Concordance between predicted HLA type using next generation sequencing data generated for non-HLA purposes and clinical HLA type

Ann M. Moyer, Brian Dukek, Patti Duellman, Brittany Schneider, Laurie Wakefield, Jennifer M. Skierka, Rajeswari Avula, Aditya V. Bhagwate, Krishna R. Kalari, Justin D. Kreuter, Matthew P. Goetz, Judy C. Boughey, John L. Black, Manish J. Gandhi

Research output: Contribution to journalArticlepeer-review

Abstract

We explored the feasibility of obtaining accurate HLA type using pre-existing NGS data not generated for HLA purposes. 83 exomes and 500 targeted NGS pharmacogenomic panels were analyzed using Omixon HLA Explore, OptiType, and/or HLA-Genotyper software. Results were compared against clinical HLA genotyping. 765 (94.2%) Omixon and 769 (94.7%) HLA-Genotyper of 812 germline allele calls across class I/II loci and 402 (99.5%) of 404 OptiType class I calls were concordant to the second field (i.e. HLA-A*02:01). An additional 19 (2.3%) Omixon, 39 (4.8%) HLA-Genotyper, and 2 (0.5%) OptiType allele calls were first field concordant (i.e. HLA-A*02). Using Omixon, four alleles (0.4%) were discordant and 24 (3.0%) failed to call, while 4 alleles (0.4%) were discordant using HLA-Genotyper. Tumor exomes were also evaluated and were 85.4%, 91.6%, and 100% concordant (Omixon and HLA-Genotyper with 96 alleles tested, and Optitype with 48 class I alleles, respectively). The 15 exomes and 500 pharmacogenomic panels were 100% concordant for each pharmacogenomic allele tested. This work has broad implications spanning future clinical care (pharmacogenomics, tumor response to immunotherapy, autoimmunity, etc.) and research applications.

Original languageEnglish (US)
Pages (from-to)423-429
Number of pages7
JournalHuman Immunology
Volume81
Issue number8
DOIs
StatePublished - Aug 2020

Keywords

  • Exome
  • HLA
  • Human leukocyte antigen
  • MHC
  • Next generation sequencing
  • Pharmacogenetics
  • Pharmacogenomics

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology

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