PIRCHE application major versions 3 and 4 lead to equivalent T cell epitope mismatch scores in solid organ and stem cell transplantation modules.

PIRCHE scores in organ and stem cell transplantation have been shown to correlate with increased risk of donor-specific HLA antibodies and graft-versus-host disease, respectively. With advancements of the PIRCHE application server, it is critical to compare the predicted scores with previous versions. This manuscript compares the newly introduced PIRCHE version 4.2 with its predecessor version 3.3, which was widely used in retrospective studies, using a virtual cohort of 10,000 transplant pairs. In the stem cell transplantation module, both versions yield identical results in 100% of the test population. In the solid organ module, 97% of the test population has identical PIRCHE scores. The deviating cases (3%) were attributed to refinements in the PIRCHE algorithm's specification. Furthermore, the magnitude of the difference is likely to be below the detection limit for clinical effects, confirming the equivalence in PIRCHE scores between versions 3.3 and 4.2.

Repeated local ellipsoid protrusion supplements HLA surface characterization.

Allorecognition of donor HLA is a major risk factor for long-term kidney graft survival. Although several molecular matching algorithms have been proposed that compare physiochemical and structural features of the donors' and recipients' HLA proteins in order to predict their compatibility, the exact underlying mechanisms are still not fully understood. We hypothesized that the ElliPro approach of single ellipsoid fitting and protrusion ranking lacks sensitivity for the characteristic shape of HLA molecules and developed a prediction pipeline named Snowball that is fitting smaller ellipsoids iteratively to substructures. Aggregated protrusion ranks of locally fitted ellipsoids were calculated for 712 publicly available HLA structures and 78 predicted structures using AlphaFold 2. Amino-acid sequence and protrusion ranks were used to train deep neural network predictors to infer protrusion ranks for all known HLA sequences. Snowball protrusion ranks appear to be more sensitive than ElliPro scores in fine parts of the HLA such as the helix structures forming the HLA binding groove in particular when the ellipsoids are fitted to substructures considering atoms within a 15 Å radius. A cloud-based web service was implemented based on amino-acid matching considering both protein- and position-specific surface area and protrusion ranks extending the previously presented Snowflake prediction pipeline.

Report from the extended HLA-DPA1 ~ promoter ~ HLA-DPB1 haplotype of the 18th international HLA and immunogenetics workshop.

The primary goal of the HLA-DPA1 ~ promoter ~ HLA-DPB1 haplotype component of the 18th IHIWS was to characterise the extended haplotypes within the HLA-DP region and survey the extent of genetic diversity in this region across human populations. In this report, we analysed single-nucleotide polymorphisms (SNPs) in 255 subjects from 6 different cohorts. The results from the HLA-DP haplotype component have validated findings from the initial pilot study. SNPs in this region were inherited in strong linkage, particularly HLA-DPA1, SNP-linked promoter haplotypes and motifs in exon 2 of HLA-DPB1. We reported 17 SNP-linked haplotypes in the promoter region. Together with HLA-DPA1 and HLA-DPB1 alleles, they formed 74 distinct extended HLA-DP haplotypes in 438 sequences. We also observed the presence of region-specific alleles and promoter haplotypes. Our approach involved phasing extended SNPs including promoter SNPs, HLA-DPA1 and HLA-DPB1 alleles, in a 22 kb region, GRCh38/hg38 (chr6:33,064,111-33,086,679), followed by clustering of these SNPs as one extended haplotype. This hierarchical clustering revealed four major clades, suggesting that haplotypes within each clade may have diverged from a common ancestral haplotype and undergone similar evolutionary processes. The correlation between HLA-DPA1 and the promoter region raises questions about the role of HLA-DPA1 antigen in the heterodimer. This finding requires validation on a larger sample size specifically designed for anthropological analysis. Nevertheless, the results from this study highlight the clinical potential of selecting better-matched donors for patients awaiting haematopoietic stem cell transplants from genetically overlapping groups that share common ancestral haplotypes.

Using cloud infrastructure to facilitate data collection and conversion of HLA diagnostic data for the 18th International HLA and Immunogenetics Workshop.

