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Brain aerobic glycolysis functions and Alzheimer’s disease

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Abstract

Genetic, biochemical, pathological, and biomarker data demonstrate that Alzheimer’s disease (AD) pathology, including the initiation and progressive buildup of insoluble forms of beta-amyloid (Aβ), appears to begin ~10–15 years prior to the onset of cognitive decline associated with AD. Metabolic dysfunction, a prominent feature of the evolving brain pathology, is reflected in a decline of total glucose utilization. Despite decades of interest in declining glucose use in AD no detailed consideration had been given to the possibility that this decline is not just a decline in energy consumption but rather in glycolysis alone. Glycolysis is a multi-step process that prepares the glucose molecule for oxidative phosphorylation and the generation of energy. In the normal brain, glycolysis exceeds that required for the needs of oxidative phosphorylation. Because it is occurring in a setting with adequate oxygen available for oxidative phosphorylation it is often referred to as aerobic glycolysis (AG). AG is a biomarker of a group of metabolic functions broadly supporting biosynthesis and neuroprotection. The distribution of AG in normal young adults correlates spatially with Aβ deposition in AD patients and cognitively normal individuals with elevated Aβ. In transgenic mice extracellular fluid Aβ and lactate, a marker of AG, vary in parallel regionally and with changes in activity. Reducing neuronal activity locally in transgenic mice attenuates plaque formation suggesting that plaque formation is an activity-dependent process associated with aerobic glycolysis.

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References

  1. Hebert LE, Scherr PA, Bienias JL, Bennett DA, Evans DA (2003) Alzheimer disease in the US population: prevalence estimates using the 2000 census. Arch Neurol 60(8):1119–1122

    Article  PubMed  Google Scholar 

  2. Holtzman DM, Morris JC, Goate AM (2011) Alzheimer’s disease: the challenge of the second century. Sci Transl Med 3(77):77sr71

  3. Price JL, Morris JC (1999) Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease. Ann Neurol 45(3):358–368

    Article  CAS  PubMed  Google Scholar 

  4. Morris JC, Price AL (2001) Pathologic correlates of nondemented aging, mild cognitive impairment, and early-stage Alzheimer’s disease. J Mol Neurosci 17(2):101–118

    Article  CAS  PubMed  Google Scholar 

  5. Jack CR Jr, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, Petersen RC, Trojanowski JQ (2010) Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol 9(1):119–128

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  6. Perrin RJ, Fagan AM, Holtzman DM (2009) Multimodal techniques for diagnosis and prognosis of Alzheimer’s disease. Nature 461(7266):916–922

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  7. Vlassenko AG, Mintun MA, Xiong C, Sheline YI, Goate AM, Benzinger TL, Morris JC (2011) Amyloid-beta plaque growth in cognitively normal adults: longitudinal [(11) C]Pittsburgh compound B data. Ann Neurol 70(5):857–861

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  8. Jack CR Jr, Wiste HJ, Lesnick TG, Weigand SD, Knopman DS, Vemuri P, Pankratz VS, Senjem ML, Gunter JL, Mielke MM, Lowe VJ, Boeve BF, Petersen RC (2013) Brain beta-amyloid load approaches a plateau. Neurology 80(10):890–896

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  9. Villemagne VL, Burnham S, Bourgeat P, Brown B, Ellis KA, Salvado O, Szoeke C, Macaulay SL, Martins R, Maruff P, Ames D, Rowe CC, Masters CL (2013) Amyloid beta deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: a prospective cohort study. Lancet Neurol 12(4):357–367

    Article  CAS  PubMed  Google Scholar 

  10. Langbaum JB, Chen K, Lee W, Reschke C, Bandy D, Fleisher AS, Alexander GE, Foster NL, Weiner MW, Koeppe RA, Jagust WJ, Reiman EM (2009) Categorical and correlational analyses of baseline fluorodeoxyglucose positron emission tomography images from the Alzheimer’s disease neuroimaging initiative (ADNI). Neuroimage 45(4):1107–1116

