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

Determining the impact of current Canadian stem cell registry policy on donor availability via dynamic registry simulation

BACKGROUND AND OBJECTIVES

When a haematopoietic stem cell registry size is constrained by limits on recruiting, as in Canada, identifying the right person to recruit is a critical determinant of effectiveness. The aim of this study was to evaluate the impact of changes to donor recruitment effort, within ethnic groups, on the matching effectiveness of the Canadian registry as it evolves over time.

MATERIALS AND METHODS

Simulation methods are applied to create a cohort of donor recruits and patients over a 10-year time horizon. New recruits are added to the registry each year, while some existing donors 'age-out' upon reaching their 36th birthday. In a similar fashion, simulated patient lists are created. At the end of each simulated year, simulated patients are matched against the simulated registry.

RESULTS

There are increased matches in non-White populations when diverse registrants are preferentially recruited, but there are larger decreases in the number of matches for Caucasian patients. Additionally, ethnic communities that have limited registrants in the Canadian registry in 2021 do not benefit from increased recruiting efforts as much as communities with a larger initial number of registrants.

CONCLUSION

Preferentially recruiting from non-Caucasian populations reduces the number of matches from Canadian sources because increases in non-Caucasian populations will not fully counterbalance decreases to Caucasian patient matches. Nevertheless, more than 80% of all matches are for Caucasian patients, regardless of the donor recruiting effort within ethnic groups.

Combined imputation of HLA genotype and self-identified race leads to better donor-recipient matching

Allogeneic Hematopoietic Cell Transplantation (HCT) is a curative therapy for hematologic disorders and often requires human leukocyte antigen (HLA)-matched donors. Donor registries have recruited donors utilizing evolving technologies of HLA genotyping methods. This necessitates in-silico ambiguity resolution and statistical imputation based on haplotype frequencies estimated from donor data stratified by self-identified race and ethnicity (SIRE). However, SIRE has limited genetic validity and presents a challenge for individuals with unknown or mixed SIRE. We present MR-GRIMM "Multi-Race Graph IMputation and Matching" that simultaneously imputes the race/ethnic category and HLA genotype using a SIRE based prior. Additionally, we propose a novel method to impute HLA typing inconsistent with current haplotype frequencies. The performance of MR-GRIMM was validated using a dataset of 170,000 donor-recipient pairs. MR-GRIMM has an average 20 % lower matching error (1-AUC) than single-race imputation. The recall metric (sensitivity) of the race/ethnic category imputation from HLA was measured by comparing the imputed donor race with the donor-provided SIRE. Accuracies of 0.74 and 0.55 were obtained for the prediction of 5 broad and 21 detailed US population groups respectively. The operational implementation of this algorithm in a registry search could help improve match predictions and access to HLA-matched donors.

World Marrow Donor Association guidelines for the reporting of novel HLA alleles

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.

Graphical user interface for the haplotype frequency estimation software Hapl-o-Mat

Population-specific human leukocyte antigen (HLA) haplotype frequencies are an essential basis of advanced algorithms for donor selection in unrelated hematopoietic stem cell transplantation. In 2016, we introduced Hapl-o-Mat, a versatile tool for haplotype frequency estimation based on an expectation-maximization algorithm (https://github.com/DKMS/hapl-o-Mat). Hapl-o-Mat is specifically tailored to the analysis of HLA genes and able to cope with the heterogeneous genotyping data usually found in donor registries. To make Hapl-o-Mat accessible to a wider range of users, we designed a graphical user interface module that considerably facilitates the interaction with the application (https://github.com/DKMS/hapl-o-Mat_GUI). We further provide a precompiled version of Hapl-o-Mat that can be used on Windows personal computers without dependency on additional software libraries (https://github.com/DKMS/hapl-o-Mat_WinBin). We are confident that these new, user-oriented features will encourage more researchers to apply Hapl-o-Mat to their data, thereby increasing knowledge and public availability of population-specific HLA haplotype frequencies.