The International HLA and Immunogenetics Workshop (IHIW) is a recurring gathering of researchers, technologists and clinicians where participants contribute to collaborative projects with a variety of goals, and come to consensus on definitions and standards for representing HLA and immunogenic determinants. The collaborative and international nature of these workshops, combined with the multifaceted goals of several specific workshop components, necessitates the collection and curation of a wide assortment of data, as well as an adaptable platform for export and analysis. With the aim of ensuring data quality and creation of reusable datasets, specific standards and nomenclature conventions are continuously being developed, and are an integral part of IHIW. Here we present the 18th IHIW Database, a purpose-built and extensible cloud-based file repository and web application for collecting and analyzing project-specific data. This platform is based on open-source software and uses established HLA data standards and web technologies to facilitate de-centralized data repository ownership, reduce duplicated efforts, and promote continuity for future IHIWs.

Snowflake epitope matching correlates with child-specific antibodies during pregnancy and donor-specific antibodies after kidney transplantation.

Development of donor-specific human leukocyte antigen (HLA) antibodies (DSA) remains a major risk factor for graft loss following organ transplantation, where DSA are directed towards patches on the three-dimensional structure of the respective organ donor's HLA proteins. Matching donors and recipients based on HLA epitopes appears beneficial for the avoidance of DSA. Defining surface epitopes however remains challenging and the concepts underlying their characterization are not fully understood. Based on our recently implemented computational deep learning pipeline to define HLA Class I protein-specific surface residues, we hypothesized a correlation between the number of HLA protein-specific solvent-accessible interlocus amino acid mismatches (arbitrarily called Snowflake) and the incidence of DSA. To validate our hypothesis, we considered two cohorts simultaneously. The kidney transplant cohort (KTC) considers 305 kidney-transplanted patients without DSA prior to transplantation. During the follow-up, HLA antibody screening was performed regularly to identify DSA. The pregnancy cohort (PC) considers 231 women without major sensitization events prior to pregnancy who gave live birth. Post-delivery serum was screened for HLA antibodies directed against the child's inherited paternal haplotype (CSA). Based on the involved individuals' HLA typings, the numbers of interlocus-mismatched antibody-verified eplets (AbvEPS), the T cell epitope PIRCHE-II model and Snowflake were calculated locus-specific (HLA-A, -B and -C), normalized and pooled. In both cohorts, Snowflake numbers were significantly elevated in recipients/mothers that developed DSA/CSA. Univariable regression revealed significant positive correlation between DSA/CSA and AbvEPS, PIRCHE-II and Snowflake. Snowflake numbers showed stronger correlation with numbers of AbvEPS compared to Snowflake numbers with PIRCHE-II. Our data shows correlation between Snowflake scores and the incidence of DSA after allo-immunization. Given both AbvEPS and Snowflake are B cell epitope models, their stronger correlation compared to PIRCHE-II and Snowflake appears plausible. Our data confirms that exploring solvent accessibility is a valuable approach for refining B cell epitope definitions.

Snowflake: A deep learning-based human leukocyte antigen matching algorithm considering allele-specific surface accessibility.

Histocompatibility in solid-organ transplantation has a strong impact on long-term graft survival. Although recent advances in matching of both B-cell epitopes and T-cell epitopes have improved understanding of allorecognition, the immunogenic determinants are still not fully understood. We hypothesized that HLA solvent accessibility is allele-specific, thus supporting refinement of HLA B-cell epitope prediction. We developed a computational pipeline named Snowflake to calculate solvent accessibility of HLA Class I proteins for deposited HLA crystal structures, supplemented by constructed HLA structures through the AlphaFold protein folding predictor and peptide binding predictions of the APE-Gen docking framework. This dataset trained a four-layer long short-term memory bidirectional recurrent neural network, which in turn inferred solvent accessibility of all known HLA Class I proteins. We extracted 676 HLA Class-I experimental structures from the Protein Data Bank and supplemented it by 37 Class-I alleles for which structures were predicted. For each of the predicted structures, 10 known binding peptides as reported by the Immune Epitope DataBase were rendered into the binding groove. Although HLA Class I proteins predominantly are folded similarly, we found higher variation in root mean square difference of solvent accessibility between experimental structures of different HLAs compared to structures with identical amino acid sequence, suggesting HLA's solvent accessible surface is protein specific. Hence, residues may be surface-accessible on e.g. HLA-A*02:01, but not on HLA-A*01:01. Mapping these data to antibody-verified epitopes as defined by the HLA Epitope Registry reveals patterns of (1) consistently accessible residues, (2) only subsets of an epitope's residues being consistently accessible and (3) varying surface accessibility of residues of epitopes. Our data suggest B-cell epitope definitions can be refined by considering allele-specific solvent-accessibility, rather than aggregating HLA protein surface maps by HLA class or locus. To support studies on epitope analyses in organ transplantation, the calculation of donor-allele-specific solvent-accessible amino acid mismatches was implemented as a cloud-based web service.