    Article  PubMed Central  PubMed  Google Scholar 

  11. Reiman EM, Caselli RJ, Yun LS, Chen K, Bandy D, Minoshima S, Thibodeau SN, Osborne D (1996) Preclinical evidence of Alzheimer’s disease in persons homozygous for the epsilon 4 allele for apolipoprotein E. N Eng J Med 334(12):752–758

    Article  CAS  Google Scholar 

  12. Reiman EM, Chen K, Alexander GE, Caselli RJ, Bandy D, Osborne D, Saunders AM, Hardy J (2004) Functional brain abnormalities in young adults at genetic risk for late-onset Alzheimer’s dementia. Proc Natl Acad Sci USA 101(1):284–289

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  13. Hoyer S, Nitsch R, Oesterreich K (1991) Predominant abnormality in cerebral glucose utilization in late-onset dementia of the Alzheimer type: a cross-sectional comparison against advanced late-onset and incipient early-onset cases. J Neural Transm Park Dis Dement Sect 3(1):1–14

    Article  CAS  PubMed  Google Scholar 

  14. Fukuyama H, Ogawa M, Yamauchi H, Yamaguchi S, Kimura J, Yonekura Y, Konishi J (1994) Altered cerebral energy metabolism in Alzheimer’s disease: a PET study. J Nucl Med 35(1):1–6

    CAS  PubMed  Google Scholar 

  15. Blass JP, Gibson GE, Hoyer S (2002) The role of the metabolic lesion in Alzheimer’s disease. J Alzheimers Dis 4(3):225–232

    CAS  PubMed  Google Scholar 

  16. Lying-Tunell U, Lindblad BS, Malmlund HO, Persson B (1981) Cerebral blood flow and metabolic rate of oxygen, glucose, lactate, pyruvate, ketone bodies and amino acids. Acta Neurol Scand 63(6):337–350

    Article  CAS  PubMed  Google Scholar 

  17. Rodriguez-Rodriguez P, Fernandez E, Bolanos JP (2013) Underestimation of the pentose-phosphate pathway in intact primary neurons as revealed by metabolic flux analysis. J Cereb Blood Flow Metab 33(12):1843–1845

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  18. Vaishnavi SN, Vlassenko AG, Rundle MM, Snyder AZ, Mintun MA, Raichle ME (2010) Regional aerobic glycolysis in the human brain. Proc Natl Acad Sci USA 107(41):17757–17762

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  19. Raichle ME, Posner JB, Plum F (1970) Cerebral blood flow during and after hyperventilation. Arch Neurol 23(5):394–403

    Article  CAS  PubMed  Google Scholar 

  20. Vlassenko AG, Vaishnavi SN, Couture L, Sacco D, Shannon BJ, Mach RH, Morris JC, Raichle ME, Mintun MA (2010) Spatial correlation between brain aerobic glycolysis and amyloid-beta (Abeta) deposition. Proc Natl Acad Sci USA 107(41):17763–17767

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Lunt SY, Vander Heiden MG (2011) Aerobic glycolysis: meeting the metabolic requirements of cell proliferation. Annu Rev Cell Dev Biol 27:441–464

    Article  CAS  PubMed  Google Scholar 

  22. Vaughn AE, Deshmukh M (2008) Glucose metabolism inhibits apoptosis in neurons and cancer cells by redox inactivation of cytochrome c. Nat Cell Biol 10:1477–1483

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. Li Z, Sheng M (2012) Caspases in synaptic plasticity. Mol Brain 5:15

    Article  PubMed Central  PubMed  Google Scholar 

  24. Mercer RW, Dunham PB (1981) Membrane-bound ATP fuels the Na/K pump. Studies on membrane-bound glycolytic enzymes on inside-out vesicles from human red cell membranes. J Gen Physiol 78(5):547–568

    Article  CAS  PubMed  Google Scholar 

  25. Okamoto K, Wang W, Rounds J, Chambers EA, Jacobs DO (2001) ATP from glycolysis is required for normal sodium homeostasis in resting fast-twitch rodent skeletal muscle. Am J Physiol Endocrinol Metab 281(3):E479–E488

