HLA alleles and haplotypes observed in 263 US families

A Tool for the Assessment of HLA-DQ Heterodimer Variation in Hematopoietic Cell Transplantation

When optimizing transplants, clinical decision-makers consider HLA-A, -B, -C, -DRB1 (8 matched alleles out of 8), and sometimes HLA-DQB1 (10 out of 10) matching between the patient and donor. HLA-DQ is a heterodimer formed by the β chain product of HLA-DQB1 and an α chain product of HLA-DQA1. In addition to molecules defined by the parentally inherited cis haplotypes, α-β trans-dimerization is possible between certain alleles, leading to unique molecules and a potential source of mismatched molecules. Recently, researchers uncovered that clinical outcome after HLA-DQB1-mismatched unrelated donor HCT depends on the total number of HLA-DQ molecule mismatches and the specific α-β heterodimer mismatch. Our objective in this study is to develop an automated tool for analyzing HLA-DQ heterodimer data and validating it through numerous datasets and analyses. By doing so, we provide an HLA-DQ heterodimer tool for DQα-DQβ trans-heterodimer evaluation, HLA-DQ imputation, and HLA-DQ-featured source selection to the transplant field. In our study, we leverage 352,148 high-confidence, statistically phased (via a modified expectation-maximization algorithm) HLA-DRB1∼DQA1∼DQB1 haplotypes, 1,052 pedigree-phased HLA-DQA1∼DQB1 haplotypes, and 13,663 historical transplants to characterize HLA-DQ heterodimers data. Using our developed QLASSy (HLA-DQA1 and HLA-DQB1 Heterodimers Assessment) tool, we first assessed the data quality of HLA-DQ heterodimers in our data for trans-dimers, missing HLA-DQA1 typing, and unexpected HLA-DQA1 and HLA-DQB1 combinations. Since trans-dimers enable up to four unique HLA-DQ molecules in individuals, we provide in-silico validations for 99.7% of 275 unique trans-dimers generated by 176,074 U.S. donors with HLA-DQA1 and HLA-DQB1 data. Many individuals lack HLA-DQA1 typing, so we developed and validated high-confidence HLA-DQ annotation imputation via HLA-DRB1 with >99% correct predictions in 23,698 individuals. A select few individuals displayed unexpected HLA-DQ combinations. We revisited the typing of 61 donors with unexpected HLA-DQ combinations based on their HLA-DQA1 and HLA-DQB1 typing and corrected 22 out of 61 (36%) cases of donors through data review or retyping and used imputation to resolve unexpected combinations. After verifying the data quality of our datasets, we analyzed our datasets further: we explored the frequencies of observed HLA-DQ combinations to compare HLA-DQ across populations (for instance, we found more high-risk molecules in Asian/Pacific Islander and Black/African American populations), demonstrated the effect of HLA-DQA1 and HLA-DQB1 mismatching on HLA-DQ molecular mismatches, and highlighted where donor selections could be improved at the time of search for historical transplants with this new HLA-DQ information (where 51.9% of G2-mismatched transplants had lower-risk, G2-matched alternatives). We encapsulated our findings into a tool that imputes missing HLA-DQA1 as needed, annotates HLA-DQ (mis)matches, and highlights other important HLA-DQ data to consider for the present and future. Altogether, these valuable datasets, analyses, and a culminating tool serve as actionable resources to enhance donor selection and improve patient outcomes.

A new strategy for systematically classifying HLA alleles into serological specificities: Update and refinement