Estimating HLA haplotype frequencies from homozygous individuals - A Technical Report

We estimated HLA haplotype frequencies based on individuals homozygous for 4, 5 or 6 loci. Validation of our approach using a sample of over 3.4 million German individuals was successful. Compared to an expectation‐maximization algorithm, the errors were larger. However, our approach allows the unequivocal detection of rare haplotypes.

HLA haplotype frequency estimation for heterogeneous populations using a graph-based imputation algorithm

HLA haplotype frequencies are estimated from ambiguous unphased HLA genotyping data using Expectation-Maximization (EM) algorithms. Current population genetics methods require independent EM frequency estimates for each population, and assume that each population is in Hardy-Weinberg Equilibrium (HWE). The HWE assumption of EM has thus far resulted in the exclusion of individuals from mixed or unknown ethnic backgrounds from reference datasets. Multi-region populations are currently poorly served by stem cell donor registry HLA imputation and matching implementations due to the inability of such algorithms to incorporate admixture into their population genetics models. To address this unmet need, we have expanded the imputation component of our GRaph IMputation and Matching (GRIMM) framework, where imputation becomes the expectation step in an iterative EM algorithm. Our novel multi-region EM implementation considers region as a Bayesian prior, enabling integration of HLA information from multiple single-region population groups, and for the first time including individuals with ambiguous or mixed ethnic backgrounds. We show that our multi-region EM produces much higher likelihood values and better haplotype recovery as measured by Kullback-Leibler divergence than all evaluated EM implementations when tested on real datasets of US donor registry HLA typings as well as simulated multi-region datasets of ambiguous HLA typings.

High-resolution HLA allele and haplotype frequencies of the Saudi Arabian population based on 45,457 individuals and corresponding stem cell donor matching probabilities

We estimated HLA allele and haplotype frequencies of the Saudi Arabian population from a sample of 45,457 registered stem cell donors. The most frequent HLA alleles were A*02:01g (18.5%), C*06:02g (16.1%), B*51:01g (14.1%), DRB1*07:01g (16.2%), DQB1*02:01g (30.5%), and DPB1*04:01g (33.6%). The most frequent 5-locus haplotypes were A*02:05g~C*06:02g~B*50:01g~DRB1*07:01g~DQB1*02:01g (1.73%), A*02:01g~C*06:02g~B*50:01g~DRB1*07:01g~DQB1*02:01g (1.66%), and A*26:01g~C*07:02g~B*08:01g~DRB1*03:01g~DQB1*02:01g (1.38%). Furthermore, we used the calculated haplotype frequencies to estimate stem cell donor matching probabilities for Saudi Arabian donor and patient populations under various matching requirements. These results are relevant for strategic donor registry planning in the Kingdom of Saudi Arabia.

Naming HLA diversity: A review of HLA nomenclature

The development of a standardized HLA nomenclature has been critical in our understanding of the HLA system and in facilitating the clinical applications of HLA. The Nomenclature Committee for Factors of the HLA System, established in 1968, has overseen the development and usage of nomenclature based on serologic specificities, cellular responses, and DNA sequences. Their decisions have been guided by community consensus reached through 17 international workshops beginning in 1964 and continuing today. Two websites provide a curated database of the sequences of over 26,000 HLA alleles and a reference site for the current nomenclature. This review covers the major steps in the development of the HLA nomenclature as well as the efforts of other groups to extend its usefulness for research and clinical applications.

