Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study

First investigation of RH gene polymorphism in patients with sickle cell disease and associated blood donors in Cameroon, Central Africa

BACKGROUND

Although genetic polymorphism of the RH blood group system is well known in sub-Saharan Africa, national/regional specificities still remain to be described precisely. For the first time in Cameroon, Central Africa, and in order to better characterize the molecular basis driving RH phenotype variability, as well as to identify the main antigens that may be potentially responsible for alloimmunization, we sought 1) to study the RH genes in a cohort of 109 patients with sickle cell disease; 2) to study the same genes in the corresponding donors whose red blood cells (RBCs) were transfused to the patients (108 donors in 98 patients); 3) to predict RH phenotype on the basis of the molecular data and compare the results with serologic testing; and 4) to identify retrospectively patients at risk for alloimmunization.

MATERIALS AND METHODS

In order to generate an exhaustive dataset, the RH genes of all patient and donor samples were systematically investigated 1) by quantitative multiplex PCR of short fluorescent fragments (QMPSF) for characterization of RHD gene zygosity and potential structural variants (SVs), and 2) by Sanger sequencing for identification of single nucleotide variants (SNVs). Subsequent to molecular analysis, the genotypes and RH phenotype were deduced and predicted, respectively, from reference databases.

RESULTS

In a total of 217 Cameroonian individuals, as many as 24 and up to 22 variant alleles were identified in the RHD and RHCE genes, respectively, in addition to the reference alleles. Interestingly, 65 patients with SCD (66.3%) were assumed to be exposed to one or more undesirable RH antigen(s) with varying degrees of clinical relevance.

DISCUSSION

Beyond the comprehensive report of the nature and distribution of RH variant alleles in a subset of Cameroonian patients treated by transfusion therapy, this work highlights the need for an extensive review of current practice, including routine serologic typing procedures, preferably in the near future.

Simultaneous high throughput genotyping of 36 blood group systems using NGS based on probe capture technology

Human blood group antigen has important biological functions, and transfusion of incompatible blood can cause alloimmunization and may lead to serious hemolytic reactions. Currently, serological methods are most commonly used in blood group typing. However, this technique has certain limitations and cannot fully meet the increasing demand for the identification of blood group antigens. This study describes a next-generation sequencing (NGS) technology platform based on exon and flanking region capture probes to detect full coding exon and flanking intron regions of the 36 blood group systems, providing a new high-throughput method for the identification of blood group antigens. The 871 capture probes were designed for the exon and flanking intron sequences of 36 blood group system genes, and synchronization analysis for 36 blood groups was developed. The library for NGS was tested using the MiSeq Sequencing Reagent Kit (v2, 300 cycles) by Illumina NovaSeq, and the data were analyzed by the CLC Genomics Workbench 21.0 software. A total of 199 blood specimens have been sequenced for the 41 genes from 36 blood groups. Among them, heterozygote genotypes were found in the ABO, Rh, MNS, Lewis, Duffy, Kidd, Diego, Gerbich, Dombrock, Globoside, JR, LAN, and Landsteiner-Wiene blood group systems. Only the homozygous genotype was found in the remaining 22 blood group systems. The obtained data in the NGS method shows a good correlation (99.98 %) with those of the polymerase chain reaction-sequence-based typing. An NGS technology platform for 36 blood group systems genotyping was successfully established, which has the characteristics of high accuracy, high throughput, and wide coverage.

Characterization of Blood Group Variants in an Omani Population by Comparison of Whole Genome Sequencing and Serology

Although blood group variation was first described over a century ago, our understanding of the genetic variation affecting antigenic expression on the red blood cell surface in many populations is lacking. This deficit limits the ability to accurately type patients, especially as serological testing is not available for all described blood groups, and targeted genotyping panels may lack rare or population-specific variants. Here, we perform serological assays across 24 antigens and whole genome sequencing on 100 Omanis, a population underrepresented in genomic databases. We inferred blood group phenotypes using the most commonly typed genetic variants. The comparison of serological to inferred phenotypes resulted in an average concordance of 96.9%. Among the 22 discordances, we identify seven known variants in four blood groups that, to our knowledge, have not been previously reported in Omanis. Incorporating these variants for phenotype inference, concordance increases to 98.8%. Additionally, we describe five candidate variants in the Lewis, Lutheran, MNS, and P1 blood groups that may affect antigenic expression, although further functional confirmation is required. Notably, we identify several blood group alleles most common in African populations, likely introduced to Oman by gene flow over the last thousand years. These findings highlight the need to evaluate individual populations and their population history when considering variants to include in genotype panels for blood group typing. This research will inform future work in blood banks and transfusion services.

Machine learning to optimize automated RH genotyping using whole-exome sequencing data

ABSTRACT

Rh phenotype matching reduces but does not eliminate alloimmunization in patients with sickle cell disease (SCD) due to RH genetic diversity that is not distinguishable by serological typing. RH genotype matching can potentially mitigate Rh alloimmunization but comprehensive and accessible genotyping methods are needed. We developed RHtyper as an automated algorithm to predict RH genotypes using whole-genome sequencing (WGS) data with high accuracy. Here, we adapted RHtyper for whole-exome sequencing (WES) data, which are more affordable but challenged by uneven sequencing coverage and exacerbated sequencing read misalignment, resulting in uncertain predictions for (1) RHD zygosity and hybrid alleles, (2) RHCE∗C vs. RHCE∗c alleles, (3) RHD c.1136C>T zygosity, and (4) RHCE c.48G>C zygosity. We optimized RHtyper to accurately predict RHD and RHCE genotypes using WES data by leveraging machine learning models and improved the concordance of WES with WGS predictions from 90.8% to 97.2% for RHD and 96.3% to 98.2% for RHCE among 396 patients in the Sickle Cell Clinical Research and Intervention Program. In a second validation cohort of 3030 cancer survivors (15.2% Black or African Americans) from the St. Jude Lifetime Cohort Study, the optimized RHtyper reached concordance rates between WES and WGS predications to 96.3% for RHD and 94.6% for RHCE. Machine learning improved the accuracy of RH predication using WES data. RHtyper has the potential, once implemented, to provide a precision medicine-based approach to facilitate RH genotype-matched transfusion and improve transfusion safety for patients with SCD. This study used data from clinical trials registered at ClinicalTrials.gov as #NCT02098863 and NCT00760656.

Extensive red blood cell matching considering patient alloimmunization risk

BACKGROUND AND OBJECTIVES

Red blood cell (RBC) transfusions pose a risk of alloantibody development in patients. For patients with increased alloimmunization risk, extended preventive matching is advised, encompassing not only the ABO-D blood groups but also the most clinically relevant minor antigens: C, c, E, e, K, Fya, Fyb, Jka, Jkb, S and s. This study incorporates patient-specific data and the clinical consequences of mismatching into the allocation process.

