BackgroundThe coagulation protein von Willebrand Factor (VWF) is known to be elevated in pregnancy. However, the timing and nature of changes in VWF and associated parameters throughout pregnancy are not well understood.ObjectivesTo better understand the changes in VWF provoked by pregnancy, we studied VWF-associated parameters in samples collected over the course of healthy pregnancies.MethodsWe measured VWF antigen (VWF:Ag), VWF propeptide (VWFpp), Factor VIII (FVIII), and ADAMTS13 activity in samples collected from 46 women during pregnancy and at non-pregnant baseline. We also characterized pregnant vs. non-pregnant VWF multimer structure in 21 pregnancies, and performed isoelectric focusing (IEF) of VWF in two pregnancies which had samples from multiple trimesters.ResultsVWF:Ag and FVIII levels were significantly increased during pregnancy. ADAMTS13 activity was unchanged. VWFpp levels increased much later in pregnancy than VWF:Ag, resulting in a progressive decrease in VWFpp:Ag ratios. FVIII:VWF ratios also decreased in pregnancy. Most pregnancies exhibited a clear loss of larger VWF multimers and altered VWF triplet structure. Further evidence of acquired VWF qualitative changes in pregnancy was found in progressive, reversible shifts in VWF IEF patterns over gestation.ConclusionsThese data support a new view of pregnancy in which VWF can acquire qualitative changes associated with advancing gestational age. Modeling supports a scenario in which both increased VWF production and doubling of the VWF half-life would account for the data observed. We propose that gestation induces a prolongation in VWF survival, which likely contributes to increased total VWF levels and altered VWF structure.

This study shows custom NGS methods can accurately detect RH SV, and that SV is important to inform prediction of relevant RH alleles. Additionally, this study provides the first large NGS survey of RH alleles in African Americans.

Background The MNS blood group system is second in diversity only to the RH blood group system, with 46 described antigens. MNS system antigens are carried on glycophorins GPA and GPB that are products of the GYPA and GYPB genes, respectively. GYPA and GYPB are homologous paralogs which lie adjacent to each other on chromosome 4 in tandem with a third GYP paralog, GYPE. Current DNA-based testing methods for predicting MNS can be confounded by all types of genetic variation at the GYP locus, particularly in individuals of non-European ancestry. We sought to develop a next generation sequencing (NGS) approach for the systematic characterization of the GYP locus to accurately predict the common M/N and S/s blood group antigens and simultaneously identify other clinically relevant GYP DNA variants. Study Methods A total of 1139 samples were DNA sequenced; 1135 were from a previous study of blood donors self-identified to be of Asian American or Native American descent, and were 4 WHO reference DNAs (NIBSC). Blood donors had been tested for M and N by serology and for M/N and S/s using a single nucleotide variant (SNV) blood group genotyping platform (Bioarray). Samples were selected to enrich for MNS serology-SNV discrepancies or indeterminate results. BloodSeq is a NGS targeted panel that includes capture of 97.4kb over 3 genomic regions including the exons, pseudo-exons, introns, and proximal intergenic regions of GYPA, GYPB, and GYPE. This custom capture was used to generate Illumina, paired-end 100 bp DNA sequence reads. Raw sequence data was aligned to the human reference genome (hg19) and SNVs assessed using standard calling methods (GATK HaplotypeCaller). To predict MNS blood group system antigens, we determined variants which identified ISBT alleles; M/N antigens were defined as codominant alleles with multiple variant sites present in GYPA exon 2, while S/s antigens were defined by GYPB c.143T>C (p.Thr48Met) and 2 known GYPB silencing SNVs. Other DNA variants were cross-referenced with ISBT to predict associated blood group antigens. Results In a preliminary analyses, standard DNA variant calling methods predicted S/s (GYPB) SNVs accurately. However, alleles with M (GYPA) blood group variants exhibited a low call rate. Visualization of aligned reads indicated alleles corresponding to the M blood group sequence align poorly to the reference GYPA sequence. We traced the origin of these poor quality alignments to the presence of a region in GYPE with high sequence homology to the GYPA M allele. Notably, in the reference genome the GYPA gene has DNA variants indicative of theN genotype. With this knowledge, we developed a new approach which considers alignments of all 3 genes (GYPA, GYPB, GYPE) to predict M/N and S/s blood group antigens. Applying this method, BloodSeq predicted M with high concordance with serology (99.2%) and SNV genotype (99.6%), similar to the SNV genotype-serology concordance for M (98.9%). BloodSeq also predicted S/s in high concordance with the SNV predicted genotype (99.4% and 99.8%, respectively for S and s). Prediction of N by both BloodSeq and SNV genotype were similar to each other (99.6%) but exhibited lower accuracy (86.1% and 85.6%, respectively) when compared to serology. Interestingly, most (90%) of the N discrepancies were genetic prediction of absent N antigen but a positive N result by serology. We suspect these discrepancies result from cross-reactivity of reagent antibodies with "N" (an N-like antigen encoded by GYPB), which would require additional DNA sequence curation, or other underlying genetic variation. Additionally, 9 GYPA and GYPB variants indicative of other named ISBT alleles were detected, as well as a novel predicted frameshift variant in GYPA. Conclusion Our results demonstrate that a targeted NGS approach followed by an analysis pipeline customized for the GYP locus can simultaneously predict M/N and S/s blood groups and detect other GYP variants of known clinical significance. We propose that use of GYP locus-specific DNA sequence analysis strategies, such as addition of alternative reference sequences, should allow for automated and reliable classification of the M/N, S/s, and other variants in the MNS blood group system using next generation DNA sequencing. This work provides the foundation for a DNA-based, high resolution blood-typing method for the detection of clinically relevant MNS blood group system genetic variation. Disclosures Johnsen: CSL Behring: Consultancy; Octapharma: Consultancy.

