Models for thrombin generation and risk of disease

Critical evaluation of kinetic schemes for coagulation

Two well-established numerical representations of the coagulation cascade either initiated by the intrinsic system (Chatterjee et al., PLOS Computational Biology 2010) or the extrinsic system (Butenas et al., Journal of Biological Chemistry, 2004) were compared with thrombin generation assays under realistic pathological conditions. Biochemical modifications such as the omission of reactions not relevant to the case studied, the modification of reactions related to factor XI activation and auto-activation, the adaptation of initial conditions to the thrombin assay system, and the adjustment of some of the model parameters were necessary to align in vitro and in silico data. The modified models are able to reproduce thrombin generation for a range of factor XII, XI, and VIII deficiencies, with the coagulation cascade initiated either extrinsically or intrinsically. The results emphasize that when existing models are extrapolated to experimental parameters for which they have not been calibrated, careful adjustments are required.

A System-Wide Investigation and Stratification of the Hemostatic Proteome in Premature Myocardial Infarction

Introduction

Advancing understanding of key factors that determine the magnitude of the hemostatic response may facilitate the identification of individuals at risk of generating an occlusive thrombus as a result of an atherothrombotic event such as an acute Myocardial Infarction (MI). While fibrinogen levels are a recognized risk factor for MI, the association of thrombotic risk with other coagulation proteins is inconsistent. This is likely due to the complex balance of pro- and anticoagulant factors in any individual.

Methods

We compared measured levels of pro- and anticoagulant proteins in plasma from 162 patients who suffered an MI at an early age (MI <50 y) and 186 age- and gender-matched healthy controls with no history of CAD. We then used the measurements from these individuals as inputs for an established mathematical model to investigate how small variations in hemostatic factors affect the overall amplitude of the hemostatic response and to identify differential key drivers of the hemostatic response in male and female patients and controls.

Results

Plasma from the MI patients contained significantly higher levels of Tissue Factor (P = 0.007), the components of the tenase (FIX and FVIII; P < 0.0001 for both) and the prothrombinase complexes (FX; P = 0.003), and lower levels of Tissue Factor Pathway Inhibitor (TFPI; P = 0.033) than controls. The mathematical model, which generates time-dependent predictions describing the depletion, activation, and interaction of the main procoagulant factors and inhibitors, identified different patterns of hemostatic response between MI patients and controls, and additionally, between males and females. Whereas, in males, TF, FVIII, FIX, and the inhibitor TFPI contribute to the differences seen between case and controls, and in females, FII, FVIII, and FIX had the greatest influence on the generation of thrombin. We additionally show that further donor stratification may be possible according to the predicted donor response to anticoagulant therapy.

Conclusions

We suggest that modeling could be of value in enhancing our prediction of risk of premature MI, recurrent risk, and therapeutic efficacy.

Computationally Driven Discovery in Coagulation

Bleeding frequency and severity within clinical categories of hemophilia A are highly variable and the origin of this variation is unknown. Solving this mystery in coagulation requires the generation and analysis of large data sets comprised of experimental outputs or patient samples, both of which are subject to limited availability. In this review, we describe how a computationally driven approach bypasses such limitations by generating large synthetic patient data sets. These data sets were created with a mechanistic mathematical model, by varying the model inputs, clotting factor, and inhibitor concentrations, within normal physiological ranges. Specific mathematical metrics were chosen from the model output, used as a surrogate measure for bleeding severity, and statistically analyzed for further exploration and hypothesis generation. We highlight results from our recent study that employed this computationally driven approach to identify FV (factor V) as a key modifier of thrombin generation in mild to moderate hemophilia A, which was confirmed with complementary experimental assays. The mathematical model was used further to propose a potential mechanism for these observations whereby thrombin generation is rescued in FVIII-deficient plasma due to reduced substrate competition between FV and FVIII for FXa (activated factor X).

