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The Genotype List (GL) String grammar for reporting HLA and Killer-cell Immunoglobulin-like Receptor (KIR) genotypes in a text string was described in 2013. Since this initial description, GL Strings have been used to describe HLA and KIR genotypes for more than 40 million subjects, allowing these data to be recorded, stored and transmitted in an easily parsed, text-based format. After a decade of working with HLA and KIR data in GL String format, with advances in HLA and KIR genotyping technologies that have fostered the generation of full-gene sequence data, the need for an extension of the GL String system has become clear. Here, we introduce the new GL String delimiter ?, which addresses the need to describe ambiguity in assigning a gene sequence to gene paralogs. GL Strings that do not include a ? delimiter continue to be interpreted as originally described. This extension represents version 1.1 of the GL String grammar.

The guidelines for the implementation and reporting of HLA nomenclature for the World Marrow Donor Association have served as a reliable standard for communication of HLA data in the hematopoietic cell transplantation process. Wider use of next‐generation sequencing made a special provision of the guidelines increasingly pertinent: how to communicate novel HLA alleles. Novel alleles need to be recognized by the WHO Nomenclature Committee for Factors of the HLA system to obtain official allele designations. Until then they have to be handled according to the specific rules. Leaving the actual rules basically unchanged we give some advice on how to communicate novel alleles to best facilitate the search process for cases where novel alleles are identified on donor or patient side. [ABSTRACT FROM AUTHOR]

We present a catalog of common and well‐documented (CWD) alleles of the German population for the six HLA loci A, B, C, DRB1, DQB1, and DPB1. This study is based on a sample of over 5 million volunteer adult hematopoietic stem cell donors from the 26 German donor centers. To establish the catalog, allele and haplotype frequencies were estimated with a validated implementation of the expectation‐maximization algorithm. CWD criteria similar to existing CWD catalogs were applied in order to be able to put our findings into the context of relevant existing references. Overall, 2155 HLA‐A, ‐B, ‐C, ‐DRB1, ‐DQB1, and ‐DPB1 alleles were identified as CWD in the German donor population representing about 20% of the HLA alleles at two‐field resolution in the IPD‐IMGT/HLA Database release v3.25.0 from July 2016 for these six loci. We found a substantial concordance of CWD alleles between the three catalogs and showed the contribution of the German donor population to the CWD alleles domain. In conclusion, the definition of CWD criteria that allow interoperability, scalability, and flexibility will be crucial for the development of a worldwide CWD catalog. [ABSTRACT FROM AUTHOR]

The degree of HLA concordance with the patient has long been known to be the major donor-related prediction factor for the success of hematopoietic stem cell transplantations and, with the progress of HLA typing technology, selection criteria became more stringent with regard to the recommended loci and resolution. A late refinement was HLA-C matching, which gained broader acceptance only after the turn of the millennium. The enormous HLA polymorphism has always necessitated registries with a large number of donors in order to be able to provide well-matched donors to a substantial fraction of patients. Using a biostatistical approach, we investigated the impact of adding HLA-C at low or high resolution as a supplementary matching criterion on some key parameters in donor provision for a European-Caucasian population. Starting point is donor selection based on allele level matching for HLA-A, -B, -DRB1, and, optionally, HLA-DQB1.Without typing for HLA-C, 68% of the donors selected based on matching for HLA-A, -B, -DRB1, and -DQB1 at high resolution will also match for HLA-C, 29% will have a single and only 3% will have two HLA-C alleles different from the patient. In order to provide the same fraction of patients with a fully matched donor, a registrywould have to be about twice the size if HLA-C is considered in addition to the four other loci, with the exact factor increasing with the registry's size. If the provision of donors with up to a single allele mismatch is considered, this factor doubles due to the strong linkage between HLA-B and -C.These figures only change slightly when HLA-DQB1 is completely ignored or HLA-C matching is only considered at low resolution. Our results contribute to quantifying the medical and economic impact of the progress in donor selection algorithms. [ABSTRACT FROM AUTHOR]

Aim For the modernization of its Search & Match Service started in 2016, Bone Marrow Donors Worldwide (BMDW) envisaged to utilize an established HLA matching algorithm. The OptiMatch® search engine for the probabilistic matching of volunteer unrelated stem cell donors to patients in need of transplant was introduced by the German National Bone Marrow Donor Registry (ZKRD) in 2006. In the subsequent years, the core parts of OptiMatch® were isolated into a deployable stand-alone matching service called OptiMaS (OptiMatch® as a Service). OptiMaS has been used in the production environments of the Canadian OneMatch registry since 2012 and of the Australian Bone Marrow Donor Registry since 2013 and has meanwhile demonstrated to be a sound option for registries to benefit from the advantages of the OptiMatch® matching service locally. Methods In addition to the OptiMatch® search engine, the OptiMaS framework uses solely open-source software. Altogether, OptiMaS is a black box computer giving access to the capabilities of OptiMatch® via a small set of high-level web service functions. It fully supports the EMDIS matching preferences and is compliant with the WMDA HLA Nomenclature Guidelines. Results For this study, we have investigated the live system’s performance for 60 consecutive days as well as for a complete recalculation of the search reports for all patients. The analysis is based on over 29 million donors and cord blood units and on over 4000 for the daily and over 3000 patients for the complete calculation. We have focused on average matching times for typical search settings and highlighted special constellations leading to extreme (low and high) system burden. We have also studied the effects of input parameters on parallel processing. Daily average match time is 2 min with 50% of the searches returning within 25 s on a machine with 4 dedicated matching processes. Conclusions OptiMaS has shown for two representative scenarios to provide an appropriate matching service for BMDW’s global patient and donor load. [ABSTRACT FROM AUTHOR]

