Genetic prediction of 33 blood group phenotypes using an existing genotype dataset
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Genetic prediction of 33 blood group phenotypes using an existing genotype dataset. / Moslemi, Camous; Sækmose, Susanne G.; Larsen, Rune; Bay, Jakob T.; Brodersen, Thorsten; Didriksen, Maria; Hjalgrim, Henrik; Banasik, Karina; Nielsen, Kaspar R.; Bruun, Mie T.; Dowsett, Joseph; Dinh, Khoa M.; Mikkelsen, Susan; Mikkelsen, Christina; Hansen, Thomas F.; Ullum, Henrik; Erikstrup, Christian; Brunak, Søren; Krogfelt, Karen Angeliki; Storry, Jill R.; Ostrowski, Sisse R.; Olsson, Martin L.; Pedersen, Ole B.
In: Transfusion, Vol. 63, No. 12, 2023, p. 2297-2310.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Genetic prediction of 33 blood group phenotypes using an existing genotype dataset
AU - Moslemi, Camous
AU - Sækmose, Susanne G.
AU - Larsen, Rune
AU - Bay, Jakob T.
AU - Brodersen, Thorsten
AU - Didriksen, Maria
AU - Hjalgrim, Henrik
AU - Banasik, Karina
AU - Nielsen, Kaspar R.
AU - Bruun, Mie T.
AU - Dowsett, Joseph
AU - Dinh, Khoa M.
AU - Mikkelsen, Susan
AU - Mikkelsen, Christina
AU - Hansen, Thomas F.
AU - Ullum, Henrik
AU - Erikstrup, Christian
AU - Brunak, Søren
AU - Krogfelt, Karen Angeliki
AU - Storry, Jill R.
AU - Ostrowski, Sisse R.
AU - Olsson, Martin L.
AU - Pedersen, Ole B.
N1 - Publisher Copyright: © 2023 The Authors. Transfusion published by Wiley Periodicals LLC on behalf of AABB.
PY - 2023
Y1 - 2023
N2 - Background: Accurate blood type data are essential for blood bank management, but due to costs, few of 43 blood group systems are routinely determined in Danish blood banks. However, a more comprehensive dataset of blood types is useful in scenarios such as rare blood type allocation. We aimed to investigate the viability and accuracy of predicting blood types by leveraging an existing dataset of imputed genotypes for two cohorts of approximately 90,000 each (Danish Blood Donor Study and Copenhagen Biobank) and present a more comprehensive overview of blood types for our Danish donor cohort. Study Design and Methods: Blood types were predicted from genome array data using known variant determinants. Prediction accuracy was confirmed by comparing with preexisting serological blood types. The Vel blood group was used to test the viability of using genetic prediction to narrow down the list of candidate donors with rare blood types. Results: Predicted phenotypes showed a high balanced accuracy >99.5% in most cases: A, B, C/c, Coa/Cob, Doa/Dob, E/e, Jka/Jkb, Kna/Knb, Kpa/Kpb, M/N, S/s, Sda, Se, and Yta/Ytb, while some performed slightly worse: Fya/Fyb, K/k, Lua/Lub, and Vel ~99%–98% and CW and P1 ~96%. Genetic prediction identified 70 potential Vel negatives in our cohort, 64 of whom were confirmed correct using polymerase chain reaction (negative predictive value: 91.5%). Discussion: High genetic prediction accuracy in most blood groups demonstrated the viability of generating blood types using preexisting genotype data at no cost and successfully narrowed the pool of potential individuals with the rare Vel-negative phenotype from 180,000 to 70.
AB - Background: Accurate blood type data are essential for blood bank management, but due to costs, few of 43 blood group systems are routinely determined in Danish blood banks. However, a more comprehensive dataset of blood types is useful in scenarios such as rare blood type allocation. We aimed to investigate the viability and accuracy of predicting blood types by leveraging an existing dataset of imputed genotypes for two cohorts of approximately 90,000 each (Danish Blood Donor Study and Copenhagen Biobank) and present a more comprehensive overview of blood types for our Danish donor cohort. Study Design and Methods: Blood types were predicted from genome array data using known variant determinants. Prediction accuracy was confirmed by comparing with preexisting serological blood types. The Vel blood group was used to test the viability of using genetic prediction to narrow down the list of candidate donors with rare blood types. Results: Predicted phenotypes showed a high balanced accuracy >99.5% in most cases: A, B, C/c, Coa/Cob, Doa/Dob, E/e, Jka/Jkb, Kna/Knb, Kpa/Kpb, M/N, S/s, Sda, Se, and Yta/Ytb, while some performed slightly worse: Fya/Fyb, K/k, Lua/Lub, and Vel ~99%–98% and CW and P1 ~96%. Genetic prediction identified 70 potential Vel negatives in our cohort, 64 of whom were confirmed correct using polymerase chain reaction (negative predictive value: 91.5%). Discussion: High genetic prediction accuracy in most blood groups demonstrated the viability of generating blood types using preexisting genotype data at no cost and successfully narrowed the pool of potential individuals with the rare Vel-negative phenotype from 180,000 to 70.
KW - ABO
KW - blood group systems
KW - blood groups
KW - Danish blood type rates
KW - Danish population
KW - Denmark
KW - Diego
KW - Dombrock
KW - donor blood typing
KW - Duffy
KW - erythrocyte antigens
KW - genetic blood typing
KW - Kell
KW - Kidd
KW - Knops
KW - Lewis
KW - Lutheran
KW - MNS
KW - P1PK
KW - Rh
KW - secretor
KW - Vel
KW - Yt
U2 - 10.1111/trf.17575
DO - 10.1111/trf.17575
M3 - Journal article
C2 - 37921035
AN - SCOPUS:85175740684
VL - 63
SP - 2297
EP - 2310
JO - Transfusion
JF - Transfusion
SN - 0041-1132
IS - 12
ER -
ID: 372967678