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Five locus allele-level HLA-A, -B, -C, -DRB1, -DQB1 allele and haplotype frequencies have been calculated for almost 29,000 people from three Arab populations that live in Israel and were recruited as donors to the Hadassah bone marrow donor registry. These groups are of Muslim, Christian and Bedouin Arab descent which represent more than 90% of the Arabs that live in Israel. The goal of the study was to describe the HLA genetic profiles of the Hadassah Arab registry donors and investigate the utility of these donors for the local and international hematopoietic stem-cell transplant community. The results demonstrate that the analyzed Arab populations share at least seven of the top ten most frequent alleles. Comparison with other populations confirmed the proximity of the three Arab populations to each other and to the Be The Match® Middle Eastern population. Despite these similarities, some alleles are private to each of the three groups, possibly because of historical, environmental or societal events. Clinical data showed that Arab donors were HLA matched with Arab and international patients. This analysis indicates the value added by the Hadassah Arab donors to the local and global transplant community. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Registries of Bone Marrow Donors around the world include more than 30 million volunteer donors from 57 different countries, and were responsible for over 17,000 hematopoietic stem cell transplants in 2016. The Brazilian Bone Marrow Volunteer Donor Registry (REDOME) was established in 1993 and is the third largest registry in the world with more than 4.3 million donors. We characterized HLA allele and haplotypes frequencies from REDOME comparing them with the donor self-reported race group classification. Five-locus haplotype frequencies (A~C~B~DRB1~DQB1) were estimated for each of the six race groups, resolving phase and allelic ambiguity using the expectation-maximization (EM) algorithm. The top 100 haplotypes in the race groups were separated into eight clusters of haplotypes, based on haplotype similarity, using CLUTO. We present HLA allele and haplotype frequency data from six race groups from 2,938,259 individuals from REDOME. The most frequent haplotype was the same for all groups: A*01:01g~C*07:01g~B*08:01g~DRB1*03:01g~DQB1*02:01g. Some frequent haplotypes such as A*02:01g~C*16:01g~B*44:03~DRB1*07:01g~DQB1*02:01g was not found in people with Preta (Sub-Saharan African descent). A cluster including Branca (European) and Parda or non-informed (admixed) could be distinguished from both Preta (SubSaharan) and Indígena (Amerindian) groups, and from the Amarela (Asian) ones, which clustered with their original population. These results have implications on cross-population matching and can help in donor searches and population-based recruitment strategies. [ABSTRACT FROM AUTHOR]

HLA haplotype frequencies in a volunteer bone marrow donor registry should reflect the frequencies of potential transplant recipients served by that registry, a challenge in a country with diverse subethnicities of immigrants from Eastern and Western cultures, such as Israel. We evaluated the likelihood of finding suitable donors for hypothetical patients drawn from defined subethnicities in the Ezer Mizion Bone Marrow Donor Registry (EM BMDR) from donors both within and outside the registry now and during the coming decade. On average, bioinformatics modeling predicts that, given current donor recruitment trends, 6/6 high-resolution HLA match rates for Israelis, which currently stand at 40% to 55% for most subethnicities, will rise by up to 1% per year over the next decade. Subethnicities with historically lower rates of interethnic admixture are less likely to find matches outside of their designated group but will benefit from expansion of the registry, whereas ethnically directed drives will enhance matching rates for currently underrepresented subethnicities. Donor searches for the same cohort using a large extramural registry was of only slight benefit for most of the 19 EM BMDR subethnicities evaluated, confirming that local donor registries that reflect the ethnic diversity of the community being served are best equipped to serve the needs of their respective communities. Contemporary trends of an increasingly multiethnic admixture in Israel may impact the effect of ethnic profiling in assessing future match rates for EM BMDR. [ABSTRACT FROM AUTHOR]

We have investigated HLA population alleles and haplotype frequencies for the ethnicities that comprise the contemporary population of Israel, using a large data set from the Ezer Mizion Bone Barrow Donor Registry. We genotyped 275,699 individuals at the HLA-A, -B and -DRB1 loci using HLA genotyping methods. HLA A∼B∼DRB1 haplotype frequencies were estimated from 19 sub-ethnic Jewish populations and other non-Jewish minorities using the maximum likelihood model, which accommodates typing ambiguities. We present overall and sub-ethnicity specific HLA diversity results of the registry, which will help guide a data-driven strategy for future registry expansion. [ABSTRACT FROM AUTHOR]