Estimation of German KIR Allele Group Haplotype Frequencies

The impact of the highly polymorphic Killer-cell immunoglobulin-like receptor (KIR) gene cluster on the outcome of hematopoietic stem cell transplantation (HCST) is subject of current research. To further understand the involvement of this gene family into Natural Killer (NK) cell-mediated graft-versus-leukemia reactions, knowledge of haplotype structures, and allelic linkage is of importance. In this analysis, we estimate population-specific KIR haplotype frequencies at allele group resolution in a cohort of n = 458 German families. We addressed the polymorphism of the KIR gene complex and phasing ambiguities by a combined approach. Haplotype inference within first-degree family relations allowed us to limit the number of possible diplotypes. Structural restriction to a pattern set of 92 previously described KIR copy number haplotypes further reduced ambiguities. KIR haplotype frequency estimation was finally accomplished by means of an expectation-maximization algorithm. Applying a resolution threshold of ½ n, we were able to identify a set of 551 KIR allele group haplotypes, representing 21 KIR copy number haplotypes. The haplotype frequencies allow studying linkage disequilibrium in two-locus as well as in multi-locus analyses. Our study reveals associations between KIR haplotype structures and allele group frequencies, thereby broadening our understanding of the KIR gene complex.

Hap-E Search 2.0: Improving the Performance of a Probabilistic Donor-Recipient Matching Algorithm Based on Haplotype Frequencies

In the setting of hematopoietic stem cell transplantation, donor-patient HLA matching is the prime donor selection criterion. Matching algorithms provide ordered lists of donors where the probability of a donor to be an HLA match is calculated in cases where either donor or patient HLA typing information is ambiguous or incomplete. While providing important information for the selection of suitable donors, these algorithms are computationally demanding and often need several minutes up to hours to generate search results. Here, we present a new search kernel implementation for Hap-E Search, the haplotype frequency-based matching algorithm of DKMS. The updated search kernel uses pre-calculated information on donor genotypes to speed up the search process. The new algorithm reliably provides search results in <1 min for a large donor database (>9 Mio donors) including matching and mismatching donors, even for frequent or incomplete patient HLA data where the matching list contains several thousand donors. In these cases, the search process is accelerated by factors of 10 and more compared to the old Hap-E Search implementation. The predicted matching probabilities of the new algorithm were validated with data from verification typing requests of 67,550 donor-patient pairs.

Degree of HLA class II eplet mismatch load improves prediction of antibody-mediated rejection in living donor kidney transplantation

BACKGROUND

HLA mismatching is a well known risk factor for worst outcomes in kidney transplantation.

METHODS

In the present study, HLA antigen and eplet mismatches were determined in 151 living donor-recipient pairs transplanted between 2007 and 2014 and rejection episodes and graft survival were evaluated.

RESULTS

We found that high HLA-II eplet mismatch load (EpMM ≥ 13, versus low EpMM ≤ 5), was an independent predictor of AMR (adjusted HR = 14.839; P = 0.011), while HLA-II AgMM was not. We also showed that HLA-II EpMM load was a significant better predictor of AMR than AgMM (c-statistic = 0.064; P = 0.023). After discriminating HLA-II into HLA-DR and HLA-DQ loci we demonstrated that high versus low eplet mismatch load for HLA-DR (T3 ≥ 6 versus T = 0-1, p = 0.013) and HLA-DQ (T3 ≥ 7 versus T = 0-1, p = 0.009) are independent predictors for AMR. HLA-II EpMM increased discrimination performance of the classical HLA-II AgMM risk model (IDI, 0.061, 95%CI: 0.005-0.195) for AMR. Compared with AgMM, HLA-II eplet model adequately reclassified 13 of 17 patients (76.5%) with AMR and 92 of 134 patients (68.7%) without AMR (cfNRI, 0.785, 95%CI: 0.300-1.426).

CONCLUSIONS

Our study evidences that eplet-based matching is a refinement of the classical HLA antigen mismatch analysis in LDKT and is a potential biomarker for personalized assessment of alloimmune risk.

HLA Haplotypes In 250 Families: The Baylor Laboratory Results And A Perspective On A Core NGS Testing Model For The 17th International HLA And Immunogenetics Workshop

