Von Willebrand Factor Multimer Densitometric Analysis: Validation of the Clinical Accuracy and Clinical Implications in von Willebrand Disease

Von Willebrand factor (VWF) multimer analysis is important in the classification of von Willebrand disease (VWD). Current visual VWF multimer analysis is time consuming and inaccurate in detecting subtle changes in multimer patterns. Although VWF multimer densitometric analysis may be useful, the accuracy needs further investigation before it can be widely applied. In this study we aimed to validate VWF multimer densitometric analysis in a large cohort of VWD patients and to identify patient characteristics associated with densitometric outcomes. Patients were included from the Willebrand in the Netherlands (WiN) study, in which a bleeding score (BS) was obtained, and blood was drawn. For multimer analysis, citrated blood was separated on an agarose gel and visualized by Western blotting. IMAGEJ was used to generate densitometric images and medium-large VWF multimer index was calculated. We included 560 VWD patients: 328 type 1, 211 type 2, and 21 type 3 patients. Medium-large VWF multimer index performed excellent in distinguishing visually classified normal VWF multimers from reduced high-molecular-weight (HMW) multimers (area under the curve [AUC]: 0.96 [0.94-0.98], P < 0.001), normal multimers from absence of HMW multimers (AUC 1.00 [1.00-1.00], P < 0.001), and type 2A and 2B from type 2M and 2N (AUC: 0.96 [0.94-0.99], P < 0.001). Additionally, higher medium-large VWF multimer index was associated with lower BS in type 1 VWD: β = -7.6 (-13.0 to -2.1), P = 0.007, adjusted for confounders. Densitometric analysis of VWF multimers had an excellent accuracy compared with visual multimer analysis and may contribute to a better understanding of the clinical features such as the bleeding phenotype of VWD patients

Von Willebrand disease type 2M: Correlation between genotype and phenotype

Background: An appropriate clinical diagnosis of von Willebrand disease (VWD) can be challenging because of a variable bleeding pattern and laboratory phenotype. Genotyping is a powerful diagnostic tool and may have an essential role in the diagnostic field of VWD.  Objectives: To unravel the clinical and laboratory heterogeneity of genetically confirmed VWD type 2M patients and to investigate their relationship.  Methods: Patients with a confirmed VWD type 2M genetic variant in the A1 or A3 domain of von Willebrand factor (VWF) and normal or only slightly aberrant VWF multimers were selected from all subjects genotyped at the Radboud university medical center because of a high suspicion of VWD. Bleeding scores and laboratory results were analyzed.  Results: Fifty patients had a clinically relevant genetic variant in the A1 domain. Median bleeding score was 5. Compared with the nationwide Willebrand in the Netherlands study type 2 cohort, bleeding after surgery or delivery was reported more frequently and mucocutaneous bleedings less frequently. Median VWF activity/VWF antigen (VWF:Act/VWF:Ag) ratio was 0.32, whereas VWF collagen binding activity/VWF antigen (VWF:CB/VWF:Ag) ratio was 0.80. Variants in the A3 domain were only found in two patients with low to normal VWF:Act/VWF:Ag ratios (0.45, 1.03) and low VWF:CB/VWF:Ag ratios (0.45, 0.63).  Conclusion: Genetically confirmed VWD type 2M patients have a relatively mild clinical phenotype, except for bleeding after surgery and delivery. Laboratory phenotype is variable and depends on the underlying genetic variant. Addition of genotyping to the current phenotypic characterization may improve diagnosis and classification of VWD

A dominant-negative GFI1B mutation in the gray platelet syndrome

Contains fulltext : 127547.pdf (publisher's version ) (Open Access)The gray platelet syndrome is a hereditary, usually autosomal recessive bleeding disorder caused by a deficiency of alpha granules in platelets. We detected a nonsense mutation in the gene encoding the transcription factor GFI1B (growth factor independent 1B) that causes autosomal dominant gray platelet syndrome. Both gray platelets and megakaryocytes had abnormal marker expression. In addition, the megakaryocytes had dysplastic features, and they were abnormally distributed in the bone marrow. The GFI1B mutant protein inhibited nonmutant GFI1B transcriptional activity in a dominant-negative manner. Our studies show that GFI1B, in addition to being causally related to the gray platelet syndrome, is key to megakaryocyte and platelet development

