Measuring Ambiguity in HLA Typing Methods

Abstract

In hematopoietic stem cell transplantation, donor selection is based primarily on matching donor and patient HLA genes. These genes are highly polymorphic and their typing can result in exact allele assignment at each gene (the resolution at which patients and donors are matched), but it can also result in a set of ambiguous assignments, depending on the typing methodology used. To facilitate rapid identification of matched donors, registries employ statistical algorithms to infer HLA alleles from ambiguous genotypes. Linkage disequilibrium information encapsulated in haplotype frequencies is used to facilitate prediction of the most likely haplotype assignment. An HLA typing with less ambiguity produces fewer high-probability haplotypes and a more reliable prediction. We estimated ambiguity for several HLA typing methods across four continental populations using an information theory-based measure, Shannon's entropy. We used allele and haplotype frequencies to calculate entropy for different sets of 1,000 subjects with simulated HLA typing. Using allele frequencies we calculated an average entropy in Caucasians of 1.65 for serology, 1.06 for allele family level, 0.49 for a 2002-era SSO kit, and 0.076 for single-pass SBT. When using haplotype frequencies in entropy calculations, we found average entropies of 0.72 for serology, 0.73 for allele family level, 0.05 for SSO, and 0.002 for single-pass SBT. Application of haplotype frequencies further reduces HLA typing ambiguity. We also estimated expected confirmatory typing mismatch rates for simulated subjects. In a hypothetical registry with all donors typed using the same method, the entropy values based on haplotype frequencies correspond to confirmatory typing mismatch rates of 1.31% for SSO versus only 0.08% for SBT. Intermediate-resolution single-pass SBT contains the least ambiguity of the methods we evaluated and therefore the most certainty in allele prediction. The presented measure objectively evaluates HLA typing methods and can help define acceptable HLA typing for donor recruitment.

HLA Haplotyping from RNA-seq Data Using Hierarchical Read Weighting

“…Third, HLAforest reports only two haplotypes and does not produce confidence scores at this time. Finally, this method does not yet incorporate population-based frequency data that has been shown to improve the accuracy of all typing methods in well-studied populations [34]…”

Different DRB1*03:01‐DQB1*02:01 haplotypes confer different risk for celiac disease

“…Although celiac disease risk is strongly influenced by combinations of known DR3 and DR4 HLA haplotypes in linkage disequilibrium with DQ, further exploration of the DRB3, DRB4, DRB5 and DRB1 haplotypes in relation to DQ remains mainly unresolved . Many previous studies have tried to assess the risk associated with different HLA genotypes using statistical methods based on case‐control studies . However, analyzing ultra‐polymorphic sequences in celiac disease are yet to be performed.…”

“…12 Many previous studies have tried to assess the risk associated with different HLA genotypes using statistical methods based on case-control studies. 13,14 However, analyzing ultra-polymorphic sequences in celiac disease are yet to be performed.…”

A catalog of HLA type, HLA expression, and neo-epitope candidates in human cancer cell lines

“…In some cases, ambiguous typings were adjusted manually based on population specific HLA frequencies, 13,42 if the origin of the donor of the cell line is reported or pan-population HLA frequencies otherwise. In case of replicate samples, the consensus of the calls is reported (Table S2).…”