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Mathematical Modeling of Thrombin Generation and Wave Propagation: From Simple to Complex Models and Backwards

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Trends in Biomathematics: Mathematical Modeling for Health, Harvesting, and Population Dynamics

Abstract

Blood coagulation is an extremely complex biochemical system consisting of more than twenty proteins involved in more than a hundred chemical reactions. Correct functioning of this system is indispensable for normal hemostasis, thus its malfunctions lead to life threatening bleedings and thromboses. Huge efforts are directed to understand how this system is organized and controlled, how its response can be predicted, and what experimental methods should be used in patient diagnostics and treatment. Here, we briefly review mathematical modeling approaches existing in this field. We pay special attention to the transitions from simple to complex models and to the reduction of complex models back to simple ones, as such reduction actually provides possibility to understand the fundamental mechanisms of functioning of complex biological systems besides coagulation.

The author “A. Tokarev” was working in the institute “Dmitry Rogachev” at the time of presentation of this work in a session of the BIOMAT 2018 in Morocco.

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References

  1. H.C. Hemker, S. Béguin, Thrombin generation in plasma: its assessment via the endogenous thrombin potential. Thromb. Haemost. 74, 134–138 (1995)

    Google Scholar 

  2. H.C. Hemker, P. Giesen, R. AlDieri, V. Regnault, E. De Smed, R. Wagenvoord, T. Lecompte, S. Béguin, The calibrated automated thrombogram (CAT): a universal routine test for hyper- and hypocoagulability. Pathophysiol. Haemost. Thromb. 32, 249–253 (2002)

    Article  Google Scholar 

  3. N.M.M. Dashkevich, M.V. V. Ovanesov, A.N.N. Balandina, S.S.S. Karamzin, P.I.I. Shestakov, N.P.P. Soshitova, A.A.A. Tokarev, M.A.A. Panteleev, F.I.I. Ataullakhanov, Thrombin activity propagates in space during blood coagulation as an excitation wave. Biophys. J. 103, 2233–2240 (2012)

    Article  Google Scholar 

  4. A.S. Zhalyalov, M.A. Panteleev, M.A. Gracheva, F.I. Ataullakhanov, A.M. Shibeko, Co-ordinated spatial propagation of blood plasma clotting and fibrinolytic fronts. PLoS One 12 (2017)

    Google Scholar 

  5. A.N. Balandina, I.I. Serebriyskiy, A.V. Poletaev, D.M. Polokhov, M.A. Gracheva, E.M. Koltsova, D.M. Vardanyan, I.A. Taranenko, A.Y. Krylov, E.S. Urnova, K.V. Lobastov, A.V. Chernyakov, E.M. Shulutko, A.P. Momot, A.M. Shulutko, F.I. Ataullakhanov, Thrombodynamics—a new global hemostasis assay for heparin monitoring in patients under the anticoagulant treatment. PLoS One 13, 1–18 (2018)

    Article  Google Scholar 

  6. A.A. Onasoga-Jarvis, T.J. Puls, S.K. O’Brien, L. Kuang, H.J. Liang, K.B. Neeves, Thrombin generation and fibrin formation under flow on biomimetic tissue factor-rich surfaces. J. Thromb. Haemost. 12, 373–382 (2014)

    Article  Google Scholar 

  7. K.B. Neeves, D.A.R. Illing, S.L. Diamond, Thrombin flux and wall shear rate regulate fibrin fiber deposition state during polymerization under flow. Biophys. J. 98, 1344–1352 (2010)

    Article  Google Scholar 

  8. K.E. Brummel-Ziedins, S.J. Everse, K.G. Mann, T. Orfeo, Modeling thrombin generation: plasma composition based approach. J. Thromb. Thrombolysis 37, 32–44 (2014)

    Article  Google Scholar 

  9. K.B. Neeves, K. Leiderman, Mathematical models of hemostasis, in Trauma Induced Coagulopathy, ed. by A.l. EG et al. (Springer, New York, 2016), pp. 567–584

    Google Scholar 

  10. K.G. Mann, Is there value in kinetic modeling of thrombin generation? Yes. J. Thromb. Haemost. 10, 1463–1469 (2012)

    Article  Google Scholar 

  11. H.C. Hemker, S. Kerdelo, R.M.W. Kremers, Is there value in kinetic modeling of thrombin generation? No (unless …). J. Thromb. Haemost. 10, 1470–1477 (2012)

