Comparison of high-resolution human leukocyte antigen haplotype frequencies in different ethnic groups: Consequences of sampling fluctuation and haplotype frequency distribution tail truncation

Optimisation of global stem cell donor recruitment based on analysis of unsuccessful donor searches

Despite over 41 million registered potential volunteer stem cell donors worldwide, many patients in need of a transplant do not find an HLA-matched unrelated donor or cord blood units, with the respective odds differing significantly between various populations. In this study, we analysed data of 2205 unsuccessful real-life donor searches sent to the DKMS Registry to identify populations in which further donor recruitment would be associated with particularly large patient benefits. For that purpose, we estimated haplotype frequencies of 67 donor populations at various sample sizes and entered them into two different mathematical models. These models assessed patient benefits from population-specific donor recruitment, operationalised by the number of originally unsuccessful searches that may become successful due to new donors. Consistently, across the different mathematical models and sample sizes, we obtained several countries from East and Southeast Asia (Thailand, Vietnam, China, and the Philippines) and the population of Asians in the USA as countries/populations where donor recruitment activities would be particularly beneficial for patients. We also identified various countries in Southeast and Central Europe as possible target regions for donor recruitment with above-average patient benefits. The results presented are registry-specific in the sense that they were obtained by optimising unsuccessful searches that had been sent to the DKMS Registry. Therefore, it would be desirable to apply the presented methods to a global data set that includes all unsuccessful stem cell donor searches worldwide and uses population-specific haplotype frequencies based on all donors available in the WMDA Search & Match Service.

Providing hematopoietic stem cell products from unrelated donors to the world: DKMS donor centers and DKMS Registry

Allogeneic hematopoietic stem cell (HSC) transplantation is a curative therapy for many severe blood diseases. As many patients have no suitable family donor, large unrelated donor registries and donor centers have been established in many countries, along with an international system for the provision of unrelated donor HSC products. As an essential part of this system, DKMS operates donor centers in 7 countries with a total of 12.2 million donors and over 114,000 donations so far, and a multinational donor registry. In 2022, DKMS donors contributed 57.5% of all cross-border donations worldwide. In this review, we describe the international system for the provision of unrelated donor HSC products as well as tasks and responsibilities of donor registries and donor centers. We also discuss relevant aspects of DKMS donor centers, namely donor file composition, matching and donation probabilities and actual donations, and the unique multinational approach of the DKMS Registry.

Optimal population-specific HLA imputation with dimension reduction

Human genomics has quickly evolved, powering genome-wide association studies (GWASs). SNP-based GWASs cannot capture the intense polymorphism of HLA genes, highly associated with disease susceptibility. There are methods to statistically impute HLA genotypes from SNP-genotypes data, but lack of diversity in reference panels hinders their performance. We evaluated the accuracy of the 1000 Genomes data as a reference panel for imputing HLA from admixed individuals of African and European ancestries, focusing on (a) the full dataset, (b) 10 replications from 6 populations, and (c) 19 conditions for the custom reference panels. The full dataset outperformed smaller models, with a good F1-score of 0.66 for HLA-B. However, custom models outperformed the multiethnic or population models of similar size (F1-scores up to 0.53, against up to 0.42). We demonstrated the importance of using genetically specific models for imputing populations, which are currently underrepresented in public datasets, opening the door to HLA imputation for every genetic population.

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.

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.

GMP-grade CD34+ selection from HLA-homozygous licensed cord blood units and short-term expansion under European ATMP regulations

BACKGROUND

Based on a synergistic consortium, the cord blood (CB) bank Düsseldorf was responsible for the selection of HLA-homozygous (HLA-h) donors, contacting/re-consenting the mothers, Good Manufacturing Practice (GMP)-grade CD34⁺ enrichment, followed by short-term expansion of CD34⁺ cells and qualification of the resulting CD34⁺ population as advanced therapy medicinal product (ATMP)-starting material. Among 20 639 licensed Düsseldorf cord blood units (CBUs), 139 potential HLA-h donors were identified with the most frequent 10 German haplotypes. 100% of the donors were contacted, and for 47·5%, consent was obtained. HLA-A, -B, -C, -DR, -DQ and -DP were determined by sequencing.

METHODS

Thawing/washing of the CBUs was performed in the presence of Volulyte/HSA with Sepax^® , CD34⁺ selection by automated CliniMACS^® -system (Miltenyi), expansion with qualified GMP-grade cytokines and media in the GMP facility.

