The prothrombotic phenotypes in familial protein C deficiency are differentiated by computational modeling of thrombin generation

Mathematical models of coagulation-are we there yet?

BACKGROUND

Mathematical models of coagulation have been developed to mirror thrombin generation in plasma, with the aim of investigating how variation in coagulation factor levels regulates hemostasis. However, current models vary in the reactions they capture and the reaction rates used, and their validation is restricted by a lack of large coherent datasets, resulting in questioning of their utility.

OBJECTIVES

To address this debate, we systematically assessed current models against a large dataset, using plasma coagulation factor levels from 348 individuals with normal hemostasis to identify the causes of these variations.

METHODS

We compared model predictions with measured thrombin generation, quantifying and comparing the ability of each model to predict thrombin generation, the contributions of the individual reactions, and their dependence on reaction rates.

RESULTS

We found that no current model predicted the hemostatic response across the whole cohort and all produced thrombin generation curves that did not resemble those obtained experimentally. Our analysis has identified the key reactions that lead to differential model predictions, where experimental uncertainty leads to variability in predictions, and we determined reactions that have a high influence on measured thrombin generation, such as the contribution of factor XI.

CONCLUSION

This systematic assessment of models of coagulation, using large dataset inputs, points to ways in which these models can be improved. A model that accurately reflects the effects of the multiple subtle variations in an individual's hemostatic profile could be used for assessing antithrombotics or as a tool for precision medicine.

A Review of Quantitative Systems Pharmacology Models of the Coagulation Cascade: Opportunities for Improved Usability

Despite the numerous therapeutic options to treat bleeding or thrombosis, a comprehensive quantitative mechanistic understanding of the effects of these and potential novel therapies is lacking. Recently, the quality of quantitative systems pharmacology (QSP) models of the coagulation cascade has improved, simulating the interactions between proteases, cofactors, regulators, fibrin, and therapeutic responses under different clinical scenarios. We aim to review the literature on QSP models to assess the unique capabilities and reusability of these models. We systematically searched the literature and BioModels database reviewing systems biology (SB) and QSP models. The purpose and scope of most of these models are redundant with only two SB models serving as the basis for QSP models. Primarily three QSP models have a comprehensive scope and are systematically linked between SB and more recent QSP models. The biological scope of recent QSP models has expanded to enable simulations of previously unexplainable clotting events and the drug effects for treating bleeding or thrombosis. Overall, the field of coagulation appears to suffer from unclear connections between models and irreproducible code as previously reported. The reusability of future QSP models can improve by adopting model equations from validated QSP models, clearly documenting the purpose and modifications, and sharing reproducible code. The capabilities of future QSP models can improve from more rigorous validation by capturing a broader range of responses to therapies from individual patient measurements and integrating blood flow and platelet dynamics to closely represent in vivo bleeding or thrombosis risk.

A Series of 14 Polish Patients with Thrombotic Events and PC Deficiency-Novel c.401-1G>A PROC Gene Splice Site Mutation in a Patient with Aneurysms

Objectives: Protein C (PC) deficiency is an inherited thrombophilia with a prevalence of 0.5% in the general population and 3% in subjects with a first-time deep vein thrombosis (DVT). Here we report a series of 14 PC-deficient Polish patients with comprehensive clinical and molecular characteristics, including long-term follow-up data and a deep mutational analysis of the PROC gene. Patients and Methods: Fourteen unrelated probands (mean ± SD age 43.8 ± 13.0 years) with suspicion of PC deficiency, who experienced thromboembolic events and a majority of whom received anticoagulants (92.8%), were screened for PROC mutations by sequencing the nine PROC exons and their flanking intron regions. Results: Ten probands (71.4%) had missense mutations, two patients (14.3%) carried nonsense variants, and the other two subjects (14.3%) had splice-site mutations, the latter including the c.401-1G>A variant, reported here for the very first time. The proband carrying the c.401-1A allele had a hepatic artery aneurysm with a highly positive family history of aneurysms and the absence of any mutations known to predispose to this vascular anomaly. Conclusion: A novel detrimental PROC mutation was identified in a family with aneurysms, which might suggest yet unclear links of thrombophilia to vascular anomalies, including aneurysms at atypical locations in women. The present case series also supports data indicating that novel oral anticoagulants (NOACs) are effective in PC deficient patients.

