ReviewJournal of clinical medicine2025
Genomic and Biomarker Innovations in Predicting Kidney Transplant Rejection.
Review in Journal of clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Risk Phenotyping Before Graft Implantation: FTIR Spectroscopy and Machine Learning for Complementary Risk Stratification in Kidney Transplantation.Medical sciences (Basel, Switzerland) · 2026Article
- Torque teno virus viral load and hospitalisation for infections in long-term kidney transplant recipients: a single-centre prospective cohort study.BMC nephrology · 2026Article
- Multiple omics-based machine learning reveals peripheral blood immune cell landscape during acute rejection of kidney transplantation and constructs a precise non-invasive diagnostic strategy.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Donor-Derived Cell-Free DNA in Allograft Transplantation: Exaggerated Hope or Cautious Reality?Biomedicines · 2025Review
- Steroid Avoidance in Kidney Transplantation: From Vision to Velocity.Kidney international reports · 2025Article
- The application of genetic testing technology in kidney transplantation: precision matching, non-invasive monitoring and personalized management.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Currently, approximately 90,000 patients are on the kidney transplant waitlist in the United States, including 10,000 individuals awaiting re-transplantation due to prior graft failure. Allograft rejection remains a leading cause of kidney transplant failure. While the current gold standard for diagnosing rejection is tissue biopsy, it is invasive and impractical for routine or longitudinal graft surveillance. This review summarizes the current landscape of non-invasive biomarkers for detecting and predicting kidney transplant rejection, with a focus on both historical context and recent advancements. In particular, we highlight the roles of donor-derived cell-free DNA (dd-cfDNA) and gene expression profiling (GEP) in identifying acute rejection. We also discuss emerging biomarkers such as torque teno virus (TTV), which has shown potential as an indirect indicator of immunosuppression levels and rejection risk. Importantly, this review excludes biomarker studies that rely on tissue biopsy, emphasizing non-invasive approaches to rejection monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.