ArticleThe Journal of clinical investigation2010
A molecular classifier for predicting future graft loss in late kidney transplant biopsies.
Article in The Journal of clinical investigation, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers, 1 of them a synthesis that pooled it.
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Who cites it
98 citing papers in PubMed, 1 synthesis or guideline pooled it, 210 citations in OpenAlex.
- Identification of Candidate Biomarkers for Transplant Rejection from Transcriptome Data: A Systematic Review.Molecular diagnosis & therapy · 2019Pooled it
- Biopsy transcriptome expression profiling to identify kidney transplants at risk of chronic injury: a multicentre, prospective study.Lancet (London, England) · 2016Trial
- Expression of decoy receptor 3 in kidneys is associated with allograft survival after kidney transplant rejection.Scientific reports · 2015Trial
- Identification and functional validation of mitochondria-related genes associated with tubular injury in kidney transplantation and ischemia-reperfusion injury.Biology direct · 2026Article
- A Subset of Pro-inflammatory CXCL10+ LILRB2+ Macrophages Derives From Recipient Monocytes and Drives Renal Allograft Rejection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Review
- Renal allograft interstitial fibrosis: multicellular interactions and therapeutic strategies.Frontiers in immunology · 2026Review
- Immune Infiltration-Related Genes as Potential Biomarkers and Predicted Targets for Renal Allograft Delayed Graft Function and Survival Outcome: An Integrated Machine Learning Approach and Drugs Analysis.Mediators of inflammation · 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
- Article
- Identification and Cross-Platform Validation of Sparse Molecular Classifiers for Antibody-Mediated and T-Cell-Mediated Rejection After Kidney Transplantation.Kidney international reports · 2025Article
- A cross-sectional study of the role of epithelial cell injury in kidney transplant outcomes.JCI insight · 2025Observational
- The inhibitory receptor Siglec-E controls antigen-presenting cell activation and T cell-mediated transplant rejection.Science translational medicine · 2025Article
- Late Allograft Loss and Contemporary Cardiorenal Metabolic Therapies.Journal of the American Society of Nephrology : JASN · 2025Review
- Identification and characterization of senescent macrophages in renal allograft rejection: a cross-species MultiOmics study.Frontiers in immunology · 2025Article
- Identifying Immuno-Fibrotic Roles of Lactylation-Related T Cell Hub Genes in Renal Ischemia-Reperfusion Injury: A Multi-Omics Study and Experimental Validation.Journal of inflammation research · 2025Article
- CAV1 promotes epithelial-to-mesenchymal transition (EMT) and chronic renal allograft interstitial fibrosis by activating the ferroptosis pathway.Frontiers in immunology · 2025Article
- Article
- High-dimensional analysis of NK cells in kidney transplantation uncovers subsets associated with antibody-independent graft dysfunction.JCI insight · 2024Article
- Article
38 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kidney transplant recipients that develop signs of renal dysfunction or proteinuria one or more years after transplantation are at considerable risk for progression to renal failure. To assess the kidney at this time, a "for-cause" biopsy is performed, but this provides little indication as to which recipients will go on to organ failure. In an attempt to identify molecules that could provide this information, we used microarrays to analyze gene expression in 105 for-cause biopsies taken between 1 and 31 years after transplantation. Using supervised principal components analysis, we derived a molecular classifier to predict graft loss. The genes associated with graft failure were related to tissue injury, epithelial dedifferentiation, matrix remodeling, and TGF-beta effects and showed little overlap with rejection-associated genes. We assigned a prognostic molecular risk score to each patient, identifying those at high or low risk for graft loss. The molecular risk score was correlated with interstitial fibrosis, tubular atrophy, tubulitis, interstitial inflammation, proteinuria, and glomerular filtration rate. In multivariate analysis, molecular risk score, peritubular capillary basement membrane multilayering, arteriolar hyalinosis, and proteinuria were independent predictors of graft loss. In an independent validation set, the molecular risk score was the only predictor of graft loss. Thus, the molecular risk score reflects active injury and is superior to either scarring or function in predicting graft failure.
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