Six-locus high resolution HLA haplotype frequencies derived from mixed-resolution DNA typing for the entire US donor registry

HLA reduction of human T cells facilitates generation of immunologically multicompatible cellular products

ABSTRACT

Adoptive cellular therapies have shown enormous potential but are complicated by personalization. Because of HLA mismatch, rejection of transferred T cells frequently occurs, compromising the T-cell graft's functionality. This obstacle has led to the development of HLA knock-out (KO) T cells as universal donor cells. Whether such editing directly affects T-cell functionality remains poorly understood. In addition, HLA KO T cells are susceptible to missing self-recognition through natural killer (NK) cells and lack of canonical HLA class I expression may represent a safety hazard. Engineering of noncanonical HLA molecules could counteract NK-cell recognition, but further complicates the generation of cell products. Here, we show that HLA KO does not alter T-cell functionality in vitro and in vivo. Although HLA KO abrogates allogeneic T-cell responses, it elicits NK-cell recognition. To circumvent this problem, we demonstrate that selective editing of individual HLA class I molecules in primary human T cells is possible. Such HLA reduction not only inhibits T-cell alloreactivity and NK-cell recognition simultaneously, but also preserves the T-cell graft's canonical HLA class I expression. In the presence of allogeneic T cells and NK cells, T cells with remaining expression of a single, matched HLA class I allele show improved functionality in vivo in comparison with conventional allogeneic T cells. Since reduction to only a few, most frequent HLA haplotypes would already be compatible with large shares of patient populations, this approach significantly extends the toolbox to generate broadly applicable cellular products.

HLA Genotype Imputation Results in Largely Accurate Epitope Mismatch Risk Categorization Across Racial Groups

Background

Biomarkers that predict posttransplant alloimmunity could lead to improved long-term graft survival. Evaluation of the number of mismatched epitopes between donor and recipient HLA proteins, termed molecular mismatch analysis, has emerged as an approach to classify transplant recipients as having high, intermediate, or low risk of graft rejection. When high-resolution genotypes are unavailable, molecular mismatch analysis requires algorithmic assignment, or imputation, of a high-resolution genotyping. Although imputation introduces inaccuracies in molecular mismatch analyses, it is unclear whether these inaccuracies would impact the clinical risk assessment for graft rejection.

Methods

Using renal transplant patients and donors from our center, we constructed cohorts of surrogate donor-recipient pairs with high-resolution and low-resolution HLA genotyping that were racially concordant or discordant. We systemically assessed the impact of imputation on molecular mismatch analysis for cohorts of 180-200 donor-recipient pairs for each of 4 major racial groups. We also evaluated the effect of imputation for a racially diverse validation cohort of 35 real-world renal transplant pairs.

Results

In the surrogate donor-recipient cohorts, imputation preserved the molecular mismatch risk category for 90.5%-99.6% of racially concordant donor-recipient pairs and 92.5%-100% of racially discordant pairs. In the validation cohort, which comprised 72% racially discordant pairs, we found that imputation preserved the molecular mismatch risk category for 97.1% of pairs.

Conclusions

Overall, these data demonstrate that imputation preserves the molecular mismatch risk assessment in the vast majority of cases and provides evidence supporting imputation in the performance of molecular mismatch analysis for clinical assessment.

Identifying MAGE-A4-positive tumors for TCR T cell therapies in HLA-A∗02-eligible patients

T cell receptor (TCR) T cell therapies target tumor antigens in a human leukocyte antigen (HLA)-restricted manner. Biomarker-defined therapies require validation of assays suitable for determination of patient eligibility. For clinical trials evaluating TCR T cell therapies targeting melanoma-associated antigen A4 (MAGE-A4), screening in studies NCT02636855 and NCT04044768 assesses patient eligibility based on: (1) high-resolution HLA typing and (2) tumor MAGE-A4 testing via an immunohistochemical assay in HLA-eligible patients. The HLA/MAGE-A4 assays validation, biomarker data, and their relationship to covariates (demographics, cancer type, histopathology, tissue location) are reported here. HLA-A∗02 eligibility was 44.8% (2,959/6,606) in patients from 43 sites across North America and Europe. While HLA-A∗02:01 was the most frequent HLA-A∗02 allele, others (A∗02:02, A∗02:03, A∗02:06) considerably increased HLA eligibility in Hispanic, Black, and Asian populations. Overall, MAGE-A4 prevalence based on clinical trial enrollment was 26% (447/1,750) across 10 solid tumor types, and was highest in synovial sarcoma (70%) and lowest in gastric cancer (9%). The covariates were generally not associated with MAGE-A4 expression, except for patient age in ovarian cancer and histology in non-small cell lung cancer. This report shows the eligibility rate from biomarker screening for TCR T cell therapies and provides epidemiological data for future clinical development of MAGE-A4-targeted therapies.

A structure-guided approach to predict MHC-I restriction of T cell receptors for public antigens

Peptides presented by class I major histocompatibility complex (MHC-I) proteins provide biomarkers for therapeutic targeting using T cell receptors (TCRs), TCR-mimicking antibodies (TMAs), or other engineered protein binders. Despite the extreme sequence diversity of the Human Leucocyte Antigen (HLA, the human MHC), a given TCR or TMA is restricted to recognize epitopic peptides in the context of a limited set of different HLA allotypes. Here, guided by our analysis of 96 TCR:pHLA complex structures in the Protein Data Bank (PDB), we identify TCR contact residues and classify 148 common HLA allotypes into T-cell cross-reactivity groups (T-CREGs) on the basis of their interaction surface features. Insights from our work have actionable value for resolving MHC-I restriction of TCRs, guiding therapeutic expansion of existing therapies, and informing the selection of peptide targets for forthcoming immunotherapy modalities.

A multi-ethnic reference panel to impute HLA classical and non-classical class I alleles in admixed samples: Testing imputation accuracy in an admixed sample from Brazil

The MHC class I region contains crucial genes for the innate and adaptive immune response, playing a key role in susceptibility to many autoimmune and infectious diseases. Genome-wide association studies have identified numerous disease-associated SNPs within this region. However, these associations do not fully capture the immune-biological relevance of specific HLA alleles. HLA imputation techniques may leverage available SNP arrays by predicting allele genotypes based on the linkage disequilibrium between SNPs and specific HLA alleles. Successful imputation requires diverse and large reference panels, especially for admixed populations. This study employed a bioinformatics approach to call SNPs and HLA alleles in multi-ethnic samples from the 1000 genomes (1KG) dataset and admixed individuals from Brazil (SABE), utilising 30X whole-genome sequencing data. Using HIBAG, we created three reference panels: 1KG (n = 2504), SABE (n = 1171), and the full model (n = 3675) encompassing all samples. In extensive cross-validation of these reference panels, the multi-ethnic 1KG reference exhibited overall superior performance than the reference with only Brazilian samples. However, the best results were achieved with the full model. Additionally, we expanded the scope of imputation by developing reference panels for non-classical, MICA, MICB and HLA-H genes, previously unavailable for multi-ethnic populations. Validation in an independent Brazilian dataset showcased the superiority of our reference panels over the Michigan Imputation Server, particularly in predicting HLA-B alleles among Brazilians. Our investigations underscored the need to enhance or adapt reference panels to encompass the target population's genetic diversity, emphasising the significance of multiethnic references for accurate imputation across different populations.

Experimental Data on PIRCHE and T-Cell Reactivity: HLA-DPB1-Derived Peptides Identified by PIRCHE-I Show Binding to HLA-A*02:01 in vitro and T-Cell Activation in vivo

Introduction

Human leukocyte antigen (HLA)-DPB1 mismatches during hematopoietic stem cell transplantation (HSCT) with an unrelated donor result in an increased risk for the development of graft-versus-host disease (GvHD). The number of CD8+ T-cell epitopes available for indirect allorecognition as predicted by the PIRCHE algorithm has been shown to be associated with GvHD development. As a proof of principle, PIRCHE-I predictions for HLA-DPB1 mismatches were validated in vitro and in vivo.

Methods

PIRCHE-I analysis was performed to identify HLA-DPB1-derived peptides that could theoretically bind to HLA-A*02:01. PIRCHE-I predictions for HLA-DPB1 mismatches were validated in vitro by investigating binding affinities of HLA-DPB1-derived peptides to the HLA-A*02:01 in a competition-based binding assay. To investigate the capacity of HLA-DPB1-derived peptides to elicit a T-cell response in vivo, mice were immunized with these peptides. T-cell alloreactivity was subsequently evaluated using an interferon-gamma ELISpot assay.

