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1H NMR metabolomics investigation of an Alzheimer’s disease (AD) mouse model pinpoints important biochemical disturbances in brain and plasma

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Abstract

In this study data generated by 1H NMR were combined with chemometrics to analyse brain and plasma samples from APP/PS1 and wild type mice with the aim of developing a statistical model capable of predicting the features of Alzheimer’s disease (AD) displayed by this animal model. APP/PS1 is a well characterised double transgenic mouse model of AD and the results here demonstrate the potential of NMR technology as a platform for the detecting this disease. Using partial least squares discriminant analysis a model was built using both brain extracts (R2 = 0.99; Q2 = 0.66) and a high throughput method of plasma analysis (R2 = 0.98; Q2 = 0.75) capable of predicting AD in APP/PS1 mice. Analysis of brain extracts led to the elucidation of 20 metabolites and 16 of these were quantifiable. Relative brain levels of ascorbate, creatine, γ-aminobutyric acid and N-acetyl aspartic acid were significantly altered in APP/PS1 mice (p < 0.05). Analysis of plasma identified 14 metabolites and the levels of acetate, citrate, glutamate, glutamine, methionine, and an unknown signal were significantly altered in APP/PS1 mice (p < 0.05). Combining 1H NMR spectral data with chemometrics has been previously used to study biochemical disturbances in various disease states. This study further indicates the translational potential of this technology for identifying AD in people attending the memory clinic.

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References

  • Alzheimer, A. (1907). Ueber eine eigenartige Erkrankung der Hirnrinde. Zeitschrift fuer Psychiatrie, 64, 146–149.

    Google Scholar 

  • Amenta, F., Parnetti, L., Gallai, V., & Wallin, A. (2001). Treatment of cognitive dysfunction associated with Alzheimer’s disease with cholinergic precursors. Ineffective treatments or inappropriate approaches? Mechanisms of Ageing and Development, 122, 2025–2040.

    Article  PubMed  CAS  Google Scholar 

  • Beckonert, O., Keun, H. C., Ebbels, T. M., et al. (2007). Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nature Protocols, 2, 2692–2703.

    Article  PubMed  CAS  Google Scholar 

  • Birken, D. L., & Oldendorf, W. H. (1989). N-acetyl-l-aspartic acid: A literature review of a compound prominent in 1H-NMR spectroscopic studies of brain. Neuroscience and Biobehavioral Reviews, 13, 23–31.

    Article  PubMed  CAS  Google Scholar 

  • Cudalbu, C., Cavassila, S., Ratiney, H., Beuf, O., Briguet, A., & Graveron-Demilly, D. (2005). Metabolite concentrations of healthy mouse brain by magnetic resonance spectroscopy at 7 Tesla. Conference Proceedings IEEE Engineering in Medicine and Biology Society, 2, 1392–1395.

    CAS  Google Scholar 

  • Cui, Q., Lewis, I. A., Hegeman, A. D., Anderson, M. E., Li, J., Schulte, C. F., et al. (2008). Metabolite identification via the Madison Metabolomics Consortium Database. Nature Biotechnology, 26(2), 162–164.

    Article  PubMed  CAS  Google Scholar 

  • Daikhin, Y., & Yudkoff, M. (2000). Compartmentation of brain glutamate metabolism in neurons and glia. Journal of Nutrition, 130, 1026S–1031S.

    PubMed  CAS  Google Scholar 

  • Davies, P. (1999). Challenging the cholinergic hypothesis in Alzheimer disease. JAMA, 281, 1433–1434.

    Article  PubMed  CAS  Google Scholar 

  • de Graaf, R. A., Chowdhury, G. M., & Behar, K. L. (2011). Quantification of high-resolution (1)H NMR spectra from rat brain extracts. Analytical Chemistry, 83, 216–224.

    Article  PubMed  Google Scholar 

  • Dervilly-Pinel, G., Weigel, S., Lommen, A., et al. (2011). Assessment of two complementary liquid chromatography coupled to high resolution mass spectrometry metabolomics strategies for the screening of anabolic steroid treatment in calves. Analytica Chimica Acta, 700, 144–154.

