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Under the ISBT, the Working Party (WP) for Red Cell Immunogenetics and Blood Group Terminology is charged with ratifying blood group systems, antigens and alleles. This report presents the outcomes from four WP business meetings, one located in Basel in 2019 and three held as virtual meetings during the COVID-19 pandemic in 2020 and 2021.As in previous meetings, matters pertaining to blood group antigen nomenclature were discussed. New blood group systems and antigens were approved and named according to the serologic, genetic, biochemical and cell biological evidence presented.Seven new blood group systems, KANNO (defined numerically as ISBT 037), SID (038), CTL2 (039), PEL (040), MAM (041), EMM (042) and ABCC1 (043) were ratified. Two (039 and 043) were de novo discoveries, and the remainder comprised reported antigens where the causal genes were previously unknown. A further 15 blood group antigens were added to the existing blood group systems: MNS (002), RH (004), LU (005), DI (010), SC (013), GE (020), KN (022), JMH (026) and RHAG (030).The ISBT now recognizes 378 antigens, of which 345 are clustered within 43 blood group systems while 33 still have an unknown genetic basis. The ongoing discovery of new blood group systems and antigens underscores the diverse and complex biology of the red cell membrane. The WP continues to update the blood group antigen tables and the allele nomenclature tables. These can be found on the ISBT website (http://www.isbtweb.org/working-parties/red-cell-immunogenetics-and-blood-group-terminology/).

Genome sequencing holds the promise for great public health benefits. It is currently being used in the context of rare disease diagnosis and novel gene identification, but also has the potential to identify genetic disease risk factors in healthy individuals. Genome sequencing technologies are currently being used to identify genetic factors that may influence variability in symptom severity and immune response among patients infected by SARS-CoV-2. The GENCOV study aims to look at the relationship between genetic, serological, and biochemical factors and variability of SARS-CoV-2 symptom severity, and to evaluate the utility of returning genome screening results to study participants. Study participants select which results they wish to receive with a decision aid. Medically actionable information for diagnosis, disease risk estimation, disease prevention, and patient management are provided in a comprehensive genome report. Using a combination of bioinformatics software and custom tools, this article describes a pipeline for the analysis and reporting of genetic results to individuals with COVID-19, including HLA genotyping, large-scale continental ancestry estimation, and pharmacogenomic analysis to determine metabolizer status and drug response. In addition, this pipeline includes reporting of medically actionable conditions from comprehensive gene panels for Cardiology, Neurology, Metabolism, Hereditary Cancer, and Hereditary Kidney, and carrier screening for reproductive planning. Incorporated into the genome report are polygenic risk scores for six diseases-coronary artery disease; atrial fibrillation; type-2 diabetes; and breast, prostate, and colon cancer-as well as blood group genotyping analysis for ABO and Rh blood types and genotyping for other antigens of clinical relevance. The genome report summarizes the findings of these analyses in a way that extensively communicates clinically relevant results to patients and their physicians. © 2022 Wiley Periodicals LLC. Basic Protocol 1: HLA genotyping and disease association Basic Protocol 2: Large-scale continental ancestry estimation Basic Protocol 3: Dosage recommendations for pharmacogenomic gene variants associated with drug response Support Protocol: System setup.

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.

Background and Objectives: Non-invasive assays for predicting foetal blood group status in pregnancy serve as valuable clinical tools in the management of pregnancies at risk of detrimental consequences due to blood group antigen incompatibility. To secure clinical applicability, assays for non-invasive prenatal testing of foetal blood groups need to follow strict rules for validation and quality assurance. Here, we present a multi-national position paper with specific recommendations for validation and quality assurance for such assays and discuss their risk classification according to EU regulations. Materials and Methods: We reviewed the literature covering validation for in-vitro diagnostic (IVD) assays in general and for non-invasive foetal RHD genotyping in particular. Recommendations were based on the result of discussions between co-authors. Results: In relation to Annex VIII of the In-Vitro-Diagnostic Medical Device Regulation 2017/746 of the European Parliament and the Council, assays for non-invasive prenatal testing of foetal blood groups are risk class D devices. In our opinion, screening for targeted anti-D prophylaxis for non-immunized RhD negative women should be placed under risk class C. To ensure high quality of non-invasive foetal blood group assays within and beyond the European Union, we present specific recommendations for validation and quality assurance in terms of analytical detection limit, range and linearity, precision, robustness, pre-analytics and use of controls in routine testing. With respect to immunized women, different requirements for validation and IVD risk classification are discussed. Conclusion: These recommendations should be followed to ensure appropriate assay performance and applicability for clinical use of both commercial and in-house assays. (Less)

Adaptive immunity can target a nearly infinite range of antigens, yet it is tempered by tolerogenic mechanisms that limit autoimmunity. Such immunological tolerance, however, creates a gap in adaptive immunity against microbes decorated with self-like antigens as a form of molecular mimicry. Our results demonstrate that the innate immune lectin galectin-7 (Gal-7) binds a variety of distinct microbes, all of which share features of blood group-like antigens. Gal-7 binding to each blood group expressing microbe, including strains of

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 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.

