AUTHOR=Matern Benedict M. , Spierings Eric , Bandstra Selle , Madbouly Abeer , Schaub Stefan , Weimer Eric T. , Niemann Matthias 

TITLE=Quantifying uncertainty of molecular mismatch introduced by mislabeled ancestry using haplotype-based HLA genotype imputation

JOURNAL=Frontiers in Genetics

VOLUME=Volume 15 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2024.1444554

DOI=10.3389/fgene.2024.1444554

ISSN=1664-8021

ABSTRACT=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.