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A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation
BACKGROUND: Acute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6486998/ https://www.ncbi.nlm.nih.gov/pubmed/31029086 http://dx.doi.org/10.1186/s12865-019-0291-2 |
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author | Wittenbrink, Nicole Herrmann, Sabrina Blazquez-Navarro, Arturo Bauer, Chris Lindberg, Eric Wolk, Kerstin Sabat, Robert Reinke, Petra Sawitzki, Birgit Thomusch, Oliver Hugo, Christian Babel, Nina Seitz, Harald Or-Guil, Michal |
author_facet | Wittenbrink, Nicole Herrmann, Sabrina Blazquez-Navarro, Arturo Bauer, Chris Lindberg, Eric Wolk, Kerstin Sabat, Robert Reinke, Petra Sawitzki, Birgit Thomusch, Oliver Hugo, Christian Babel, Nina Seitz, Harald Or-Guil, Michal |
author_sort | Wittenbrink, Nicole |
collection | PubMed |
description | BACKGROUND: Acute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant HLA antigen bead assay data set that was acquired by the e:KID consortium as part of a systems medicine approach. RESULTS: The data set included single antigen bead (SAB) reactivity profiles of 52 low-risk graft recipients (negative complement dependent cytotoxicity crossmatch, PRA < 30%) who showed detectable pre-transplant anti-HLA 1 antibodies. To assess whether the reactivity profiles provide a means for ACR risk assessment, we established a novel approach which differs from standard approaches in two aspects: the use of quantitative continuous data and the use of a multiparameter classification method. Remarkably, it achieved significant prediction of the 38 graft recipients who experienced ACR with a balanced accuracy of 82.7% (sensitivity = 76.5%, specificity = 88.9%). CONCLUSIONS: The resultant classifier achieved one of the highest prediction accuracies in the literature for pre-transplant risk assessment of ACR. Importantly, it can facilitate risk assessment in non-sensitized patients who lack donor-specific antibodies. As the classifier is based on continuous data and includes weak signals, our results emphasize that not only strong but also weak binding interactions of antibodies and HLA 1 antigens contain predictive information. TRIAL REGISTRATION: ClinicalTrials.gov NCT00724022. Retrospectively registered July 2008. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12865-019-0291-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6486998 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64869982019-05-06 A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation Wittenbrink, Nicole Herrmann, Sabrina Blazquez-Navarro, Arturo Bauer, Chris Lindberg, Eric Wolk, Kerstin Sabat, Robert Reinke, Petra Sawitzki, Birgit Thomusch, Oliver Hugo, Christian Babel, Nina Seitz, Harald Or-Guil, Michal BMC Immunol Research Article BACKGROUND: Acute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant HLA antigen bead assay data set that was acquired by the e:KID consortium as part of a systems medicine approach. RESULTS: The data set included single antigen bead (SAB) reactivity profiles of 52 low-risk graft recipients (negative complement dependent cytotoxicity crossmatch, PRA < 30%) who showed detectable pre-transplant anti-HLA 1 antibodies. To assess whether the reactivity profiles provide a means for ACR risk assessment, we established a novel approach which differs from standard approaches in two aspects: the use of quantitative continuous data and the use of a multiparameter classification method. Remarkably, it achieved significant prediction of the 38 graft recipients who experienced ACR with a balanced accuracy of 82.7% (sensitivity = 76.5%, specificity = 88.9%). CONCLUSIONS: The resultant classifier achieved one of the highest prediction accuracies in the literature for pre-transplant risk assessment of ACR. Importantly, it can facilitate risk assessment in non-sensitized patients who lack donor-specific antibodies. As the classifier is based on continuous data and includes weak signals, our results emphasize that not only strong but also weak binding interactions of antibodies and HLA 1 antigens contain predictive information. TRIAL REGISTRATION: ClinicalTrials.gov NCT00724022. Retrospectively registered July 2008. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12865-019-0291-2) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-27 /pmc/articles/PMC6486998/ /pubmed/31029086 http://dx.doi.org/10.1186/s12865-019-0291-2 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Wittenbrink, Nicole Herrmann, Sabrina Blazquez-Navarro, Arturo Bauer, Chris Lindberg, Eric Wolk, Kerstin Sabat, Robert Reinke, Petra Sawitzki, Birgit Thomusch, Oliver Hugo, Christian Babel, Nina Seitz, Harald Or-Guil, Michal A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation |
title | A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation |
title_full | A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation |
title_fullStr | A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation |
title_full_unstemmed | A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation |
title_short | A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation |
title_sort | novel approach reveals that hla class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6486998/ https://www.ncbi.nlm.nih.gov/pubmed/31029086 http://dx.doi.org/10.1186/s12865-019-0291-2 |
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