Knowledge of an individual’s 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 twenty 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 KIR genotype data that can be applied to any genetic data that employs a standard nomenclature for identifying variants. The GL String format employs 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.

The human leukocyte antigen (HLA) distribution in donor registry data is typically nonrandom as, mostly for economical reasons, typing additional loci or resolving ambiguities is selectively performed based on the previously known HLA type. Analyzing a sample of over 1 million German stem cell donors, we practically show the extent of the bias caused by the restriction of the input data for HLA haplotype frequency (HF) estimation to subsets selected according to their higher HLA typing resolution and, conversely, the correctness of estimates based on unselected data with a methodology suitable for heterogeneous resolution. We discuss algorithmic aspects of this approach and, also because of the sample size, provide some new insights into the distribution of HLA-DRB1 alleles in the German population and the application of HFs in unrelated donor search.

Since the advent of the European Marrow Donor Information System in the first half of the last decade, fully automated data exchange between registry computer systems has been playing an ever-increasing role in the international search for unrelated donors of blood progenitor cells. This exchange, however, was hampered by different local conventions used to present HLA data and complicated by the need to extend the official WHO nomenclature to accommodate the registries' information systems and to cross-validate HLA data obtained with different methods and/or at different loci. The guidelines presented here have been developed by the World Marrow Donor Association to standardize the nomenclature to be used and the validation checks to be applied in the international electronic exchange of HLA-typing data among unrelated volunteer hematopoietic stem cell donor registries and umbilical cord blood banks. Two reference web sites have been designated to maintain and update the approved HLA nomenclature and all the ancillary information needed by the conventions described here.

A major goal of the World Marrow Donor Association (WMDA) is to foster international transplants of hematopoietic stem cells through the establishment of guidelines and recommendations in this field. In this tradition, this study defines a comprehensive framework for HLA matching programs, which use intricate algorithms to rapidly select potential donors for a patient from a database and to present these donors in a prioritized list. Starting with the comparison of single HLA markers of the donor and the patient possibly obtained using different testing methodologies at different resolutions, the more complex matching of loci and phenotypes is inductively built up. The consensus of this international collaborative group describes the state of the art in the field and points out many important design options compatible with the best practice. This should help existing registries to review and validate the most critical part of their IT systems and newly created donor registries around the world to tackle one of their real challenges.

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.