Les technologies de biologie moléculaire en immunohématologie

Evolution of technology for molecular genotyping in blood group systems

The molecular basis of the blood group antigens was identified first in the 1980s and 1990s. Since then the importance of molecular biology in transfusion medicine has been described extensively by several investigators. Molecular genotyping of blood group antigens is one of the important aspects and is successfully making its way into transfusion medicine. Low-, medium- and high-throughput techniques have been developed for this purpose. Depending on the requirement of the centre like screening for high- or low-prevalence antigens where antisera are not available, correct typing of multiple transfused patients, screening for antigen-negative donor units to reduce the rate of alloimmunization, etc. a suitable technique can be selected. The present review discusses the evolution of different techniques to detect molecular genotypes of blood group systems and how these approaches can be used in transfusion medicine where haemagglutination is of limited value. Currently, this technology is being used in only a few blood banks in India. Hence, there is a need for understanding this technology with all its variations.

The experience of extended blood group genotyping by next-generation sequencing (NGS): investigation of patients with sickle-cell disease

BACKGROUND

Patients suffering from haemoglobinopathies may be treated by red blood cell (RBC) transfusion on a regular basis and then exposed to multiple antigens with a recurrent, potential risk of alloimmunization routinely prevented by extended RBC antigen cross-matching. While time-consuming and labour-intensive serological analyses are the gold standard for RBC typing, genotyping by current high-throughput molecular tools, including next-generation sequencing (NGS), appears to offer a potent alternative.

STUDY DESIGN AND METHODS

The potential of extended blood group genotyping (EBGG) by NGS of 17 genes involved in 14 blood group systems was evaluated in a cohort of 48 patients with sickle-cell disease. Sample preparation and sequencing were simplified and automated for future routine implementation.

RESULTS

Sequencing data were obtained for all DNA samples with two different sequencing machines. Prediction of phenotypes could be made in 12 blood group systems and partially in two other blood group systems (Rh and MNS). Importantly, predicted phenotypes in the MNS (S/s), Duffy, Kidd and Kell systems matched well with serological data (98·9%), when available. Unreferenced alleles in the ACHE and ART4 genes, respectively, involved in the Yt and Dombrock blood groups, were identified, then contributing to extend the current knowledge of blood group molecular genetics.

CONCLUSIONS

Overall, we consider that our strategy for NGS-based EBGG, assisted by a simple method for genotyping exons 1 and 2 of the pairs of homologous genes (i.e. RHD/RHCE and GYPA/GYPB), as well as the future support of potent bioinformatics tools, may be implemented for routine diagnosis in specific populations.