RESULTS

Here, we specify minimal criteria (≥5 x 10⁵ viable CD34⁺ -count, ≥80% CD34⁺ -purity and ≥70% viability) and confirm that n = 10 CB units (max storage time 16 years) could be qualified for an ATMP starting material. The mean fold change expansion of isolated CD34⁺ cells at Day 3/4 (d3/4) was 3·38 ± 3·02 with a mean purity of 86·90 ± 10·38% and a high viability of 96·07 ± 4·72%.

CONCLUSION

As of March 2019, approval was obtained by the Bezirksregierung Düsseldorf for the GMP-compliant production. The production of HLA-homozygous expanded CD34⁺ cells from cryopreserved CB under European ATMP regulations presented here describes the successful clinical translation and implementation of a qualified manufacturing process. This approach considers the main obstacle of rejection of transplanted cells (due to the immunological HLA barrier) by preselection of HLA-homozygous transplants.

Easy-HLA: a validated web application suite to reveal the full details of HLA typing

MOTIVATION

The HLA system plays a pivotal role in both clinical applications and immunology research. Typing HLA genes in patient and donor is indeed required in hematopoietic stem cell and solid-organ transplantation, and the histocompatibility complex region exhibits countless genetic associations with immune-related pathologies. Since the discovery of HLA antigens, the HLA system nomenclature and typing methods have constantly evolved, which leads to difficulties in using data generated with older methodologies.

RESULTS

Here, we present Easy-HLA, a web-based software suite designed to facilitate analysis and gain knowledge from HLA typing, regardless of nomenclature or typing method. Easy-HLA implements a computational and statistical method of HLA haplotypes inference based on published reference populations containing over 600 000 haplotypes to upgrade missing or partial HLA information: 'HLA-Upgrade' tool infers high-resolution HLA typing and 'HLA-2-Haplo' imputes haplotype pairs and provides additional functional annotations (e.g. amino acids and KIR ligands). We validated both tools using two independent cohorts (total n = 2500). For HLA-Upgrade, we reached a prediction accuracy of 92% from low- to high-resolution of European genotypes. We observed a 96% call rate and 76% accuracy with HLA-2-Haplo European haplotype pairs prediction. In conclusion, Easy-HLA tools facilitate large-scale immunogenetic analysis and promotes the multi-faceted HLA expertise beyond allelic associations by providing new functional immunogenomics parameters.

AVAILABILITY AND IMPLEMENTATION

Easy-HLA is a web application freely available (free account) at: https://hla.univ-nantes.fr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Immunogenetics in stem cell donor registry work: The DKMS example (Part 1)

Currently, stem cell donor registries include more than 35 million potential donors worldwide to provide HLA-matched stem cell products for patients in need of an unrelated donor transplant. DKMS is a leading stem cell donor registry with more than 9 million donors from Germany, Poland, the United States, the United Kingdom, India and Chile. DKMS donors have donated hematopoietic stem cells more than 80,000 times. Many aspects of donor registry work are closely related to topics from immunogenetics or population genetics. In this two-part review article, we describe, analyse and discuss these areas of donor registry work by using the example of DKMS. Part 1 of the review gives a general overview on DKMS and includes typical donor registry activities with special focus on the HLA system: high-throughput HLA typing of potential stem cell donors, HLA haplotype frequencies and resulting matching probabilities, and donor file optimization with regard to HLA diversity.

HLA alleles and haplotypes observed in 263 US families

The 17th International HLA and Immunogenetics Workshop (IHIW) conducted a project entitled "The Study of Haplotypes in Families by NGS HLA". We investigated the HLA haplotypes of 1017 subjects in 263 nuclear families sourced from five US clinical immunogenetics laboratories, primarily as part of the evaluation of related donor candidates for hematopoietic stem cell and solid organ transplantation. The parents in these families belonged to five broad groups - African (72 parents), Asian (115), European (210), Hispanic (118) and "Other" (11). High-resolution HLA genotypes were generated for each subject using next-generation sequencing (NGS) HLA typing systems. We identified the HLA haplotypes in each family using HaplObserve, software that builds haplotypes in families by reviewing HLA allele segregation from parents to children. We calculated haplotype frequencies within each broad group, by treating the parents in each family as unrelated individuals. We also calculated standard measures of global linkage disequilibrium (LD) and conditional asymmetric LD for each ethnic group, and used untruncated and two-field allele names to investigate LD patterns. Finally we demonstrated the utility of consensus DNA sequences in identifying novel variants, confirming them using HLA allele segregation at the DNA sequence level.