Aim A publicly available service for assigning HLA allele names to consensus sequences would be a valuable community resource. Our aim was to use existing technologies to develop a publicly available, graph-based HLA allele calling service. Methods Gene feature enumeration (GFE) notation has been developed as a way of describing sequence variation outside of current HLA nomenclature. We generated GFE notation for every sequence in the IPD-IMGT/HLA Database, and loaded the results into a neo4j graph database ( neo4j.b12x.org ), which includes HLA, GFE and sequence feature nodes. We developed an allele calling tool (ACT) that leverages this graph to return an HLA allele call and GFE notation from submitted consensus sequence. ACT uses the GFE service ( gfe.b12x.org ) to convert the consensus sequences to GFE notation, and then searches the graph database for HLA alleles that share the most features with the generated GFE. A RESTful service interface makes ACT easy to use and allows for cross-platform compatibility ( act.b12x.org ). We used 30,000 Be the Match® donors typed at high resolution and with consensus sequences available for HLA-A, B, and C to test ACT. We compared the HLA calls ACT produced to the allele names reported by the typing labs. Comparisons were made with and without mapping alleles to their G group equivalent. Results When mapping alleles to their respective G group equivalent, the reported HLA typing for all 30,000 donors matched the ACT typing to the 2nd field with no ambiguity. Without mapping alleles to their G groups, the number of exact matches to the 4th field at HLA-A, B and C was 17,142 (57%), 16,540 (55%) and 10,024 (33%), respectively. Using G groups, ambiguity at the 4th field was reduced substantially; the number of exact matches increased to 29,914 (99.7%), 29,733 (99.1%) and 29,985 (99.9%) for HLA-A, B, and C, respectively. In 75 instances, ACT called alleles at a higher resolution than reported by the typing lab. Conclusions HLA class I allele names can be accurately called from consensus sequences using our GFE-based ACT. This service will allow anyone to easily convert HLA class I consensus sequences into the corresponding GFE notation and HLA allele name. Class II HLA and KIR are already represented in the graph, and we plan to extend ACT functions to these loci. [ABSTRACT FROM AUTHOR]

The human leukocyte antigen (HLA) is the most polymorphic region in humans. Anthropologists use HLA to trace populations' migration and evolution. However, recent admixture between populations can mask the ancestral haplotype frequency distribution. We present a statistical method based on high-resolution HLA haplotype frequencies to resolve population admixture using a non-negative matrix factorization formalism and validated using haplotype frequencies from 56 world populations. The result is a minimal set of source components (SCs) decoding roughly 90% of the total variance in the studied admixtures. These SCs agree with the geographical distribution, phylogenies, and recent admixture events of the studied groups. With the growing population of multi-ethnic individuals, or individuals that do not report race/ethnic information, the HLA matching process for stem-cell and solid organ transplants is becoming more challenging. The presented algorithm provides a framework that facilitates the breakdown of highly admixed populations into SCs, which can be used to better match the rapidly growing population of multi-ethnic individuals worldwide. [ABSTRACT FROM AUTHOR]

Non-permissive HLA-DPB1 mismatches in hematopoietic stem cell transplantations (HSCT) have been defined in terms of T-Cell epitope (TCE) reactivity groups (Zino et al.) and DPB1 expression variants (Petersdorf et al). The non-permissive HLA-DPB1 mismatches identified in both models are associated with a statistically significant increase in the risk of graft versus host disease in HSCT. We aimed to measure the ability to predict TCE and expression permissibility for all major race groups by imputing donor DPB1 genotypes using high-resolution A∼C∼B∼DRB1∼DQB1∼DPB1 haplotype frequencies. We used 512,201 donors typed at high resolution (HR) at A∼C∼B∼DRB1∼DQB1∼DPB1 for evaluating the imputation of DPB1 permissibility. We analyzed 18 populations that had at least 4000 donors typed at HR for all six loci. The most HR donors were observed in the European population (301,401) and the least HR in the Vietnamese population (4326). We used the algorithm outlined in Zino et al. for determining the DPB1 TCE permissibility and Petersdorf et al. for determining the DPB1 expression risk. From each population we randomly selected 2500 HR subjects and then simulated 6250,000 donor-recipient pairs. We removed the donor’s DPB1 genotype for each pair and imputed it back using A∼C∼B∼DRB1∼DQB1∼DPB1 haplotype frequencies. The randomly selected HR subjects were removed from the calculation of the haplotype frequencies. Based on the DPB1 allele likelihoods, we calculated probabilities for each pair being TCE permissive or non-permissive and DPB1 expression permissive or non-permissive. We compared the predicted TCE and expression permissibility for each pair to their true TCE and expression permissibility using the receiver operator characteristic (ROC). The ROC area under the curve (AUC) was greater than 0.90 for every population except Vietnamese (0.87). The three highest AUC were observed in the Filipino (0.96), Middle Eastern (0.95) and the Caribbean (0.95) populations. The average AUC observed was 0.92 with a standard deviation of 0.02 between populations. Imputation of DPB1 permissibility can be performed with strong predictive power for every major population when using A∼C∼B∼DRB1∼DQB1∼DPB1 haplotype frequencies. Donor search results for HSCT could be enhanced with the addition of DPB1 permissibility predictions. [ABSTRACT FROM AUTHOR]