BACKGROUND: Although P1 and Xg(a) are known to be associated with the A4GALT and XG genes respectively, the genetic basis of antigen expression has been elusive. Recent reports link both P1 and Xg(a) expression with nucleotide changes in the promotor regions and with antigen negative phenotypes due to disruption of transcription factor binding. STUDY DESIGN AND METHODS: Whole genome sequencing was performed on 113 individuals as part of the MedSeq Project with serologic RBC antigen typing for P1 (n=77) and Xg(a) (n=15). Genomic data were analyzed by two approaches, nucleotide frequency correlation or serologic correlation, to find A4GALT and XG changes associated with P1 and Xg(a) expression. RESULTS: For P1, the frequency approach identified 29 possible associated nucleotide changes, and the serologic approach revealed four among them correlating with the P1+/P1− phenotype: chr22:43,115,523_43,115,520AAAG/delAAAG (rs66781836); chr 22:43,114,551C/T (rs8138197); chr22:43,114,020T/G (rs2143918); and chr22:43,113,793G/T (rs5751348). For Xg(a), the frequency approach identified 82 possible associated nucleotide changes, and among these the serologic approach revealed one correlating with the Xg(a+)/Xg(a–) phenotype: chrX:2,666,384G/C (rs311103). CONCLUSION: A bioinformatics analysis pipeline was created to identify genetic changes responsible for RBC antigen expression. This study, in progress prior to the recently published reports, independently confirms the basis for P1 and Xg(a). Although, this enabled molecular typing of these antigens, the Y chromosome PAR1 region interfered with Xg(a) typing in males. This approach could be used to identify and confirm the genetic basis of antigens, potentially replacing the historical approach using family pedigrees as genomic sequencing becomes common place.

Summary Background There are more than 300 known red blood cell (RBC) antigens and 33 platelet antigens that differ between individuals. Sensitisation to antigens is a serious complication that can occur in prenatal medicine and after blood transfusion, particularly for patients who require multiple transfusions. Although pre-transfusion compatibility testing largely relies on serological methods, reagents are not available for many antigens. Methods based on single-nucleotide polymorphism (SNP) arrays have been used, but typing for ABO and Rh—the most important blood groups—cannot be done with SNP typing alone. We aimed to develop a novel method based on whole-genome sequencing to identify RBC and platelet antigens. Methods This whole-genome sequencing study is a subanalysis of data from patients in the whole-genome sequencing arm of the MedSeq Project randomised controlled trial (NCT01736566) with no measured patient outcomes. We created a database of molecular changes in RBC and platelet antigens and developed an automated antigen-typing algorithm based on whole-genome sequencing (bloodTyper). This algorithm was iteratively improved to address cis–trans haplotype ambiguities and homologous gene alignments. Whole-genome sequencing data from 110 MedSeq participants (30 × depth) were used to initially validate bloodTyper through comparison with conventional serology and SNP methods for typing of 38 RBC antigens in 12 blood-group systems and 22 human platelet antigens. bloodTyper was further validated with whole-genome sequencing data from 200 INTERVAL trial participants (15 × depth) with serological comparisons. Findings We iteratively improved bloodTyper by comparing its typing results with conventional serological and SNP typing in three rounds of testing. The initial whole-genome sequencing typing algorithm was 99·5% concordant across the first 20 MedSeq genomes. Addressing discordances led to development of an improved algorithm that was 99·8% concordant for the remaining 90 MedSeq genomes. Additional modifications led to the final algorithm, which was 99·2% concordant across 200 INTERVAL genomes (or 99·9% after adjustment for the lower depth of coverage). Interpretation By enabling more precise antigen-matching of patients with blood donors, antigen typing based on whole-genome sequencing provides a novel approach to improve transfusion outcomes with the potential to transform the practice of transfusion medicine. Funding National Human Genome Research Institute, Doris Duke Charitable Foundation, National Health Service Blood and Transplant, National Institute for Health Research, and Wellcome Trust.

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.

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.