Modeling Thrombin Generation in Plasma under Diffusion and Flow

We investigate the capacity of published numerical models of thrombin generation to reproduce experimentally observed threshold behavior under conditions in which diffusion and/or flow are important. Computational fluid dynamics simulations incorporating species diffusion, fluid flow, and biochemical reactions are compared with published data for thrombin generation in vitro in 1) quiescent plasma exposed to patches of tissue factor and 2) plasma perfused through a capillary coated with tissue factor. Clot time is correctly predicted in individual cases, and some models qualitatively replicate thrombin generation thresholds across a series of tissue factor patch sizes or wall shear rates. Numerical results suggest that there is not a genuine patch size threshold in quiescent plasma-clotting always occurs given enough time-whereas the shear rate threshold observed under flow is a genuine physical limit imposed by flow-mediated washout of active coagulation factors. Despite the encouraging qualitative results obtained with some models, no single model robustly reproduces all experiments, demonstrating that greater understanding of the underlying reaction network, and particularly of surface reactions, is required. In this direction, additional simulations provide evidence that 1) a surface-localized enzyme, speculatively identified as meizothrombin, is significantly active toward the fluorescent thrombin substrate used in the experiments or, less likely, 2) thrombin is irreversibly inhibited at a faster-than-expected rate, possibly explained by a stimulatory effect of plasma heparin on antithrombin. These results highlight the power of simulation to provide novel mechanistic insights that augment experimental studies and build our understanding of complex biophysicochemical processes. Further validation work is critical to unleashing the full potential of coagulation models as tools for drug development and personalized medicine.

Assessing the impact of product inhibition in a chromogenic assay

Chromogenic substrates (CS) are synthetic substrates used to monitor the activity of a target enzyme. It has been reported that some CSs display competitive product inhibition with their target enzyme. Thus, in assays where enzyme activity is continuously monitored over long periods of time, the product inhibition may significantly interfere with the reactions being monitored. Despite this knowledge, it is rare for CSs to be directly incorporated into mathematical models that simulate these assays. This devalues the predictive power of the models. In this study, we examined the interactions between a single enzyme, coagulation factor Xa, and its chromogenic substrate. We developed, and experimentally validated, a mathematical model of a chromogenic assay for factor Xa that explicitly included product inhibition from the CS. We employed Bayesian inference, in the form of Markov-Chain Monte Carlo, to estimate the strength of the product inhibition and other sources of uncertainty such as pipetting error and kinetic rate constants. Our model, together with carefully calibrated biochemistry experiments, allowed for full characterization of the strength and impact of product inhibition in the assay. The effect of CS product inhibition in more complex reaction mixtures was further explored using mathematical models.

In silico thrombin generation: Plasma composition imbalance and mortality in human immunodeficiency virus

Background

Effective HIV treatment with antiretroviral therapy has prolonged survival and shifted causes of death to non-AIDS illnesses such as cardiovascular disease. We have shown that inflammation and HIV viral load associate with pro- and anticoagulant factor imbalances resulting in increased thrombin generation when mathematically modeled. We explore the hypothesis that factor compositional imbalance, corresponding to increased in silico thrombin generation, predicts mortality among HIV+ persons.

Methods

In a nested case-control study of HIV+ individuals on continuous antiretroviral therapy in two large trials, we evaluated cases (any non-violent mortality, n = 114) and matched controls (n = 318). Thrombin generation in response to a tissue-factor initiator for each individual was calculated by a mathematical model incorporating levels of factors (F)II, V, VII, VIII, IX, X, antithrombin, tissue factor pathway inhibitor, and protein C (PC) measured at study entry to the trials. In silico thrombin generation metrics included clot time, maximum rate (MaxR), maximum level (MaxL), and area under the curve (AUC).

Results

Levels of antithrombin and PC decreased, while FV and FVIII were higher in cases vs controls. This resulted in a more procoagulant phenotype with increased MaxR, MaxL, and AUC in cases compared to controls (P < 0.05 for all).

Conclusions

Antithrombin, FV, FVIII, and PC were the major contributors to the increased thrombin generation associated with mortality risk. Our results suggest that mortality in HIV is associated with an increase in in silico thrombin generation via altered balance of pro- and anticoagulant factors, likely due to an inflammatory response signal, and resulting coagulopathy.

