High-throughput sequencing defines donor and recipient HLA B-cell epitope frequencies for prospective matching in transplantation

Abstract

Compatibility for human leukocyte antigen (HLA) genes between transplant donors and recipients improves graft survival but prospective matching is rarely performed due to the vast heterogeneity of this gene complex. To reduce complexity, we have combined next-generation sequencing and in silico mapping to determine transplant population frequencies and matching probabilities of 150 antibody-binding eplets across all 11 classical HLA genes in 2000 ethnically heterogeneous renal patients and donors. We show that eplets are more common and uniformly distributed between donors and recipients than the respective HLA isoforms. Simulations of targeted eplet matching shows that a high degree of overall compatibility, and perfect identity at the clinically important HLA class II loci, can be obtained within a patient waiting list of approximately 250 subjects. Internal epitope-based allocation is thus feasible for most major renal transplant programs, while regional or national sharing may be required for other solid organs.

Can We Use Eplets (or Molecular) Mismatch Load Analysis to Improve Organ Allocation? The Hope and the Hype

“…They further calculated “epitypes” (a new terminology, probably referring to the identity of eplets within a genotype = 2 per subject). 39 Similar to the genotype data, they found 1010 unique epitypes among patients, 751 unique epitypes donors with 1.8% of epitypes occurring in both groups. In conclusion, the authors recognized that identical matching at the epitype, or at each gene region, is improbable in a diverse transplant population.…”

“…A common argument for the use for epitope or eplet “matching” claims that the frequency of individual alleles in the population is smaller than the frequency of the different eplets, and therefore, it will be easier to find a match based on a polymorphism that is more prevalent in the population. For example, Tran et al 39 studied 2000 subjects from the BC transplant program who had high-resolution typing for all HLA loci. Of those, 154 were excluded because their alleles are not present as part of the HLAMatchmaker database.…”

“…Building on those, new bioinformatic tools are being developed, for example, HLA-Epi. 42 New terms are introduced, for example, “epitope typing,” 43 “antibody-binding eplets‚” or “epitypes.” 39 The use of such tools and the associated evocative terminology continues to build on precarious infrastructure and supports a false sense of familiarity and confidence. The use of a computer program, as well as terms that sound sophisticated and advanced, may help promote and market tools that have poor scientific basis.…”

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

“…Although the current epitope matching strategies add prognostic value to classic antigen matching as implemented by many allocation organizations, further refinements of these approaches may specifically integrate epitope immunogenicity, antigenicity and hierarchy ( 44 – 46 ). Despite the current algorithms’ imperfections, simulation studies have shown the beneficial impact of currently available epitope matching algorithms in organ allocation ( 47 , 48 ). Applied to a broad population, organ donor allocation supported by epitope matching may decrease overall frequency of immunological events that ultimately cause graft rejection.…”

Pediatric Kidney Transplantation—Can We Do Better? The Promise and Limitations of Epitope/Eplet Matching

“…These models are under development and will require close monitoring after implementation. More data are needed to inform approaches to optimize matching for children and one approach might include a focus on class II matching (79).…”