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Computational Modeling of the Coagulation Response During Trauma

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Complex Systems and Computational Biology Approaches to Acute Inflammation

Abstract

Coagulation and platelet aggregation are the primary mechanisms for maintaining hemostasis upon traumatic injury. However, prolonged bleeding may lead to trauma-induced coagulopathy (TIC) or the apparent phenomenon of blood coagulation is impaired upon prolonged blood loss. This has been studied extensively via computational modeling, where the overall goal is to quantify metabolic responses, predict responses to physiological perturbations, and develop “on-the-fly” patient-specific strategies. Models of trauma patient evolution and clot growth rates have been developed to better understand the evolution of TIC in a trauma patient. Mechanistic and statistical models have been informed via experiment, whereby the trauma patient blood is acquired at marked time intervals after injury to better stratify the patient bleeding risks, prioritize biomarkers, and identify new opportunities for safer treatment options.

Evan J. Tsiklidis and Christopher C. Verni are co-first authors.

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Abbreviations

ADP:

Adenosine diphosphate

DIC:

Disseminated intravascular coagulation

FEM:

Finite element method

LB:

Lattice Boltzmann

LKMC:

Lattice kinetic Monte Carlo

NN:

Neural network

ODE:

Ordinary differential equation

PAS:

Pairwise agonist scanning

PAS-FC:

Pairwise agonist scanning-flow cytometry

PBRC:

Packed red blood cells

PDE:

Partial differential equation

PRP:

Platelet-rich plasma

TAT:

Thrombin-antithrombin

TBI:

Traumatic brain injury

TEG:

Thromboelastography

TF:

Inflammatory tissue factor

TIC:

Trauma-induced coagulopathy

References

  1. Tsiklidis EJ, Sinno T, Diamond SL (2019) Coagulopathy implications using a multiscale model of traumatic bleeding matching macro- and microcirculation. Am J Physiol Heart Circ Physiol 317:H73–H86

    Article  CAS  Google Scholar 

  2. Ursino M (1998) Interaction between carotid baroregulation and the pulsating heart: a mathematical model. Am J Physiol 275(5):H1733–H1747

    CAS  Google Scholar 

  3. Ursino M, Magosso E (2000) Acute cardiovascular response to isocapnic hypoxia. I. A mathematical model. Am J Physiol Heart Circ Physiol 279(1):H149–H165

    Article  CAS  Google Scholar 

  4. Reisner AT, Heldt T (2013) A computational model of hemorrhage and dehydration suggests a pathophysiological mechanism: Starling-mediated protein trapping. Am J Physiol Heart Circ Physiol 304(4):H620–H631

    Article  CAS  Google Scholar 

  5. Li R, Elmongy H, Sims C, Diamond SL (2016) Ex vivo recapitulation of trauma-induced coagulopathy and preliminary assessment of trauma patient platelet function under flow using microfluidic technology. J Trauma Acute Care Surg 80(3):440–449

    Article  CAS  Google Scholar 

  6. Tsiklidis E, Sims C, Sinno T, Diamond SL (2018) Multiscale systems biology of trauma-induced coagulopathy. Wiley Interdiscip Rev Syst Biol Med 10(4):1–10

    Article  Google Scholar 

  7. Namas RA, Vodovotz Y (2016) From static to dynamic: a sepsis-specific dynamic model from clinical criteria in polytrauma patients. Ann Transl Med 4(24):1–4

    Article  Google Scholar 

  8. Day JD, Cockrell C, Namas R, Zamora R, An G, Vodovotz Y (2018) Inflammation and disease: modelling and modulation of the inflammatory response to alleviate critical illness. Curr Opin Syst Biol 12:22–29

    Article  Google Scholar 

  9. Canuto D, Chong K, Bowles C, Dutson EP, Eldredge JD, Benharash P (2018) A regulated multiscale closed-loop cardiovascular model, with applications to hemorrhage and hypertension. Int J Numer Method Biomed Eng 34(6):e2975

    Article  Google Scholar 

  10. Lee C, Porter KM, Hodgetts TJ (2007) Tourniquet use in the civilian prehospital setting. Emerg Med J 24(8):584–587

    Article  CAS  Google Scholar 

  11. Hirshberg A, Dugas M, Banez EI, Scott BG, Wall MJ Jr, Mattox KL (2003) Minimizing dilutional coagulopathy in exsanguinating hemorrhage: a computer simulation. J Trauma 54(3):454–463

