Red Cell Antigen Genotyping Compared to Standard Serological Phenotyping in Sickle Cell Disease Patients in Canada: Potential for Reducing Alloimmunization
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».