    Article  Google Scholar 

  12. K.E. Brummel-Ziedins, A.S. Wolberg, Global assays of hemostasis. Curr. Opin. Hematol. 21, 395–403 (2014)

    Article  Google Scholar 

  13. K.E. Brummel-Ziedins, Models for thrombin generation and risk of disease. J. Thromb. Haemost. 11(Suppl), 212–223 (2013)

    Article  Google Scholar 

  14. K. Leiderman, A. Fogelson, An overview of mathematical modeling of thrombus formation under flow. Thromb. Res. 133, S12–S14 (2014)

    Article  Google Scholar 

  15. E. Tsiklidis, C. Sims, T. Sinno, S.L. Diamond, Multiscale systems biology of trauma-induced coagulopathy. Wiley Interdiscip. Rev. Syst. Biol. Med. 10, 1–10 (2018)

    Article  Google Scholar 

  16. A.V. Belyaev, J.L. Dunster, J.M. Gibbins, M.A. Panteleev, V. Volpert, Modeling thrombosis in silico: frontiers, challenges, unresolved problems and milestones. Phys. Life Rev. 1, 1–39 (2018)

    Google Scholar 

  17. S.L. Diamond, Systems analysis of thrombus formation. Circ. Res. 118, 1348–1362 (2016)

    Article  Google Scholar 

  18. A.A. Tokarev, Y.V. Krasotkina, M.V. Ovanesov, M.A. Panteleev, M.A. Azhigirova, V.A. Volpert, F.I. Ataullakhanov, A.A. Butilin, Spatial dynamics of contact-activated fibrin clot formation in vitro and in silico in haemophilia B: effects of severity and Ahemphil B treatment. Math. Model. Nat. Phenom. 1, 124–137 (2006)

    Article  MathSciNet  Google Scholar 

  19. K.G. Mann, S. Butenas, K. Brummel, The dynamics of thrombin formation. Arterioscler. Thromb. Vasc. Biol. 23, 17–25 (2003)

    Article  Google Scholar 

  20. M. Hoffman, Z.H. Meng, H.R. Roberts, D.M. Monroe, Rethinking the Coagulation Cascade. Jpn. J. Thromb. Hemost. 16, 70–81 (2005)

    Article  Google Scholar 

  21. A.Y. Kondratovich, A.V. Pokhilko, F.I. Ataullakhanov, Spatiotemporal dynamics of contact activation factors of blood coagulation. Biochim. Biophys. Acta. Gen. Subj. 1569, 86–104 (2002)

    Article  Google Scholar 

  22. M.A. Panteleev, V.I. Zarnitsina, F.I. Ataullakhanov, Tissue factor pathway inhibitor: a possible mechanism of action. Eur. J. Biochem. 269, 2016–2031 (2002)

    Article  Google Scholar 

  23. L. Smith, J. Engelbreth-Holm, W. Dameshek, R.S. Schwartz, E. Undritz, H. Braunsteiner, F. Pakesch, R.J.V. Pulvertaft, J.G. Humble, L.J. Witts, H.A. Magnus, B. von Bonsdorff, W. Nyberg, R. Gräsbeck, L. Heilmeyer, M. Bessis, L. Hallberg, K.N. von Kaulla, E. Deutsch, A. Videbaek, N.A. Feodorov, S.V. Skurkovich, A. Gajano, M. Seligmann, R. Di Guglielmo, J.R. Squire, E. Neumark, I.M. Nilsson, M. Blombäck, B. Blombäck, R. Biggs, C. Hougie, The nomenclature of blood coagulation factors. Acta Haematol. 24, 151–162 (1960)

    Google Scholar 

  24. R.G. Macfarlane, An enzyme cascade in the blood clotting mechanism and its function as a biochemical amplifier. Nature 202 498–499 (1964)

    Article  Google Scholar 

  25. S.N. Levine, Enzyme amplifier kinetics. Science(80) 152, 651–653 (1966)

    Google Scholar 

  26. H.C. Hemker, P.W. Hemker, General kinetics of enzyme cascades. Proc. R. Soc. Lond. Ser. B Biol. Sci. 173, 411–20 (1969)

    Article  Google Scholar 

  27. F. Martorana, A. Moro, On the kinetics of enzyme amplifier systems with negative feedback. Math. Biosci. 21, 77–84 (1974)

    Article  Google Scholar 

  28. V.V. Semenov, M.A. Khanin, Nonlinear effects in kinetics of blood coagulation. Biofizika [in Russia] 35, 139–141 (1990)

    Google Scholar 

  29. M.A. Khanin, V.V. Semenov, A mathematical model of the kinetics of blood coagulation. J. Theor. Biol. 136, 127–134 (1989)