HLA antigens were historically defined according to the unique reactivity pattern of cells expressing HLA molecules with distinctive clusters of allo-antisera and/or monoclonal antibodies. Subsequently, amino acid residues determining epitopes (DEP) in the HLA molecule were correlated with reactivity patterns. In current clinical practice, the presence of allo-antibodies is assessed using Luminex-based solid phase single antigen bead (SAB) assays for transplantation. Recently, novel antigens were proposed for HLA molecules with DEP patterns that do not match any serologically defined antigens recognised by the WHO Nomenclature Committee. To validate the antigens, mean fluorescence intensity values of SABs tested on >13,000 patients' sera were extracted from clinical databases and analysed by scatter plots using a linear regression model. We found that when two proteins were considered as the same antigen in the original study, for example, HLA-A*02:01 and -A*02:06, their correlation ranked among the highest values at each locus. In contrast, discrete asymmetric outliers were observed when there were different antigens, for example, HLA-A*30:01 and -A*30:02, allowing validation and confirmation of 20 novel antigens for HLA-A, -B, -C and -DR. The outliers were confirmed to be true or false by flow cytometric crossmatches. In addition to the previously defined residues for antigen assignments, findings suggest that further distinction should be made for common antigens by including the substitutions at residue 67 of HLA-B, 67 and 74 of -DR. These serologic analyses can be applied systematically to identify and confirm novel antigens. These developments will lead to designing optimal SAB panels and further improving virtual donor-specific antibodies assessment.

HLA-DR3 ~ DQ2 associates with sensory neuropathy in paraneoplastic neurological syndromes with Hu antibodies

OBJECTIVES

To investigate the association between human leukocyte antigen (HLA) and paraneoplastic neurological syndromes (PNS) with Hu antibodies, and potential specificities according to clinical presentation and cancer status.

METHODS

HLA genotypes at four-digit resolution were imputed from available genome-wide association data. Allele carrier frequencies were compared between patients (whole cohort, n = 100, and according to clinical presentation and cancer status) and matched healthy controls (n = 508) using logistic regression controlled by the three main principal components.

RESULTS

The clinical presentation of 100 anti-Hu patients involved the central nervous system (28, 28%), the peripheral nervous system (36, 36%) or both combined (36, 36%). Cancer diagnosis was certain in 75 (75%). HLA association analyses revealed that anti-Hu PNS patients were more frequently carriers of DQA1*05:01 (39% vs. 19%, OR = 2.8 [1.74-4.49]), DQB1*02:01 (39% vs. 18%, OR = 2.88 [1.79-4.64]) and DRB1*03:01 (41% vs. 19%, OR = 2.92 [1.80-4.73]) than healthy controls. Remarkably, such DR3 ~ DQ2 association was absent in patients with pure central involvement, but more specific to those manifesting with peripheral involvement: DQA1*05:01 (OR = 3.12 [1.48-6.60]), DQB1*02:01 (OR = 3.35 [1.57-7.15]) and DRB1*03:01 (OR = 3.62 [1.64-7.97]); being even stronger in cases with sensory neuropathy, DQA1*05:01 (OR = 4.41 [1.89-10.33]), DQB1*02:01 (OR = 4.85 [2.04-11.53]) and DRB1*03:01 (OR = 5.79 [2.28-14.74]). Similarly, DR3 ~ DQ2 association was only observed in patients with cancer.

DISCUSSION

Patients with anti-Hu PNS show different HLA profiles according to clinical presentation and, probably, cancer status, suggesting pathophysiological differences.

HLA-DQB1*05 subtypes and not DRB1*10:01 mediates risk in anti-IgLON5 disease

Anti-IgLON5 disease is a rare and likely underdiagnosed subtype of autoimmune encephalitis. The disease displays a heterogeneous phenotype that includes sleep, movement and bulbar-associated dysfunction. The presence of IgLON5-antibodies in CSF/serum, together with a strong association with HLA-DRB1*10:01∼DQB1*05:01, supports an autoimmune basis. In this study, a multicentric human leukocyte antigen (HLA) study of 87 anti-IgLON5 patients revealed a stronger association with HLA-DQ than HLA-DR. Specifically, we identified a predisposing rank-wise association with HLA-DQA1*01:05∼DQB1*05:01, HLA-DQA1*01:01∼DQB1*05:01 and HLA-DQA1*01:04∼DQB1*05:03 in 85% of patients. HLA sequences and binding cores for these three DQ heterodimers were similar, unlike those of linked DRB1 alleles, supporting a causal link to HLA-DQ. This association was further reflected in an increasingly later age of onset across each genotype group, with a delay of up to 11 years, while HLA-DQ-dosage dependent effects were also suggested by reduced risk in the presence of non-predisposing DQ1 alleles. The functional relevance of the observed HLA-DQ molecules was studied with competition binding assays. These proof-of-concept experiments revealed preferential binding of IgLON5 in a post-translationally modified, but not native, state to all three risk-associated HLA-DQ receptors. Further, a deamidated peptide from the Ig2-domain of IgLON5 activated T cells in two patients, compared with one control carrying HLA-DQA1*01:05∼DQB1*05:01. Taken together, these data support a HLA-DQ-mediated T-cell response to IgLON5 as a potentially key step in the initiation of autoimmunity in this disease.