Background: Calculated panel reactive antibody (cPRA) scoring is used to assess whether platelet refractoriness is mediated by human leukocyte antigen (HLA) antibodies in the recipient. cPRA testing uses a national sample of US kidney donors to estimate the population frequency of HLA antigens, which may be different than HLA frequencies within local platelet inventories. We aimed to determine the impact on patient cPRA scores of using HLA frequencies derived from typing local platelet donations rather than national HLA frequencies. Methods: We built an open-source web service to calculate cPRA scores based on national frequencies or custom-derived frequencies. We calculated cPRA scores for every hematopoietic stem cell transplantation (HSCT) patient at our institution based on the United Network for Organ Sharing (UNOS) frequencies and local frequencies. We compared frequencies and correlations between the calculators, segmented by gender. Finally, we put all scores into three buckets (mild, moderate, and high sensitizations) and looked at intergroup movement. Results: 2531 patients that underwent HSCT at our institution had at least 1 antibody and were included in the analysis. Overall, the difference in medians between each group's UNOS cPRA and local cPRA was statistically significant, but highly correlated (UNOS vs. local total: 0.249 and 0.243, ρ = 0.994; UNOS vs. local female: 0.474 and 0.463, ρ = 0.987, UNOS vs. local male: 0.165 and 0.141, ρ = 0.996; P < 0.001 for all comparisons). The median difference between UNOS and cPRA scores for all patients was low (male: 0.014, interquartile range [IQR]: 0.004–0.029; female: 0.0013, IQR: 0.003–0.028). Placement of patients into three groups revealed little intergroup movement, with 2.96% (75/2531) of patients differentially classified. Conclusions: cPRA scores using local frequencies were modestly but significantly different than those obtained using national HLA frequencies. We released our software as open source, so other groups can calculate cPRA scores from national or custom-derived frequencies. Further investigation is needed to determine whether a local-HLA frequency approach can improve outcomes in patients who are immune-refractory to platelets.

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 Fyb and one N serologic typing errors and one undetected SNP encoding a Jknull 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.

BACKGROUND:Cold agglutinin disease (CAD) is a rare autoimmune hemolytic anemia mediated by autoantibodies that preferentially react at 4°C. Laboratory testing for cold-reactive autoantibodies is laborious and may not be ordered judiciously, particularly in patients with a negative direct antiglobuli

Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on data-sets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation.

Recent studies have highlighted the promise of targeting tumor neoantigens to generate potent antitumor immune responses and provide strong motivation for improving our understanding of antigen-T-cell receptor (TCR) interactions. Advances in single-cell sequencing technologies have opened the door for detailed investigation of the TCR repertoire, providing paired information from TCRα and TCRβ, which together determine specificity. However, a need remains for efficient methods to assess the specificity of discovered TCRs. We developed a streamlined approach for matching TCR sequences with cognate antigen through on-demand cloning and expression of TCRs and screening against candidate antigens. Here, we first demonstrate the system’s capacity to identify viral-antigen-specific TCRs and compare the functional avidity of TCRs specific for a given antigen target. We then apply this system to identify neoantigen-specific TCR sequences from patients with melanoma treated with personalized neoantigen vaccines and characterize functional avidity of neoantigen-specific TCRs. Furthermore, we use a neoantigen-prediction pipeline to show that an insertion-deletion mutation in a putative chronic lymphocytic leukemia (CLL) driver gives rise to an immunogenic neoantigen mut-MGA, and use this approach to identify the mut-MGA-specific TCR sequence. This approach provides a means to identify and express TCRs, and then rapidly assess antigen specificity and functional avidity of a reconstructed TCR, which can be applied for monitoring antigen-specific T-cell responses, and potentially for guiding the design of effective T-cell-based immunotherapies.

BACKGROUND There are 346 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet (PLT) antigens, most of which have known genetic changes in 45 RBC or six PLT genes that correlate with antigen expression. Polymorphic sites associated with antigen expression in the primary literature and reference databases are annotated according to nucleotide positions in cDNA. This makes antigen prediction from next-generation sequencing data challenging, since it uses genomic coordinates. STUDY DESIGN AND METHODS The conventional cDNA reference sequences for all known RBC and PLT genes that correlate with antigen expression were aligned to the human reference genome. The alignments allowed conversion of conventional cDNA nucleotide positions to the corresponding genomic coordinates. RBC and PLT antigen prediction was then performed using the human reference genome and whole genome sequencing (WGS) data with serologic confirmation. RESULTS Some major differences and alignment issues were found when attempting to convert the conventional cDNA to human reference genome sequences for the following genes: ABO, A4GALT, RHD, RHCE, FUT3, ACKR1 (previously DARC), ACHE, FUT2, CR1, GCNT2, and RHAG. However, it was possible to create usable alignments, which facilitated the prediction of all RBC and PLT antigens with a known molecular basis from WGS data. Traditional serologic typing for 18 RBC antigens were in agreement with the WGS-based antigen predictions, providing proof of principle for this approach. CONCLUSION Detailed mapping of conventional cDNA annotated RBC and PLT alleles can enable accurate prediction of RBC and PLT antigens from whole genomic sequencing data.

