Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study.
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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
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Journal | Lancet Haematol
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Volume | 5
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Issue | 6
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Pages | e241-e251
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Date Published | 2018 Jun
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ISSN | 2352-3026
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DOI | 10.1016/S2352-3026(18)30053-X
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PubMed ID | 29780001
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PubMed Central ID | PMC6438177
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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
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