Low Hydrophobic Mismatch Scores Calculated for HLA-A/B/DR/DQ Loci Improve Kidney Allograft Survival

Maximizing matching, equity and survival in kidney transplantation using molecular HLA immunogenicity quantitation

HLA matching improves long-term outcomes of kidney transplantation, yet implementation challenges persist, particularly within the African American (Black) patient demographic due to donor scarcity. Consequently, kidney survival rates among Black patients significantly lag behind those of other racial groups. A refined matching scheme holds promise for improving kidney survival, with prioritized matching for Black patients potentially bolstering rates of HLA-matched transplants. To facilitate quantity, quality and equity in kidney transplants, we propose two matching algorithms based on quantification of HLA immunogenicity using the hydrophobic mismatch score (HMS) for prospective transplants. We mined the national transplant patient database (SRTR) for a diverse group of donors and recipients with known racial backgrounds. Additionally, we use novel methods to infer survival assessment in the simulated transplants generated by our matching algorithms, in the absence of actual target outcomes, utilizing modified unsupervised clustering techniques. Our allocation algorithms demonstrated the ability to match 87.7% of Black and 86.1% of White recipients under the HLA immunogenicity threshold of 10. Notably, at the lowest HMS threshold of 0, 4.4% of Black and 12.1% of White recipients were matched, a marked increase from the 1.8% and 6.6% matched under the prevailing allocation scheme. Furthermore, our allocation algorithms yielded similar or improved survival rates, as illustrated by Kaplan-Meier (KM) curves, and enhanced survival prediction accuracy, evidenced by C-indices and Integrated Brier Scores.

Belatacept with time-limited tacrolimus coimmunosuppression modifies the 3-year risk of eplet mismatch in kidney transplantation

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.

A rational approach to guide cost-effective de novo donor-specific antibody surveillance with tacrolimus immunosuppression

De novo donor-specific antibody (dnDSA) after renal transplantation has been shown to correlate with antibody-mediated rejection and allograft loss. However, the lack of proven interventions and the time and cost associated with annual screening for dnDSA are difficult to justify for all recipients. We studied a well-characterized consecutive cohort (n = 949) with over 15 years of prospective dnDSA surveillance to identify risk factors that would help institute a resource-responsible surveillance strategy. Younger recipient age and HLA-DR/DQ molecular mismatch were independent predictors of dnDSA development. Combining both risk factors into recipient age molecular mismatch categories, we found that 52% of recipients could be categorized as low-risk for dnDSA development (median subclinical dnDSA-free survival at 5 and 10 years, 98% and 97%, respectively). After adjustment, multivariate correlates of dnDSA development included tacrolimus versus cyclosporin maintenance immunosuppression (hazard ratio [HR], 0.37; 95% CI, 0.2-0.6; P < .0001) and recipient age molecular mismatch category: intermediate versus low (HR, 2.48; 95% CI, 1.5-4.2; P = .0007), high versus intermediate (HR, 2.56; 95% CI, 1.6-4.2; P = .0002), and high versus low (HR, 6.36; 95% CI, 3.7-10.8; P < .00001). When combined, recipient age and HLA-DR/DQ molecular mismatch provide a novel data-driven approach to reduce testing by >50% while selecting those most likely to benefit from dnDSA surveillance.

Progress in kidney transplantation: The role for systems immunology

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.

Improving Access to HLA-Matched Kidney Transplants for African American Patients

Introduction

Kidney transplants fail more often in Black than in non-Black (White, non-Black Hispanic, and Asian) recipients. We used the estimated physicochemical immunogenicity for polymorphic amino acids of donor/recipient HLAs to select weakly immunogenic kidney transplants for Black vs. White or non-Black patients.

Methods

OPTN data for 65,040 donor/recipient pairs over a 20-year period were used to calculate the individual physicochemical immunogenicity by hydrophobic, electrostatic and amino acid mismatch scores (HMS, EMS, AMS) and graft-survival outcomes for Black vs. White or vs. non-Black recipients, using Kaplan-Meier survival and Cox regression analyses. Simulations for re-matching recipients with donors were based on race-adjusted HMS thresholds with clinically achievable allocations.

Results

The retrospective median kidney graft survival was 12.0 years in Black vs. 18.6 years in White (6.6-year difference; p>0.001) and 18.4 years in non-Black (6.4-year difference; p>0.01) recipients. Only 0.7% of Blacks received transplants matched at HLA-A/B/DR/DQ (HMS=0) vs. 8.1% in Whites (p<0.001). Among fully matched Blacks (HMS=0), graft survival was 16.1-years and in well-matched Blacks (HMS ≤ 3.0) it was 14.0-years. Whites had 21.6-years survival at HMS ≤ 3.0 and 18.7-years at HMS ≤ 7.0 whereas non-Blacks had 22.0-year at HMS ≤ 3.0 and 18.7-year at HMS ≤ 7.0, confirming that higher HMS thresholds produced excellent survival. Simulation of ABO-compatible donor-recipient pairs using race-adjusted HMS thresholds identified weakly immunogenic matches at HMS=0 for 6.1% Blacks and 18.0% at HMS ≤ 3.0. Despite prioritizing Black patients, non-Black patients could be matched at the same level as in current allocation (47.0% vs 56.5%, at HMS ≤ 7.0).

Conclusions

Race-adjusted HMS (EMS, AMS)-based allocation increased the number of weakly immunogenic donors for Black patients, while still providing excellent options for non-Black recipients.

hlaR: A rapid and reproducible tool to identify eplet mismatches between transplant donors and recipients

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.