Detection of somatic mutations in human leukocyte antigen (HLA) genes using whole-exome sequencing (WES) is hampered by the high polymorphism of the HLA loci, which prevents alignment of sequencing reads to the human reference genome. We describe a computational pipeline that enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using the inferred alleles as a reference. Analysis of WES data from 7,930 pairs of tumor and healthy tissue from the same patient revealed 298 nonsilent HLA mutations in tumors from 266 patients. These 298 mutations are enriched for likely functional mutations, including putative loss-of-function events. Recurrence of mutations suggested that these 'hotspot' sites were positively selected. Cancers with recurrent somatic HLA mutations were associated with upregulation of signatures of cytolytic activity characteristic of tumor infiltration by effector lymphocytes, supporting immune evasion by altered HLA function as a contributory mechanism in cancer.

SummaryPlatelet transfusions are a cornerstone of therapy for patients who develop thrombocytopenia while undergoing Hematopoietic Stem Cell Transplantation (HSCT). Many patients who develop Platelet Transfusion Refractoriness (PTR) require HLA-matched platelets. Identifying these patients early could lead to better utilization of platelets as well as increased platelet counts. We built a SMART on FHIR visualization tool to aid the oncology, blood bank, and blood donor center teams in identifying these patients by showing trends in thrombocytopenia along with a computer generated calculated Panel Reactive Antibody (cPRA) level. To do this, we required a FHIR interface to our HLA database. We describe our methods and outcome for constructing this FHIR interface, as well as the architecture and data flow of HLA data from its proprietary database to the SMART on FHIR environment and application database along with RESTful cPRA web service calculator. Future work will evaluate the clinical impact of this platelet visualization tool and overall success of our FHIR implementation. Citation: Gordon WJ, Baronas J, Lane WJ. A FHIR human leukocyte antigen (HLA) interface for platelet transfusion Support. Appl Clin Inform 2017; 8: 603–611 https://doi.org/10.4338/ACI-2017-01-CR-0010

Aim Currently, there are two different approaches to calculating cPRA. The first, used in USA since 2009, is the expectation maximization (EM) algorithm. The second, utilized in Europe/Canada, is to simply observe the percentage of donors with a particular antigen (“count method”). Recently, the UNOS/OPTN Histocompatibility Committee has been re-evaluating the optimal method for determining cPRA. This has been driven by the need to consider incorporating DP (and other) locus antibodies. The benefit of the EM method, based on haplotype frequencies, is to estimate population frequencies that would include unobserved, rare phenotypes. However, because DP is not in linkage disequilibrium, it may no longer be feasible to use. Here, we evaluate the use of the count method in comparison with the EM approach for determining HLA antigen frequencies in the U.S. donor population. Methods Using the UNOS/OPTN data, we evaluated HLA typings from 39,568 deceased donors from 1/2015–1/2018. We then compared the observed antigen frequencies (count method) with those derived from the UNet cPRA calculator (EM method). Results See table. Download : Download high-res image (81KB) Download : Download full-size image Conclusions There was high concordance between the two methods of calculating cPRA in antigen frequencies within the A, B, and DR loci. Instances where there were large discrepancies were primarily due to parent antigens that were subsequently split; the UNet cPRA was based upon a pool of donors from 2007–9. This suggests, at the very least, that updates to the cPRA calculator are needed. Since DPB is not in linkage disequilibrium with the other loci, thereby negating our ability to use the EM algorithm, we suggest a new updated cPRA calculator be based upon the count method of calculating antigen frequencies.

Aim ABO-incompatible (ABOi) organs have been successfully transplanted from A2 donors into B recipients, especially when the recipient’s anti-A titers are reduced. Laboratories typically use serological methods to perform ABO typing. However, serology has significant limitations including (i) recently transfused patients may exhibit mixed field agglutination and (ii) both forward and reverse typing must be performed, but may yield discordant results. These limitations are most problematic with phenotypes involving weakly expressed antigens and ABO subgroups (i.e. A2). However, current ABO subgrouping methods using anti-A1 lectin have limitations: they only indirectly determine A2, and typically include a gray zone reactivity range for which subgroups cannot be reliably called. A combination of genotyping solutions (SSP, sequencing, etc) can be used for ABO subgrouping, but these methods are time- and labor-consuming, and require interpretation by subject matter experts. Methods The Thermo Fisher Scientific solution is based on its LinkSēq real-time PCR technology, which was developed over 10 years ago for genotyping the complex Human Leukocyte Antigen (HLA) system. LinkSēq ABO analyzes 19 reactions that identify multiple relevant SNPs located within the ABO gene. We evaluated this solution by analyzing 40 archived DNA samples, including blood blank samples for which serotyping failed or produced discordant results, and samples from deceased solid organ donors for comparison with A1 lectin testing. Results Genotyping results generated by LinkSēq were 100% concordant with typing obtained by traditional methodologies. In two cases, serology couldn’t provide conclusive results and typing had to be reflexed to lectin tests or SBT. LinkSēq overcomes the major challenges of molecular typing by providing a robust, automated approach that increases laboratory productivity and reduces turn-around time. With less than 10 min of hands-on set-up, no further operator intervention with reagents, and SureTyper software fully automating all analysis, LinkSēq delivers genotyping and predicted phenotyping results in approximately 90 min. Conclusions We conclude that LinkSēq can provide a simple, effective and robust method for ABO typing including accurate A2 subgrouping.

