The HemoTwin-BD project will investigate how qualitative and quantitative variants of hemostatic proteins (proteoforms) present in plasma, platelets and endothelial cells contribute to the variability of
bleeding phenotypes in patients with congenital bleeding disorders (CBDs) or bleeding disorders of unknown cause (BDUC). A key unresolved challenge in the management of these disorders is why some
individuals experience severe bleeding while others with the same diagnosis or similar laboratory results do not. This variability within disorders remains largely unexplained because the underlying molecular
mechanismsóat the protein levelóare not captured by current genetic and functional diagnostics.
Bleeding disorders are traditionally studied within isolated diagnostic categories, limiting the ability to uncover shared disease mechanisms. Particularly, heavy menstrual bleeding (HMB) is considered a
major clinical challenge in the field. Although evidence suggests that HMB may be linked to bleeding severity, there is a lack of evidence for congenital deficiencies in this group. Current diagnostic laboratory
testing fails to define any abnormalities responsible for the bleeding phenotype seen in these women, and they are often classified as a BDUC. However, it is likely that different levels and/or proteoforms of
critical hemostatic proteins underly HMB. In addition, other clinical features, including postpartum hemorrhage, peri-operative bleeding and joint damage, are observed across different bleeding disorders
and may occur independent of traditional diagnostic classifications. This suggests the existence of common proteoform variants or shared biological modifiers that influence bleeding risk across different
diagnoses. HemoTwin-BD aims to address these knowledge gaps by applying a systems-level approach that combines deep proteomic phenotyping with the integration of nationwide, well-characterized clinical
cohorts. By analyzing these cohorts both individually and in combination, the project seeks to resolve outstanding questions within specific bleeding disorders and to enable the discovery of shared
mechanisms underlying bleeding variability.
The work plan is structured around four work packages (WPs). WP1 maps Willebrand factor (VWF) proteoforms and their impact on trafficking and function in von Willebrand Disease (VWD). WP2
quantifies variant coagulation factor proteoforms and assesses their contribution to stage-specific defects in secondary hemostasis and fibrinolysis. WP3 defines proteomic signatures in BDUC using
multi-omic profiling of plasma, platelet, and endothelial proteins. WP4 integrates clinical, diagnostic, and molecular data into an AI-driven platform - HemoTwin-BD - to improve bleeding severity stratification
and predict treatment response.
Together, these WPs will create an in-depth, individualized map of bleeding risk and treatment response, moving diagnostics beyond ìone-size-fits-allî to a tailored, proteoform-level understanding for patient
stratification, and individualized treatment planning. Leveraging advanced mass spectrometry-based multi-proteomics for in-depth molecular profiling with Artificial Intelligence (AI)-guided machine learning,
the project will identify key molecular determinants of bleeding variability and support improved risk assessment and therapeutic decision-making. Building on nationwide collaboration among Dutch
hematologists as well as the continuous advancement of technological innovation at Sanquin, this consortium is uniquely positioned to deliver translational impact on care for individuals with a bleeding disorder.