The Value of Single-cell Technologies in Solid Organ Transplantation Studies.

Single-cell technologies open up new opportunities to explore the behavior of cells at the individual level. For solid organ transplantation, single-cell technologies can provide in-depth insights into the underlying mechanisms of the immunological processes involved in alloimmune responses after transplantation by investigating the role of individual cells in tolerance and rejection. Here, we review the value of single-cell technologies, including cytometry by time-of-flight and single-cell RNA sequencing, in the context of solid organ transplantation research. Various applications of single-cell technologies are addressed, such as the characterization and identification of immune cell subsets involved in rejection or tolerance. In addition, we explore the opportunities for analyzing specific alloreactive T- or B-cell clones by linking phenotype data to T- or B-cell receptor data, and for distinguishing donor- from recipient-derived immune cells. Moreover, we discuss the use of single-cell technologies in biomarker identification and risk stratification, as well as the remaining challenges. Together, this review highlights that single-cell approaches contribute to a better understanding of underlying immunological mechanisms of rejection and tolerance, thereby potentially accelerating the development of new or improved therapies to avoid allograft rejection.

The MHC class I MICA gene is a histocompatibility antigen in kidney transplantation.

The identity of histocompatibility loci, besides human leukocyte antigen (HLA), remains elusive. The major histocompatibility complex (MHC) class I MICA gene is a candidate histocompatibility locus. Here, we investigate its role in a French multicenter cohort of 1,356 kidney transplants. MICA mismatches were associated with decreased graft survival (hazard ratio (HR), 2.12; 95% confidence interval (CI): 1.45-3.11; P < 0.001). Both before and after transplantation anti-MICA donor-specific antibodies (DSA) were strongly associated with increased antibody-mediated rejection (ABMR) (HR, 3.79; 95% CI: 1.94-7.39; P < 0.001; HR, 9.92; 95% CI: 7.43-13.20; P < 0.001, respectively). This effect was synergetic with that of anti-HLA DSA before and after transplantation (HR, 25.68; 95% CI: 3.31-199.41; P = 0.002; HR, 82.67; 95% CI: 33.67-202.97; P < 0.001, respectively). De novo-developed anti-MICA DSA were the most harmful because they were also associated with reduced graft survival (HR, 1.29; 95% CI: 1.05-1.58; P = 0.014). Finally, the damaging effect of anti-MICA DSA on graft survival was confirmed in an independent cohort of 168 patients with ABMR (HR, 1.71; 95% CI: 1.02-2.86; P = 0.041). In conclusion, assessment of MICA matching and immunization for the identification of patients at high risk for transplant rejection and loss is warranted.

T-Cell Epitopes Shared Between Immunizing HLA and Donor HLA Associate With Graft Failure After Kidney Transplantation.

CD4+ T-helper cells play an important role in alloimmune reactions following transplantation by stimulating humoral as well as cellular responses, which might lead to failure of the allograft. CD4+ memory T-helper cells from a previous immunizing event can potentially be reactivated by exposure to HLA mismatches that share T-cell epitopes with the initial immunizing HLA. Consequently, reactivity of CD4+ memory T-helper cells toward T-cell epitopes that are shared between immunizing HLA and donor HLA could increase the risk of alloimmunity following transplantation, thus affecting transplant outcome. In this study, the amount of T-cell epitopes shared between immunizing and donor HLA was used as a surrogate marker to evaluate the effect of donor-reactive CD4+ memory T-helper cells on the 10-year risk of death-censored kidney graft failure in 190 donor/recipient combinations using the PIRCHE-II algorithm. The T-cell epitopes of the initial theoretical immunizing HLA and the donor HLA were estimated and the number of shared PIRCHE-II epitopes was calculated. We show that the natural logarithm-transformed PIRCHE-II overlap score, or Shared T-cell EPitopes (STEP) score, significantly associates with the 10-year risk of death-censored kidney graft failure, suggesting that the presence of pre-transplant donor-reactive CD4+ memory T-helper cells might be a strong indicator for the risk of graft failure following kidney transplantation.

