From antigens to eplets: The evolution of HLA

Two-field resolution on-call HLA typing for deceased donors using nanopore sequencing

The current practice of HLA genotyping in deceased donors poses challenges due to limited resolution within time constraints. Nevertheless, the assessment of compatibility between anti-HLA sensitized recipients and mismatched donors remains a critical medical need, particularly when dealing with allele-specific (second field genotyping level) donor-specific antibodies. In this study, we present a customized protocol based on the NanoTYPE® HLA typing kit, employing the MinION® sequencer, which enables rapid HLA typing of deceased donors within a short timeframe of 3.75 h on average at a three-field resolution with almost no residual ambiguities. Through a prospective real-time analysis of HLA typing in 18 donors, we demonstrated the efficacy and precision of our nanopore-based method in comparison to the conventional approach and without delaying organ allocation. Indeed, this duration was consistent with the deceased donor organ donation procedure leading to organ allocation via the French Biomedicine Agency. The improved resolution achieved with our protocol enhances the security of organ allocation, particularly benefiting highly sensitized recipients who often present intricate HLA antibody profiles. By overcoming technical challenges and providing comprehensive genotyping data, this approach holds the potential to significantly impact deceased donor HLA genotyping, thereby facilitating optimal organ allocation strategies.

Epitopes, paratopes, and other topes 30 years on: Understanding what we are talking about

The question of which protein antigens, such as HLA class I or class II molecules, will bind, and how well, to a given antibody is often assumed to depend exclusively on the details of protein surface structure. These structures are usually based on static models resulting from X-ray crystallography. While these notions are useful, the ultimate causal factors determining how well a given antigen binds a given antibody are based in thermodynamics and can include atomic mobility and the time-varying conformations of proteins. In this article, fundamental biophysical principles of antibody-antigen interaction are discussed, concepts critical for a deeper understanding of the pertinent molecular phenomena are highlighted, and common misunderstandings are identified and debunked.

Dissecting the impact of molecular T-cell HLA mismatches in kidney transplant failure: A retrospective cohort study

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.