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March 3, 2026Current Transplantation Reports3 citationsOpen Access

Non-Invasive Biomarkers for Kidney Transplant Monitoring: A Comprehensive Review

JDJuliana DamasFCFernando CaeiroMRMaria Jose Ramirez-Bajo

Key Points

  • Donor-derived cell-free DNA shows promise in detecting allograft injury and antibody-mediated rejection.
  • Focus on gene expression profiling reveals immune response signatures for subclinical and acute rejection detection.
  • Emerging microRNAs and long non-coding RNAs are recognized as potential tissue-specific biomarkers but face clinical translation challenges.
  • Integration of biomarkers, potentially with AI, may improve diagnostic accuracy and individual immunosuppression strategies.

Abstract

Kidney transplant rejection presents a clinical challenge, requiring an accurate and timely diagnosis. While kidney graft biopsy remains the gold standard, its inherent limitations motivate the need for noninvasive diagnosis. This review comprehensively examines emerging non-invasive biomarkers for the monitoring of kidney allograft, specifically donor-derived cell-free DNA (dd-cfDNA), gene expression profiling (GEP), microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), chemokines, and DNA methylation patterns. We review their underlying biological principles and discuss their diagnostic accuracy, clinical applications, and limitations in the current available evidence. Donor-derived cfDNA, a promising predictor of allograft injury, shows particular utility in detecting antibody-mediated rejection (ABMR), lacking however for standardization concerning its cutoff. Gene expression profiling provides insights into immune responses, with various gene signatures developed for detecting subclinical and acute rejection. MicroRNAs and long non-coding RNAs demonstrate potential as tissue-specific biomarkers of injury and rejection, yet face challenges in standardization and clinical translation. Chemokines like urinary CXCL9 and CXCL10 exhibit diagnostic and prognostic value for acute rejection. Furthermore, DNA methylation patterns offer a novel approach to identify cell-specific cfDNA and reflect cell death processes within transplanted organs. The integration of these diverse biomarkers, potentially augmented by artificial intelligence platforms, holds immense promise for improving diagnostic precision, minimizing the need for biopsies, and enabling personalized immunosuppression strategies, which would improve long-term graft survival.

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Cite This Study

Damas et al. (2026) studied this question.

synapsesocial.com/papers/69a76085c6e9836116a2d575https://doi.org/10.1007/s40472-025-00501-8
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Plasma DNA as Cell Death Marker in Elderly Patients2009 · 89 citations
  2. 2Urinary-Cell mRNA Profile and Acute Cellular Rejection in Kidney Allografts2013 · 10 citations
  3. 3Cell-Free DNA and Active Rejection in Kidney Allografts2017 · 591 citations
  4. 4Circulating microRNAs as stable blood-based markers for cancer detection2008 · 8,019 citations
  5. 5Molecular immune monitoring in kidney transplant rejection: a state-of-the-art review2023 · 20 citations