Aim: The completeness and resolution of the HLA typing of registered volunteer donors is usually not sufficient to determine their suitability for a concrete patient. Therefore, knowing the probability for each ambiguity in a donor to turn out to be a match is indispensable for planning the search strategy at large and for deciding each single step. Methods: Since the update to version 2 in late 2009, OptiMatch® has been using HLA-A, -B, -C, -DRB1, -DQB1 high resolution haplotype frequencies (HF) to predict the probability that each donor will be a 10/10 or 9/10 match as well as the probability of identity for each of the five loci individually. The HF used had been derived from over 145.000 active donors of ZKRD typed for the five loci at intermediate or high resolution. We retrospectively validated the predictions performing the same calculation for over 38,500 CT samples requested between January 2000 and March 2011 where no high resolution information was available for HLA-A, -B, -C, -DRB1 and -DQB1 at the time of request, but was revealed by the CT result. We grouped predictions in intervals of 5%, then compared the expected and observed number of matches per interval and performed a weighted linear regression. Results: The R2 were >.995, regression coefficients >.94 and absolute intercepts <.05 for all seven variants of predictions carried out [Fig. 1]. Display Omitted Conclusions: The predictive power of the OptiMatch® algorithm exceeds our own expectations. With an adequate base of haplotype frequencies it is an excellent tool for speedy, economic and tailored unrelated donor searches. [Copyright &y& Elsevier]

Study Objectives: Narcolepsy with cataplexy is tightly associated with the HLA class II allele DQB1*06:02. Evidence indicates a complex contribution of HLA class II genes to narcolepsy susceptibility with a recent independent association with HLA-DPB1. The cause of narcolepsy is supposed be an autoimmune attack against hypocretin-producing neurons. Despite the strong association with HLA class II, there is no evidence for CD4+ T-cell-mediated mechanism in narcolepsy. Since neurons express class I and not class II molecules, the final effector immune cells involved might include class I-restricted CD8+ T-cells., Methods: HLA class I (A, B, and C) and II (DQB1) genotypes were analyzed in 944 European narcolepsy with cataplexy patients and in 4,043 control subjects matched by country of origin. All patients and controls were DQB1*06:02 positive and class I associations were conditioned on DQB1 alleles., Results: HLA-A*11:01 (OR = 1.49 [1.18-1.87] P = 7.0*10(-4)), C*04:01 (OR = 1.34 [1.10-1.63] P = 3.23*10(-3)), and B*35:01 (OR = 1.46 [1.13-1.89] P = 3.64*10(-3)) were associated with susceptibility to narcolepsy. Analysis of polymorphic class I amino-acids revealed even stronger associations with key antigen-binding residues HLA-A-Tyr(9) (OR = 1.32 [1.15-1.52] P = 6.95*10(-5)) and HLA-C-Ser(11) (OR = 1.34 [1.15-1.57] P = 2.43*10(-4))., Conclusions: Our findings provide a genetic basis for increased susceptibility to infectious factors or an immune cytotoxic mechanism in narcolepsy, potentially targeting hypocretin neurons., (© 2016 Associated Professional Sleep Societies, LLC.)

Study Objective: Prior research has identified five common genetic variants associated with narcolepsy with cataplexy in Caucasian patients. To replicate and/or extend these findings, we have tested HLA-DQB1, the previously identified 5 variants, and 10 other potential variants in a large European sample of narcolepsy with cataplexy subjects., Design: Retrospective case-control study., Setting: A recent study showed that over 76% of significant genome-wide association variants lie within DNase I hypersensitive sites (DHSs). From our previous GWAS, we identified 30 single nucleotide polymorphisms (SNPs) with P < 10(-4) mapping to DHSs. Ten SNPs tagging these sites, HLADQB1, and all previously reported SNPs significantly associated with narcolepsy were tested for replication., Patients and Participants: For GWAS, 1,261 narcolepsy patients and 1,422 HLA-DQB1*06:02-matched controls were included. For HLA study, 1,218 patients and 3,541 controls were included., Measurements and Results: None of the top variants within DHSs were replicated. Out of the five previously reported SNPs, only rs2858884 within the HLA region (P < 2x10(-9)) and rs1154155 within the TRA locus (P < 2x10(-8)) replicated. DQB1 typing confirmed that DQB1*06:02 confers an extraordinary risk (odds ratio 251). Four protective alleles (DQB1*06:03, odds ratio 0.17, DQB1*05:01, odds ratio 0.56, DQB1*06:09 odds ratio 0.21, DQB1*02 odds ratio 0.76) were also identified., Conclusion: An overwhelming portion of genetic risk for narcolepsy with cataplexy is found at DQB1 locus. Since DQB1*06:02 positive subjects are at 251-fold increase in risk for narcolepsy, and all recent cases of narcolepsy after H1N1 vaccination are positive for this allele, DQB1 genotyping may be relevant to public health policy.