MATERIALS AND METHODS

We have redefined the MINimize Relative Alloimmunization Risks (MINRAR) model to include patient group preferences in selecting RBC units from a finite supply. A linear optimization approach was employed, considering both antigen immunogenicity and the clinical impact of mismatches for specific patient groups. We also explore the advantages of informing the blood bank about scheduled transfusions, allowing for a more strategic blood distribution. The model is evaluated using historical data from two Dutch hospitals, measuring shortages and minor antigen mismatches.

RESULTS

The updated model, emphasizing patient group-specific considerations, achieves a similar number of mismatches as the original, yet shifts mismatches among patient groups and antigens, reducing expected alloimmunization consequences. Simultaneous matching for multiple hospitals at the distribution centre level, considering scheduled demands, led to a 30% decrease in mismatches and a 92% reduction in shortages.

CONCLUSION

The reduction of expected alloimmunization consequences by incorporating patient group preferences demonstrates our strategy's effectiveness for patient health. Substantial reductions in mismatches and shortages with multi-hospital collaboration highlights the importance of sharing information in the blood supply chain.

Transfusing children with sickle cell disease using blood group genotyping when the pool of Black donors is limited

BACKGROUND

Red blood cell transfusion is an effective treatment for patients with sickle cell disease (SCD). Alloimmunization can occur after a single transfusion, limiting further usage of blood transfusion. It is recommended to match for the ABO, D, C, E, and K antigens to reduce risks of alloimmunization. However, availability of compatible blood units can be challenging for blood providers with a limited number of Black donors.

STUDY DESIGN AND METHODS

A prospective cohort of 205 pediatric patients with SCD was genotyped for the RH and FY genes. Transfusion and alloimmunization history were collected. Our capacity to find RhCE-matched donors was evaluated using a database of genotyped donors.

RESULTS

Nearly 9.8% of patients carried a partial D variant and 5.9% were D-. Only 45.9% of RHCE alleles were normal, with the majority of variants affecting the RH5 (e) antigen. We found an alloimmunization prevalence of 20.7% and a Rh alloimmunization prevalence of 7.1%. Since Black donors represented only 1.40% of all blood donors in our province, D- Caucasian donors were mostly used to provide phenotype matched products. Compatible blood for patients with rare Rh variants was found only in Black donors. A donor with compatible RhCE could be identified for all patients.

CONCLUSION

Although Rh-compatible donors were identified, blood units might not be available when needed and/or the extended phenotype or ABO group might not match the patient. A greater effort has to be made for the recruitment of Black donors to accommodate patients with SCD.

A machine-learning method for biobank-scale genetic prediction of blood group antigens

A key element for successful blood transfusion is compatibility of the patient and donor red blood cell (RBC) antigens. Precise antigen matching reduces the risk for immunization and other adverse transfusion outcomes. RBC antigens are encoded by specific genes, which allows developing computational methods for determining antigens from genomic data. We describe here a classification method for determining RBC antigens from genotyping array data. Random forest models for 39 RBC antigens in 14 blood group systems and for human platelet antigen (HPA)-1 were trained and tested using genotype and RBC antigen and HPA-1 typing data available for 1,192 blood donors in the Finnish Blood Service Biobank. The algorithm and models were further evaluated using a validation cohort of 111,667 Danish blood donors. In the Finnish test data set, the median (interquartile range [IQR]) balanced accuracy for 39 models was 99.9 (98.9-100)%. We were able to replicate 34 out of 39 Finnish models in the Danish cohort and the median (IQR) balanced accuracy for classifications was 97.1 (90.1-99.4)%. When applying models trained with the Danish cohort, the median (IQR) balanced accuracy for the 40 Danish models in the Danish test data set was 99.3 (95.1-99.8)%. The RBC antigen and HPA-1 prediction models demonstrated high overall accuracies suitable for probabilistic determination of blood groups and HPA-1 at biobank-scale. Furthermore, population-specific training cohort increased the accuracies of the models. This stand-alone and freely available method is applicable for research and screening for antigen-negative blood donors.

Next Generation Sequencing of Red Blood Cell Antigens in Transfusion Medicine: Systematic Review and Meta-Analysis

Molecular analysis of blood groups is important in transfusion medicine, allowing the prediction of red blood cell (RBC) antigens. Many blood banks use single nucleotide variant (SNV) based methods for blood group analysis. While this is a well-established approach, it is limited to the polymorphisms included in genotyping panels. Thus, variants that alter antigenic expression may be ignored, resulting in incorrect prediction of phenotypes. The popularization of next-generation sequencing (NGS) has led to its application in transfusion medicine, including for RBC antigens determination. The present review/meta-analysis aimed to evaluate the applicability of the NGS for the prediction of RBC antigens. A systematic review was conducted following a comprehensive literature search in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. Studies were selected based on predefined criteria and evaluated using Strengthening the Reporting of Observational studies in Epidemiology guidelines. The characteristics and results of the studies were extracted and meta-analysis was performed to verify the agreement between results from standard molecular methods and NGS. Kell (rs8176058), Duffy (rs2814778, rs12078), or Kidd (rs1085396) alleles were selected as a model for comparisons. Additionally, results are presented for other blood group systems. Of the 864 eligible studies identified, 10 met the inclusion criteria and were selected for meta-analysis. The pooled concordance proportion for NGS compared to other methods ranged from 0.982 to 0.994. The sequencing depth coverage was identified as crucial parameters for the reliability of the results. Some studies reported difficulty in analyzing more complex systems, such as Rh and MNS, requiring the adoption of specific strategies. NGS is a technology capable of predicting blood group phenotypes and has many strengths such as the possibility of simultaneously analyzing hundred individuals and gene regions, and the ability to provide comprehensive genetic analysis, which is useful in the description of new alleles and a better understanding of the genetic basis of blood groups. The implementation of NGS in the routine of blood banks depends on several factors such as cost reduction, the availability of widely validated panels, the establishment of clear quality parameters and access to bioinformatics analysis tools that are easy to access and operate.

Prevalence and molecular basis of null blood group phenotypes in the Korean population: Analysis using a public database

BACKGROUND

Null phenotypes are characterized by complete absence of all antigens within a blood group system and caused by null variants (e.g., nonsense, frameshift, initiation codon, and canonical splice site variants) in the genes encoding the antigens. Knowing the prevalence and molecular basis of null phenotypes is essential to establish a rare donor program, and the aim of this study was to reveal the prevalence and molecular basis of null phenotypes using the Korean Reference Genome Database (KRGDB) containing whole-genome sequences of 1722 Korean individuals.

STUDY DESIGN AND METHODS

Population allele frequencies of null alleles in 39 blood group systems except ABO, MNS, Rh, Lewis, and FORS were obtained from the KRGDB. The prevalence of null phenotypes was calculated using Hardy-Weinberg equation.

