Thrombin generation profiles in deep venous thrombosis

BACKGROUND: Reliable markers and methods to predict risk for thrombosis are essential to clinical management. OBJECTIVE: Using an integrated approach that defines an individual’s comprehensive coagulation phenotype might prove valuable in identifying individuals at risk for experiencing a thrombotic event. METHODS: Using a numerical simulation model, we generated tissue factor (TF) initiated thrombin curves using coagulation factor levels from the Leiden Thrombophilia Study population and evaluated thrombotic risk, by sex, age, smoking, alcohol consumption, body mass index (BMI) and oral contraceptive (OC) use. We quantitated the initiation, propagation and termination phases of each individuals’ comprehensive TF-initiated thrombin generation curve by the parameters: time to 10nM thrombin, maximum time, level and rate (MaxR) of thrombin generated and total thrombin. RESULTS: The greatest risk association was obtained using MaxR; with a 2.6 fold increased risk at MaxR exceeding the 90(th) percentile. The odds ratio (OR) for MaxR was 3.9 in men, 2.1 in women, and 2.9 in women on OCs. The association of risk with thrombin generation did not differ by age (OR:2.8≤45 years>OR:2.5), BMI (OR:2.9≤26 kg/m(2)>OR:2.3) or alcohol use. In both numerical simulations and empirical synthetic plasma, OC use created extreme shifts in thrombin generation in both control women and women with a prior thrombosis, with a larger shift in thrombin generation in control women. This suggests an interaction of OC use with underlying prothrombotic abnormalities. CONCLUSIONS: Thrombin generation based upon the individual’s blood composition is associated with the risk for thrombosis and may be useful as a predictive marker for evaluating thrombosis on an individual basis

Analysis of the potential of cancer cell lines to release tissue factor-containing microvesicles: correlation with tissue factor and PAR2 expression

BackgroundDespite the association of cancer-derived circulating tissue factor (TF)-containing microvesicles and hypercoagulable state, correlations with the incidence of thrombosis remain unclear.MethodsIn this study the upregulation of TF release upon activation of various cancer cell lines, and the correlation with TF and PAR2 expression and/or activity was examined. Microvesicle release was induced by PAR2 activation in seventeen cell lines and released microvesicle density, microvesicle-associated TF activity, and phoshpatidylserine-mediated activity were measured. The time-course for TF release was monitored over 90 min in each cell line. In addition, TF mRNA expression, cellular TF protein and cell-surface TF activities were quantified. Moreover, the relative expression of PAR2 mRNA and cellular protein were analysed. Any correlations between the above parameters were examined by determining the Pearson’s correlation coefficients.ResultsTF release as microvesicles peaked between 30–60 min post-activation in the majority of cell lines tested. The magnitude of the maximal TF release positively correlated with TF mRNA (c = 0.717; p

Factor Xa Generation by Computational Modeling: An Additional Discriminator to Thrombin Generation Evaluation

Factor (f)Xa is a critical enzyme in blood coagulation that is responsible for the initiation and propagation of thrombin generation. Previously we have shown that analysis of computationally generated thrombin profiles is a tool to investigate hemostasis in various populations. In this study, we evaluate the potential of computationally derived time courses of fXa generation as another approach for investigating thrombotic risk. Utilizing the case (n = 473) and control (n = 426) population from the Leiden Thrombophilia Study and each individual's plasma protein factor composition for fII, fV, fVII, fVIII, fIX, fX, antithrombin and tissue factor pathway inhibitor, tissue factor-initiated total active fXa generation was assessed using a mathematical model. FXa generation was evaluated by the area under the curve (AUC), the maximum rate (MaxR) and level (MaxL) and the time to reach these, TMaxR and TMaxL, respectively. FXa generation was analyzed in the entire populations and in defined subgroups (by sex, age, body mass index, oral contraceptive use). The maximum rates and levels of fXa generation occur over a 10- to 12- fold range in both cases and controls. This variation is larger than that observed with thrombin (3–6 fold) in the same population. The greatest risk association was obtained using either MaxR or MaxL of fXa generation; with an ∼2.2 fold increased risk for individuals exceeding the 90th percentile. This risk was similar to that of thrombin generation(MaxR OR 2.6). Grouping defined by oral contraceptive (OC) use in the control population showed the biggest differences in fXa generation; a >60% increase in the MaxR upon OC use. FXa generation can distinguish between a subset of individuals characterized by overlapping thrombin generation profiles. Analysis of fXa generation is a phenotypic characteristic which may prove to be a more sensitive discriminator than thrombin generation among all individuals

Syncytiotrophoblast Microvesicles Released from Pre-Eclampsia Placentae Exhibit Increased Tissue Factor Activity