Results

The PIRCHE-I algorithm identified five HLA-DPB1-derived peptides (RMCRHNYEL, YIYNREEFV, YIYNREELV, YIYNREEYA, and YIYNRQEYA) to be presented by HLA-A*02:01. Binding of these peptides to HLA-A*02:01 was confirmed in a competition-based peptide binding assay, all showing an IC50 value of 21 μm or lower. The peptides elicited an interferon-gamma response in vivo.

Conclusion

Our results indicate that the PIRCHE-I algorithm can identify potential immunogenic HLA-DPB1-derived peptides present in recipients of an HLA-DPB1-mismatched donor. These combined in vitro and in vivo observations strengthen the validity of the PIRCHE-I algorithm to identify HLA-DPB1 mismatch-related GvHD development upon HSCT.

Individual HLAs affect survival after allogeneic stem cell transplantation in adult T-cell leukaemia/lymphoma

Allogeneic haematopoietic stem cell transplantation (allo-HSCT) is the only curative therapy for adult T-cell leukaemia/lymphoma (ATL). Specific HLAs are associated with outcomes of immunotherapy and allo-HSCT. We hypothesised that individual HLAs would affect the clinical outcomes of ATL patients after allo-HSCT. Using data from a Japanese registry, we retrospectively analysed 829 patients with ATL who received transplants from HLA-identical sibling donors or HLA-A, -B, -C or -DRB1 allele-matched unrelated donors between 1996 and 2015. We evaluated the overall mortality risk of HLA-A, -B and -DR antigens with frequencies exceeding 3%. Outcomes were compared between transplants with or without specific HLA antigens. Of the 25 HLAs, two candidates were identified but showed no statistically significant differences by multiple comparison. HLA-B62 was associated with a lower risk of mortality (hazard ratio [HR], 0.68; 95% confidence interval [CI]: 0.51-0.90; p = 0.008), whereas HLA-B60 was associated with a higher risk of mortality (HR, 1.64; 95% CI: 1.19-2.27; p = 0.003). In addition, HLA-B62 was associated with a lower risk of transplant-related mortality (TRM) (HR, 0.52; 95% CI: 0.32-0.85, p = 0.009), whereas HLA-B60 was associated with a higher risk of grades III-IV acute graft-versus-host disease (HR, 2.63; 95% CI: 1.62-4.27; p < 0.001). Neither HLA influenced relapse. The higher risk of acute GVHD in HLA-B60-positive patients and the lower risk of TRM in HLA-B62-positive patients were consistent with previously obtained results from patients with other haematological malignancies. Consideration of HLA in ATL patients may help to predict risk and outcomes after allo-HSCT.

Positive Long-Term Outcome of Kidney Allocation via Acceptable Mismatch Program in Highly Sensitized Patients

Introduction

Eurotransplant established the acceptable mismatch (AM) program to facilitate timely kidney transplantations of highly sensitized patients, but long-term granular clinical and immunological outcomes regarding overall graft survival and de novo DSA (dnDSA) formation are still intensively researched. The right choice of induction therapy in patients with differing immunological risk is not conclusively determined, as well as the impact of human leukocyte antigen (HLA) epitope matching on dnDSA formation.

Methods

This monocentric, retrospective study analyzed 94 patients transplanted within the AM program between 2000 and 2019 compared to case-control matched cohorts of non- (PRA 0-5%; PRA-0) and intermediately sensitized (PRA 6-84%; PRA-6/84) patients transplanted through Eurotransplant Kidney Allocation System.

Results

Estimated 10-year overall graft survival between the PRA-0 and AM cohorts was similar, whereas PRA-6/84 was significantly disadvantageous compared to PRA-0. Estimated 10-year incidence of antibody-mediated rejection rates was significantly lower in the PRA-0 group compared to AM and PRA-6/84 groups. Compared to the AM group, estimated incidence of de novo donor-specific antibody (dnDSA) was significantly lower in PRA-0 patients, with no differences between the AM and PRA-6/84 cohorts. The PRA-6/84 cohort was the only subgroup in which interleukin-2 receptor antagonist (IL2RA) induction was associated with longer overall graft survival, patient survival, and graft survival compared to depleting induction (ATG or OKT3). Broad HLA-A, -B, -DR mismatches (mmABDR) and HLA epitope mismatches determined by Eplets and PIRCHE-II were predictive for dnDSA formation in the total cohort, and the AM subgroup.

Discussion

The high efforts expended on AM patients are justified to allow timely organ transplantation with acceptable risk profile and non-inferior outcomes. IL2RA induction in intermediately sensitized patients is associated with superior overall graft survival, patient survival, and graft survival compared to ATG/OKT3 induction, without negative effects on rejection episodes or dnDSA formation. In silico epitope matching might further help reduce dnDSA formation, particularly in high-risk AM patients.

The Evolution of Hematopoietic Stem Cell Transplantation to Overcome Access Disparities: The Role of NMDP

NMDP recognizes that despite advances in hematopoietic stem cell transplantation (HSCT) and other cell therapies, not all patients have equitable access to treatment, and disparities in outcomes remain. This paper explores the recent work of NMDP to accelerate progress and expand access to more patients through transformative clinical research, particularly in the use of mismatched unrelated donors for HSCT.

A bioinformatic analysis of T-cell epitope diversity in SARS-CoV-2 variants: association with COVID-19 clinical severity in the United States population

Long-term immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires the identification of T-cell epitopes affecting host immunogenicity. In this computational study, we explored the CD8+ epitope diversity estimated in 27 of the most common HLA-A and HLA-B alleles, representing most of the United States population. Analysis of 16 SARS-CoV-2 variants [B.1, Alpha (B.1.1.7), five Delta (AY.100, AY.25, AY.3, AY.3.1, AY.44), and nine Omicron (BA.1, BA.1.1, BA.2, BA.4, BA.5, BQ.1, BQ.1.1, XBB.1, XBB.1.5)] in analyzed MHC class I alleles revealed that SARS-CoV-2 CD8+ epitope conservation was estimated at 87.6%-96.5% in spike (S), 92.5%-99.6% in membrane (M), and 94.6%-99% in nucleocapsid (N). As the virus mutated, an increasing proportion of S epitopes experienced reduced predicted binding affinity: 70% of Omicron BQ.1-XBB.1.5 S epitopes experienced decreased predicted binding, as compared with ~3% and ~15% in the earlier strains Delta AY.100-AY.44 and Omicron BA.1-BA.5, respectively. Additionally, we identified several novel candidate HLA alleles that may be more susceptible to severe disease, notably HLA-A*32:01, HLA-A*26:01, and HLA-B*53:01, and relatively protected from disease, such as HLA-A*31:01, HLA-B*40:01, HLA-B*44:03, and HLA-B*57:01. Our findings support the hypothesis that viral genetic variation affecting CD8 T-cell epitope immunogenicity contributes to determining the clinical severity of acute COVID-19. Achieving long-term COVID-19 immunity will require an understanding of the relationship between T cells, SARS-CoV-2 variants, and host MHC class I genetics. This project is one of the first to explore the SARS-CoV-2 CD8+ epitope diversity that putatively impacts much of the United States population.

Prediction of KIR3DL1/Human Leukocyte Antigen binding

KIR3DL1 is a polymorphic inhibitory Natural Killer (NK) cell receptor that recognizes Human Leukocyte Antigen (HLA) class I allotypes that contain the Bw4 motif. Structural analyses have shown that in addition to residues 77-83 that span the Bw4 motif, polymorphism at other sites throughout the HLA molecule can influence the interaction with KIR3DL1. Given the extensive polymorphism of both KIR3DL1 and HLA class I, we built a machine learning prediction model to describe the influence of allotypic variation on the binding of KIR3DL1 to HLA class I. Nine KIR3DL1 tetramers were screened for reactivity against a panel of HLA class I molecules which revealed different patterns of specificity for each KIR3DL1 allotype. Separate models were trained for each of KIR3DL1 allotypes based on the full amino sequence of exons 2 and 3 encoding the α1 and α2 domains of the class I HLA allotypes, the set of polymorphic positions that span the Bw4 motif, or the positions that encode α1 and α2 but exclude the connecting loops. The Multi-Label-Vector-Optimization (MLVO) model trained on all alpha helix positions performed best with AUC scores ranging from 0.74 to 0.974 for the 9 KIR3DL1 allotype models. We show that a binary division into binder and non-binder is not precise, and that intermediate levels exist. Using the same models, within the binder group, high- and low-binder categories can also be predicted, the regions in HLA affecting the high vs low binder being completely distinct from the classical Bw4 motif. We further show that these positions affect binding affinity in a nonadditive way and induce deviations from linear models used to predict interaction strength. We propose that this approach should be used in lieu of simpler binding models based on a single HLA motif.

