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Cohen GS, Gareau AJ, Kallarakal MA, Farooq T, Bettinotti MP, Sullivan HC, Madbouly A, Krummey SM. HLA Genotype Imputation Results in Largely Accurate Epitope Mismatch Risk Categorization Across Racial Groups. Transplant Direct 2024; 10:e1639. [PMID: 38911277 PMCID: PMC11191912 DOI: 10.1097/txd.0000000000001639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 05/09/2024] [Indexed: 06/25/2024] Open
Abstract
Background Biomarkers that predict posttransplant alloimmunity could lead to improved long-term graft survival. Evaluation of the number of mismatched epitopes between donor and recipient HLA proteins, termed molecular mismatch analysis, has emerged as an approach to classify transplant recipients as having high, intermediate, or low risk of graft rejection. When high-resolution genotypes are unavailable, molecular mismatch analysis requires algorithmic assignment, or imputation, of a high-resolution genotyping. Although imputation introduces inaccuracies in molecular mismatch analyses, it is unclear whether these inaccuracies would impact the clinical risk assessment for graft rejection. Methods Using renal transplant patients and donors from our center, we constructed cohorts of surrogate donor-recipient pairs with high-resolution and low-resolution HLA genotyping that were racially concordant or discordant. We systemically assessed the impact of imputation on molecular mismatch analysis for cohorts of 180-200 donor-recipient pairs for each of 4 major racial groups. We also evaluated the effect of imputation for a racially diverse validation cohort of 35 real-world renal transplant pairs. Results In the surrogate donor-recipient cohorts, imputation preserved the molecular mismatch risk category for 90.5%-99.6% of racially concordant donor-recipient pairs and 92.5%-100% of racially discordant pairs. In the validation cohort, which comprised 72% racially discordant pairs, we found that imputation preserved the molecular mismatch risk category for 97.1% of pairs. Conclusions Overall, these data demonstrate that imputation preserves the molecular mismatch risk assessment in the vast majority of cases and provides evidence supporting imputation in the performance of molecular mismatch analysis for clinical assessment.
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Affiliation(s)
- Gregory S. Cohen
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Alison J. Gareau
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD
- Johns Hopkins Immunogenetics Laboratory, Baltimore, MD
| | | | - Tayyiaba Farooq
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Maria P. Bettinotti
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD
- Johns Hopkins Immunogenetics Laboratory, Baltimore, MD
| | - H. Cliff Sullivan
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA
| | - Abeer Madbouly
- National Marrow Donor Program/Be The Match, Minneapolis, MN
- Center for International Blood and Marrow Transplant Research, Minneapolis, MN
| | - Scott M. Krummey
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD
- Johns Hopkins Immunogenetics Laboratory, Baltimore, MD
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Johnson AC, Zhang J, Karadkhele G, Gragert L, Hertzberg V, Larsen CP. Belatacept with time-limited tacrolimus coimmunosuppression modifies the 3-year risk of eplet mismatch in kidney transplantation. Am J Transplant 2024; 24:260-270. [PMID: 37778459 PMCID: PMC10842047 DOI: 10.1016/j.ajt.2023.09.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 09/16/2023] [Accepted: 09/19/2023] [Indexed: 10/03/2023]
Abstract
Solid organ transplant donor-recipient eplet mismatch has been correlated with donor-specific antibody (DSA) formation, antibody-mediated rejection, and overall rejection rates. However, studies have been predominantly in patients on tacrolimus-based immunosuppression regimens and have not fully explored differences in ethnically and racially diverse populations. Evidence indicates that patients on belatacept have lower rates of DSA formation, suggesting mediation of the immunogenicity of mismatched human leukocyte antigen polymorphisms. We performed a retrospective, single-center analysis of class II eplet disparity in a cohort of kidney transplant recipients treated using belatacept with tacrolimus induction (Bela/TacTL) or tacrolimus regimens between 2016 and 2019. Bela/TacTL (n = 294) and tacrolimus (n = 294) cohorts were propensity score-matched with standardized difference <0.15. Single-molecule eplet risk level was associated with immune event rates for both groups. In Cox regression analysis stratified by eplet risk level, Bela/TacTL immunosuppression was associated with a decreased rate of DSA (hazard ratio [HR] = 0.4), antibody-mediated rejection (HR = 0.2), and rejection (HR = 0.45). In the low-risk group, cumulative graft failure was lower for patients on Bela/TacTL (P < .02). Analysis of eplet mismatch burden may be a useful adjunct in identifying high-risk populations with increased immunosuppression requirements and should encourage the design of allocation rules to incentivize lower-risk pairings without negatively impacting equity in access.