RESULTS

The prevalence of null phenotypes were estimated to be less than 0.001% in all blood group systems except JR and SID. The prevalence of the Jr(a-) and Sd(a-) phenotypes were estimated to be 0.0453% and 0.2323%, respectively. The most frequent null allele of the JR system was ABCG2*01N.01, accounting for approximately 85% of null alleles.

DISCUSSION

Our approach using a public database allowed us to investigate the prevalence and molecular basis of null phenotypes in the Korean population, which will serve as a guide for establishing a rare donor program in Korea. Considering the clinical significance, Jr(a-) is an important null phenotype that should be typed in the Korean population, and molecular assays targeting the most frequent allele ABCG2*01N.01 may be useful in detecting this phenotype.

Genetic prediction of 33 blood group phenotypes using an existing genotype dataset

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.

Association between ABO blood group/genotype and COVID-19 in a Japanese population

An association between coronavirus disease 2019 (COVID-19) and the ABO blood group has been reported. However, such an association has not been studied in the Japanese population on a large scale. Little is known about the association between COVID-19 and ABO genotype. This study investigated the association between COVID-19 and ABO blood group/genotype in a large Japanese population. All Japanese patients diagnosed with COVID-19 were recruited through the Japan COVID-19 Task Force between February 2020 and October 2021. We conducted a retrospective cohort study involving 1790 Japanese COVID-19 patients whose DNA was used for a genome-wide association study. We compared the ABO blood group/genotype in a healthy population (n = 611, control) and COVID-19 patients and then analyzed their associations and clinical outcomes. Blood group A was significantly more prevalent (41.6% vs. 36.8%; P = 0.038), and group O was significantly less prevalent (26.2% vs. 30.8%; P = 0.028) in the COVID-19 group than in the control group. Moreover, genotype OO was significantly less common in the COVID-19 group. Furthermore, blood group AB was identified as an independent risk factor for most severe diseases compared with blood group O [aOR (95% CI) = 1.84 (1.00-3.37)]. In ABO genotype analysis, only genotype AB was an independent risk factor for most severe diseases compared with genotype OO. Blood group O is protective, whereas group A is associated with the risk of infection. Moreover, blood group AB is associated with the risk of the "most" severe disease.

Irregular Antibody Screening Using a Microdroplet Platform

The screening procedure for antibodies is considered the most tedious among the three pretransfusion operations, i.e., ABO and Rhesus (Rh) typing, irregular antibody screening/identification, and crossmatching tests. The commonly used screening method for irregular antibodies in clinics at present is a manual polybrene test (MP). The MP test involves numerous reagent replacement and centrifuge procedures, and the sample volume is expected to be relatively less. Herein, screening red blood cells (RBCs) and serum irregular antibodies are encapsulated in microdroplets with a diameter of ~300 μm for a hemagglutination reaction. Owing to the advantage of spatial limitation in microdroplets, screening RBCs and irregular antibodies can be directly agglutinated, thereby eliminating the need for centrifugation and the addition of reagents to promote agglutination, as required by the MP method. Furthermore, the results for a large number of repeated tests can be concurrently obtained, further simplifying the steps of irregular antibody screening and increasing accuracy. Eight irregular antibodies are screened using the proposed platform, and the results are consistent with the MP method. Moreover, the volume of blood samples and antibodies can be reduced to 10 μL and 5 μL, respectively, which is ten times less than that using the MP method.

Haplotype sequence collection of ABO blood group alleles by long-read sequencing reveals putative A1-diagnostic variants

In the era of blood group genomics, reference collections of complete and fully resolved blood group gene alleles have gained high importance. For most blood groups, however, such collections are currently lacking, as resolving full-length gene sequences as haplotypes (ie, separated maternal/paternal origin) remains exceedingly difficult with both Sanger and short-read next-generation sequencing. Using the latest third-generation long-read sequencing, we generated a collection of fully resolved sequences for all 6 main ABO allele groups: ABO∗A1/A2/B/O.01.01/O.01.02/O.02. We selected 77 samples from an ABO genotype data set (n = 25 200) of serologically typed Swiss blood donors. The entire ABO gene was amplified in 2 overlapping long-range polymerase chain reactions (covering ∼23.6 kb) and sequenced by long-read Oxford Nanopore sequencing. For quality validation, 2 samples per ABO group were resequenced using Illumina and Pacific Biosciences technology. All 154 full-length ABO sequences were resolved as haplotypes. We observed novel, distinct sequence patterns for each ABO group. Most genetic diversity was found between, not within, ABO groups. Phylogenetic tree and haplotype network analyses highlighted distinct clades of each ABO group. Strikingly, our data uncovered 4 genetic variants putatively specific for ABO∗A1, for which direct diagnostic targets are currently lacking. We validated A1-diagnostic potential using whole-genome data (n = 4872) of a multiethnic cohort. Overall, our sequencing strategy proved powerful for producing high-quality ABO haplotypes and holds promise for generating similar collections for other blood groups. The publicly available collection of 154 haplotypes will serve as a valuable resource for molecular analyses of ABO, as well as studies about the function and evolutionary history of ABO.

The Development and Consequences of Red Blood Cell Alloimmunization

While red blood cell (RBC) transfusion is the most common medical intervention in hospitalized patients, as with any therapeutic, it is not without risk. Allogeneic RBC exposure can result in recipient alloimmunization, which can limit the availability of compatible RBCs for future transfusions and increase the risk of transfusion complications. Despite these challenges and the discovery of RBC alloantigens more than a century ago, relatively little has historically been known regarding the immune factors that regulate RBC alloantibody formation. Through recent epidemiological approaches, in vitro-based translational studies, and newly developed preclinical models, the processes that govern RBC alloimmunization have emerged as more complex and intriguing than previously appreciated. Although common alloimmunization mechanisms exist, distinct immune pathways can be engaged, depending on the target alloantigen involved. Despite this complexity, key themes are beginning to emerge that may provide promising approaches to not only actively prevent but also possibly alleviate the most severe complications of RBC alloimmunization.

ABO Genotyping finds more A2 to B kidney transplant opportunities than lectin-based subtyping

ABO compatibility is important for kidney transplantation, with longer waitlist times for blood group B kidney transplant candidates. However, kidneys from non-A₁ (eg, A₂) subtype donors, which express less A antigen, can be safely transplanted into group B recipients. ABO subtyping is routinely performed using anti-A₁ lectin, but DNA-based genotyping is also possible. Here, we compare lectin and genotyping testing. Lectin and genotype subtyping was performed on 554 group A deceased donor samples at 2 transplant laboratories. The findings were supported by 2 additional data sets of 210 group A living kidney donors and 124 samples with unclear lectin testing sent to a reference laboratory. In deceased donors, genotyping found 65% more A₂ donors than lectin testing, most with weak lectin reactivity, a finding supported in living donors and samples sent for reference testing. DNA sequencing and flow cytometry showed that the discordances were because of several factors, including transfusion, small variability in A antigen levels, and rare ABO∗A2.06 and ABO∗A2.16 sequences. Although lectin testing is the current standard for transplantation subtyping, genotyping is accurate and could increase A₂ kidney transplant opportunities for group B candidates, a difference that should reduce group B wait times and improve transplant equity.