Personalized modulation of coagulation factors using a thrombin dynamics model to treat trauma-induced coagulopathy

Current trauma-induced coagulopathy resuscitation protocols use slow laboratory measurements, rules-of-thumb, and clinician gestalt to administer large volumes of uncharacterized, non-tailored blood products. These one-size-fits-all treatment approaches have high mortality. Here, we provide significant evidence that trauma patient survival 24 h after hospital admission occurs if and only if blood protein coagulation factor concentrations equilibrate at a normal value, either from inadvertent plasma-based modulation or from innate compensation. This result motivates quantitatively guiding trauma patient coagulation factor levels while accounting for protein interactions. Toward such treatment, we develop a Goal-oriented Coagulation Management (GCM) algorithm, a personalized and automated ordered sequence of operations to compute and specify coagulation factor concentrations that rectify clotting. This novel GCM algorithm also integrates new control-oriented advancements that we make in this work: an improvement of a prior thrombin dynamics model that captures the coagulation process to control, a use of rapidly-measurable concentrations to help predict patient state, and an accounting of patient-specific effects and limitations when adding coagulation factors to remedy coagulopathy. Validation of the GCM algorithm's guidance shows superior performance over clinical practice in attaining normal coagulation factor concentrations and normal clotting profiles simultaneously.

PC Deficiency Testing: Thrombin-Thrombomodulin as PC Activator and Aptamer-Based Enzyme Capturing Increase Diagnostic Accuracy

Protein C (PC) activity tests are routinely performed in a thrombophilia workup to screen for PC deficiency. Currently used tests combine conversion of PC to activated PC (APC) by the snake venom Protac with subsequent APC detection through hydrolysis of a chromogenic peptide substrate or prolongation of a clotting time. In this prospective cohort study, we analyzed how different modes of PC activation and subsequent APC determination influence the diagnostic accuracy of PC activity testing in a cohort of 31 patients with genetically confirmed PC deficiency. In addition to chromogenic and clot-based measurement, an oligonucleotide-based enzyme capture assay utilizing a basic exosite-targeting aptamer was used for APC detection. To study the influence of the PC activation step on diagnostic sensitivity, PC activation through Protac and through the thrombin-thrombomodulin (TM) complex were compared. Twenty-six (84%) and 24 (77%) PC deficient patients were identified as true-positive using the chromogenic and the clot-based PC activity assay, respectively. True-positive results increased to 27 (87%) when the basic exosite-targeting aptamer approach was used for APC measurement. Additional replacement of the PC activator Protac by thrombin-TM gave true-positive results in all patients. These data indicate that the mode of PC activation is crucial in determining the accuracy of PC activity testing and that diagnostic sensitivity can be significantly improved by replacing the PC activator Protac with thrombin-TM. APC detection using a basic exosite-targeting aptamer achieves high sensitivity toward mutations outside the active center while being less subject to interfering factors than clot-based PC activity assays.

Associations of longitudinal D-Dimer and Factor II on early trauma survival risk

BACKGROUND

Trauma-induced coagulopathy (TIC) is a disorder that occurs in one-third of severely injured trauma patients, manifesting as increased bleeding and a 4X risk of mortality. Understanding the mechanisms driving TIC, clinical risk factors are essential to mitigating this coagulopathic bleeding and is therefore essential for saving lives. In this retrospective, single hospital study of 891 trauma patients, we investigate and quantify how two prominently described phenotypes of TIC, consumptive coagulopathy and hyperfibrinolysis, affect survival odds in the first 25 h, when deaths from TIC are most prevalent.

METHODS

We employ a joint survival model to estimate the longitudinal trajectories of the protein Factor II (% activity) and the log of the protein fragment D-Dimer ([Formula: see text]g/ml), representative biomarkers of consumptive coagulopathy and hyperfibrinolysis respectively, and tie them together with patient outcomes. Joint models have recently gained popularity in medical studies due to the necessity to simultaneously track continuously measured biomarkers as a disease evolves, as well as to associate them with patient outcomes. In this work, we estimate and analyze our joint model using Bayesian methods to obtain uncertainties and distributions over associations and trajectories.

RESULTS

We find that a unit increase in log D-Dimer increases the risk of mortality by 2.22 [1.57, 3.28] fold while a unit increase in Factor II only marginally decreases the risk of mortality by 0.94 [0.91,0.96] fold. This suggests that, while managing consumptive coagulopathy and hyperfibrinolysis both seem to affect survival odds, the effect of hyperfibrinolysis is much greater and more sensitive. Furthermore, we find that the longitudinal trajectories, controlling for many fixed covariates, trend differently for different patients. Thus, a more personalized approach is necessary when considering treatment and risk prediction under these phenotypes.