    CAS  PubMed  Google Scholar 

  26. Newington JT, Pitts A, Chien A, Arseneault R, Schubert D, Cumming RC (2011) Amyloid beta resistance in nerve cell lines is mediated by the Warburg effect. PLoS One 6(4):e19191

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  27. Newington JT, Rappon T, Albers S, Wong DY, Rylett RJ, Cumming RC (2012) Overexpression of pyruvate dehydrogenase kinase 1 and lactate dehydrogenase A in nerve cells confers resistance to amyloid beta and other toxins by decreasing mitochondrial respiration and ROS production. J Biol Chem 44(287):37245–37258

    Google Scholar 

  28. Glasser MF, Goyal MS, Preuss TM, Raichle ME, Van Essen DC (2014) Trends and properties of human cerebral cortex: correlations with cortical myelin content. Neuroimage 93P2:165–175

  29. Sims-Robinson C, Kim B, Rosko A, Feldman EL (2010) How does diabetes accelerate Alzheimer disease pathology? Nat Rev Neurol 6(10):551–559

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  30. Raichle ME, Snyder AZ (2007) A default mode of brain function: a brief history of an evolving idea. Neuroimage 37(4):1083–1090 (discussion 1097–1089)

  31. Buckner RL, Andrews-Hanna JR, Schacter DL (2008) The brain’s default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci 1124:1–38

    Article  PubMed  Google Scholar 

  32. Braver TS, Barch DM (2006) Extracting core components of cognitive control. Trends Cogn Sci 10(12):529–532

    Article  PubMed  Google Scholar 

  33. Dosenbach NU, Fair DA, Cohen AL, Schlaggar BL, Petersen SE (2008) A dual-networks architecture of top-down control. Trends Cogn Sci 12(3):99–105

    Article  PubMed Central  PubMed  Google Scholar 

  34. Vincent JL, Kahn I, Snyder AZ, Raichle ME, Buckner RL (2008) Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. J Neurophysiol 100(6):3328–3342

    Article  PubMed Central  PubMed  Google Scholar 

  35. Shulman GL, Fiez JA, Corbetta M, Buckner RL, Miezin FM, Raichle ME, Petersen SE (1997) Common blood flow changes across visual tasks II: decreases in cerebral cortex. J Cognit Neurosci 9:648–663

    Article  CAS  Google Scholar 

  36. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL (2001) A default mode of brain function. Proc Natl Acad Sci USA 98(2):676–682

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  37. Fox MD, Raichle M (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8:700–711

    Article  CAS  PubMed  Google Scholar 

  38. Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ, Sporns O (2008) Mapping the structural core of human cerebral cortex. PLoS Biol 6(7):e159

    Article  PubMed Central  PubMed  Google Scholar 

  39. Buckner RL, Sepulcre J, Talukdar T, Krienen FM, Liu H, Hedden T, Andrews-Hanna JR, Sperling RA, Johnson KA (2009) Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer’s disease. J Neurosci 29(6):1860–1873

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. Buckner RL, Snyder AZ, Shannon BJ, LaRossa G, Sachs R, Fotenos AF, Sheline YI, Klunk WE, Mathis CA, Morris JC, Mintun MA (2005) Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci 25(34):7709–7717

    Article  CAS  PubMed  Google Scholar 

  41. Sheline YI, Raichle ME, Snyder AZ, Morris JC, Head D, Wang S, Mintun MA (2010) Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly. Biol Psychiatry 67(6):584–587

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  42. Sperling RA, Laviolette PS, O’Keefe K, O’Brien J, Rentz DM, Pihlajamaki M, Marshall G, Hyman BT, Selkoe DJ, Hedden T, Buckner RL, Becker JA, Johnson KA (2009) Amyloid deposition is associated with impaired default network function in older persons without dementia. Neuron 63(2):178–188