DOCK2 is involved in the host genetics and biology of severe COVID-19

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge^1–5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

A genome-wide association study highlights a variant in DOCK2, which is common in East Asian populations but rare in Europeans, as a host genetic risk factor for severe COVID-19.

Clodronate inhibits alloimmunization against distinct red blood cell alloantigens in mice

BACKGROUND

Alloimmunization can be a significant barrier to red blood cell (RBC) transfusion. While alloantigen matching protocols hold promise in reducing alloantibody formation, transfusion-dependent patients can still experience RBC alloimmunization and associated complications even when matching protocols are employed. As a result, complementary strategies capable of actively preventing alloantibody formation following alloantigen exposure are warranted.

STUDY DESIGN AND METHODS

We examined whether pharmacological removal of macrophages using clodronate may provide an additional strategy to actively inhibit RBC alloimmunization using two preclinical models of RBC alloimmunization. To accomplish this, mice were treated with clodronate, followed by transfusion of RBCs expressing the HOD (HEL, OVA, and Duffy) or KEL antigens. On days 5 and 14 post transfusion, anti-HOD or anti-KEL IgM and IgG antibodies were evaluated.

RESULTS

Low dose clodronate effectively eliminated key marginal zone macrophage populations from the marginal sinus. Prior treatment with clodronate, but not empty liposomes, also significantly inhibited IgM and IgG anti-HOD alloantibody formation following transfusion of HOD RBCs. Similar exposure to clodronate inhibited IgM and IgG antibody formation following KEL RBC transfusion.

CONCLUSIONS

Clodronate can inhibit anti-HOD and anti-KEL antibody formation following RBC transfusion in preclinical models. These results suggest that clodronate may provide an alternative approach to actively inhibit or prevent the development of alloantibodies following RBC transfusion, although future studies will certainly be needed to fully explore this possibility.

Using Whole Genome Sequencing to Characterize Clinically Significant Blood Groups Among Healthy Older Australians

There have been no comprehensive studies of a full range of blood group polymorphisms within the Australian population. This problem is compounded by the absence of any databases carrying genomic information on chronically transfused patients and low frequency blood group antigens in Australia. Here, we use RBCeq, a web server–based blood group genotyping software, to identify unique blood group variants among Australians and compare the variation detected vs global data. Whole-genome sequencing data were analyzed for 2796 healthy older Australians from the Medical Genome Reference Bank and compared with data from 1000 Genomes phase 3 (1KGP3) databases comprising 661 African, 347 American, 503 European, 504 East Asian, and 489 South Asian participants. There were 661 rare variants detected in this Australian sample population, including 9 variants that had clinical associations. Notably, we identified 80 variants that were computationally predicted to be novel and deleterious. No clinically significant rare or novel variants were found associated with the genetically complex ABO blood group system. For the Rh blood group system, 2 novel and 15 rare variants were found. Our detailed blood group profiling results provide a starting point for the creation of an Australian blood group variant database.

The genomic landscape of blood groups in Indigenous Australians in remote communities

Background

Methods and materials

Results

Conclusion

Application of Blood Group Genotyping by Next-Generation Sequencing in Various Immunohaematology Cases

BACKGROUND

Next-generation sequencing (NGS) technology has been recently introduced into blood group genotyping; however, there are few studies using NGS-based blood group genotyping in real-world clinical settings. In this study, we applied NGS-based blood group genotyping into various immunohaematology cases encountered in routine clinical practice.

METHODS

This study included 4 immunohaematology cases: ABO subgroup, ABO chimerism, antibody to a high-frequency antigen (HFA), and anti-CD47 interference. We designed a hybridization capture-based NGS panel targeting 39 blood group-related genes and applied it to the 4 cases.

RESULTS

NGS analysis revealed a novel intronic variant (NM_020469.3:c.29-10T>G) in a patient with an Ael phenotype and detected a small fraction of ABO*A1.02 (approximately 3-6%) coexisting with the major genotype ABO*B.01/O.01.02 in dizygotic twins. In addition, NGS analysis found a homozygous stop-gain variant (NM_004827.3:c.376C>T, p.Gln126*; ABCG2*01N.01) in a patient with an antibody to an HFA; consequently, this patient's phenotype was predicted as Jr(a-). Lastly, blood group phenotypes predicted by NGS were concordant with those determined by serology in 2 patients treated with anti-CD47 drugs.

CONCLUSION

NGS-based blood group genotyping can be used for identifying ABO subgroup alleles, low levels of blood group chimerism, and antibodies to HFAs. Furthermore, it can be applied to extended blood group antigen matching for patients treated with anti-CD47 drugs.

Blood Group Testing

Red blood cell (RBC) transfusion is one of the most frequently performed clinical procedures and therapies to improve tissue oxygen delivery in hospitalized patients worldwide. Generally, the cross-match is the mandatory test in place to meet the clinical needs of RBC transfusion by examining donor-recipient compatibility with antigens and antibodies of blood groups. Blood groups are usually an individual's combination of antigens on the surface of RBCs, typically of the ABO blood group system and the RH blood group system. Accurate and reliable blood group typing is critical before blood transfusion. Serological testing is the routine method for blood group typing based on hemagglutination reactions with RBC antigens against specific antibodies. Nevertheless, emerging technologies for blood group testing may be alternative and supplemental approaches when serological methods cannot determine blood groups. Moreover, some new technologies, such as the evolving applications of blood group genotyping, can precisely identify variant antigens for clinical significance. Therefore, this review mainly presents a clinical overview and perspective of emerging technologies in blood group testing based on the literature. Collectively, this may highlight the most promising strategies and promote blood group typing development to ensure blood transfusion safety.

RBCeq: A robust and scalable algorithm for accurate genetic blood typing

Background

While blood transfusion is an essential cornerstone of hematological care, patients requiring repetitive transfusion remain at persistent risk of alloimmunization due to the diversity of human blood group polymorphisms. Despite the promise, user friendly methods to accurately identify blood types from next-generation sequencing data are currently lacking. To address this unmet need, we have developed RBCeq, a novel genetic blood typing algorithm to accurately identify 36 blood group systems.

Methods

RBCeq can predict complex blood groups such as RH, and ABO that require identification of small indels and copy number variants. RBCeq also reports clinically significant, rare, and novel variants with potential clinical relevance that may lead to the identification of novel blood group alleles.

