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Red Cell Antigen Genotyping Compared to Standard Serological Phenotyping in Sickle Cell Disease Patients in Canada: Potential for Reducing Alloimmunization

2015· article· en· W2592264389 on OpenAlexaffabout
Khalid S. Al‐Habsi, Andrew W. Shih, Rebecca Barty, Grace Wang, Allahna Elahie, Mona Azzam, Reda Siddiqui, Michael Parvizian, Nancy M. Heddle, Uma H. Athale, Mindy Goldman, Madeleine Verhovsek

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsHamilton Regional Laboratory Medicine ProgramHamilton Health SciencesMcMaster Children's HospitalCanadian Blood ServicesMcMaster University
Fundersnot available
KeywordsGenotypingMedicineAntigenImmunologyLeukoreductionBlood transfusionPopulationHemoglobinopathyGenotypeThalassemiaSerologyInternal medicineHemolytic anemiaAntibodyBiologyGenetics

Abstract

fetched live from OpenAlex

Abstract Introduction: Red blood cell (RBC) transfusion is the cornerstone of management in many patients with sickle cell disease (SCD). However, RBC transfusion can be complicated by alloimmunization and hemolytic transfusion reactions in this population despite providing extended phenotype-matched RBC transfusions. This is due to heterogeneity of RBC antigens, unique variant mutations in this population, and genetic mismatch between the blood donor pool and SCD patients in North American settings. In this study, we evaluated the level of discrepancy between RBC antigen genotyping and traditional phenotyping methods and the association of these discrepancies with the presence of RBC alloantibodies in SCD patients at our centre in Canada. Methods: Commencing in January 2015, RBC antigen genotyping has been included in the care for patients with SCD treated at our Hemoglobinopathy Clinic in an academic medical centre. Patient blood samples are sent to a reference laboratory to perform genotyping of RhCE, Kell, Kidd, Duffy, and S antigens. RBC antigen phenotyping was performed locally using both tube and automated solid phase assays. Additional clinical data, demographic and transfusion-related data were obtained from a local transfusion registry databse and thorough clinical chart reviews. Approval from our centre's research ethics board was obtained prior to commencement of data collection. Results: To date, RBC antigen genotyping has been performed on 45/88 SCD patients treated at our centre. The mean age of these patients was 25, and 58% were female. The majority of patients had HbSS SCD genotype (64.4%), or HbSC (26.7%). Overall, 32/45 (71%) of patients had variant mutations detected by genotyping, including 9 (20%) patients with more than one variant mutation. The most common mutation detected was the GATA mutation (n= 23; 51%) resulting in loss of Fyb antigen expression on RBCs, but associated with expression of Fyb on non-erythroid tissues. The RhCE system showed variant mutations resulting in partial expression of antigens in 9 (20%) patients. Alloantibodies were found in 9/36 (25%) patients with either a GATA mutation or no variant mutations. Alloantibodies were found in 2/9 (22.2%) patients with mutations resulting in partial antigen expression. The proportion of patients with any discrepancy between genotyping and phenotyping was 34/45 (75.6%). The largest rates of discordance were seen in the RhCE system, with the c antigen having a kappa of 0.68 and e antigen having a kappa of 0.32 (Table 1). Conclusion: Our results showed a high prevalence of variant mutations and significant discrepancies between genotyping and phenotyping methods, most notably in the RhCE antigen system. Mutations resulting in partial antigen expression were associated with development of alloantibodies in 22.2% of patients in our study, which may have been prevented with a genotype-based antigen-matching strategy. Additionally, knowledge of presence of GATA mutation will enhance feasibility of antigen matching for affected patients, who may have otherwise required RBC units negative for Fyb based on local policies. To our knowledge these results represent the first published data from a Canadian centre, showing similar rates of discrepancy between traditional phenotyping methods and RBC antigen genotyping as reported in other regions. Although phenotype-based matching strategies are used in many centres, these strategies can place patients with partial RBC antigen variant mutations at a direct increased risk of alloimmunization. Thus genotype-based antigen-matching strategies should be considered for transfusion of matched RBCs in patients with SCD. Table 1. Blood Group Antigen Frequency In SCD Patients By Phenotyping/Genotyping with Level of Agreement Between Both Methods Antigen Phenotype Genotype Kappa Positive Negative Positive Negative Partial C 37.78 62.22 28.89 62.22 8.89 0.82 c 88.89 11.11 80.00 11.11 8.89 0.68 E 13.33 86.67 13.33 86.67 1.00 e 97.78 2.22 88.89 2.22 8.89 0.32 Fya 13.33 86.67 13.33 86.67 1.00 Fyb 22.22 68.89 26.67 73.33 0.94 Jka 80.00 20.00 82.22 17.78 0.93 Jkb 51.11 48.89 55.56 44.44 0.91 S 28.89 42.22 46.67 53.33 1.00 s 51.11 6.67 86.67 13.33 1.00 Disclosures No relevant conflicts of interest to declare.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.221
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2015
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