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  43. Fagan AM, Roe CM, Xiong C, Mintun MA, Morris JC, Holtzman DM (2007) Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults. Arch Neurol 64(3):343–349

    Article  PubMed  Google Scholar 

  44. Li G, Sokal I, Quinn JF, Leverenz JB, Brodey M, Schellenberg GD, Kaye JA, Raskind MA, Zhang J, Peskind ER, Montine TJ (2007) CSF tau/Abeta42 ratio for increased risk of mild cognitive impairment: a follow-up study. Neurology 69(7):631–639

    Article  CAS  PubMed  Google Scholar 

  45. Morris JC, Roe CM, Grant EA, Head D, Storandt M, Goate AM, Fagan AM, Holtzman DM, Mintun MA (2009) Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease. Arch Neurol 66(12):1469–1475

    Article  PubMed Central  PubMed  Google Scholar 

  46. Hyder F, Fulbright RK, Shulman RG, Rothman DL (2013) Glutamatergic function in the resting awake human brain is supported by uniformly high oxidative energy. J Cereb Blood Flow Metab 33(3):339–347

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  47. Bullmore E, Sporns O (2012) The economy of brain network organization. Nat Rev Neurosci 13(5):336–349

    CAS  PubMed  Google Scholar 

  48. Pellerin L, Magistretti PJ (1994) Glutamate uptake into astrocytes stimulates aerobic glycolysis: a mechanism coupling neuronal activity to glucose utilization. Proc Natl Acad Sci USA 91(22):10625–10629

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  49. Belanger M, Allaman I, Magistretti P (2011) Brain energy metabolism: focus on astrocyte-neuron metabolic cooperation. Cell Metab 14:724–738

    Article  CAS  PubMed  Google Scholar 

  50. Pellerin L, Magistretti PJ (2012) Sweet sixteen for ANLS. J Cereb Blood Flow Metab 32(7):1152–1166

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  51. Fernandez-Moncada I, Barros LF (2014) Non-preferential fuelling of the Na(+)/K(+)-ATPase pump. Biochem J 460(3):353–361

    Article  CAS  PubMed  Google Scholar 

  52. McGilvery RW, Goldstein GW (1983) Biochemistry: a functional approach. Saunders, Philadelphia

    Google Scholar 

  53. Campbell JD, Paul RJ (1992) The nature of fuel provision for the Na+, K(+)-ATPase in porcine vascular smooth muscle. J Physiol 447:67–82

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  54. Wu K, Aoki C, Elste A, Rogalski-Wilk AA, Siekevitz P (1997) The synthesis of ATP by glycolytic enzymes in the postsynaptic density and the effect of endogenously generated nitric oxide. Proc Natl Acad Sci USA 94(24):13273–13278

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  55. Azevedo FA, Carvalho LR, Grinberg LT, Farfel JM, Ferretti RE, Leite RE, Jacob Filho W, Lent R, Herculano-Houzel S (2009) Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J Comp Neurol 513(5):532–541

    Article  PubMed  Google Scholar 

  56. Kennedy MJ, Ehlers MD (2006) Organelles and trafficking machinery for postsynaptic plasticity. Annu Rev Neurosci 29:325–362

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  57. Marder E, Goaillard JM (2006) Variability, compensation and homeostasis in neuron and network function. Nat Rev Neurosci 7(7):563–574

    Article  CAS  PubMed  Google Scholar 

  58. Zhang D, Hou Q, Wang M, Lin A, Jarzylo L, Navis A, Raissi A, Liu F, Man HY (2009) Na, K-ATPase activity regulates AMPA receptor turnover through proteasome-mediated proteolysis. J Neurosci 29(14):4498–4511

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  59. Li Z, Okamoto K, Hayashi Y, Sheng M (2004) The importance of dendritic mitochondria in the morphogenesis and plasticity of spines and synapses. Cell 119(6):873–887

    Article  CAS  PubMed  Google Scholar 

  60. Sheng M, Hoogenraad CC (2007) The postsynaptic architecture of excitatory synapses: a more quantitative view. Annu Rev Biochem 76:823–847