An immunogenomic exome landscape of triple positive primary antiphospholipid patients

Primary antiphospholipid syndrome is characterized by thrombosis and autoantibodies directed against phospholipids or associated proteins. The genetic etiology of PAPS remains unknown. We enrolled 21 patients with thromboembolic events associated to lupus anticoagulant, anticardiolipin and anti β2 glycoprotein1 autoantibodies. We performed whole exome sequencing and a systematic variant-based analysis in genes associated with thrombosis, in candidate genes previously associated with APS or inborn errors of immunity. Data were compared to public databases and to a control cohort of 873 non-autoimmune patients. Variants were identified following a state-of-the-art pipeline. Enrichment analysis was performed by comparing with the control cohort. We found an absence of significant HLA bias and genetic heterogeneity in these patients, including when testing combinations of rare variants in genes encoding for proteins involved in thrombosis and of variants in genes linked with inborn errors of immunity. These results provide evidence of genetic heterogeneity in PAPS, even in a homogenous series of triple positive patients. At the individual scale, a combination of variants may participate to the breakdown of B cell tolerance and to the vessel damage.

Resolving unknown nucleotides in the IPD-IMGT/HLA database by extended and full-length sequencing of HLA class I and II alleles

In the past, identification of HLA alleles was limited to sequencing the region of the gene coding for the peptide binding groove, resulting in a lack of sequence information in the HLA database, challenging HLA allele assignment software programs. We investigated full-length sequences of 19 HLA class I and 7 HLA class II alleles, and we extended another 47 HLA class I alleles with sequences of 5' and 3' UTR regions that were all not yet available in the IPD-IMGT/HLA database. We resolved 8638 unknown nucleotides in the coding sequence of HLA class I and 2139 of HLA class II. Furthermore, with full-length sequencing of the 26 alleles, more than 90 kb of sequence information was added to the non-coding sequences, whereas extension of the 47 alleles resulted in the addition of 5.5 kb unknown nucleotides to the 5' UTR and > 31.7 kb to the 3' UTR region. With this information, some interesting features were observed, like possible recombination events and lineage evolutionary origins. The continuing increase in the availability of full-length sequences in the HLA database will enable the identification of the evolutionary origin and will help the community to improve the alignment and assignment accuracy of HLA alleles.

Race, ethnicity, ancestry, and aspects that impact HLA data and matching for transplant

Race, ethnicity, and ancestry are terms that are often misinterpreted and/or used interchangeably. There is lack of consensus in the scientific literature on the definition of these terms and insufficient guidelines on the proper classification, collection, and application of this data in the scientific community. However, defining groups for human populations is crucial for multiple healthcare applications and clinical research. Some examples impacted by population classification include HLA matching for stem-cell or solid organ transplant, identifying disease associations and/or adverse drug reactions, defining social determinants of health, understanding diverse representation in research studies, and identifying potential biases. This article describes aspects of race, ethnicity and ancestry information that impact the stem-cell or solid organ transplantation field with particular focus on HLA data collected from donors and recipients by donor registries or transplant centers.

HLA-class II restricted TCR targeting human papillomavirus type 18 E7 induces solid tumor remission in mice

T cell receptor (TCR)-engineered T cell therapy is a promising potential treatment for solid tumors, with preliminary efficacy demonstrated in clinical trials. However, obtaining clinically effective TCR molecules remains a major challenge. We have developed a strategy for cloning tumor-specific TCRs from long-term surviving patients who have responded to immunotherapy. Here, we report the identification of a TCR (10F04), which is human leukocyte antigen (HLA)-DRA/DRB1*09:01 restricted and human papillomavirus type 18 (HPV18) E784-98 specific, from a multiple antigens stimulating cellular therapy (MASCT) benefited metastatic cervical cancer patient. Upon transduction into human T cells, the 10F04 TCR demonstrated robust antitumor activity in both in vitro and in vivo models. Notably, the TCR effectively redirected both CD4+ and CD8+ T cells to specifically recognize tumor cells and induced multiple cytokine secretion along with durable antitumor activity and outstanding safety profiles. As a result, this TCR is currently being investigated in a phase I clinical trial for treating HPV18-positive cancers. This study provides an approach for developing safe and effective TCR-T therapies, while underscoring the potential of HLA class II-restricted TCR-T therapy as a cancer treatment.

Divergent HLA variations and heterogeneous expression but recurrent HLA loss-of- heterozygosity and common HLA-B and TAP transcriptional silencing across advanced pediatric solid cancers

The human leukocyte antigen (HLA) system is a major factor controlling cancer immunosurveillance and response to immunotherapy, yet its status in pediatric cancers remains fragmentary. We determined high-confidence HLA genotypes in 576 children, adolescents and young adults with recurrent/refractory solid tumors from the MOSCATO-01 and MAPPYACTS trials, using normal and tumor whole exome and RNA sequencing data and benchmarked algorithms. There was no evidence for narrowed HLA allelic diversity but discordant homozygosity and allele frequencies across tumor types and subtypes, such as in embryonal and alveolar rhabdomyosarcoma, neuroblastoma MYCN and 11q subtypes, and high-grade glioma, and several alleles may represent protective or susceptibility factors to specific pediatric solid cancers. There was a paucity of somatic mutations in HLA and antigen processing and presentation (APP) genes in most tumors, except in cases with mismatch repair deficiency or genetic instability. The prevalence of loss-of-heterozygosity (LOH) ranged from 5.9 to 7.7% in HLA class I and 8.0 to 16.7% in HLA class II genes, but was widely increased in osteosarcoma and glioblastoma (~15-25%), and for DRB1-DQA1-DQB1 in Ewing sarcoma (~23-28%) and low-grade glioma (~33-50%). HLA class I and HLA-DR antigen expression was assessed in 194 tumors and 44 patient-derived xenografts (PDXs) by immunochemistry, and class I and APP transcript levels quantified in PDXs by RT-qPCR. We confirmed that HLA class I antigen expression is heterogeneous in advanced pediatric solid tumors, with class I loss commonly associated with the transcriptional downregulation of HLA-B and transporter associated with antigen processing (TAP) genes, whereas class II antigen expression is scarce on tumor cells and occurs on immune infiltrating cells. Patients with tumors expressing sufficient HLA class I and TAP levels such as some glioma, osteosarcoma, Ewing sarcoma and non-rhabdomyosarcoma soft-tissue sarcoma cases may more likely benefit from T cell-based approaches, whereas strategies to upregulate HLA expression, to expand the immunopeptidome, and to target TAP-independent epitopes or possibly LOH might provide novel therapeutic opportunities in others. The consequences of HLA class II expression by immune cells remain to be established. Immunogenetic profiling should be implemented in routine to inform immunotherapy trials for precision medicine of pediatric cancers.

Evaluating NetMHCpan performance on non-European HLA alleles not present in training data

Bias in neural network model training datasets has been observed to decrease prediction accuracy for groups underrepresented in training data. Thus, investigating the composition of training datasets used in machine learning models with healthcare applications is vital to ensure equity. Two such machine learning models are NetMHCpan-4.1 and NetMHCIIpan-4.0, used to predict antigen binding scores to major histocompatibility complex class I and II molecules, respectively. As antigen presentation is a critical step in mounting the adaptive immune response, previous work has used these or similar predictions models in a broad array of applications, from explaining asymptomatic viral infection to cancer neoantigen prediction. However, these models have also been shown to be biased toward hydrophobic peptides, suggesting the network could also contain other sources of bias. Here, we report the composition of the networks' training datasets are heavily biased toward European Caucasian individuals and against Asian and Pacific Islander individuals. We test the ability of NetMHCpan-4.1 and NetMHCpan-4.0 to distinguish true binders from randomly generated peptides on alleles not included in the training datasets. Unexpectedly, we fail to find evidence that the disparities in training data lead to a meaningful difference in prediction quality for alleles not present in the training data. We attempt to explain this result by mapping the HLA sequence space to determine the sequence diversity of the training dataset. Furthermore, we link the residues which have the greatest impact on NetMHCpan predictions to structural features for three alleles (HLA-A*34:01, HLA-C*04:03, HLA-DRB1*12:02).

UK NEQAS and BSHI guideline: Laboratory testing and clinical interpretation of HLA genotyping results supporting the diagnosis of coeliac disease

Coeliac disease is a common immune-mediated inflammatory disorder caused by dietary gluten in genetically susceptible individuals. While the diagnosis of coeliac disease is based on serological and histological criteria, HLA-DQ genotyping can be useful, especially in excluding the diagnosis in patients who do not carry the relevant DQ heterodimers: DQA1*05 DQB1*02, DQB1*03:02 or DQA1*02 DQB1*02 (commonly referred to as DQ2.5, DQ8 and DQ2.2, respectively). External quality assessment results for HLA genotyping in coeliac disease have revealed concerning errors in HLA genotyping, reporting and clinical interpretation. In response, these guidelines have been developed as an evidence-based approach to guide laboratories undertaking HLA genotyping for coeliac disease and provide recommendations for reports to standardise and improve the communication of results.

