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MULTISCALE SYSTEMS MODELLING OF
        THE TETRALOGY OF FALLOT
                  1                1                  1                       2               2                       2                    3
Ron Summers, Tariq Abdulla, Ryan Imms, Jean-Marc Schleich, Guy Carrault, Alfredo Hernandez and Lucile Houyel
1
  Electronic and Electrical Engineering, SEIC, Loughborough University, Leics, UK, LE11 3TU
  E-mail: R.Summers@lboro.ac.uk Web: http://syseng.lboro.ac.uk
2
  LTSI, University of Rennes 1, Rennes, F-35000, France
3
  Marie-Lannelongue Hospital, Paris, F-92350, France

Introduction
Between week 3 and 6 of embryonic development, the human heart morphs from a linear tube to a four chambered
organ. It is one of the few organs that become functional as it is formed. Remarkably, the conduction system and
blood flow both change radically while maintaining cardiac function at every step of development. Heart defects are
the most common type of congenital disorder, severely affecting 6/1000 live births. A number of genes have been
identified as playing a crucial role in heart morphogenesis. However the mechanisms by which altered gene
transcription affects cell signalling, cell behaviour, and tissue-tissue interactions that lead to altered development
are not well understood. The tetralogy of Fallot is one type of congenital heart disease (CHD), comprising multiple
defects, for which a theory of aetiology exists. However this sits within a spectrum of CHD in which one gene acts
through many mechanisms and can cause one of several diseases. Multiscale modelling, mediated through
information models, provides a means to study heart development as a system.

    Tetralogy of Fallot                                             Complexity of CHD
    The tetralogy of Fallot is the most common                       Several mechanisms are involved in heart development, each of which
    congenital heart defect causing cyanosis, and is                 are controlled by several genes. CHD commonly involves abnormal
    defined as four coinciding anomalies:                            remodelling of the outflow tract (OFT) which can be caused by a
     A Pulmonary stenosis                                            combination of mechanisms, as illustrated below. As the OFT loops
     B An over-riding aorta, displaced to the right                  behind the atria, it septates into the aorta and pulmonary artery, and
     C Ventricular septal defect                                     wedges aligned with the atrioventricular septum. Thus there is a range
       (always in the membranous septum)                             of CHDs caused by abnormal degrees of OFT rotation.
     D Right ventricle hypertrophy

                                                     Wikipedia
                                                   User:Wapcaplet




                                       A

                                               B
                                               C

                                           D



     Normal Heart               Tetralogy of Fallot
    As the four abnormalities co-occur so frequently, it is
    likely there is a common cause. One theory is that
    hypoplasia of the subpulmonary conus leads to both
    pulmonary stenosis and a shorter rotation of the
    Outflow Tract (OFT), which leads to anomalies B , C
    and D .                                                         Several genes control several mechanisms, which lead to one of several CHDs [1]
Multiscale Modelling                                                                                                                                                                            -9                                                -3
The modelling framework encompasses spatial scales from 10 m (protein interactions) to 10 m (the primitive heart tube) and
                        -6                        6
temporal scales from 10 s (molecular events) to 10 s (weeks of development). This is illustrated schematically below, left. The
approach adopted owes much to other methods including those from: systems engineering (e.g. integration technologies and
information modelling); the world-wide Physiome consortium and the EU-funded Network of Excellence on the Virtual
Physiological Human. Modelling approaches suitable for different levels of scale are illustrated, as well as markup language
specifications. These enable model interchange, potentially between tools that are suitable for modelling at different scales.
                        -9                                         -6                                     -4                                                -3                                                                   Composite
 Spatial Scale      10 m                                    10 m                                    10 m                                                 10 m                                          Biosimulation                                     Ontology      Data Source
                                                                                                                                                                                                                                 Annotation
                Protein                          Cell                                       Tissue                                                Heart Tube                                                                                                          Gel Electrophoresis
              Interaction                      Behaviour                                Transformation                                           Morphogenesis                                                                       SNAIL
                                                                                                                                                                                                                                   decreased
                                       High                 VEGF                              High VEGF                                                                                                //computation              concentration          PRO, GO-MF
                            2+         VEGF
                       CA
                                                                                                           BMP2
                                                                                                                       Snail   VE Cadherin