CONCLUSION

This study reinforces the finding that hyperfibrinolysis is linked with poor patient outcomes regardless of factor consumption levels. Furthermore, it quantifies the degree to which measured D-Dimer levels correlate with increased risk. The single hospital, retrospective nature can be understood to specify the results to this particular hospital's patients and protocol in treating trauma patients. Expanding to a multi-hospital setting would result in better estimates about the underlying nature of consumptive coagulopathy and hyperfibrinolysis with survival, regardless of protocol. Individual trajectories obtained with these estimates can be used to provide personalized dynamic risk prediction when making decisions regarding management of blood factors.

Computational model of tranexamic acid on urokinase mediated fibrinolysis

Understanding the coagulation process is critical to developing treatments for trauma and coagulopathies. Clinical studies on tranexamic acid (TXA) have resulted in mixed reports on its efficacy in improving outcomes in trauma patients. The largest study, CRASH-2, reported that TXA improved outcomes in patients who received treatment prior to 3 hours after the injury, but worsened outcomes in patients who received treatment after 3 hours. No consensus has been reached about the mechanism behind the duality of these results. In this paper we use a computational model for coagulation and fibrinolysis to propose that deficiencies or depletions of key anti-fibrinolytic proteins, specifically antiplasmin, a1-antitrypsin and a2-macroglobulin, can lead to worsened outcomes through urokinase-mediated hyperfibrinolysis.

Mathematical model of thrombin generation and bleeding phenotype in Amish carriers of Factor IX:C deficiency vs. controls

INTRODUCTION

Factor IX:C (FIX:C) levels vary in hemophilia B carriers even in pedigrees with a unifying genetic defect. Analyzing the balance between pro-and anticoagulants might increase our understanding of carriers' bleeding potential.

AIM

In this research study, we evaluated bleeding scores (BS) and a novel mathematical model of thrombin generation (TG) in Amish FIX:C deficient carriers and controls.

METHODS

Blood samples and BS were obtained from post-menarchal females, including 59 carriers and 57 controls from the same extended pedigree. Factors II, V, VII, VIII, IX, X, antithrombin, tissue factor pathway inhibitor and protein C were assayed to generate mathematical models of TG in response to 5pM tissue factor (TF) and for TF + thrombomodulin. BS was based on a modification of the MCMDM-1VWD scoring system.

RESULTS

Carriers had a lower mean FIX:C (68% vs. 119%), von Willebrand factor antigen (108 vs.133) and Tissue activatable fibrinolysis inhibitor (103 vs. 111) compared to controls; both groups had a similar mean BS. Carriers demonstrated significantly lower TG parameters on both mathematical models compared to controls. Carriers with FIX:C ≤ 50% had lower TG curves than those >50% but similar BS.

CONCLUSION

Thrombin generation showed significant differences between carriers and controls, between low (≤50%) and high (>50%) FIX:C carriers, and specifically in the TF + thrombomodulin model, between high FIX:C carriers and controls, although the BS were not different.

Analysis of the role of thrombomodulin in all-trans retinoic acid treatment of coagulation disorders in cancer patients

BACKGROUND

Clinical studies have shown that all-trans retinoic acid (RA), which is often used in treatment of cancer patients, improves hemostatic parameters and bleeding complications such as disseminated intravascular coagulation (DIC). However, the mechanisms underlying this improvement have yet to be elucidated. In vitro studies have reported that RA upregulates thrombomodulin (TM) expression on the endothelial cell surface. The objective of this study was to investigate how and to what extent the TM concentration changes after RA treatment in cancer patients, and how this variation influences the blood coagulation cascade.

RESULTS

In this study, we introduced an ordinary differential equation (ODE) model of gene expression for the RA-induced upregulation of TM concentration. Coupling the gene expression model with a two-compartment pharmacokinetic model of RA, we obtained the time-dependent changes in TM and thrombomodulin-mRNA (TMR) concentrations following oral administration of RA. Our results indicated that the TM concentration reached its peak level almost 14 h after taking a single oral dose (110 [Formula: see text]) of RA. Continuous treatment with RA resulted in oscillatory expression of TM on the endothelial cell surface. We then coupled the gene expression model with a mechanistic model of the coagulation cascade, and showed that the elevated levels of TM over the course of RA therapy with a single daily oral dose (110 [Formula: see text]) of RA, reduced the peak thrombin levels and endogenous thrombin potential (ETP) up to 50 and 49%, respectively. We showed that progressive reductions in plasma levels of RA, observed in continuous RA therapy with a once-daily oral dose (110 [Formula: see text]) of RA, did not affect TM-mediated reduction of thrombin generation significantly. This finding prompts the hypothesis that continuous RA treatment has more consistent therapeutic effects on coagulation disorders than on cancer.