Determination of the clinical relevance of donor epitope-specific HLA-antibodies in kidney transplantation

In kidney transplantation, survival rates are still partly impaired due to the deleterious effects of donor specific HLA antibodies (DSA). However, not all luminex-defined DSA appear to be clinically relevant. Further analysis of DSA recognizing polymorphic amino acid configurations, called eplets or functional epitopes, might improve the discrimination between clinically relevant vs. irrelevant HLA antibodies. To evaluate which donor epitope-specific HLA antibodies (DESAs) are clinically important in kidney graft survival, relevant and irrelevant DESAs were discerned in a Dutch cohort of 4690 patients using Kaplan-Meier analysis and tested in a cox proportional hazard (CPH) model including nonimmunological variables. Pre-transplant DESAs were detected in 439 patients (9.4%). The presence of certain clinically relevant DESAs was significantly associated with increased risk on graft loss in deceased donor transplantations (p < 0.0001). The antibodies recognized six epitopes of HLA Class I, 3 of HLA-DR, and 1 of HLA-DQ, and most antibodies were directed to HLA-B (47%). Fifty-three patients (69.7%) had DESA against one donor epitope (range 1-5). Long-term graft survival rate in patients with clinically relevant DESA was 32%, rendering DESA a superior parameter to classical DSA (60%). In the CPH model, the hazard ratio (95% CI) of clinically relevant DESAs was 2.45 (1.84-3.25) in deceased donation, and 2.22 (1.25-3.95) in living donation. In conclusion, the developed model shows the deleterious effect of clinically relevant DESAs on graft outcome which outperformed traditional DSA-based risk analysis on antigen level.

PIRCHE-II Risk and Acceptable Mismatch Profile Analysis in Solid Organ Transplantation

To optimize outcomes in solid organ transplantation, the HLA genes are regularly compared and matched between the donor and recipient. However, in many cases a transplant cannot be fully matched, due to widespread variation across populations and the hyperpolymorphism of HLA alleles. Mismatches of the HLA molecules in transplanted tissue can be recognized by immune cells of the recipient, leading to immune response and possibly organ rejection. These adverse outcomes are reduced by analysis using epitope-focused models that consider the immune relevance of the mismatched HLA.PIRCHE, an acronym for Predicted Indirectly ReCognizable HLA Epitopes, aims to categorize and quantify HLA mismatches in a patient-donor pair by predicting HLA-derived T cell epitopes. Specifically, the algorithm predicts and counts the HLA-derived peptides that can be presented by the host HLA, known as indirectly-presented T cell epitopes. Looking at the immune-relevant epitopes within HLA allows a more biologically relevant understanding of immune response, and provides an expanded donor pool for a more refined matching strategy compared with allele-level matching. This PIRCHE algorithm is available for analysis of single transplantations, as well as bulk analysis for population studies and statistical analysis for comparison of probability of organ availability and risk profiles.

Graph-Based Imputation Methods and Their Applications to Single Donors and Families

The outcome of Hematopoietic Stem Cell (HSCT) and organ transplant is strongly affected by the matching of the HLA alleles of the donor and the recipient. However, donors and sometimes recipients are often typed at low resolution, with some alleles either missing or ambiguous. Thus, imputation methods are required to detect the most probably high-resolution HLA haplotypes consistent with a typing. Such imputation algorithms require predefined haplotype frequencies. As such, the phasing of the typing is required for both imputation and frequency generation.We have developed a new approach to HLA haplotype and genotype imputation, where first all candidate phases of a typing are explicated, and then the ambiguity within each phase is solved. This ambiguity is solved through a graph structure of all partial haplotypes and the haplotypes consistent with them.This phasing approach was used to produce an imputation algorithm (GRIMM-Graph Imputation and Matching). GRIMM was then combined with the possibility of combining information from multiple races to produce MR-GRIMM (Multi-Race GRIMM). When family information is available, the phasing of each family member can be restricted by the others. We propose GRAMM (GRaph-bAsed faMily iMputation) to phase alleles in family pedigree HLA typing data and in mother-cord blood unit pairs. Finally, we combined MR-GRIMM with an expectation-maximization (EM) algorithm to estimate haplotype frequencies sharing information between races to produce MR-GRIMME (MR-GRIMM EM).We have shown that these algorithms naturally combine information between races and family members. The accuracy of each of these algorithms is significantly better than its current parallel methods. MR-GRIMM leads to high accuracy in matching predictions. GRAMM better imputes family members than either MR-GRIMM or any existing algorithm and has practically no phasing errors. MR-GRIMME obtains a higher likelihood than existing algorithms.MR-GRIMM, MR-GRIMME, and GRAMM are available as servers or through stand-alone versions in GITHUB and PyPi, as detailed in the appropriate sections.

Ellipro scores of donor epitope specific HLA antibodies are not associated with kidney graft survival

In kidney transplantation, donor HLA antibodies are a risk factor for graft loss. Accessibility of donor eplets for HLA antibodies is predicted by the ElliPro score. The clinical usefulness of those scores in relation to transplant outcome is unknown. In a large Dutch kidney transplant cohort, Ellipro scores of pretransplant donor antibodies that can be assigned to known eplets (donor epitope specific HLA antibodies [DESAs]) were compared between early graft failure and long surviving deceased donor transplants. We did not observe a significant Ellipro score difference between the two cohorts, nor significant differences in graft survival between transplants with DESAs having high versus low total Ellipro scores. We conclude that Ellipro scores cannot be used to identify DESAs associated with early versus late kidney graft loss in deceased donor transplants.

Improving HLA typing imputation accuracy and eplet identification with local next-generation sequencing training data

Assessing donor/recipient HLA compatibility at the eplet level requires second field DNA typings but these are not always available. These can be estimated from lower-resolution data either manually or with computational tools currently relying, at best, on data containing typing ambiguities. We gathered NGS typing data from 61,393 individuals in 17 French laboratories, for loci A, B, and C (100% of typings), DRB1 and DQB1 (95.5%), DQA1 (39.6%), DRB3/4/5, DPB1, and DPA1 (10.5%). We developed HaploSFHI, a modified iterative maximum likelihood algorithm, to impute second field HLA typings from low- or intermediate-resolution ones. Compared with the reference tools HaploStats, HLA-EMMA, and HLA-Upgrade, HaploSFHI provided more accurate predictions across all loci on two French test sets and four European-independent test sets. Only HaploSFHI could impute DQA1, and solely HaploSFHI and HaploStats provided DRB3/4/5 imputations. The improved performance of HaploSFHI was due to our local and nonambiguous data. We provided explanations for the most common imputation errors and pinpointed the variability of a low number of low-resolution haplotypes. We thus provided guidance to select individuals for whom sequencing would optimize incompatibility assessment and cost-effectiveness of HLA typing, considering not only well-imputed second field typing(s) but also well-imputed eplets.

Honduras HIV cohort: HLA class I and CCR5-Δ32 profiles and their associations with HIV disease outcome

IMPORTANCE

We identify both canonical and novel human leukocyte antigen (HLA)-HIV associations, providing a first step toward improved understanding of HIV immune control among the understudied Honduras Mestizo population. Our results are relevant to understanding the protective or detrimental effects of HLA subtypes in Latin America because their unique HLA diversity poses challenges for designing vaccines against HIV and interpreting results from such vaccine trials. Likewise, the description of the HLA profile in an understudied population that shows a unique HLA immunogenetic background is not only relevant for HIV immunology but also relevant in population genetics, molecular anthropology, susceptibility to other infections, autoimmune diseases, and allograft transplantation.

HLA frequency distribution of the Portuguese bone marrow donor registry

Introduction

The Portuguese donor Registry of CEDACE was the fifth largest per capita bone marrow donor Registry of the WMDA as of 2019 and has yet to be thoroughly analyzed. We aimed to characterize its various aspects, including demographics and HLA allele and haplotype frequencies, to evaluate the genetic matching propensity score and ultimately further develop it.

Methods

We described and compared characteristics of the donor population with census data and used an Expectation-Maximization algorithm and analyses of molecular variance to assess haplotype frequencies and establish phylogenetic distances between regions and districts within the country.

