Publications

HLA (HLA) are a major barrier to transplant success, as HLA-A and -B molecules are principal ligands for T-cells, and HLA-C for Killer cell Immunoglobulin-like Receptors (KIR), directing Natural Killer (NK) cell function. HLA-C molecules are designated “C1” or “C2” ligands based on residues 77 and 80, which determine the NK cell responses. Here, we investigated donor/recipient HLA-C mismatch associations with the development of chronic lung allograft dysfunction (CLAD) following lung transplantation (LTx). 310 LTx donor/recipient pairs were Next Generation Sequenced and assessed for C1 and C2 allotypes. PIRCHE scores were used to quantify HLA mismatching between donor/recipients at amino acid level and stratify recipients into low, moderate or highly mismatched groups (n = 103–104). Associations between C ligands and freedom from CLAD was assessed with Cox regression models and survival curves. C2/C2 recipients (n = 42) had less CLAD than those with C1/C1 (n = 138) or C1/C2 genotypes (n = 130) (p < 0.05). Incidence of CLAD was lower in C2/C2 recipients receiving a mismatched C1/C1 allograft (n = 14), compared to matched (n = 8) or heterozygous (n = 20) allografts. Furthermore, 80% of these recipients (C2/C2 recipients receiving C1/C1 transplants) remained CLAD-free for 10 years post-LTx. Recipients with higher HLA-C mismatching had less CLAD (p < 0.05) an observation not explained by linkage disequilibrium with other HLA loci. Our data implicates a role for HLA-C in CLAD development. HLA-C mismatching was not detrimental to LTx outcome, but potentially beneficial, representing a paradigm shift in assessing donor/recipient matching. This may inform better selection of donor/recipient pairs and potentially more targeted approaches to treating CLAD.

Background Optimizing graft survival and diminishing human leukocyte antigen (HLA) sensitization are essential for pediatric kidney transplant recipients. More precise HLA matching predicting epitope mismatches could reduce alloreactivity. We investigated the association of predicted HLA B- and T-cell molecular mismatches with the formation of de novo donor-specific antibodies, HLA antibodies, rejection, and graft survival. Methods Forty-nine pediatric kidney transplant recipients transplanted from 2009 to 2020 were retrospectively studied. Donors and recipients were high-resolution HLA typed, and recipients were screened for HLA antibodies posttransplant. HLA-EMMA (HLA Epitope MisMatch Algorithm) and PIRCHE-II (Predicted Indirectly ReCognizable HLA Epitopes) predicted the molecular mismatches. The association of molecular mismatches and the end-points was explored with logistic regression. Results Five recipients (11%) developed de novo donor-specific antibodies. All five had de novo donor-specific antibodies against HLA class II, with four having HLA-DQ antibodies. We found no associations between PIRCHE-II or HLA-EMMA with de novo donor-specific antibodies, HLA sensitization, graft loss, or rejection. However, we did see a tendency towards an increased odds ratio in PIRCHE-II predicting de novo donor-specific antibodies formation, with an odds ratio of 1.12 (95% CI: 0.99; 1.28) on HLA class II. Conclusion While the study revealed no significant associations between the number of molecular mismatches and outcomes, a notable trend was observed – indicating a reduced risk of dnDSA formation with improved molecular match. It is important to acknowledge, however, that the modest population size and limited observed outcomes preclude us from making definitive conclusions.

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.

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.

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.

Background Recent advances in hardware and software enabled the use of artificial intelligence (AI) algorithms for analysis of complex data in a wide range of daily-life use cases. We aim to explore the benefits of applying AI to a specific use case in transplant nephrology: risk prediction for severe posttransplant events. For the first time, we combine multinational real-world transplant data, which require specific legal and technical protection measures. Objective The German-Canadian NephroCAGE consortium aims to develop and evaluate specific processes, software tools, and methods to (1) combine transplant data of more than 8000 cases over the past decades from leading transplant centers in Germany and Canada, (2) implement specific measures to protect sensitive transplant data, and (3) use multinational data as a foundation for developing high-quality prognostic AI models. Methods To protect sensitive transplant data addressing the first and second objectives, we aim to implement a decentralized NephroCAGE federated learning infrastructure upon a private blockchain. Our NephroCAGE federated learning infrastructure enables a switch of paradigms: instead of pooling sensitive data into a central database for analysis, it enables the transfer of clinical prediction models (CPMs) to clinical sites for local data analyses. Thus, sensitive transplant data reside protected in their original sites while the comparable small algorithms are exchanged instead. For our third objective, we will compare the performance of selected AI algorithms, for example, random forest and extreme gradient boosting, as foundation for CPMs to predict severe short- and long-term posttransplant risks, for example, graft failure or mortality. The CPMs will be trained on donor and recipient data from retrospective cohorts of kidney transplant patients. Results We have received initial funding for NephroCAGE in February 2021. All clinical partners have applied for and received ethics approval as of 2022. The process of exploration of clinical transplant database for variable extraction has started at all the centers in 2022. In total, 8120 patient records have been retrieved as of August 2023. The development and validation of CPMs is ongoing as of 2023. Conclusions For the first time, we will (1) combine kidney transplant data from nephrology centers in Germany and Canada, (2) implement federated learning as a foundation to use such real-world transplant data as a basis for the training of CPMs in a privacy-preserving way, and (3) develop a learning software system to investigate population specifics, for example, to understand population heterogeneity, treatment specificities, and individual impact on selected posttransplant outcomes. International Registered Report Identifier (IRRID) DERR1-10.2196/48892

Molecular matching is a new approach for virtual histocompatibility testing in organ transplantation. The aim of our study was to analyze whether the risk for de novo donor‐specific HLA antibodies (dnDSA) after lung transplantation (LTX) can be predicted by molecular matching algorithms (MMA) and their combination. In this retrospective study we included 183 patients undergoing LTX at our center from 2012–2020. We monitored dnDSA development for 1 year. Eplet mismatches (epMM) using HLAMatchmaker were calculated and highly immunogenic eplets based on their ElliPro scores were identified. PIRCHE‐II scores were calculated using PIRCHE‐II algorithm (5‐ and 11‐loci). We compared epMM and PIRCHE‐II scores between patients with and without dnDSA using t‐test and used ROC‐curves to determine optimal cut‐off values to categorize patients into four groups. We used logistic regression with AIC to compare the predictive value of PIRCHE‐II, epMM, and their combination. In total 28.4% of patients developed dnDSA ( n  = 52), 12.5% class I dnDSA ( n  = 23), 24.6% class II dnDSA ( n  = 45), and 8.7% both class II and II dnDSA ( n  = 16). Mean epMMs ( p ‐value = 0.005), mean highly immunogenic epMMs ( p ‐value = 0.003), and PIRCHE‐II (11‐loci) ( p  = 0.01) were higher in patients with compared to without class II dnDSA. Patients with highly immunogenic epMMs above 30.5 and PIRCHE‐II 11‐loci above 560.0 were more likely to develop dnDSA (31.1% vs. 14.8%, p ‐value = 0.03). The logistic regression model including the grouping variable showed the best predictive value. MMA can support clinicians to identify patients at higher or lower risk for developing class II dnDSA and might be helpful tools for immunological risk assessment in LTX patients.