CONCLUSIONS

Our results indicate that the oscillatory upregulation of TM expression on the endothelial cells over the course of RA therapy could potentially contribute to the treatment of coagulation abnormalities in cancer patients. Further studies on the impacts of RA therapy on the procoagulant activity of cancer cells are needed to better elucidate the mechanisms by which RA therapy improves hemostatic abnormalities in cancer.

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.

Computational Model for Hyperfibrinolytic Onset of Acute Traumatic Coagulopathy

The onset of acute traumatic coagulopathy in trauma patients exacerbates hemorrhaging and dramatically increases mortality. The disease is characterized by increased localized bleeding, and the mechanism for its onset is not yet known. We propose that the fibrinolytic response, specifically the release of tissue-plasminogen activator (t-PA), within vessels of different sizes leads to a variable susceptibility to local coagulopathy through hyperfibrinolysis which can explain many of the clinical observations in the early stages from severely injured coagulopathic patients. We use a partial differential equation model to examine the consequences of vessel geometry and extent of injury on fibrinolysis profiles. In addition, we simulate the efficacy of tranexamic acid treatment on coagulopathy initiated through endothelial t-PA release, and are able to reproduce the time-sensitive nature of the efficacy of this treatment as observed in clinical studies.

Identification of disease states associated with coagulopathy in trauma

Background

Trauma is the leading cause of death between the ages of 1 to 44 in the United States. Blood loss is the primary cause of these deaths. The discrimination of states through which patients transition would be helpful in understanding the disease process, and in identification of critical states and appropriate interventions. Even though these states are strongly associated with patients’ blood composition data, there has not been a way to directly identify them. Statistical tools such as hidden Markov models can be used to infer the discrete latent states from the blood composition data.

Methods

We applied a hidden Markov model to time-series multivariate patient measurements from the UCSF/ San Francisco General Hospital and Trauma Center. Ten blood factor related measurements were used to identify the model: factors II, V, VII, VIII, IX, X, antithrombin III, protein C, prothrombin time and partial thromboplastin time. Missing data in the time-series dataset was considered in the hidden Markov model. The number of states was determined by minimizing the Bayesian information criterion across different numbers of states.

Results

After preprocessing, 1090 patients with a total number of 2176 time point measurements were included in the analysis. The hidden Markov model identified 6 disease states and 3 stages. We analyzed their relationships to the blood composition data and the coagulation cascade. The states are very indicative of the disease progression status of patients.

Conclusions

Six disease states and 3 stages associated with Coagulopathy in trauma were identified in our study. The hidden Markov model can be useful in identifying latent states by using patients’ time-series multivariate data. The information obtained from the states and stages can be useful in the clinical setting.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-016-0360-x) contains supplementary material, which is available to authorized users.

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.

Genetic Risk Factors in Venous Thromboembolism

Genetic risk factors predispose to thrombophilia and play the most important etiopathogenic role in venous thromboembolism (VTE) in people younger than 50 years old. At least one inherited risk factor could be found in about half of the cases with a first episode of idiopathic VTE.Roughly, genetic risk factors are classified into two main categories: loss of function mutations (such as deficiencies of antithrombin, protein C, protein S) and gain of function mutations, (such as prothrombin mutation G20210A, factor V Leiden). A revolutionary contribution to the genetic background of VTE was brought by the achievements of the genome-wide association studies which analyze the association of a huge number of polymorphisms in large sample size.Hereditary thrombophilia testing should be done only in selected cases. The detection of hereditary thrombophilia has impact on the management of the anticoagulation in children with purpura fulminans, pregnant women at risk of VTE and may be useful in the assessment of the risk for recurrent thrombosis in patients presenting an episode of VTE at a young age (<40 years) and in cases with positive family history regarding thrombosis.

Age-specific onset and distribution of the natural anticoagulant deficiency in pediatric thromboembolism

BACKGROUND

The early diagnosis of inherited thrombophilia in children is challenging because of the rarity and hemostatic maturation.

METHODS

We explored protein C (PC), protein S (PS), and antithrombin (AT) deficiencies in 306 thromboembolic patients aged ≤20 y using the screening of plasma activity and genetic analysis.

