, Germany
- Schwäble Santamaría, Amauri, Numares AG, Regensburg, Germany
- Mark, Simone, Numares AG, Regensburg, Germany
- Schiffer, Eric, Numares AG, Regensburg, Germany
Background
Kidney transplantation is the preferred treatment for end stage kidney disease, offering improved survival rates and quality of life compared to dialysis. However, acute allograft rejection remains a significant complication, necessitating accurate diagnosis for timely intervention. Standard serum creatinine monitoring lacks specificity, leading to unnecessary biopsies and missed subclinical rejection. Previously we published a novel metabolom-based urinary non-invasive test for the detection of renal allograft rejection (Banas M et al., EBioMedicine, 2019).
Methods
In this study, conducted as part of the UMBRELLA study, n=682 urine samples from 109 transplant recipients were analyzed using a recently introduced urine metabolite constellation of alanine, citrate, lactate, and urea. Parameters (n=29) such as induction therapy, warm ischemia time, and donor type were examined for their impact on the test's performance to identify biopsy confirmed rejection in the first 14 days post-transplant.
Results
Univariate analysis identified 10 significant confounders, particularly the influence of deceased organ donation on metabolic urine profiles. Multivariate analysis confirmed the relevance of parameters related to living donation and highlighted warm ischemia time as an independent factor affecting metabolite profiles. Subgroup analysis directly testing the performance of the rejection score revealed living donor recipients as the most accurately discriminated subgroup with an AUC of 0.720 (95% CI 0.62-0.82), followed by those with short (<30 min) warm ischemia times 0.702 (95% CI 0.61-0.79). Clinical observations supported these findings, with anomalies in the urine metabolite test often correlating with clinical complications.
Conclusion
The study underscores the importance of considering donor type and ischemia times when interpreting metabolomics data for rejection monitoring in kidney transplant recipients. Understanding these factors could enhance the accuracy of non-invasive rejection detection methods, facilitating timely intervention and improving patient outcomes.
Funding
- Commercial Support – Numares AG, Regensburg, Germany