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Affiliation(s)
- Aileen C Johnson
- Department of Surgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Joan Zhang
- Department of Surgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Geeta Karadkhele
- Department of Surgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Loren Gragert
- Department of Pathology, Tulane University School of Medicine, New Orleans, Louisiana, USA
| | - Vicki Hertzberg
- Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA
| | - Christian P Larsen
- Department of Surgery, Emory University School of Medicine, Atlanta, Georgia, USA.
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Lhotte R, Letort V, Usureau C, Jorge-Cordeiro D, Siemowski J, Gabet L, Cournede PH, Taupin JL. Improving HLA typing imputation accuracy and eplet identification with local next-generation sequencing training data. HLA 2024; 103:e15222. [PMID: 38589051 DOI: 10.1111/tan.15222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/26/2023] [Accepted: 08/26/2023] [Indexed: 04/10/2024]
Abstract
Assessing donor/recipient HLA compatibility at the eplet level requires second field DNA typings but these are not always available. These can be estimated from lower-resolution data either manually or with computational tools currently relying, at best, on data containing typing ambiguities. We gathered NGS typing data from 61,393 individuals in 17 French laboratories, for loci A, B, and C (100% of typings), DRB1 and DQB1 (95.5%), DQA1 (39.6%), DRB3/4/5, DPB1, and DPA1 (10.5%). We developed HaploSFHI, a modified iterative maximum likelihood algorithm, to impute second field HLA typings from low- or intermediate-resolution ones. Compared with the reference tools HaploStats, HLA-EMMA, and HLA-Upgrade, HaploSFHI provided more accurate predictions across all loci on two French test sets and four European-independent test sets. Only HaploSFHI could impute DQA1, and solely HaploSFHI and HaploStats provided DRB3/4/5 imputations. The improved performance of HaploSFHI was due to our local and nonambiguous data. We provided explanations for the most common imputation errors and pinpointed the variability of a low number of low-resolution haplotypes. We thus provided guidance to select individuals for whom sequencing would optimize incompatibility assessment and cost-effectiveness of HLA typing, considering not only well-imputed second field typing(s) but also well-imputed eplets.