3314 ABO(H) is a carbohydrate blood group system primarily expressed on red cells, blood vessels, and mucosal surfaces. ABO blood group is known to influence von Willebrand Factor (VWF) levels, with low VWF associated with blood group O and increased diagnosis of von Willebrand Disease. Conversely, non-O blood group is associated with high VWF levels, and both non-O blood group and high VWF are associated with thrombotic vascular disease. We sought to characterize VWF levels relative to ABH glycan phenotypes in 1129 individuals from a healthy sibling cohort, the Genes and Blood Clotting Cohort (GABC). VWF:Ag levels were determined by AlphaLISA (Perkin Elmer) in platelet poor plasma. ABH forensic techniques were adapted to samples of RBC-rich, frozen buffy coat in the study repository. In brief, buffy coat fractions were diluted in TBS, applied to nitrocellulose, and A and B glycans detected using murine monoclonal anti-A (Immucor) or murine monoclonal anti-B (Immucor) followed by and streptavidin-conjugated donkey anti-mouse IgG HRP (Jackson ImmunoResearch). A biotinylated Ulex europaeus agglutinin (UEA lectin, Vector Labs) was used to detect H, followed by streptavidin-HRP. Blots were imaged using ImageQuant (GE) and scored semi-quantitatively for glycan density by two blinded independent observers using reference buffy coats from normal blood donors. ABO blood group frequencies were similar to that of the U.S. population (O=40%, A=42%, B=12%, AB=6%). Also consistent with previous reports, VWF:Ag levels varied significantly between ABO blood groups (O<A<B=AB, see Table 1). Within blood group A, we observed variation in A glycan density (scored 1+ to 3+). Lower A glycan density (similar to the A2 reference) correlated significantly (p<0.01) with lower VWF:Ag levels (see Table 1), and also appeared to have higher detectable H antigen. We also observed wide variation in H glycan density (scored 1+ to 5+). Overall, detection of A and B glycan density patterns were inversely related to H glycan, consistent with glycosylation of H by the ABO enzyme. Interestingly, higher H density correlated significantly (p<0.01) with lower VWF:Ag levels, even within blood group O (see Table 2). In summary, ABH glycan variation may impact VWF in a more complex fashion than previously suspected. Although these data are limited to semi-quantitative analyses by the heterogeneous nature of RBC-rich buffy coat, our findings are consistent with expectations for major ABO blood group frequencies and show that variation of RBC rich-buffy coat ABH glycan density within and between ABO blood groups correlates with VWF:Ag level. This work also suggests a previously unsuspected association between VWF and variation in H antigen, which we hypothesize may be due to variation in the FUT genes or other loci affecting H glcosylation patterns. Further work to characterize the complexity of the ABH carbohydrate system and its genetic determinants is warranted to better understand the impact of ABH subtypes on VWF and vascular phenotypes. Table 1. ABO Blood Groups, Buffy Coat A Glycan Density, and VWF:Ag Level Number of Subjects ABO Blood Group VWF:Ag (+/−1SD) VWF Difference (Ovs.Avs.Bvs.AB)* Difference from Group O* 454 O 90+/−35 473 A 119+/−45 p<0.01 p<0.01 138 B 130+/−50 p<0.01 p<0.01 64 AB 128+/−52 NS p<0.01 Number of Subjects A Glycan Density Avg H Glycan Density VWF:Ag (+/−1SD) VWF Difference (A1+vs.2+vs.3+)* Difference from A 1+* 68 1+ 3.5 98+/−40 195 2+ 2.4 123+/−44 p<0.01 p<0.01 210 3+ 2.0 123+/−45 NS p<0.01 * Each section above: One-way ANOVA; post-hoc Tukey's Least Significant Difference. Table 2. Buffy Coat H Glycan Density and VWF:Ag Level H Glycan Density in All Subjects Number of Subjects H Glycan Density VWF:Ag (+/−1SD) VWF Difference (H1vs.2vs.3vs.4vs.5)* Difference from H 1+* 52 1+ 135+/−46 257 2+ 130+/−53 NS NS 260 3+ 117+/−44 p<0.01 p<0.01 307 4+ 99+/−37 p<0.01 p<0.01 252 5+ 88+/−32 p<0.05 p<0.01 H Glycan Density in Blood Group O Subjects Number of Subjects H Glycan Density** VWF:Ag (+/−1SD) VWF Difference (H3+vs.4+vs.5+)* Difference from H 3+* 29 3+ 115+/−57 207 4+ 92+/−33 p<0.01 p<0.01 214 5+ 85+/−30 NS p<0.01 * One-way ANOVA; post-hoc: Tukey's Least Significant Difference. ** No blood group O individuals scored <3+ H glycan density. Disclosures: No relevant conflicts of interest to declare.