    Article  PubMed  CAS  Google Scholar 

  • Erecinska, M., & Silver, I. (1989). ATP and brain function. Journal of Cerebral Blood Flow and Metabolism, 9(1), 2–19.

    Article  PubMed  CAS  Google Scholar 

  • Govindaraju, V., Young, K., & Maudsley, A. A. (2000). Proton NMR chemical shifts and coupling constants for brain metabolites. NMR in Biomedicine, 13, 129–153.

    Article  PubMed  CAS  Google Scholar 

  • Graham, S. F., Chevallier, O. P., Roberts, D., Holscher, C., Elliott, C. T., & Green, B. D. (2013). Investigation of the human brain metabolome to identify potential markers for early diagnosis and therapeutic targets of Alzheimer’s disease. Analytical Chemistry, 85(3), 1803–1811.

    Article  PubMed  CAS  Google Scholar 

  • Graham, S. F., Kennedy, T., Chevallier, O., et al. (2010). The application of NMR to study changes in polar metabolite concentrations in beef longissimus dorsi stored for different periods post mortem. Metabolomics, 6, 395–404.

    Article  CAS  Google Scholar 

  • Holscher, C. (2005). Development of beta-amyloid-induced neurodegeneration in Alzheimer’s disease and novel neuroprotective strategies. Reviews in the Neurosciences, 16, 181–212.

    Article  PubMed  CAS  Google Scholar 

  • Jones, G. L., Sang, E., Goddard, C., Mortishire-Smith, R. J., Sweatman, B. C., Haselden, J. N., et al. (2005). A functional analysis of mouse models of cardiac disease through metabolic profiling. Journal of Biological Chemistry, 280, 7530–7539.

    Article  PubMed  CAS  Google Scholar 

  • Knight, W. D., Okello, A. A., Ryan, N. S., et al. (2011). Carbon-11-Pittsburgh compound B positron emission tomography imaging of amyloid deposition in presenilin 1 mutation carriers. Brain, 134, 293–300.

    Article  PubMed  Google Scholar 

  • Kork, F., Holthues, J., Hellweg, R., et al. (2009). A possible new diagnostic biomarker in early diagnosis of Alzheimer's disease. Current Alzheimer's Research, 6, 519–524.

    Article  CAS  Google Scholar 

  • Lalonde, R., Kim, H. D., Maxwell, J. A., & Fukuchi, K. (2005). Exploratory activity and spatial learning in 12-month-old APP695SWE/co + PS1/ΔE9 mice with amyloid plaques. Neuroscience Letters, 390, 87–92.

    Article  PubMed  CAS  Google Scholar 

  • Mallidis, C., Green, B. D., Rogers, D., et al. (2009). Metabolic profile changes in the testes of mice with streptozotocin-induced type 1 diabetes mellitus. International Journal of Andrology, 32, 156–165.

    Article  PubMed  CAS  Google Scholar 

  • McClean, P. L., Parthsarathy, V., Faivre, E., & Holscher, C. (2011). The diabetes drug liraglutide prevents degenerative processes in a mouse model of Alzheimer’s disease. Journal of Neuroscience, 31, 6587–6594.

    Article  PubMed  CAS  Google Scholar 

  • Monge-Argiles, J. A., Munoz-Ruiz, C., Pampliega-Perez, A., et al. (2011). Biomarkers of Alzheimer’s disease in the cerebrospinal fluid of Spanish patients with mild cognitive impairment. Neurochemical Research, 36, 986–993.

    Article  PubMed  CAS  Google Scholar 

  • Pears, M. R., Cooper, J. D., Mitchison, H. M., Mortishire-Smith, R. J., Pearce, D. A., & Griffin, J. L. (2005). High resolution 1H NMR-based metabolomics indicates a neurotransmitter cycling deficit in cerebral tissue from a mouse model of Batten disease. Journal of Biological Chemistry, 280, 42508–42514.

    Article  PubMed  CAS  Google Scholar 

  • Poly, C., Massaro, J. M., Seshadri, S., et al. (2011). The relation of dietary choline to cognitive performance and white-matter hyperintensity in the Framingham Offspring Cohort 1, 2. American Journal of Clinical Nutrition, 94, 1584–1591.

