AI Article Synopsis

  • The study explores the use of molecular mismatch analysis to predict graft rejection risk in kidney transplants by assessing the compatibility of donor and recipient HLA proteins.
  • Imputation, or algorithmic assignment of high-resolution genotyping, was found to maintain the accuracy of risk categories for graft rejection in a significant majority of cases, even in racially diverse pairs.
  • The results suggest that using imputation is a valuable approach in clinical settings for better predicting long-term graft survival after transplantation.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11191912PMC
http://dx.doi.org/10.1097/TXD.0000000000001639DOI Listing

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