Results

We identified 396545 donors, corresponding to 3.85% of the Portuguese population; the median donor age was 39 years, with 60.4% of female donors. Most donors were Portuguese nationals, although 40 other nationalities were present, with a significant proportion of donors from Brazil and Portuguese-speaking African Countries; almost all donors self-reported as Western, with the second largest group reporting African ancestry. There was an asymmetric contribution of donors from different districts and regions, with most coming from coastal districts and few from the southern districts and autonomous regions; foreign and self-declared non-Western donors were mainly located in the Metropolitan Area of Lisbon and the South. Although most donors were typed in three loci (HLA-A, HLA-B and HLA-DRB1), only 44% were also typed in HLA-C, 1.28% in HLA-DQB1 and only 0.77% in all five loci and in high-resolution. There were varying allele and haplotype frequencies across districts and regions, with the most common three loci, low-resolution haplotypes, being HLA-A*01~B*08~DRB1*03, A*29~B*44~DRB1*07 and HLA-A*02~B*44~DRB1*04; some haplotypes were more prevalent in the South, others in the North and a few in the autonomous regions; African and foreign donors presented relevant differences in haplotype frequency distributions, including rare haplotypes of potential interest. We also report on four loci, low-resolution frequency distributions. Using AMOVA, we compared genetic distances between districts and regions, which recapitulated the country's geography.

Discussion

Our analysis showed potential paths to optimization of the Registry, including increasing the male donor pool and focusing on underrepresented districts and particular populations of interest, such as donors from Portuguese-speaking African countries.

Structural principles of peptide-centric chimeric antigen receptor recognition guide therapeutic expansion

Peptide-centric chimeric antigen receptors (PC-CARs) recognize oncoprotein epitopes displayed by cell-surface human leukocyte antigens (HLAs) and offer a promising strategy for targeted cancer therapy. We have previously developed a PC-CAR targeting a neuroblastoma-associated PHOX2B peptide, leading to robust tumor cell lysis restricted by two common HLA allotypes. Here, we determine the 2.1-angstrom crystal structure of the PC-CAR-PHOX2B-HLA-A*24:02-β2m complex, which reveals the basis for antigen-specific recognition through interactions with CAR complementarity-determining regions (CDRs). This PC-CAR adopts a diagonal docking mode, where interactions with both conserved and polymorphic HLA framework residues permit recognition of multiple HLA allotypes from the A9 serological cross-reactive group, covering a combined global population frequency of up to 46.7%. Biochemical binding assays, molecular dynamics simulations, and structural and functional analyses demonstrate that high-affinity PC-CAR recognition of cross-reactive pHLAs necessitates the presentation of a specific peptide backbone, where subtle structural adaptations of the peptide are critical for high-affinity complex formation, and CAR T cell killing. Our results provide a molecular blueprint for engineering CARs with optimal recognition of tumor-associated antigens in the context of different HLAs, while minimizing cross-reactivity with self-epitopes.

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.

Bw4 ligand and direct T-cell receptor binding induced selection on HLA A and B alleles

Introduction

The HLA region is the hallmark of balancing selection, argued to be driven by the pressure to present a wide variety of viral epitopes. As such selection on the peptide-binding positions has been proposed to drive HLA population genetics. MHC molecules also directly binds to the T-Cell Receptor and killer cell immunoglobulin-like receptors (KIR).

Methods

We here combine the HLA allele frequencies in over six-million Hematopoietic Stem Cells (HSC) donors with a novel machine-learning-based method to predict allele frequency.

Results

We show for the first time that allele frequency can be predicted from their sequences. This prediction yields a natural measure for selection. The strongest selection is affecting KIR binding regions, followed by the peptide-binding cleft. The selection from the direct interaction with the KIR and TCR is centered on positively charged residues (mainly Arginine), and some positions in the peptide-binding cleft are not associated with the allele frequency, especially Tyrosine residues.

Discussion

These results suggest that the balancing selection for peptide presentation is combined with a positive selection for KIR and TCR binding.

Existence of HLA-Mismatched Unrelated Donors Closes the Gap in Donor Availability Regardless of Recipient Ancestry

In patients without a matched sibling donor (MSD) or well-matched unrelated donor (MUD), hematopoietic cell transplantation (HCT) can still be successful when using an HLA-mismatched unrelated donor (MMUD) in combination with post-transplantation cyclophosphamide (PTCy), abatacept, or other novel approaches. This may allow clinicians to choose a suitable donor from a wide range of donor options while optimizing other donor selection characteristics, including donor age. We hypothesized that allowing for a 5/8 HLA match level considering high-resolution matching at HLA-A, -B, -C and -DRB1, there is a potential to close the donor availability gap for all patients regardless of their race/ethnicity. In this work, we estimate the likelihood of matching for all racial/ethnic groups at different HLA match thresholds. Our study aimed to assess the potential for identifying an available MUD or MMUD in the National Marrow Donor Program (NMDP)/Be The Match (BTM) donor registry for 21 detailed and 5 broad racial/ethnic groups, using high-resolution HLA matching for HLA-A, -B, -C, and -DRB1 at various levels (8/8, 7/8, 6/8, and 5/8). We used donor registry population data from the NMDP/BTM in 2020 and redistributed the donor registry data according to existing population ratios, accounting for demonstrated donor availability. Finally, we used a genetic model at the population level to estimate the match likelihood for detailed and broad racial/ethnic groups. Likelihood of 8/8 HLA match ranging from 16% to 74% were obtained for various detailed racial/ethnic groups with available donors age ≤35 years. When considering more mismatches in the HLA loci, registry coverage became >99% with a 5/8 HLA match level for donors of all ages or those age ≤35 years, with HLA-DPB1 T cell epitope permissive matching, or when searching for donors outside of their racial/ethnic group. Our registry models demonstrate the potential for using MMUDs at various HLA match levels to study whether this will expand access to HCT across racial/ethnic groups. Expanded donor options may erase the donor availability gap for all patients while allowing for selection of MMUDs with favorable characteristics, such as younger age.

HLA-haplotype redundancy and rareness in Canadian Blood Services' Stem Cell Registry and Cord Blood Bank: Novel metrics for optimizing utility

BACKGROUND

The utility of unrelated donor registries that support allogeneic hematopoietic cell transplantation could be optimized through greater understanding of redundancy and rareness of HLA phenotypes.

METHODS

HLA phenotype rareness was determined using known HLA haplotype frequencies. Donor redundancy was determined through pairwise comparison of donor HLA profiles within an inventory.

RESULTS

Among 61,730 registrants in the Canadian Blood Services (CBS) Stem Cell Registry (SCR) with high resolution HLA typing at 5 loci, 6.6% of HLA phenotypes were redundant with variation across ethnic groups (8.3% of Caucasian phenotypes; 8% of Native American/First Nations, 4.4% of Asia-Pacific Islanders (API), 2.1% of Hispanic, 0.7% of African-American (AFA), and 4.5% of other ethnicities). A total of 18.5% of registrants had redundant HLA phenotypes with variation across ethnic groups. All 3716 cord blood units in the CBS's cord blood bank (CBB) had high resolution HLA typing at 5 loci and 202 units were redundant (5.4%) comprising 78 HLA phenotypes, with varying rareness. Repeated HLA phenotypes were from Caucasian donors (77%), multiple ethnicity (13%), API (9%), and AFA (1%). Registrants and CBUs with AFA ethnicity had the rarest phenotypes while Caucasian ethnicity was associated with the most common HLA phenotypes.

CONCLUSIONS

Redundancy was greater in the SCR compared to the CBB and was most common with CAU ethnicity. Recruiting non-Caucasian registrants and continued cord blood banking should reduce redundancy. A sub-inventory of redundant donors and cord blood units could support new uses for donor-supported cellular therapies that do not require HLA matching.

GRAMM: A new method for analysis of HLA in families

Recently, haplo-identical transplantation with multiple HLA mismatches has become a viable option for stem cell transplants. Haplotype sharing detection requires the imputation of donor and recipient. We show that even in high-resolution typing when all alleles are known, there is a 15% error rate in haplotype phasing, and even more in low-resolution typings. Similarly, in related donors, the parents' haplotypes should be imputed to determine what haplotype each child inherited. We propose graph-based family imputation (GRAMM) to phase alleles in family pedigree HLA typing data, and in mother-cord blood unit pairs. We show that GRAMM has practically no phasing errors when pedigree data are available. We apply GRAMM to simulations with different typing resolutions as well as paired cord-mother typings, and show very high phasing accuracy, and improved allele imputation accuracy. We use GRAMM to detect recombination events and show that the rate of falsely detected recombination events (false-positive rate) in simulations is very low. We then apply recombination detection to typed families to estimate the recombination rate in Israeli and Australian population datasets. The estimated recombination rate has an upper bound of 10%-20% per family (1%-4% per individual).

