Dina Zielinski, Valentin Goutaudier, Marta Sablik, Gillian Divard, Olivier Aubert, Alexis Piedrafita, Fariza Mezine, Jessy Dagobert, Anais Certain, Blaise Robin, Juliette Gueguen, Marion Rabant, Jean-Paul Duong van Huyen, Aurélie Sannier, Christine Randoux-Lebrun, Mehdi Maanaoui, Arnaud Lionet, Jean-Baptiste Gibier, Viviane Gnemmi, Moglie Le Quintrec, Bertrand Chauveau, Agathe Vermorel, Lionel Couzi, Oriol Bestard, Michelle Elias, Kevin Louis, Ivy A. Rosales, R. Neal Smith, Vanderlene L. Kung, Dany Anglicheau, Christophe Legendre, Arnaud Del Bello, Edmund Huang, Benjamin Adam, Nassim Kamar, Robert B. Colvin, Michael Mengel, Carmen Lefaucheur, Alexandre Loupy
{"title":"Molecular diagnosis of kidney allograft rejection based on the Banff Human Organ Transplant (B-HOT) gene panel: a multicenter international study","authors":"Dina Zielinski, Valentin Goutaudier, Marta Sablik, Gillian Divard, Olivier Aubert, Alexis Piedrafita, Fariza Mezine, Jessy Dagobert, Anais Certain, Blaise Robin, Juliette Gueguen, Marion Rabant, Jean-Paul Duong van Huyen, Aurélie Sannier, Christine Randoux-Lebrun, Mehdi Maanaoui, Arnaud Lionet, Jean-Baptiste Gibier, Viviane Gnemmi, Moglie Le Quintrec, Bertrand Chauveau, Agathe Vermorel, Lionel Couzi, Oriol Bestard, Michelle Elias, Kevin Louis, Ivy A. Rosales, R. Neal Smith, Vanderlene L. Kung, Dany Anglicheau, Christophe Legendre, Arnaud Del Bello, Edmund Huang, Benjamin Adam, Nassim Kamar, Robert B. Colvin, Michael Mengel, Carmen Lefaucheur, Alexandre Loupy","doi":"10.1016/j.ajt.2025.04.025","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":123,"journal":{"name":"American Journal of Transplantation","volume":"27 1","pages":""},"PeriodicalIF":8.9000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Transplantation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.ajt.2025.04.025","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
The American Journal of Transplantation is a leading journal in the field of transplantation. It serves as a forum for debate and reassessment, an agent of change, and a major platform for promoting understanding, improving results, and advancing science. Published monthly, it provides an essential resource for researchers and clinicians worldwide.
The journal publishes original articles, case reports, invited reviews, letters to the editor, critical reviews, news features, consensus documents, and guidelines over 12 issues a year. It covers all major subject areas in transplantation, including thoracic (heart, lung), abdominal (kidney, liver, pancreas, islets), tissue and stem cell transplantation, organ and tissue donation and preservation, tissue injury, repair, inflammation, and aging, histocompatibility, drugs and pharmacology, graft survival, and prevention of graft dysfunction and failure. It also explores ethical and social issues in the field.