    Article  MathSciNet  Google Scholar 

  30. K.A. Bauer, B.L. Kass, H. ten Cate, J.J. Hawiger, R.D. Rosenberg, Factor IX is activated in vivo by the tissue factor mechanism. Blood 76, 731–736 (1990)

    Google Scholar 

  31. K.A. Bauer, B.L. Kass, H. ten Cate, M.A. Bednarek, J.J. Hawiger, R.D. Rosenberg, Detection of factor X activation in humans. Blood 74, 2007–2015 (1989)

    Google Scholar 

  32. J. Jesty, E. Beltrami, Positive feedbacks of coagulation: their role in threshold regulation. Arterioscler. Thromb. Vasc. Biol. 25, 2463–2469 (2005)

    Article  Google Scholar 

  33. H.L. Nossel, I. Yudelman, R.E. Canfield, V.P. Butler, Jr., K. Spanondis, G.D. Wildner, G.D. Qureshi, Measurement of fibrinopeptide A in human blood. J. Clin. Invest. 54, 43–53 (1974)

    Article  Google Scholar 

  34. S. Butenas, T. Orfeo, M.T. Gissel, K.E. Brummel, K.G. Mann, The significance of circulating factor IXa in blood. J. Biol. Chem. 279, 22875–22882 (2004)

    Article  Google Scholar 

  35. V.I. Zarnitsina, Study of mechanisms for arresting thrombus growth. PhD Thesis (1997)

    Google Scholar 

  36. J. Jesty, E. Beltrami, G. Willems, Mathematical analysis of a proteolytic positive-feedback loop: dependence of lag time and enzyme yields on the initial conditions and kinetic parameters. Biochemistry 32, 6266–6274 (1993)

    Article  Google Scholar 

  37. E. Beltrami, J. Jesty, Mathematical analysis of activation thresholds in enzyme-catalyzed positive feedbacks: application to the feedbacks of blood coagulation. Proc. Natl. Acad. Sci. U. S. A. 92, 8744–8748 (1995)

    Article  Google Scholar 

  38. F.I. Ataullakhanov, G.T. Guriia, Spatial aspects of the dynamics of blood coagulation. I. Hypothesis. Biophysics (Oxf) 39(1), 89–96 (1994)

    Google Scholar 

  39. F.I. Ataullakhanov, G.T. Guria, A.Y. Safroshkina, Spatial aspects of the dynamics of blood coagulation. II. Phenomenological model. Biophysics (Oxf) 39, 99–108 (1994)

    Google Scholar 

  40. G.M. Willems, T. Lindhout, W.T. Hermens, H.C. Hemker, Simulation model for thrombin generation in plasma. Haemostasis 21, 197–207 (1991)

    Google Scholar 

  41. R.J. Wagenvoord, P.W. Hemker, H.C. Hemker, The limits of simulation of the clotting system. J. Thromb. Haemost. 4, 1331–1338 (2006)

    Article  Google Scholar 

  42. R.M.W. Kremers, B. De Laat, R.J. Wagenvoord, H.C. Hemker, Computational modelling of clot development in patient-specific cerebral aneurysm cases: comment. J. Thromb. Haemost. 15, 395–396 (2017)

    Article  Google Scholar 

  43. F.I. Ataullakhanov, D.A. Molchanova, A.V. Pokhilko, A simulated mathematical model of the blood coagulation system intrinsic pathway. Biofiz. Russ. 40, 434–42 (1995)

    Google Scholar 

  44. A.V. Pokhilko, Threshold properties of the blood coagulation system, PhD Thesis (1994)

    Google Scholar 

  45. F.I. Ataullakhanov, A.V. Pohilko, E.I. Sinauridze, R.I. Volkova, Calcium threshold in human plasma clotting kinetics. Thromb. Res. 75, 383–394 (1994)

    Article  Google Scholar 

  46. M.A. Khanin, D.V. Rakov, A.E. Kogan, Mathematical model for the blood coagulation prothrombin time test. Thromb. Res. 89, 227–232 (1998)

    Article  Google Scholar 

  47. A.E. Kogan, D.V. Kardakov, M.A. Khanin, Analysis of the activated partial thromboplastin time test using mathematical modeling. Thromb. Res. 101, 299–310 (2001)

    Article  Google Scholar 

  48. J.H. Lawson, M. Kalafatis, S. Stram, K.G. Mann, A model for the tissue factor pathway to thrombin. I. An empirical study. J. Biol. Chem. 269, 23357–23366 (1994)

    Google Scholar 

  49. K.C. Jones, K.G. Mann, A model for the tissue factor pathway to thrombin. II. A mathematical simulation. J. Biol. Chem. 269, 23367–23373 (1994)

