In recent years, significant advances in understanding the molecular basis of bleeding disorders have been made, but a large portion of the variability in bleeding severity remains unexplained. In this project, the focus is on hemophilia and von Willebrand disease (VWD), where the observed variability in bleeding patterns cannot be assigned to a single measurable parameter. Clot formation is a complex, non-linear process seriously impaired in persons with these disorders. Because it involves the large biochemical pathway of coagulation coupled to platelet function and biophysical mechanisms including blood flow, it is well suited for study with a systems biology approach. The long-term goal of this research is to develop complementary computational and in vitro models that predict an individual's bleeding potential based on variables measured from their blood. The objective in this application is to identify biochemical and biophysical modifiers of bleeding in hemophilia and VWD. Potential modifiers include variables such as the composition of blood, platelet attributes, and the physical properties of clots. The central hypothesis is that our computational models that encompass the biochemical pathways of thrombus formation and platelet function coupled to the blood's fluid dynamics can identify the primary modifiers of bleeding patterns in these disorders. This hypothesis was formulated on the basis of preliminary data produced in the applicants'laboratories. The rationale for the proposed research is that the reductionist approach to predicting bleeding based on individual plasma components has failed. There is great detailed knowledge of the biochemical pathways that contribute to bleeding, but it is still not possible to reliably assign bleeding risk. Guided by strong preliminary data, this hypothesis will be tested by pursuing three specific aims: 1) Develop and validate computational models of bleeding;2) Identify modifiers of bleeding in hemophilia and VWD by computational sensitivity analyses;and 3) Predict clinical bleeding in a cohort of bleeding disorder patients. Under the first aim, existing models of thrombosis will be modified to simulate the unique biophysical environment of bleeding, defined by the transport of plasma proteins and blood cells into a porous extravascular space. Computational models will be validated against a microfluidic-based bleeding assay. Under the second aim, the computational models will be used to screen the large parameter space of variables known to affect clot formation. Parameters that significantly alter bleeding in the models will be tested experimentally, and, in the third aim, correlated to clinical bleeding patterns. The models will also be used to predict th response to therapy in a cohort of hemophilia patients with inhibitors. The approach is innovative because it represents a new and substantive departure from the status quo, namely a focus on the biophysical mechanisms of bleeding. The proposed research is significant because it is the first step in a continuum of research expected to lead ultimately to improved diagnosis and therapeutic strategies to prevent bleeding across a wide range of pathologies.

Public Health Relevance

It important to understand why some people bleed more than others. Currently, there are no methods that can accurately predict this problem. We are trying to develop models where we can diagnose bleeding disorders and eventually predict risk for bleeding for example during surgery.

National Institute of Health (NIH)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Qasba, Pankaj
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Colorado School of Mines
Engineering (All Types)
Schools of Arts and Sciences
United States
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