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Modelling and Simulation of Brain Energy Metabolism: Energy and Parkinson’s Disease

  • Peter Wellstead
  • Mathieu Cloutier
Chapter

Abstract

The brain is the most energy intensive organ in the human body, so it is to be expected that weaknesses in brain energy metabolism could be a potential factor in neurodegenerative conditions. This is the starting point for a systems biology study of how known Parkinson’s disease (PD) risks can weaken brain energy metabolism and contribute to the preconditions for disease. We begin by describing PD as a multifactorial condition in which energy deficits form a common denominator for known risk factors. This is followed by a description of a mathematical model of brain energy metabolism, and its structural and dynamic properties. Simulations of the model are then used to illustrate how external risk factors, plus structural and dynamic weaknesses in neural energy supplies, particularly affect neurons most vulnerable to PD damage. Taken together, these issues form the basis of an energy-deficit theory for how the preconditions for PD are formed.

Keywords

Head Trauma Adenylate Kinase Brain Energy Metabolism Neuronal Stimulation High Demand Period 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

We acknowledge the support of Science Foundation Ireland (Award 03/RP1/I382) for the research described in this chapter.

References

  1. 1.
    von Bohlen und Halbach O, Schober A, Krieglstein K (2004) Genes, proteins, and neurotoxins involved in Parkinson’s disease. Prog Neurobiol 73(3):151–177PubMedCrossRefGoogle Scholar
  2. 2.
    Seidler A, Hellenbrand W, Robra B-P, Vieregge P, Nischan P, Joerg J, Oertel WH, Ulmand G, Schneider E (1996) Possible environmental, occupational, and other etiologic factors for Parkinson’s disease. Neurology 47:1275–1285Google Scholar
  3. 3.
    Tanner CM, Ross GW, Jewell SA, Hauser RA et al (2009) Occupation and risk of parkinsonism. Arch Neurol 9(66):1106–1113CrossRefGoogle Scholar
  4. 4.
    Litvan I et al (2007) The etiopathogenesis of Parkinson’s disease and suggestions for future research. Part 1. J Neuropathol Exp Neurol 66:251–257PubMedCrossRefGoogle Scholar
  5. 5.
    Hughes AJ, Daniel SE, Kilford L, Lees AJ (1992) Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: a clinico-pathological study of 100 cases. J Neurol Neurosurg Psychiatry 55:181–184PubMedCrossRefGoogle Scholar
  6. 6.
    Semchuk KM, Love EJ, Lee RG (1993) Parkinson’s disease: a test of the multifactorial etiology hypothesis. Neurology 43:1173–1180PubMedGoogle Scholar
  7. 7.
    Van den Eeden SK, Tanner CM, Bernstein AL, Fross RD, Leimpeter A, Bloch DA, Nelson LM (2003) Incidence of Parkinson’s disease: variation by age, gender and race/ethnicity. Am Jour Epidemiol 11:1015–1022CrossRefGoogle Scholar
  8. 8.
    Tanner CM, Kamel F, Ross GW, Hoppin JA, Goldman SM, Korell M et al (2011) Rotenone, paraquat and Parkinson’s disease, Environ. Health Perspect 119(6):866–872CrossRefGoogle Scholar
  9. 9.
    Lucchini RG, Albini E, Benedetti L et al (2007) High prevalence of Parkinsonian disorders associated to manganese exposure in the vicinities of ferroalloy industries. Am Jour Ind Med 50(11):788–800CrossRefGoogle Scholar
  10. 10.
    Gash DM, Rutland K, Hudson NL et al (2008) Trichloroethylene: Parkinsonism and complex 1 mitochondrial neurotoxicity. Ann Neurol 63:184–192PubMedCrossRefGoogle Scholar
  11. 11.
    Langston JW, Palfreman J (1995) The case of the frozen addicts. Pantheon, New YorkGoogle Scholar
  12. 12.
