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Review

Metabolomics markers in Neurology: current knowledge and future perspectives for therapeutic targeting

ORCID Icon, ORCID Icon & ORCID Icon
Pages 725-738 | Received 28 Mar 2020, Accepted 11 Jun 2020, Published online: 27 Jun 2020

References

  • Zapalska-Sozoniuk M, Chrobak L, Kowalczyk K, et al. Is it useful to use several “omics” for obtaining valuable results? Mol Biol Rep. 2019 Jun;46(3):3597–3606.
  • Hassan-Smith G, Wallace GR, Douglas MR, et al. The role of metabolomics in neurological disease. J Neuroimmunol. 2012;248(1–2):48‐52.
  • Friedland RP, Budinger TF, Ganz E, et al. Regional cerebral metabolic alterations in dementia of the Alzheimer type: positron emission tomography with [18F] fluorodeoxyglucose. J Comput Assist Tomogr. 1983;7(4):590–598.
  • Foster NL, Chase TN, Mansi L, et al. Cortical abnormalities in Alzheimer’s disease. Ann Neurol. 1984;16(6):649–654.
  • Minoshima S, Giordani B, Berent S, et al. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol. 1997;42(1):85–94.
  • Sakamoto S, Ishii K, Sasaki M, et al. Differences in cerebral metabolic impairment between early and late onset types of Alzheimer’s disease. J Neurol Sci. 2002;200(1–2):27–32.
  • Ishii K, Sasaki H, Kono AK, et al. Comparison of gray matter and metabolic reduction in mild Alzheimer’s disease using FDG-PET and voxel-based morphometric MR studies. Eur J Nucl Med Mol Imaging. 2005;32(8):959–963.
  • Panov A, Schonfeld P, Dikalov S, et al. The neuromediator glutamate, through specific substrate interactions, enhances mitochondrial ATP production and reactive oxygen species generation in nonsynaptic brain mitochondria. J Biol Chem. 2009;21(284):14448–14456.
  • Panov AV, Kubalik N, Zinchenko N, et al. Metabolic and functional differences between brain and spinal cord mitochondria underlie different predisposition to pathology. Am J Physiol Regul Integr Comp Physiol. 2011;4(300):844–854.
  • Trushina E, Mielke MM. Recent advances in the application of metabolomics to Alzheimer’s disease. Biochim Biophys Acta. 2014;1842(8):1232–1239.
  • Han J, Kaufman RJ. The role of ER stress in lipid metabolism and lipotoxicity. J Lipid Res. 2016 Aug;57(8):1329–1338.
  • Yi L, Liu W, Wang Z, et al. Characterizing Alzheimer’s disease through metabolomics and investigating anti-Alzheimer’s disease effects of natural products. Ann N Y Acad Sci. 2017 Jun;1398(1):130–141.
  • Ebert D, Haller RG, Walton ME. Energy contribution of octanoate to intact rat brain metabolism measured by13C nuclear magnetic resonance spectroscopy. J Neurosci. 2003 Jul 2;23(13):5928–5935.
  • Weed LH, Cushing H. Studies on cerebrospinal fluid. VIII. The effect of pituitary extract upon its secretion (choroidorrhoea). Amer J Physiol. 1915;36(2):77–103.
  • Weed LH. The cerebrospinal fluid. Physiol Rev. 1922;2(2):171–203.
  • Cushing H. Studies in lntracranial physiology and surgery. London: Oxford Univ. Press; 1926. p. 146.
  • Kasser TR, Deutch A, Martin RJ. Uptake and utilization of metabolites in specific brain sites relative to feeding status. Physiol Behav. 1986;36(6):1161–1165.
  • el-Bacha RS, Minn A. Drug metabolizing enzymes in cerebrovascular endothelial cells afford a metabolic protection to the brain. Cell Mol Biol (Noisy-le-grand). 1999 Feb;45(1):15–23.
  • Greene DA, Winegrad AI. In vitro studies of the substrates for energy production and the effects of insulin on glucose utilization in the neural components of peripheral nerve. Diabetes. 1979;28(10):878–887.
  • Véga C, Martiel JL, Drouhault D, et al. Uptake of locally applied deoxyglucose, glucose and lactate by axons and Schwann cells of rat vagus nerve. J Physiol. 2003;546(2):551–564.
  • Ludvigson MA, Sorenson RL. Immunohistochemical localization of aldose reductase. I. Enzyme purification and antibody preparation–localization in peripheral nerve, artery, and testis. Diabetes. 1980;29(6):438–449.
  • Jiang Y, Calcutt NA, Ramos KM, et al. Novel sites of aldose reductase immunolocalization in normal and streptozotocin-diabetic rats [published correction appears in j peripher nerv syst 2007;12:64]. J Peripher Nerv Syst. 2006;11(4):274–285.
  • Cortese A, Zhu Y, Rebelo AP, et al. Biallelic mutations in SORD cause a common and potentially treatable hereditary neuropathy with implications for diabetes. Nat Genet. 2020;52(5):473‐481.
  • Freeman OJ, Unwin RD, Dowsey AW, et al. Metabolic dysfunction is restricted to the sciatic nerve in experimental diabetic neuropathy. Diabetes. 2016 Jan;65(1):228–238.
  • Fink BR, Cairns AM. A bioenergetic basis for peripheral nerve fiber dissociation. Pain. 1982 Apr;12(4):307–317.
  • Low PA, Schmelzer JD, Ward KK, et al. Experimental chronic hypoxic neuropathy: relevance to diabetic neuropathy. Am J Physiol. 1986 Jan;250(1 Pt 1):E94–9.
  • Low PA, Schmelzer JD, Ward KK. The effect of age on energy metabolism and resistance to ischaemic conduction failure in rat peripheral nerve. J Physiol. 1986 May;374(1):263–271.
  • Zala D, Hinckelmann MV, Yu H, et al. Vesicular glycolysis provides on-board energy for fast axonal transport. Cell. 2013;152(3):479‐491.
