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.

No abstract

Genetic matching for loci in the human leukocyte antigen (HLA) region between a donor and a patient in hematopoietic stem cell transplantation (HSCT) is critical to outcome; however, methods for HLA genotyping of donors in unrelated stem cell registries often yield results with allelic and phase ambiguity and/or do not query all clinically relevant loci. We present and evaluate a statistical method for in silico imputation of HLA alleles and haplotypes in large ambiguous population data from the Be The Match(®) Registry. Our method builds on haplotype frequencies estimated from registry populations and exploits patterns of linkage disequilibrium (LD) across HLA haplotypes to infer high resolution HLA assignments. We performed validation on simulated and real population data from the Registry with non-trivial ambiguity content. While real population datasets caused some predictions to deviate from expectation, validations still showed high percent recall for imputed results with average recall >76% when imputing HLA alleles from registry data. We simulated ambiguity generated by several HLA genotyping methods to evaluate the imputation performance on several levels of typing resolution. On average, imputation percent recall of allele-level HLA haplotypes was >95% for allele-level typing, >92% for intermediate resolution typing and >58% for serology (low-resolution) typing. Thus, allele-level HLA assignments can be imputed through the application of a set of statistical and population genetics inferences and with knowledge of haplotype frequencies and self-identified race and ethnicities.

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.

Single-center studies have previously reported associations of MHC Class I Chain-Related Gene A (MICA) polymorphisms and donor-recipient MICA mismatching with graft-versus-host disease (GVHD) after unrelated donor hematopoietic cell transplantation (HCT). In this study, we investigated the association of MICA polymorphism (MICA-129, MM versus MV versus VV) and MICA mismatches after HCT with 10/10 HLA–matched (n = 552) or 9/10 (n = 161) unrelated donors. Included were adult patients with a first unrelated bone marrow or peripheral blood HCT for acute lymphoblastic leukemia, acute myeloid leukemia, or myelodysplastic syndrome that were reported to the Center for International Blood and Marrow Transplant Research between 1999 and 2011. Our results showed that neither MICA mismatch nor MICA-129 polymorphism were associated with any transplantation outcome (P < .01), with the exception of a higher relapse in recipients of MICA-mismatched HLA 10/10 donors (hazard ratio [HR], 1.7; P = .003). There was a suggestion of association between MICA mismatches and a higher risk of acute GVHD grades II to IV (HR, 1.4; P = .013) There were no significant interactions between MICA mismatches and HLA matching (9/10 versus 10/10). In conclusion, the findings in this cohort did not confirm prior studies reporting that MICA polymorphism and MICA mismatches were associated with HCT outcomes.

In hematopoietic stem cell transplantation, donor selection is based primarily on matching donor and patient HLA genes. These genes are highly polymorphic and their typing can result in exact allele assignment at each gene (the resolution at which patients and donors are matched), but it can also result in a set of ambiguous assignments, depending on the typing methodology used. To facilitate rapid identification of matched donors, registries employ statistical algorithms to infer HLA alleles from ambiguous genotypes. Linkage disequilibrium information encapsulated in haplotype frequencies is used to facilitate prediction of the most likely haplotype assignment. An HLA typing with less ambiguity produces fewer high-probability haplotypes and a more reliable prediction. We estimated ambiguity for several HLA typing methods across four continental populations using an information theory-based measure, Shannon's entropy. We used allele and haplotype frequencies to calculate entropy for different sets of 1,000 subjects with simulated HLA typing. Using allele frequencies we calculated an average entropy in Caucasians of 1.65 for serology, 1.06 for allele family level, 0.49 for a 2002-era SSO kit, and 0.076 for single-pass SBT. When using haplotype frequencies in entropy calculations, we found average entropies of 0.72 for serology, 0.73 for allele family level, 0.05 for SSO, and 0.002 for single-pass SBT. Application of haplotype frequencies further reduces HLA typing ambiguity. We also estimated expected confirmatory typing mismatch rates for simulated subjects. In a hypothetical registry with all donors typed using the same method, the entropy values based on haplotype frequencies correspond to confirmatory typing mismatch rates of 1.31% for SSO versus only 0.08% for SBT. Intermediate-resolution single-pass SBT contains the least ambiguity of the methods we evaluated and therefore the most certainty in allele prediction. The presented measure objectively evaluates HLA typing methods and can help define acceptable HLA typing for donor recruitment.