Haplotype reconstruction for genetically complex regions with ambiguous genotype calls: Illustration by the KIR gene region

Advances in DNA sequencing technologies have enabled genotyping of complex genetic regions exhibiting copy number variation and high allelic diversity, yet it is impossible to derive exact genotypes in all cases, often resulting in ambiguous genotype calls, that is, partially missing data. An example of such a gene region is the killer-cell immunoglobulin-like receptor (KIR) genes. These genes are of special interest in the context of allogeneic hematopoietic stem cell transplantation. For such complex gene regions, current haplotype reconstruction methods are not feasible as they cannot cope with the complexity of the data. We present an expectation-maximization (EM)-algorithm to estimate haplotype frequencies (HTFs) which deals with the missing data components, and takes into account linkage disequilibrium (LD) between genes. To cope with the exponential increase in the number of haplotypes as genes are added, we add three components to a standard EM-algorithm implementation. First, reconstruction is performed iteratively, adding one gene at a time. Second, after each step, haplotypes with frequencies below a threshold are collapsed in a rare haplotype group. Third, the HTF of the rare haplotype group is profiled in subsequent iterations to improve estimates. A simulation study evaluates the effect of combining information of multiple genes on the estimates of these frequencies. We show that estimated HTFs are approximately unbiased. Our simulation study shows that the EM-algorithm is able to combine information from multiple genes when LD is high, whereas increased ambiguity levels increase bias. Linear regression models based on this EM, show that a large number of haplotypes can be problematic for unbiased effect size estimation and that models need to be sparse. In a real data analysis of KIR genotypes, we compare HTFs to those obtained in an independent study. Our new EM-algorithm-based method is the first to account for the full genetic architecture of complex gene regions, such as the KIR gene region. This algorithm can handle the numerous observed ambiguities, and allows for the collapsing of haplotypes to perform implicit dimension reduction. Combining information from multiple genes improves haplotype reconstruction.

Analysis of the Origin of Emiratis as Inferred from a Family Study Based on HLA-A, -C, -B, -DRB1, and -DQB1 Genes

In this study, we investigated HLA class I and class II allele and haplotype frequencies in Emiratis and compared them to those of Asian, Mediterranean, and Sub-Saharan African populations.

METHODS

Two-hundred unrelated Emirati parents of patients selected for bone marrow transplantation were genotyped for HLA class I (A, B, C) and class II (DRB1, DQB1) genes using reverse sequence specific oligonucleotide bead-based multiplexing. HLA haplotypes were assigned with certainty by segregation (pedigree) analysis, and haplotype frequencies were obtained by direct counting. HLA class I and class II frequencies in Emiratis were compared to data from other populations using standard genetic distances (SGD), Neighbor-Joining (NJ) phylogenetic dendrograms, and correspondence analysis.

RESULTS

The studied HLA loci were in Hardy-Weinberg Equilibrium. We identified 17 HLA-A, 28 HLA-B, 14 HLA-C, 13 HLA-DRB1, and 5 HLA-DQB1 alleles, of which HLA-A*02 (22.2%), -B*51 (19.5%), -C*07 (20.0%), -DRB1*03 (22.2%), and -DQB1*02 (32.8%) were the most frequent allele lineages. DRB1*03~DQB1*02 (21.2%), DRB1*16~DQB1*05 (17.3%), B*35~C*04 (11.7%), B*08~DRB1*03 (9.7%), A*02~B*51 (7.5%), and A*26~C*07~B*08~DRB1*03~DQB1*02 (4.2%) were the most frequent two- and five-locus HLA haplotypes. Correspondence analysis and dendrograms showed that Emiratis were clustered with the Arabian Peninsula populations (Saudis, Omanis and Kuwaitis), West Mediterranean populations (North Africans, Iberians) and Pakistanis, but were distant from East Mediterranean (Turks, Albanians, Greek), Levantine (Syrians, Palestinians, Lebanese), Iranian, Iraqi Kurdish, and Sub-Saharan populations.