    Thacker EL, Chen H, Patel AV, McCullough ML, Calle EE, Thun MJ, Schwarzschild MA, Ascherio A (2008) Recreational Physical Activity and Risk of Parkinson’s disease. Mov Disord 1(23):69–74CrossRefGoogle Scholar
  13. 13.
    Singleton AD, Farrer M, Johnson J, Singleton A et al (2003) Alpha-synuclein locus triplication causes Parkinson’s disease. Science 302:841–844PubMedCrossRefGoogle Scholar
  14. 14.
    Foltyne T, Sawcer S, Brayne C, Barker RA (2002) The genetic basis for Parkinson’s disease. Journ Neurol Neurosurg Psychiatry 73:363–370CrossRefGoogle Scholar
  15. 15.
    Willis MW, Ketter TA, Kimbrell TA, George MS, Herscovitch P, Danielson AL, Benson BE, Post RM (2002) Age, sex and laterality effects on cerebral glucose metabolism in healthy adults. Psychiatric Research: Neuroimaging 114(1):23–37PubMedCrossRefGoogle Scholar
  16. 16.
    Roberts SB, Rosenberg I (2006) Nutrition and aging: changes in the regulation of energy metabolism with aging. Physiological Review 86:651–667CrossRefGoogle Scholar
  17. 17.
    Sherer TB, Betarbet R, Testa CM, Seo BB et al (2003) Mechanisms of toxicity in rotenone models of Parkinson’s disease, Jour. Neuroscience 23(24):10756–10764PubMedGoogle Scholar
  18. 18.
    Attwell D, Laughlin SB (2001) An energy budget for signalling in the grey matter of the brain. J Cereb Blood Flow Metab 21:1133–1145PubMedCrossRefGoogle Scholar
  19. 19.
    Matsuda W, Furuta T, Nakamura KC, Hioki H, Fujiyama F, Arai R, Kaneko T (2009) Single nigrostratal dopaminergic neurons form widely spread and high dense axonal arborisations in the neostriatum, Jour. Neuroscience 29(2):444–453PubMedCrossRefGoogle Scholar
  20. 20.
    Braak H, Del Tredici K (2004) Poor and protracted myelination as a contributory factor in neurodegenerative disorders. Neurbiology of Aging 25:19–23CrossRefGoogle Scholar
  21. 21.
    Kelly M (2010) private communicationGoogle Scholar
  22. 22.
    Paynter HM (1961) Analysis and design of engineering systems. MIT, CambridgeGoogle Scholar
  23. 23.
    Wellstead P (2010) Systems biology and the spirit of Tustin. IEEE Contr Syst Mag 57–102Google Scholar
  24. 24.
    Aubert A, Costalat R (2002) A model of the coupling between brain electrical activity, metabolism, and hemodynamics: application to the interpretation of functional neuroimaging. Neuroimage 17:1162–1181PubMedCrossRefGoogle Scholar
  25. 25.
    Pellerin L, Magistretti PJ (1994) Glutamate uptake into astrocytes stimulates aerobic glycolysis: A mechanism coupling neuronal activity to glucose utilization. Proceedings of the National Academy of Science 91:10625–10629CrossRefGoogle Scholar
  26. 26.
    Pellerin L, Bouzier-Sore AK, Auber A, Serres S, Merle M, Costalat R, Magistretti PJ (2007) Activity-Dependant Regulation of Energy Metabolism by Astrocytes: An Update. Glia 55:1251–1262PubMedCrossRefGoogle Scholar
  27. 27.
    Aubert A, Costalat R (2005) Interactions between astrocytes and neurons studied using a mathematical of compartimentalized energy metabolism. J Cereb Blood Flow Metab 25:1476–1490PubMedCrossRefGoogle Scholar
  28. 28.
    Aubert A, Costalat R, Magistretti PJ, Pellerin L (2005) Brain lactate kinetics: modeling evidence for neuronal lactate uptake upon activation. Proceedings of the National Academy of Science 102(45):16448–16453CrossRefGoogle Scholar
  29. 29.
    Cloutier M, Bolger FB, Lowry JP, Wellstead P (2009) An integrative dynamical model of brain energy metabolism using in-vivo neurochemical measurements, Jour of Comp. Neuroscience 27(3):391–414Google Scholar
  30. 30.
    Geddje A (2002) Coupling of Blood Flow to Neuronal Excitability. In: Walz W (ed) The Neuronal Environment: Brain Homeostasis in Health and Disease. Humana Press, Totowa, NJ, USA, p 432Google Scholar