                                                                                                                                                                                                       VAR =
                     Calcineurin
                        p           VEGF
                                                                                                                     Notch

                                                                                                                                                                                                                                 endothelial cell
                    NFAT    NFAT                                                                                     Delta4
                                                                                              Low VEGF

                            VEGF                                        VE-Cadherin
                                                     2+
                                                CA
                                                                                                          TGF-beta
                                              Calcineurin    TGF-beta
                         Wnt /
                        BetaCat
                                      Low
                                      VEGF
                                                 p
                                              NFAT   NFAT


                                                     VEGF
                                                                         Snail                                                                                                                                                            part_of
                                                                                              High VEGF
                                                  Wnt /
                                                              BMP
                                                 BetaCat
                                                                        Notch
                            BMP4                     BMP4


     Markup
   Language     SBML                                        CellML                               CBML                                                 FieldML                                                                          SNAIL                             Histochemistry
   Modelling Pathway Models                Stochastic Models                              Agent Based Models                                      Finite Element                                                                     decreased             PATO
                                                                                                                                                                                                        OPB:concentration
   Approach ODEs                           Reaction Diffusion PDEs                        Reactive Animation                                      Image Analysis
                                                                                                                                                                                                            =53 pg ml
                                                                                                                                                                                                                      -1            concentration
             Petri Nets                    Systems of ODEs                                Cellular Automata                                       3D Reconstruction                                                                                        GO-CC
                 Boolean Networks          Stochastic Petri Nets                          Cellular Potts                                          Multiphysics Simulation                                                        endocardial cushion
                                                                                                                                                                     Independent Continuant                                                                  CL
                   PRO, ChEBI                             CL, FMA, GO-CC                                                                     FMA, EHDA                                                 Validation
                                                                                                                                                                     (Proteins, Cells, Structures)
                                                                                                                                                                                                                                          derives_into
 Ontologies            GO-MF                              Cell Behaviour                              PATO, Mammalian Phenotype Dependent Continuant                                                                                                                   Segemented MRI
                                                                                                                                                                     (Functions, Roles, Qualities)

                                                                                                                                                                                                                                    decreased
                                                                                      GO-BP                                                                          Occurent                             OPB:area volume
                                                                                                                                                                     (Processes)                                      6  3            volume
                                                                                                                                                                                                              =3 x 10 μm
Temporal Scale
                                                                                                                                                                                                                                 membranous part of      FMA, EHDA
                      -6                                           -3                                                3                                           6                                                                cardiac septum
                                                                                                                                                                                                     OMIM / Snomed / AEPC:
                  10 s                                      10 s                                          10 s                                              10 s
          Molecular Events                   Cell Signalling                                              Mitosis                                  Heart Development                                 Ventricular Septal Defect

 Spatial and temporal scales of the multiscale modelling initiative [2]                                                                                                                              Composite annotation of biomedical data from multiscale sources [2]
Reference ontologies applicable to the different levels of scale are illustrated along the bottom of the left-hand figure. These are
further split between occurents, independent continuants and dependent continuants. Occurents are processes that unfold
through time, while continuants are entities that exist in full through a period of time. This provides a clear conceptual division
between the spatial and temporal domains. Annotating models, model components and parameters using well defined
ontologies enables reuse and integration. But multiscale modelling presents a challenge in that no single ontology can include
terms of the required specificity. A post-coordinated annotation strategy, which allows the combination of terms from multiple
ontologies, is a partial solution to this issue, and is illustrated above, right. Modelling of morphogenesis provides the further
challenge of increased importance of the temporal domain, which is currently less well defined ontologically.