Comprehensive multiple sequence alignments of the multisubunit DNA-dependent RNA polymerase (RNAP) large subunits, including the bacterial β and β′ subunits and their homologs from archaebacterial RNAPs, eukaryotic RNAPs I–III, nuclear–cytoplasmic large double-stranded DNA virus RNAPs, and plant plastid RNAPs, were created [Lane, W. J. and Darst, S. A. (2009). Molecular evolution of multisubunit RNA polymerases: sequence analysis. In press]. The alignments were used to delineate sequence regions shared among all classes of multisubunit RNAPs, defining common, fundamental RNAP features as well as identifying highly conserved positions. Here, we present a systematic, detailed structural analysis of these shared regions and highly conserved positions in terms of the RNAP structure, as well as the RNAP structure/function relationship, when known.

Cold agglutinin disease (CAD) is a rare autoimmune hemolytic anemia mediated by autoantibodies that preferentially react at 4°C. Laboratory testing for cold-reactive autoantibodies is laborious and may not be ordered judiciously, particularly in patients with a negative direct antiglobulin test (DAT). We sought to determine whether a negative DAT using anti-human complement (anti-C3) rules out elevated cold agglutinin (CA) titers and the diagnosis of CAD.We performed a retrospective study of patients with a CA test performed at three major academic medical centers: Barnes-Jewish Hospital (2003-2014), Vanderbilt University Medical Center (2007-2009), and Massachusetts General Hospital (2009-2014).This study included 801 patients, of whom 51% (n = 410) had a DAT within the 7 days before CA testing. A total of 98% of patients with a negative DAT using anti-C3 had a negative CA titer (64). Only five subjects had a negative DAT using anti-C3 and an elevated CA titer.Overutilization of CA testing could be reduced by establishing laboratory acceptance criteria based on a positive DAT using anti-C3. Such acceptance criteria would have reduced CA testing by 68% for those with an available DAT result.

In the Rh blood group system, the RHD gene is bordered by two homologous DNA sequences called the upstream and downstream Rhesus boxes. The most common cause of the D− phenotype in people of European descent is a deletion of the RHD gene region, which results in a hybrid combination of the two Rhesus boxes. PCRbased testing can detect the presence or absence of the hybrid box to determine RHD zygosity. PCR hybrid box testing on fathers can stratify risk for haemolytic disease of the fetus and new born in mothers with anti-D antibodies. Red blood cells and genomic DNA were isolated from 37 individuals of European descent undergoing whole genome sequencing as part of the MedSeq Project. A whole genome sequence-based RHD sequence read depth analysis was used to determine RHD zygosity (homozygous, hemizygous, or null states) with 100% agreement (n=37) when compared to conventional RhD serology and PCR-based hybrid box assay.

BACKGROUND There are 346 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet (PLT) antigens, most of which have known genetic changes in 45 RBC or six PLT genes that correlate with antigen expression. Polymorphic sites associated with antigen expression in the primary literature and reference databases are annotated according to nucleotide positions in cDNA. This makes antigen prediction from next‐generation sequencing data challenging, since it uses genomic coordinates. STUDY DESIGN AND METHODS The conventional cDNA reference sequences for all known RBC and PLT genes that correlate with antigen expression were aligned to the human reference genome. The alignments allowed conversion of conventional cDNA nucleotide positions to the corresponding genomic coordinates. RBC and PLT antigen prediction was then performed using the human reference genome and whole genome sequencing (WGS) data with serologic confirmation. RESULTS Some major differences and alignment issues were found when attempting to convert the conventional cDNA to human reference genome sequences for the following genes: ABO, A4GALT, RHD, RHCE, FUT3, ACKR1 (previously DARC), ACHE, FUT2, CR1, GCNT2, and RHAG. However, it was possible to create usable alignments, which facilitated the prediction of all RBC and PLT antigens with a known molecular basis from WGS data. Traditional serologic typing for 18 RBC antigens were in agreement with the WGS‐based antigen predictions, providing proof of principle for this approach. CONCLUSION Detailed mapping of conventional cDNA annotated RBC and PLT alleles can enable accurate prediction of RBC and PLT antigens from whole genomic sequencing data.

