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

被引:74
作者
Lane, William J. [1 ,4 ]
Westhoff, Connie M. [5 ]
Gleadall, Nicholas S. [6 ,12 ]
Aguad, Maria [1 ]
Smeland-Wagman, Robin [1 ]
Vege, Sunitha [5 ]
Simmons, Daimon P. [1 ]
Mah, Helen H. [1 ]
Lebo, Matthew S. [1 ,4 ,13 ,14 ]
Walter, Klaudia [15 ]
Soranzo, Nicole [6 ,15 ,16 ]
Di Angelantonio, Emanuele [7 ,8 ,9 ,16 ]
Danesh, John [7 ,8 ,9 ,10 ,11 ,15 ,16 ]
Roberts, David J. [9 ,17 ,18 ]
Watkins, Nick A. [12 ]
Ouwehand, Willem H. [6 ,10 ,11 ,12 ,17 ]
Butterworth, Adam S. [7 ,8 ,9 ,16 ]
Kaufman, Richard M. [1 ]
Rehm, Heidi L. [4 ,13 ,14 ,19 ,20 ]
Silberstein, Leslie E. [2 ,4 ]
Green, Robert C. [3 ,4 ,14 ,20 ]
机构
[1] Brigham & Womens Hosp, Dept Pathol, 75 Francis St, Boston, MA 02115 USA
[2] Brigham & Womens Hosp, Div Transfus Med, 75 Francis St, Boston, MA 02115 USA
[3] Brigham & Womens Hosp, Dept Med, Div Genet, 75 Francis St, Boston, MA 02115 USA
[4] Harvard Med Sch, Boston, MA USA
[5] New York Blood Ctr, New York, NY 10021 USA
[6] Univ Cambridge, Dept Haematol, Cambridge, England
[7] Univ Cambridge, Med Res Council, Cambridge, England
[8] Univ Cambridge, British Heart Fdn, Cardiovasc Epidemiol Unit, Cambridge, England
[9] Univ Cambridge, Natl Inst Hlth, Res Blood & Transplant Res Unit Donor Hlth & Geno, Cambridge, England
[10] Univ Cambridge, Dept Publ Hlth & Primary Care, Cambridge, England
[11] Univ Cambridge, British Heart Fdn, Cambridge Ctr Excellence, Dept Med, Cambridge, England
[12] Natl Hlth Serv NHS Blood & Transplant, Cambridge, England
[13] Lab Mol Med, Boston, MA USA
[14] Partners Personalized Med, Boston, MA USA
[15] Wellcome Trust Sanger Inst, Hinxton, England
[16] Hlth Data Res UK, Wellcome Genome Campus, Cambridge Substant Site, Hinxton, England
[17] NHS Blood & Transplant Oxford Ctr, Oxford, England
[18] Univ Oxford, Biomed Res Ctr, Haematol Theme & Radcliffe Dept Med, Oxford, England
[19] Massachusetts Gen Hosp, Dept Med, Boston, MA 02114 USA
[20] Broad Inst MIT & Harvard, Boston, MA USA
基金
英国惠康基金;
关键词
HEALTHY ADULT; GROUP SYSTEMS; DATABASE; DNA; ALLOANTIBODIES; PREDICTION; DONORS; PROOF; TIME;
D O I
10.1016/S2352-3026(18)30053-X
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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 x 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 x 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 center dot 5% concordant across the first 20 MedSeq genomes. Addressing discordances led to development of an improved algorithm that was 99 center dot 8% concordant for the remaining 90 MedSeq genomes. Additional modifications led to the final algorithm, which was 99 center dot 2% concordant across 200 INTERVAL genomes (or 99 center dot 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.
引用
收藏
页码:E241 / E251
页数:11
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