Donor-derived cell-free DNA and renal allograft rejection in surveillance biopsies and indication biopsies

Integration of FTIR Spectroscopy and Machine Learning for Kidney Allograft Rejection: A Complementary Diagnostic Tool

Background: Kidney transplantation is a life-saving treatment for end-stage kidney disease, but allograft rejection remains a critical challenge, requiring accurate and timely diagnosis. The study aims to evaluate the integration of Fourier Transform Infrared (FTIR) spectroscopy and machine learning algorithms as a minimally invasive method to detect kidney allograft rejection and differentiate between T Cell-Mediated Rejection (TCMR) and Antibody-Mediated Rejection (AMR). Additionally, the goal is to discriminate these rejection types aiming to develop a reliable decision-making support tool. Methods: This retrospective study included 41 kidney transplant recipients and analyzed 81 serum samples matched to corresponding allograft biopsies. FTIR spectroscopy was applied to pre-biopsy serum samples, and Naïve Bayes classification models were developed to distinguish rejection from non-rejection and classify rejection types. Data preprocessing involved, e.g., atmospheric compensation, second derivative, and feature selection using Fast Correlation-Based Filter for spectral regions 600-1900 cm-1 and 2800-3400 cm-1. Model performance was assessed via area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and accuracy. Results: The Naïve Bayes model achieved an AUC-ROC of 0.945 in classifying rejection versus non-rejection and AUC-ROC of 0.989 in distinguishing TCMR from AMR. Feature selection significantly improved model performance, identifying key spectral wavenumbers associated with rejection mechanisms. This approach demonstrated high sensitivity and specificity for both classification tasks. Conclusions: The integration of FTIR spectroscopy with machine learning may provide a promising, minimally invasive method for early detection and precise classification of kidney allograft rejection. Further validation in larger, more diverse populations is needed to confirm these findings' reliability.

Clinical use of donor-derived cell-free DNA in kidney transplantation

Traditional monitoring of kidney transplant recipients for allograft dysfunction caused by rejection involves serial checks of serum creatinine with biopsy of the renal allograft if dysfunction is suspected. This approach is labor-intensive, invasive and costly. In addition, because this approach relies on a rise in serum creatinine above historical baselines, injury to the allograft can be extensive before this rise occurs. In an effort to address this, donor-derived cell-free DNA (dd-cf DNA) is being used with increasing frequency in the clinical setting as a means of diagnosing a rejection of the renal allograft early in the course. This can potentially allow for early intervention to minimize not only injury, but the intensity of antirejection therapy needed and the avoidance of side effects. Here, we will review the available methodology for the determination and quantification of dd-cf DNA, the data supporting its use in clinical practice and the limitations of this technology.

Utilization of donor-derived Cell-Free DNA in pediatric kidney transplant recipients: A single center study

High donor-derived cell-free DNA (dd-cfDNA) levels indicate transplant allograft injury and can identify graft rejection in kidney transplant recipients. Here, we evaluated the use of dd-cfDNA in pediatric kidney transplant rejection monitoring and treatment.

METHODS

Forty-two pediatric kidney transplant patients were enrolled between February 2020 and August 2021. Dd-cfDNA was tested before and after biopsy/rejection treatment. There was a total of 61 allograft biopsies (44 for-cause, 17 surveillance).

RESULTS

Graft rejection was found in 35/61 biopsies. Rejection was more common in basiliximab induction compared to rATG (77.1% vs. 22.9%, p = .0121). Median dd-cfDNA was higher in those with rejection (1.2% [0.34-3.12] vs. 0.24% [0.08-0.78], p < .0001). Dd-cfDNA was highest in biopsies with AMR and mixed AMR/TCMR. In addition, dd-cfDNA in basiliximab induction was higher compared to rATG (0.92% [0.27-1.8] vs. 0.26% [0.08-2], p = .0437). Median change in dd-cfDNA after rejection treatment was -0.57% (-1.67 to 0.05). Median time to dd-cfDNA <1% post-rejection treatment was 8.5 days (3.0-19.5). Dd-cfDNA in AMR was higher compared to TCMR or mixed rejection, and levels remained higher in AMR after treatment. In surveillance biopsies, 4/17 had rejection. Median dd-cfDNA was not different in those with versus without rejection (0.48% vs. 0.28%, p = .2342). Those without rejection all had dd-cfDNA <1%. In those with rejection, only one patient had dd-cfDNA >1%, and all had TCMR.

CONCLUSIONS

Our findings support dd-cfDNA as a useful indicator of graft rejection and response to treatment. Additional studies are needed to determine the role of dd-cfDNA in graft health surveillance.

European Society of Organ Transplantation Consensus Statement on Testing for Non-Invasive Diagnosis of Kidney Allograft Rejection

To address the need for improved biomarkers for kidney transplant rejection, European Society of Organ Transplantation (ESOT) convened a dedicated working group comprised of experts in kidney transplant biomarkers to review literature pertaining to clinical and subclinical acute rejection to develop guidelines in the screening and diagnosis of acute rejection that were subsequently discussed and voted on during the Consensus Conference that took place in person in Prague. The findings and recommendations of the Working Group on Molecular Biomarkers of Kidney Transplant Rejection are presented in this article.

Understanding Donor-derived Cell-free DNA in Kidney Transplantation: An Overview and Case-based Guide for Clinicians

Kidney transplant recipients undergo lifelong monitoring of allograft function and evaluation for transplant complications. The current monitoring paradigm utilizes blood, urine, and tissue markers that are insensitive, nonspecific, or invasive to obtain. As a result, problems are detected late, after significant damage has accrued, and often beyond the time at which complete resolution is possible. Indeed, most kidney transplants eventually fail, usually because of chronic rejection and other undetected injury. There is a clear need for a transplant-specific biomarker that enables a proactive approach to monitoring via early detection of reversible pathology. A biomarker that supports timely and personalized treatment would assist in achieving the ultimate goal of improving allograft survival and limiting therapeutic toxicity to the recipient. Donor-derived cell-free DNA (ddcfDNA) has been proposed as one such transplant biomarker. Although the test is presently utilized most in the United States, it is conceivable that its use will become more widespread. This review covers aspects of ddcfDNA that support informed use of the test by general nephrologists, including the basic biology of ddcfDNA, methodological nuances of testing, and general recommendations for use in the kidney transplant population. Clinical contexts are used to illustrate evidence-supported interpretation of ddcfDNA results and subsequent management. Finally, knowledge gaps and areas for further study are discussed.