  • Skene DJ, Arendt J. Human circadian rhythms: physiological and therapeutic relevance of light and melatonin. Ann Clin Biochem. 2006 Sep;43(Pt 5):344–353.
  • Damiola F, Le Minh N, Preitner N, et al. Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes Dev. 2000 Dec 1;14(23):2950–2961.
  • Stokkan KA, Yamazaki S, Tei H, et al. Entrainment of the circadian clock in the liver by feeding. Science. 2001 Jan 19;291(5503):490–493.
  • Oster H, Challet E, Ott V, et al. The functional and clinical significance of the 24-hour rhythm of circulating glucocorticoids. Endocr Rev. 2017 Feb 1;38(1):3–45.
  • Zani F, Breasson L, Becattini B, et al. PER2 promotes glucose storage to liver glycogen during feeding and acute fasting by inducing Gys2 PTG and G L expression. Mol Metab. 2013;2(3):292–305.
  • Kornmann B, Schaad O, Bujard H, et al. System-driven and oscillator-dependent circadian transcription in mice with a conditionally active liver clock. PLoS Biol. 2007;5(2):e34.
  • Lamia KA, Storch KF, Weitz CJ. Physiological significance of a peripheral tissue circadian clock. Proc Natl Acad Sci USA.. 2008;105(39):15172–15177.
  • Davies SK, Ang JE, Revell VL, et al. Effect of sleep deprivation on the human metabolome. Proc Natl Acad Sci USA. 2014;111(29):10761–10766.
  • Honma A, Revell VL, Gunn PJ, et al. Effect of acute total sleep deprivation on plasma melatonin, cortisol and metabolite rhythms in females. Eur J Neurosci. 2020 Jan; 51(1):366–378.
  • Dallmann R, Viola AU, Tarokh L, et al. The human circadian metabolome. Proc Natl Acad Sci USA. 2012;109:2625–2629.
  • Kasukawa T, Sugimoto M, Hida A, et al. Human blood metabolite timetable indicates internal body time. Proc Natl Acad Sci USA. 2012;109(37):15036–15041.
  • Chua EC, Shui G, Lee IT, et al. Extensive diversity in circadian regulation of plasma lipids and evidence for different circadian metabolic phenotypes in humans. Proc Natl Acad Sci USA. 2013;110(35):14468–14473.
  • Wishart DS, Tzur D, Knox C, et al. HMDB: the human metabolome database. Nucleic Acids Res. 2007;35(Database):521–526.
  • Wishart DS, Knox C, Guo AC, et al. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res. 2009;37(783):603–610.
  • Weljie AM, Newton J, Mercier P, et al. Targeted profiling: quantitative analysis of 1H NMR metabolomics data. Anal Chem. 2006;78(13):4430–4442.
  • Surowiec I, Karimpour M, Gouveia-Figueira S, et al. Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study. Anal Bioanal Chem. 2016;408(17):4751–4764.
  • Contrepois K, Jiang L, Snyder M. Optimized analytical procedures for the untargeted metabolomic profiling of human urine and plasma by combining hydrophilic interaction (HILIC) and reverse-phase liquid chromatography (RPLC)–mass spectrometry. Mol Cell Proteomics. 2015;14(6):1684–1695.
  • Chen S, Kong H, Lu X, et al. Pseudotargeted metabolomics method and its application in serum biomarker discovery for hepatocellular carcinoma based on ultra high-performance liquid chromatography/triple quadrupole mass spectrometry. Anal Chem. 2013;85(17):8326–8333.
  • Khamis MM, Adamko DJ, El-Aneed A. Mass spectrometric based approaches in urine metabolomics and biomarker discovery. Mass Spectrom Rev. 2017;36(2):115–134.
  • Matsuo T, Tsugawa H, Miyagawa H, et al. Integrated strategy for unknown EI-MS identification using quality control calibration curve. multivariate analysis. EI-MS spectral database, and retention index prediction. Anal Chem. 2017;89(12):6766–6773.
  • Dossin E, Martin E, Diana P, et al. Prediction models of retention indices for increased confidence in structural elucidation during complex matrix analysis: application to gas chromatography coupled with high-resolution mass spectrometry. Anal Chem. 2016;88(15):7539–7547.
  • Ni Y, Su M, Qiu Y, et al. ADAP-GC 3.0: improved peak detection and deconvolution of co-eluting metabolites from GC/TOF-MS data for metabolomics studies. Anal Chem. 2016;88(17):8802–8811.
  • Domingo-Almenara X, Brezmes J, Vinaixa M, et al. eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics. Anal Chem. 2016;88(19):9821–9829.
  • Shao Y, Ye G, Ren S, et al. Metabolomics and transcriptomics profiles reveal the dysregulation of the tricarboxylic acid cycle and related mechanisms in prostate cancer. Int J Cancer. 2018 Jul 15;143(2):396–407.
  • Ye G, Liu Y, Yin P, et al. Study of induction chemotherapy efficacy in oral squamous cell carcinoma using pseudotargeted metabolomics. J Proteome Res. 2014;13(4):829 1994–2004.
  • Zhou Y, Song R, Zhang Z, et al. The development of plasma pseudotargeted GC-MS metabolic profiling and its application in bladder cancer. Anal Bioanal Chem. 2016 Sep;408(24):6741–6749.
  • Zhou J, Yin Y. Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry. Analyst. 2016;141(23):6362–6373.
  • Chen J, Wang W, Lv S, et al. Metabonomics study of liver cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations. Anal Chim Acta. 2009;650(1):3–9.
  • Ren S, Shao Y, Zhao X, et al. Integration of metabolomics and transcriptomics reveals major metabolic pathways and potential biomarker involved in prostate cancer. Mol Cell Proteomics. 2016;15(1):154–163.
  • Luo P, Yin P, Hua R, et al. A Large-scale, multicenter serum metabolite biomarker identification study for the early detection of hepatocellular carcinoma. Hepatology. 2018;67(2):662–675.
  • Zhou L, Wang Q, Yin P, et al. Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases. Anal Bioanal Chem. 2012;926(1):203–213.