HLA-VBSeq v2: improved HLA calling accuracy with full-length Japanese class-I panel

HLA-VBSeq is an HLA calling tool developed to infer the most likely HLA types from high-throughput sequencing data. However, there is still room for improvement in specific genetic groups because of the diversity of HLA alleles in human populations. Here, we present HLA-VBSeq v2, a software application that makes use of a new Japanese HLA reference panel to enhance calling accuracy for Japanese HLA class-I genes. Our analysis showed significant improvements in calling accuracy in all HLA regions, with prediction accuracies achieving over 99.0, 97.8, and 99.8% in HLA-A, B and C, respectively.

Utility of allogeneic hematopoietic stem cell transplantation using international donors in a homogenous ethnic population: question in the era of various alternative donors

The advent of various alternative donors in allogeneic hematopoietic stem cell transplantation (HSCT) raises the question of using international donors, especially in ethnically homogenous populations. We analyzed the clinical outcome and medical expense of human leukocyte antigen (HLA)-matched HSCT using domestic and international donors. We analyzed the patients who received allogeneic HSCT at five medical centers in Korea in the last 10 years. Using propensity-score matching, we compared overall survival (OS), relapse-free survival (RFS), and transplantation-related complications. Medical expense was analyzed based on National Health Insurance Service (NHIS) data. A total of 269 patients were analyzed after 3:1 (domestic/international) matching. There was no difference in OS (p = 0.395) and RFS (p = 0.604) between the domestic and international donor groups (5-year OS rate 42.9 and 37.8%, 5-year RFS rate 37.6 and 33.5% for domestic and international groups, respectively). No difference in chronic graft-versus-host disease (GVHD) incidence was observed (34.2% in domestic and 35.9% in international group, p = 0.804). Early infection was more frequent in the domestic group (55.0 vs. 35.8%, p = 0.007), whereas infection after 30 days was more frequent in the international group (28.7 vs. 49.3%, p = 0.001). Mean medical expense was far higher in the international group, by US $51,944 in the entire follow-up period (p < 0.001). We would expect similar outcomes for international and domestic donors in terms of survival and treatment-related complications with HLA-matched HSCT in other ethnically homogenous populations. These findings should be considered together with the high cost of using international donors in the era of various alternative donors.

Highly conserved extended haplotypes of the major histocompatibility complex and their relationship to multiple sclerosis susceptibility

Objective

To determine the relationship between highly-conserved extended-haplotypes (CEHs) in the major histocompatibility complex (MHC) and MS-susceptibility.

Background

Among the ~200 MS-susceptibility regions, which are known from genome-wide analyses of single nucleotide polymorphisms (SNPs), the MHC accounts for roughly a third of the currently explained variance and the strongest MS-associations are for certain Class II alleles (e.g., HLA-DRB1*15:01; HLA-DRB1*03:01; and HLA-DRB1*13:03), which frequently reside on CEHs within the MHC.

Design/Methods

Autosomal SNPs (441,547) from 11,376 MS cases and 18,872 controls in the WTCCC dataset were phased. The most significant MS associated SNP haplotype was composed of 11 SNPs in the MHC Class II region surrounding the HLA-DRB1 gene. We also phased alleles at the HLA-A, HLA-C, HLA-B, HLA-DRB1, and HLA-DQB1 loci. This data was used to probe the relationship between CEHs and MS susceptibility.

Results

We phased a total of 59,884 extended haplotypes (HLA-A, HLA-C, HLA-B, HLA-DRB1, HLA-DQB1 and SNP haplotypes) from 29,942 individuals. Of these, 10,078 unique extended haplotypes were identified. The 10 most common CEHs accounted for 22% (13,302) of the total. By contrast, the 8,446 least common extended haplotypes also accounted for approximately 20% (12,298) of the total. This extreme frequency-disparity among extended haplotypes necessarily complicates interpretation of reported disease-associations with specific HLA alleles. In particular, the HLA motif HLA-DRB1*15:01~HLA-DQB1*06:02 is strongly associated with MS risk. Nevertheless, although this motif is almost always found on the a1 SNP haplotype, it can rarely be found on others (e.g., a27 and a36), and, in these cases, it seems to have no apparent disease-association (OR = 0.7; CI = 0.3–1.3 and OR = 0.7; CI = 0.2–2.2, respectively). Furthermore, single copy carriers of the a1 SNP-haplotype without this HLA motif still have an increased disease risk (OR = 2.2; CI = 1.2–3.8). In addition, even among the set of CEHs, which carry the Class II motif of HLA-DRB1*15:01~HLA-DQB1*06:02~a1, different CEHs have differing strengths in their MS-associations.

