Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study.

Published

Journal Article

BACKGROUND:There are more than 300 known red blood cell (RBC) antigens and 33 platelet antigens that differ between individuals. Sensitisation to antigens is a serious complication that can occur in prenatal medicine and after blood transfusion, particularly for patients who require multiple transfusions. Although pre-transfusion compatibility testing largely relies on serological methods, reagents are not available for many antigens. Methods based on single-nucleotide polymorphism (SNP) arrays have been used, but typing for ABO and Rh-the most important blood groups-cannot be done with SNP typing alone. We aimed to develop a novel method based on whole-genome sequencing to identify RBC and platelet antigens. METHODS:This whole-genome sequencing study is a subanalysis of data from patients in the whole-genome sequencing arm of the MedSeq Project randomised controlled trial (NCT01736566) with no measured patient outcomes. We created a database of molecular changes in RBC and platelet antigens and developed an automated antigen-typing algorithm based on whole-genome sequencing (bloodTyper). This algorithm was iteratively improved to address cis-trans haplotype ambiguities and homologous gene alignments. Whole-genome sequencing data from 110 MedSeq participants (30 × depth) were used to initially validate bloodTyper through comparison with conventional serology and SNP methods for typing of 38 RBC antigens in 12 blood-group systems and 22 human platelet antigens. bloodTyper was further validated with whole-genome sequencing data from 200 INTERVAL trial participants (15 × depth) with serological comparisons. FINDINGS:We iteratively improved bloodTyper by comparing its typing results with conventional serological and SNP typing in three rounds of testing. The initial whole-genome sequencing typing algorithm was 99·5% concordant across the first 20 MedSeq genomes. Addressing discordances led to development of an improved algorithm that was 99·8% concordant for the remaining 90 MedSeq genomes. Additional modifications led to the final algorithm, which was 99·2% concordant across 200 INTERVAL genomes (or 99·9% after adjustment for the lower depth of coverage). INTERPRETATION:By enabling more precise antigen-matching of patients with blood donors, antigen typing based on whole-genome sequencing provides a novel approach to improve transfusion outcomes with the potential to transform the practice of transfusion medicine. FUNDING:National Human Genome Research Institute, Doris Duke Charitable Foundation, National Health Service Blood and Transplant, National Institute for Health Research, and Wellcome Trust.

Full Text

Duke Authors

Cited Authors

  • Lane, WJ; Westhoff, CM; Gleadall, NS; Aguad, M; Smeland-Wagman, R; Vege, S; Simmons, DP; Mah, HH; Lebo, MS; Walter, K; Soranzo, N; Di Angelantonio, E; Danesh, J; Roberts, DJ; Watkins, NA; Ouwehand, WH; Butterworth, AS; Kaufman, RM; Rehm, HL; Silberstein, LE; Green, RC; MedSeq Project,

Published Date

  • June 2018

Published In

Volume / Issue

  • 5 / 6

Start / End Page

  • e241 - e251

PubMed ID

  • 29780001

Pubmed Central ID

  • 29780001

Electronic International Standard Serial Number (EISSN)

  • 2352-3026

International Standard Serial Number (ISSN)

  • 2352-3026

Digital Object Identifier (DOI)

  • 10.1016/S2352-3026(18)30053-X

Language

  • eng