  • Son J, Lyssiotis CA, Ying H, et al. Glutamine supports pancreatic cancer growth through a KRAS-regulated metabolic pathway. Nature. 2013;496(7443):101–105.
  • Cieslarova Z, Lopes FS, Do Lago CL, et al. Capillary electrophoresis tandem mass spectrometry determination of glutamic acid and homocysteine’s metabolites: potential biomarkers of amyotrophic lateral sclerosis. Talanta. 2017;170:63–68.
  • Rodrigues KT, Mekahli D, Tavares MF, et al. Development and validation of a CE-MS method for the targeted assessment of amino acids in urine. Electrophoresis. 2016;37(7–8):1039–1047.
  • Ciborowski M, Adamska E, Rusak M, et al. CE-MS-based serum fingerprinting to track evolution of type 2 diabetes mellitus. Electrophoresis. 2015 Sep;36(18):2286–2293.
  • Hirayama A, Kami K, Sugimoto M, et al. Quantitative metabolome profiling of colon and stomach cancer microenvironment by capillary electrophoresis time-of-flight mass spectrometry. Cancer Res. 2009;69(11):4918–4925.
  • Bojstrup M, Petersen BO, Beeren SR, et al. Fast and accurate quantitation of glucans in complex mixtures by optimized heteronuclear NMR spectroscopy. Anal Chem. 2013;85(18):8802–8808.
  • Nagana Gowda GA, Raftery D. Whole blood metabolomics by 1H NMR spectroscopy provides a new opportunity to evaluate coenzymes and antioxidants. Anal Chem. 2017;89(8):4620–4627.
  • Winter G, Kroemer JO. Fluxomics - connecting ‘omics analysis and phenotypes. Environ Microbiol. 2013;15(7):1901–1916.
  • Srour O, Young JD, Eldar YC. Fluxomers: a new approach for C-13 metabolic flux analysis. BMC Syst Biol. 2011 Aug 16;5(1):129.
  • Nöh K, Droste P, Wiechert W. Visual workflows for 13 C-metabolic flux analysis. Bioinformatics. 2015;31(3):346–354.
  • Aguilar E, Marin de Mas I, Zodda E, et al. Metabolic reprogramming and dependencies associated with epithelial cancer stem cells independent of the epithelial-mesenchymal transition program. Stem Cells. 2016 May;34(5):1163–1176.
  • Ahn E, Kumar P, Mukha D, et al. Temporal fluxomics reveals oscillations in TCA cycle flux throughout the mammalian cell cycle. Mol Syst Biol. 2017 Nov 6;13(11):953.
  • Rhee EP, Gerszten RE. Metabolomics and cardiovascular biomarker discovery. Clin Chem. 2012;58(1):139–147.
  • Wilson RB, Hoggard JC, Synovec RE. Fast, high peak capacity separations in gas chromatography-time-of-flight mass spectrometry. Anal Chem. 2012;84(9):4167‐4173.
  • Gathungu RM, Kautz R, Kristal BS, et al. The integration of LC-MS and NMR for the analysis of low molecular weight trace analytes in complex matrices. Mass Spectrom Rev. 2020;39(1–2):35‐54.
  • Yin P, Peter A, Franken H, et al. Preanalytical aspects and sample quality assessment in metabolomics studies of human blood. Clin Chem. 2013;59(5):833‐845.
  • Stevens VL, Hoover E, Wang Y, et al. Pre-analytical factors that affect metabolite stability in human urine, plasma, and serum: a review. Metabolites. 2019;9(8):156.
  • Kim K, Mall C, Taylor SL, et al. Mealtime, temporal, and daily variability of the human urinary and plasma metabolomes in a tightly controlled environment. PLoS One. 2014 Jan 24;9(1):e86223.
  • Houtkooper RH, Argmann C, Houten SM, et al. The metabolic footprint of aging in mice. Sci Rep. 2011;1(1):134.
  • Son N, Hur HJ, Sung MJ, et al. Liquid chromatography-mass spectrometry-based metabolomic analysis of livers from aged rats. J Proteome Res. 2012;11(4):2551–2558.
  • Calvani R, Brasili E, Praticò G, et al. Fecal and urinary NMR-based metabolomics unveil an aging signature in mice. Exp Gerontol. 2014;49:5–11.
  • Ivanisevic J, Stauch KL, Petrascheck M, et al. Metabolic drift in the aging brain. Aging (Albany NY). 2016;8(5):1000–1020.
  • Kregel KC, Zhang HJ. An integrated view of oxidative stress in aging: basic mechanisms, functional effects, and pathological considerations. Am J Physiol Regul Integr Comp Physiol. 2007;292(1):18–36.
  • Findeisen HM, Pearson KJ, Gizard F, et al. Oxidative stress accumulates in adipose tissue during aging and inhibits adipogenesis. PLoS ONE. 2011;6(4):e18532.
  • Lee SH, Park S, Kim H, et al. Metabolomic approaches to the normal aging process. Metabolomics. 2014;10(6):1268–1292.
  • Yu Z, Zhai G, Singmann P, et al. Human serum metabolic profiles are age dependent. Aging Cell. 2012 Dec;11(6):960–967.
  • Chung HY, Cesari M, Anton S, et al. Molecular inflammation: underpinnings of aging and age-related diseases. Ageing Res Rev. 2009;8(1):18–30.
  • Hong SE, Heo HS, Kim DH, et al. Revealing system-level correlations between aging and calorie restriction using a mouse transcriptome. Age (Omaha). 2010;32(1):15–30.
  • Choe M, Jackson C, Yu BP. Lipid peroxidation contributes to age-related membrane rigidity. Free Radic Biol Med. 1995 Jun;18(6):977–984.
  • Wick G, Grubeck-Loebenstein B. The aging immune system: primary and secondary alterations of immune reactivity in the elderly. Exp Gerontol. 1997 Jul-Oct;32(4–5):401–413.
