Transplantation Direct (Jul 2024)

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

  • Gregory S. Cohen, BA,
  • Alison J. Gareau, PhD,
  • Melissa A. Kallarakal, BA,
  • Tayyiaba Farooq, MS,
  • Maria P. Bettinotti, PhD,
  • H. Cliff Sullivan, MD,
  • Abeer Madbouly, PhD,
  • Scott M. Krummey, MD, PhD

DOI
https://doi.org/10.1097/TXD.0000000000001639
Journal volume & issue
Vol. 10, no. 7
p. e1639

Abstract

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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.