A common allele of HLA is associated with asymptomatic SARS-CoV-2 infection

Studies have demonstrated that at least 20% of individuals infected with SARS-CoV-2 remain asymptomatic1-4. Although most global efforts have focused on severe illness in COVID-19, examining asymptomatic infection provides a unique opportunity to consider early immunological features that promote rapid viral clearance. Here, postulating that variation in the human leukocyte antigen (HLA) loci may underly processes mediating asymptomatic infection, we enrolled 29,947 individuals, for whom high-resolution HLA genotyping data were available, in a smartphone-based study designed to track COVID-19 symptoms and outcomes. Our discovery cohort (n = 1,428) comprised unvaccinated individuals who reported a positive test result for SARS-CoV-2. We tested for association of five HLA loci with disease course and identified a strong association between HLA-B*15:01 and asymptomatic infection, observed in two independent cohorts. Suggesting that this genetic association is due to pre-existing T cell immunity, we show that T cells from pre-pandemic samples from individuals carrying HLA-B*15:01 were reactive to the immunodominant SARS-CoV-2 S-derived peptide NQKLIANQF. The majority of the reactive T cells displayed a memory phenotype, were highly polyfunctional and were cross-reactive to a peptide derived from seasonal coronaviruses. The crystal structure of HLA-B*15:01-peptide complexes demonstrates that the peptides NQKLIANQF and NQKLIANAF (from OC43-CoV and HKU1-CoV) share a similar ability to be stabilized and presented by HLA-B*15:01. Finally, we show that the structural similarity of the peptides underpins T cell cross-reactivity of high-affinity public T cell receptors, providing the molecular basis for HLA-B*15:01-mediated pre-existing immunity.

HLA class I signal peptide polymorphism determines the level of CD94/NKG2-HLA-E-mediated regulation of effector cell responses

Human leukocyte antigen (HLA)-E binds epitopes derived from HLA-A, HLA-B, HLA-C and HLA-G signal peptides (SPs) and serves as a ligand for CD94/NKG2A and CD94/NKG2C receptors expressed on natural killer and T cell subsets. We show that among 16 common classical HLA class I SP variants, only 6 can be efficiently processed to generate epitopes that enable CD94/NKG2 engagement, which we term 'functional SPs'. The single functional HLA-B SP, known as HLA-B/-21M, induced high HLA-E expression, but conferred the lowest receptor recognition. Consequently, HLA-B/-21M SP competes with other SPs for providing epitope to HLA-E and reduces overall recognition of target cells by CD94/NKG2A, calling for reassessment of previous disease models involving HLA-B/-21M. Genetic population data indicate a positive correlation between frequencies of functional SPs in humans and corresponding cytomegalovirus mimics, suggesting a means for viral escape from host responses. The systematic, quantitative approach described herein will facilitate development of prediction algorithms for accurately measuring the impact of CD94/NKG2-HLA-E interactions in disease resistance/susceptibility.

Multiple sclerosis: Exploring the limits and implications of genetic and environmental susceptibility

OBJECTIVE

To explore and describe the basis and implications of genetic and environmental susceptibility to multiple sclerosis (MS) using the Canadian population-based data.

BACKGROUND

Certain parameters of MS-epidemiology are directly observable (e.g., the recurrence-risk of MS in siblings and twins, the proportion of women among MS patients, the population-prevalence of MS, and the time-dependent changes in the sex-ratio). By contrast, other parameters can only be inferred from the observed parameters (e.g., the proportion of the population that is "genetically susceptible", the proportion of women among susceptible individuals, the probability that a susceptible individual will experience an environment "sufficient" to cause MS, and if they do, the probability that they will develop the disease).

DESIGN/METHODS

The "genetically susceptible" subset (G) of the population (Z) is defined to include everyone with any non-zero life-time chance of developing MS under some environmental conditions. The value for each observed and non-observed epidemiological parameter is assigned a "plausible" range. Using both a Cross-sectional Model and a Longitudinal Model, together with established parameter relationships, we explore, iteratively, trillions of potential parameter combinations and determine those combinations (i.e., solutions) that fall within the acceptable range for both the observed and non-observed parameters.

RESULTS

Both Models and all analyses intersect and converge to demonstrate that probability of genetic-susceptibitly, P(G), is limited to only a fraction of the population {i.e., P(G) ≤ 0.52)} and an even smaller fraction of women {i.e., P(G│F) < 0.32)}. Consequently, most individuals (particularly women) have no chance whatsoever of developing MS, regardless of their environmental exposure. However, for any susceptible individual to develop MS, requires that they also experience a "sufficient" environment. We use the Canadian data to derive, separately, the exponential response-curves for men and women that relate the increasing likelihood of developing MS to an increasing probability that a susceptible individual experiences an environment "sufficient" to cause MS. As the probability of a "sufficient" exposure increases, we define, separately, the limiting probability of developing MS in men (c) and women (d). These Canadian data strongly suggest that: (c < d ≤ 1). If so, this observation establishes both that there must be a "truly" random factor involved in MS pathogenesis and that it is this difference, rather than any difference in genetic or environmental factors, which primarily accounts for the penetrance difference between women and men.

CONCLUSIONS

The development of MS (in an individual) requires both that they have an appropriate genotype (which is uncommon in the population) and that they have an environmental exposure "sufficient" to cause MS given their genotype. Nevertheless, the two principal findings of this study are that: P(G) ≤ 0.52)} and: (c < d ≤ 1). Threfore, even when the necessary genetic and environmental factors, "sufficient" for MS pathogenesis, co-occur for an individual, they still may or may not develop MS. Consequently, disease pathogenesis, even in this circumstance, seems to involve an important element of chance. Moreover, the conclusion that the macroscopic process of disease development for MS includes a "truly" random element, if replicated (either for MS or for other complex diseases), provides empiric evidence that our universe is non-deterministic.

Identification of 58 novel HLA alleles identified in Chinese individuals by next-generation sequencing

HLA genes are the most polymorphic in the human genome. High resolution HLA typing from 13,870 bone marrow donors in Hong Kong was obtained using Next-generation sequencing (NGS) technology. Among the 67 novel alleles identified, official HLA allele names of 50 novel class I alleles (HLA-A, -B, -C) and 8 novel class II alleles (HLA-DRB1, -DQB1) were assigned by the World Health Organization (WHO) Nomenclature Committee for Factors of the HLA System.

Allele and haplotype frequencies of 11 HLA loci in Koreans by next-generation sequencing

Data on HLA genotype distribution, including DQA1 and DPA1, in the Korean population are limited. We aimed to investigate the allele and haplotype frequencies of 11 HLA loci in 339 Korean subjects using next-generation sequencing (NGS)-based HLA typing. A total of 339 samples from unrelated healthy subjects were genotyped for HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQB1, -DQA1, -DPB1, and -DPA1 using two different NGS-based HLA typing kits (166 tested using the NGSgo-MX11-3 kit [GenDx, Netherlands] and 173 by the AllType NGS 11 Loci Amplification kit [One Lambda, USA]). PyPop software was used to estimate allele and haplotype frequencies and linkage disequilibrium between the loci. Additionally, a principal component analysis was performed to compare the allele distribution of Koreans with that of other populations. A total of 214 HLA alleles (97 class I and 117 class II alleles) were assigned. The most frequent alleles for each locus were A*24:02:01 (24.78%), B*15:01:01 (10.18%), C*01:02:01 (18.44%), DRB1*04:05:01 (9.59%), DRB3*02:02:01 (13.72%), DRB4*01:03:01 (25.81%), DRB5*01:01:01 (9.0%), DQA1*01:02:01 (16.96%), DQB1*03:01:01 (14.31%), DPA1*01:03:01 (44.4%), and DPB1*05:01:01 (35.1%), respectively. The most frequent haplotypes were A*33:03:01-C*03:02:02-B*58:01:01 for HLA class I (5.01%) and DRB1*04:05:01-DQA1*03:03:01-DQB1*04:01:01-DPA1*02:02:02-DPB1*05:01:01 for HLA class II (6.23%). The total allelic ambiguities by NGS were estimated to be minimal and considerably decreased compared with those by Sanger sequencing. The Japanese population had the most similar allele distribution to Koreans, followed by the Chinese population. Frequency data of 11 HLA loci in Koreans can provide essential data for population genetics and disease association studies.

