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

Lancet Haematol
Authors
Keywords
Abstract

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.

Year of Publication
2018
Journal
Lancet Haematol
Volume
5
Issue
6
Pages
e241-e251
Date Published
2018 Jun
ISSN
2352-3026
DOI
10.1016/S2352-3026(18)30053-X
PubMed ID
29780001
PubMed Central ID
PMC6438177
Links
Grant list
RF1 AG047866 / AG / NIA NIH HHS / United States
T32 HL007627 / HL / NHLBI NIH HHS / United States
U01 AG024904 / AG / NIA NIH HHS / United States
P60 AR047782 / AR / NIAMS NIH HHS / United States
U19 HD077671 / HD / NICHD NIH HHS / United States
R01 CA154517 / CA / NCI NIH HHS / United States
U01 HG006500 / HG / NHGRI NIH HHS / United States
P01 HL095489 / HL / NHLBI NIH HHS / United States
WT_ / Wellcome Trust / United Kingdom
U01 HG008685 / HG / NHGRI NIH HHS / United States
R03 HG008809 / HG / NHGRI NIH HHS / United States