Findings

The RBCeq algorithm demonstrated 99·07% concordance when validated on 402 samples which included 29 antigens with serology and 9 antigens with SNP-array validation in 14 blood group systems and 59 antigens validation on manual predicted phenotype from variant call files. We have also developed a user-friendly web server that generates detailed blood typing reports with advanced visualization (https://www.rbceq.org/).

Interpretation

RBCeq will assist blood banks and immunohematology laboratories by overcoming existing methodological limitations like scalability, reproducibility, and accuracy when genotyping and phenotyping in multi-ethnic populations. This Amazon Web Services (AWS) cloud based platform has the potential to reduce pre-transfusion testing time and to increase sample processing throughput, ultimately improving quality of patient care.

Funding

This work was supported in part by Advance Queensland Research Fellowship, MRFF Genomics Health Futures Mission (76,757), and the Australian Red Cross LifeBlood. The Australian governments fund the Australian Red Cross Lifeblood for the provision of blood, blood products and services to the Australian community.

Accurate long-read sequencing allows assembly of the duplicated RHD and RHCE genes harboring variants relevant to blood transfusion

Next-generation sequencing (NGS) technologies have transformed medical genetics. However, short-read lengths pose a limitation on identification of structural variants, sequencing repetitive regions, phasing of distant nucleotide changes, and distinguishing highly homologous genomic regions. Long-read sequencing technologies may offer improvements in the characterization of genes that are currently difficult to assess. We used a combination of targeted DNA capture, long-read sequencing, and a customized bioinformatics pipeline to fully assemble the RH region, which harbors variation relevant to red cell donor-recipient mismatch, particularly among patients with sickle cell disease. RHD and RHCE are a pair of duplicated genes located within an ∼175 kb region on human chromosome 1 that have high sequence similarity and frequent structural variations. To achieve the assembly, we utilized palindrome repeats in PacBio SMRT reads to obtain consensus sequences of 2.1 to 2.9 kb average length with over 99% accuracy. We used these long consensus sequences to identify 771 assembly markers and to phase the RHD-RHCE region with high confidence. The dataset enabled direct linkage between coding and intronic variants, phasing of distant SNPs to determine RHD-RHCE haplotypes, and identification of known and novel structural variations along with the breakpoints. A limiting factor in phasing is the frequency of heterozygous assembly markers and therefore was most successful in samples from African Black individuals with increased heterogeneity at the RH locus. Overall, this approach allows RH genotyping and de novo assembly in an unbiased and comprehensive manner that is necessary to expand application of NGS technology to high-resolution RH typing.

BGvar: A comprehensive resource for blood group immunogenetics

BACKGROUND

Blood groups form the basis of effective and safe blood transfusion. There are about 43 well-recognised human blood group systems presently known. Blood groups are molecularly determined by the presence of specific antigens on the red blood cells and are genetically determined and inherited following Mendelian principles. The lack of a comprehensive, relevant, manually compiled and genome-ready dataset of red cell antigens limited the widespread application of genomic technologies to characterise and interpret the blood group complement of an individual from genomic datasets.

MATERIALS AND METHODS

A range of public datasets was used to systematically annotate the variation compendium for its functionality and allele frequencies across global populations. Details on phenotype or relevant clinical importance were collated from reported literature evidence.

RESULTS

We have compiled the Blood Group Associated Genomic Variant Resource (BGvar), a manually curated online resource comprising all known human blood group related allelic variants including a total of 1700 International Society of Blood Transfusion approved alleles and 1706 alleles predicted and curated from literature reports. This repository includes 1682 single nucleotide variations (SNVs), 310 Insertions, Deletions (InDels) and Duplications (Copy Number Variations) and about 1360 combination mutations corresponding to 43 human blood group systems and 2 transcription factors. This compendium also encompasses gene fusion and rearrangement events occurring in human blood group genes.

CONCLUSION

To the best of our knowledge, BGvar is a comprehensive and a user-friendly resource with most relevant collation of blood group alleles in humans. BGvar is accessible online at URL: http://clingen.igib.res.in/bgvar/.

Hemagglutination Detection with Paper-Plastic Hybrid Passive Microfluidic Chip

Hemagglutination is a critical reaction that occurs when antigens expressed on red blood cells (RBCs) react with the antibodies used for blood typing. Even though blood typing devices have been introduced to the market, they continue to face several limitations in terms of observation by the eye alone, blood manipulation difficulties, and the need for large-scale equipment, particularly process automated machines. Thus, this study aimed to design, fabricate, and test a novel hybrid passive microfluidic chip made of filter paper and polymer using a cost-effective xurography manufacturing technique. This chip is referred to as the microfluidic paper-plastic hybrid passive device (PPHD). A passive PPHD does not require external sources, such as a syringe pump. It is composed of a paper-based component that contains dried antibodies within its porous paper and a polymer component that serves as the detection zone. A single blood sample was injected into the chip's inlet, and classification was determined using the mean intensity image. The results indicated that embedded antibodies were capable of causing RBC agglutination without a saline washing step and that the results could be classified as obviously agglutination or nonagglutination for blood typing using both the naked eye and a mean intensity image. As a proof-of-concept, this study demonstrated efficiency in quantitative hemagglutination measurement within a passive PPHD for blood typing, which could be used to simplify blood biomarker analysis.

Extended red blood cell matching for all transfusion recipients is feasible

OBJECTIVE

To demonstrate the feasibility and effectiveness of extended matching of red blood cells (RBC) in practice.

BACKGROUND

At present, alloimmunisation preventing matching strategies are only applied for specific transfusion recipient groups and include a limited number of RBC antigens. The general assumption is that providing fully matched RBC units to all transfusion recipients is not feasible. In this article we refute this assumption and compute the proportion of alloimmunisation that can be prevented, when all donors and transfusion recipients are typed for A, B, D plus twelve minor blood group antigens (C, c, E, e, K, Fy^a , Fy^b , Jk^a , Jk^b , M, S and s).

METHODS

We developed a mathematical model that determines the optimal sequence for antigen matching. The model allows for various matching strategies, issuing policies and inventory sizes.

RESULTS

For a dynamic inventory composition (accounting for randomness in the phenotypes supplied and requested) and an antigen identical issuing policy 97% and 94% of alloimmunisation events can be prevented, when respectively one and two RBC units per recipient are requested from an inventory of 1000 units. Although this proportion decreases with smaller inventory sizes, even for an inventory of 60 units almost 50% of all alloimmunisation events can be prevented.

CONCLUSION

In case antigen of both donors and recipients are comprehensively typed, extended preventive matching is feasible for all transfusion recipients in practice and will significantly reduce transfusion-induced alloimmunisation and (alloantibody-induced) haemolytic transfusion reactions.

Current advances in transfusion medicine 2020: A critical review of selected topics by the AABB Clinical Transfusion Medicine Committee

BACKGROUND

The AABB Clinical Transfusion Medicine Committee (CTMC) compiles an annual synopsis of the published literature covering important developments in the field of transfusion medicine (TM), which has been made available as a manuscript published in Transfusion since 2018.