Aim: Recent data show that DP matching plays an important role in hematopoietic cell transplantation. Our previous work demonstrated that in European Americans haplotypic associations for the DP heterodimer are determined by near complete linkage disequilibrium between amino acid motifs on DPA1 (pos 31) and DPB1 (pos 85–87). We aimed to generate motif and allele-level haplotype frequencies (HF) for four race groups to extend these insights to minorities. Methods: We calculated DPA1∼DPB1 HF at allele and motif level from 16,802 Be the Match Registry® members typed by DNA methods, resolving phase, allelic and motif ambiguity using expectation maximization. Motif frequencies were calculated for position 31 on DPA1 and positions 85–87 on DPB1, which play a critical role in the P1 pocket of the peptide binding region. Normalized linkage disequilibrium (LD) was calculated on each haplotype (D′) and globally (Wn) for each population. Results: The top three allele-level haplotypes in all populations account for over 66% of the HF, with DPA1∗01:03 DPB1∗04:01 most common in the Caucasian (CAU), Asian Pacific Islander (API) and Hispanic (HIS) populations and DPA1∗02:02 DPB1∗01:01 in the African American (AFA) population. Wn for DPA1∼DPB1 allele associations for CAU, HIS, API, and AFA populations was .55, .45, .49, and .52 respectively. At the motif level there were only four possible haplotypes. M GPM and Q EAV were the two most common in every population. M GPM was the most common in CAU, HIS and API with frequencies 69%, 68% and 56% respectively, with D′= 0.97 for CAU (complete LD). The most common haplotype for AFA was Q EAV, at 48% and D′=.99. Conclusions: Low global LD was observed at the allele level for all populations. However, at the motif level haplotypes were in near complete LD suggesting that for the DPA1 DPB1 heterodimer the unit of selection for all populations is the combined amino acid motif rather than the allele, as previously observed in European Americans. [ABSTRACT FROM AUTHOR]

Aim: The Arab Bone Marrow Registry in Hadassah Medical Center collected HLA typings for 18,000 Arab adult donors. We used this information to estimate population allele and haplotype frequencies (HFs). Methods: We calculated HLA A∼B∼DRB1 HFs from 1,541 Christian Arab (CA) and 16,129 Muslim Arab (MA) donors typed by SBT, resolving phase and allelic ambiguity using Expectation Maximization. HFs were estimated at the four-digit level. Results: The most common CA haplotype was A∗33:01∼B∗14:02∼DRB1∗01:02 at a frequency of 1.6%, which is the fifth most common MA haplotype at 0.9%. This haplotype was the second ranked in the US Middle Eastern/North Coast of Africa (MENAFC) at 0.8% and is also a common Jewish haplotype. The most common MA haplotype was A∗01:01∼B∗52:01∼DRB1∗15:02 at 1.4%, which is ranked 41st in CA at 0.04%. This haplotype was ranked 12th in MENAFC at 0.26%. The fourth ranked haplotype for both CA and MA, A∗02:05∼B∗50:01∼DRB1∗07:01, is the most common in Saudi Arabia, Kuwait and Qatar and the fourth most common among Jewish populations. Average homozygosity for CA and MA for HLA-A, -B and -DRB1 was estimated at 6.7% and 6.2% while the top 30 haplotypes had a cumulative frequency of 25% and 19% respectively indicating higher MA genetic diversity. Interestingly, eight DRB1 alleles: 01:02, 03:01, 04:03, 07:01, 11:01, 11:04, 13:03 and 15:02 constituted over 63% of the allele frequencies for both CA and MA while 97% and 30% of patients served by the Arab registry had one or two of these alleles respectively. Additionally, DRB1∗03:01 occurred without the common Caucasian B∗08:01 association in about 85% of CA and MA donors. Clinical data showed that 40% of transplants were for Arab patients while others were for patients worldwide. Conclusions: Comparing CA and MA to other published HFs, it is clear that some haplotypes have migrated across populations while others remain isolated, thus adding these donors to the world registry is vital to increase genetic diversity for the benefits of all patients. [Copyright &y& Elsevier]