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

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.

When and why is red blood cell genotyping applicable in transfusion medicine: a systematic review of the literature

This review aims to provide a better understanding of when and why red blood cell (RBC) genotyping is applicable in transfusion medicine. Articles published within the last 8 years in peer-reviewed journals were reviewed in a systematic manner. RBC genotyping has many applications in transfusion medicine including predicting a patient's antigen profile when serologic methods cannot be used, such as in a recently transfused patient, in the presence of autoantibody, or when serologic reagents are not available. RBC genotyping is used in prenatal care to determine zygosity and guide the administration of Rh immune globulin in pregnant women to prevent hemolytic disease of the fetus and newborn. In donor testing, RBC genotyping is used for resolving ABO/D discrepancies for better donor retention or for identifying donors negative for high-prevalence antigens to increase blood availability and compatibility for patients requiring rare blood. RBC genotyping is helpful to immunohematology reference laboratory staff performing complex antibody workups and is recommended for determining the antigen profiles of patients and prospective donors for accurate matching for C, E, and K in multiply transfused patients. Such testing is also used to determine patients or donors with variant alleles in the Rh blood group system. Information from this testing aides in complex antibody identification as well as sourcing rare allele-matched RBC units. While RBC genotyping is useful in transfusion medicine, there are limitations to its implementation in transfusion services, including test availability, turn-around time, and cost.

Estimating the serological underrecognition of patients with weak or partial RHD variants

BACKGROUND

For patients with weak or discrepant RhD RBC phenotypes, RHD genotyping is employed to determine need for RhD-negative management. However, many RHD variants are type D-negative or D-positive. Serological recognition rates (RRs) of weak and partial RHD variants are poorly characterized.

STUDY DESIGN AND METHODS

Four US studies employing RHD genotyping for weak or discrepant RhD phenotypes provided data for race/ethnicity-specific serological recognition. Three studies used microplate, and 1 used gel and tube; 2 had anti-D data. We obtained White and Hispanic/Latino allele frequencies (AFs) of weak D types 1, 2, and 3 single-nucleotide variants (SNVs) from the Genome Aggregation Database (gnomAD, v4.0.0) and devised Hardy-Weinberg-based formulas to correct for gnomAD's overcount of hemizygous RHD SNVs as homozygous. We compiled common partial RHD AF from genotyped cohorts of US Black or sickle cell disease subjects. From variant AF, we calculated hemizygous-plus-homozygous genetic prevalences. Serological prevalence: genetic prevalence ratios yielded serological RRs.

RESULTS

Overall RRs of weak D types 1-3 were 17% (95% confidence interval 12%-24%) in Whites and 12% (5%-27%) in Hispanics/Latinos. For eight partial RHD variants in Blacks, overall RR was 11% (8%-14%). However, DAR RR was 80% (38%-156%). Compared to microplate, gel-tube recognition was higher for type 2 and DAU5 and lower for type 4.0. Anti-D was present in 6% of recognized partial RHD cases, but only in 0.7% of estimated total genetic cases.

DISCUSSION

Based on AF, >80% of patients with weak or partial RHD variants were unrecognized serologically. Although overall anti-D rates were low, better detection of partial RHD variants is desirable.

Red Blood Cell Alloimmunization in Pregnancy: A Review of the Pathophysiology, Prevalence, and Risk Factors

This review paper provides an overview of the risk factors and laboratory testing for red blood cell (RBC) alloimmunization in pregnancy. RBC alloimmunization is a significant medical issue that can cause haemolytic disease of the fetus and newborn (HDFN), leading to neonatal morbidity and mortality. Current HDFN prophylaxis targets only Rhesus D (RhD) alloimmunization, with no effective measures to prevent alloimmunization to other RBC antigen groups. Several factors can increase the risk of developing RBC alloimmunization during pregnancy, including fetomaternal haemorrhage, RBC and maternal genetic status, and previous transfusions. Identifying these risk factors is essential to execute the appropriate management strategies to minimize the risk of HDFN. The review also discusses the laboratory methods and overview of pregnancy management. The paper highlights the importance of identifying and managing the risk factors for RBC alloimmunization in pregnancy to minimize the risk of HDFN and improve neonatal outcomes.

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.

Proinflammatory state promotes red blood cell alloimmunization in pediatric patients with sickle cell disease

We examined risk factors for red blood cell (RBC) alloimmunization in pediatric patients with sickle cell disease, focusing on the recipients' inflammatory state at the time of transfusion and anti-inflammatory role of hydroxyurea (HU). Among 471 participants, 55 (11.70%) participants were alloimmunized and formed 59 alloantibodies and 17 autoantibodies with an alloimmunization rate of 0.36 alloantibodies per 100 units. Analysis of 27 participants in whom alloantibodies were formed with specificities showed 23.8% (30/126) of units transfused during a proinflammatory event resulting in alloantibody formation compared with 2.8% (27/952) of units transfused at steady state. Therefore, transfusion during proinflammatory events increased the risk for alloimmunization (odds ratio [OR], 4.22; 95% confidence interval [CI], 1.64-10.85; P = .003). Further analysis of all the 471 participants showed that alloimmunization of patients who received episodic transfusion, mostly during proinflammatory events, was not reduced with HU therapy (OR, 6.52; 95% CI, 0.85-49.77; P = .071), HU therapy duration (OR, 1.13; 95% CI, 0.997-1.28; P = .056), or HU dose (OR, 1.06; 95% CI, 0.96-1.16; P = .242). The analysis also identified high transfusion burden (OR, 1.02; 95% CI, 1.003-1.04; P = .020) and hemoglobin S (HbSS) and HbSβ0-thalassemia genotypes (OR, 11.22, 95% CI, 1.51-83.38; P = .018) as additional risk factors for alloimmunization. In conclusion, the inflammatory state of transfusion recipients affects the risk of RBC alloimmunization, which is not modified by HU therapy. Judicious use of transfusion during proinflammatory events is critical for preventing alloimmunization.

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.