Measuring fibrinolysis: from research to routine diagnostic assays

Development and standardization of fibrinolysis methods have progressed more slowly than coagulation testing and routine high-throughput screening tests for fibrinolysis are still lacking. In laboratory research, a variety of approaches are available and are applied to understand the regulation of fibrinolysis and its contribution to the hemostatic balance. Fibrinolysis in normal blood is slow to develop. For practical purposes plasminogen activators can be added to clotting plasma, or euglobulin prepared to reduce endogenous inhibitors, but results are complicated by these manipulations. Observational studies to identify a 'fibrinolysis deficit' have concluded that excess fibrinolysis inhibitors, plasminogen activator inhibitor 1 (PAI-1) or thrombin-activatable fibrinolysis inhibitor (TAFI), zymogen or active enzyme, may be associated with an increased risk of thrombosis. However, results are not always consistent and problems of adequate standardization are evident with these inhibitors and also for measurement of fibrin degradation products (D-dimer). Few methods are available to investigate fibrinolysis under flow, or in whole blood, but viscoelastic methods (VMs) such as ROTEM and TEG do permit the contribution of cells, and importantly platelets, to be explored. VMs are used to diagnose clinical hyperfibrinolysis, which is associated with high mortality. There is a debate on the usefulness of VMs as a point-of-care test method, particularly in trauma. Despite the difficulties of many fibrinolysis methods, research on the fibrinolysis system, taking in wider interactions with hemostasis proteins, is progressing so that in future we may have more complete models and better diagnostic methods and therapeutics.

In silico thrombin and factor Xa generation profiles in adult patients after Fontan operation

: Single-ventricle defects are associated with increased risk of thromboembolic events. To analyze the prothrombotic potential in a long-term follow-up on Fontan patients via plasma contribution to thrombin and factor (F)Xa generation profiles. Thrombin and FXa generation was simulated from plasma concentrations of FII, FV, FVII, FVIII, FIX, FX, antithrombin and tissue factor (TF) pathway inhibitor from Fontan patients (n = 48) and healthy controls (n = 34). TF and thrombin-antithrombin complex (TAT) were measured by ELISA. Fontan patients had significantly reduced procoagulant protein concentrations and increased anticoagulant protein concentrations over controls, resulting in a lowered procoagulant potential. However, Fontan patients showed increased hemostatic activation as evidenced by increased TF and TAT. Modeling this increased TF showed a more prothrombotic profile. Observed changes in procoagulant and anticoagulant proteins may be a compensatory mechanism aimed at mitigating the underlying disease effects characterized by elevated TF and TAT.

Serum albumin levels and depression in people living with Human Immunodeficiency Virus infection: a cross-sectional study

BACKGROUND

Lower serum albumin levels and depression are common among HIV-infected persons. High serum albumin levels may provide protection against depression through its defensive role in inflammation and infection. We tested the hypothesis of an independent relationship between serum albumin levels and depressive symptoms in a cohort of HIV-infected persons.

METHODS

A cross-sectional survey was conducted among 310 HIV-infected persons (176 men and 134 women) aged 20-60years residing in the Kathmandu Valley, Nepal. The bromocresol green method was used to measure serum albumin levels and the Beck Depression Inventory method was used to measure depressive symptoms, with a cut off score of 20 or higher indicating likely depression. The relationship between serum albumin levels and depressive symptoms was assessed using both multiple linear regression analysis and multiple logistic regression analysis, with adjustment for sociodemographic, cardiovascular, life-style, and HIV-related clinical and treatment confounding factors.

RESULTS

Serum albumin levels were inversely associated with depressive symptoms scores (beta for 1 unit change in serum albumin levels: β=-3.91; p=0.001) for the total participant sample. This inverse association was significant in both men (β=-3.93; p=0.009) and women (β=-4.47; p=0.03). A significantly decreased risk of depression was observed among participants with the highest serum albumin levels, with odds ratio and 95% CI for those with >5.0g/dL versus <4.0g/dL of 0.22 (0.06-0.80) (p=0.01).

CONCLUSION

Serum albumin levels were inversely associated with depressive symptoms scores in HIV-infected persons.

Random Forests Are Able to Identify Differences in Clotting Dynamics from Kinetic Models of Thrombin Generation

Current methods for distinguishing acute coronary syndromes such as heart attack from stable coronary artery disease, based on the kinetics of thrombin formation, have been limited to evaluating sensitivity of well-established chemical species (e.g., thrombin) using simple quantifiers of their concentration profiles (e.g., maximum level of thrombin concentration, area under the thrombin concentration versus time curve). In order to get an improved classifier, we use a 34-protein factor clotting cascade model and convert the simulation data into a high-dimensional representation (about 19000 features) using a piecewise cubic polynomial fit. Then, we systematically find plausible assays to effectively gauge changes in acute coronary syndrome/coronary artery disease populations by introducing a statistical learning technique called Random Forests. We find that differences associated with acute coronary syndromes emerge in combinations of a handful of features. For instance, concentrations of 3 chemical species, namely, active alpha-thrombin, tissue factor-factor VIIa-factor Xa ternary complex, and intrinsic tenase complex with factor X, at specific time windows, could be used to classify acute coronary syndromes to an accuracy of about 87.2%. Such a combination could be used to efficiently assay the coagulation system.

