William J Lane1, Connie M Westhoff2, Nicholas S Gleadall3, Maria Aguad4, Robin Smeland-Wagman4, Sunitha Vege2, Daimon P Simmons4, Helen H Mah4, Matthew S Lebo5, Klaudia Walter6, Nicole Soranzo7, Emanuele Di Angelantonio8, John Danesh9, David J Roberts10, Nick A Watkins11, Willem H Ouwehand12, Adam S Butterworth8, Richard M Kaufman4, Heidi L Rehm13, Leslie E Silberstein14, Robert C Green15. 1. Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. Electronic address: wlane@bwh.harvard.edu. 2. New York Blood Center, New York, NY, USA. 3. Department of Haematology, University of Cambridge, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge, UK. 4. Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA. 5. Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Laboratory for Molecular Medicine, Boston, MA, USA; Partners Personalized Medicine, Boston, MA, USA. 6. Wellcome Trust Sanger Institute, Hinxton, UK. 7. Department of Haematology, University of Cambridge, Cambridge, UK; Wellcome Trust Sanger Institute, Hinxton, UK; Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK. 8. Medical Research Council and British Heart Foundation Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK; Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK. 9. Medical Research Council and British Heart Foundation Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK; Department of Public Health and Primary Care, and British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK; Wellcome Trust Sanger Institute, Hinxton, UK; Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK. 10. National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK; NHS Blood and Transplant-Oxford Centre, Oxford, UK; Biomedical Research Centre Haematology Theme and Radcliffe Department of Medicine, University of Oxford, Oxford, UK. 11. National Health Service (NHS) Blood and Transplant, Cambridge, UK. 12. Department of Haematology, University of Cambridge, Cambridge, UK; Department of Public Health and Primary Care, and British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge, UK; NHS Blood and Transplant-Oxford Centre, Oxford, UK. 13. Harvard Medical School, Boston, MA, USA; Laboratory for Molecular Medicine, Boston, MA, USA; Partners Personalized Medicine, Boston, MA, USA; Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology and Harvard, Boston, MA, USA. 14. Division of Transfusion Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. 15. Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Partners Personalized Medicine, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology and Harvard, Boston, MA, USA.
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.
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.
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