Inferred HLA haplotype information for donors from hematopoietic stem cells donor registries

Hum Immunol. 2005 May;66(5):563-70. doi: 10.1016/j.humimm.2005.01.011. Epub 2005 Mar 3.


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 Moelle). 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 <10(-3)) and linkage disequilibrium (p <10(-3)) 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • France
  • Gene Frequency
  • HLA Antigens / genetics*
  • Haplotypes / genetics*
  • Hematopoietic Stem Cells / immunology*
  • Homozygote
  • Humans
  • Linkage Disequilibrium
  • Models, Genetic
  • Models, Statistical*
  • Phenotype
  • Registries*
  • Tissue Donors*


  • HLA Antigens