Purpose This study retrospectively investigated the association between the level of human leukocyte antigen (HLA) mismatches (MMs), direction of disparities and differences at particular HLA locus on clinical outcomes of hematopoietic stem cell transplantation (HSCT). Investigated outcomes were overall survival (OS) and disease-free survival (DFS), graft-versus-host disease (GvHD), relapse and non-relapse mortality (NRM). Patients and methods Study cohort included 108 adult patients transplanted between 2011 and 2021 and their 9/10 mismatched unrelated donors (MMUD). All individuals were typed for HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 loci using Polymerase Chain Reaction-Sequence Specific Primers, PCR-Sequence Based Typing and Next-Generation Sequencing. All statistical analyses were done in the MedCalc software, version 19.2.6. Results Patients with MMs at HLA-B locus demonstrated worse OS (P ​= ​0.0440, HR ​= ​2.00, n ​= ​20). Absence of HLA-DRB5 was associated with a higher incidence of GvHD (P ​= ​0.0112, HR ​= ​1.93, n ​= ​67). A lower incidence of GvHD was observed in patients with HLA class II MMs compared to patients with HLA class I MMs (P ​= ​0.0166, HR ​= ​1.94, n ​= ​29). Finally, analysis of PIRCHE score (PS) impact revealed that patients with HLA class II PS ​> ​10 in GvH direction showed higher incidence of GvHD compared to patients with HLA class II PS ​< ​10 (P ​= ​0.0073, HR ​= ​2.01, n ​= ​55). Conclusion Obtained results undisputedly indicate the necessity to further investigate this matter on a larger patient group, with focus on specific HLA alleles to define precisely priority criteria for selecting the best donor for all patients, thus improving the outcome of HSCT with an MMUD.

Abstract Background An increased incidence of subsequent solid cancers (SSCs) has been reported in long‐term survivors of allogeneic hematopoietic stem cell transplantation (allo‐HSCT), and SSC is associated with inferior mortality and morbidity. Previous studies showed that the incidence of SSC is significantly higher in those who underwent allo‐HSCT from HLA‐mismatched donors, suggesting that persistent alloimmunity may predispose patients to SSCs. It was recently reported that, in a cohort of patients who received allo‐HSCT from an unrelated donor matched at HLA‐A, ‐B, ‐C, ‐DRB1/3/4/5, and ‐DQB1 loci, HLA‐DPB1 alloimmunity determined by high mismatched eplets (MEs) and Predicted Indirectly Recognizable HLA Epitopes (PIRCHE) score (PS), was associated with relapse protection and increased risk of acute graft‐versus‐host disease (GVHD). Methods In the present study, the impact of HLA‐DPB1 alloimmunity assessed by molecular mismatch algorithms on the development of SSCs in a cohort of 1514 patients who underwent allo‐HSCT for hematologic malignancies was further investigated. ME load at the HLA‐DPB1 locus was measured using the HLAMatchmaker module incorporated in HLA Fusion software, and the PS for mismatched HLA‐DPB1 was calculated using the HSCT module from the PIRCHE online matching service. Results In multivariable analysis after adjusting for baseline risk factors, higher ME, PS‐I, and PS‐II in the GVH direction, but not in the HVG direction, were associated with an increased risk of SSCs (ME: subdistribution hazard ratio [SHR] 1.58, p = .01; PS‐I: SHR 1.59, p = .009; PS‐II: SHR 1.71, p = .003). In contrast, nonpermissive HLA‐DPB1 mismatches defined by the conventional T‐cell epitope algorithm were not predictive of the risk of SSCs. Moreover, posttransplant cyclophosphamide‐based GVHD prophylaxis was associated with a reduced risk of subsequent solid cancer (SHR 0.34, p = .021). Conclusions These results indicate for the first time that increased GVH alloreactivity could contribute to the development of SSCs in allo‐HSCT survivors. , HLA‐DPB1 graft‐versus‐host (GVH) alloreactivity assessed by molecular mismatch methods is significantly associated with the higher risk of subsequent solid cancer in survivors of allogeneic hematopoietic stem cell transplantation (allo‐HSCT). Posttransplant cyclophosphamide–based GVH disease prophylaxis that downregulates the GVH alloresponse is associated with a lower risk of SSC after allo‐HSCT.

Abstract Background Before the availability of mRNA vaccines, many transplant centers chose to significantly reduce maintenance immunosuppression in kidney transplant recipients (KTRs) with SARS‐CoV‐2 infection. The extent to which this increases the risk of allosensitization is unclear. Methods In this observational cohort study, we analyzed 47 KTRs from March 2020 to February 2021 who underwent substantial reduction of maintenance immunosuppression during SARS‐CoV‐2 infection. KTRs were followed at 6 and 18 months concerning the development of de novo donor‐specific anti‐HLA (human leukocyte antigen) antibodies (DSA). The HLA‐derived epitope mismatches were calculated using the predicted indirectly recognizable HLA‐epitopes (PIRCHE‐II) algorithm. Results In total, 14 of 47 KTRs (30%) developed de novo HLA antibodies after the reduction of maintenance immunosuppression. KTRs with higher total PIRCHE‐II scores and higher PIRCHE‐II scores for the HLA‐DR locus were more likely to develop de novo HLA antibodies ( p = .023, p = .009). Furthermore, 4 of the 47 KTRs (9%) developed de novo DSA after reduction of maintenance immunosuppression, which were exclusively directed against HLA‐class II antigens and also showed higher PIRCHE‐II scores for HLA‐class II. The cumulative mean fluorescence intensity of 40 KTRs with preexisting anti‐HLA antibodies and 13 KTRs with preexisting DSA at the time of SARS‐CoV‐2 infection remained stable after the reduction of maintenance immunosuppression ( p = .141; p = .529). Conclusions Our data show that the HLA‐derived epitope mismatch load between donor and recipient influences the risk of de novo DSA development when immunosuppression is temporarily reduced. Our data further suggest that reduction in immunosuppression should be made more cautiously in KTRs with high PIRCHE‐II scores for HLA‐class II antigens. image

