We have calculated six-locus high resolution HLA A∼C∼B∼DRB3/4/5∼DRB1∼DQB1 haplotype frequencies using all Be The Match(®) Registry volunteer donors typed by DNA methods at recruitment. Mixed resolution HLA typing data was inputted to a modified expectation-maximization (EM) algorithm in the form of genotype lists generated by interpretation of primary genomic typing data to the IMGT/HLA v3.4.0 allele list. The full cohort consists of 6.59 million subjects categorized at a broad race level. Overall 25.8% of the individuals were typed at the C locus, and 5.2% typed at the DQB1 locus, while all individuals were typed for A, B, DRB1. We also present a subset of 2.90 million subjects with detailed race/ethnic information mapped to 21 population subgroups, 64.1% of which have primary DNA typing data across at least A, B, and DRB1 loci. Sample sizes at the detailed race level range from 1,242,890 for European Caucasian to 1,376 Alaskan Native or Aleut. Genetic distance measurements show high levels of HLA genetic divergence among the 21 detailed race categories, especially among the eight Asian-American populations. These haplotype frequencies will be used to improve match predictions for donor selection algorithms for hematopoietic stem cell transplantation and improve the accuracy in modeling registry match rates.

Many panels of ancestry informative single nucleotide polymorphisms have been proposed in recent years for various purposes including detecting stratification in biomedical studies and determining an individual's ancestry in a forensic context. All of the panels have limitations in their generality and efficiency for routine forensic work. Some panels have used only a few populations to validate them. Some panels are based on very large numbers of SNPs thereby limiting the ability of others to test different populations. We have been working toward an efficient and globally useful panel of ancestry informative markers that is comprised of a small number of highly informative SNPs. We have developed a panel of 55 SNPs analyzed on 73 populations from around the world. We present the details of the panel and discuss its strengths and limitations.

Here, we present results for DPA1 and DPB1 four-digit allele-level typing in a large (n = 5,944) sample of unrelated European American stem cell donors previously characterized for other class I and class II loci. Examination of genetic data for both chains of the DP heterodimer in the largest cohort to date, at the amino acid epitope, allele, genotype, and haplotype level, allows new insights into the functional units of selection and association for the DP heterodimer. The data in this study suggest that for the DPA1-DPB1 heterodimer, the unit of selection is the combined amino acid epitope contributed by both the DPA1 and DPB1 genes, rather than the allele, and that patterns of LD are driven primarily by dimer stability and conformation of the P1 pocket. This may help explain the differential pattern of allele frequency distribution observed for this locus relative to the other class II loci. These findings further support the notion that allele-level associations in disease and transplantation may not be the most important unit of analysis, and that they should be considered instead in the molecular context.Electronic supplementary materialThe online version of this article (doi:10.1007/s00251-012-0615-3) contains supplementary material, which is available to authorized users.

The search for a suitable human leukocyte antigen (HLA)-matched unrelated adult stem cell donor (URD) or umbilical cord blood unit (UCB) is a complex process. The National Marrow Donor Program (NMDP) developed a search algorithm known as HapLogic, which is currently provided within the NMDP Traxis application. The HapLogic algorithm has been in use since 2006 and has advanced URD/UCB HLA-matching technology. The algorithm has been shown to have high predictive accuracy, which can streamline URD/UCB selection and drive efficiencies in the search process to the benefit of the stem cell transplantation community. Here, we describe the fundamental components of the NMDP matching algorithm, output, validation, and future directions.

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