CONCLUSIONS

Emiratis were closely related to Arabian Peninsula populations, West Mediterranean populations and Pakistanis. However, the contribution of East Mediterranean, Levantine Arab, Iranian, and Sub-Saharan populations to the Emiratis' gene pool appears to be minor.

Genetic Modifiers of Cystic Fibrosis Lung Disease Severity: Whole-Genome Analysis of 7,840 Patients

Rationale: Lung disease is the major cause of morbidity and mortality in persons with cystic fibrosis (pwCF). Variability in CF lung disease has substantial non-CFTR (CF transmembrane conductance regulator) genetic influence. Identification of genetic modifiers has prognostic and therapeutic importance. Objectives: Identify genetic modifier loci and genes/pathways associated with pulmonary disease severity. Methods: Whole-genome sequencing data on 4,248 unique pwCF with pancreatic insufficiency and lung function measures were combined with imputed genotypes from an additional 3,592 patients with pancreatic insufficiency from the United States, Canada, and France. This report describes association of approximately 15.9 million SNPs using the quantitative Kulich normal residual mortality-adjusted (KNoRMA) lung disease phenotype in 7,840 pwCF using premodulator lung function data. Measurements and Main Results: Testing included common and rare SNPs, transcriptome-wide association, gene-level, and pathway analyses. Pathway analyses identified novel associations with genes that have key roles in organ development, and we hypothesize that these genes may relate to dysanapsis and/or variability in lung repair. Results confirmed and extended previous genome-wide association study findings. These whole-genome sequencing data provide finely mapped genetic information to support mechanistic studies. No novel primary associations with common single variants or rare variants were found. Multilocus effects at chr5p13 (SLC9A3/CEP72) and chr11p13 (EHF/APIP) were identified. Variant effect size estimates at associated loci were consistently ordered across the cohorts, indicating possible age or birth cohort effects. Conclusions: This premodulator genomic, transcriptomic, and pathway association study of 7,840 pwCF will facilitate mechanistic and postmodulator genetic studies and the development of novel therapeutics for CF lung disease.

Establishment of NGS-based HLA 9-locus haplotypes in the Eastern Han Chinese population highlights the role of HLA-DP in donor selection for transplantation

We collected human leukocyte antigen (HLA) typing data from 653 families in the Eastern Han Chinese population. HLA-A, B, C, DRB1, DRB3, DRB4, DRB5, DQA1, DQB1, DPA1, and DPB1 (HLA-11 loci) typing of 1,781 subjects was performed using a commercial next-generation sequencing (NGS) method in our laboratory. The phasing of haplotypes in each family was determined by Mendelian segregation. Haplotype analysis revealed 1,634 different haplotypes among a total of 2,230 haplotypes. The predominant haplotype was A*30:01-C*06:02-B*13:02-DRB1*07:01-DRB4*01:03-DQA1*02:01-DQB1*02:02-DPA1*02:01-DPB1*17:01 (HF = 4.04%), followed by A*02:07-C*01:02-B*46:01-DRB1*09:01-DRB4*01:03-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*05:01 (HF = 1.84%) and A*33:03-C*03:02-B*58:01-DRB1*03:01-DRB3*02:02-DQA1*05:01-DQB1*02:01-DPA1*01:03-DPB1*04:01 (HF = 1.48%), accounting for 7.35% of the total. Meanwhile 76.41% of all haplotypes were observed only once or twice (HF < 0.1%). Different from HLA-DRB3/4/5 and DQA1 loci, DP linkage markedly increased haplotype variation by 34.82% based on the 5-locus haplotype. The much weaker linkage disequilibrium (LD) of DQB1-DPB1 indicated the reason. We observed 10 analyzable recombination events, most of which occurred at DP loci. Even with the same common 5-locus haplotype, HLA-DP linkage alters the haplotype diversity and frequency. Analysis of related haplotype assignment and unrelated recipient-donor pairs matching at the 9-locus haplotype revealed that HLA-DP affects the donor selection strategy. Haplotype study of a large sample size using NGS identified linkage haplotypes beyond the 5 loci. LD, recombination events, and haplotype variation caused by DP loci emphasized that HLA 9-locus haplotype matching should be considered in donor selection, particularly the effect of DP loci. The finding lays the foundation for further studies on the effect of HLA-DP mismatch on transplantation. This article is protected by copyright. All rights reserved.