Conclusions

The MHC in diverse human populations consists, primarily, of a very small collection of very highly-selected CEHs. Our findings suggest that the MS-association with the HLA-DRB1*15:01~HLA-DQB1*06:02 haplotype may be due primarily to the combined attributes of the CEHs on which this particular HLA-motif often resides.

Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation

Epitope-based HLA matching has been emerged over the last few years as an improved method for HLA matching in solid organ transplantation. The epitope-based matching concept has been incorporated in both the PIRCHE-II and the HLAMatchmaker algorithm to find the most suitable donor for a recipient. For these algorithms, high-resolution HLA genotype data of both donor and recipient is required. Since high-resolution HLA genotype data is often not available, we developed a computational method which allows epitope-based HLA matching from serological split level HLA typing relying on HLA haplotype frequencies. To validate this method, we simulated a donor-recipient population for which PIRCHE-II and eplet values were calculated when using both high-resolution HLA genotype data and serological split level HLA typing. The majority of the serological split level HLA-determined ln(PIRCHE-II)/ln(eplet) values did not or only slightly deviate from the reference group of high-resolution HLA-determined ln(PIRCHE-II)/ln(eplet) values. This deviation was slightly increased when HLA-C or HLA-DQ was omitted from the input and was substantially decreased when using two-field resolution HLA genotype data of the recipient and serological split level HLA typing of the donor. Thus, our data suggest that our computational approach is a powerful tool to estimate PIRCHE-II/eplet values when high-resolution HLA genotype data is not available.

High-Accuracy HLA Type Inference from Whole-Genome Sequencing Data Using Population Reference Graphs

Genetic variation at the Human Leucocyte Antigen (HLA) genes is associated with many autoimmune and infectious disease phenotypes, is an important element of the immunological distinction between self and non-self, and shapes immune epitope repertoires. Determining the allelic state of the HLA genes (HLA typing) as a by-product of standard whole-genome sequencing data would therefore be highly desirable and enable the immunogenetic characterization of samples in currently ongoing population sequencing projects. Extensive hyperpolymorphism and sequence similarity between the HLA genes, however, pose problems for accurate read mapping and make HLA type inference from whole-genome sequencing data a challenging problem. We describe how to address these challenges in a Population Reference Graph (PRG) framework. First, we construct a PRG for 46 (mostly HLA) genes and pseudogenes, their genomic context and their characterized sequence variants, integrating a database of over 10,000 known allele sequences. Second, we present a sequence-to-PRG paired-end read mapping algorithm that enables accurate read mapping for the HLA genes. Third, we infer the most likely pair of underlying alleles at G group resolution from the IMGT/HLA database at each locus, employing a simple likelihood framework. We show that HLA*PRG, our algorithm, outperforms existing methods by a wide margin. We evaluate HLA*PRG on six classical class I and class II HLA genes (HLA-A, -B, -C, -DQA1, -DQB1, -DRB1) and on a set of 14 samples (3 samples with 2 x 100bp, 11 samples with 2 x 250bp Illumina HiSeq data). Of 158 alleles tested, we correctly infer 157 alleles (99.4%). We also identify and re-type two erroneous alleles in the original validation data. We conclude that HLA*PRG for the first time achieves accuracies comparable to gold-standard reference methods from standard whole-genome sequencing data, though high computational demands (currently ~30–250 CPU hours per sample) remain a significant challenge to practical application.

Determining an individual’s HLA type (the sequence of the exons of the HLA genes) is important in many areas of biomedical research. For example, HLA types shape immune epitope repertoires, which are relevant in cancer immunotherapy, and influence autoimmune and infectious disease risk. Whole-genome sequencing data, currently being generated for hundreds of thousands of individuals, contains the information necessary for HLA typing–but inferring accurate HLA types from these is a challenging problem. First, the HLA genes are the most polymorphic genes in the human genome; second, these genes and their variant alleles exhibit high degrees of sequence similarity (due to a shared evolutionary origin). This makes it difficult to establish which specific HLA gene a given observed sequencing read derives from. We show that this problem can be addressed using a Population Reference Graph (PRG): for each gene, the PRG contains not only the reference sequence but also variant alleles, thus enabling, using a novel sequence-to-graph mapping algorithm, the accurate mapping of reads to HLA genes. We also show that HLA*PRG, the algorithm implementing our approach, achieves–based on standard whole-genome sequencing data–accuracies comparable to those of specialized gold-standard methods. HLA*PRG is open source and freely available.

