Dataset Information

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.

SUBMITTER: Paunic V

PROVIDER: S-EPMC3430707 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Measuring ambiguity in HLA typing methods.

Paunić Vanja V Gragert Loren L Madbouly Abeer A Freeman John J Maiers Martin M

PloS one 20120829 8

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 fr ...[more]

PMID: 22952712

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Project description:Accurate and full-length typing of the HLA region is important in many clinical and research settings. With the advent of next generation sequencing (NGS), several HLA typing algorithms have been developed, including many that are applicable to whole exome sequencing (WES). However, most of these solutions operate by providing the closest-matched HLA allele among the known alleles in IPD-IMGT/HLA Database. These database-matching approaches have demonstrated very high performance when typing well characterized HLA alleles. However, as they rely on the completeness of the HLA database, they are not optimal for detecting novel or less well characterized alleles. Furthermore, the database-matching approaches are also not adequate in the context of cancer, where a comprehensive characterization of somatic HLA variation and expression patterns of a tumor's HLA locus may guide therapy and clinical outcome, because of the pivotal role HLA alleles play in tumor antigen recognition and immune escape. Here, we describe a personalized HLA typing approach applied to WES data that leverages the strengths of database-matching approaches while simultaneously allowing for the discovery of novel HLA alleles and tumor-specific HLA variants, through the systematic integration of germline and somatic variant calling. We applied this approach on WES from 10 metastatic melanoma patients and validated the HLA typing results using HLA targeted NGS sequencing from patients where at least one HLA germline candidate was detected on Class I HLA. Targeted NGS sequencing confirmed 100% performance for the 1st and 2nd fields. In total, five out of the six detected HLA germline variants were because of Class I ambiguities at the third or fourth fields, and their detection recovered the correct HLA allele genotype. The sixth germline variant let to the formal discovery of a novel Class I allele. Finally, we demonstrated a substantially improved somatic variant detection accuracy in HLA alleles with a 91% of success rate in simulated experiments. The approach described here may allow the field to genotype more accurately using WES data, leading to the discovery of novel HLA alleles and help characterize the relationship between somatic variation in the HLA region and immunosurveillance.

Dataset Information

Measuring ambiguity in HLA typing methods.

Publications

Measuring ambiguity in HLA typing methods.

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