HLA amino acid Mismatch-Based risk stratification of kidney allograft failure using a novel Machine learning algorithm

OBJECTIVE

While associations between HLA antigen-level mismatches (Ag-MM) and kidney allograft failure are well established, HLA amino acid-level mismatches (AA-MM) have been less explored. Ag-MM fails to consider the substantial variability in the number of MMs at polymorphic amino acid (AA) sites within any given Ag-MM category, which may conceal variable impact on allorecognition. In this study we aim to develop a novel Feature Inclusion Bin Evolver for Risk Stratification (FIBERS) and apply it to automatically discover bins of HLA amino acid mismatches that stratify donor-recipient pairs into low versus high graft survival risk groups.

METHODS

Using data from the Scientific Registry of Transplant Recipients, we applied FIBERS on a multiethnic population of 166,574 kidney transplants between 2000 and 2017. FIBERS was applied (1) across all HLA-A, B, C, DRB1, and DQB1 locus AA-MMs with comparison to 0-ABDR Ag-MM risk stratification, (2) on AA-MMs within each HLA locus individually, and (3) using cross validation to evaluate FIBERS generalizability. The predictive power of graft failure risk stratification was evaluated while adjusting for donor/recipient characteristics and HLA-A, B, C, DRB1, and DQB1 Ag-MMs as covariates.

RESULTS

FIBERS's best-performing bin (on AA-MMs across all loci) added significant predictive power (hazard ratio = 1.10, Bonferroni adj. p < 0.001) in stratifying graft failure risk (where low-risk is defined as zero AA-MMs and high-risk is one or more AA-MMs) even after adjusting for Ag-MMs and donor/recipient covariates. The best bin also categorized more than twice as many patients to the low-risk category, compared to traditional 0-ABDR Ag mismatching (∼24.4% vs ∼ 9.1%). When HLA loci were binned individually, the bin for DRB1 exhibited the strongest risk stratification; relative to zero AA-MM, one or more MMs in the bin yielded HR = 1.11, p < 0.005 in a fully adjusted Cox model. AA-MMs at HLA-DRB1 peptide contact sites contributed most to incremental risk of graft failure. Additionally, FIBERS points to possible risk associated with HLA-DQB1 AA-MMs at positions that determine specificity of peptide anchor residues and HLA-DQ heterodimer stability.

CONCLUSION

FIBERS's performance suggests potential for discovery of HLA immunogenetics-based risk stratification of kidney graft failure that outperforms traditional assessment.

HLA allele and haplotype frequencies of registered stem cell donors in Chile

Patients in need of hematopoietic stem cell transplantation often rely on unrelated stem cell donors matched in certain human leukocyte antigen (HLA) genes. Donor search is complicated by the extensive allelic variability of the HLA system. Therefore, large registries of potential donors are maintained in many countries worldwide. Population-specific HLA characteristics determine the registry benefits for patients and also the need for further regional donor recruitment. In this work, we analyzed HLA allele and haplotype frequencies of donors of DKMS Chile, the first Chilean donor registry, with self-assessed "non-Indigenous" (n=92,788) and "Mapuche" (n=1,993) ancestry. We identified HLA alleles that were distinctly more abundant in the Chilean subpopulations than in worldwide reference populations, four of them particularly characteristic for the Mapuche subpopulation, namely B*39:09g, B*35:09, DRB1*04:07g, and DRB1*16:02g. Both population subsamples carried haplotypes of both Native American and European origin at high frequencies, reflecting Chile's complex history of admixture and immigration. Matching probability analysis revealed limited benefits for Chilean patients (both non-Indigenous and Mapuche) from donor registries of non-Chilean donors, thus indicating a need for ongoing significant donor recruitment efforts in Chile.

Development of a calculated panel reactive antibody calculator for the United Arab Emirates: a proof of concept study

Calculated panel reactive antibody (CPRA) is used to help increase sensitized patient's access to transplantation. United Arab Emirates (UAE) has a diverse resident population hence we developed a UAE-CPRA calculator based on HLA antigen frequencies of the different ethnic groups that represent the UAE population. HLA antigen frequencies at serological split antigen level for HLA-A, -B, -C, -DRB1 and -DQB1 of 1002 healthy unrelated donors were performed. We subsequently compared the performance of the UAE CPRA calculator with the Organ Procurement and Transplantation Network (OPTN) and the Canadian CPRA calculators in 110 Kidney Transplant waitlist patients from January 2016 to December 2018. Lin's concordance correlation coefficient showed a moderate agreement between the UAE and OPTN calculator (Rc = 0.949, 95% CI 0.929-0.963) and the UAE and Canadian calculators (Rc = 0.952, 95% CI 0.932-0.965). While there continued to be a moderate agreement (Rc = 0.937, UAE versus OPTN calculator) in the lower sensitized group, a poor agreement (Rc = 0.555, UAE versus OPTN calculator) was observed in the higher sensitized group. In this study, we provide a template for countries to develop their own population-specific CPRA calculator. Implementation of the CPRA algorithm based on HLA frequencies of the multi-ethnic UAE population will be more fitting to increase access to transplantation and improve transplant outcomes. Our study demonstrates that the CPRA calculators developed using the data from the western population had poor correlation in our higher sensitized patients disadvantaging them in potential organ allocations systems. We plan to further refine this calculator by using high resolution HLA typing to address the problem of a genetically diverse population.

Structural principles of peptide-centric Chimeric Antigen Receptor recognition guide therapeutic expansion

Peptide-Centric Chimeric Antigen Receptors (PC-CARs), which recognize oncoprotein epitopes displayed by human leukocyte antigens (HLAs) on the cell surface, offer a promising strategy for targeted cancer therapy ¹ . We have previously developed a PC-CAR targeting a neuroblastoma- associated PHOX2B peptide, leading to robust tumor cell lysis restricted by two common HLA allotypes ² . Here, we determine the 2.1 Å structure of the PC-CAR:PHOX2B/HLA-A*24:02/β2m complex, which reveals the basis for antigen-specific recognition through interactions with CAR complementarity-determining regions (CDRs). The PC-CAR adopts a diagonal docking mode, where interactions with both conserved and polymorphic HLA framework residues permit recognition of multiple HLA allotypes from the A9 serological cross-reactivity group, covering a combined American population frequency of up to 25.2%. Comprehensive characterization using biochemical binding assays, molecular dynamics simulations, and structural and functional analyses demonstrate that high-affinity PC-CAR recognition of cross-reactive pHLAs necessitates the presentation of a specific peptide backbone, where subtle structural adaptations of the peptide are critical for high-affinity complex formation and CAR-T cell killing. Our results provide a molecular blueprint for engineering CARs with optimal recognition of tumor-associated antigens in the context of different HLAs, while minimizing cross-reactivity with self-epitopes.

An immunogenic and oncogenic feature-based classification for chemotherapy plus PD-1 blockade in advanced esophageal squamous cell carcinoma

Although chemotherapy plus PD-1 blockade (chemo+anti-PD-1) has become the standard first-line therapy for advanced esophageal squamous cell carcinoma (ESCC), reliable biomarkers for this regimen are lacking. Here we perform whole-exome sequencing on tumor samples from 486 patients of the JUPITER-06 study and develop a copy number alteration-corrected tumor mutational burden that depicts immunogenicity more precisely and predicts chemo+anti-PD-1 efficacy. We identify several other favorable immunogenic features (e.g., HLA-I/II diversity) and risk oncogenic alterations (e.g., PIK3CA and TET2 mutation) associated with chemo+anti-PD-1 efficacy. An esophageal cancer genome-based immuno-oncology classification (EGIC) scheme incorporating these immunogenic features and oncogenic alterations is established. Chemo+anti-PD-1 achieves significant survival improvements in EGIC1 (immunogenic feature-favorable and oncogenic alteration-negative) and EGIC2 (either immunogenic feature-favorable or oncogenic alteration-negative) subgroups, but not the EGIC3 subgroup (immunogenic feature-unfavorable and oncogenic alteration-positive). Thus, EGIC may guide future individualized treatment strategies and inform mechanistic biomarker research for chemo+anti-PD-1 treatment in patients with advanced ESCC.