HLA Haplotype Validator for quality assessments of HLA typing

HLA alleles are observed in specific haplotypes, due to Linkage Disequilibrium (LD) between particular alleles. Haplotype frequencies for alleles in strong LD have been established for specific ethnic groups and racial categories. Application of high-resolution HLA typing using Next Generation Sequencing (NGS) is becoming a common practice in research and clinical laboratory settings. HLA typing errors using NGS occasionally occur due to allelic sequence imbalance or misalignment. Manual inspection of HLA genotypes is labor intensive and requires an in-depth knowledge of HLA alleles and haplotypes. We developed the "HLA Haplotype Validator (HLAHapV)" software, which inspects an HLA genotype for both the presence of common and well-documented alleles and observed haplotypes. The software also reports warnings when rare alleles, or alleles that do not belong to recognized haplotypes, are found. The software validates observable haplotypes in genotype data, providing increased confidence regarding the accuracy of the HLA typing, and thus reducing the effort involved in correcting potential HLA typing errors. The HLAHapV software is a powerful tool for quality control of HLA genotypes prior to the application of downstream analyses. We demonstrate the use of the HLAHapV software for identifying unusual haplotypes, which can lead to finding potential HLA typing errors.

Asymmetric linkage disequilibrium: Tools for assessing multiallelic LD

Standard measures of linkage disequilibrium (LD) provide an incomplete description of the correlation between two loci. Recently, Thomson and Single (2014) described a new asymmetric pair of LD measures (ALD) that give a more complete description of LD. The ALD measures are symmetric and equivalent to the correlation coefficient r when both loci are bi-allelic. When the numbers of alleles at the two loci differ, the ALD measures capture this asymmetry and provide additional detail about the LD structure. In disease association studies the ALD measures are useful for identifying additional disease genes in a genetic region, by conditioning on known effects. In evolutionary genetic studies ALD measures provide insight into selection acting on individual amino acids of specific genes, or other loci in high LD (see Thomson and Single (2014) for these examples). Here we describe new software for computing and visualizing ALD. We demonstrate the utility of this software using haplotype frequency data from the National Marrow Donor Program (NMDP). This enhances our understanding of LD patterns in the NMDP data by quantifying the degree to which LD is asymmetric and also quantifies this effect for individual alleles.

Proceedings: human leukocyte antigen haplo-homozygous induced pluripotent stem cell haplobank modeled after the california population: evaluating matching in a multiethnic and admixed population

The development of a California-based induced pluripotent stem cell (iPSC) bank based on human leukocyte antigen (HLA) haplotype matching represents a significant challenge and a valuable opportunity for the advancement of regenerative medicine. However, previously published models of iPSC banks have neither addressed the admixed nature of populations like that of California nor evaluated the benefit to the population as a whole. We developed a new model for evaluating an iPSC haplobank based on demographic and immunogenetic characteristics reflecting California. The model evaluates haplolines or cell lines from donors homozygous for a single HLA-A, HLA-B, HLA-DRB1 haplotype. We generated estimates of the percentage of the population matched under various combinations of haplolines derived from six ancestries (black/African American, American Indian, Asian/Pacific Islander, Hispanic, and white/not Hispanic) and data available from the U.S. Census Bureau, the California Institute for Regenerative Medicine, and the National Marrow Donor Program. The model included both cis (haplotype-level) and trans (genotype-level) matching between a modeled iPSC haplobank and the recipient population following resampling simulations. We showed that serving a majority (>50%) of a simulated California population through cis matching would require the creation, redundant storage, and maintenance of almost 207 different haplolines representing the top 60 most frequent haplotypes from each ancestry group. Allowances for trans matching reduced the haplobank to fewer than 141 haplolines found among the top 40 most frequent haplotypes. Finally, we showed that a model optimized, custom haplobank was able to serve a majority of the California population with fewer than 80 haplolines.