  31. 31.
    Heinrich R, Schuster S (1996) The regulation of cellular systems. ITP Chapman & Hall, New YorkCrossRefGoogle Scholar
  32. 32.
    Shen J, Petersen K, Behar K, Brown P, Nixon T, Mason G, Petroff O, Shulmann G, Shulman R, Rothman D (1999) Determination of the rate of the glutamate/glutamine cycle in the human brain by in vivo 13 C NMR. Proceedings of the National Academy of Science 96:8235–8240CrossRefGoogle Scholar
  33. 33.
    Zwingmann C, Butterworth R (2005) An update on the role of brain glutamine synthesis and its relation to cell-specific energy metabolism in the hyperammonemic brain: further studies using NMR spectroscopy. Neurochem Int 47:19–30PubMedCrossRefGoogle Scholar
  34. 34.
    Hyder F, Patel AB, Gjedde A, Rothman DL, Behar KL, Shulman RG (2006) Neuronal-Glial Glucose Oxidation and Glutamatergic-GABAergic Function. J Cereb Blood Flow Metab 26:865–877PubMedCrossRefGoogle Scholar
  35. 35.
    Schmidt H, Jirstand M (2006) Systems Biology Toolbox for MATLAB: A computational platform for research in Systems Biology. Bioinformatics 22(4):514–515PubMedCrossRefGoogle Scholar
  36. 36.
    Simpson IA, Carruthers A, Vannucci SJ (2007) Supply and Demand in Cerebral Energy Metabolism: The Role of Nutrient Transporters. J Cereb Blood Flow Metab 27(11):1766–1791PubMedCrossRefGoogle Scholar
  37. 37.
    Barros LF, Bittner CX, Loaiza A, Porras OH (2007) A Quantitative Overview of Glucose Dynamics in the Gliovascular Unit. Glia 55:1222–1237PubMedCrossRefGoogle Scholar
  38. 38.
    Fillenz M, Lowry JP (1998) Studies of the Source of Glucose in the Extracellular Compartment of the Rat Brain. Dev Neurosci 20:365–368PubMedCrossRefGoogle Scholar
  39. 39.
    Bolger F, Serra PA, O’Neill RD, Fillenz M, Lowry JP (2006) Real-time monitoring of brain extracellular lactate. In: Di Chiara G, Carboni E, Valentini V, Acquas E, Bassareo V, Cadoni C (eds) Monitoring Molecules in Neuroscience. University of Cagliari Press, Cagliara, Italy, pp 286–288Google Scholar
  40. 40.
    Clouter M, Wellstead P (2010) The control systems structures of energy metabolism. J R Soc Interface 7(45):651–665CrossRefGoogle Scholar
  41. 41.
    Hess B (1979) The glycolytic oscillator. J Exp Biol 81:7–14PubMedGoogle Scholar
  42. 42.
    Attwell D, Laughlin SB (2001) An energy budget for signalling in the grey matter of the brain. J Cereb Blood Flow Metab 21:1133–1145PubMedCrossRefGoogle Scholar
  43. 43.
    Hu Y, Wilson GS (1997) A temporal local energy pool coupled to neuronal activity: fluctuations of extracellular lactate levels in rat brain monitored with rapid-response enzyme-based sensor. J Neurochem 69:1484–1490PubMedCrossRefGoogle Scholar
  44. 44.
    McMahon CP, Rocchitta G, Serra PA, Kirwan SM, Lowry JP, O’Neill RD (2006) Control of the oxygen dependence of an implantable polymer/enzyme composite biosensor for glutamate. Anal Chem 78:2352–2359PubMedCrossRefGoogle Scholar
  45. 45.
    Seborg DE, Edgar TF, Mellichamp DA (1989) Process dynamics and control (Chapter 18). Wiley, New YorkGoogle Scholar
  46. 46.
    Tyson JJ, Chen KC, Novak B (2003) Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. Curr Opin Cell Biol 15:221–231PubMedCrossRefGoogle Scholar
  47. 47.
    Brown AM, Ransom BR (2007) Astrocyte glycogen and brain energy metabolism. Glia 55(12):1263–1271PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Hamilton InstituteNational University of IrelandMaynooth, County KildareIreland
  2. 2.GERAD and Ecole Polytechnique de MontrealMontrealCanada

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