Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9264198 | Human Immunology | 2005 | 8 Pages |
Abstract
Human leukocyte antigen (HLA) matching remains a key issue in the outcome of transplantation. In hematopoietic stem cell transplantation with unrelated donors, the matching for compatible donors is based on the HLA phenotype information. In familial transplantation, the matching is achieved at the haplotype level because donor and recipient share the block-transmitted major histocompatibility complex region. We present a statistical method based on the HLA haplotype inference to refine the HLA information available in an unrelated situation. We implement a systematic statistical inference of the haplotype combinations at the individual level. It computes the most likely haplotype pair given the phenotype and its probability. The method is validated on 301 phase-known phenotypes from CEPH families (Centre d'Etude du Polymorphisme Humain). The method is further applied to 85,933 HLA-A B DR typed unrelated donors from the French Registry of hematopoietic stem cells donors (France Greffe de Moëlle). The average value of prediction probability is 0.761 (SD 0.199) ranging from 0.26 to 1. Correlations between phenotype characteristics and predictions are also given. Homozygosity (OR = 2.08; [2.02-2.14] p <10â3) and linkage disequilibrium (p <10â3) are the major factors influencing the quality of prediction. Limits and relevance of the method are related to limits of haplotype estimation. Relevance of the method is discussed in the context of HLA matching refinement.
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Immunology
Authors
Pierre-Antoine Gourraud, Phillipe Lamiraux, Nabil El-Kadhi, Colette Raffoux, Anne Cambon-Thomsen,