Human leukocyte antigen (HLA) molecular mismatch is a powerful biomarker of rejection. Few studies have explored its use in assessing rejection risk in heart transplant recipients. We tested the hypothesis that a combination of HLA Epitope Mismatch Algorithm (HLA-EMMA) and Predicted Indirectly Recognizable HLA Epitopes (PIRCHE-II) algorithms can improve risk stratification of pediatric heart transplant recipients. Class I and II HLA genotyping were performed by next-generation sequencing on 274 recipient/donor pairs enrolled in the Clinical Trials in Organ Transplantation in Children (CTOTC). Using high-resolution genotypes, we performed HLA molecular mismatch analysis with HLA-EMMA and PIRCHE-II, and correlated these findings with clinical outcomes. Patients without pre-formed donor specific antibody (DSA) (n=100) were used for correlations with post-transplant DSA and antibody mediated rejection (ABMR). Risk cut-offs were determined for DSA and ABMR using both algorithms. HLA-EMMA cut-offs alone predict the risk of DSA and ABMR; however, if used in combination with PIRCHE-II, the population could be further stratified into low-, intermediate-, and high-risk groups. The combination of HLA-EMMA and PIRCHE-II enables more granular immunological risk stratification. Intermediate-risk cases, like low-risk cases, are at a lower risk of DSA and ABMR. This new way of risk evaluation may facilitate individualized immunosuppression and surveillance.

The process and evolution of an organ transplant procedure has evolved in terms of the prevention of immunological rejection with the improvement in the determination of immune response genes. These techniques include considering more important genes, more polymorphism detection, more refinement of the response motifs, as well as the analysis of epitopes and eplets, its capacity to fix complement, the PIRCHE algorithm and post-transplant monitoring with promising new biomarkers that surpass the classic serum markers such as creatine and other similar parameters of renal function. Among these new biomarkers, we analyze new serological, urine, cellular, genomic and transcriptomic biomarkers and computational prediction, with particular attention to the analysis of donor free circulating DNA as an optimal marker of kidney damage.

The development of systems biology represents an immense breakthrough in our ability to perform translational research and deliver personalized and precision medicine. A multidisciplinary approach in combination with use of novel techniques allows for the extraction and analysis of vast quantities of data even from the volume and source limited samples that can be obtained from human subjects. Continued advances in microfluidics, scalability and affordability of sequencing technologies, and development of data analysis tools have made the application of a multi-omics, or systems, approach more accessible for use outside of specialized centers. The study of alloimmune and protective immune responses after solid organ transplant offers innumerable opportunities for a multi-omics approach, however, transplant immunology labs are only just beginning to adopt the systems methodology. In this review, we focus on advances in biological techniques and how they are improving our understanding of the immune system and its interactions, highlighting potential applications in transplant immunology. First, we describe the techniques that are available, with emphasis on major advances that allow for increased scalability. Then, we review initial applications in the field of transplantation with a focus on topics that are nearing clinical integration. Finally, we examine major barriers to adapting these methods and discuss potential future developments.

Introduction Kidney transplantation is the optimal treatment in end-stage kidney disease, but de-novo donor specific antibody development continues to negatively impact patients undergoing kidney transplantation. One of the recent advances in solid organ transplantation has been the definition of molecular mismatching between donors and recipients’ Human Leukocyte Antigens (HLA). While not fully integrated in standard clinical care, cumulative molecular mismatch at the level of eplets (EMM) as well as the PIRCHE-II score have shown promise in predicting transplant outcomes. In this manuscript, we sought to study whether certain T-cell molecular mismatches (TcEMM) were highly predictive of death-censored graft failure (DCGF). Methods We studied a retrospective cohort of kidney donor:recipient pairs from the Scientific Registry of Transplant Recipients (2000-2015). Allele level HLA-A, B, C, DRB1 and DQB1 types were imputed from serologic types using the NMDP algorithm. TcEMMs were then estimated using the PIRCHE-II algorithm. Multivariable Accelerated Failure Time (AFT) models assessed the association between each TcEMM and DCGF. To discriminate between TcEMMs most predictive of DCGF, we fit multivariable Lasso penalized regression models. We identified co-expressed TcEMMs using weighted correlation network analysis (WGCNA). Finally, we conducted sensitivity analyses to address PIRCHE and IMGT/HLA version updates. Results A total of 118,309 donor:recipient pairs meeting the eligibility criteria were studied. When applying the PIRCHE-II algorithm, we identified 1,935 distinct TcEMMs at the population level. A total of 218 of the observed TcEMM were independently associated with DCGF by AFT models. The Lasso penalized regression model with post selection inference identified a smaller subset of 86 TcEMMs (56 and 30 TcEMM derived from HLA Class I and II, respectively) to be highly predictive of DCGF. Of the observed TcEMM, 38.14% appeared as profiles of highly co-expressed TcEMMs. In addition, sensitivity analyses identified that the selected TcEMM were congruent across IMGT/HLA versions. Conclusion In this study, we identified subsets of TcEMMs highly predictive of DCGF and profiles of co-expressed mismatches. Experimental verification of these TcEMMs determining immune responses and how they may interact with EMM as predictors of transplant outcomes would justify their consideration in organ allocation schemes and for modifying immunosuppression regimens.

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.

Abstract The development of donor‐specific antibodies (DSA) has a significant impact on graft outcome in solid organ transplantation. Mismatched HLAs are recognized directly and indirectly by the recipient immune system. Both pathways occur in parallel and result in the generation of plasma cells, DSA, cytotoxic and T helper lymphocytes. Here, we present the results of an analysis of the epitope load of mismatched HLAs in a cohort of 220 lung transplant recipients using two in silico algorithms, HLAMatchmaker and PIRCHE‐II (Predicted Indirectly ReCognizable HLA Epitopes). De novo DSA (dnDSA) were detected by single antigen bead assays. The percentage of recipients who developed dnDSA was significantly higher in the group of patients who received lung transplants with a mismatching score above the detected threshold than in the group of patients who received lung transplants with a mismatching score below the threshold. In a multivariate Cox proportional hazard analysis, the PIRCHE‐II score appeared to be a superior predictor of dnDSA formation. In addition, PIRCHE‐II technology was shown to be useful in predicting separate dnDSA1 and dnDSA2 formation. We conclude that both algorithms can be used for the evaluation of the epitope load of mismatched HLAs and the prediction of DSA development in lung transplant recipients.

