A comparative reference study for the validation of HLA-matching algorithms in the search for allogeneic hematopoietic stem cell donors and cord blood units.

The accuracy of human leukocyte antigen (HLA)-matching algorithms is a prerequisite for the correct and efficient identification of optimal unrelated donors for patients requiring hematopoietic stem cell transplantation. The goal of this World Marrow Donor Association study was to validate established matching algorithms from different international donor registries by challenging them with simulated input data and subsequently comparing the output. This experiment addressed three specific aspects of HLA matching using different data sets for tasks of increasing complexity. The first two tasks targeted the traditional matching approach identifying discrepancies between patient and donor HLA genotypes by counting antigen and allele differences. Contemporary matching procedures predicting the probability for HLA identity using haplotype frequencies were addressed by the third task. In each task, the identified disparities between the results of the participating computer programs were analyzed, classified and quantified. This study led to a deep understanding of the algorithms participating and finally produced virtually identical results. The unresolved discrepancies total to less than 1%, 4% and 2% for the three tasks and are mostly because of individual decisions in the design of the programs. Based on these findings, reference results for the three input data sets were compiled that can be used to validate future matching algorithms and thus improve the quality of the global donor search process.

Validation of statistical imputation of allele-level multilocus phased genotypes from ambiguous HLA assignments.

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.

Comparative validation of computer programs for haplotype frequency estimation from donor registry data.

Estimation of human leukocyte antigen (HLA) haplotype frequencies from unrelated stem cell donor registries presents a challenge because of large sample sizes and heterogeneity of HLA typing data. For the 14th International HLA and Immunogenetics Workshop, five bioinformatics groups initiated the 'Registry Diversity Component' aiming to cross-validate and improve current haplotype estimation tools. Five datasets were derived from different donor registries and then used as input for five different computer programs for haplotype frequency estimation. Because of issues related to heterogeneity and complexity of HLA typing data identified in the initial phase, the same five implementations, and two new ones, were used on simulated datasets in a controlled experiment where the correct results were known a priori. These datasets contained various fractions of missing HLA-DR modeled after European haplotype frequencies. We measured the contribution of sampling fluctuation and estimation error to the deviation of the frequencies from their true values, finding equivalent contributions of each for the chosen samples. Because of patient-directed activities, selective prospective typing strategies and the variety and evolution of typing technology, some donors have more complete and better HLA data. In this setting, we show that restricting estimation to fully typed individuals introduces biases that could be overcome by including all donors in frequency estimation. Our study underlines the importance of critical review and validation of tools in registry-related activity and provides a sustainable framework for validating the computational tools used. Accurate frequencies are essential for match prediction to improve registry operations and to help more patients identify suitably matched donors.

Genotype List String: a grammar for describing HLA and KIR genotyping results in a text string.

Knowledge of an individual's human leukocyte antigen (HLA) genotype is essential for modern medical genetics, and is crucial for hematopoietic stem cell and solid-organ transplantation. However, the high levels of polymorphism known for the HLA genes make it difficult to generate an HLA genotype that unambiguously identifies the alleles that are present at a given HLA locus in an individual. For the last 20 years, the histocompatibility and immunogenetics community has recorded this HLA genotyping ambiguity using allele codes developed by the National Marrow Donor Program (NMDP). While these allele codes may have been effective for recording an HLA genotyping result when initially developed, their use today results in increased ambiguity in an HLA genotype, and they are no longer suitable in the era of rapid allele discovery and ultra-high allele polymorphism. Here, we present a text string format capable of fully representing HLA genotyping results. This Genotype List (GL) String format is an extension of a proposed standard for reporting killer-cell immunoglobulin-like receptor (KIR) genotype data that can be applied to any genetic data that use a standard nomenclature for identifying variants. The GL String format uses a hierarchical set of operators to describe the relationships between alleles, lists of possible alleles, phased alleles, genotypes, lists of possible genotypes, and multilocus unphased genotypes, without losing typing information or increasing typing ambiguity. When used in concert with appropriate tools to create, exchange, and parse these strings, we anticipate that GL Strings will replace NMDP allele codes for reporting HLA genotypes.

16(th) IHIW: global analysis of registry HLA haplotypes from 20 million individuals: report from the IHIW Registry Diversity Group.

This project has the goal to validate bioinformatics methods and tools for HLA haplotype frequency analysis specifically addressing unique issues of haematopoietic stem cell registry data sets. In addition to generating new methods and tools for the analysis of registry data sets, the intent is to produce a comprehensive analysis of HLA data from 20 million donors from the Bone Marrow Donors Worldwide (BMDW) database. This report summarizes the activity on this project as of the 16IHIW meeting in Liverpool.

Genetic differentiation of Jewish populations.

The Jewish diaspora can be viewed as a natural process in population dispersion and differentiation. We extend genetic studies on the Jewish diaspora to an analysis of human leukocyte antigen (HLA) haplotype distributions in the Jewish peoples, and show the value of this information for the design of Jewish marrow donor registries. HLA data from the Hadassah Bone Marrow Registry having parental country-of-origin information comprise samples of geographically discrete regions. We analyzed the HLA allele and haplotype frequencies for each national sample using population genetic and clustering methods. Population differentiation among diaspora populations was shown on the basis of HLA haplotype frequencies, including differences within the more recently diverged European groups. A method of haplotype and population clustering showed patterns of unique haplotype affinities associated with specific Jewish populations. The evidence showed that diaspora Jewish populations can be sorted into distinct clades of which the Ashkenazi are but one. Relationships among Jewish populations are interpretable in light of the historical record. We suggest that a major contributing factor to the genetic divergence between Jewish groups may have been admixture with local host populations, while, at the same time, threads of Eastern Mediterranean ancestry remain evident.

Four-locus high-resolution HLA typing in a sample of Mexican Americans.

Mexicans are the most common minority population of the United States. From a sample of 553 bone marrow donor registrants of self-described Mexican ancestry, human leukocyte antigen (HLA) loci A, C, B and DRB1 were typed by high resolution sequence based typing (SBT) methods. A total of 47, 34, 76 and 46 distinct alleles at A, C, B and DRB1 respectively were identified, including 3 new alleles. The four-locus haplotype frequency distribution was extremely skewed with only 53.9% of 1106 chromosomes present with more than one estimated copy. Haplotypes of Native American origin were identified. These data form an initial basis for determining the requirements for an adequate donor pool for stem cell transplantation in this population.