Since their inception, the International HLA & Immunogenetics Workshops (IHIW) served as a collaborative platform for exchange of specimens, reference materials, experiences and best practices. In this report we present a subset of the results of human leukocyte antigen (HLA) haplotypes in families tested by next generation sequencing (NGS) under the 17th IHIW. We characterized 961 haplotypes in 921 subjects belonging to 250 families from 8 countries (Argentina, Austria, Egypt, Jamaica, Germany, Greece, Kuwait, and Switzerland). These samples were tested in a single core laboratory in a high throughput fashion using 6 different reagents/software platforms. Families tested included patients evaluated clinically as transplant recipients (kidney and hematopoietic cell transplant) and their respective family members. We identified 486 HLA alleles at the following loci HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, -DPB1 (77, 115, 68, 69, 10, 6, 4, 44, 31, 20 and 42 alleles, respectively). We also identified nine novel alleles with polymorphisms in coding regions. This approach of testing samples from multiple laboratories across the world in different stages of technology implementation in a single core laboratory may be useful for future international workshops. Although data presented may not be reflective of allele and haplotype frequencies in the countries to which the families belong, they represent an extensive collection of 3rd and 4th field resolution level 11-locus haplotype associations of 486 alleles identified in families from 8 countries.

A study of selected hematopoietic stem cell donors provided by an intermediate size registry

OBJECTIVE

Planning new hematopoietic stem cell (HSC) donor recruitment strategies requires a sound understanding of the factors underlying donor selection, especially considering HLA-matching criteria.

METHOD

A total of 182 consecutive workups of Swiss donors performed from 2014 to 2017 were analyzed for HLA match level, locus disparities, number of potentially 10/10 matched donors in the international database, donor ranking on the lists, donor date of registration, age, ABO, CMV, gender matching, patient genotype frequency, and country performing the search.

RESULTS

Matching status of the selected donors was 10/10 for 38.5%, 10-12/12 for 35.1%, and 8-9/10 for 26.4% donors, without differences in average donor age in the three categories. HLA-A and -C mismatches were most frequent and -DRB1 very rare. 8.2% patients were matched for HLA-DPB1 (12/12). ABO matching was 46.3%, and CMV matching was 59.1%. Based on "HaploStat"-derived genotype frequencies, 50.3% patients belonged to the "good," 38.5% to the "fair," and 11.2% to the "poor" search prognosis categories. 37.9% of transplants were gender-mismatched, and 42.3% of donors were female.

CONCLUSION

HLA typing quality (high resolution, all loci typed), great diversity of haplotypes and donor age are main factors impacting the selection of Swiss donors, while gender and ABO matching seem to be of secondary importance.

Common and well-documented HLA alleles of German stem cell donors by haplotype frequency estimation

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.

Extended HLA Haplotypes and Their Impact on DPB1 Matching of Unrelated Hematologic Stem Cell Transplant Donors

Although HLA-DPB1 has long been considered of lesser importance in the selection of an unrelated donor (URD) hematologic stem cell transplantation, currently in many instances the DPB1 type of the donor is relevant or even critical. At present, however, only a minority of registry donors are DPB1 typed. It is also unclear to what extent the DPB1 alleles are linked to the 5-locus HLA-A-, B-, C-, DRB1, -DQB1 haplotypes. We sought to study whether there is such a linkage by using donors in the Finnish Stem Cell Registry as the study population. The 6-locus HLA-A, -B, -C, -DRB1, -DQB1, -DPB1 haplotype frequencies were estimated from a group of 43,365 Finnish registry donors using the German National Bone Marrow Registry algorithm. Five-locus haplotype (HLA-A, -B, -C, -DRB1, -DQB1) and HLA-DPB1 allele frequencies were calculated as marginal frequencies of the estimated 6-locus haplotype frequencies. The Finnish average frequency of individual DPB1 alleles was compared with their respective frequencies in association with individual 5-locus HLA haplotypes (haplotype-specific frequencies). Finally, the probability of DPB1 matching in 10/10 matched URD transplants was assessed. Haplotype-specific DPB1 frequencies differed significantly from the average DPB1 frequencies in 81 of 100 most frequent Finnish 5-locus HLA haplotypes, including some infrequent DPB1 alleles that were associated almost exclusively with certain individual 5-locus haplotypes. Five-locus haplotypes that are enriched in Finland but rare among other Europeans carried stronger DPB1 associations than haplotypes that are frequent European-wide. Finally, 10/10 matched transplants from domestic registry donors were significantly more likely to also be DPB1 matched than those from foreign donors. The results indicate an extension of linkage disequilibrium in the MHC complex in the Finnish population. With continuing upfront DPB1 typing of registry donors, it will be possible to perform similar extended 6-locus haplotype frequency estimations also in other registries. The associations are likely to be population specific but may be weaker in more heterogeneous populations. In the future the results might be used to predict the probability of DPB1 match or permissive/nonpermissive DPB1 mismatch for non-DPB1 typed donors in registry donor searches.