METHODS

CTMC committee members reviewed original manuscripts including TM-related topics published electronically (ahead) or in print from December 2019 to December 2020. The selection of topics and manuscripts was discussed at committee meetings and chosen based on relevance and originality. Next, committee members worked in pairs to create a synopsis of each topic, which was then reviewed by two additional committee members. The first and senior authors of this manuscript assembled the final manuscript. Although this synopsis is extensive, it is not exhaustive, and some papers may have been excluded or missed.

RESULTS

The following topics are included: COVID-19 effects on the blood supply and regulatory landscape, COVID convalescent plasma, adult transfusion practices, whole blood, molecular immunohematology, pediatric TM, cellular therapy, and apheresis medicine.

CONCLUSIONS

This synopsis provides easy access to relevant topics and may be useful as an educational tool.

Cataloguing experimentally confirmed 80.7 kb-long ACKR1 haplotypes from the 1000 Genomes Project database

Background

Clinically effective and safe genotyping relies on correct reference sequences, often represented by haplotypes. The 1000 Genomes Project recorded individual genotypes across 26 different populations and, using computerized genotype phasing, reported haplotype data. In contrast, we identified long reference sequences by analyzing the homozygous genomic regions in this online database, a concept that has rarely been reported since next generation sequencing data became available.

Study design and methods

Phased genotype data for a 80.6 kb region of chromosome 1 was downloaded for all 2,504 unrelated individuals of the 1000 Genome Project Phase 3 cohort. The data was centered on the ACKR1 gene and bordered by the CADM3 and FCER1A genes. Individuals with heterozygosity at a single site or with complete homozygosity allowed unambiguous assignment of an ACKR1 haplotype. A computer algorithm was developed for extracting these haplotypes from the 1000 Genome Project in an automated fashion. A manual analysis validated the data extracted by the algorithm.

Results

We confirmed 902 ACKR1 haplotypes of varying lengths, the longest at 80,584 nucleotides and shortest at 1,901 nucleotides. The combined length of haplotype sequences comprised 19,895,388 nucleotides with a median of 16,014 nucleotides. Based on our approach, all haplotypes can be considered experimentally confirmed and not affected by the known errors of computerized genotype phasing.

Conclusions

Tracts of homozygosity can provide definitive reference sequences for any gene. They are particularly useful when observed in unrelated individuals of large scale sequence databases. As a proof of principle, we explored the 1000 Genomes Project database for ACKR1 gene data and mined long haplotypes. These haplotypes are useful for high throughput analysis with next generation sequencing. Our approach is scalable, using automated bioinformatics tools, and can be applied to any gene.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04169-6.

A novel algorithm comprehensively characterizes human RH genes using whole-genome sequencing data

RHD and RHCE genes encode Rh blood group antigens and exhibit extensive single-nucleotide polymorphisms and chromosome structural changes in patients with sickle cell disease (SCD). RH variation can drive loss of antigen epitopes or expression of new epitopes, predisposing patients with SCD to Rh alloimmunization. Serologic antigen typing is limited to common Rh antigens, necessitating a genetic approach to detect variant antigen expression. We developed a novel algorithm termed RHtyper for RH genotyping from existing whole-genome sequencing (WGS) data. RHtyper determined RH genotypes in an average of 3.4 and 3.3 minutes per sample for RHD and RHCE, respectively. In a validation cohort consisting of 57 patients with SCD, RHtyper achieved 100% accuracy for RHD and 98.2% accuracy for RHCE, when compared with genotypes obtained by RH BeadChip and targeted molecular assays and after verification by Sanger sequencing and independent next-generation sequencing assays. RHtyper was next applied to WGS data from an additional 827 patients with SCD. In the total cohort of 884 patients, RHtyper identified 38 RHD and 28 RHCE distinct alleles, including a novel RHD DAU allele, RHD* 602G, 733C, 744T 1136T. RHtyper provides comprehensive and high-throughput RH genotyping from WGS data, facilitating deconvolution of the extensive RH genetic variation among patients with SCD. We have implemented RHtyper as a cloud-based public access application in DNAnexus (https://platform.dnanexus.com/app/RHtyper), enabling clinicians and researchers to perform RH genotyping with next-generation sequencing data.

Development and validation of a universal blood donor genotyping platform: a multinational prospective study

Each year, blood transfusions save millions of lives. However, under current blood-matching practices, sensitization to non-self-antigens is an unavoidable adverse side effect of transfusion. We describe a universal donor typing platform that could be adopted by blood services worldwide to facilitate a universal extended blood-matching policy and reduce sensitization rates. This DNA-based test is capable of simultaneously typing most clinically relevant red blood cell (RBC), human platelet (HPA), and human leukocyte (HLA) antigens. Validation was performed, using samples from 7927 European, 27 South Asian, 21 East Asian, and 9 African blood donors enrolled in 2 national biobanks. We illustrated the usefulness of the platform by analyzing antibody data from patients sensitized with multiple RBC alloantibodies. Genotyping results demonstrated concordance of 99.91%, 99.97%, and 99.03% with RBC, HPA, and HLA clinically validated typing results in 89 371, 3016, and 9289 comparisons, respectively. Genotyping increased the total number of antigen typing results available from 110 980 to >1 200 000. Dense donor typing allowed identification of 2 to 6 times more compatible donors to serve 3146 patients with multiple RBC alloantibodies, providing at least 1 match for 176 individuals for whom previously no blood could be found among the same donors. This genotyping technology is already being used to type thousands of donors taking part in national genotyping studies. Extraction of dense antigen-typing data from these cohorts provides blood supply organizations with the opportunity to implement a policy of genomics-based precision matching of blood.

A Review of the Literature Organized Into a New Database: RHeference

Hundreds of articles containing heterogeneous data describe D variants or add to the knowledge of known alleles. Data can be difficult to find despite existing online blood group resources and genetic and literature databases. We have developed a modern, elaborate database for D variants, thanks to an extensive literature search with meticulous curation of 387 peer-reviewed articles and 80 abstracts from major conferences and other sources. RHeference contains entries for 710 RHD alleles, 11 RHCE alleles, 30 phenotype descriptions (preventing data loss from historical sources), 35 partly characterized alleles, 3 haplotypes, and 16 miscellaneous entries. The entries include molecular, phenotypic, serological, alloimmunization, haplotype, geographical, and other data, detailed for each source. The main characteristics are summarized for each entry. The sources for all information are included and easily accessible through doi and PMID links. Overall, the database contains more than 10,000 individual pieces of data. We have set up the database architecture based on our previous expertise on database setup and biocuration for other topics, using modern technologies such as the Django framework, BioPython, Bootstrap, and Jquery. This architecture allows an easy access to data and enables simple and complex queries: combining multiple mutations, keywords, or any of the characteristics included in the database. RHeference provides a complement to existing resources and will continue to grow as our knowledge expands and new articles are published. The database url is http://www.rheference.org/.