The role of the indirect T-cell recognition pathway of allorecognition in acute T cell-mediated rejection (aTCMR) is not well defined. The amount of theoretical T-cell epitopes available for indirect allorecognition can be quantified for donor-recipient combinations by the Predicted Indirectly ReCognizable HLA Epitopes algorithm (PIRCHE-II). The PIRCHE-II score was calculated for 688 donor kidney-recipient combinations and associated with the incidence of first-time diagnosed cases of TCMR. A diagnosis of TCMR was made in 182 cases; 121 cases of tubulo-interstitial rejection cases (79 cases of borderline TCMR, 42 cases of TCMR IA-B) and 61 cases of vascular TCMR (TCMR II-III). The PIRCHE-II score for donor HLA-DR/DQ (PIRCHE-II DR/DQ) was highly associated with vascular rejection. At one year after transplantation, the cumulative percentage of recipients with a vascular rejection was 12.7%, 8.6% and 2.1% within respectively the high, medium and low tertile of the PIRCHE-II DR/DQ score (p<0.001). In a multivariate regression analysis this association remained significant (p<0.001 for PIRCHE-II DR/DQ tertiles). The impact of a high PIRCHE-II DR/DQ score was mitigated by older recipient age and a living donor kidney. In conclusion, indirect antigen presentation of donor HLA-peptides may significantly contribute to the risk for acute vascular rejection.

Background Indication biopsies for deterioration of kidney allograft function often require follow-up biopsies to assess treatment response or lack of improvement. Immune-mediated injury, namely borderline rejection (BLR), T-cell mediated rejection (TCMR), or antibody-mediated rejection (ABMR), results from preformed or de novo alloreactivity due to donor and recipient HLA-mismatches. The impact of HLA-mismatches on alloreactivity is determined by highly immunogenic HLA-epitopes. Methods We analyzed 123 kidney transplant recipients (KTRs) from 2009 to 2019 who underwent a first indication and a follow-up biopsy. KTRs were divided into three groups according to the first biopsy: No rejection (NR)/BLR (n=68); TCMR (n=21); ABMR (n=34). The HLA-derived epitope-mismatches were calculated using the Predicted Indirectly Recognizable HLA-Epitopes (PIRCHE-II) algorithm. Results Group NR/BLR: KTRs with higher total PIRCHE-II scores were more likely to develop TCMR in the follow-up biopsy (p=0.031). Interestingly, these differences were significant for both HLA-class I- (p=0.017) and HLA-class II-derived (p=0.017) PIRCHE-II scores. Group TCMR: KTRs with ongoing TCMR in the follow-up biopsy were more likely to show higher total PIRCHE-II scores (median 101.50 vs. 74.00). Group ABMR: KTRs with higher total PIRCHE-II scores were more likely to show an increase in the microvascular inflammation score in the follow-up biopsy. This difference was more pronounced for the HLA-class II-derived PIRCHE-II scores (median 70.00 vs. 31.76; p=0.086). Conclusions PIRCHE-II scores may prove useful as a biomarker to predict the histopathological changes of immune-related injury from a first indication to a follow-up biopsy. This immunological risk stratification may contribute to individualized treatment strategies.

Abstract For liver transplantations, human leukocyte antigen (HLA) matching is not routinely performed because observed effects have been inconsistent. Nevertheless, long‐term liver transplantation outcomes remain suboptimal. The availability of a more precise HLA‐matching algorithm, Predicted Indirectly Recognizable HLA Epitopes II (PIRCHE‐II), now enables robust assessment of the association between HLA matching and liver transplantation outcomes. We performed a single‐center retrospective cohort study of 736 liver transplantation patients. Associations between PIRCHE‐II and HLAMatchmaker scores and mortality, graft loss, acute and chronic rejection, ischemic cholangiopathy, and disease recurrence were evaluated with Cox proportional hazards models. Associations between PIRCHE‐II with 1‐year, 2‐year, and 5‐year outcomes and severity of acute rejection were assessed with logistic and linear regression analyses, respectively. Subgroup analyses were performed for autoimmune and nonautoimmune indications, and patients aged 30 years and younger, and older than 30 years. PIRCHE‐II and HLAMatchmaker scores were not associated with any of the outcomes. However, patients who received transplants for autoimmune disease showed more acute rejection and graft loss, and these risks negatively associated with age. Rhesus mismatch more than doubled the risk of disease recurrence. Moreover, PIRCHE‐II was inversely associated with graft loss in the subgroup of patients aged 30 years and younger with autoimmune indications. The absence of associations between PIRCHE‐II and HLAMatchmaker scores and the studied outcomes refutes the need for HLA matching for liver (stem cell) transplantations for nonautoimmune disease. For autoimmune disease, the activated immune system seems to increase risks of acute rejection and graft loss. Our results may suggest the benefits of transplantations with rhesus matched but PIRCHE‐II mismatched donor livers.

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.

Abstract Background & Aims Low calcineurin inhibitor (CNI) levels expose liver transplant recipients to rejection episodes and potentially to antibody‐mediated rejection. There are little data on the impact of CNI‐free immunosuppression on de novo donor‐specific HLA antibody (dnDSA) development. Here we evaluated the prevalence of dnDSA in liver transplant recipients on CNI‐free maintenance regimens and their associations with histopathological abnormalities of allografts. Methods Seven hundred and twenty‐seven liver transplant recipients underwent a first liver transplant between 2000 and 2018 in three French transplant centres and had protocolized follow‐up with dnDSA screening and allograft biopsy 1, 5 and 10 years after transplantation. Results CNIs were withdrawn in 166 (22.8%) patients with or without conversion to mammalian target of rapamycin inhibitors and/or maintenance with mycophenolic acid. DSA were present after withdrawal in 30.1% (50/166) patients on CNI‐free immunosuppression compared with 16% (90/561) on CNI maintenance therapy ( p < 0.001). The cumulative incidence of dnDSA 10 years after transplant was 20% in the CNI group versus 28% in the CNI‐free group ( p < 0.01). dnDSAs were associated with histological graft abnormalities (significant allograft fibrosis or rejection) (HR 2.24, 95% CI 1.2–4.1; p = 0.01). In univariate Cox regression analysis, being on a CNI‐free regimen did not impact graft histology. Conclusions Patients on a CNI‐free IS regimen have a higher prevalence of dnDSA than patients on a standard IS regimen. dnDSAs but not CNI‐free immunosuppression were associated with abnormal allograft histology.

Abstract Introduction We investigated the association of HLA on clinical outcomes in our cohort of patients in the haplo‐HSCT program using the HLAMatchmaker (EM) and PIRCHE score (PS) algorithms. Methods The group comprised 64 patients (male = 35–54.7%, female 29–45.3%; median age 43 years) and their related haplo‐HSCT donors (male = 30–46.9%, female 34–53.1%). HLA‐A/B/C/DRB1/DQB1/DPB1 loci were analyzed. Results Multivariate analysis of the association between different HLA or patient/donor‐related parameters and clinical outcome revealed the following associations with statistical significance: GvHD and HLA class I PS in the GvH direction ( p = .0420) and relapse with diagnosis ( p = .0163). For OS, the only variable showing a tendency of association was the source of HSCT ( p = .0965). Conclusion Combined results of univariate and multivariate analysis suggest that the patients awaiting the selection of the best haplo‐HSCT donor could benefit the most from the combination of all three approaches, in cases when a suitable donor can be chosen from a number of potential donors.