Regulation of Early Steps of GPVI Signal Transduction by Phosphatases: A Systems Biology Approach

We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation.

Mechanistic Modeling of the Effects of Acidosis on Thrombin Generation

Supplemental Digital Content is available in the text.

Published ahead of print April 2, 2015

BACKGROUND:

Acidosis, a frequent complication of trauma and complex surgery, results from tissue hypoperfusion and IV resuscitation with acidic fluids. While acidosis is known to inhibit the function of distinct enzymatic reactions, its cumulative effect on the blood coagulation system is not fully understood. Here, we use computational modeling to test the hypothesis that acidosis delays and reduces the amount of thrombin generation in human blood plasma. Moreover, we investigate the sensitivity of different thrombin generation parameters to acidosis, both at the individual and population level.

METHODS:

We used a kinetic model to simulate and analyze the generation of thrombin and thrombin–antithrombin complexes (TAT), which were the end points of this study. Large groups of temporal thrombin and TAT trajectories were simulated and used to calculate quantitative parameters, such as clotting time (CT), thrombin peak time, maximum slope of the thrombin curve, thrombin peak height, area under the thrombin trajectory (AUC), and prothrombin time. The resulting samples of parameter values at different pH levels were compared to assess the acidosis-induced effects. To investigate intersubject variability, we parameterized the computational model using the data on clotting factor composition for 472 subjects from the Leiden Thrombophilia Study. To compare acidosis-induced relative parameter changes in individual (“virtual”) subjects, we estimated the probabilities of relative change patterns by counting the pattern occurrences in our virtual subjects. Distribution overlaps for thrombin generation parameters at distinct pH levels were quantified using the Bhattacharyya coefficient.

RESULTS:

Acidosis in the range of pH 6.9 to 7.3 progressively increased CT, thrombin peak time, AUC, and prothrombin time, while decreasing maximum slope of the thrombin curve and thrombin peak height (P < 10^–5). Acidosis delayed the onset and decreased the amount of TAT generation (P < 10^–5). As a measure of intrasubject variability, maximum slope of the thrombin curve and CT displayed the largest and second-largest acidosis-induced relative changes, and AUC displayed the smallest relative changes among all thrombin generation parameters in our virtual subject group (1-sided 95% lower confidence limit on the fraction of subjects displaying the patterns, 0.99). As a measure of intersubject variability, the overlaps between the maximum slope of the thrombin curve distributions at acidotic pH levels with the maximum slope of the thrombin curve distribution at physiological pH level systematically exceeded analogous distribution overlaps for CT, thrombin peak time, and prothrombin time.

CONCLUSIONS:

Acidosis affected all quantitative parameters of thrombin and TAT generation. While maximum slope of the thrombin curve showed the highest sensitivity to acidosis at the individual-subject level, it may be outperformed by CT, thrombin peak time, and prothrombin time as an indicator of acidosis at the subject-group level.

Calibrated automated thrombography for monitoring coagulation function in patients with intracerebral haemorrhage

OBJECTIVE

To monitor coagulation function in patients with intracerebral haemorrhage (ICH) using calibrated automated thrombography.

METHODS

Patients admitted to hospital with ICH (confirmed within 18 h of symptom onset) were enrolled. Patient history and blood samples were obtained within 6 h of admission; further blood samples were collected on days 4, 8 and 15 (or on discharge between days 9-15: grouped with day 15 data). Blood samples were also collected from age- and sex-matched healthy controls. All samples underwent calibrated automated thrombography.

RESULTS

At admission, thrombin lag time and time to peak was longer, and endogenous thrombin potential and peak height were lower, in patients with ICH (n = 20) than in healthy controls (n = 29). Lag time in patients with ICH gradually decreased, but remained significantly longer than in controls until day 8. Time to peak also gradually decreased, but remained longer in patients than in controls by day 15. Endogenous thrombin potential and peak height gradually increased in patients, but remained lower than in controls on day 15.

