The utility of imputation for molecular mismatch analysis in solid organ transplantation

HLA Genotype Imputation Results in Largely Accurate Epitope Mismatch Risk Categorization Across Racial Groups

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.

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.

Improving HLA typing imputation accuracy and eplet identification with local next-generation sequencing training data

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.

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.

On the clinical relevance of using complete high-resolution HLA typing for an accurate interpretation of posttransplant immune-mediated graft outcomes

Complete and high-resolution (HR) HLA typing improves the accurate assessment of donor–recipient compatibility and pre-transplant donor-specific antibodies (DSA). However, the value of this information to identify de novo immune-mediated graft events and its impact on outcomes has not been assessed. In 241 donor/recipient kidney transplant pairs, DNA samples were re-evaluated for six-locus (A/B/C/DRB1/DQB1+A1/DPB1) HR HLA typing. De novo anti-HLA antibodies were assessed using solid-phase assays, and dnDSA were classified either (1) as per current clinical practice according to three-locus (A/B/DRB1) low-resolution (LR) typing, estimating donor HLA-C/DQ typing with frequency tables, or (2) according to complete six-locus HR typing. The impact on graft outcomes was compared between groups. According to LR HLA typing, 36 (15%) patients developed dnDSA (LR_dnDSA+). Twenty-nine out of 36 (80%) were confirmed to have dnDSA by HR typing (LR_dnDSA+/HR_dnDSA+), whereas 7 (20%) did not (LR_dnDSA+/HR_dnDSA−). Out of 49 LR_dnDSA specificities, 34 (69%) were confirmed by HR typing whereas 15 (31%) LR specificities were not confirmed. LR_dnDSA+/HR_dnDSA+ patients were at higher risk of ABMR as compared to dnDSA− and LR_dnDSA+/HR_dnDSA− (logRank < 0.001), and higher risk of death-censored graft loss (logRank = 0.001). Both LR_dnDSA+ (HR: 3.51, 95% CI = 1.25–9.85) and LR_dnDSA+/HR_dnDSA+ (HR: 4.09, 95% CI = 1.45–11.54), but not LR_dnDSA+/HR_dnDSA− independently predicted graft loss. The implementation of HR HLA typing improves the characterization of biologically relevant de novo anti-HLA DSA and discriminates patients with poorer graft outcomes.