Future Work
There are several important mechanisms in heart development, and each of these can be studied as a multiscale system. The
endocardial cushions are swellings in the early heart tube, which fuse to form the valves and membranous septum, and play a role
in OFT remodelling. Endocardial cushions grow by a process of Epithelial to Mesenchymal Transition (EMT). Cellular behaviour
and tissue interaction during EMT can be simulated as Potts models using Compucell3D. Existing models of signal pathways
involved in EMT are modelled as ODEs and are available in Systems Biology Markup Language (SBML). Future plans are to use
the SBML ODE Solver Library (SOSlib) to incorporate reaction networks within Compucell3D and thus determine intracellular
concentrations in a multiscale model. From a chronological perspective, we are using state charts to represent processes and sub-
processes in heart development hierarchically. The UML formalism allows the recursive stacking of state machines, and this
approach neatly matches the problem of modelling in multiple time scales.

References
[1] F. Bajolle, S. Zaffran, and D. Bonnet, "Genetics and embryological mechanisms of congenital heart diseases.," Archives of
cardiovascular diseases, vol. 102, 2009, pp. 59-63.
[2] T. Abdulla, R. Imms, J.M. Schleich, and R. Summers, "Multiscale information modelling for heart morphogenesis," Journal of
Physics: Conference Series (in press).

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Multiscale Systems Modelling of the Tetralogy of Fallot, Summers, 32nd IEEE-EMBC