  • Mittelstrass K, Ried JS, Yu Z, et al. Discovery of sexual dimorphisms in metabolic and genetic biomarkers. PLoS Genet. 2011;7(8):e1002215.
  • Menni C, Kastenmüller G, Petersen AK, et al. Metabolomic markers reveal novel pathways of ageing and early development in human populations. Int J Epidemiol. 2013;42(4):1111–1119.
  • Krumsiek J, Mittelstrass K, Do KT, et al. Gender‐specific pathway differences in the human serum metabolome. Metabolomics. 2015;11(6):1815–1833.
  • Dunn WB, Lin W, Broadhurst D, et al. Molecular phenotyping of a UK population: defining the human serum metabolome. Metabolomics. 2015;11(1):9–26.
  • Chaleckis R, Murakami I, Takada J, et al. Individual variability in human blood metabolites identifies age‐related differences. Proc Natl Acad Sci USA. 2016;113(16):4252–4259.
  • Rist MJ, Roth A, Frommherz L, et al. Metabolite patterns predicting sex and age in participants of the Karlsruhe Metabolomics and Nutrition (KarMeN) study. PLoS One. 2017;12(8):e0183228.
  • Darst BF, Koscik RL, Hogan KJ, et al. Longitudinal plasma metabolomics of aging and sex. Aging (Albany NY). 2019 Feb 24;11(4):1262–1282.
  • Gonzalez‐Covarrubias V, Beekman M, Uh HW, et al. Lipidomics of familial longevity. Aging Cell. 2013;12(3):426–434.
  • Vermeulen A. Andropause. Maturitas. 2000 Jan 15;34(1):5–15.
  • Auro K, Joensuu A, Fischer K, et al. A metabolic view on menopause and ageing. Nat Commun. 2014;5(1):4708.
  • Ke C, Hou Y, Zhang H, et al. Plasma metabolic profiles in women are menopause dependent. PLoS One. 2015;10(11):e0141743.
  • Jové M, Maté I, Naudí A, et al. Human aging is a metabolome-related matter of gender. J Gerontol A Biol Sci Med Sci. 2016;71(5):578‐585.
  • Jové M, Naudí A, Gambini J, et al. A stress-resistant lipidomic signature confers extreme longevity to humans. J Gerontol A Biol Sci Med Sci. 2017;72(1):30‐37.
  • Pradas I, Jové M, Huynh K, et al. Exceptional human longevity is associated with a specific plasma phenotype of ether lipids. Redox Biol. 2019;21:101127.
  • Yin H, Xu L, Porter NA. Free radical lipid peroxidation: mechanisms and analysis. Chem Rev. 2011;111(10):5944‐5972.
  • Przedborski S, Vila M, Jackson-Lewis V. Series Introduction: neurodegeneration: what is it and where are we? J Clin Invest. 2003 Jan;111(1):3–10.
  • Bjornevik K, Zhang Z, ÉJ O, et al. Prediagnostic plasma metabolomics and the risk of amyotrophic lateral sclerosis. Neurology. 2019 Apr 30;92(18):e2089–e2100.
  • Palamiuc L, Schlagowski A, Ngo ST, et al. A metabolic switch toward lipid use in glycolytic muscle is an early pathologic event in a mouse model of amyotrophic lateral sclerosis. EMBO Mol Med. 2015;7(5):526–546.
  • Kumar A, Bala L, Kalita J, et al. Metabolomic analysis of serum by (1) H NMR spectroscopy in amyotrophic lateral sclerosis. Clin Chim Acta. 2010;411(7–8):563–567.
  • Schonfeld P, Reiser G. Why does brain metabolism not favor burning of fatty acids to provide energy? - Reflections on disadvantages of the use of free fatty acids as fuel for brain. J Cereb Blood Flow Metab. 2013;33(10):1493–1499.
  • Tracey TJ, Steyn FJ, Wolvetang EJ, et al. Neuronal lipid metabolism: multiple pathways driving functional outcomes in health and disease. Front Mol Neurosci. 2018;11:10.
  • Cacabelos D, Ayala V, Granado-Serrano AB, et al. Interplay between TDP-43 and docosahexaenoic acid-related processes in amyotrophic lateral sclerosis. Neurobiol Dis. 2016;88:148‐160.
  • Blasco H, Corcia P, Pradat PF, et al. Metabolomics in cerebrospinal fluid of patients with amyotrophic lateral sclerosis: an untargeted approach via high-resolution mass spectrometry. J Proteome Res. 2013;12(8):3746‐3754.
  • Wuolikainen A, Andersen PM, Moritz T, et al. ALS patients with mutations in the SOD1 gene have an unique metabolomic profile in the cerebrospinal fluid compared with ALS patients without mutations. Mol Genet Metab. 2012;105(3):472‐478.
  • Pean A, Steventon GB, Waring RH, et al. Pathways of cysteine metabolism in MND/ALS. J Neurol Sci. 1994;124:59–61.
  • Woolsey PB. Cysteine, sulfite, and glutamate toxicity: a cause of ALS? J Altern Complement Med. 2008;14(9):1159–1164.
  • Wuolikainen A, Moritz T, Marklund SL, et al. Disease related changes in the cerebrospinal fluid metabolome in amyotrophic lateral sclerosis detected by GC/TOFMS. PLoS One. 2011;6(4):17947.
  • Ginsberg L, Rafique S, Xuereb JH, et al. Disease and anatomic specificity of ethanolamine plasmalogen deficiency in Alzheimer’s disease brain. Brain Res. 1995;698(1–2):223–226.
  • Han X, Holtzman DM, McKeel DW Jr. Plasmalogen deficiency in early Alzheimer’s disease subjects and in animal models: molecular characterization using electrospray ionization mass spectrometry. J Neurochem. 2001;77(4):1168–1180.
  • Han X. Lipid alterations in the earliest clinically recognizable stage of Alzheimer’s disease: implication of the role of lipids in the pathogenesis of Alzheimer’s disease. Curr Alzheimer Res. 2005;2(1):65–77.
