Skip to main content
SpringerLink
Log in

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

  • Chapter
  • First Online:
Systems Biology of Parkinson's Disease

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. von Bohlen und Halbach O, Schober A, Krieglstein K (2004) Genes, proteins, and neurotoxins involved in Parkinson’s disease. Prog Neurobiol 73(3):151–177

    Article  PubMed  CAS  Google Scholar 

  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 47:1275–1285

    Google Scholar 

  3. Tanner CM, Ross GW, Jewell SA, Hauser RA et al (2009) Occupation and risk of parkinsonism. Arch Neurol 9(66):1106–1113

    Article  Google Scholar 

  4. Litvan I et al (2007) The etiopathogenesis of Parkinson’s disease and suggestions for future research. Part 1. J Neuropathol Exp Neurol 66:251–257

    Article  PubMed  CAS  Google Scholar 

  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 55:181–184

    Article  PubMed  CAS  Google Scholar 

  6. Semchuk KM, Love EJ, Lee RG (1993) Parkinson’s disease: a test of the multifactorial etiology hypothesis. Neurology 43:1173–1180

    PubMed  CAS  Google Scholar 

  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 11:1015–1022

    Article  Google Scholar 

  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):866–872

    Article  CAS  Google Scholar 

  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):788–800

    Article  CAS  Google Scholar 

  10. Gash DM, Rutland K, Hudson NL et al (2008) Trichloroethylene: Parkinsonism and complex 1 mitochondrial neurotoxicity. Ann Neurol 63:184–192

    Article  PubMed  Google Scholar 

  11. Langston JW, Palfreman J (1995) The case of the frozen addicts. Pantheon, New York

    Google Scholar 

  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):69–74

    Article  Google Scholar 

  13. Singleton AD, Farrer M, Johnson J, Singleton A et al (2003) Alpha-synuclein locus triplication causes Parkinson’s disease. Science 302:841–844

    Article  PubMed  CAS  Google Scholar 

  14. Foltyne T, Sawcer S, Brayne C, Barker RA (2002) The genetic basis for Parkinson’s disease. Journ Neurol Neurosurg Psychiatry 73:363–370

    Article  Google Scholar 

  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):23–37

    Article  PubMed  CAS  Google Scholar 

  16. Roberts SB, Rosenberg I (2006) Nutrition and aging: changes in the regulation of energy metabolism with aging. Physiological Review 86:651–667

    Article  CAS  Google Scholar 

  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):10756–10764

    PubMed  CAS  Google Scholar 

  18. Attwell D, Laughlin SB (2001) An energy budget for signalling in the grey matter of the brain. J Cereb Blood Flow Metab 21:1133–1145

    Article  PubMed  CAS  Google Scholar 

  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):444–453

    Article  PubMed  CAS  Google Scholar 

  20. Braak H, Del Tredici K (2004) Poor and protracted myelination as a contributory factor in neurodegenerative disorders. Neurbiology of Aging 25:19–23

    Article  CAS  Google Scholar 

  21. Kelly M (2010) private communication

    Google Scholar 

  22. Paynter HM (1961) Analysis and design of engineering systems. MIT, Cambridge

    Google Scholar 

  23. Wellstead P (2010) Systems biology and the spirit of Tustin. IEEE Contr Syst Mag 57–102

    Google Scholar 

  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 17:1162–1181

    Article  PubMed  Google Scholar 

  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 91:10625–10629

    Article  CAS  Google Scholar 

  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 55:1251–1262

    Article  PubMed  Google Scholar 

  27. Aubert A, Costalat R (2005) Interactions between astrocytes and neurons studied using a mathematical of compartimentalized energy metabolism. J Cereb Blood Flow Metab 25:1476–1490

    Article  PubMed  CAS  Google Scholar 

  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):16448–16453

    Article  CAS  Google Scholar 

  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):391–414

    Google Scholar 

  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 432

    Google Scholar 

  31. Heinrich R, Schuster S (1996) The regulation of cellular systems. ITP Chapman & Hall, New York

    Book  Google Scholar 

  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 96:8235–8240

    Article  CAS  Google Scholar 

  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 47:19–30

    Article  PubMed  CAS  Google Scholar 

  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 26:865–877

    Article  PubMed  CAS  Google Scholar 

  35. Schmidt H, Jirstand M (2006) Systems Biology Toolbox for MATLAB: A computational platform for research in Systems Biology. Bioinformatics 22(4):514–515

    Article  PubMed  CAS  Google Scholar 

  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):1766–1791

    Article  PubMed  CAS  Google Scholar 

  37. Barros LF, Bittner CX, Loaiza A, Porras OH (2007) A Quantitative Overview of Glucose Dynamics in the Gliovascular Unit. Glia 55:1222–1237

    Article  PubMed  CAS  Google Scholar 

  38. Fillenz M, Lowry JP (1998) Studies of the Source of Glucose in the Extracellular Compartment of the Rat Brain. Dev Neurosci 20:365–368

    Article  PubMed  CAS  Google Scholar 

  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 286–288

    Google Scholar 

  40. Clouter M, Wellstead P (2010) The control systems structures of energy metabolism. J R Soc Interface 7(45):651–665

    Article  Google Scholar 

  41. Hess B (1979) The glycolytic oscillator. J Exp Biol 81:7–14

    PubMed  CAS  Google Scholar 

  42. Attwell D, Laughlin SB (2001) An energy budget for signalling in the grey matter of the brain. J Cereb Blood Flow Metab 21:1133–1145

    Article  PubMed  CAS  Google Scholar 

  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 69:1484–1490

    Article  PubMed  CAS  Google Scholar 

  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 78:2352–2359

    Article  PubMed  CAS  Google Scholar 

  45. Seborg DE, Edgar TF, Mellichamp DA (1989) Process dynamics and control (Chapter 18). Wiley, New York

    Google Scholar 

  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 15:221–231

    Article  PubMed  CAS  Google Scholar 

  47. Brown AM, Ransom BR (2007) Astrocyte glycogen and brain energy metabolism. Glia 55(12):1263–1271

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

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

Author information

Authors and Affiliations

  1. Hamilton Institute, National University of Ireland, Maynooth, County Kildare, Ireland

    Peter Wellstead

  2. GERAD and Ecole Polytechnique de Montreal, Montreal, QC, Canada

    Mathieu Cloutier

Authors
  1. Peter Wellstead
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mathieu Cloutier
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Wellstead .

Editor information

Editors and Affiliations

  1. , Hamilton Institute, National University of Ireland, Maynooth, Maynooth, Kildare, Ireland

    Peter Wellstead

  2. Ecole Polytechnique de Montreal, C.P. 6079, Succ. Centre-ville, Montreal, H3C 3A7, Québec, Canada

    Mathieu Cloutier

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media New York

About this chapter

Cite this chapter

Wellstead, P., Cloutier, M. (2012). Modelling and Simulation of Brain Energy Metabolism: Energy and Parkinson’s Disease. In: Wellstead, P., Cloutier, M. (eds) Systems Biology of Parkinson's Disease. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3411-5_2

Download citation

Publish with us

Policies and ethics

Search

Navigation