Background— CD133 (AC133) is a surface antigen that defines a broad population of stem cells, including myogenic and endothelial progenitors. CD133 + cells are rare in adult tissues, and the factors that support their differentiation into mature angiomyogenic cells are not known. These hurdles have hampered the use of CD133 + cells for therapeutic purposes. Because human fetal liver is a rich source of CD133 + cells, we sought to identify the growth factors that promote codifferentiation of these cells into angiogenic and myogenic cells. Methods and Results— Human fetal liver CD133 + and CD133 − cell subpopulations were cultured with 5′-azacytidine or vascular endothelial growth factor (VEGF 165 ) and/or brain-derived nerve growth factor (BDNF). CD133 + but not CD133 − cells from human fetal liver codifferentiated into spindle-shaped cells, as well as flat adherent multinucleated cells capable of spontaneous contractions in culture. The resulting spindle-shaped cells were confirmed to be endothelial cells by immunohistochemistry analysis for von Willebrand factor and by acetylated LDL uptake. Multinucleated cells were characterized as striated muscles by electron microscopy and immunohistochemistry analysis for myosin heavy chain. Presence of VEGF 165 and BDNF significantly enhanced angiomyogenesis in vitro. Inoculation of cells derived from CD133 + cells, but not CD133 − cells, into the ear pinna of NOD/SCID mice resulted in the formation of cardiomyocytes, as identified by immunostaining with cardiac troponin-T antibody. These cells generated electrical action potentials, detectable by ECG tracing. Conclusions— CD133 defines a population of human fetal liver cells capable of differentiating into both angiogenic and myogenic cells. Preconditioning of these CD133 + cells with VEGF 165 and BDNF enhances the angiomyogenesis. CD133 + fetal liver cells ultimately may be used for therapeutic angiomyogenesis.

Nature 547, 217–221 (2017); doi:10.1038/nature22991 In this Letter, the ‘Data availability’ section in the Methods should state ‘WES and RNA-seq data are deposited in dbGaP (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001451.v1.p1). All other data are available from the corresponding author upon reasonable request.

Aim DNA library preparation for next generation sequencing (NGS) consists of several hundred material transfer and wash steps, which are time consuming, labor intensive, and increase the risk of repetitive strain injury. Robotic liquid handlers can automate and standardize library preparation, but few HLA laboratories have experience with high-complexity robotic platforms. We sought to evaluate the use of robotics for library preparation in conjunction with a NGS based HLA typing assay. Methods A Beckman Coulter Biomek NXp Span-8 robotic liquid handler was acquired along with the vendor supplied robotics method for the Illumina TruSight HLA v2 sequencing panel. The robotics method was first optimized with a series of runs using water, 50% glycerol, 85% ethanol, and AMPure beads. Next, DNA and reagents were run to identify sample viscosity and reagent issues. After each run, issues were communicated to the vendor for method improvement. The finalized method was run on 78 DNA samples over seven runs to assess the quality of normalization, pooling, sequencing, and reproducibility of results. Results Robotic issues were encountered with pipette calibration, labware definitions, proper labware selection, and efficiency. To add complexity, these issues had subtle compounding effects on the overall success of the method, which required that each be addressed individually and in detail. Eleven versions of the method were subsequently produced and tested to ensure robustness and consistency. The finalized method produced consistent high quality sequencing metrics on the NGS typing platform which agreed with the known HLA typing results. Conclusions Detailed documentation of issues by lab staff and clear communication with the vendor allowed for a rapid and iterative improvement of the robotics method. The lessons learned during the implementation process formed a roadmap that allowed for successful implementation of a robotics platform for NGS based HLA typing.