  • Goodenowe DB, Cook LL, Liu J, et al. Peripheral ethanolamine plasmalogen deficiency: a logical causative factor in Alzheimer’s disease and dementia. J Lipid Res. 2007 Nov;48(11):2485–2498.
  • Wood PL, Mankidy R, Ritchie S, et al. Circulating plasmalogen levels and Alzheimer disease assessment scale-cognitive scores in Alzheimer patients. J Psychiatry Neurosci. 2010 Jan;35(1):59–62.
  • Brites P, Waterham H, Wanders R. Functions and biosynthesis of plasmalogens in health and disease. Biochim Biophys Acta. 2004;1636(2–3):219–231.
  • Oresic M, Hyotylainen T, Herukka SK, et al. Metabolome in progression to Alzheimer’s disease. Transl Psychiatry. 2011;1(12):e57.
  • Xu XH, Huang Y, Wang G, et al. Metabolomics: a novel approach to identify potential diagnostic biomarkers and pathogenesis in Alzheimer’s disease. Neurosci Bull. 2012;28(5):641–648.
  • Han X, Rozen S, Boyle SH, et al. Metabolomics in early Alzheimer’s disease: identification of altered plasma sphingolipidome using shotgun lipidomics. PLoS One. 2011;6(7):e21643.
  • Mielke MM, Bandaru VV, Haughey NJ, et al. Serum sphingomyelins and ceramides are early predictors of memory impairment. Neurobiol Aging. 2010;31(1):17–24.
  • Bernath MM, Bhattacharyya S, Nho K, et al. Serum triglycerides in Alzheimer disease: relation to neuroimaging and CSF biomarkers. Neurology. 2020;94(20):e2088‐e2098.
  • Toledo JB, Arnold M, Kastenmuller G, et al. Metabolic network failures in Alzheimer’s disease: a biochemical road map. Alzheimers Dement. 2017;13(9):965–984.
  • Tynkkynen J, Chouraki V, van der Lee SJ, et al. Association of branched-chain amino acids and other circulating metabolites with risk of incident dementia and Alzheimer’s disease: a prospective study in eight cohorts. Alzheimers Dement. 2018;14(6):723–733.
  • Chouraki V, Preis SR, Yang Q, et al. Association of amine biomarkers with incident dementia and Alzheimer’s disease in the Framingham Study. Alzheimers Dement. 2017;13(12):1327–1336.
  • van der Lee SJ, Teunissen CE, Pool R, et al. Circulating metabolites and general cognitive ability and dementia: evidence from 11 cohort studies. Alzheimers Dement. 2018;14(6):707–722.
  • Ansoleaga B, Jové M, Schlüter A, et al. Deregulation of purine metabolism in Alzheimer’s disease. Neurobiol Aging. 2015;36(1):68‐80.
  • Niedzwiecki MM, Walker DI, Howell JC, et al. High-resolution metabolomic profiling of Alzheimer’s disease in plasma. Ann Clin Transl Neurol. 2020 Jan;7(1):36–45.
  • Graham SF, Holscher C, Green BD. Metabolic signatures of human Alzheimer’s disease (AD): 1H NMR analysis of the polar metabolome of post-mortem brain tissue. Metabolomics. 2014;10(4):744–753.
  • Kaddurah-Daouk R, Zhu H, Sharma S, et al. Alterations in metabolic pathways and networks in Alzheimer’s disease. Transl Psychiatry. 2013;3(4):e244.
  • Kaddurah-Daouk R, Rozen S, Matson W, et al. Metabolomic changes in autopsy-confirmed Alzheimer’s disease. Alzheimers Dement. 2011;7(3):309–317.
  • Tukiainen T, Tynkkynen T, Meakinen V-P, et al. A multimetabolite analysis of serum by 1H NMR spectroscopy: early systemic signs of Alzheimer’s disease. Biochem Biophys Res Comm. 2008;375(3):356–361.
  • Czech C, Berndt P, Busch K, et al. Metabolite profiling of Alzheimer’s disease cerebrospinal fluid. PLoS One. 2012;7(2):e31501.
  • Motsinger-Reif AA, Zhu H, Kling MA, et al. Comparing metabolomic and pathologic biomarkers alone and in combination for discriminating Alzheimer’s disease from normal cognitive aging. Acta Neuropathol Commun. 2013;1(1):28.
  • Mittal R, Gupta RL. In vitro antioxidant activity of piperine. Methods Find Exp Clin Pharmacol. 2000;22(5):271–274.
  • Mujumdar AM, Dhuley JN, Deshmukh VK, et al. Antiinflammatory activity of piperine. Jpn J Med Sci Biol. 1990;43(3):95–100.
  • Murata K, Matsumura S, Yoshioka Y, et al. Screening of beta-secretase and acetylcholinesterase inhibitors from plant resources. J Nat Med. 2015;69(1):123–129.
  • Stoessel D, Stellmann JP, Willing A, et al. Metabolomic profiles for primary progressive multiple sclerosis stratification and disease course monitoring. Front Hum Neurosci. 2018;12:226.
  • Del Boccio P, Pieragostino D, Di Ioia M, et al. Lipidomic investigations for the characterization of circulating serum lipids in multiple sclerosis. J Proteomics. 2011;74(12):2826–2836.
  • Mulder C, Wahlund LO, Teerlink T, et al. Decreased lysophosphatidylcholine/phosphatidylcholine ratio in cerebrospinal fluid in Alzheimer’s disease. J Neural Transm. 2003;110(8):949–955.
  • Treede I, Braun A, Sparla R, et al. Anti-inflammatory effects of phosphatidylcholine. J Biol Chem. 2007;282(37):27155–27164.
  • Miller LG Jr, Young JA, Ray SK, et al. Sphingosine toxicity in EAE and MS: evidence for ceramide generation via serine-palmitoyltransferase activation. Neurochem Res. 2017;42(10):2755–2768.
  • Hannun YA, Obeid LM. Principles of bioactive lipid signalling: lessons from sphingolipids. Nat Rev Mol Cell Biol. 2008 Feb;9(2):139–150.
