Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibility
IntroductionThe immune-mediated rejection of transplanted organs is a complex interplay between T cells and B cells, where the recognition of HLA-derived epitopes plays a crucial role. Several algorithms of molecular compatibility have been suggested, each focusing on a specific aspect of epitope im...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1548934/full |
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| author | Matthias Niemann Matthias Niemann Benedict M. Matern Benedict M. Matern Gaurav Gupta Bekir Tanriover Fabian Halleck Klemens Budde Eric Spierings Eric Spierings |
| author_facet | Matthias Niemann Matthias Niemann Benedict M. Matern Benedict M. Matern Gaurav Gupta Bekir Tanriover Fabian Halleck Klemens Budde Eric Spierings Eric Spierings |
| author_sort | Matthias Niemann |
| collection | DOAJ |
| description | IntroductionThe immune-mediated rejection of transplanted organs is a complex interplay between T cells and B cells, where the recognition of HLA-derived epitopes plays a crucial role. Several algorithms of molecular compatibility have been suggested, each focusing on a specific aspect of epitope immunogenicity.MethodsConsidering reported death-censored graft survival in the SRTR dataset, we evaluated four models of molecular compatibility: antibody-verified Eplets, Snow, PIRCHE-II and amino acid matching. We have statistically evaluated their co-dependency and synergistic effects between models systematically on 400,935 kidney transplantations using Cox proportional hazards and XGBoost models.ResultsMultivariable models of histocompatibility generally outperformed univariable predictors, with a combined model of HLA-A, -B, -DR matching, Snow and PIRCHE-II yielding highest AUC in XGBoost and lowest BIC in Cox models. Augmentation of a clinical prediction model of pre-transplant parameters by molecular compatibility metrics improved model performance particularly considering long-term outcomes.DiscussionOur study demonstrates that the use of multiple specialized molecular HLA matching predictors improves prediction performance, thereby improving risk classification and supporting informed decision-making in kidney transplantation. |
| format | Article |
| id | doaj-art-4d68c1dcf3bf4a4ab9537fb7f37ffe39 |
| institution | Kabale University |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Immunology |
| spelling | doaj-art-4d68c1dcf3bf4a4ab9537fb7f37ffe392025-02-11T07:00:19ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-02-011610.3389/fimmu.2025.15489341548934Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibilityMatthias Niemann0Matthias Niemann1Benedict M. Matern2Benedict M. Matern3Gaurav Gupta4Bekir Tanriover5Fabian Halleck6Klemens Budde7Eric Spierings8Eric Spierings9Research and Development, PIRCHE AG, Berlin, GermanyDepartment of Nephrology and Medical Intensive Care, Charité Universitätsmedizin Berlin, Berlin, GermanyResearch and Development, PIRCHE AG, Berlin, GermanyCenter for Translational Immunology, University Medical Center, Utrecht, NetherlandsDepartment of Internal Medicine, Virginia Commonwealth University, Richmond, VA, United StatesDivision of Nephrology, The University of Arizona, Tucson, AZ, United StatesDepartment of Nephrology and Medical Intensive Care, Charité Universitätsmedizin Berlin, Berlin, GermanyDepartment of Nephrology and Medical Intensive Care, Charité Universitätsmedizin Berlin, Berlin, GermanyCenter for Translational Immunology, University Medical Center, Utrecht, NetherlandsCentral Diagnostic Laboratory, University Medical Center, Utrecht, NetherlandsIntroductionThe immune-mediated rejection of transplanted organs is a complex interplay between T cells and B cells, where the recognition of HLA-derived epitopes plays a crucial role. Several algorithms of molecular compatibility have been suggested, each focusing on a specific aspect of epitope immunogenicity.MethodsConsidering reported death-censored graft survival in the SRTR dataset, we evaluated four models of molecular compatibility: antibody-verified Eplets, Snow, PIRCHE-II and amino acid matching. We have statistically evaluated their co-dependency and synergistic effects between models systematically on 400,935 kidney transplantations using Cox proportional hazards and XGBoost models.ResultsMultivariable models of histocompatibility generally outperformed univariable predictors, with a combined model of HLA-A, -B, -DR matching, Snow and PIRCHE-II yielding highest AUC in XGBoost and lowest BIC in Cox models. Augmentation of a clinical prediction model of pre-transplant parameters by molecular compatibility metrics improved model performance particularly considering long-term outcomes.DiscussionOur study demonstrates that the use of multiple specialized molecular HLA matching predictors improves prediction performance, thereby improving risk classification and supporting informed decision-making in kidney transplantation.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1548934/fullmolecular matchingXGBoostSnowPIRCHEclinical prediction modelkidney transplantation |
| spellingShingle | Matthias Niemann Matthias Niemann Benedict M. Matern Benedict M. Matern Gaurav Gupta Bekir Tanriover Fabian Halleck Klemens Budde Eric Spierings Eric Spierings Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibility Frontiers in Immunology molecular matching XGBoost Snow PIRCHE clinical prediction model kidney transplantation |
| title | Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibility |
| title_full | Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibility |
| title_fullStr | Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibility |
| title_full_unstemmed | Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibility |
| title_short | Advancing risk stratification in kidney transplantation: integrating HLA-derived T-cell epitope and B-cell epitope matching algorithms for enhanced predictive accuracy of HLA compatibility |
| title_sort | advancing risk stratification in kidney transplantation integrating hla derived t cell epitope and b cell epitope matching algorithms for enhanced predictive accuracy of hla compatibility |
| topic | molecular matching XGBoost Snow PIRCHE clinical prediction model kidney transplantation |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1548934/full |
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