    Article  PubMed  CAS  Google Scholar 

  • Posse, S., Dager, S. R., Richards, T. L., et al. (1997). In vivo measurement of regional brain metabolic response to hyperventilation using magnetic resonance: Proton echo planar spectroscopic imaging (PEPSI). Magnetic Resonance in Medicine, 37, 858–865.

    Article  PubMed  CAS  Google Scholar 

  • Ross, B. D. (1991). Biochemical considerations in 1H spectroscopy. Glutamate and glutamine; myo-inositol and related metabolites. NMR in Biomedicine, 4, 59–63.

    Article  PubMed  CAS  Google Scholar 

  • Salek, R. M., Xia, J., Innes, A., et al. (2010). A metabolomic study of CRND8 transgenic mouse model of Alzheimer’s disease. Neurochemistry International, 56, 937–947.

    Article  PubMed  CAS  Google Scholar 

  • Sappey-Marinier, D., Calabrese, G., Fein, G., Hugg, J. W., Biggins, C., & Weiner, M. W. (1992). Effect of photic stimulation on human visual cortex lactate and phosphates using 1H and 31P magnetic resonance spectroscopy. Journal of Cerebral Blood Flow and Metabolism, 12, 584–592.

    Article  PubMed  CAS  Google Scholar 

  • Schechter, P. J., & Sjoerdsma, A. (1990). Clinical relevance of measuring GABA concentrations in cerebrospinal fluid. Neurochemical Research, 15, 419–423.

    Article  PubMed  CAS  Google Scholar 

  • Smythies, J. R. (1996). The role of ascorbate in the brain: Therapeutic implications. JRSM, 89(5), 241.

    CAS  Google Scholar 

  • Tsang, T. M., Haselden, J. N., & Holmes, E. (2009). Metabonomic characterization of the 3-nitropropionic acid rat model of Huntington’s disease. Neurochemical Research, 34, 1261–1271.

    Article  PubMed  CAS  Google Scholar 

  • Veech, R. L. (1991). The metabolism of lactate. NMR in Biomedicine, 4, 53–58.

    Article  PubMed  CAS  Google Scholar 

  • Want, E. J., Wilson, I. D., Gika, H., et al. (2010). Global metabolic profiling procedures for urine using UPLC-MS. Nature Protocols, 5, 1005–1018.

    Article  PubMed  CAS  Google Scholar 

  • Wishart, D. S., Jewison, T., Guo, A. C., et al. (2013). The human metabolome database in 2013. Nucleic Acids Research, 1(41), D801–D807.

    Article  Google Scholar 

  • Xia, J., Psychogios, N., Young, N., & Wishart, D. S. (2009). MetaboAnalyst: A web server for metabolomic data analysis and interpretation. Nucleic Acids Research, 37, W652–W660.

    Article  PubMed  CAS  Google Scholar 

  • Xia, J., & Wishart, D. S. (2011). Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst. Nature Protocols, 6, 743–760.

    Article  PubMed  CAS  Google Scholar 

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Authors and Affiliations

  1. Institute of Global Food Security, Queen’s University Belfast, Stranmillis Road, Belfast, BT9 5AG, Northern Ireland

    Stewart F. Graham, Christopher T. Elliott & Brian D. Green

  2. School of Biomedical Sciences, University of Ulster, Coleraine Campus, Cromore Road, Coleraine, BT52 1SA, Northern Ireland

    Christian Holscher & Paula McClean

Authors
  1. Stewart F. Graham
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  2. Christian Holscher
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  3. Paula McClean
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  4. Christopher T. Elliott
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  5. Brian D. Green
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Correspondence to Stewart F. Graham.

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Graham, S.F., Holscher, C., McClean, P. et al. 1H NMR metabolomics investigation of an Alzheimer’s disease (AD) mouse model pinpoints important biochemical disturbances in brain and plasma. Metabolomics 9, 974–983 (2013). https://doi.org/10.1007/s11306-013-0516-y

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  • DOI: https://doi.org/10.1007/s11306-013-0516-y

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