    Google Scholar 

  50. R.J. Leipold, T.A. Bozarth, A.L. Racanelli, I.B. Dicker, Mathematical model of serine protease inhibition in the tissue factor pathway to thrombin. J. Biol. Chem. 270, 25383–25387 (1995)

    Article  Google Scholar 

  51. M.F. Hockin, K.C. Jones, S.J. Everse, K.G. Mann, A model for the stoichiometric regulation of blood coagulation. J. Biol. Chem. 277, 18322–18333 (2002)

    Article  Google Scholar 

  52. T. Orfeo, S. Butenas, K.E. Brummel-Ziedins, K.G. Mann, The tissue factor requirement in blood coagulation. J. Biol. Chem. 280, 42887–42896 (2005)

    Article  Google Scholar 

  53. C.M. Danforth, T. Orfeo, K.G. Mann, K.E. Brummel-Ziedins, S.J. Everse, The impact of uncertainty in a blood coagulation model. Math. Med. Biol. 26, 323–336 (2009)

    Article  MathSciNet  Google Scholar 

  54. C.M. Danforth, T. Orfeo, S.J. Everse, K.G. Mann, K.E. Brummel-Ziedins, Defining the boundaries of normal thrombin generation: investigations into hemostasis. PLoS One 7, e30385 (2012)

    Article  Google Scholar 

  55. K.E. Brummel-Ziedins, T. Orfeo, P.W. Callas, M. Gissel, K.G. Mann, E.G. Bovill, The prothrombotic phenotypes in familial protein C deficiency are differentiated by computational modeling of thrombin generation. PLoS One 7, e44378 (2012)

    Article  Google Scholar 

  56. M.C. Bravo, T. Orfeo, K.G. Mann, S.J. Everse, Modeling of human factor Va inactivation by activated protein C. BMC Syst. Biol. 6, 45 (2012)

    Article  Google Scholar 

  57. A.Y. Mitrophanov, F.R. Rosendaal, J. Reifman, Computational analysis of the effects of reduced temperature on thrombin generation: the contributions of hypothermia to coagulopathy. Anesth. Analg. 117, 565–574 (2013)

    Article  Google Scholar 

  58. A.Y. Mitrophanov, A.S. Wolberg, J. Reifman, Kinetic model facilitates analysis of fibrin generation and its modulation by clotting factors: implications for hemostasis-enhancing therapies. Mol. Biosyst. 10, 2347 (2014)

    Article  Google Scholar 

  59. V.I. Zarnitsina, A.V. Pokhilko, F.I. Ataullakhanov, A mathematical model for the spatio-temporal dynamics of intrinsic pathway of blood coagulation. I. The model description. Thromb. Res. 84, 225–236 (1996)

    Article  Google Scholar 

  60. V.I. Zarnitsina, A.V. Pokhilko, F.I. Ataullakhanov, A mathematical model for the spatio-temporal dynamics of intrinsic pathway of blood coagulation. II. Results. Thromb. Res. 84, 333–344 (1996)

    Article  Google Scholar 

  61. A.V. Pokhilko, F.I. Ataullakhanov, Spatial dynamics of blood coagulation. A mathematical model. Biol. Membr. 3, 250–263 (2002)

    Google Scholar 

  62. M.A. Panteleev, M. V. Ovanesov, D.A. Kireev, A.M. Shibeko, E.I. Sinauridze, N.M. Ananyeva, A.A. Butylin, E.L. Saenko, F.I. Ataullakhanov, Spatial propagation and localization of blood coagulation are regulated by intrinsic and protein C pathways, respectively. Biophys. J. 90, 1489–1500 (2006)

    Article  Google Scholar 

  63. A.M. Shibeko, E.S. Lobanova, M.A. Panteleev, F.I. Ataullakhanov, Blood flow controls coagulation onset via the positive feedback of factor VII activation by factor Xa. BMC Syst. Biol. 4 (2010)

    Google Scholar 

  64. A.N. Balandina, A.M. Shibeko, D.A. Kireev, A.A. Novikova, I.I. Shmirev, M.A. Panteleev, F.I. Ataullakhanov, Positive feedback loops for factor V and factor VII activation supply sensitivity to local surface tissue factor density during blood coagulation. Biophys. J. 101, 1816–1824 (2011)

    Article  Google Scholar 

  65. M.A. Panteleev, A.N. Balandina, E.N. Lipets, M. V. Ovanesov, F.I. Ataullakhanov, Task-Oriented modular decomposition of biological networks: trigger mechanism in blood coagulation. Biophys. J. 98, 1751–1761 (2010)