In silico prediction of nonpermissive HLA-DPB1 mismatches in unrelated HCT by functional distance

In silico prediction of high-risk donor-recipient HLA mismatches after unrelated donor (UD) hematopoietic cell transplantation (HCT) is an attractive, yet elusive, objective. Nonpermissive T-cell epitope (TCE) group mismatches were defined by alloreactive T-cell cross-reactivity for 52/80 HLA-DPB1 alleles (TCE-X). More recently, a numerical functional distance (FD) scoring system for in silico prediction of TCE groups based on the median impact of exon 2-encoded amino acid polymorphism on T-cell alloreactivity was developed for all DPB1 alleles (TCE-FD), including the 28/80 common alleles not assigned by TCE-X. We compared clinical outcome associations of nonpermissive DPB1 mismatches defined by TCE-X or TCE-FD in 8/8 HLA-matched UD-HCT for acute leukemia, myelodysplastic syndrome, and chronic myelogenous leukemia between 1999 and 2011 (N = 2730). Concordance between the 2 models was 92.3%, with most differences arising from DPB1*06:01 and DPB1*19:01 being differently assigned by TCE-X and TCE-FD. In both models, nonpermissive mismatches were associated with reduced overall survival (hazard ratio [HR], 1.15, P < .006 and HR, 1.12, P < .03), increased transplant-related mortality (HR, 1.31, P < .001 and HR, 1.26, P < .001) as well as acute (HR, 1.16, P < .02 and HR, 1.22, P < .001) and chronic (HR, 1.20, P < .003 and HR, 1.22, P < .001) graft-versus-host disease (GVHD). We show that in silico prediction of nonpermissive DPB1 mismatches significantly associated with major transplant outcomes is feasible for any DPB1 allele with known exon 2 sequence based on experimentally elaborated FD scores. This proof-of-principle observation opens new avenues for developing HLA risk-prediction models in HCT and has practical implications for UD searches.

Tools for building, analyzing and evaluating HLA haplotypes from families

The highly polymorphic classical human leukocyte antigen (HLA) genes display strong linkage disequilibrium (LD) that results in conserved multi-locus haplotypes. For unrelated individuals in defined populations, HLA haplotype frequencies can be estimated using the expectation-maximization (EM) method. Haplotypes can also be constructed using HLA allele segregation from nuclear families. It is straightforward to identify many HLA genotyping inconsistencies by visually reviewing HLA allele segregation in family members. It is also possible to identify potential crossover events when two or more children are available in a nuclear family. This process of visual inspection can be unwieldy, and we developed the "HaplObserve" program to standardize the process and automatically build haplotypes using family-based HLA allele segregation. HaplObserve facilitates systematically building haplotypes, and reporting potential crossover events. HLA Haplotype Validator (HLAHapV) is a program originally developed to impute chromosomal phase from genotype data using reference haplotype data. We updated and adapted HLAHapV to systematically compare observed and estimated haplotypes. We also used HLAHapV to identify haplotypes when uninformative HLA genotypes are present in families. Finally, we developed "pould", an R package that calculates haplotype frequencies, and estimates standard measures of global (locus-level) LD from both observed and estimated haplotypes.

GRIMM: GRaph IMputation and matching for HLA genotypes

Motivation

For over 10 years allele-level HLA matching for bone marrow registries has been performed in a probabilistic context. HLA typing technologies provide ambiguous results in that they could not distinguish among all known HLA alleles equences; therefore registries have implemented matching algorithms that provide lists of donor and cord blood units ordered in terms of the likelihood of allele-level matching at specific HLA loci. With the growth of registry sizes, current match algorithm implementations are unable to provide match results in real time.