  • 1. MULTISCALE SYSTEMS MODELLING OF THE TETRALOGY OF FALLOT 1 1 1 2 2 2 3 Ron Summers, Tariq Abdulla, Ryan Imms, Jean-Marc Schleich, Guy Carrault, Alfredo Hernandez and Lucile Houyel 1 Electronic and Electrical Engineering, SEIC, Loughborough University, Leics, UK, LE11 3TU E-mail: R.Summers@lboro.ac.uk Web: http://syseng.lboro.ac.uk 2 LTSI, University of Rennes 1, Rennes, F-35000, France 3 Marie-Lannelongue Hospital, Paris, F-92350, France Introduction Between week 3 and 6 of embryonic development, the human heart morphs from a linear tube to a four chambered organ. It is one of the few organs that become functional as it is formed. Remarkably, the conduction system and blood flow both change radically while maintaining cardiac function at every step of development. Heart defects are the most common type of congenital disorder, severely affecting 6/1000 live births. A number of genes have been identified as playing a crucial role in heart morphogenesis. However the mechanisms by which altered gene transcription affects cell signalling, cell behaviour, and tissue-tissue interactions that lead to altered development are not well understood. The tetralogy of Fallot is one type of congenital heart disease (CHD), comprising multiple defects, for which a theory of aetiology exists. However this sits within a spectrum of CHD in which one gene acts through many mechanisms and can cause one of several diseases. Multiscale modelling, mediated through information models, provides a means to study heart development as a system. Tetralogy of Fallot Complexity of CHD The tetralogy of Fallot is the most common Several mechanisms are involved in heart development, each of which congenital heart defect causing cyanosis, and is are controlled by several genes. CHD commonly involves abnormal defined as four coinciding anomalies: remodelling of the outflow tract (OFT) which can be caused by a A Pulmonary stenosis combination of mechanisms, as illustrated below. As the OFT loops B An over-riding aorta, displaced to the right behind the atria, it septates into the aorta and pulmonary artery, and C Ventricular septal defect wedges aligned with the atrioventricular septum. Thus there is a range (always in the membranous septum) of CHDs caused by abnormal degrees of OFT rotation. D Right ventricle hypertrophy Wikipedia User:Wapcaplet A B C D Normal Heart Tetralogy of Fallot As the four abnormalities co-occur so frequently, it is likely there is a common cause. One theory is that hypoplasia of the subpulmonary conus leads to both pulmonary stenosis and a shorter rotation of the Outflow Tract (OFT), which leads to anomalies B , C and D . Several genes control several mechanisms, which lead to one of several CHDs [1]
  • 2. Multiscale Modelling -9 -3 The modelling framework encompasses spatial scales from 10 m (protein interactions) to 10 m (the primitive heart tube) and -6 6 temporal scales from 10 s (molecular events) to 10 s (weeks of development). This is illustrated schematically below, left. The approach adopted owes much to other methods including those from: systems engineering (e.g. integration technologies and information modelling); the world-wide Physiome consortium and the EU-funded Network of Excellence on the Virtual Physiological Human. Modelling approaches suitable for different levels of scale are illustrated, as well as markup language specifications. These enable model interchange, potentially between tools that are suitable for modelling at different scales. -9 -6 -4 -3 Composite Spatial Scale 10 m 10 m 10 m 10 m Biosimulation Ontology Data Source Annotation Protein Cell Tissue Heart Tube Gel Electrophoresis Interaction Behaviour Transformation Morphogenesis SNAIL decreased High VEGF High VEGF //computation concentration PRO, GO-MF 2+ VEGF CA BMP2 Snail VE Cadherin VAR = Calcineurin p VEGF Notch endothelial cell NFAT NFAT Delta4 Low VEGF VEGF VE-Cadherin 2+ CA TGF-beta Calcineurin TGF-beta Wnt / BetaCat Low VEGF p NFAT NFAT VEGF Snail part_of High VEGF Wnt / BMP BetaCat Notch BMP4 BMP4 Markup Language SBML CellML CBML FieldML SNAIL Histochemistry Modelling Pathway Models Stochastic Models Agent Based Models Finite Element decreased PATO OPB:concentration Approach ODEs Reaction Diffusion PDEs Reactive Animation Image Analysis =53 pg ml -1 concentration Petri Nets Systems of ODEs Cellular Automata 3D Reconstruction GO-CC Boolean Networks Stochastic Petri Nets Cellular Potts Multiphysics Simulation endocardial cushion Independent Continuant CL PRO, ChEBI CL, FMA, GO-CC FMA, EHDA Validation (Proteins, Cells, Structures) derives_into Ontologies GO-MF Cell Behaviour PATO, Mammalian Phenotype Dependent Continuant Segemented MRI (Functions, Roles, Qualities) decreased GO-BP Occurent OPB:area volume (Processes) 6 3 volume =3 x 10 μm Temporal Scale membranous part of FMA, EHDA -6 -3 3 6 cardiac septum OMIM / Snomed / AEPC: 10 s 10 s 10 s 10 s Molecular Events Cell Signalling Mitosis Heart Development Ventricular Septal Defect Spatial and temporal scales of the multiscale modelling initiative [2] Composite annotation of biomedical data from multiscale sources [2] Reference ontologies applicable to the different levels of scale are illustrated along the bottom of the left-hand figure. These are further split between occurents, independent continuants and dependent continuants. Occurents are processes that unfold through time, while continuants are entities that exist in full through a period of time. This provides a clear conceptual division between the spatial and temporal domains. Annotating models, model components and parameters using well defined ontologies enables reuse and integration. But multiscale modelling presents a challenge in that no single ontology can include terms of the required specificity. A post-coordinated annotation strategy, which allows the combination of terms from multiple ontologies, is a partial solution to this issue, and is illustrated above, right. Modelling of morphogenesis provides the further challenge of increased importance of the temporal domain, which is currently less well defined ontologically. Future Work There are several important mechanisms in heart development, and each of these can be studied as a multiscale system. The endocardial cushions are swellings in the early heart tube, which fuse to form the valves and membranous septum, and play a role in OFT remodelling. Endocardial cushions grow by a process of Epithelial to Mesenchymal Transition (EMT). Cellular behaviour and tissue interaction during EMT can be simulated as Potts models using Compucell3D. Existing models of signal pathways involved in EMT are modelled as ODEs and are available in Systems Biology Markup Language (SBML). Future plans are to use the SBML ODE Solver Library (SOSlib) to incorporate reaction networks within Compucell3D and thus determine intracellular concentrations in a multiscale model. From a chronological perspective, we are using state charts to represent processes and sub- processes in heart development hierarchically. The UML formalism allows the recursive stacking of state machines, and this approach neatly matches the problem of modelling in multiple time scales. References [1] F. Bajolle, S. Zaffran, and D. Bonnet, "Genetics and embryological mechanisms of congenital heart diseases.," Archives of cardiovascular diseases, vol. 102, 2009, pp. 59-63. [2] T. Abdulla, R. Imms, J.M. Schleich, and R. Summers, "Multiscale information modelling for heart morphogenesis," Journal of Physics: Conference Series (in press).