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Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation

Epitope-based HLA matching has been emerged over the last few years as an improved method for HLA matching in solid organ transplantation. The epitope-based matching concept has been incorporated in both the PIRCHE-II and the HLAMatchmaker algorithm to find the most suitable donor for a recipient. F...

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Autores principales: Geneugelijk, Kirsten, Wissing, Jeroen, Koppenaal, Dirk, Niemann, Matthias, Spierings, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5329668/
https://www.ncbi.nlm.nih.gov/pubmed/28286782
http://dx.doi.org/10.1155/2017/9130879
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author Geneugelijk, Kirsten
Wissing, Jeroen
Koppenaal, Dirk
Niemann, Matthias
Spierings, Eric
author_facet Geneugelijk, Kirsten
Wissing, Jeroen
Koppenaal, Dirk
Niemann, Matthias
Spierings, Eric
author_sort Geneugelijk, Kirsten
collection PubMed
description Epitope-based HLA matching has been emerged over the last few years as an improved method for HLA matching in solid organ transplantation. The epitope-based matching concept has been incorporated in both the PIRCHE-II and the HLAMatchmaker algorithm to find the most suitable donor for a recipient. For these algorithms, high-resolution HLA genotype data of both donor and recipient is required. Since high-resolution HLA genotype data is often not available, we developed a computational method which allows epitope-based HLA matching from serological split level HLA typing relying on HLA haplotype frequencies. To validate this method, we simulated a donor-recipient population for which PIRCHE-II and eplet values were calculated when using both high-resolution HLA genotype data and serological split level HLA typing. The majority of the serological split level HLA-determined ln(PIRCHE-II)/ln(eplet) values did not or only slightly deviate from the reference group of high-resolution HLA-determined ln(PIRCHE-II)/ln(eplet) values. This deviation was slightly increased when HLA-C or HLA-DQ was omitted from the input and was substantially decreased when using two-field resolution HLA genotype data of the recipient and serological split level HLA typing of the donor. Thus, our data suggest that our computational approach is a powerful tool to estimate PIRCHE-II/eplet values when high-resolution HLA genotype data is not available.
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spelling pubmed-53296682017-03-12 Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation Geneugelijk, Kirsten Wissing, Jeroen Koppenaal, Dirk Niemann, Matthias Spierings, Eric J Immunol Res Research Article Epitope-based HLA matching has been emerged over the last few years as an improved method for HLA matching in solid organ transplantation. The epitope-based matching concept has been incorporated in both the PIRCHE-II and the HLAMatchmaker algorithm to find the most suitable donor for a recipient. For these algorithms, high-resolution HLA genotype data of both donor and recipient is required. Since high-resolution HLA genotype data is often not available, we developed a computational method which allows epitope-based HLA matching from serological split level HLA typing relying on HLA haplotype frequencies. To validate this method, we simulated a donor-recipient population for which PIRCHE-II and eplet values were calculated when using both high-resolution HLA genotype data and serological split level HLA typing. The majority of the serological split level HLA-determined ln(PIRCHE-II)/ln(eplet) values did not or only slightly deviate from the reference group of high-resolution HLA-determined ln(PIRCHE-II)/ln(eplet) values. This deviation was slightly increased when HLA-C or HLA-DQ was omitted from the input and was substantially decreased when using two-field resolution HLA genotype data of the recipient and serological split level HLA typing of the donor. Thus, our data suggest that our computational approach is a powerful tool to estimate PIRCHE-II/eplet values when high-resolution HLA genotype data is not available. Hindawi Publishing Corporation 2017 2017-02-12 /pmc/articles/PMC5329668/ /pubmed/28286782 http://dx.doi.org/10.1155/2017/9130879 Text en Copyright © 2017 Kirsten Geneugelijk et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Geneugelijk, Kirsten
Wissing, Jeroen
Koppenaal, Dirk
Niemann, Matthias
Spierings, Eric
Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation
title Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation
title_full Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation
title_fullStr Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation
title_full_unstemmed Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation
title_short Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation
title_sort computational approaches to facilitate epitope-based hla matching in solid organ transplantation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5329668/
https://www.ncbi.nlm.nih.gov/pubmed/28286782
http://dx.doi.org/10.1155/2017/9130879
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