  • Diestel A, Aktas O, Hackel D, et al. Activation of microglial poly(ADP-ribose)-polymerase-1 by cholesterol breakdown products during neuroinflammation: a link between demyelination and neuronal damage. J Exp Med. 2003;198(11):1729–1740.
  • Safaiyan S, Kannaiyan N, Snaidero N, et al. Age-related myelin degradation burdens the clearance function of microglia during aging. Nat Neurosci. 2016;19(8):995–998.
  • Garseth M, White LR, Aasly J. Little change in cerebrospinal fluid amino acids in subtypes of multiple sclerosis compared with acute polyradiculoneuropathy. Neurochem Int. 2001;39(2):111–115.
  • Musgrave T, Tenorio G, Rauw G, et al. Tissue concentration changes of amino acids and biogenic amines in the central nervous system of mice with experimental autoimmune encephalomyelitis (EAE). Neurochem Int. 2011;59(1):28–38.
  • Nogueras L, Gonzalo H, Jové M, et al. Lipid profile of cerebrospinal fluid in multiple sclerosis patients: a potential tool for diagnosis. Sci Rep. 2019 Aug 5;9(1):11313.
  • Gonzalo H, Brieva L, Tatzber F, et al. Lipidome analysis in multiple sclerosis reveals protein lipoxidative damage as a potential pathogenic mechanism. J Neurochem. 2012;123(4):622‐634.
  • LeWitt PA, Huber BR, Zhang J. An update on CSF biomarkers of Parkinson’s disease. In: Mandel S, editor. Neurodegenerative diseases: integrative PPPM approach as the medicine of the future: advances in predictive, preventive, and personalized medicine. Vol. 2. Dordrecht: Springer; 2013. p. 161–184.
  • Bogdanov M, Matson WR, Wang L, et al. Metabolomic profiling to develop blood biomarkers for Parkinson’s disease. Brain. 2008;131(Pt 2):389‐396.
  • Carvalho C, Correia SC, Cardoso S, et al. The role of mitochondrial disturbances in Alzheimer, Parkinson and Huntington diseases. Expert Rev Neurother. 2015;15(8):867–884.
  • Vilchez D, Saez I, Dillin A. The role of protein clearance mechanisms in organismal ageing and age-related diseases. Nat Commun. 2014;5(1):5659.
  • LeWitt PA, Li J, Lu M, et al. Parkinson study group–DATATOP investigators. Metabolomic biomarkers as strong correlates of Parkinson disease progression. Neurology. 2017 Feb 28;88(9):862–869.
  • Palacios N, Gao X, McCullough ML, et al. Caffeine and the risk of Parkinson’s disease in a large cohort of men and women. Mov Disord. 2013;27(10):1276–1282.
  • Loeffler DA, LeWitt PA, Juneau PL, et al. Altered guanosine and guanine concentrations in rabbit striatum following increased dopamine turnover. Brain Res Bull. 1998;45(3):297–299.
  • Tyurina YY, Polimova AM, Maciel E, et al. LC/MS analysis of cardiolipins in substantia nigra and plasma of rotenonetreated rats: implication for mitochondrial dysfunction in Parkinson’s disease. Free Radic Res. 2015;49(5):681–691.
  • Fagotti J, Targa ADS, Rodrigues LS, et al. Chronic sleep restriction in the rotenone Parkinson’s disease model in rats reveals peripheral early-phase biomarkers. Sci Rep. 2019 Feb 13;9(1):1898.
  • Farmer K, Smith CA, Hayley S, et al. Major alterations of phosphatidylcholine and lysophosphotidyl lipids in the substantia nigra using an early stage model of Parkinson’s disease. Int J Mol Sci. 2015;16(8):18865–18877.
  • Morton AJ, Middleton B, Rudiger S, et al. Increased plasma melatonin in presymptomatic Huntington disease sheep (Ovis aries): compensatory neuroprotection in a neurodegenerative disease? J Pineal Res. 2020 Mar; 68(2):e12624.
  • Chiang MC, Chen HM, Lee YH, et al. Dysregulation of C/EBPalpha by mutant Huntingtin causes the urea cycle deficiency in Huntington’s disease. Hum Mol Genet. 2007;16(5):483–498.
  • Chen CM, Lin YS, Wu YR, et al. High protein diet and Huntington’s disease. PLoS One. 2015 May 19;10(5):e0127654.
  • Skene DJ, Middleton B, Fraser CK, et al. Metabolic profiling of presymptomatic Huntington’s disease sheep reveals novel biomarkers. Sci Rep. 2017 Feb 22;7(1):43030.
  • Gray PA, Burtness HI. Hypoglycemic headache. Endocrinology. 1935;19(5):549–560.
  • Amery WK. Brain hypoxia: the turning- point in the genesis of the migraine attack? Cephalalgia. 1982;2(2):83–109.
  • Pingitore A, Lima GP, Mastorci F, et al. Exercise and oxidative stress: potential effects of antioxidant dietary strategies in sports. Nutrition. 2015;31(7–8):916–922.
  • Powers SK, Radak Z, Ji LL. Exercise-induced oxidative stress: past, present and future. J Physiol. 2016;594(18):5081–5092.
  • Schoonman GG, Evers DJ, Terwindt GM, et al. The prevalence of premonitory symptoms in migraine: a questionnaire study in 461 patients. Cephalalgia. 2006;26(10):1209–1213.
  • Arngrim N, Schytz HW, Britze J, et al. Migraine induced by hypoxia: an MRI spectroscopy and angiography study. Brain. 2016 Mar;139(Pt 3):723–737.
  • Trivedi MS, Holger D, Bui AT, et al. Short-term sleep deprivation leads to decreased systemic redox metabolites and altered epigenetic status. PloS One. 2017;12(7):e0181978.
  • Reyngoudt H, Paemeleire K, Descamps B, et al. 31 P-MRS demonstrates a reduction in high-energy phosphates in the occipital lobe of migraine without aura patients. Cephalalgia. 2011;31(12):1243–1253.