Challenges for the standardized reporting of NGS HLA genotyping: Surveying gaps between clinical and research laboratories

Next generation sequencing (NGS) is being applied for HLA typing in research and clinical settings. NGS HLA typing has made it feasible to sequence exons, introns and untranslated regions simultaneously, with significantly reduced labor and reagent cost per sample, rapid turnaround time, and improved HLA genotype accuracy. NGS technologies bring challenges for cost-effective computation, data processing and exchange of NGS-based HLA data. To address these challenges, guidelines and specifications such as Genotype List (GL) String, Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING), and Histoimmunogenetics Markup Language (HML) were proposed to streamline and standardize reporting of HLA genotypes. As part of the 17th International HLA and Immunogenetics Workshop (IHIW), we implemented standards and systems for HLA genotype reporting that included GL String, MIRING and HML, and found that misunderstanding or misinterpretations of these standards led to inconsistencies in the reporting of NGS HLA genotyping results. This may be due in part to a historical lack of centralized data reporting standards in the histocompatibility and immunogenetics community. We have worked with software and database developers, clinicians and scientists to address these issues in a collaborative fashion as part of the Data Standard Hackathons (DaSH) for NGS. Here we report several categories of challenges to the consistent exchange of NGS HLA genotyping data we have observed. We hope to address these challenges in future DaSH for NGS efforts.

Relevance of Polymorphic KIR and HLA Class I Genes in NK-Cell-Based Immunotherapies for Adult Leukemic Patients

Simple Summary

Immunotherapies are promising approaches to curing different acute leukemias. Natural killer (NK) cells are lymphocytes that are efficient in the elimination of leukemic cells. NK-cell-based immunotherapies are particularly attractive, but the landscape of the heterogeneity of NK cells must be deciphered. This review provides an overview of the polymorphic KIR and HLA class I genes that modulate the NK cell repertoire and how these markers can improve the outcomes of patients with acute leukemia. A better knowledge of these genetic markers that are linked to NK cell subsets that are efficient against hematological diseases will optimize hematopoietic stem-cell donor selection and NK immunotherapy design.

Abstract

Since the mid-1990s, the biology and functions of natural killer (NK) cells have been deeply investigated in healthy individuals and in people with diseases. These effector cells play a particularly crucial role after allogeneic hematopoietic stem-cell transplantation (HSCT) through their graft-versus-leukemia (GvL) effect, which is mainly mediated through polymorphic killer-cell immunoglobulin-like receptors (KIRs) and their cognates, HLA class I ligands. In this review, we present how KIRs and HLA class I ligands modulate the structural formation and the functional education of NK cells. In particular, we decipher the current knowledge about the extent of KIR and HLA class I gene polymorphisms, as well as their expression, interaction, and functional impact on the KIR⁺ NK cell repertoire in a physiological context and in a leukemic context. In addition, we present the impact of NK cell alloreactivity on the outcomes of HSCT in adult patients with acute leukemia, as well as a description of genetic models of KIRs and NK cell reconstitution, with a focus on emergent T-cell-repleted haplo-identical HSCT using cyclosphosphamide post-grafting (haplo-PTCy). Then, we document how the immunogenetics of KIR/HLA and the immunobiology of NK cells could improve the relapse incidence after haplo-PTCy. Ultimately, we review the emerging NK-cell-based immunotherapies for leukemic patients in addition to HSCT.