    Article  CAS  PubMed  Google Scholar 

  61. Cai Q, Sheng ZH (2009) Mitochondrial transport and docking in axons. Exp Neurol 218(2):257–267

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  62. Pierre K, Chatton JY, Parent A, Repond C, Gardoni F, Di Luca M, Pellerin L (2009) Linking supply to demand: the neuronal monocarboxylate transporter MCT2 and the alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionic acid receptor GluR2/3 subunit are associated in a common trafficking process. Eur J Neurosci 29(10):1951–1963

    Article  PubMed  Google Scholar 

  63. Chih CP, Roberts EL Jr (2003) Energy substrates for neurons during neural activity: a critical review of the astrocyte-neuron lactate shuttle hypothesis. J Cereb Blood Flow Metab 23(11):1263–1281

    Article  CAS  PubMed  Google Scholar 

  64. Pellerin L, Magistretti PJ (2003) Food for thought: challenging the dogmas. J Cereb Blood Flow Metab 23(11):1282–1286

    Article  PubMed  Google Scholar 

  65. Raichle ME, Mintun MA (2006) Brain work and brain imaging. Annu Rev Neurosci 29:449–476

    Article  CAS  PubMed  Google Scholar 

  66. Barros LF (2013) Metabolic signaling by lactate in the brain. Trends Neurosci 36(7):396–404

    Article  CAS  PubMed  Google Scholar 

  67. Suzuki A, Stern SA, Bozdagi O, Huntley GW, Walker RH, Magistretti PJ, Alberini CM (2011) Astrocyte-neuron lactate transport is required for long-term memory formation. Cell 144(5):810–823

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  68. Bozzo L, Puyal J, Chatton JY (2013) Lactate modulates the activity of primary cortical neurons through a receptor-mediated pathway. PLoS One 8(8):e71721

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  69. Yang J, Ruchti E, Petit JM, Jourdain P, Grenningloh G, Allaman I, Magistretti PJ (2014) Lactate promotes plasticity gene expression by potentiating NMDA signaling in neurons. Proc Natl Acad Sci USA 33(111):12228–12233

    Article  Google Scholar 

  70. Brand KA, Hermfisse U (1997) Aerobic glycolysis by proliferating cells: a protective strategy against reactive oxygen species. FASEB J 11(5):388–395

    CAS  PubMed  Google Scholar 

  71. Mattson MP, Magnus T (2006) Ageing and neuronal vulnerability. Nat Rev Neurosci 7(4):278–294

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  72. Fukui H, Moraes CT (2008) The mitochondrial impairment, oxidative stress and neurodegeneration connection: reality or just an attractive hypothesis? Trends Neurosci 31(5):251–256

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  73. Mejias R, Villadiego J, Pintado CO, Vime PJ, Gao L, Toledo-Aral JJ, Echevarria M, Lopez-Barneo J (2006) Neuroprotection by transgenic expression of glucose-6-phosphate dehydrogenase in dopaminergic nigrostriatal neurons of mice. J Neurosci 26(17):4500–4508

    Article  CAS  PubMed  Google Scholar 

  74. Soucek T, Cumming R, Dargusch R, Maher P, Schubert D (2003) The regulation of glucose metabolism by HIF-1 mediates a neuroprotective response to amyloid beta peptide. Neuron 39(1):43–56

    Article  CAS  PubMed  Google Scholar 

  75. Vulliamy T, Mason P, Luzzatto L (1992) The molecular basis of glucose-6-phosphate dehydrogenase deficiency. Trends Genet TIG 8(4):138–143

    Article  CAS  PubMed  Google Scholar 

  76. Patra KC, Hay N (2014) The pentose phosphate pathway and cancer. Trends Biochem Sci 39(8):347–354

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  77. Janniere L, Canceill D, Suski C, Kanga S, Dalmais B, Lestini R, Monnier AF, Chapuis J, Bolotin A, Titok M, Le Chatelier E, Ehrlich SD (2007) Genetic evidence for a link between glycolysis and DNA replication. PLoS One 2(5):e447