CONCLUSIONS

Patients with ICH have poorer coagulation function than healthy individuals, but this function gradually recovers during hospitalization.

Global assays of hemostasis

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.

Modeling thrombin generation: plasma composition based approach

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.

Real-time measurement of thrombin generation using continuous droplet microfluidics

Thrombin, which has the leading role in the blood coagulation cascade, is an important biomarker in hemostasis and cardiovascular disease (CVD) development. In this study, a measurement system capable of continuously monitoring individual thrombin generation using droplet microfluidic technology is manipulated. The thrombin generation assay based on fluogenic substrate is performed within the droplets and the thrombin generation curve of plasma sample activated by tissue factor is measured in real-time to reflect the sample conditions dynamically. The injection of the inhibitor of thrombin generation is developed to assay the inhibited curve which relates to thrombin self-inhibition in biological systems. This microfluidic system is integrated with the microdialysis probe, which is useful to connect to the living animals for future in vivo real time thrombin measurements for rapid CVD diagnosis.

Massive exploration of perturbed conditions of the blood coagulation cascade through GPU parallelization

The introduction of general-purpose Graphics Processing Units (GPUs) is boosting scientific applications in Bioinformatics, Systems Biology, and Computational Biology. In these fields, the use of high-performance computing solutions is motivated by the need of performing large numbers of in silico analysis to study the behavior of biological systems in different conditions, which necessitate a computing power that usually overtakes the capability of standard desktop computers. In this work we present coagSODA, a CUDA-powered computational tool that was purposely developed for the analysis of a large mechanistic model of the blood coagulation cascade (BCC), defined according to both mass-action kinetics and Hill functions. coagSODA allows the execution of parallel simulations of the dynamics of the BCC by automatically deriving the system of ordinary differential equations and then exploiting the numerical integration algorithm LSODA. We present the biological results achieved with a massive exploration of perturbed conditions of the BCC, carried out with one-dimensional and bi-dimensional parameter sweep analysis, and show that GPU-accelerated parallel simulations of this model can increase the computational performances up to a 181× speedup compared to the corresponding sequential simulations.

A meta-analysis of genome-wide association studies identifies ORM1 as a novel gene controlling thrombin generation potential

Genetic variations at the ORM1 locus and concentrations of the encoded protein associate with thrombin generation. These findings may guide the development of novel antithrombotic treatments.

Systemic effects of inflammation on health during chronic HIV infection

Combination antiretroviral therapy for HIV infection improves immune function and eliminates the risk of AIDS-related complications but does not restore full health. HIV-infected adults have excess risk of cardiovascular, liver, kidney, bone, and neurologic diseases. Many markers of inflammation are elevated in HIV disease and strongly predictive of the risk of morbidity and mortality. A conceptual model has emerged to explain this syndrome of diseases where HIV-mediated destruction of gut mucosa leads to local and systemic inflammation. Translocated microbial products then pass through the liver, contributing to hepatic damage, impaired microbial clearance, and impaired protein synthesis. Chronic activation of monocytes and altered liver protein synthesis subsequently contribute to a hypercoagulable state. The combined effect of systemic inflammation and excess clotting on tissue function leads to end-organ disease. Multiple therapeutic interventions designed to reverse these pathways are now being tested in the clinic. It is likely that knowledge gained on how inflammation affects health in HIV disease could have implications for our understanding of other chronic inflammatory diseases and the biology of aging.

A simplified mathematical model for thrombin generation

A new phenomenological mathematical model based directly on laboratory data for thrombin generation and having a patient-specific character is described. A set of the solved equations for cell-based models of blood coagulation that can reproduce the temporal evolution of thrombin generation is proposed; such equations are appropriate for use in computational fluid dynamic (CFD) simulations. The initial values for the reaction rates are either taken from already existing model or experimental data, or they can obtained from simple reasoning under certain assumptions; it is shown that coefficients can be adjusted in order to fit a range of different thrombin generation curves as derived from thrombin generation assays. The behaviour of the model for different platelet concentration seems to be in good agreement with reported experimental data. It is shown that the reduced set of equations used represents to a good approximation a low-order model of the detailed mechanism and thus it can represent a cost-effective and-case specific mathematical model of coagulation reactions up to thrombin generation.