Background The diagnosis of borderline rejection (BLR) ranges from mild inflammation to clinically significant TCMR and is associated with an increased risk of allograft dysfunction. Currently, there is no consensus regarding its treatment due in part to a lack of biomarkers to identify cases with increased risk for immune-mediated injury. Methods We identified 60 of 924 kidney transplant recipients (KTRs) with isolated and untreated BLR. We analyzed the impact of predicted indirectly recognizable HLA epitopes (PIRCHE) score on future rejection, de novo DSA development, and recovery to baseline allograft function. Additionally, we compared the outcomes of different Banff rejection phenotypes. Results Total PIRCHE scores were significantly higher in KTRs with BLR compared to the entire study population (p=0.016). Among KTRs with BLR total PIRCHE scores were significantly higher in KTRs who developed TCMR/ABMR in follow-up biopsies (p=0.029). Notably, the most significant difference was found in PIRCHE scores for the HLA-A locus (p=0.010). PIRCHE scores were not associated with the development of de novo DSA or recovery to baseline allograft function among KTRs with BLR (p>0.05). However, KTRs under cyclosporine-based immunosuppression were more likely to develop de novo DSA (p=0.033) than those with tacrolimus, whereas KTRs undergoing retransplantation were less likely to recover to baseline allograft function (p=0.003). Conclusions High PIRCHE scores put KTRs with BLR at an increased risk for future TCMR/ABMR and contribute to improved immunological risk stratification. The benefit of anti-rejection treatment, however, needs to be evaluated in future studies.

Abstract De novo donor‐specific human leucocyte antigen (HLA) antibodies (dnDSA) are associated with increased risk of rejection and mortality in solid organ transplantation. Such dnDSA is produced in some recipients upon allorecognition of mismatched HLA post‐transplant. HLA matching is not currently considered in the allocation of deceased donor hearts and lungs and pre‐transplant immunological risk stratification is based entirely on the mean fluorescence intensity (MFI) of circulating donor‐directed HLA antibodies. HLA epitope‐based matching tools predict B‐cell or T‐cell HLA epitopes that are present in the donor's HLA but absent in the recipient's HLA. We hypothesized that patients with higher epitope mismatch loads would be at increased risk of dnDSA development. We retrospectively analysed 73 heart and/or lung transplant recipients who were tested for DSA between 2015 and 2020. HLAMatchmaker, PIRCHE‐II and HLA epitope mismatch algorithm (HLA‐EMMA) were used to calculate eplet mismatch (EpMM) loads, T‐cell epitope mismatch (TEpMM) loads and solvent accessible amino acid mismatch (SAMM) loads, respectively. Multivariate analyses showed that HLA‐EMMA was the only tool with a significant association between the total score for all HLA loci and dnDSA production [odds ratio (OR) 1.021, 95% confidence interval (CI) 1.003–1.042, p = .0225] though this increased risk was marginal. The majority of dnDSA were directed against HLA‐DQ and patients with higher HLA‐DQ TEpMM loads (OR = 1.008, CI = 1.002–1.014, p = .007), and HLA‐DR+DQ SAMM loads (OR = 1.035, CI = 1.010–1.064, p = .0077) were most at risk of producing dnDSA. We also showed that patients with a risk epitope within the HLA molecule encoded for by HLA‐DQA1*05 + HLA‐DQB1*02/03:01 were significantly more likely to produce dnDSA. The use of HLA epitope‐based matching tools could be used for cardiothoracic transplant risk stratification to enable early intervention and monitoring of patients at increased risk of producing dnDSA.

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.

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.

Abstract HLA compatibility is a key factor for survival after unrelated hematopoietic stem cell transplantation (HSCT). HLA-A, -B, -C, -DRB1, and -DQB1 are usually matched between donor and recipient. By contrast, HLA-DPB1 mismatches are frequent, although it is feasible to optimize donor selection and DPB1 matching with prospective typing. Because classical DPB1 allele mismatches are often unavoidable, however, several biological models have been developed to predict the optimal DPB1 mismatch combination for less graft-versus-host disease (GVHD) and better overall survival. In 909 recipient/donor pairs, we analyzed the role of 3 biological models: T-cell epitopes (TCEs) based on the immunogenicity of DPB1, cell surface expression of DPB1 molecules based on a single-nucleotide polymorphism located in the 3′ untranslated region, and the Predicted Indirectly ReCognizable HLA Epitopes (PIRCHE) model based on the presentation of allogeneic peptides derived from mismatched HLA, compared with the classical allele mismatch. Matching for both DPB1 alleles remains the best option to prevent acute GVHD. In the situation of one DPB1 allele mismatch, the donor associated with the lowest acute GVHD risks is mismatched for an allele with a low expression profile in the recipient, followed by a permissive TCE3/4 mismatch and/or the absence of PIRCHE II potential against the recipient. In the context of 2 DPB1 mismatches, the same considerations apply for a permissive TCE3/4 mismatch and no PIRCHE II. By combining the biological models, the most favorable DPB1 constellation can be defined. This approach will help optimize donor selection and improve post-HSCT complications and patient prognosis.

HLA-DPB1 mismatches between donor and recipient are commonly seen in allogeneic hematopoietic stem cell transplantation from an unrelated donor. HLA-DPB1 mismatch, conventionally determined by the similarity of the T-cell epitope (TCE), is associated with an increased risk of acute graft-versus-host disease (GVHD) and a decreased risk of disease relapse. We investigated the clinical impact of HLA-DPB1 molecular mismatch quantified by mismatched eplets (ME) and the Predicted Indirectly Recognizable HLA Epitopes Score (PS) in a cohort of 1,514 patients receiving hematopoietic stem cell transplants from unrelated donors matched at HLA-A, -B, -C, -DRB1/3/4/5, and - DQB1 loci. HLA-DPB1 alloimmunity in the graft-versus-host direction, determined by high graft-versus-host ME/PS, was associated with a reduced risk of relapse (hazard ratio [HR]=0.83, P=0.05 for ME) and increased risk of grade 2-4 acute GVHD (HR=1.44, P<0.001 for ME), whereas high host-versus-graft ME/PS was only associated with an increased risk of grade 2-4 acute GVHD (HR=1.26, P=0.004 for ME). Notably, in the permissive mismatch subgroup classified by TCE grouping, high host-versus-graft ME/PS was associated with an increased risk of relapse (HR=1.36, P=0.026 for ME) and grade 2-4 acute GVHD (HR=1.43, P=0.003 for PS-II). Decision curve analysis showed that graftversus- host ME outperformed other models and provided the best clinical net benefit for the modification of acute GVHD prophylaxis regimens in patients with a high risk of developing clinically significant acute GVHD. In conclusion, molecular assessment of HLA-DPB1 mismatch enables separate prediction of host-versus-graft or graft-versus-host alloresponse quantitatively and allows further refinement of HLA-DPB1 permissiveness as defined by conventional TCE grouping.