Aim Platelet transfusions are a cornerstone of therapy for patients who develop thrombocytopenia while undergoing hematopoietic stem cell transplantation (HSCT). Many of these patients demonstrate anti-HLA alloantibody mediated platelet transfusion refractoriness (PTR) and require HLA-matched platelets. The calculated panel reactive antibody (cPRA) is a useful tool for identifying patients at risk for PTR, but it requires manual intervention to calculate and so it is only calculated when requested. However, routine use of cPRA before every HSCT, using the existing pre-HSCT alloantibody results, could identify PTR earlier and more efficiently manage its complex transfusion needs for improved patient care. To accomplish this goal, we created an electronic medical record (EMR) web app for use by clinicians, blood bank/donor center, and tissue typing lab to better identify and manage PTR patients. Methods An online cPRA web-service was created to electronically receive alloantibody data and return cPRA values for several different ethnicities. Additionally, to increase flexibility, the cPRA web-service calculation can be customized with user defined antigen frequencies and epitopes. To utilize the cPRA web-service, a PTR web app was created with connections to several clinical data sources including: Tissue Typing Lab, Blood Bank, Donor Center, and EMR. The PTR web app was embedded into the EMR so that it could be easily viewed while caring for patients undergoing HSCT. Platelet utilization and transfusion effectiveness were compared before and after implementation. Results The cPRA web-service allows for automated computer generated cPRAs, making it feasible to calculate up-to-date cPRAs for every HSCT patient. The web app displays platelet counts along with platelet transfusion events, platelet units in inventory, and has a section for the clinical care teams and lab staff to communicate. We plan on making the cPRA web-service publicly available for others to use and customize. Conclusions We built a customizable cPRA web-service and platelet transfusion visualization web app to provide better point-of-care access to real time cPRA values to enable PTR risk stratification of HSCT patients. The web app also summarizes all of the key clinical data to efficiently manage PRT and improve platelet usage.

Aim Chimerism testing is a valuable tool for determining the proportion of donor vs. recipient DNA in a sample. The commonly used polymerase chain reaction amplifications of short tandem repeats assay (Promega, Madison, WI) produces results for 21 loci, but only 9 loci are used in manual calculations. We sought to improve the tedious and time consuming process of manually calculating a patient’s percent chimerism by developing an automated chimerism calculator for rapid and accurate chimerism calculations based off of all 21 loci. Methods The calculator was developed using Microsoft Excel Macros and is able to report the percent donor chimerism +/− the margin of error. To determine whether precision is improved by using 21 loci, the results of a 21 loci analysis and a 9 loci analysis were compared in 111 patient samples. Additionally, each of the 21 loci was evaluated for its average deviation from the mean. Finally, 298 patient samples were analyzed by the program in order to determine if precision is equal at all chimerism percentages. Results When the same loci are analyzed, the chimerism calculator results are identical to the manual calculations, but completed in 10% of the time. The analysis of patient samples using 21 and 9 loci yielded, on average, chimerism percentages within 2.0% of each other. The average margin of error using 9 loci for analysis is 2.41% compared to 0.8% using all 21 loci. Among the 21 loci, the average deviation from the mean was found to range from 8.9% and 5.9%. Finally, we found that the average margin of error for patients between 90 and 100 percent donor chimerism is 0.19% while patients between 30 and 40 percent donor chimerism have 10.1% margin of error. Conclusions The chimerism calculator allows for routine use of all 21 STR loci with significantly reduced analysis time, 30% less margin of error, and an informative statistical analysis. In various laboratory settings, similar methods of computer assisted chimerism analysis can be easily implemented.

Aim Accurate classification of serologically-distinct antigens (Ag) is critical in organ allocation, and nowadays it is possible to define anti-HLA antibody specificity to the allelic level. We examined class I antibodies (Ab) for allelic specificities that may be serologically distinct and evaluated its impact on crossmatch (XM) results and organ allocation. Methods 6726 sera were tested for anti-HLA Ab using LABScreen Single Ag assay (One Lambda), in which 17 class I HLA Ag are represented by more than one allele. Discordance in MFI values between the two allelic beads was examined as a categorical variable to mimic clinical practice, and as a continuous variable (MFI value) to better reflect biological plausibility. To evaluate the significance of an allele-specific Ab on XM results, we examined an unbiased cohort of deceased donor-candidate testing (125,828 CDC XMs between 2014 and 2017). In our lab, all candidates within a blood group have a CDC XM performed, regardless of whether they have donor-specific antibody (DSA). This uniquely allows us to examine whether a candidate with an allele-specific DSA, who has already been excluded from the match run, would indeed have a positive XM against a donor who has a different allele. Statistical analyses were performed using JMP12Pro (SAS Institute). Results 1. The incidence of discordance between the two allelic beads varied depending on whether MFI values were considered as continuous vs categorical variables. 2. The presence of allele-specific Ab for rare alleles was out of proportion to their frequencies in the population. 3. The presence of Ab against only the rare allele was a poor predictor of a positive CDC XM, with a positive predictive value of 0–7% compared with 52.5% if the candidate had DSA against an A or B locus Ag. Conclusions 9 out of 17 Class I HLA antigens had potential allele-specific reactivity, meaning that candidates with antibody selectivity against rare alleles may be unnecessarily excluded from many organ offers based on definition of unacceptable antigens by serological equivalence. Conversely, for centers relying on virtual-XM, prematurely defining alleles as new serological splits could unfortunately allow transplants for which the recipient has DSA. Further testing is needed to rigorously confirm these allele-specific reactivity patterns.