    Article  Google Scholar 

  66. A.L. Fogelson, Continuum models of platelet aggregation: formulation and mechanical properties. SIAM J. Appl. Math. 52, 1089–1110 (1992)

    Article  MathSciNet  Google Scholar 

  67. A.L. Fogelson, A.L. Kuharsky, Membrane binding-site density can modulate activation thresholds in enzyme systems. J. Theor. Biol. 193, 1–18 (1998)

    Article  Google Scholar 

  68. A.L. Kuharsky, A.L. Fogelson, Surface-mediated control of blood coagulation: the role of binding site densities and platelet deposition. Biophys. J. 80, 1050–1074 (2001)

    Article  Google Scholar 

  69. K. Leiderman, A.L. Fogelson, Grow with the flow: a spatial-temporal model of platelet deposition and blood coagulation under flow. Math. Med. Biol. 28, 47–84 (2011)

    Article  MathSciNet  Google Scholar 

  70. A.L. Fogelson, Y.H. Hussain, K. Leiderman, Blood clot formation under flow: the importance of factor XI depends strongly on platelet count. Biophys. J. 102, 10–18 (2012)

    Article  Google Scholar 

  71. K.G. Link, M.T. Stobb, J. Di Paola, K.B. Neeves, A.L. Fogelson, S.S. Sindi, K. Leiderman, A local and global sensitivity analysis of a mathematical model of coagulation and platelet deposition under flow. PLoS One 13, e0200917 (2018)

    Article  Google Scholar 

  72. A.A. Onasoga-Jarvis, K. Leiderman, A.L. Fogelson, M. Wang, M.J. Manco-Johnson, J.A. Di Paola, K.B. Neeves, The effect of factor VIII deficiencies and replacement and bypass therapies on thrombus formation under venous flow conditions in microfluidic and computational models. PLoS One 8(11), e78732 (2013)

    Google Scholar 

  73. V. Govindarajan, V. Rakesh, J. Reifman, A.Y. Mitrophanov, Computational study of thrombus formation and clotting factor effects under venous flow conditions. Biophys. J. 110, 1869–1885 (2016)

    Article  Google Scholar 

  74. S.W. Jordan, E.L. Chaikof, Simulated surface-induced thrombin generation in a flow field. Biophys. J. 101, 276–286 (2011)

    Article  Google Scholar 

  75. D.A. Molchanova, A.A. Butylin, F.I. Ataullakhanov, Investigation of dynamic blood coagulation regimes using a mathematical model. Biol. Membr. 21, 420–432 (2004)

    Google Scholar 

  76. V.I. Zarnitsina, F.I. Ataullakhanov, A.I. Lobanov, O.L. Morozova, Dynamics of spatially nonuniform patterning in the model of blood coagulation. Chaos 11, 57–70 (2001)

    Article  Google Scholar 

  77. E.S. Lobanova, F.I. Ataullakhanov, Unstable trigger waves induce various intricate dynamic regimes in a reaction-diffusion system of blood clotting. Phys. Rev. Lett. 91, 1–4 (2003)

    Article  Google Scholar 

  78. E.S. Lobanova, F.I. Ataullakhanov, Running pulses of complex shape in a reaction-diffusion model. Phys. Rev. Lett. 93, 1–4 (2004)

    Article  Google Scholar 

  79. E.S. Lobanova, E.E. Shnol, F.I. Ataullakhanov, Complex dynamics of the formation of spatially localized standing structures in the vicinity of saddle-node bifurcations of waves in the reaction-diffusion model of blood clotting. Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Top. 70, 4 (2004)

    MathSciNet  Google Scholar 

  80. E.A. Ermakova, M.A. Panteleev, E.E. Shnol, Blood coagulation and propagation of autowaves in flow. Pathophysiol. Haemost. Thromb. 34, 135–142 (2005)

    Article  Google Scholar 

  81. The Systems Biology Markup Language (SBML). http://sbml.org

Download references

Acknowledgements

This work was partially supported by the “RUDN University Program 5-100” to A.T. and V.V. and by the Dynasty Foundation Fellowship to A.T.

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Tokarev, A., Ratto, N., Volpert, V. (2019). Mathematical Modeling of Thrombin Generation and Wave Propagation: From Simple to Complex Models and Backwards. In: Mondaini, R. (eds) Trends in Biomathematics: Mathematical Modeling for Health, Harvesting, and Population Dynamics. Springer, Cham. https://doi.org/10.1007/978-3-030-23433-1_1

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