    Article  PubMed Central  PubMed  Google Scholar 

  78. DeBerardinis RJ, Mancuso A, Daikhin E, Nissim I, Yudkoff M, Wehrli S, Thompson CB (2007) Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc Natl Acad Sci USA 104(49):19345–19350

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  79. Gaitonde MK, Jones J, Evans G (1987) Metabolism of glucose into glutamate via the hexose monophosphate shunt and its inhibition by 6-aminonicotinamide in rat brain in vivo. Proc R Soc Lond B Biol Sci 231(1262):71–90

    Article  CAS  PubMed  Google Scholar 

  80. Dringen R, Hoepken HH, Minich T, Ruedig C, Gibson GE, Dienel GA (2007) Pentose phosphate pathway and NADPH metabolism. In: Lajtha A (ed) Brain energetics, integration of molecular and cellular processes, vol 3. Handbook of Neurochemistry and Molecular Neurobiology, Springer, New York, pp 41–62

  81. Goyal MS, Hawrylycz M, Miller JA, Snyder AZ, Raichle ME (2014) Aerobic glycolysis in the human brain is associated with development and neotenous gene expression. Cell Metab 19(1):49–57

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  82. Dastur DK (1985) Cerebral blood flow and metabolism in normal human aging, pathological aging, and senile dementia. J Cereb Blood Flow Metab 5(1):1–9

    Article  CAS  PubMed  Google Scholar 

  83. Bufill E, Agusti J, Blesa R (2011) Human neoteny revisited: the case of synaptic plasticity. Am J Hum Biol Off J Hum Biol Counc 23(6):729–739

    Article  Google Scholar 

  84. Kang HJ, Kawasawa YI, Cheng F, Zhu Y, Xu X, Li M, Sousa AM, Pletikos M, Meyer KA, Sedmak G, Guennel T, Shin Y, Johnson MB, Krsnik Z, Mayer S, Fertuzinhos S, Umlauf S, Lisgo SN, Vortmeyer A, Weinberger DR, Mane S, Hyde TM, Huttner A, Reimers M, Kleinman JE, Sestan N (2011) Spatio-temporal transcriptome of the human brain. Nature 478(7370):483–489

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  85. Madsen PL, Hasselbalch SG, Hagemann LP, Olsen KS, Bulow J, Holm S, Wildschiodtz G, Paulson OB, Lassen NA (1995) Persistent resetting of the cerebral oxygen/glucose uptake ratio by brain activation: evidence obtained with the Kety–Schmidt technique. J Cereb Blood Flow Metab 15(3):485–491

    Article  CAS  PubMed  Google Scholar 

  86. Fox PT, Raichle ME, Mintun MA, Dence C (1988) Nonoxidative glucose consumption during focal physiologic neural activity. Science 241(4864):462–464

    Article  CAS  PubMed  Google Scholar 

  87. Blomqvist G, Seitz RJ, Sjogren I, Halldin C, Stone-Elander S, Widen L, Solin O, Haaparanta M (1994) Regional cerebral oxidative and total glucose consumption during rest and activation studied with positron emission tomography. Acta Physiol Scand 151(1):29–43

    Article  CAS  PubMed  Google Scholar 

  88. Mintun MA, Vlassenko AG, Rundle MM, Raichle ME (2004) Increased lactate/pyruvate ratio augments blood flow in physiologically activated human brain. Proc Natl Acad Sci USA 101(2):659–664

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  89. Vlassenko AG, Rundle MM, Raichle ME, Mintun MA (2006) Regulation of blood flow in activated human brain by cytosolic NADH/NAD+ ratio. Proc Natl Acad Sci USA 103(6):1964–1969

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  90. Nitsch RM, Deng M, Tennis M, Schoenfeld D, Growdon JH (2000) The selective muscarinic M1 agonist AF102B decreases levels of total Abeta in cerebrospinal fluid of patients with Alzheimer’s disease. Ann Neurol 48(6):913–918