Background: Pre-eclampsia is a complication of pregnancy associated with activation of coagulation. It is caused by the placenta, which sheds increased amounts of syncytiotrophoblast microvesicles (STBM) into the maternal circulation. We hypothesized that STBM could contribute to the haemostatic activation observed in pre-eclampsia. Methodology/Principal Findings: STBM were collected by perfusion of the maternal side of placentae from healthy pregnant women and women with pre-eclampsia at caesarean section. Calibrated automated thrombography was used to assess thrombin generation triggered by STBM-borne tissue factor in platelet poor plasma (PPP). No thrombin was detected in PPP alone but the addition of STBM initiated thrombin generation in 14/16 cases. Pre-eclampsia STBM significantly shortened the lag time (LagT, P = 0.01) and time to peak thrombin generation (TTP, P = 0.005) when compared to normal STBM. Blockade of tissue factor eliminated thrombin generation, while inhibition of tissue factor pathway inhibitor significantly shortened LagT (p = 0.01) and TTP (P,0.0001), with a concomitant increase in endogenous thrombin potential. Conclusions/Significance: STBM triggered thrombin generation in normal plasma in a tissue factor dependent manner, indicating that TF activity is expressed by STBM. This is more pronounced in STBM shed from pre-eclampsia placentae. As more STBM are shed in pre-eclampsia these observations give insight into the disordered haemostasis observed in thi

Coagulation factor XII genetic variation, ex vivo thrombin generation, and stroke risk in the elderly: results from the Cardiovascular Health Study

Relationships of thrombin generation (TG) with cardiovascular disease risk are under-evaluated in population-based cohorts

Defining the Boundaries of Normal Thrombin Generation: Investigations into Hemostasis

In terms of its soluble precursors, the coagulation proteome varies quantitatively among apparently healthy individuals. The significance of this variability remains obscure, in part because it is the backdrop against which the hemostatic consequences of more dramatic composition differences are studied. In this study we have defined the consequences of normal range variation of components of the coagulation proteome by using a mechanism-based computational approach that translates coagulation factor concentration data into a representation of an individual's thrombin generation potential. A novel graphical method is used to integrate standard measures that characterize thrombin generation in both empirical and computational models (e.g max rate, max level, total thrombin, time to 2 nM thrombin (“clot time”)) to visualize how normal range variation in coagulation factors results in unique thrombin generation phenotypes. Unique ensembles of the 8 coagulation factors encompassing the limits of normal range variation were used as initial conditions for the computational modeling, each ensemble representing “an individual” in a theoretical healthy population. These “individuals” with unremarkable proteome composition was then compared to actual normal and “abnormal” individuals, i.e. factor ensembles measured in apparently healthy individuals, actual coagulopathic individuals or artificially constructed factor ensembles representing individuals with specific factor deficiencies. A sensitivity analysis was performed to rank either individual factors or all possible pairs of factors in terms of their contribution to the overall distribution of thrombin generation phenotypes. Key findings of these analyses include: normal range variation of coagulation factors yields thrombin generation phenotypes indistinguishable from individuals with some, but not all, coagulopathies examined; coordinate variation of certain pairs of factors within their normal ranges disproportionately results in extreme thrombin generation phenotypes, implying that measurement of a smaller set of factors may be sufficient to identify individuals with aberrant thrombin generation potential despite normal coagulation proteome composition

Anticoagulants and the Propagation Phase of Thrombin Generation

The view that clot time-based assays do not provide a sufficient assessment of an individual's hemostatic competence, especially in the context of anticoagulant therapy, has provoked a search for new metrics, with significant focus directed at techniques that define the propagation phase of thrombin generation. Here we use our deterministic mathematical model of tissue-factor initiated thrombin generation in combination with reconstructions using purified protein components to characterize how the interplay between anticoagulant mechanisms and variable composition of the coagulation proteome result in differential regulation of the propagation phase of thrombin generation. Thrombin parameters were extracted from computationally derived thrombin generation profiles generated using coagulation proteome factor data from warfarin-treated individuals (N = 54) and matching groups of control individuals (N = 37). A computational clot time prolongation value (cINR) was devised that correlated with their actual International Normalized Ratio (INR) values, with differences between individual INR and cINR values shown to derive from the insensitivity of the INR to tissue factor pathway inhibitor (TFPI). The analysis suggests that normal range variation in TFPI levels could be an important contributor to the failure of the INR to adequately reflect the anticoagulated state in some individuals. Warfarin-induced changes in thrombin propagation phase parameters were then compared to those induced by unfractionated heparin, fondaparinux, rivaroxaban, and a reversible thrombin inhibitor. Anticoagulants were assessed at concentrations yielding equivalent cINR values, with each anticoagulant evaluated using 32 unique coagulation proteome compositions. The analyses showed that no anticoagulant recapitulated all features of warfarin propagation phase dynamics; differences in propagation phase effects suggest that anticoagulants that selectively target fXa or thrombin may provoke fewer bleeding episodes. More generally, the study shows that computational modeling of the response of core elements of the coagulation proteome to a physiologically relevant tissue factor stimulus may improve the monitoring of a broad range of anticoagulants