An open-source python library for detection of known and novel Kell, Duffy and Kidd variants from exome sequencing

BACKGROUND AND OBJECTIVES

Next generation sequencing (NGS) has promising applications in transfusion medicine. Exome sequencing (ES) is increasingly used in the clinical setting, and blood group interpretation is an additional value that could be extracted from existing data sets. We provide the first release of an open-source software tailored for this purpose and describe its validation with three blood group systems.

MATERIALS AND METHODS

The DTM-Tools algorithm was designed and used to analyse 1018 ES NGS files from the ClinSeq® cohort. Predictions were correlated with serology for 5 antigens in a subset of 108 blood samples. Discrepancies were investigated with alternative phenotyping and genotyping methods, including a long-read NGS platform.

RESULTS

Of 116 genomic variants queried, those corresponding to 18 known KEL, FY and JK alleles were identified in this cohort. 596 additional exonic variants were identified KEL, ACKR1 and SLC14A1, including 58 predicted frameshifts. Software predictions were validated by serology in 108 participants; one case in the FY blood group and three cases in the JK blood group were discrepant. Investigation revealed that these discrepancies resulted from (1) clerical error, (2) serologic failure to detect weak antigenic expression and (3) a frameshift variant absent in blood group databases.

CONCLUSION

DTM-Tools can be employed for rapid Kell, Duffy and Kidd blood group antigen prediction from existing ES data sets; for discrepancies detected in the validation data set, software predictions proved accurate. DTM-Tools is open-source and in continuous development.

Blood group typing from whole-genome sequencing data

Many questions can be explored thanks to whole-genome data. The aim of this study was to overcome their main limits, software availability and database accuracy, and estimate the feasibility of red blood cell (RBC) antigen typing from whole-genome sequencing (WGS) data. We analyzed whole-genome data from 79 individuals for HLA-DRB1 and 9 RBC antigens. Whole-genome sequencing data was analyzed with software allowing phasing of variable positions to define alleles or haplotypes and validated for HLA typing from next-generation sequencing data. A dedicated database was set up with 1648 variable positions analyzed in KEL (KEL), ACKR1 (FY), SLC14A1 (JK), ACHE (YT), ART4 (DO), AQP1 (CO), CD44 (IN), SLC4A1 (DI) and ICAM4 (LW). Whole-genome sequencing typing was compared to that previously obtained by amplicon-based monoallelic sequencing and by SNaPshot analysis. Whole-genome sequencing data were also explored for other alleles. Our results showed 93% of concordance for blood group polymorphisms and 91% for HLA-DRB1. Incorrect typing and unresolved results confirm that WGS should be considered reliable with read depths strictly above 15x. Our results supported that RBC antigen typing from WGS is feasible but requires improvements in read depth for SNV polymorphisms typing accuracy. We also showed the potential for WGS in screening donors with rare blood antigens, such as weak JK alleles. The development of WGS analysis in immunogenetics laboratories would offer personalized care in the management of RBC disorders.

Targeted exome sequencing designed for blood group, platelet, and neutrophil antigen investigations: Proof-of-principle study for a customized single-test system

BACKGROUND

Immunohematology reference laboratories provide red blood cell (RBC), platelet (PLT), and neutrophil typing to resolve complex cases, using serology and commercial DNA tests that define clinically important antigens. Broad-range exome sequencing panels that include blood group targets provide accurate blood group antigen predictions beyond those defined by serology and commercial typing systems and identify rare and novel variants. The aim of this study was to design and assess a panel for targeted exome sequencing of RBC, PLT, and neutrophil antigen-associated genes to provide a comprehensive profile in a single test, excluding unrelated gene targets.

STUDY DESIGN AND METHODS

An overlapping probe panel was designed for the coding regions of 64 genes and loci involved in gene expression. Sequencing was performed on 34 RBC and 17 PLT/neutrophil reference samples. Variant call outputs were analyzed using software to predict star allele diplotypes. Results were compared with serology and previous sequence genotyping data.

RESULTS

Average coverage exceeded 250×, with more than 94% of targets at Q30 quality or greater. Increased coverage revealed a variant in the Scianna system that was previously undetected. The software correctly predicted allele diplotypes for 99.5% of RBC blood groups tested and 100% of PLT and HNA antigens excepting HNA-2. Optimal throughput was 12 to 14 samples per run.

CONCLUSION

This single-test system demonstrates high coverage and quality, allowing for the detection of previously overlooked variants and increased sample throughput. This system has the potential to integrate genomic testing across laboratories within hematologic reference settings.

Overcoming the challenges of interpreting complex and uncommon RH alleles from whole genomes

BACKGROUND AND OBJECTIVES

Rh is one of the most diverse and complex blood group systems. Recently, next generation sequencing (NGS) has proven to be a viable option for RH genotyping. We have developed automated software (bloodTyper) for determining alleles encoding RBC antigens from NGS-based whole genome sequencing (WGS). The bloodTyper algorithm has not yet been optimized and evaluated for complex and uncommon RH alleles.

MATERIALS AND METHODS

Twenty-two samples with previous polymerase chain reaction (PCR) and Sanger sequencing-based RH genotyping underwent WGS. bloodTyper was used to detect RH alleles including those defined by structural variation (SV) using a combination of three independent strategies: sequence read depth of coverage, split reads and paired reads.

RESULTS

bloodTyper was programmed to identify D negative and positive phenotypes as well as the presence of alleles encoding weak D, partial D and variant RHCE. Sequence read depth of coverage calculation accurately determined RHD zygosity and detected the presence of RHD/RHCE hybrids. RHCE*C was determined by sequence read depth of coverage and by split read methods. RHD hybrid alleles and RHCE*C were confirmed by using a paired read approach. Small SVs present in RHCE*CeRN and RHCE*ceHAR were detected by a combined read depth of coverage and paired read approach.

CONCLUSIONS

The combination of several different interpretive approaches allowed for automated software based-RH genotyping of WGS data including RHD zygosity and complex compound RHD and RHCE heterozygotes. The scalable nature of this automated analysis will enable RH genotyping in large genomic sequencing projects.

Multiple GYPB gene deletions associated with the U- phenotype in those of African ancestry

BACKGROUND

The MNS blood group system is defined by three homologous genes: GYPA, GYPB, and GYPE. GYPB encodes for glycophorin B (GPB) carrying S/s and the "universal" antigen U. RBCs of approximately 1% of individuals of African ancestry are U- due to absence of GPB. The U- phenotype has long been attributed to a deletion encompassing GYPB exons 2 to 5 and GYPE exon 1 (GYPB*01N).