    Article  CAS  PubMed  Google Scholar 

  91. Caccamo A, Oddo S, Billings LM, Green KN, Martinez-Coria H, Fisher A, LaFerla FM (2006) M1 receptors play a central role in modulating AD-like pathology in transgenic mice. Neuron 49(5):671–682

    Article  CAS  PubMed  Google Scholar 

  92. Lesne S, Ali C, Gabriel C, Croci N, MacKenzie ET, Glabe CG, Plotkine M, Marchand-Verrecchia C, Vivien D, Buisson A (2005) NMDA receptor activation inhibits alpha-secretase and promotes neuronal amyloid-beta production. J Neurosci 25(41):9367–9377

    Article  CAS  PubMed  Google Scholar 

  93. Kamenetz F, Tomita T, Hsieh H, Seabrook G, Borchelt D, Iwatsubo T, Sisodia S, Malinow R (2003) APP processing and synaptic function. Neuron 37(6):925–937

    Article  CAS  PubMed  Google Scholar 

  94. Cirrito JR, Yamada KA, Finn MB, Sloviter RS, Bales KR, May PC, Schoepp DD, Paul SM, Mennerick S, Holtzman DM (2005) Synaptic activity regulates interstitial fluid amyloid-beta levels in vivo. Neuron 48(6):913–922

    Article  CAS  PubMed  Google Scholar 

  95. Cirrito JR, Kang JE, Lee J, Stewart FR, Verges DK, Silverio LM, Bu G, Mennerick S, Holtzman DM (2008) Endocytosis is required for synaptic activity-dependent release of amyloid-beta in vivo. Neuron 58(1):42–51

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  96. Yan P, Bero AW, Cirrito JR, Xiao Q, Hu X, Wang Y, Gonzales E, Holtzman DM, Lee JM (2009) Characterizing the appearance and growth of amyloid plaques in APP/PS1 mice. J Neurosci 29(34):10706–10714

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  97. Bero AW, Yan P, Roh JH, Cirrito JR, Stewart FR, Raichle ME, Lee JM, Holtzman DM (2011) Neuronal activity regulates the regional vulnerability to amyloid-beta deposition. Nat Neurosci 14(6):750–756

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  98. Melzer P, Van der Loos H, Dorfl J, Welker E, Robert P, Emery D, Berrini JC (1985) A magnetic device to stimulate selected whiskers of freely moving or restrained small rodents: its application in a deoxyglucose study. Brain Res 348(2):229–240

    Article  CAS  PubMed  Google Scholar 

  99. Durham D, Woolsey TA (1978) Acute whisker removal reduces neuronal activity in barrels of mouse SmL cortex. J Comp Neurol 178(4):629–644

    Article  CAS  PubMed  Google Scholar 

  100. Mielke R, Herholz K, Grond M, Kessler J, Heiss WD (1994) Clinical deterioration in probable Alzheimer’s disease correlates with progressive metabolic impairment of association areas. Dementia 5(1):36–41

    CAS  PubMed  Google Scholar 

  101. Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE (1997) Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol 42(1):85–94

    Article  CAS  PubMed  Google Scholar 

  102. Mesulam MM (1999) Neuroplasticity failure in Alzheimer’s disease: bridging the gap between plaques and tangles. Neuron 24(3):521–529

    Article  CAS  PubMed  Google Scholar 

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Conflict of interest

The authors, Andrei G. Vlassenko, MD, PhD, and Marcus E. Raichle, MD declare no conflict of interest regarding this article.

Human and animal studies

For studies previously published by the authors all institutional and national guidelines for the care and use of laboratory animals were followed; human studies were approved by the Human Research Protection Office and Radioactive Drug Research Committee, and written informed consent was provided by all participants or their caregivers.

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Vlassenko, A.G., Raichle, M.E. Brain aerobic glycolysis functions and Alzheimer’s disease. Clin Transl Imaging 3, 27–37 (2015). https://doi.org/10.1007/s40336-014-0094-7

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