Quantifying uncertainty of molecular mismatch introduced by mislabeled ancestry using haplotype-based HLA genotype imputation - Matern, Benedict M.; Spierings, Eric; Bandstra, Selle; Madbouly, Abeer; Schaub, Stefan; Weimer, Eric T.; Niemann, Matthias (Frontiers in Genetics, 2024)
Modern histocompatibility algorithms depend on the comparison and analysis of high-resolution HLA protein sequences and structures, especially when considering epitope-based algorithms, which aim to model the interactions involved in antibody or T cell binding. HLA genotype imputation can be performed in the cases where only low/intermediate-resolution HLA genotype is available or if specific loci are missing, and by providing an individuals' race/ethnicity/ancestry information, imputation results can be more accurate. This study assesses the effect of imputing high-resolution genotypes on molecular mismatch scores under a variety of ancestry assumptions. We analyzed a simulated patient-donor dataset and confirmed using two real-world datasets. By comparing molecular matching scores from "ground-truth" high-resolution genotypes against imputed genotypes, we found that correct ancestry assumptions can reduce error introduced during imputation. We conclude that for epitope analysis, imputation is a valuable and low-risk strategy, as long as care is taken regarding epitope analysis context, ancestry assumptions, and (multiple) imputation strategy.