American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant SurgeonsJournal Article
07 May 2025
Transcriptomic analysis of kidney biopsies has demonstrated potential to improve diagnosis of allograft rejection.
Here, we developed a molecular assessment of antibody-mediated rejection (AMR) and T-cell-mediated rejection (TCMR) based on the Banff-Human-Organ-Transplant (B-HOT) consensus gene panel.
Expression assays of formalin-fixed paraffin-embedded kidney biopsies from well-phenotyped cohorts were used to develop prediction models for AMR and TCMR and an automated report of gene expression-based diagnosis.
The study population consisted of 950 kidney allograft biopsies from 10 transplantation centers in Europe and North America. The development cohort included 664 renal allograft biopsies split into a training (n=537) and test set (n=127), and two external validation cohorts (n=286).
We performed gene selection using regularized regression and developed several different base models based on B-HOT expression data, which were combined into a single ensemble model for each rejection diagnosis.
Model performance was assessed in the test set and the two external validation cohorts, showing good discriminative abilities (respective PR-AUC AMR=0. 811, 0. 891, 0. 832 and TCMR=0. 736, 0. 810, 0. 782).
We identified challenging biopsies with histology below diagnostic thresholds for which gene expression-based probability can refine rejection diagnosis.
This automated molecular diagnostic system shows potential for improving kidney allograft rejection diagnosis in routine practice and clinical trials.
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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