    Article  Google Scholar 

  12. Neeves KB, Leiderman K (2016) Mathematical models of hemostasis. In: Gonzalez E, Moore HB, Moore EE (eds) Trauma induced coagulopathy [internet]. Springer International Publishing, Cham, pp 567–584. https://doi.org/10.1007/978-3-319-28308-1_35

    Chapter  Google Scholar 

  13. Diamond SL (2016) Systems analysis of thrombus formation. Circ Res 118(9):1348–1362

    Article  CAS  Google Scholar 

  14. Sakurai Y, Hardy ET, Ahn B, Tran R, Fay ME, Ciciliano JC et al (2018) A microengineered vascularized bleeding model that integrates the principal components of hemostasis. Nat Commun 9:509

    Article  CAS  Google Scholar 

  15. Hockin MF, Jones KC, Everse SJ, Mann KG (2002) A model for the stoichiometric regulation of blood coagulation. J Biol Chem 277(21):18322–18333

    Article  CAS  Google Scholar 

  16. Chatterjee MS, Denney WS, Jing H, Diamond SL (2010) Systems biology of coagulation initiation: kinetics of thrombin generation in resting and activated human blood. PLoS Comput Biol 6(9):e1000950

    Article  CAS  Google Scholar 

  17. Kuharsky AL, Fogelson AL (2001) Surface-mediated control of blood coagulation: the role of binding site densities and platelet deposition. Biophys J 80(3):1050–1074

    Article  CAS  Google Scholar 

  18. Okorie UM, Denney WS, Chatterjee MS, Neeves KB, Diamond SL (2008) Determination of surface tissue factor thresholds that trigger coagulation at venous and arterial shear rates: amplification of 100 fM circulating tissue factor requires flow. Blood 111(7):3507–3513

    Article  CAS  Google Scholar 

  19. Leiderman K, Fogelson A (2011) Grow with the flow: a spatial-temporal model of platelet deposition and blood coagulation under flow. Math Med Biol 28(1):47–84

    Article  Google Scholar 

  20. Chen J, Diamond SL (2019) Reduced model to predict thrombin and fibrin during thrombosis on collagen/tissue factor under venous flow: roles of γ’-fibrin and factor XIa. PLoS Comput Biol 15(8):e1007266

    Article  CAS  Google Scholar 

  21. Purvis JE, Chatterjee MS, Brass LF, Diamond SL (2008) A molecular signaling model of platelet phosphoinositide and calcium regulation during homeostasis and P2Y1 activation. Blood 112(10):4069–4079

    Article  CAS  Google Scholar 

  22. Dolan AT, Diamond SL (2014) Systems modeling of Ca2+ homeostasis and mobilization in platelets mediated by IP3 and store-operated Ca2+ entry. Biophys J 106(9):2049–2060

    Article  CAS  Google Scholar 

  23. Lenoci L, Duvernay M, Satchell S, DiBenedetto E, Hamm HE (2011) Mathematical model of PAR1-mediated activation of human platelets. Mol BioSyst 7(4):1129–1137

    Article  CAS  Google Scholar 

  24. Flamm MH, Colace TV, Chatterjee MS, Jing H, Zhou S, Jaeger D et al (2012) Multiscale prediction of patient-specific platelet function under flow. Blood 120(1):190–198

    Article  CAS  Google Scholar 

  25. Chatterjee MS, Purvis JE, Brass LF, Diamond SL (2010) Pairwise agonist scanning predicts cellular signaling responses to combinatorial stimuli. Nat Biotechnol 28(7):727–732

    Article  CAS  Google Scholar 

  26. Lee MY, Diamond SL (2015) A human platelet calcium calculator trained by pairwise agonist scanning. PLoS Comput Biol 11(2):e1004118

    Article  CAS  Google Scholar 

  27. Lu Y, Lee MY, Zhu S, Sinno T, Diamond SL (2017) Multiscale simulation of thrombus growth and vessel occlusion triggered by collagen/tissue factor using a data-driven model of combinatorial platelet signalling. Math Med Biol 34(4):523–546

    Google Scholar 

  28. Stalker TJ, Traxler EA, Wu J, Wannemacher KM, Cermignano SL, Voronov R et al (2013) Hierarchical organization in the hemostatic response and its relationship to the platelet-signaling network. Blood 121(10):1875–1885