RESULTS

Reduced activities were determined in 122 patients (40%). Low PC patients were most frequently found in the lowest age group (0-2 y, 45%), while low PS or low AT patients were found in the highest age group (16-20 y; PS: 30% and AT: 20%). Genetic study was completed in 62 patients having no other causes of thromboembolism. Mutations were determined in 18 patients (8 PC, 8 PS, and 2 AT genes). Six of eight patients with PC gene mutation were found in age 0-2 y (75%), while six of eight patients with PS gene mutation were in 7-20 y. Two AT gene-mutated patients were older than 4 y. Four PC-deficient and two PS-deficient patients carried compound heterozygous mutations. All but one PC gene-mutated patient suffered from intracranial thromboembolism, while PS/AT gene-mutated patients mostly developed extracranial venous thromboembolism.

CONCLUSION

Stroke in low PC infants and deep vein thrombosis in low PS/AT school age children could be targeted for genetic screening of pediatric thrombophilias.

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.

Kinetic model facilitates analysis of fibrin generation and its modulation by clotting factors: implications for hemostasis-enhancing therapies

Current mechanistic knowledge of protein interactions driving blood coagulation has come largely from experiments with simple synthetic systems, which only partially represent the molecular composition of human blood plasma. Here, we investigate the ability of the suggested molecular mechanisms to account for fibrin generation and degradation kinetics in diverse, physiologically relevant in vitro systems. We represented the protein interaction network responsible for thrombin generation, fibrin formation, and fibrinolysis as a computational kinetic model and benchmarked it against published and newly generated data reflecting diverse experimental conditions. We then applied the model to investigate the ability of fibrinogen and a recently proposed prothrombin complex concentrate composition, PCC-AT (a combination of the clotting factors II, IX, X, and antithrombin), to restore normal thrombin and fibrin generation in diluted plasma. The kinetic model captured essential features of empirically detected effects of prothrombin, fibrinogen, and thrombin-activatable fibrinolysis inhibitor titrations on fibrin formation and degradation kinetics. Moreover, the model qualitatively predicted the impact of tissue factor and tPA/tenecteplase level variations on the fibrin output. In the majority of considered cases, PCC-AT combined with fibrinogen accurately approximated both normal thrombin and fibrin generation in diluted plasma, which could not be accomplished by fibrinogen or PCC-AT acting alone. We conclude that a common network of protein interactions can account for key kinetic features characterizing fibrin accumulation and degradation in human blood plasma under diverse experimental conditions. Combined PCC-AT/fibrinogen supplementation is a promising strategy to reverse the deleterious effects of dilution-induced coagulopathy associated with traumatic bleeding.

HIV replication alters the composition of extrinsic pathway coagulation factors and increases thrombin generation

Background

HIV infection leads to activation of coagulation, which may increase the risk for atherosclerosis and venous thromboembolic disease. We hypothesized that HIV replication increases coagulation potentially through alterations in extrinsic pathway factors.

Methods and Results

Extrinsic pathway factors were measured among a subset of HIV participants from the Strategies for Management of Anti‐Retroviral Therapy (SMART) trial. Thrombin generation was estimated using validated computational modeling based on factor composition. We characterized the effect of antiretroviral therapy (ART) treatment versus the untreated state (HIV replication) via 3 separate analyses: (1) a cross‐sectional comparison of those on and off ART (n=717); (2) a randomized comparison of deferring versus starting ART (n=217); and (3) a randomized comparison of stopping versus continuing ART (n=500). Compared with viral suppression, HIV replication consistently showed short‐term increases in some procoagulants (eg, 15% to 23% higher FVIII; P<0.001) and decreases in key anticoagulants (eg, 5% to 9% lower antithrombin [AT] and 6% to 10% lower protein C; P<0.01). The net effect of HIV replication was to increase coagulation potential (eg, 24% to 48% greater thrombin generation from computational models; P<0.01 for all). The pattern of changes from HIV replication was reversed with ART treatment and consistent across all 3 independent comparisons.

Conclusions

HIV replication leads to complex changes in extrinsic pathway factors, with the net effect of increasing coagulation potential to a degree that may be clinically relevant. The key influence of changes in FVIII and AT suggests that HIV‐related coagulation abnormalities may involve changes in hepatocyte function in the context of systemic inflammation.

Clinical Trial Registration

URL: ClinicalTrials.gov. Unique identifier: NCT00027352.

Models for thrombin generation and risk of disease

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.

From principle to practice: bridging the gap in patient profiling

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.