  • Welch KM, Levine SR, D’Andrea G, et al. Preliminary observations on brain energy metabolism in migraine studied by in vivo phosphorus 31 NMR spectroscopy. Neurology. 1989;39(4):538–541.
  • Barbiroli B, Montagna P, Cortelli P, et al. Abnormal brain and muscle energy metabolism shown by 31P magnetic resonance spectroscopy in patients affected by migraine with aura. Neurology. 1992 Jun;42(6):1209–1214.
  • Montagna P, Cortelli P, Monari L, et al. 31P-magnetic resonance spectroscopy in migraine without aura. Neurology. 1994 Apr;44(4):666–669.
  • Lodi R, Montagna P, Soriani S, et al. Deficit of brain and skeletal muscle bioenergetics and low brain magnesium in juvenile migraine: an in vivo 31P magnetic resonance spectroscopy interictal study. Pediatr Res. 1997 Dec;42(6):866–871.
  • Lodi R, Iotti S, Cortelli P, et al. Deficient energy metabolism is associated with low free magnesium in the brains of patients with migraine and cluster headache. Brain Res Bull. 2001 Mar 1;54(4):437–441.
  • Schulz UG, Blamire AM, Corkill RG, et al. Association between cortical metabolite levels and clinical manifestations of migrainous aura: an MR-spectroscopy study. Brain. 2007 Dec;130(Pt 12):3102–3110.
  • Kim JH, Kim S, Suh SI, et al. Interictal metabolic changes in episodic migraine: a voxel-based FDG-PET study. Cephalalgia. 2010 Jan;30(1):53–61.
  • Reyngoudt H, Achten E, Paemeleire K. Magnetic resonance spectroscopy in migraine: what have we learned so far? Cephalalgia. 2012;32(11):845–859.
  • Watanabe H, Kuwabara T, Ohkubo M, et al. Elevation of cerebral lactate detected by localized 1H-magnetic resonance spectroscopy in migraine during the interictal period. Neurology. 1996;47(4):1093–1095.
  • Sándor PS, Dydak U, Schoenen J, et al. MR-spectroscopic imaging during visual stimulation in subgroups of migraine with aura. Cephalalgia. 2005 Jul;25(7):507–518.
  • Prescot A, Becerra L, Pendse G, et al. Excitatory neurotransmitters in brain regions in interictal migraine patients. Mol Pain. 2009;5:34.
  • Reyngoudt H, Paemeleire K, Dierickx A, et al. Does visual cortex lactate increase following photic stimulation in migraine without aura patients? A functional (1)H-MRS study. J Headache Pain. 2011 Jun;12(3):295–302.
  • Mohamed RE, Aboelsafa AA, Al-Malt AM. Interictal alterations of thalamic metabolic concentration ratios in migraine without aura detected by proton magnetic resonance spectroscopy. Egypt J Radio Nucl Med. 2013;44(4):859–870.
  • Becerra L, Veggeberg R, Prescot A, et al. A ‘complex’ of brain metabolites distinguish altered chemistry in the cingulate cortex of episodic migraine patients. Neuroimage Clin. 2016;11:588–594.
  • Sappey-Marinier D, Calabrese G, Fein G, et al. Effect of photic stimulation on human visual cortex lactate and phosphates using 1H and 31P magnetic resonance spectroscopy. J Cereb Blood Flow Metab. 1992 Jul;12(4):584–592.
  • Gross EC, Lisicki M, Fischer D, et al. The metabolic face of migraine from pathophysiology to treatment. Nat Rev Neurol. 2019 Nov;15(11):627–643.
  • Niemann A, Berger P, Suter U. Pathomechanisms of mutant proteins in Charcot-Marie-Tooth disease. Neuromolecular Med. 2006;8(1–2):217–242.
  • Timmerman V, Strickland AV, Züchner S. Genetics of Charcot-Marie-Tooth (CMT) disease within the frame of the Human Genome Project success. Genes (Basel). 2014;5(1):13–32.
  • Fridman V, Bundy B, Reilly MM, et al. CMT subtypes and disease burden in patients enrolled in the Inherited Neuropathies Consortium natural history study: a cross-sectional analysis. J Neurol Neurosurg Psychiatry. 2015;86(8):873–878.
  • Klein CJ, Duan X, Shy ME. Inherited neuropathies: clinical overview and update. Muscle Nerve. 2013;48(4):604–622.
  • Saporta AS, Sottile SL, Miller LJ, et al. Charcot–Marie–Tooth disease subtypes and genetic testing strategies. Ann Neurol. 2011;69(1):22–33.
  • Argyriou AA, Bruna J, Genazzani AA, et al. Chemotherapy-induced peripheral neurotoxicity: management informed by pharmacogenetics. Nat Rev Neurol. 2017 Aug;13(8):492–504.
  • Bais P, Beebe K, Morelli KH, et al. Metabolite profile of a mouse model of Charcot-Marie-Tooth type 2D neuropathy: implications for disease mechanisms and interventions. Biol Open. 2016 Jul 15;5(7):908–920.
  • Callander N, Markovina S, Eickhoff J, et al. Acetyl-L-carnitine (ALCAR) for the prevention of chemotherapy-induced peripheral neuropathy in patients with relapsed or refractory multiple myeloma treated with bortezomib, doxorubicin and low-dose dexamethasone: a study from the Wisconsin Oncology Network. Cancer Chemother Pharmacol. 2014;74(4):875–882.
  • Rojas DR, Kuner R, Agarwal N. Metabolomic signature of type 1 diabetes-induced sensory loss and nerve damage in diabetic neuropathy. J Mol Med (Berl). 2019 Jun; 97(6):845–854.
  • Tang HY, Chiu DT, Lin JF, et al. Disturbance of plasma lipid metabolic profile in Guillain-Barre syndrome. Sci Rep. 2017 Aug 15;7(1):8140.
  • Park SJ, Kim JK, Kim HH, et al. Integrative metabolomics reveals unique metabolic traits in Guillain-Barré Syndrome and its variants. Sci Rep. 2019 Jan 31;9(1):1077.