    Article  CAS  Google Scholar 

  29. Muthard RW, Welsh JD, Brass LF, Diamond SL (2015) Fibrin, γ’-fibrinogen, and transclot pressure gradient control hemostatic clot growth during human blood flow over a collagen/tissue factor wound. Arterioscler Thromb Vasc Biol 35(3):645–654

    Article  CAS  Google Scholar 

  30. Davis PK, Musunuru H, Walsh M, Cassady R, Yount R, Losiniecki A et al (2013) Platelet dysfunction is an early marker for traumatic brain injury-induced coagulopathy. Neurocrit Care 18(2):201–208

    Article  CAS  Google Scholar 

  31. Oshiro A, Yanagida Y, Gando S, Henzan N, Takahashi I, Makise H (2014) Hemostasis during the early stages of trauma: comparison with disseminated intravascular coagulation. Crit Care 18(2):R61

    Article  Google Scholar 

  32. Li Z, Delaney MK, O’Brien KA, Du X (2010) Signaling during platelet adhesion and activation. Arterioscler Thromb Vasc Biol 30(12):2341–2349

    Article  CAS  Google Scholar 

  33. Varga-Szabo D, Braun A, Nieswandt B (2009) Calcium signaling in platelets. J Thromb Haemost 7(7):1057–1066

    Article  CAS  Google Scholar 

  34. Sorensen EN, Burgreen GW, Wagner WR, Antaki JF (1999) Computational simulation of platelet deposition and activation: I. Model development and properties. Ann Biomed Eng 27(4):436–448

    Article  CAS  Google Scholar 

  35. Sorensen EN, Burgreen GW, Wagner WR, Antaki JF (1999) Computational simulation of platelet deposition and activation: II. Results for Poiseuille flow over collagen. Ann Biomed Eng 27(4):449–458

    Article  CAS  Google Scholar 

  36. Verni CC, Davila A Jr, Balian S, Sims CA, Diamond SL (2019) Platelet dysfunction during trauma involves diverse signaling pathways and an inhibitory activity in patient-derived plasma. J Trauma Acute Care Surg 86(2):250–259

    Article  CAS  Google Scholar 

  37. Chang R, Cardenas JC, Wade CE, Holcomb JB (2016) Advances in the understanding of trauma-induced coagulopathy. Blood 128(8):1043–1049

    Article  CAS  Google Scholar 

  38. Kutcher ME, Redick BJ, McCreery RC, Crane IM, Greenberg MD, Cachola LM et al (2012) Characterization of platelet dysfunction after trauma. J Trauma Acute Care Surg 73(1):13–19

    Article  CAS  Google Scholar 

  39. Saillant NN, Sims CA (2014) Platelet dysfunction in injured patients. Mol Cell Ther 2(1):37

    Article  Google Scholar 

  40. Yun S-H, Sim E-H, Goh R-Y, Park J-I, Han J-Y (2016) Platelet activation: the mechanisms and potential biomarkers. Biomed Res Int 2016:9060143

    Article  CAS  Google Scholar 

  41. Lentz BR (2003) Exposure of platelet membrane phosphatidylserine regulates blood coagulation. Prog Lipid Res 42(5):423–438

    Article  CAS  Google Scholar 

  42. Jaeger DTL, Diamond SL (2013) Pairwise agonist scanning-flow cytometry (PAS-FC) measures inside-out signaling and patient-specific response to combinatorial platelet agonists. Biotechniques 54(5):271–277

    Article  CAS  Google Scholar 

  43. Yoon JG, Heo J, Kim M, Park YJ, Choi MH, Song J et al (2018) Machine learning-based diagnosis for disseminated intravascular coagulation (DIC): development, external validation, and comparison to scoring systems. PLoS One 13(5):e0195861

    Article  CAS  Google Scholar 

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Correspondence to Scott L. Diamond .

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Tsiklidis, E.J., Verni, C.C., Sinno, T., Diamond, S.L. (2021). Computational Modeling of the Coagulation Response During Trauma. In: Vodovotz, Y., An, G. (eds) Complex Systems and Computational Biology Approaches to Acute Inflammation. Springer, Cham. https://doi.org/10.1007/978-3-030-56510-7_9

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