Olivier Aubert1,2, Sarah Higgins1,3, Yassine Bouatou1,4,5, Daniel Yoo1, Marc Raynaud1, Denis Viglietti1,5, Marion Rabant6, Luis Hidalgo7, Denis Glotz1,5, Christophe Legendre1,2, Michel Delahousse8, Nikhil Shah9, Banu Sis7, Patricia Campbell7,9, Michael Mengel7, Xavier Jouven1,10, Jean-Paul Duong Van Huyen1,6, Carmen Lefaucheur1,5, Alexandre Loupy11,2. 1. Paris Translational Research Center for Organ Transplantation, Institut national de la santé et de la recherche médicale, Unité mixte de recherche-S970, Paris, France. 2. Paris Cite and Kidney Transplantation Department, Necker Hospital, Assistance Publique-Hôpitaux de Paris, Paris Descartes University Sorbonne, Paris, France. 3. Department of Nephrology, Sherbrooke University, Sherbrooke, Québec, Canada. 4. Department of Pathology, Academic Medical Center-University of Amsterdam, Amsterdam, The Netherlands. 5. Department of Nephrology and Organ Transplantation, Saint-Louis Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France. 6. Department of Pathology, Necker Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France. 7. Department of Laboratory Medicine and Pathology and. 8. Department of Transplantation, Nephrology and Clinical Immunology, Hôpital Foch, Suresnes, France; and. 9. Division of Nephrology and Transplant Immunology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada. 10. Department of Cardiology, Georges Pompidou European Hospital, Paris, France. 11. Paris Translational Research Center for Organ Transplantation, Institut national de la santé et de la recherche médicale, Unité mixte de recherche-S970, Paris, France; alexandre.loupy@inserm.fr.
Abstract
BACKGROUND: Transplant glomerulopathy, a common glomerular lesion observed after kidney transplant that is associated with poor prognosis, is not a specific entity but rather the end stage of overlapping disease pathways. Its heterogeneity has not been precisely characterized to date. METHODS: Our study included consecutive kidney transplant recipients from three centers in France and one in Canada who presented with a diagnosis of transplant glomerulopathy (Banff cg score ≥1 by light microscopy), on the basis of biopsies performed from January of 2004 through December of 2014. We used an unsupervised archetype analysis of comprehensive pathology findings and clinical, immunologic, and outcome data to identify distinct groups of patients. RESULTS: Among the 8207 post-transplant allograft biopsies performed during the inclusion period, we identified 552 biopsy samples (from 385 patients) with transplant glomerulopathy (incidence of 6.7%). The median time from transplant to transplant glomerulopathy diagnosis was 33.18 months. Kidney allograft survival rates at 3, 5, 7, and 10 years after diagnosis were 69.4%, 57.1%, 43.3%, and 25.5%, respectively. An unsupervised learning method integrating clinical, functional, immunologic, and histologic parameters revealed five transplant glomerulopathy archetypes characterized by distinct functional, immunologic, and histologic features and associated causes and distinct allograft survival profiles. These archetypes showed significant differences in allograft outcomes, with allograft survival rates 5 years after diagnosis ranging from 88% to 22%. Based on those results, we built an online application, which can be used in clinical practice on the basis of real patients. CONCLUSIONS: A probabilistic data-driven archetype analysis approach applied in a large, well defined multicenter cohort refines the diagnostic and prognostic features associated with cases of transplant glomerulopathy. Reducing heterogeneity among such cases can improve disease characterization, enable patient-specific risk stratification, and open new avenues for archetype-based treatment strategies and clinical trials optimization.
BACKGROUND:Transplant glomerulopathy, a common glomerular lesion observed after kidney transplant that is associated with poor prognosis, is not a specific entity but rather the end stage of overlapping disease pathways. Its heterogeneity has not been precisely characterized to date. METHODS: Our study included consecutive kidney transplant recipients from three centers in France and one in Canada who presented with a diagnosis of transplant glomerulopathy (Banff cg score ≥1 by light microscopy), on the basis of biopsies performed from January of 2004 through December of 2014. We used an unsupervised archetype analysis of comprehensive pathology findings and clinical, immunologic, and outcome data to identify distinct groups of patients. RESULTS: Among the 8207 post-transplant allograft biopsies performed during the inclusion period, we identified 552 biopsy samples (from 385 patients) with transplant glomerulopathy (incidence of 6.7%). The median time from transplant to transplant glomerulopathy diagnosis was 33.18 months. Kidney allograft survival rates at 3, 5, 7, and 10 years after diagnosis were 69.4%, 57.1%, 43.3%, and 25.5%, respectively. An unsupervised learning method integrating clinical, functional, immunologic, and histologic parameters revealed five transplant glomerulopathy archetypes characterized by distinct functional, immunologic, and histologic features and associated causes and distinct allograft survival profiles. These archetypes showed significant differences in allograft outcomes, with allograft survival rates 5 years after diagnosis ranging from 88% to 22%. Based on those results, we built an online application, which can be used in clinical practice on the basis of real patients. CONCLUSIONS: A probabilistic data-driven archetype analysis approach applied in a large, well defined multicenter cohort refines the diagnostic and prognostic features associated with cases of transplant glomerulopathy. Reducing heterogeneity among such cases can improve disease characterization, enable patient-specific risk stratification, and open new avenues for archetype-based treatment strategies and clinical trials optimization.
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