Results

We present here a novel computationally-efficient open source implementation of an HLA imputation and match algorithm using a graph database platform. Using graph traversal, the matching algorithm runtime is practically not affected by registry size. This implementation generates results that agree with consensus output on a publicly-available match algorithm cross-validation dataset.

Availability and implementation

The Python, Perl and Neo4j code is available at https://github.com/nmdp-bioinformatics/grimm.

Supplementary information

Supplementary data are available at Bioinformatics online.

A European HLA Isolate and Its Implications for Hematopoietic Stem Cell Transplant Donor Procurement

Europeans have often been considered a homogenous group in registry donor match predictions, but it is now evident that HLA haplotype frequencies vary across the European continent. Earlier studies have indicated that Finns in northeastern Europe have unique HLA characteristics, and the increasing availability of high-resolution registry donor data is now making more detailed comparisons possible. In the first phase of the present study, estimated HLA haplotype frequencies in stem cell donor registries of Finland and its neighbors Sweden and Russia were calculated using the algorithm of the German National Bone Marrow Donor Registry (ZKRD) and their frequencies were compared with one another and also with that of Germany. Virtual donor searches for 1492 high-resolution typed Finnish patients in the Finnish, Swedish and German registries were then performed, using individual match predictions for each registry. In the last phase, the impact of specifically Finnish-enriched HLA haplotypes on Finnish patients and the use of Finnish registry donors was assessed by analyzing 647 consecutive hematopoietic stem cell transplantation (HSCT) donor searches and 40 exported Finnish HSCTs. The Finnish HLA landscape was more homogenous than the 3 other studied populations, but also genetically distinct from them. The match predictions found a probable 10/10 match for 71%, 41%, and 31% of the Finnish patients in the German, Finnish, and Swedish registries, respectively. Thirty-four of Finland's 100 most frequent HLA haplotypes were represented with a frequency of <.0003 in Germany, and with an 8- to 3262-fold greater frequency in Finland than in Germany. Patients carrying these Finnish-enriched haplotypes were less likely to receive a matched HSCT but more likely to receive it from a domestic donor. Registry donors carrying them were more likely to donate stem cells, both nationally and internationally. The Finnish HLA isolate has a significant impact on both Finnish patients and registry donors, explaining the high use of national registry donors for Finnish patients. Haplotype frequency estimations are an important tool for small registries as well, to help optimize donor match predictions and the size of individual registries.

HLA Amino Acid Polymorphisms and Kidney Allograft Survival

Background

The association of HLA mismatching with kidney allograft survival has been well established. We examined whether amino acid (AA) mismatches (MMs) at the antigen recognition site of HLA molecules represent independent and incremental risk factors for kidney graft failure (GF) beyond those MMs assessed at the antigenic (2-digit) specificity.

Methods

Data on 240 024 kidney transplants performed between 1987 and 2009 were obtained from the Scientific Registry of Transplant Recipients. We imputed HLA-A, -B, and -DRB1 alleles and corresponding AA polymorphisms from antigenic specificity through the application of statistical and population genetics inferences. GF risk was evaluated using Cox proportional-hazards regression models adjusted for covariates including patient and donor risk factors and HLA antigen MMs.

Results

We show that estimated AA MMs at particular positions in the peptide-binding pockets of HLA-DRB1 molecule account for a significant incremental risk that was independent of the well-known association of HLA antigen MMs with graft survival. A statistically significant linear relationship between the estimated number of AA MMs and risk of GF was observed for HLA-DRB1 in deceased donor and living donor transplants. This relationship was strongest during the first 12 months after transplantation (hazard ratio, 1.30 per 15 DRB1 AA MM; P < 0.0001).

Conclusions

This study shows that independent of the well-known association of HLA antigen (2-digit specificity) MMs with kidney graft survival, estimated AA MMs at peptide-binding sites of the HLA-DRB1 molecule account for an important incremental risk of GF.