The EuroTransplant Kidney Allocation System (ETKAS) aims at allocating organs to patients on the waiting list fairly whilst optimizing HLA match grades. ETKAS currently considers the number of HLA-A, -B, -DR mismatches. Evidently, epitope matching is biologically and clinically more relevant. We here executed ETKAS-based computer simulations to evaluate the impact of epitope matching on allocation and compared the strategies. A virtual population of 400,000 individuals was generated using the National Marrow Donor Program (NMDP) haplotype frequency dataset of 2011. Using this population, a waiting list of 10,400 patients was constructed and maintained during simulation, matching the 2015 Eurotransplant Annual Report characteristics. Unacceptable antigens were assigned randomly relative to their frequency using HLAMatchmaker. Over 22,600 kidneys were allocated in 10 years in triplicate using Markov Chain Monte Carlo simulations on 32-CPU-core cloud-computing instances. T-cell epitopes were calculated using the www.pirche.com portal. Waiting list effects were evaluated against ETKAS for five epitope matching scenarios. Baseline simulations of ETKAS slightly overestimated reported average HLA match grades. The best balanced scenario maintained prioritisation of HLA A-B-DR fully matched donors while replacing the HLA match grade by PIRCHE-II score and exchanging the HLA mismatch probability (MMP) by epitope MMP. This setup showed no considerable impact on kidney exchange rates and waiting time. PIRCHE-II scores improved, whereas the average HLA match grade diminishes slightly, yet leading to an improved estimated graft survival. We conclude that epitope-based matching in deceased donor kidney allocation is feasible while maintaining equal balances on the waiting list.

In pre-sensitizing events, immunological memory is mainly created via indirect allorecognition where CD4 + T cells recognize foreign peptides in the context of self-HLA class II (pHLA) presented on antigen-presenting cells. This recognition makes it possible for naive CD4 + T-helper cells to differentiate into memory cells, resulting in the creation of further antibody memory. These responses contribute to effective secretion of donor-specific anti-HLA antibodies (DSA) after second encounters with the same peptide. Preformed donor-reactive CD4 + memory T cells may induce early immune responses after transplantation; however, the tools to evaluate them are limited. This study evaluated shared T cell epitopes (TEs) between the pre-sensitizing and donor HLA using an in silico assay, an alternative to estimate donor-reactive CD4 + memory T cells before transplantation. In 578 living donor kidney transplants without preformed DSA, 69 patients had anti-HLA antibodies before transplantation. Of them, 40 had shared TEs and were estimated to have donor-reactive CD4 + memory T cells. De novo DSA formation in the early phase was significantly higher in the shared TE-positive group than in the anti-HLA antibody- and shared TE-negative groups (p=0.001 and p=0.02, respectively). In conclusion, evaluation of shared TEs for estimating preformed donor-reactive CD4 + memory T cells may help predict the risk of early de novo DSA formation after kidney transplantation.

Donor/recipient molecular human leukocyte antigen (HLA) mismatch predicts primary B-cell alloimmune activation, yet the impact on de novo donor-specific T-cell alloimmunity (dnDST) remains undetermined. The hypothesis of our study is that donor/recipient HLA mismatches assessed at the molecular level may also influence a higher susceptibility to the development of posttransplant primary T-cell alloimmunity. In this prospective observational study, 169 consecutive kidney transplant recipients without preformed donor-specific antibodies (DSA) and with high resolution donor/recipient HLA typing were evaluated for HLA molecular mismatch scores using different informatic algorithms [amino acid mismatch, eplet MM, and Predicted Indirectly Recognizable HLA Epitopes (PIRCHE-II)]. Primary donor-specific alloimmune activation over the first 2 years posttransplantation was assessed by means of both dnDSA and dnDST using single antigen bead (SAB) and IFN-γ ELISPOT assays, respectively. Also, the predominant alloantigen presenting pathway priming DST alloimmunity and the contribution of main alloreactive T-cell subsets were further characterized in vitro . Pretransplantation, 78/169 (46%) were DST+ whereas 91/169 (54%) DST−. At 2 years, 54/169 (32%) patients showed detectable DST responses: 23/54 (42%) dnDST and 31/54 (57%) persistently positive (persistDST+). 24/169 (14%) patients developed dnDSA. A strong correlation was observed between the three distinct molecular mismatch scores and they all accurately predicted dnDSA formation, in particular at the DQ locus. Likewise, HLA molecular incompatibility predicted the advent of dnDST, especially when assessed by PIRCHE-II score (OR 1.014 95% CI 1.001–1.03, p=0.04). While pretransplant DST predicted the development of posttransplant BPAR (OR 5.18, 95% CI=1.64–16.34, p=0.005) and particularly T cell mediated rejection (OR 5.33, 95% CI=1.45–19.66, p=0.012), patients developing dnDST were at significantly higher risk of subsequent dnDSA formation (HR 2.64, 95% CI=1.08–6.45, p=0.03). In vitro experiments showed that unlike preformed DST that is predominantly primed by CD8+ direct pathway T cells, posttransplant DST may also be activated by the indirect pathway of alloantigen presentation, and predominantly driven by CD4+ alloreactive T cells in an important proportion of patients. De novo donor-specific cellular alloreactivity seems to precede subsequent humoral alloimmune activation and is influenced by a poor donor/recipient HLA molecular matching.

We analyzed in a cohort of 68,606 first deceased donor kidney transplantations reported to the Collaborative Transplant Study whether an epitope-based matching of donor-recipient pairs using the Predicted Indirectly ReCognizable HLA Epitopes algorithm (PIRCHE-II) is superior to currently applied HLA antigen matching. PIRCHE-II scores were calculated based on split antigen HLA-A, -B, -DRB1 typing and adjusted to the 0–6 range of HLA mismatches. PIRCHE-II scores correlated strongly with the number of HLA mismatches (Spearman ρ = 0.65, P < 0.001). In multivariable analyses both parameters were found to be significant predictors of 5-year death-censored graft loss with high prognostic power [hazard ratio (HR) per adjusted PIRCHE-II score = 1.102, per HLA mismatch = 1.095; z -value PIRCHE-II: 9.8, HLA: 11.2; P < 0.001 for both]. When PIRCHE-II scores and HLA mismatches were analyzed simultaneously, their predictive power decreased but remained significant (PIRCHE-II: P = 0.002; HLA: P < 0.001). Influence of PIRCHE-II was especially strong in presensitized and influence of HLA mismatches in non-sensitized recipients. If the level of HLA-incompatibility was low (0–3 mismatches), PIRCHE-II scores showed a low impact on graft survival (HR = 1.031) and PIRCHE-II matching did not have additional significant benefit ( P = 0.10). However, if the level of HLA-incompatibility was high (4–6 mismatches), PIRCHE-II improved the positive impact of matching compared to applying the traditional HLA matching alone (HR = 1.097, P = 0.005). Our results suggest that the PIRCHE-II score is useful and can be included into kidney allocation algorithms in addition to HLA matching; however, at the resolution level of HLA typing that is currently used for allocation it cannot fully replace traditional HLA matching.