Predicting future from past: The genomic basis of recurrent and rapid stickleback evolution

Similar forms often evolve repeatedly in nature, raising long-standing questions about the underlying mechanisms. Here, we use repeated evolution in stickleback to identify a large set of genomic loci that change recurrently during colonization of freshwater habitats by marine fish. The same loci used repeatedly in extant populations also show rapid allele frequency changes when new freshwater populations are experimentally established from marine ancestors. Marked genotypic and phenotypic changes arise within 5 years, facilitated by standing genetic variation and linkage between adaptive regions. Both the speed and location of changes can be predicted using empirical observations of recurrence in natural populations or fundamental genomic features like allelic age, recombination rates, density of divergent loci, and overlap with mapped traits. A composite model trained on these stickleback features can also predict the location of key evolutionary loci in Darwin's finches, suggesting that similar features are important for evolution across diverse taxa.

High Resolution Haplotype Analyses of Classical HLA Genes in Families With Multiple Sclerosis Highlights the Role of HLA-DP Alleles in Disease Susceptibility

Multiple sclerosis (MS) susceptibility shows strong genetic associations with HLA alleles and haplotypes. We genotyped 11 HLA genes in 477 non-Hispanic European MS patients and their 954 unaffected parents using a validated next-generation sequencing (NGS) methodology. HLA haplotypes were assigned unequivocally by tracing HLA allele transmissions. We explored HLA haplotype/allele associations with MS using the genotypic transmission disequilibrium test (gTDT) and multiallelic TDT (mTDT). We also conducted a case-control (CC) study with all patients and 2029 healthy unrelated ethnically matched controls. We performed separate analyses of 54 extended multi-case families by reviewing transmission of haplotype blocks. The haplotype fragment including DRB5*01:01:01~DRB1*15:01:01:01 was significantly associated with predisposition (gTDT: p < 2.20e-16; mTDT: p =1.61e-07; CC: p < 2.22e-16) as reported previously. A second risk allele, DPB1*104:01 (gTDT: p = 3.69e-03; mTDT: p = 2.99e-03; CC: p = 1.00e-02), independent from the haplotype bearing DRB1*15:01 was newly identified. The allele DRB1*01:01:01 showed significant protection (gTDT: p = 8.68e-06; mTDT: p = 4.50e-03; CC: p = 1.96e-06). Two DQB1 alleles, DQB1*03:01 (gTDT: p = 2.86e-03; mTDT: p = 5.56e-02; CC: p = 4.08e-05) and DQB1*03:03 (gTDT: p = 1.17e-02; mTDT: p = 1.16e-02; CC: p = 1.21e-02), defined at two-field level also showed protective effects. The HLA class I block, A*02:01:01:01~C*03:04:01:01~B*40:01:02 (gTDT: p = 5.86e-03; mTDT: p = 3.65e-02; CC: p = 9.69e-03) and the alleles B*27:05 (gTDT: p = 6.28e-04; mTDT: p = 2.15e-03; CC: p = 1.47e-02) and B*38:01 (gTDT: p = 3.20e-03; mTDT: p = 6.14e-03; CC: p = 1.70e-02) showed moderately protective effects independently from each other and from the class II associated factors. By comparing statistical significance of 11 HLA loci and 19 haplotype segments with both untruncated and two-field allele names, we precisely mapped MS candidate alleles/haplotypes while eliminating false signals resulting from 'hitchhiking' alleles. We assessed genetic burden for the HLA allele/haplotype identified in this study. This family-based study including the highest-resolution of HLA alleles proved to be powerful and efficient for precise identification of HLA genotypes associated with both, susceptibility and protection to development of MS.

Standard reference sequences for submission of HLA genotyping for the 18th International HLA and Immunogenetics Workshop

The International human leukocyte antigen (HLA) and Immunogenetics Workshops (IHIWs) have fostered international collaborations of researchers and experts in the fields of HLA, histocompatibility and immunology. These IHIW collaborations have comprised many projects focused on achieving a variety of specific goals. The international and collaborative nature of these projects necessitates the collection and analysis of complex data generated in multiple laboratories, often using multiple methods of acquisition. Collection and storage of these data in a consistent way adds value to IHIW projects, which can be extended to future work. DNA‐based genotyping data, especially HLA genotyping data, can be transmitted in the form of a Histoimmunogenetics Markup Language (HML) document. HML facilitates clear communication of a genotype and supporting metadata, such as, sequencing platform, laboratory assays, consensus sequence, and interpretation. Sequence information can be reported relative to known reference sequences, which add meaning and context to genotypes. Selecting the correct reference sequence for a given allele sequence is nuanced, and guidelines have emerged through collaborative community efforts such as Data Standards Hackathons. Here, we describe the guidelines established for the selection of reference sequences to be used in transmission of HLA (and MICA/MICB) genotyping data for the 18th IHIW.