  • Capodivento G, Visigalli D, Garnero M, et al. Sphingomyelin as a myelin biomarker in CSF of acquired demyelinating neuropathies. Sci Rep. 2017;7(1):7831.
  • Park SJ, Jeong IH, Kong BS, et al. Disease type- and status-specific alteration of CSF metabolome coordinated with clinical parameters in inflammatory demyelinating diseases of CNS. PLoS One. 2016 Nov 17;11(11):e0166277.
  • Chakraborty G, Mekala P, Yahya D, et al. Intraneuronal N‐acetylaspartate supplies acetyl groups for myelin lipid synthesis: evidence for myelin‐associated aspartoacylase. J Neurochem. 2001;78(4):736–745.
  • Karelson G, Ziegler A, Künnecke B, et al. Feeding versus infusion: a novel approach to study the NAA metabolism in rat brain. NMR Biomed. 2003;16(67):413–423.
  • Moffett JR, Ross B, Arun P, et al. N-Acetylaspartate in the CNS: from neurodiagnostics to neurobiology. Prog Neurobiol. 2007;81(2):89–131.
  • Fujiwara S, Oshika H, Motoki K, et al. Diabetic ketoacidosis associated with Guillain-Barré syndrome with autonomic dysfunction. Int Med. 2000 Jul 10;89(7):1398–1414.
  • Wang Y, Li G, Yang S, et al. Fasting glucose levels correlate with disease severity of Guillain-Barré syndrome. PloS One. 2015;10(12):e0145075.
  • Ghasemlou N, Jeong SY, Lacroix S, et al. T cells contribute to lysophosphatidylcholine‐induced macrophage activation and demyelination in the CNS. Glia. 2007;55(3):294–302.
  • Cavaletti G, Cornblath DR. Chemotherapy-induced peripheral neurotoxicity: facts, needs and future directions. J Peripher Nerv Syst. 2019 Oct;24(Suppl 2):S86–S87.
  • André N, Braguer D, Brasseur G, et al. Paclitaxel induces release of cytochrome c from mitochondria isolated from human neuroblastoma cells. Cancer Res. 2000;60(19):5349–5353.
  • Bernardi P, Krauskopf A, Basso E, et al. The mitochondrial permeability transition from in vitro artifact to disease target. Febs J. 2006;273(10):2077–2099.
  • Flatters SJ, Bennett GJ. Studies of peripheral sensory nerves in paclitaxel-induced painful peripheral neuropathy: evidence for mitochondrial dysfunction. Pain. 2006;122(3):245–257.
  • Martin LJ, Gertz B, Pan Y, et al. The mitochondrial permeability transition pore in motor neurons: involvement in the pathobiology of ALS mice. Exp Neurol. 2009;218(2):333–346.
  • Xiao W, Boroujerdi A, Bennett GJ, et al. Chemotherapyevoked painful peripheral neuropathy: analgesic effects of gabapentin and effects on expression of the alpha-2-delta type-1 calcium channel subunit. Neuroscience. 2007;144(2):714–720.
  • Nieto FR, Entrena JM, Cendán CM, et al. Tetrodotoxin inhibits the development and expression of neuropathic pain induced by paclitaxel in mice. Pain. 2008;137(3):520–531.
  • Zhang YY, Li G, Che H, et al. Characterization of functional ion channels in human cardiac c-kit+ progenitor cells. Basic Res Cardiol. 2014;109(3):407.
  • Ledeboer A, Jekich BM, Sloane EM, et al. Intrathecal interleukin-10 gene therapy attenuates paclitaxel-induced mechanical allodynia and proinflammatory cytokine expression in dorsal root ganglia in rats. Brain Behav Immun. 2007;21(5):686–698.
  • Dutra RC, Bicca MA, Segat GC, et al. The antinociceptive effects of the tetracyclic triterpene euphol in inflammatory and neuropathic pain models: the potential role of PKCε. Neuroscience. 2015;303:126–137.
  • Li D, Huang ZZ, Ling YZ, et al. Up-regulation of CX3CL1 via nuclear factor-kappab-dependent histone acetylation is involved in paclitaxel-induced peripheral neuropathy. Anesthesiology. 2015;122(5):1142–1151.
  • Wu FZ, Xu WJ, Deng B, et al. Wen-luo-tong decoction attenuates paclitaxel-induced peripheral neuropathy by regulating linoleic acid and glycerophospholipid metabolism pathways. Front Pharmacol. 2018 Aug;28(9):956.
  • Patwardhan AM, Akopian AN, Ruparel NB, et al. Heat generates oxidized linoleic acid metabolites that activate TRPV1 and produce pain in rodents. J Clin Invest. 2010;120(5):1617–1626.
  • Wang HY, Tsai YJ, Chen SH, et al. Lysophosphatidylcholine causes neuropathic pain via the increase of neuronal nitric oxide synthase in the dorsal root ganglion and cuneate nucleus. Pharmacol. Biochem Behav. 2013;106: 47–56.
  • Sisignano M, Angioni C, Park CK, et al. Targeting CYP2J to reduce paclitaxel-induced peripheral neuropathic pain. Proc Natl Acad Sci USA. 2016;113(5):12544–12549.
  • Lunt SY, Vander Heiden MG. Aerobic glycolysis: meeting the metabolic requirements of cell proliferation. Annu Rev Cell Dev Biol. 2011;27(1):441–464.
  • Ahn CS, Metallo CM. Mitochondria as biosynthetic factories for cancer proliferation. Cancer Metab. 2015;3(1):1.
  • Young RM, Ackerman D, Quinn ZL, et al. Dysregulated mTORC1 renders cells critically dependent on desaturated lipids for survival under tumor-like stress. Genes Dev. 2013;27(10):1115–1131.
  • Krishnaiah SY, Wu G, Altman BJ, et al. Clock regulation of metabolites reveals coupling between transcription and metabolism. Cell Metab. 2017 Apr 4;25(4):961–974.e4.

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