A dominant-negative GFI1B mutation in the gray platelet syndrome

Contains fulltext : 127547.pdf (publisher's version ) (Open Access)The gray platelet syndrome is a hereditary, usually autosomal recessive bleeding disorder caused by a deficiency of alpha granules in platelets. We detected a nonsense mutation in the gene encoding the transcription factor GFI1B (growth factor independent 1B) that causes autosomal dominant gray platelet syndrome. Both gray platelets and megakaryocytes had abnormal marker expression. In addition, the megakaryocytes had dysplastic features, and they were abnormally distributed in the bone marrow. The GFI1B mutant protein inhibited nonmutant GFI1B transcriptional activity in a dominant-negative manner. Our studies show that GFI1B, in addition to being causally related to the gray platelet syndrome, is key to megakaryocyte and platelet development

Le Paysan de Cochinchine... Hebdomadaire de soutien des intérêts agricoles ["puis" Hebdomadaire français]

22 février 19401940/02/22 (N246)-1940/02/22

Von Willebrand Factor antigen and age explain variation in baseline FVIII:C among nonsevere hemophilia A patients with the same F8 genotype (Arg593Cys and Asn618Ser)

Introduction and Objectives: Non-severe hemophilia A (baseline FVIII:C, 2-40 IU/dL) is caused by a mutation in the F8 gene. There is limited knowledge on the factors determining the variation in baseline FVIII:C. The aim is to identify the determinants of baseline FVIII:C in non-severe hemophilia A patients. Materials and Methods: We analyzed clinical data for non-severe hemophilia A patients, treated between 1980-2013, in European Haemophilia Treatment Centers (HTCs) participating in the INSIGHT/RISE project. We performed analyses on mutations that were present in ≥10 patients. Age (at FVIII:C measurement), F8 gene mutation, VWF:Ag, VWF:Act and HTC were analyzed as potential determinants by multivariate regression analyses. Results: We identified nine missense mutations present in ≥10 patients in 321 individuals, median age 23 years (IQR 7-47). From these individuals we had data on 667 FVIII:C measurements in 5 HTCs. Median baseline FVIII:C, VWF:Ag and VWF: Act were 17 IU/dL (IQR 11-22), 98 IU/dL (IQR 78-128) and 91 IU/dL (70-115) respectively. Baseline FVIII:C, VWF:Ag and VWF:Act all increased with age, both in the total population and within the two largest mutation groups (Asn618Ser, 113 patients; Arg593Cys, 107 patients). VWF:Ag, age and F8 mutation were significant predictors of baseline FVIII:C (p <0.0001-0.024). In mutations that were present in ≥10 patients the determinants age, F8 mutation, VWF:Ag and HTC together explained 61% of the variation in baseline FVIII:C. Within the specific mutation group Asn618Ser only 21% of the variance in baseline FVIII:C was explained by the combined potential determinants, with VWF:Ag and HTC as significant predictors (p = 0.008 and 0.013 respectively). Among individuals with the Arg593Cys F8 genotype the determinants age, VWF:Ag and HTC were significant predictors (p <0.0001 for age and VWF:Ag and p = 0.04 for HTC), together explaining 34% of the variance in baseline FVIII:C. Conclusion: In non-severe hemophilia A patients carrying the same F8 mutation the determinants age, VWF:Ag and HTC contribute to baseline FVIII:C to variable extends. With the studied determinants we can only explain 61% of the variance in baseline FVIII:C. This suggests that yet unknown factors influence FVIII:C in nonsevere hemophilia A