HLA diversity in the Argentinian Umbilical Cord Blood Bank: frequencies according to donor's reported ancestry and geographical distribution

Umbilical cord blood (UCB) is a suitable source for hematopoietic stem cell transplantation. The study of HLA genes by next generation sequencing is commonly used in transplants. Donor/patient HLA matching is often higher within groups of common ancestry, however "Hispanic" is a broad category that fails to represent Argentina's complex genetic admixture. Our aim is to describe HLA diversity of banked UCB units collected across the country taking into consideration donor's reported ancestral origins as well as geographic distribution. Our results showed an evenly distribution of units mainly for 2 groups: of European and of Native American descent, each associated to a defined geographic location pattern (Central vs. North regions). We observed differences in allele frequency distributions for some alleles previously described in Amerindian populations: for Class I (A*68:17, A*02:11:01G, A*02:22:01G, B*39:05:01, B*35:21, B*40:04, B*15:04:01G, B*35:04:01, B*51:13:01) and Class II (DRB1*04:11:01, DRB1*04:07:01G/03, DRB1*08:02:01, DRB1*08:07, DRB1*09:01:02G, DRB1*14:02:01, DRB1*16:02:01G). Our database expands the current knowledge of HLA diversity in Argentinian population. Although further studies are necessary to fully comprehend HLA heterogeneity, this report should prove useful to increase the possibility of finding compatible donors for successful allogeneic transplant and to improve recruitment strategies for UCB donors across the country.

Variations in MHC class I antigen presentation and immunopeptidome selection pathways

Major histocompatibility class I (MHC-I) proteins mediate immunosurveillance against pathogens and cancers by presenting antigenic or mutated peptides to antigen receptors of CD8+ T cells and by engaging receptors of natural killer (NK) cells. In humans, MHC-I molecules are highly polymorphic. MHC-I variations permit the display of thousands of distinct peptides at the cell surface. Recent mass spectrometric studies have revealed unique and shared characteristics of the peptidomes of individual MHC-I variants. The cell surface expression of MHC-I–peptide complexes requires the functions of many intracellular assembly factors, including the transporter associated with antigen presentation (TAP), tapasin, calreticulin, ERp57, TAP-binding protein related (TAPBPR), endoplasmic reticulum aminopeptidases (ERAPs), and the proteasomes. Recent studies provide important insights into the structural features of these factors that govern MHC-I assembly as well as the mechanisms underlying peptide exchange. Conformational sensing of MHC-I molecules mediates the quality control of intracellular MHC-I assembly and contributes to immune recognition by CD8 at the cell surface. Recent studies also show that several MHC-I variants can follow unconventional assembly routes to the cell surface, conferring selective immune advantages that can be exploited for immunotherapy.

OGRDB: a reference database of inferred immune receptor genes

High-throughput sequencing of the adaptive immune receptor repertoire (AIRR-seq) is providing unprecedented insights into the immune response to disease and into the development of immune disorders. The accurate interpretation of AIRR-seq data depends on the existence of comprehensive germline gene reference sets. Current sets are known to be incomplete and unrepresentative of the degree of polymorphism and diversity in human and animal populations. A key issue is the complexity of the genomic regions in which they lie, which, because of the presence of multiple repeats, insertions and deletions, have not proved tractable with short-read whole genome sequencing. Recently, tools and methods for inferring such gene sequences from AIRR-seq datasets have become available, and a community approach has been developed for the expert review and publication of such inferences. Here, we present OGRDB, the Open Germline Receptor Database (https://ogrdb.airr-community.org), a public resource for the submission, review and publication of previously unknown receptor germline sequences together with supporting evidence.