From Principle to Practice: Bridging the Gap in Patient Profiling

Department of Biochemistry, University of Vermont, Burlington, Vermont, United States of America.
PLoS ONE (Impact Factor: 3.23). 01/2013; 8(1):e54728. DOI: 10.1371/journal.pone.0054728
Source: PubMed


The standard clinical coagulation assays, activated partial thromboplastin time (aPTT) and prothrombin time (PT) cannot predict thrombotic or bleeding risk. Since thrombin generation is central to haemorrhage control and when unregulated, is the likely cause of thrombosis, thrombin generation assays (TGA) have gained acceptance as "global assays" of haemostasis. These assays generate an enormous amount of data including four key thrombin parameters (lag time, maximum rate, peak and total thrombin) that may change to varying degrees over time in longitudinal studies. Currently, each thrombin parameter is averaged and presented individually in a table, bar graph or box plot; no method exists to visualize comprehensive thrombin generation data over time. To address this need, we have created a method that visualizes all four thrombin parameters simultaneously and can be animated to evaluate how thrombin generation changes over time. This method uses all thrombin parameters to intrinsically rank individuals based on their haemostatic status. The thrombin generation parameters can be derived empirically using TGA or simulated using computational models (CM). To establish the utility and diverse applicability of our method we demonstrate how warfarin therapy (CM), factor VIII prophylaxis for haemophilia A (CM), and pregnancy (TGA) affects thrombin generation over time. The method is especially suited to evaluate an individual's thrombotic and bleeding risk during "normal" processes (e.g pregnancy or aging) or during therapeutic challenges to the haemostatic system. Ultimately, our method is designed to visualize individualized patient profiles which are becoming evermore important as personalized medicine strategies become routine clinical practice.

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    ABSTRACT: Computational models can offer an integrated view of blood clotting dynamics and may ultimately be instructive regarding an individual's risk of bleeding or clotting. Appropriately, developed and validated models could allow clinicians to simulate the outcomes of therapeutics and estimate risk of disease. Computational models that describe the dynamics of thrombin generation have been developed and have been used in combination with empirical studies to understand thrombin dynamics on a mechanistic basis. The translation of an individual's specific coagulation factor composition data using these models into an integrated assessment of hemostatic status may provide a route for advancing the long-term goal of individualized medicine. This review details the integrated approaches to understanding: (i) What is normal thrombin generation in individuals? (ii) What is the effect of normal range plasma composition variation on thrombin generation in pathologic states? (iii) Can disease progression or anticoagulation be followed by understanding the boundaries of normal thrombin generation defined by plasma composition? (iv) What are the controversies and limitations of current computational approaches? Progress in these areas can bring us closer to developing models that can be used to aid in identifying hemostatic risk.
    Preview · Article · Jun 2013 · Journal of Thrombosis and Haemostasis
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    ABSTRACT: Thrombin has multiple functions in blood coagulation and its regulation is central to maintaining the balance between hemorrhage and thrombosis. Empirical and computational methods that capture thrombin generation can provide advancements to current clinical screening of the hemostatic balance at the level of the individual. In any individual, procoagulant and anticoagulant factor levels together act to generate a unique coagulation phenotype (net balance) that is reflective of the sum of its developmental, environmental, genetic, nutritional and pharmacological influences. Defining such thrombin phenotypes may provide a means to track disease progression pre-crisis. In this review we briefly describe thrombin function, methods for assessing thrombin dynamics as a phenotypic marker, computationally derived thrombin phenotypes versus determined clinical phenotypes, the boundaries of normal range thrombin generation using plasma composition based approaches and the feasibility of these approaches for predicting risk.
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    ABSTRACT: Purpose of review: There exists an imbalance between our understanding of the physiology of the blood coagulation process and the translation of this understanding into useful assays for clinical application. As technology advances, the capabilities for merging the two areas have become more attainable. Global assays have advanced our understanding of the dynamics of the blood coagulation process beyond end point assays and are at the forefront of implementation in the clinic. Recent findings: We will review recent advances in the main global assays with a focus on thrombin generation that have potential for clinical utility. These assays include direct (thrombogram, whole blood, purified systems) and indirect empirical measures of thrombin generation (thromboelastography) and mechanism-based computational models that use plasma composition data from individuals to generate thrombin generation profiles. Summary: Empirical thrombin generation assays (direct and indirect) and computational modeling of thrombin generation have greatly advanced our understanding of the hemostatic balance. Implementation of these types of assays and visualization approaches in the clinic will potentially provide a basis for the development of individualized patient care. Advances in both empirical and computational global assays have made the goal of predicting precrisis changes in an individual's hemostatic state one step closer.
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