Background: ABO(H) is a carbohydrate blood group system expressed in multiple tissues including red blood cells, blood vessels, and mucosal surfaces. ABO is the largest known genetic modifier of plasma VWF level (VWF:Ag). It has been hypothesized that the effect of ABO on VWF is mediated by H glycan density. FUT2, the gene underlying Secretor phenotype, encodes a glycosyltransferase synthesizing H antigen in mucosal tissues, and variation in the gene has also previously been associated with VWF:Ag, but past studies have been conflicting. To clarify these relationships, we studied the relationship between VWF:Ag, ABH glycans, and FUT2 genotype. Methods: The primary study group was a representative cohort of US blood donors from the Retrovirus Epidemiology Donor Study (REDS, N=499). A validation cohort of unrelated individuals was created from the Genes and Blood Clotting Study (GABC), healthy siblings between ages 14 and 35 years from University of Michigan, Ann Arbor, by choosing a random individual from each family (N=488). VWF:Ag was determined by ELISA in platelet poor plasma. Forensic techniques were adapted to detect ABH glycans in whole blood (REDS) or RBC-rich, frozen buffy coat (GABC). A and B glycans were detected using anti-A or anti-B (Immucor). A biotinylated Ulex europaeus agglutinin (UEA lectin, Vector Labs) was used to detect H. Relative A, B, and H antigen density was quantified on dot blots with ImageQuant (GE). In REDS, functional FUT2 alleles (Secretor) were determined by Sanger sequencing of FUT2 exon 2. FUT2 copy-number was assayed with real-time quantitative PCR. In GABC, FUT2 genotypes were determined through SNP genotyping (Illumina). In REDS, genotype data was phased (BEAGLE) to identify functional haplotypes. In GABC, functional alleles were inferred from the genotypes of two SNPs (rs601338, rs1047781) that determined secretor status in nearly all samples in REDS (see below). Multivariate regression was applied to VWF:Ag as a function H antigen density and O vs. non-O blood group, both separately and within the same model. All models were adjusted for age, gender, and self-reported ethnicity. Results: ABO blood group frequencies in both cohorts were similar to that of the US population. VWF:Ag differed significantly between ABO blood groups with lower values in blood group O versus non-O (REDS: ratio = 0.75, 95% CI [0.71, 0.80], p<2.2e-16, log-linear regression). H glycan density also differed between ABO blood group (p<2.2e-16, Kruskal-Wallis; O vs. non-O, ratio = 2.03, 95% CI [1.88, 2.19], p<2.2e-16). A significant fraction of H glycan density variation was attributable to ABO (REDS r2 =0.45; GABC r2 =0.34), but a wide range of H glycan density was observed in all blood groups, including within blood group O. In multivariate regression, both H glycan density and O versus non-O blood group, considered separately or in the same model, were significantly associated with VWF:Ag (REDS combined model: p = 2.9e-5 and 2.7e-4 for H glycan and blood group, respectively). In GABC but not in REDS, regression was also significant for an interaction between H glycan density and blood group (p = 0.031). Both cohorts estimated a stronger association of VWF:Ag with H in non-O blood groups. FUT2 sequencing in the REDS cohort identified 22 distinct FUT2 haplotypes. 99.5% (497/499) of individuals could be accurately assigned FUT2 genotypes based on the common W154* (rs601338) polymorphism alone. In GABC, this decreased to 94% (476/488) due to higher frequency of a hypomorphic allele (rs1047781) more commonly found in Asian individuals. In REDS, quantitative PCR did not identify copy-number variation at FUT2. There was no significant association between FUT2 genotype-predicted function and VWF:Ag or H glycan density in either cohort. Conclusion: H glycan density correlated with VWF:Ag in both cohorts. H glycan density could mediate the association between ABO blood group and VWF:Ag. If so, this suggests a non-linear, complex relationship between H and VWF and a separate ABO mechanism cannot be excluded. In both cohorts, there was no association of FUT2 (Secretor) genotype with VWF. Our data suggest prior focused approaches to FUT2 genotyping are at risk to undercall non-functional alleles, particularly in cohorts with non-European ancestries. Taken together, these indicate blood group H may be a significant modifier of VWF:Ag, and that this effect is not due to the influence of Secretor phenotype. Disclosures Johnsen: Octapharma: Other: Speaker; Biogen: Research Funding; CSL Behring: Other: Speaker.