In a population of 240 024 kidney transplant recipients using the data of the Scientific Registry of Transplant recipients, the authors demonstrate that, independently of HLA antigen mismatches, estimated amino-acid mismatches at peptide-binding sites of the HLA-DRB1 molecule, accounts for an increased graft failure risk. Supplemental digital content is available in the text.

HLA-DP in unrelated hematopoietic cell transplantation revisited: challenges and opportunities

When considering HLA-matched hematopoietic cell transplantation (HCT), sibling and unrelated donors (UDs) are biologically different because UD-HCT is typically performed across HLA-DP disparities absent in sibling HCT. Mismatched HLA-DP is targeted by direct alloreactive T cell responses with important implications for graft-versus-host disease and graft-versus-leukemia. This concise review details special features of HLA-DP as model antigens for clinically permissive mismatches mediating limited T-cell alloreactivity with minimal toxicity, and describes future avenues for their exploitation in cellular immunotherapy of malignant blood disorders.

Directionality of non-permissive HLA-DPB1 T-cell epitope group mismatches does not improve clinical risk stratification in 8/8 matched unrelated donor hematopoietic cell transplantation

In 8/8 HLA-matched unrelated donor (UD) hematopoietic cell transplants (HCT), HLA-DPB1 mismatches between alleles from different T-cell epitope (TCE) groups (non-permissive mismatches) are associated with significantly higher risks of mortality compared with those between alleles from the same TCE group (permissive mismatches); however, the relevance of mismatch directionality, that is (host vs graft (uni-directional HvG), graft vs host (uni-directional GvH) or both (bi-directional) in the non-permissive setting is unknown. We show here significantly higher in vitro relative responses (RR) to bi-directional mismatches compared with uni-directional HvG or GvH mismatches in a total of 420 one-way mixed lymphocyte reactions between 10/10 matched pairs (RR 27.5 vs 7.5 vs 15.5, respectively, P<0.001). However, in 3281 8/8 matched UD HCT for leukemia or myelodysplastic syndrome, the hazards of transplant-related mortality (TRM) were similar for uni-directional HvG or GvH mismatches and bi-directional mismatches (hazard ratio (HR) 1.32, P=0.001 vs HR 1.28, P=0.005 and HR 1.34, P=0.046), compared with permissive mismatches. Similar results were observed for overall survival. No statistical differences between the uni- and the bi-directional non-permissive groups were detected in pairwise comparisons for any of the outcomes tested. We conclude that consideration of directionality does not improve risk stratification by non-permissive HLA-DPB1 TCE mismatches in UD searches.

Hapl-o-Mat: open-source software for HLA haplotype frequency estimation from ambiguous and heterogeneous data

BACKGROUND

Knowledge of HLA haplotypes is helpful in many settings as disease association studies, population genetics, or hematopoietic stem cell transplantation. Regarding the recruitment of unrelated hematopoietic stem cell donors, HLA haplotype frequencies of specific populations are used to optimize both donor searches for individual patients and strategic donor registry planning. However, the estimation of haplotype frequencies from HLA genotyping data is challenged by the large amount of genotype data, the complex HLA nomenclature, and the heterogeneous and ambiguous nature of typing records.

RESULTS

To meet these challenges, we have developed the open-source software Hapl-o-Mat. It estimates haplotype frequencies from population data including an arbitrary number of loci using an expectation-maximization algorithm. Its key features are the processing of different HLA typing resolutions within a given population sample and the handling of ambiguities recorded via multiple allele codes or genotype list strings. Implemented in C++, Hapl-o-Mat facilitates efficient haplotype frequency estimation from large amounts of genotype data. We demonstrate its accuracy and performance on the basis of artificial and real genotype data.

CONCLUSIONS

Hapl-o-Mat is a versatile and efficient software for HLA haplotype frequency estimation. Its capability of processing various forms of HLA genotype data allows for a straightforward haplotype frequency estimation from typing records usually found in stem cell donor registries.