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DOI 10.1016/j.ajt.2025.04.025

Медицинская библиотека · American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2025

Molecular diagnosis of kidney allograft rejection based on the Banff Human Organ Transplant gene panel: A multicenter international study.

Zielinski Dina, Goutaudier Valentin, Sablik Marta, Divard Gillian, Aubert Olivier, Piedrafita Alexis, Mezine Fariza, Dagobert Jessy, Certain Anais, Robin Blaise, Gueguen Juliette, Rabant Marion, Duong van Huyen Jean-Paul, Sannier Aurélie, Randoux-Lebrun Christine, Maanaoui Mehdi, Lionet Arnaud, Gibier Jean-Baptiste, Gnemmi Viviane, Le Quintrec Moglie, Chauveau Bertrand, Vermorel Agathe, Couzi Lionel, Bestard Oriol, Elias Michelle, Louis Kevin, Rosales Ivy A, Smith R Neal, Kung Vanderlene L, Anglicheau Dany, Legendre Christophe, Del Bello Arnaud, Huang Edmund, Adam Benjamin, Kamar Nassim, Colvin Robert B, Mengel Michael, Lefaucheur Carmen, Loupy Alexandre

СтатьяМногоцентровое исследованиеПеревод в очереди

Аннотация

Transcriptomic analysis of kidney biopsies has demonstrated the 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 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 2 external validation cohorts (n = 286). We performed gene selection using regularized regression and developed several different base models based on Banff Human Organ Transplant expression data, which were combined into a single ensemble model for each rejection diagnosis. Model performance was assessed in the test set and the 2 external validation cohorts, showing good discriminative abilities (respective areas under the precision-recall curve: AMR = 0.811, 0.891, and 0.832 and TCMR = 0.736, 0.810, and 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.

Для цитирования: Zielinski Dina, Goutaudier Valentin, Sablik Marta, Divard Gillian, Aubert Olivier, Piedrafita Alexis, Mezine Fariza, Dagobert Jessy, Certain Anais, Robin Blaise, Gueguen Juliette, Rabant Marion, Duong van Huyen Jean-Paul, Sannier Aurélie, Randoux-Lebrun Christine, Maanaoui Mehdi, Lionet Arnaud, Gibier Jean-Baptiste, Gnemmi Viviane, Le Quintrec Moglie, Chauveau Bertrand, Vermorel Agathe, Couzi Lionel, Bestard Oriol, Elias Michelle, Louis Kevin, Rosales Ivy A, Smith R Neal, Kung Vanderlene L, Anglicheau Dany, Legendre Christophe, Del Bello Arnaud, Huang Edmund, Adam Benjamin, Kamar Nassim, Colvin Robert B, Mengel Michael, Lefaucheur Carmen, Loupy Alexandre. Molecular diagnosis of kidney allograft rejection based on the Banff Human Organ Transplant gene panel: A multicenter international study.. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons. 2025. DOI: 10.1016/j.ajt.2025.04.025.

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