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.

PIGG defines the Emm blood group system.

Emm is a high incidence red cell antigen with eight previously reported Emm- probands. Anti-Emm appears to be naturally occurring yet responsible for a clinically significant acute hemolytic transfusion reaction. Previous work suggests that Emm is located on a GPI-anchored protein, but the antigenic epitope and genetic basis have been elusive. We investigated samples from a South Asian Indian family with two Emm- brothers by whole genome sequencing (WGS). Additionally, samples from four unrelated Emm- individuals were investigated for variants in the candidate gene. Filtering for homozygous variants found in the Emm- brothers and by gnomAD frequency of < 0.001 resulted in 1818 variants with one of high impact; a 2-bp deletion causing a frameshift and premature stop codon in PIGG [NM_001127178.3:c.2624_2625delTA, p.(Leu875*), rs771819481]. PIGG encodes for a transferase, GPI-ethanolaminephosphate transferase II, which adds ethanolamine phosphate (EtNP) to the second mannose in a GPI-anchor. The four additional unrelated Emm- individuals had various PIGG mutations; deletion of Exons 2-3, deletion of Exons 7-9, insertion/deletion (indel) in Exon 3, and new stop codon in Exon 5. The Emm- phenotype is associated with a rare deficiency of PIGG, potentially defining a new Emm blood group system composed of EtNP bound to mannose, part of the GPI-anchor. The results are consistent with the known PI-linked association of the Emm antigen, and may explain the production of the antibody in the absence of RBC transfusion. Any association with neurologic phenotypes requires further research.

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.