STUDY DESIGN AND METHODS

Samples from two U-individuals underwent Illumina short read whole genome sequencing (WGS) and Nanopore long read WGS. In addition, two existing WGS datasets, MedSeq (n = 110) and 1000 Genomes (1000G, n = 2535), were analyzed for GYPB deletions. Deletions were confirmed by Sanger sequencing. Twenty known U- donor samples were tested by a PCR assay to determine the specific deletion alleles present in African Americans.

RESULTS

Two large GYPB deletions in U- samples of African ancestry were identified: a 110 kb deletion extending left of GYPB (DEL_B_LEFT) and a 103 kb deletion extending right (DEL_B_RIGHT). DEL_B_LEFT and DEL_B_RIGHT were the most common GYPB deletions in the 1000 Genomes Project 669 African genomes (allele frequencies 0.04 and 0.02). Seven additional deletions involving GYPB were seen in African, Admixed American, and South Asian samples. No samples analyzed had GYPB*01N.

CONCLUSIONS

The U- phenotype in those of African ancestry is primarily associated with two different complete deletions of GYPB (with intact GYPE). Seven additional less common GYPB deletion backgrounds were found. GYPB*01N, long assumed to be the allele commonly encoding U- phenotypes, appears to be rare.

Next-Generation Sequencing Technologies in Blood Group Typing

Sequencing of the human genome has led to the definition of the genes for most of the relevant blood group systems, and the polymorphisms responsible for most of the clinically relevant blood group antigens are characterized. Molecular blood group typing is used in situations where erythrocytes are not available or where serological testing was inconclusive or not possible due to the lack of antisera. Also, molecular testing may be more cost-effective in certain situations. Molecular typing approaches are mostly based on either PCR with specific primers, DNA hybridization, or DNA sequencing. Particularly the transition of sequencing techniques from Sanger-based sequencing to next-generation sequencing (NGS) technologies has led to exciting new possibilities in blood group genotyping. We describe briefly the currently available NGS platforms and their specifications, depict the genetic background of blood group polymorphisms, and discuss applications for NGS approaches in immunohematology. As an example, we delineate a protocol for large-scale donor blood group screening established and in use at our institution. Furthermore, we discuss technical challenges and limitations as well as the prospect for future developments, including long-read sequencing technologies.

Banking with precision: transfusion medicine as a potential universal application in clinical genomics

PURPOSE OF REVIEW

To summarize the most recent scientific progress in transfusion medicine genomics and discuss its role within the broad genomic precision medicine model, with a focus on the unique computational and bioinformatic aspects of this emergent field.

RECENT FINDINGS

Recent publications continue to validate the feasibility of using next-generation sequencing (NGS) for blood group prediction with three distinct approaches: exome sequencing, whole genome sequencing, and PCR-based targeted NGS methods. The reported correlation of NGS with serologic and alternative genotyping methods ranges from 92 to 99%. NGS has demonstrated improved detection of weak antigens, structural changes, copy number variations, novel genomic variants, and microchimerism. Addition of a transfusion medicine interpretation to any clinically sequenced genome is proposed as a strategy to enhance the cost-effectiveness of precision genomic medicine. Interpretation of NGS in the blood group antigen context requires not only advanced immunohematology knowledge, but also specialized software and hardware resources, and a bioinformatics-trained workforce.

SUMMARY

Blood transfusions are a common inpatient procedure, making blood group genomics a promising facet of precision medicine research. Further efforts are needed to embrace transfusion bioinformatic challenges and evaluate its clinical utility.

The role of genomics in transfusion medicine

PURPOSE OF REVIEW

To summarize recent advances in red blood cell (RBC) blood group genotyping, with an emphasis on advances in the use of NGS next generation sequencing (NGS) to detect clinically relevant blood group gene variation.

RECENT FINDINGS

Genetic information is useful in predicting RBC blood group antigen expression in several clinical contexts, particularly, for patients at high-risk for allosensitization, such as multiple transfused patients. Blood group antigen expression is directed by DNA variants affecting multiply genes. With over 300 known antigens, NGS offers the attractive prospect of comprehensive blood group genotyping. Recent studies from several groups show that NGS reliably detects blood group gene single nucleotide variants (SNVs) with good correlation with other genetic methods and serology. Additionally, new custom NGS methods accurately detect complex DNA variants, including hybrid RH alleles. Thus, recent work shows that NGS detects known and novel blood group gene variants in patients, solves challenging clinical cases, and detects relevant blood group variation in donors.

SUMMARY

New work shows that NGS is particularly robust in identifying SNVs in blood group genes, whereas custom genomic tools can be used to identify known and novel complex structural variants, including in the RH system.

Impact of Genotyping on Selection of Red Blood Cell Donors for Transfusion

Red blood cell (RBC) antigen phenotyping is an essential component of transfusion compatibility testing. Serology has been the gold standard method, but its low throughput and risk of diagnostic interference in certain situations limits its applicability. Genotyping is useful for phenotyping in these cases, providing a high-throughput and reliable alternative to serology. Genotyping is indicated in several hematology and oncology patient populations. Because genotyping requires a complex testing environment and bears an additional risk of genotype-phenotype discrepancy, its use is currently limited, but it serves as a useful adjunct and may eventually supplant serology as a new gold standard.

Automated typing of red blood cell and platelet antigens from whole exome sequences

BACKGROUND

Genotyping has expanded the number red blood cell (RBC) and platelet (PLT) antigens that can readily be typed, but often represents an additional testing cost. The analysis of existing genomic data offers a cost-effective approach. We recently developed automated software (bloodTyper) for determination of RBC and PLT antigens from whole genome sequencing. Here we extend the algorithm to whole exome sequencing (WES).

STUDY DESIGN AND METHODS

Whole exome sequencing was performed on samples from 75 individuals. WES-based bloodTyper RBC and PLT typing was compared to conventional polymerase chain reaction (PCR) RHD zygosity testing and serologic and single-nucleotide polymorphism (SNP) typing for 38 RBC antigens in 12 systems (17 serologic and 35 SNPs) and 22 PLT antigens (22 SNPs). Samples from the first 20 individuals were used to modify bloodTyper to interpret WES followed by blinded typing of 55 samples.

RESULTS

Over the first 20 samples, discordances were noted for C, M, and N antigens, which were due to WES-specific biases. After modification, bloodTyper was 100% accurate on blinded evaluation of the last 55 samples and outperformed both serologic (99.67% accurate) and SNP typing (99.97% accurate) reflected by two Fy^b and one N serologic typing errors and one undetected SNP encoding a Jk_null phenotype. RHD zygosity testing by bloodTyper was 100% concordant with a combination of hybrid Rhesus box PCR and PCR-restriction fragment length polymorphism for all samples.

CONCLUSION

The automated bloodTyper software was modified for WES biases to allow for accurate RBC and PLT antigen typing. Such analysis could become a routing part of future WES efforts.