Abstract Background New strategies to optimize donor selection for hematopoietic stem cell transplantation (HSCT) have mainly been evaluated in adults, but the disease spectrum requiring HSCT differs significantly in children and has consequences for the risk of complications, such as graft‐versus‐host disease (GvHD). Procedures Here we evaluated whether HLA‐DPB1 and Predicted Indirectly ReCognizable HLA‐Epitope (PIRCHE) matching can improve donor selection and minimize risks specific for a pediatric cohort undergoing HSCT in Berlin between 2014 and 2016. Results The percentage of HLA‐DPB1–mismatched HSCT in the pediatric cohort was in line with the general distribution among matched unrelated donor HSCT. Nonpermissive HLA‐DPB1 mismatches were not associated with a higher incidence of GvHD, but the incidence of relapse was higher in patients undergoing HSCT from HLA‐DPB1–matched transplantations. High PIRCHE‐I scores were associated with a significantly higher risk for developing GvHD in patients undergoing HSCT from nine of ten matched unrelated donors. This finding persisted after including HLA‐DPB1 into the PIRCHE analysis. Conclusions Implementing PIRCHE typing in the donor selection process for HSCT in children could particularly benefit children with nonmalignant diseases and support further validation of PIRCHE‐based donor selection in a larger number of children treated at different sites.

Abstract Human leukocyte antigen (HLA) mismatches between donors and recipients may lead to alloreactivity after solid organ transplantation. Over the last few decades, our knowledge of the complexity of the HLA system has dramatically increased, as numerous new HLA alleles have been identified. As a result, the likelihood of alloreactive responses towards HLA mismatches after solid organ transplantation cannot easily be assessed. Algorithms are promising solutions to estimate the risk for alloreactivity after solid organ transplantation. In this review, we show that the recently developed PIRCHE-II (Predicted Indirectly ReCognizable HLA Epitopes) algorithm can be used to minimize alloreactivity towards HLA mismatches. Together with the use of other algorithms and simulation approaches, the PIRCHE-II algorithm aims for a better estimated alloreactive risk for individual patients and eventually an improved graft survival after solid organ transplantation.

目的 分析肾移植供受者人类白细胞抗原（HLA）分布频率与受者HLA抗体分布频率，揭示预测间接可识别的HLA表位（PIRCHE）评分与供者特异性抗体（DSA）的产生和抗体介导排斥反应（AMR）发生的关系。方法 选取西安交通大学第一附属医院肾移植科2013年11月至2017年6月798例肾移植病例。采用HLA高分辨分型LABType SSO法，HLAⅠ、Ⅱ类抗体检测采用LABcreen Single Antigen试剂，Luminex 200技术进行检测。PIRCHE评分系统进行PIRCHE评分。结果 798例受者，409例供者的HLA高分辨分型资料结果显示，常见供受体HLA A位点以A2、A11、A24最为常见；B位点以B13、B46、B51、B60、B35、B62、B61最为常见；DR位点以DR9、DR4、DR15、DR12、DR7、DR11最为常见；DQ位点以DQ7、DQ6、DQ5、DQ9、DQ2最为常见。术后HLAⅠ类抗体阳性105例，HLAⅡ抗体阳性40例，DSA阳性32例。HLAⅠ类抗体最常见为A24，B7抗体；HLA Ⅱ类抗体最常见为DQ抗体，包括DQ2，DQ9，DQ4，DQ6，DQ7，DQ8。活体移植供受者PIRCHE评分低于DCD供肾组（0.01），差异有统计学意义；DSA组及DSAAMR组PIRCHE评分分别高于DSA组及DSAAMR组（0.01），差异有统计学意义；ROC曲线对PIRCHE评分预测DSA产生及AMR发生进行了分析发现，DSA产生的AUC为0.80，临界值为115.5；AMR发生的AUC为0.89，临界值为133.5。结论 常见的HLA抗原，免疫原性强，容易刺激机体产生HLA抗体；肾脏移植前应重视常见抗原位点的匹配以及HLAⅡ抗原的匹配。PIRCHE评分用于HLA配型，可有效预测DSA的产生和AMR的发生，具有比传统方法更灵敏，包含信息量更大的优势。

For several malignant and nonmalignant disorders such as leukemias, lymphomas, or inborn errors of hematopoiesis, stem cell transplantation is the only curative option. Depending on the underlying cause of the disease, the conditioning regimens, source of the stem cells, and graft composition may vary. Possible stem cell donors are selected from databases considering existing major histocompatibility genes of the donor and the recipient. This is currently performed by matching human leukocyte antigen (HLA)-A, -B, and -C for class I, as well as HLA-DRB1 and -DQB1 for class II. Stem cell transplantation for nonmalignant disorders is a specialty of pediatrics. While algorithms for donor selection in these cases are generally similar, the objective of optimizing a possible graft-versus-leukemia effect is less important. In this article, we aim to provide an overview on the current methods for HLA typing and the algorithms for HLA matching. We also address ethical aspects regarding children and minors as stem cell donors.

There is no established standard for selection of mismatched unrelated donors. Indirect recognition of HLA mismatches can be predicted using the model of “Predicted Indirectly ReCognizable HLA Epitopes” (PIRCHE). We performed a multicenter retrospective study evaluating the impact PIRCHE on outcome after allogeneic stem cell transplantation (allo-HSCT) from single mismatched (HLA 9/10 matched) unrelated donors. The study cohort included 424 adult recipients of HLA 9/10 matched unrelated donor transplants (9/10 MUD), treated for AML or MDS at 6 transplant centers across Germany. Detection of PIRCHE was associated with lower overall survival (OS) (47 vs. 57%, p = 0.04), higher non-relapse mortality (NRM) (32 vs. 20%, p = 0.05), and higher incidence of chronic graft-versus-host disease (GVHD) (49 vs. 31%, p = 0.04) at 2 years. Cumulative incidence of acute GVHD grade 2–4 at 6 months was not significantly different (30 vs. 23%, p = 0.2). OS for 9/10 MUD with no PIRCHE was similar to 10/10 MUD (57 vs. 55%). In multivariate analysis, PIRCHE retained negative impact on OS (RR 1.5, 95% CI 1.0–2.1, p = 0.03) and NRM (RR 1.7, 95% CI 1.0–2.9, p = 0.03). To the best of our knowledge, for the first time, we show the association of PIRCHE and survival outcome after allo-HSCT. The PIRCHE model, if validated in an independent cohort, may allow selection of permissible HLA mismatches that enable improved transplant outcome.