Aim ABO typing of recipients and donors is important for optimal transplant outcomes. ABO typing by serology requires a fresh blood sample, whereas living donor evaluations as well as collection of samples for the donor registry often involve a buccal swab for DNA isolation. ASHI and CAP have recently released guidelines that allow DNA-based genetic ABO determination as a screening tool for initial donor evaluation or for listing donors on the registry. We sought to develop a targeted ABO next generation sequencing (NGS) assay, along with companion interpretive software, for automated data processing and ABO prediction. Methods To develop a target approach, a series of PCR primer combinations spanning the ABO gene were evaluated on blood and buccal swab isolated DNA. The DNA products were run on agarose gel and Agilent bioanalyzer to determine product size and quality. PCR products underwent Illumina TruSight NGS library preparation and sequencing using Illumina MiSeq. A curated ABO allele table was created, and customize software developed to detect and phase ABO alleles from NGS data. Results PCR primer evaluation showed reproducible PCR products spanning exons 6–7 of the ABO gene, which yielded good quality NGS data. These exons encode the major ABO specificities and variations. To verify the ABO NGS assay, a combination of 50 blood and buccal swab samples were tested and found to be 100% concordant with serologic ABO typing which included 19 Group A, 18 Group O, 12 Group B, and 1 Group AB. Conclusions A targeted ABO NGS based assay was developed and optimized for blood and buccal swab isolated DNA. Companion interpretive software, which automates NGS ABO analysis, was developed and correctly determined the ABO type when compared with serology. This assay and software interpretation provides a screening tool for prediction of ABO blood type when no blood sample is available.

Personalized neoantigen therapies for cancer require accurate epitope selection. However, most Class I prediction algorithms in common use today are based on biochemical binding assays that are difficult to scale and do not address processing steps upstream of peptide-MHC binding. Here we present an alternative approach based on the LC-MS/MS identification of MHC Class I-bound peptides. While MS-based profiling is not new, we optimized the system for rule learning by focusing on cell lines expressing only a single HLA-A or HLA-B allele and by collecting parallel transcriptomic and proteomic measurements. Identifying over 24,000 peptides across 16 individual alleles, we were able to discover novel binding motifs, which were validated biochemically, and develop novel neural network algorithms. Furthermore, we systematically interrogated processing rules - discovering a novel motif conserved across multiple cell types - and developed a principled framework for integrating epitope cleavability, expression, and MHC binding potential into an overall ranking. Validating on external datasets, we saw a doubling in positive predictive value with respect to standard approaches. We thus demonstrate a scalable strategy for systematically learning the rules of endogenous antigen presentation that can be deployed for the optimal selection of patient-specific cancer neoantigens. Citation Format: Michael S. Rooney, Jenn Abelin, Siranush Sarkizova, Derin Keskin, Christine Hartigan, Wandi Zhang, John Sidney, William Lane, Jonathan Stevens, Guang L. Zhang, Karl Clauser, Nir Hacohen, Steve Carr, Cathy Wu. Next-generation epitope prediction using mass spectrometry and integrative genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-179. doi:10.1158/1538-7445.AM2017-LB-179

Background The MedSeq Project is a randomized clinical trial developing approaches to assess the impact of integrating genome sequencing into clinical medicine. To facilitate the return of results of potential medical relevance to physicians and patients participating in the MedSeq Project, we sought to develop a reporting approach for the effective communication of such findings. Methods Genome sequencing was performed on the Illumina HiSeq platform. Variants were filtered, interpreted, and validated according to methods developed by the Laboratory for Molecular Medicine and consistent with current professional guidelines. The GeneInsight software suite, which is integrated with the Partners HealthCare electronic health record, was used for variant curation, report drafting, and delivery. Results We developed a concise 5–6 page Genome Report (GR) featuring a single-page summary of results of potential medical relevance with additional pages containing structured variant, gene, and disease information along with supporting evidence for reported variants and brief descriptions of associated diseases and clinical implications. The GR is formatted to provide a succinct summary of genomic findings, enabling physicians to take appropriate steps for disease diagnosis, prevention, and management in their patients. Conclusions Our experience highlights important considerations for the reporting of results of potential medical relevance and provides a framework for interpretation and reporting practices in clinical genome sequencing. Electronic supplementary material The online version of this article (doi:10.1186/s12881-014-0134-1) contains supplementary material, which is available to authorized users.

As genome sequencing technologies increasingly enter medical practice, genetics laboratories must communicate sequencing results effectively to nongeneticist physicians. We describe the design and delivery of a clinical genome sequencing report, including a one-page summary suitable for interpretation by primary care physicians. To illustrate our preliminary experience with this report, we summarize the genomic findings from 10 healthy participants in a study of genome sequencing in primary care.