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.

Peptides Derived From Mismatched Paternal Human Leukocyte Antigen Predicted to Be Presented by HLA-DRB1, -DRB3/4/5, -DQ, and -DP Induce Child-Specific Antibodies in Pregnant Women.

Predicted Indirectly ReCognizable Human Leukocyte Antigen (HLA) Epitopes (PIRCHE) are known to be a significant risk factor for the development of donor HLA-specific antibodies after organ transplantation. Most previous studies on PIRCHE limited their analyses on the presentation of the HLA-DRB1 locus, although HLA-DRB3/4/5, -DQ, and -DP are also known for presenting allopeptides to CD4+ T cells. In this study, we analyzed the impact of predicted allopeptides presented by these additional loci on the incidence of HLA-specific antibodies after an immunization event. We considered pregnancy as a model system of an HLA immunization and observed child-specific HLA antibody (CSA) development of 231 mothers during pregnancy by samples being taken at delivery. Our data confirm that PIRCHE presented by HLA-DRB1 along with HLA-DRB3/4/5, -DQ, and -DP are significant predictors for the development of CSA. Although there was limited peptidome overlap observed within the mothers' presenting HLA proteins, combining multiple presenting loci in a single predictor improved the model only marginally. Prediction performance of PIRCHE further improved when normalizing scores by the respective presenters' binding promiscuity. Immunogenicity analysis of specific allopeptides could not identify significant drivers of an immune response in this small cohort, suggesting confirmatory studies.

Specific amino acid patterns define split specificities of HLA-B15 antigens enabling conversion from DNA-based typing to serological equivalents.

The HLA-B15 typing by serological approaches defined the serological subgroups (or splits) B62, B63, B75, B76, B77 and B70 (B71 and B72). The scarcity of sera with specific anti-HLA antibodies makes the serological typing method difficult to discriminate a high variety of HLA antigens, especially between the B15 antigen subgroups. Advancements in DNA-based technologies have led to a switch from serological typing to high-resolution DNA typing methods. DNA sequencing techniques assign B15 specificity to all alleles in the HLA-B*15 allele group, without distinction of the serological split equivalents. However, the presence of antibodies in the patient defined as split B15 antigens urges the identification of HLA-B*15 allele subtypes of the donor, since the presence of donor-specific antibodies is an important contraindication for organ transplantation. Although the HLA dictionary comprises information regarding the serological subtypes of HLA alleles, there are currently 394 B15 antigens out of 516 in the IPD-IMGT/HLA database (3.38.0) without any assigned serological subtype. In this regard, we aimed to identify specific amino acid patterns for each B*15 serological split, in order to facilitate the assignment of B*15 alleles to serological equivalents after high-resolution molecular typing. As a result, serological specificities of 372/394 not yet assigned alleles could be predicted based on amino acid motifs. Furthermore, two new serological types were identified and added, B62-Bw4 and B71-Bw4.

Long-Read Nanopore Sequencing Validated for Human Leukocyte Antigen Class I Typing in Routine Diagnostics.

Matching of human leukocyte antigen (HLA) gene polymorphisms by high-resolution DNA sequence analysis is the gold standard for determining compatibility between patient and donor for hematopoietic stem cell transplantation. Single-molecule sequencing (PacBio or MinION) is a newest (third) generation sequencing approach. MinION is a nanopore sequencing platform, which provides long targeted DNA sequences. The long reads provide unambiguous phasing, but the initial high error profile prevented its use in high-impact applications, such as HLA typing for HLA matching of donor and recipient in the transplantation setting. Ongoing developments on instrumentation and basecalling software have improved the per-base accuracy of 1D2 nanopore reads tremendously. In the current study, two validation panels of samples covering 70 of the 71 known HLA class I allele groups were used to compare third field sequences obtained by MinION, with Sanger sequence-based typing showing a 100% concordance between both data sets. In addition, the first validation panel was used to set the acceptance criteria for the use of MinION in a routine setting. The acceptance criteria were subsequently confirmed with the second validation panel. In summary, the present study describes validation and implementation of nanopore sequencing HLA class I typing method and illustrates that nanopore sequencing technology has advanced to a point where it can be used in routine diagnostics with high accuracy.