Blood Group Genotyping to Prevent Alloimmunization in Children with Sickle Cell Disease
Notice bibliographique
Résumé
Abstract Introduction:Sickle cell disease (SCD) patients can suffer from devastating complications of their disease as a result of chronic hemolysis and vasculopathy. Chronic blood transfusion can effectively prevent some of the most severe organ damage such as cerebral vasculopathy. However, alloimmunization remains a major concern for chronically transfused patients, even if prophylactic antigen matching is performed for C, E and Kell antigens. Variants in the Rh blood group have been well described in people of African descent and must be considered when transfusing patients with SCD. The main objectives of this study were to determine the frequency of variants in the Rh and Duffy blood groups and to identify compatible blood donors presenting similar Rh variants Methods: Extended erythrocyte phenotypes were routinely done at diagnosis for every SCD patient followed at the SCD clinic of CHU Sainte-Justine. Serologic testing was performed by standard methods. Upon informed consent, genotyping for Rh and Fy blood groups was also proposed to all SCD patients. DNA analyses were used to predict D phenotype (including RHD pseudogene), C, c, E, e antigen profile, FY phenotype with GATA-1 status, and to confirm critical position in the RHD (DAU cluster, zygosity) and RHCEgenes (position 48, 254, 733, 1006). The study was approved by the local Research Ethics Board (REB). Results: 203 SCD patients were evaluated: HbSS 64.3%, HbSC 29.6%, HbSb0 3.1%, HbSb+ 2.5% and HbSDIran 0.5%. ABO blood groups followed published prevalence: Group O 48.7%, A 26.2%, B 20.4%and AB 4.7%. 90.2% of patients had either a normal RHD*01 or RHD*10.00 gene which would predict a normal D+ phenotype. Twenty patients would require D− units (9.8%) to reduce their alloimmunization risk (D−, weak partial D and partial D). The RHCE genotyping results were as followed: normal c allele 61.2%, normal e allele 39.3%, partial e allele 34.1% and weak e allele 17.6%. Most RHCE alleles present in the cohort reflected variants previously reported in individuals of African descent. Most patients were compound heterozygotes. 45.8% of RHCE alleles were considered normal: RHCE*ce, RHCE*Ce and RHCE*cE. Fy(a-b-) phenotype was found in 91.6% of patients (186/203). The list of RHCE variant alleles observed in the cohort was compared to Héma-Québec's (blood supplier for the province of Quebec) African descent blood donor database. For partial e, weak partial e and rare hrB− phenotypes, only D+ donors are available whereas some of the patients are D−. The same is true for one Sec− (RH46, high-prevalence antigen) patient for which no donor is available. As for CEAG− recipients (partial ce-phenotype), two compatible blood donors were identified by screening O− units from donors of African descent. Overall, five patients (2.4%) may not have suitable donors in our blood bank based upon genotype compatibility. Twenty other patients could be added to this calculation because of a variant e allele in trans to a normal E allele. Conclusions: The RH and FY results indicate that very few patients require rare blood units. More than 90% present a normal D antigen and are Fy(a−b−), similar to most blood donors of African ancestry. However, RHCE variants could be more problematic in terms of finding compatible units. This study showed a large array of RH variants, although most are present in heterozygous form accompanied by a normal allele. This could explain the low alloimmunization rate of 3% for Rh antigens observed in this cohort (overall alloimmunization rate of 18.9%). However, as all patients were younger than 18 years old, they will probably be exposed to more blood transfusion during their adult life. Having their RH and FY genotype readily available should make the blood donors' selection easier. Further prospective studies are needed to evaluate if such an approach will lower the alloimmunization rate. Disclosures No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».