Detection of Plasma DNA of Renal Origin in Kidney Transplant Patients

Overview

Donor-derived cell-free DNA (dd-cfDNA) has been proposed as a potential diagnostic tool to monitor the rejection status of the kidney transplant. It has been suggested that dd-cfDNA is increasing in the blood of kidney transplant patient presenting a graft rejection. In this project, investigators proposed a different approach to predict and characterize kidney transplant rejection/dysfunction based on the quantification of epigenetic signatures present on the donor-cell-free DNA. In 2018, Moss et al. develops a deconvolution model capable of identifying the tissue origin of circulating DNA by taking advantage of its epigenetic properties. The study confirmed that the cell-free DNA circulating in healthy subjects comes mainly from blood cells and endothelial cells, but not from kidney cells. In this study, researchers investigate the evolution of blood renal-specific cell-free DNA amount in patient with chronic kidney disease before and after the transplantation surgery by testing a set of renal-specific epigenetic markers. The purpose of this study is to identify the biological noise of "native kidney" on renal-specific cell-free DNA and to compare it with signal coming from "transplanted kidney".

At the diagnostic level, routine monitoring of graft functionality after kidney transplantation relies on the use of non-specific markers, such as serum creatinine (allowing estimation of glomerular filtration rate or GFR) and proteinuria. Definitive diagnosis of renal allograft dysfunction still requires invasive allograft biopsy, which remains the gold standard for assessing graft status. The histopathological diagnosis of renal graft dysfunction is based on the Banff classification and makes it possible to examine the immune infiltrate and the cellular lesions of the graft to make a precise diagnosis. However, Renal biopsy has certain limitations: 1/ It is invasive for the patient, with associated complications, mainly hemorrhagic in 1 to 3.5% of cases; 2/ Its effectiveness in predicting early rejection (3 months) post-transplant remains controversial. A lack of patient benefit has been proven by several studies for screening biopsy; 3/ Histological analysis is subject to intra- and inter-observer variations; and 4/ it is an expensive examination due to the medical time required to perform and interpret the biopsy. The "donor-cell-free DNA (dd-cfDNA)" has been suggested as a diagnostic tool at the service of the graft. Analyzes based on molecular signatures on the circulating DNA of the donor (Single Polymorphism Nucleotide (SNP)) have made it possible to discriminate the circulating cell-free DNA from the transplanted kidney (from the donor) from the circulating cell-free DNA specific to the recipient. Data from several studies suggest that blood dd-cfDNA levels can detect rejection in heart, lung, liver and kidney allografts. First studied by multiplex qPCR and then NGS technologies, the SNPs present on the dd-cfDNA were then quantified by digital PCR techniques. In this study, investigators proposed a different approach to predict and characterize kidney transplant rejection/dysfunction based on the quantification of epigenetic signatures present on the donor-cell-free DNA. In 2018, Moss et al. develops a deconvolution model capable of identifying the tissue origin of circulating DNA by taking advantage of its epigenetic properties. The study confirmed that the cell-free DNA circulating in healthy subjects comes mainly from blood cells and endothelial cells, but not from kidney cells. In 2023, Loyfer et al. proposed a methylation atlas of more than 200 cells type and suggested that each cell has its own epigenetic signature that can be study in cell-free DNA. In this study, researchers investigate the evolution of blood renal-specific cell-free DNA amount in patient with chronic kidney disease before and after the transplantation surgery by testing a set of renal-specific epigenetic markers. The purpose of this study is to identify the biological noise of "native kidney" on renal-specific cell-free DNA and to compare it with signal coming from "transplanted kidney". Researchers hypothesize that the biological noise from "native kidney" in chronic kidney diseases is negligible compared to that of the post-transplantation graft. To investigate this hypothesis, investigators collect blood samples before and after transplant surgery to quantify kidney-specific cell-free DNA markers. They also proposed to quantify cell-free DNA markers of graft perfusion fluid to validate the specificity of renal markers and to study graft tissue damage during organ transport. Each renal-cell-free DNA sample is quantified by a proprietary technologies using a multiplex digital-PCR assay.