Unrelated Stem Cell Donor HLA Match Likelihood in the US Registry Incorporating HLA-DPB1 Permissive Mismatching

Donor-recipient HLA matching at the DPB1 locus improves the outcomes of hematopoietic stem cell transplantation (HCT). Retrospective outcome studies found that in HCTs matched for all 8 alleles of the A, B, C, and DRB1 loci at high resolution (8/8 match), few transplantations were also allele-matched at the DPB1 locus. DPB1 allele matching was once thought to be logistically impractical; however, a DPB1-permissive mismatch model based on T cell epitope (TCE) reactivity expands the proportion of suitable donors. To understand the likelihood of finding a DPB1-permissive donor, we sought to expand population genetic match likelihood models for the US unrelated donor registry, the National Marrow Donor Program (NMDP). After extending HLA haplotype frequency estimates to include the DPB1 locus, our models found that the likelihood of having a DPB1-permissive donor was not much lower than likelihood of 8/8 matching. A maximum of 5 additional donors would need to be typed to find a more optimal DPB1-permissive donor at least 90% of the time. Linkage disequilibrium patterns between the DPB1 locus and other classical HLA loci varied markedly by haplotype and population, indicating that the known recombination hotspot between DQ and DP gene complexes has not had a uniform impact; thus, DPB1-permissive donors are easier to identify within minority populations. DPB1 TCE categories were highly predictable from HLA typing at other loci when imputed with extended haplotype frequency data. Our overall results indicate that registry search strategies that seek a more optimally matched HCT donor encompassing HLA-DPB1 permissibility are likely to be highly productive.

Molecular HLA mismatching for prediction of primary humoral alloimmunity and graft function deterioration in paediatric kidney transplantation

Introduction

Rejection remains the main cause of allograft failure in paediatric kidney transplantation and is driven by donor-recipient HLA mismatching. Modern computational algorithms enable assessment of HLA mismatch immunogenicity at the molecular level (molecular-mismatch, molMM). Whilst molMM has been shown to correlate with alloimmune outcomes, evidence demonstrating improved prediction performance against traditional antigen mismatching (antMM) is lacking.

Methods

We analysed 177 patients from the CERTAIN registry (median follow-up 4.5 years). molMM scores included Amino-Acid-Mismatch-Score (AAMS), Electrostatic-Mismatch-Score (EMS3D) and netMHCIIpan (netMHC1k: peptide binding affinity ≤1000 nM; netMHC: binding affinity ≤500 nM plus rank <2%). We stratified patients into high/low-risk groups based on risk models of DSA development.

Results

Donor-specific HLA antibodies (DSA) predominantly targeted the highest scoring molMM donor antigen within each HLA locus. MolMM scores offered superior discrimination versus antMM in predicting de novo DSA for all HLA loci; the EMS3D algorithm had particularly consistent performance (area under the receiver operating characteristic curve (AUC) >0.7 for all HLA loci vs. 0.52-0.70 for antMM). ABMR (but not TCMR) was associated with HLA-DQ molMM scores (AAMS, EMS3D and netMHC). Patients with high-risk HLA-DQ molMM had increased risk of graft function deterioration (50% reduction in baseline eGFR (eGFR50), adjusted HR: 3.5, 95% CI 1.6-8.2 high vs. low EMS3D). Multivariable modelling of the eGFR50 outcome using EMS3D HLA-DQ stratification showed better discrimination (AUC EMS3D vs. antMM at 2 years: 0.81 vs. 0.77, at 4.5 years: 0.72 vs. 0.64) and stratified more patients into the low-risk group, compared to traditional antMM.

Conclusion

Molecular mismatching was superior to antigen mismatching in predicting humoral alloimmunity. Molecular HLA-DQ mismatching appears to be a significant prognostic factor for graft function deterioration in paediatric kidney transplantation.

A universal MHCII technology platform to characterize antigen-specific CD4+ T cells

CD4+ T cells are critical to the immune system and perform multiple functions; therefore, their identification and characterization are crucial to better understanding the immune system in both health and disease states. However, current methods rarely preserve their ex vivo phenotype, thus limiting our understanding of their in vivo functions. Here we introduce a flexible, rapid, and robust platform for ex vivo CD4+ T cell identification. By combining MHCII allele purification, allele-independent peptide loading, and multiplexed flow cytometry technologies, we can enable high-throughput personalized CD4+ T cell identification, immunophenotyping, and sorting. Using this platform in combination with single-cell sorting and multimodal analyses, we identified and characterized antigen-specific CD4+ T cells relevant to COVID-19 and cancer neoantigen immunotherapy. Overall, our platform can be used to detect and characterize CD4+ T cells across multiple diseases, with potential to guide CD4+ T cell epitope design for any disease-specific immunization strategy.

HLA and red blood cell antigen genotyping in SARS-CoV-2 convalescent plasma donors

Aim: More data is required regarding the association between HLA allele and red blood cell (RBC) antigen expression in regard to SARS-CoV-2 infection and COVID-19 susceptibility. Methods: ABO, RhD, 37 other RBC antigens and HLA-A, B, C, DRB1, DQB1 and DPB1 were determined using high throughput platforms in 90 Caucasian convalescent plasma donors. Results: The AB group was significantly increased (1.5×, p = 0.018) and some HLA alleles were found to be significantly overrepresented (HLA-B*44:02, C*05:01, DPB1*04:01, DRB1*04:01 and DRB1*07:01) or underrepresented (A*01:01, B51:01 and DPB1*04:02) in convalescent individuals compared with the local bone marrow registry population. Conclusion: Our study of infection-susceptible but non-hospitalized Caucasian COVID-19 patients contributes to the global understanding of host genetic factors associated with SARS-CoV-2 infection and severity.

An HLA map of the world: A comparison of HLA frequencies in 200 worldwide populations reveals diverse patterns for class I and class II

HLA frequencies show widespread variation across human populations. Demographic factors as well as selection are thought to have shaped HLA variation across continents. In this study, a worldwide comparison of HLA class I and class II diversity was carried out. Multidimensional scaling techniques were applied to 50 HLA-A and HLA-B (class I) as well as 13 HLA-DRB1 (class II) first-field frequencies in 200 populations from all continents. Our results confirm a strong effect of geography on the distribution of HLA class I allele groups, with principal coordinates analysis closely resembling geographical location of populations, especially those of Africa-Eurasia. Conversely, class II frequencies stratify populations along a continuum of differentiation less clearly correlated to actual geographic location. Double clustering analysis revealed finer intra-continental sub-clusters (e.g., Northern and Western Europe vs. South East Europe, North Africa and Southwest Asia; South and East Africa vs. West Africa), and HLA allele group patterns characteristic of these clusters. Ancient (Austronesian expansion) and more recent (Romani people in Europe) migrations, as well as extreme differentiation (Taiwan indigenous peoples, Native Americans), and interregional gene flow (Sámi, Egyptians) are also reflected by the results. Barrier analysis comparing D_ST and geographic location identified genetic discontinuities caused by natural barriers or human behavior explaining inter and intra-continental HLA borders for class I and class II. Overall, a progressive reduction in HLA diversity from African to Oceanian and Native American populations is noted. This analysis of HLA frequencies in a unique set of worldwide populations confirms previous findings on the remarkable similarity of class I frequencies to geography, but also shows a more complex development for class II, with implications for both human evolutionary studies and biomedical research.

Old age: the crown of life, our play's last act. Question and answers on older patients undergoing allogeneic hematopoietic cell transplantation

PURPOSE OF REVIEW

Several studies showed that age alone should not be used as an arbitrary parameter to exclude patients from allogeneic hematopoietic cell transplantation (HCT). The accessibility to allogeneic HCT programs for older patients with hematological diseases is growing up constantly. The Center for International Blood and Marrow Transplant Research has recently shown that over 30% of allogeneic HCT recipients are at least 60 years old and that nearly 4% are aged 70 or more. Historically, the use of allogeneic HCT among elderly patients has been limited by age restrictions, reflecting physicians' concerns regarding prohibitive transplant-related mortality and HCT-associated morbidity.

RECENT FINDINGS

The introduction of reduced intensity/toxicity conditioning regimens has allowed transplant Centers to carry out allogeneic HCT on patients previously considered not ideal candidates. The integration of specific risk scores could lead to better capture mental and physical frailties of older patients. Older adults less frequently have available medically fit siblings, able to donate, so, unrelated donors, familial haploidentical donors or umbilical cord blood grafts could potentially abrogate such a difficulty, allowing the curative potential of allogeneic HCT.

SUMMARY

The appropriate assessing of allogeneic HCT feasibility for elderly patients should be the resonate application of different clinical and biological principles.

Pediatric immune-mediated necrotizing myopathy

Immune-mediated necrotizing myopathy (IMNM) is a type of inflammatory myopathy. Most patients with IMNM produce anti-3-hydroxy-3-methylglutaryl coenzyme A reductase or anti-signal-recognition particle autoantibodies. IMNM is much rarer in children than in adults. We conducted this mini review focusing on pediatric IMNM to present current evidence regarding its epidemiology, clinical characteristics, diagnosis, and treatment. Our findings indicate that pediatric IMNM often causes severe muscle weakness and is refractory to corticosteroids alone. Furthermore, delayed diagnosis is common because of the clinicopathological similarity between IMNM and inherited myopathy. Raising awareness regarding pediatric IMNM may facilitate early diagnosis and effective treatment.