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Affiliation(s)
- Romain Lhotte
- Immunology and Histocompatibility Laboratory, Saint-Louis Hospital, Paris, France
- MICS-Research laboratory in Mathematics and Computer Science at CentraleSupélec, Gif-Sur-Yvette, France
- INSERM U976 Eq. 3 HIPI IRSL Saint-Louis Hospital, Université de Paris-Cité, Paris, France
| | - Véronique Letort
- MICS-Research laboratory in Mathematics and Computer Science at CentraleSupélec, Gif-Sur-Yvette, France
| | - Cédric Usureau
- Immunology and Histocompatibility Laboratory, Saint-Louis Hospital, Paris, France
| | | | - Jérémy Siemowski
- Immunology and Histocompatibility Laboratory, Saint-Louis Hospital, Paris, France
| | - Lionel Gabet
- MICS-Research laboratory in Mathematics and Computer Science at CentraleSupélec, Gif-Sur-Yvette, France
| | - Paul-Henry Cournede
- MICS-Research laboratory in Mathematics and Computer Science at CentraleSupélec, Gif-Sur-Yvette, France
| | - Jean-Luc Taupin
- Immunology and Histocompatibility Laboratory, Saint-Louis Hospital, Paris, France
- INSERM U976 Eq. 3 HIPI IRSL Saint-Louis Hospital, Université de Paris-Cité, Paris, France
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Johnson AC, Zhang J, Cliff Sullivan H, Wiebe C, Bray R, Gebel H, Larsen CP. hlaR: A rapid and reproducible tool to identify eplet mismatches between transplant donors and recipients. Hum Immunol 2022; 83:248-255. [PMID: 35101308 PMCID: PMC11016307 DOI: 10.1016/j.humimm.2022.01.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 01/07/2022] [Accepted: 01/10/2022] [Indexed: 11/30/2022]
Abstract
Eplet mismatch load, both overall and at the single molecule level, correlates with transplant recipient outcomes. However, precise eplet assessment requires high-resolution HLA typing of both the donor and recipient. Anything less than high-resolution typing requires imputation of HLA types. The currently available methods to identify eplet mismatch are both tedious and demanding. Therefore, we developed a software package and user-friendly web application (hlaR), that simplifies the workflow of eplet analysis, provides functions to impute high-resolution from low-resolution data and calculates both overall and single molecule eplet mismatch for single or multiple donor recipient pairs. Compared to manual assessments using currently available tools (namely, HLAMatchMaker), hlaR resulted in only minimal discrepancy in eplet mismatches (mean absolute difference of 0.56 for class I and 0.86 for class II for unique sum across loci). Additionally, output of the single molecule eplet function compared well to manual calculation, with an average single antigen count increase of 0.19. Importantly, the hlaR tool permits rapid and reproducible imputation and eplet mismatch including comparison between eplet reference tables (e.g. HLAMatchMaker version 2 or 3). Users can import data from a spreadsheet rather than relying on keystroke entry of individual donor and recipient data, thus reducing the risk of data entry errors. The resulting improved scalability of the hlaR tool is highlighted by plotting analysis time against the size of the input dataset. The new hlaR tool can provide eplet mismatch data with a streamlined workflow. With decreased effort from the end user, eplet matching and mismatch load data can be further incorporated into both research and clinical use.
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Affiliation(s)
| | - Joan Zhang
- Department of Surgery, Emory University, United States
| | | | - Chris Wiebe
- Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Robert Bray
- Department of Pathology, Emory University, United States
| | - Howard Gebel
- Department of Pathology, Emory University, United States
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Krummey SM, Cliff Sullivan H. The utility of imputation for molecular mismatch analysis in solid organ transplantation. Hum Immunol 2022; 83:241-247. [PMID: 35216846 DOI: 10.1016/j.humimm.2021.11.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/15/2021] [Accepted: 11/26/2021] [Indexed: 02/07/2023]
Abstract
HLA genotyping has undergone a rapid progression in resolution since the development of DNA-based typing methods. Despite the advent of high-resolution next-generation sequencing, the bulk of solid organ genotyping is performed at intermediate resolution, which provides multiple possible two-field results for each classical HLA loci. As a result, several methodologies have been developed to impute the most likely allele-level (two-field) HLA genotype for the purposes of donor-recipient compatibility analysis. The advent of molecular mismatch analysis, however, has placed a new emphasis on the accuracy of imputation. While seminal molecular mismatch studies have relied on the imputation of intermediate resolution genotyping, several recent studies have performed analysis showing that imputation generates inaccuracies in epitope identification. While the clinical impact of these errors is not clear, it is important that these concerns do not preclude future progress in understanding the utility of molecular mismatch analysis in transplantation. In the future, advances in genotyping methods will result in routine two-field resolution that will abrogate these concerns. In the meantime, however, studies are needed in order to address the role of molecular mismatch in diverse patient populations and to carefully address the potential of molecular mismatch analysis in the context of imputation.
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Affiliation(s)
- Scott M Krummey
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - H Cliff Sullivan
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, United States
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