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There is ongoing debate as to whether abacavir (ABC) increases the risk for cardiovascular disease(CVD) in people living with HIV (PLHIV) and the mechanisms underlying this possible association. We recently showed that the use of an ABC-containing regimen was independently associated with increased thrombin generation (TG). In the present study, we aim to explore these findings further, by studying the mechanistical processes that underly the global thrombin generation test via thrombin dynamics analysis. Thrombin dynamics analysis can pinpoint the cause of increased thrombin generation associated with ABC-use either to the procoagulant prothrombin conversion pathway or the anticoagulant thrombin inactivation pathway. In this cross-sectional study, 208 virally suppressed PLHIV were included, of whom 94 were on a ABC-containing regimen, 92 on a tenofovir disoproxil fumarate (TDF)-containing regimen, and the remainder on other regimens. We used Calibrated Automated Thrombinography to measure thrombin generation and perform thrombin dynamics analysis. The total amount of prothrombin conversion, as well as the maximum rate of prothrombin conversion were significantly increased in PLHIV on an ABC containing regimen compared to other treatment regimens. The levels of pro- and anticoagulant factors were comparable, indicating that the ABC-induced changes affect the kinetics of prothrombin conversion rather than procoagulant factor levels. Moreover, Von Willebrand Factor (VWF), active VWF and VWF pro-peptide levels were significantly higher in PLHIV than controls without HIV. However, they did not differ between ABC and non-ABC treated participants., Competing Interests: QY, SH, RL-K, MN, and BL are employees of Synapse Research Institute, part of Diagnostica Stago SAS. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yan, Huang, van der Heijden, Ninivaggi, van de Wijer, de Laat-Kremers, Van der Ven, de Laat and de Mast.)

Recently, we have reported that asthma is associated with enhanced plasma thrombin formation and impaired fibrinolysis. The mechanisms underlying the prothrombotic state in this disease are unknown. Our aim was to investigate whether prothrombotic alterations in asthmatics are associated with inflammation. We studied 164 adult, white, stable asthmatics and 72 controls matched for age, sex, body mass index (BMI), and smoking. Plasma tumor necrosis factor α (TNFα), interleukin (IL)-6, and serum periostin were evaluated using ELISAs, and their associations with thrombin generation, fibrinolytic capacity, expressed as clot lysis time (CLT), and platelet markers were later analyzed. Asthma was characterized by 62% higher plasma IL-6 and 35% higher TNFα (both, p < 0.0001). Inflammatory cytokines were higher in sporadic and persistent asthmatics compared to controls, also after adjustment for potential confounders. IL-6 was inversely related to the forced expiratory volume in 1 s/vital capacity (FEV 1 /VC) spirometry index after correction for age, sex, and BMI. IL-6 and TNFα were associated with C-reactive protein in asthmatics (β = 0.6 [95% CI, 0.54-0.67] and β = 0.33 [95% CI, 0.25-0.41], respectively) and controls (β = 0.43 [95% CI, 0.29-0.57] and β = 0.33 [95% CI, 0.18-0.48], respectively). In asthma, IL-6 and TNFα positively correlated with the endogenous thrombin potential (β = 0.35 [95% CI, 0.28-0.42] and β = 0.15 [95% CI, 0.07-0.23], respectively) but not with CLT or platelet markers. However, TNFα predicted CLT in a multiple linear regression model. Periostin was not associated with any hemostatic parameters. Enhanced thrombin generation is driven in asthma by a systemic inflammatory state mediated by IL-6 and to a lesser extent TNFα, however, not periostin. TNFα might contribute to impaired fibrinolysis.

Background: The generation of thrombin in time is the combined effect of the processes of prothrombin conversion and thrombin inactivation. Measurement of prothrombin consumption used to provide valuable information on hemostatic disorders, but is no longer used, due to its elaborate nature., Objectives: Because thrombin generation (TG) curves are easily obtained with modern techniques, we developed a method to extract the prothrombin conversion curve from the TG curve, using a computational model for thrombin inactivation., Methods: Thrombin inactivation was modelled computationally by a reaction scheme with antithrombin, α(2) Macroglobulin and fibrinogen, taking into account the presence of the thrombin substrate ZGGR-AMC used to obtain the experimental data. The model was validated by comparison with data obtained from plasma as well as from a reaction mixture containing the same reactants as plasma., Results: The computational model fitted experimental data within the limits of experimental error. Thrombin inactivation curves were predicted within 2 SD in 96% of healthy subjects. Prothrombin conversion was calculated in 24 healthy subjects and validated by comparison with the experimental consumption of prothrombin during TG. The endogenous thrombin potential (ETP) mainly depends on the total amount of prothrombin converted and the thrombin decay capacity, and the peak height is determined by the maximum prothrombin conversion rate and the thrombin decay capacity., Conclusions: Thrombin inactivation can be accurately predicted by the proposed computational model and prothrombin conversion can be extracted from a TG curve using this computational prediction. This additional computational analysis of TG facilitates the analysis of the process of disturbed TG., (© 2014 International Society on Thrombosis and Haemostasis.)

Abstract: To obtain a thrombin generation (TG) curve from the conversion of added fluorogenic substrate, thrombin concentrations are to be derived from the observed velocity of increase of fluorescence (dF/dt). The relation between velocity and thrombin concentration varies during the experiment because substrate is consumed and because fluorescence is not linear with the concentration of product. Here we review the techniques that we developed to: A: Transform the fluorescence trace into the “ideal” trace that would be seen if substrate consumption and non-linearity of fluorescence would not play a role. B: Subtract the contribution of α2M-thrombin so as to obtain the course of free thrombin. C: Calculate the velocity of prothrombin conversion from the course of free thrombin. D: Fit a smooth curve through the points obtained in a TG experiment [Copyright &y& Elsevier]