Limited availability of allele-level HLA genotypes prompts their imputation from allele-group genotypes to estimate epitope mismatches. We evaluated the accuracy of epitope load and repertoire assignment when imputing allele-level HLA genotypes. Analyses were conducted on 175 hematopoietic stem cell (HSC) donors from the Héma-Québec registry (HQR) and 57 HSC donor-recipient pairs from McGill University Health Centre (MUHC), Québec, Canada, genotyped for HLA-A, -B, -C, -DRB1, and -DQB1. Multilocus allele-level imputation was performed using HaploStats. Disagreement in B- and T-cell epitope assignment and epitope mismatches were ascertained for imputed vs measured allele-level HLA genotypes in HSC donors and donor-recipient pairs, respectively. Imputation resulted in no differences in overall eplet mismatches and Predicted Indirectly ReCognizable HLA Epitopes (PIRCHE-II) for HLA-A, -B, and -C in 83.4% and 93.7% of HQR donors and 87.7% and 87.7% of MUHC donors, respectively. HLA-DRB1- and -DQB1-derived eplet mismatches and PIRCHE-II were correctly assigned in 72.0% and 85.1% of HQR donors and 70.2% and 71.9% of MUHC donors, respectively. No discrepancies in eplet load or PIRCHE-II were observed in 96.5% and 86.0% of HSC donor-recipient pairs and in 70.2% and 70.1% of pairs for HLA-A, -B, -C, -DRB1, and -DQB1, respectively. Kappa statistics of 0.9708 and 0.9725, 0.8724 and 0.8177, 0.9827 and 0.9022, 0.5644 and 0.4939, 0.5085 and 0.6361 were estimated when assessing agreement between eplet mismatches and PIRCHE-II of imputed vs measured HLA-A, -B, -C, -DRB1, and -DQB1 types, respectively. To avoid inaccuracies in epitope compatibility estimation, mainly for HLA class II, multilocus allele-level genotype measurement is recommended.

Summary The predicted indirectly recognizable human leucocyte antigen (HLA) epitopes ( PIRCHE ) algorithm is a novel in silico algorithm to determine donor–recipient compatibility. The PIRCHE algorithm determines donor–recipient compatibility by counting the number of mismatched HLA ‐derived epitopes that are involved in indirect T‐cell alloimmune responses; these epitopes are designated as PIRCHE . Over the last few years, the PIRCHE algorithm has been investigated in both hematopoietic stem cell transplantation and solid organ transplantation. This review describes the theory of the algorithm, its application in transplantation, and highlights the future perspectives on the clinical application of the PIRCHE algorithm.

The identification of permissible HLA class II mismatches can prevent DSA in mismatched transplantation. The HLA-DR phenotype of recipients contributes to DSA formation by presenting allo-HLA-derived peptides to T-helper cells, which induces the differentiation of B cells into plasma cells. Comparing the binding affinity of self and nonself allo-HLA-derived peptides for recipients’ HLA class II antigens may distinguish immunogenic HLA mismatches from nonimmunogenic ones. The binding affinities of allo-HLA-derived peptides to recipients’ HLA-DR and HLA-DQ antigens were predicted using the NetMHCIIpan 3.1 server. HLA class II mismatches were classified based on whether they induced DSA and whether self or nonself peptide was predicted to bind with highest affinity to recipients’ HLA-DR and HLA-DQ. Other mismatch characteristics (eplet, hydrophobic, electrostatic, and amino acid mismatch scores and PIRCHE-II) were evaluated. A significant association occurred between DSA formation and the predicted HLA-DR presentation of nonself peptides ( P = 0.0169 ; accuracy = 80%; sensitivity = 88%; specificity = 63%). In contrast, mismatch characteristics did not differ significantly between mismatches that induced DSA and the ones that did not, except for PIRCHE-II ( P = 0.0094 ). This methodology predicts DSA formation based on HLA mismatches and recipients’ HLA-DR phenotype and may identify permissible HLA mismatches to help optimize HLA matching and guide donor selection.

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

The aim of the current study was to characterize the anti-HLA antibodies before and after pancreatic islet or pancreas transplantation. We assessed the risk of anti-donor-specific antibody (DSA) sensitization in a single-center, retrospective clinical study at Geneva University Hospital. Data regarding clinical characteristics, graft outcome, HLA mismatch, donor HLA immunogenicity, and anti-HLA antibody characteristics were collected. Between January 2008 and July 2014, 18 patients received islet transplants, and 26 patients received a pancreas transplant. Eleven out of 18 patients (61.1%) in the islet group and 12 out of 26 patients (46.2%) in the pancreas group had anti-HLA antibodies. Six patients (33.3%) developed DSAs against HLA of the islets, and 10 patients (38.4%) developed DSAs against HLA of the pancreas. Most of the DSAs were at a low level. Several parameters such as gender, number of times cells were transplanted, HLA mismatch, eplet mismatch and PIRCHE-II numbers, rejection, and infection were analyzed. Only the number of PIRCHE-II was associated with the development of anti-HLA class II de novo DSAs. Overall, the development of de novo DSAs did not influence graft survival as estimated by insulin independence. Our results indicated that pretransplant DSAs at low levels do not restrict islet or pancreas transplantation [especially islet transplantation (27.8% vs. 15.4.%)]. De novo DSAs do occur at a similar rate in both pancreas and islet transplant recipients (mainly of class II), and the immunogenicity of donor HLA is a parameter that should be taken into consideration. When combined with an immunosuppressive regimen and close follow-up, development of low levels of DSAs was not found to result in reduced graft survival or graft function in the current study.

Human leukocyte Antigen (HLA) mismatching leads to severe complications after solid-organ transplantation and hematopoietic stem-cell transplantation. The alloreactive responses underlying the posttransplantation complications include both direct recognition of allogeneic HLA by HLA-specific alloantibodies and T cells and indirect T-cell recognition. However, the immunogenicity of HLA mismatches is highly variable; some HLA mismatches lead to severe clinical B-cell- and T-cell-mediated alloreactivity, whereas others are well tolerated. Definition of the permissibility of HLA mismatches prior to transplantation allows selection of donor-recipient combinations that will have a reduced chance to develop deleterious host-versus-graft responses after solid-organ transplantation and graft-versus-host responses after hematopoietic stem-cell transplantation. Therefore, several methods have been developed to predict permissible HLA-mismatch combinations. In this review we aim to give a comprehensive overview about the current knowledge regarding HLA-directed alloreactivity and several developed in vitro and in silico tools that aim to predict direct and indirect alloreactivity.