ArticleResearch and practice in thrombosis and haemostasis2024
Mathematical modeling identifies clotting factor combinations that modify thrombin generation in normal and factor VIII-, IX-, or XI-deficient blood.
Article in Research and practice in thrombosis and haemostasis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Mesoscale Simulations of Blood Coagulation in Flow and Quiescent Domains Using SDPD.International journal for numerical methods in biomedical engineering · 2026Article
- Mathematical modeling of flow-mediated thrombin generation after treatment of postoperative bleeding in cardiac surgery with cardiopulmonary bypass.Journal of thrombosis and haemostasis : JTH · 2026Article
- Fibrin-bound thrombin determines clot structure and blood thrombogenicity in normofibrinogenemia and dysfibrinogenemia.Haematologica · 2026Article
- Modeling the role of platelet-released polyphosphates in tissue factor-initiated coagulation under flow.Research and practice in thrombosis and haemostasis · 2026Article
- Mechanisms of thrombin inhibition by protein S and the TFPIα-fVshort-protein S complex.Biophysical journal · 2026Article
- Internal fibrinolysis of fibrin clots is driven by pore expansion.Scientific reports · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
Background: In healthy individuals, plasma levels of clotting proteins naturally vary within a range of 50% to 150% of their mean values. We do not know how these variations modify thrombin generation. Objectives: To assess the impact of protein level variations on simulated thrombin generation in normal and factor (F)VIII-, FIX-, or FXI-deficient blood. Methods: We used a mathematical model of flow-mediated coagulation to simulate thrombin generation with all possible combinations of clotting protein variations within the normal range and for various tissue factor levels. We selected, analyzed, and ranked combinations that enhanced thrombin generation compared with baseline. Results: Protein variations most strongly affected thrombin generation at intermediate tissue factor levels. Low tissue factor levels prevented coagulation initiation, while high tissue factor levels always triggered thrombin generation. At intermediate levels, we identified protein variations that substantially modified thrombin generation. Low-normal FV shortened lag times and increased thrombin generation, whereas high-normal FV lengthened lag times and reduced thrombin generation. With severe FVIII and FIX deficiencies, low-normal tissue factor pathway inhibitor α and antithrombin amplified the effect of low-normal FV. For moderate FVIII and FIX deficiencies, high-normal tissue factor pathway inhibitor α and antithrombin enhanced the impact of high-normal FV in reducing thrombin production. In normal and FXI-deficient blood, high-normal FVIII and FIX significantly boosted thrombin generation. Conclusion: Our mathematical model predicted how variations in clotting protein levels, within the normal range, could contribute to the variability of bleeding phenotypes observed with clotting factor deficiencies. Our study generated experimentally testable hypotheses that could aid in developing new therapies toward normal hemostasis.
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