Posted on May 25, 2018, 2 p.m.
Whole genome sequencing enables differentiating hundreds of blood type differences, making for more precise matching for future blood transfusions, as published in The Lancet Haematology.
MedSeq Project the first randomized trial of whole genome sequencing in healthy adults was leveraged to develop and validate a computer program which comprehensively and cost effectively determines differences in individuals’ blood types with upwards of 99% accuracy.
A, B, AB, and O blood types are familiar to most people, but there are hundreds of additional blood group antigens on red blood cells, which can trigger immune responses that differ from person to person. The FDA reports up to 16 deaths every year which are attributed to mismatches in red blood cells that are not related to A, B, and O blood groups. There isn’t a method currently available to determine all blood antigens. Whole genome sequencing may be possible to modernize therapy to identify rare and at risk donors and recipients before transfusions and possibly eliminate complications.
Unfortunately blood transfusion complications are common among patients needing chronic transfusion. BloodTyper Algorithm newly developed can be applied to type everyone cost effectively for all relevant blood groups efficiently once sequencing is obtained.
Blood transfusions are among the most common procedures, with upwards of 11 million units of blood transfused each years within the USA each year alone. Complications can be life threatening. The body stimulates production of antibodies when it encounters foreign antigens on donor cells which can destroy the transfused donor cells.
This new approach has potential to be one of the first routine clinical uses for genomics in medical care regarding blood transfusion, which could prevent complications as once the patients are sensitized they have life long risk of hemolytic reactions if another blood transfusion should become needed.
Most testing at present for donors and patients includes only ABO and Rh matching with more than 300 red blood cell antigens and 33 platelet antigens known. The team has created a cost effective way to type may people for these antigens by developing a database using the MedSeq project to develop the bloodTyper algorithm to rapidly and accurately predict individual’s blood group antigen profile from genomic sequences. Compared to the current more labor intensive methods bloodTyper was more than 99% accurate when typing using MedSeq Project participant genomes.
William Lane, MD, PhD notes that without access to sampling from the MedSeq Project and collaboration with MedSeq investigators Robert Green, MD, MPH, and Heidi Rehm, PhD this work would not have been possible. Genome sequencing can now effectively and cost efficiently identify potential transfusion patients who need rare blood types and the donors who can safely provide them.
Materials provided by Brigham and Women's Hospital.
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William J Lane, Connie M Westhoff, Nicholas S Gleadall, Maria Aguad, Robin Smeland-Wagman, Sunitha Vege, Daimon P Simmons, Helen H Mah, Matthew S Lebo, Klaudia Walter, Nicole Soranzo, Emanuele Di Angelantonio, John Danesh, David J Roberts, Nick A Watkins, Willem H Ouwehand, Adam S Butterworth, Richard M Kaufman, Heidi L Rehm, Leslie E Silberstein, Robert C Green, David W. Bates, Carrie Blout, Kurt D. Christensen, Allison L. Cirino, Carolyn Y. Ho, Joel B. Krier, Lisa S. Lehmann, Calum A. MacRae, Cynthia C. Morton, Denise L. Perry, Christine E. Seidman, Shamil R. Sunyaev, Jason L. Vassy, Erica Schonman, Tiffany Nguyen, Eleanor Steffens, Wendi Nicole Betting, Samuel J. Aronson, Ozge Ceyhan-Birsoy, Kalotina Machini, Heather M. McLaughlin, Danielle R. Azzariti, Ellen A. Tsai, Jennifer Blumenthal-Barby, Lindsay Z. Feuerman, Amy L. McGuire, Kaitlyn Lee, Jill O. Robinson, Melody J. Slashinski, Pamela M. Diamond, Kelly Davis, Peter A. Ubel, Peter Kraft, J. Scott Roberts, Judy E. Garber, Tina Hambuch, Michael F. Murray, Isaac Kohane, Sek Won Kong. Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study. The Lancet Haematology, 2018; DOI: 10.1016/S2352-3026(18)30053-X