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Current Alzheimer Research


ISSN (Print): 1567-2050
ISSN (Online): 1875-5828

Research Article

A Urinary Metabolomics Analysis Based on UPLC-MS and Effects of Moxibustion in APP/PS1 Mice

Author(s): Rui He, Juntian Liu, Chang Huang, Jinyi Liu, Herong Cui and Baixiao Zhao*

Volume 17 , Issue 8 , 2020

Page: [753 - 765] Pages: 13

DOI: 10.2174/1567205017666201109091759

Price: $65


Objective: Alzheimer's disease (AD) is a common neurodegenerative disorder with the symptoms of cognitive impairment and decreased learning and memory abilities. Metabolomics can reflect the related functional status and physiological and pathological changes in the process of AD. Moxibustion is a unique method in traditional Chinese medicine, which has been used in the treatment and prevention of diseases for thousands of years.

Methods: A total of 32 APP/PS1 mice were randomly divided into the model group, moxibustion group, moxa smoke group and smoke-free moxibustion group (n=8/group), using the random number table method, while eight C57BL/6 mice were used as the control group. The five groups were measured for 20 min/day, 6 days/week, for 4 weeks. After 4 weeks’ experiment, all the mice were placed in metabolic cages to collect urine continuously for 24 hours, for UPLC-MS analysis.

Results: Principal component analysis (PCA) was used to identify the different metabolites among the five groups, and partial least squares discriminant analysis (PLS-DA) was performed to reveal the effects on the metabolic variance. Sixteen potential biomarkers were identified among the five groups, primarily related to amino acid metabolism, starch metabolism, sucrose metabolism, interconversion of pentose and glucuronate, and aminoacyl biosynthesis. There were 17 differences in the potential metabolites between the control and model groups, involving the metabolism of amino acid, purine, pyrimidine, nicotinic acid and nicotinamide, and biosynthesis of pantothenate and coenzyme A. Fifteen potential biomarkers were identified between the model and moxibustion groups, related to starch metabolism, sucrose metabolism, interconversion of pentose and glucuronate, glyoxylate, dicarboxylate anions and some amino acid metabolism.

Conclusion: Moxibustion can regulate the metabolism of substance and energy by improving the synthesis and decomposition of carbohydrates and amino acids in APP/PS1 transgenic AD model mice.

Keywords: Metabolomics, Alzheimer's disease, APP/PS1 mice, UPLC-MS, moxibustion, urinary.

Vossel KA, Tartaglia MC, Nygaard HB, Zeman AZ, Miller BL. Epileptic activity in Alzheimer’s disease: Causes and clinical relevance. Lancet Neurol 2017; 16(4): 311-22.
[] [PMID: 28327340]
Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, Jones E. Alzheimer’s disease. Lancet 2011; 377(9770): 1019-31.
[] [PMID: 21371747]
Zenaro E, Pietronigro E, Della Bianca V, et al. Neutrophils promote Alzheimer’s disease-like pathology and cognitive decline via LFA-1 integrin. Nat Med 2015; 21(8): 880-6.
[] [PMID: 26214837]
Ossenkoppele R, Pijnenburg YA, Perry DC, et al. The behavioural/dysexecutive variant of Alzheimer’s disease: Clinical, neuroimaging and pathological features. Brain 2015; 138(Pt 9): 2732-49.
[] [PMID: 26141491]
Liu J, Zhao B. Effects of shenque moxibustion on behavioral changes and brain oxidative state in apolipoprotein e-deficient mice. Evid Based Complement Alternat Med 2015; 2015: 804.
Castellani RJ, Perry G. The complexities of the pathology-pathogenesis relationship in Alzheimer disease. Biochem Pharmacol 2014; 88(4): 671-6.
[] [PMID: 24447936]
Liao F, Yoon H, Kim J. Apolipoprotein E metabolism and functions in brain and its role in Alzheimer’s disease. Curr Opin Lipidol 2017; 28(1): 60-7.
[PMID: 27922847]
Leinenga G, Götz J. Scanning ultrasound removes amyloid-β and restores memory in an Alzheimer’s disease mouse model. Sci Transl Med 2015; 7(278)278ra33
[] [PMID: 25761889]
delEtoile J, Adeli H. Graph theory and brain connectivity in Alzheimer’s disease. Neuroscientist 2017; 23(6): 616-26.
[] [PMID: 28406055]
Gouras GK, Olsson TT, Hansson O. β-Amyloid peptides and amyloid plaques in Alzheimer’s disease. Neurotherapeutics 2015; 12(1): 3-11.
[] [PMID: 25371168]
Karran E, Mercken M, De Strooper B. The amyloid cascade hypothesis for Alzheimer’s disease: An appraisal for the development of therapeutics. Nat Rev Drug Discov 2011; 10(9): 698-712.
[] [PMID: 21852788]
Lim AS, Yu L, Kowgier M, Schneider JA, Buchman AS, Bennett DA. Modification of the relationship of the apolipoprotein E ε4 allele to the risk of Alzheimer disease and neurofibrillary tangle density by sleep. JAMA Neurol 2013; 70(12): 1544-51.
[] [PMID: 24145819]
Deming Y, Li Z, Kapoor M, Harari O, Del-Aguila JL, Black K, et al. Genome-wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers 2017; 133(5): 839-56.
Cuyvers E, Sleegers K. Genetic variations underlying Alzheimer’s disease: Evidence from genome-wide association studies and beyond. Lancet Neurol 2016; 15(8): 857-68.
[] [PMID: 27302364]
Sherva R, Tripodis Y, Bennett DA, et al. GENAROAD Consortium. Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Genetics Consortium. Genome-wide association study of the rate of cognitive decline in Alzheimer’s disease. Alzheimers Dement 2014; 10(1): 45-52.
[] [PMID: 23535033]
Lanoiselée HM, Nicolas G, Wallon D, et al. Collaborators of the CNR-MAJ project. APP, PSEN1, and PSEN2 mutations in early-onset Alzheimer disease: A genetic screening study of familial and sporadic cases. PLoS Med 2017; 14(3)e1002270
[] [PMID: 28350801]
Kunkle BW, Vardarajan BN, Naj AC, et al. Early-onset alzheimer disease and candidate risk genes involved in endolysosomal transport. JAMA Neurol 2017; 74(9): 1113-22.
[] [PMID: 28738127]
Cacace R, Sleegers K, Van Broeckhoven C. Molecular genetics of early-onset Alzheimer’s disease revisited. Alzheimers Dement 2016; 12(6): 733-48.
[] [PMID: 27016693]
Corder EH, Saunders AM, Strittmatter WJ, et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 1993; 261(5123): 921-3.
[] [PMID: 8346443]
Yamazaki Y, Painter MM, Bu G, Kanekiyo T. Apolipoprotein E as a therapeutic target in Alzheimer’s Disease: A review of basic research and clinical evidence. CNS Drugs 2016; 30(9): 773-89.
[] [PMID: 27328687]
Sun X, Wu Y, Gu M, et al. Selective filtering defect at the axon initial segment in Alzheimer’s disease mouse models. Proc Natl Acad Sci USA 2014; 111(39): 14271-6.
[] [PMID: 25232037]
Liu X, Locasale JW. Metabolomics: A primer. Trends Biochem Sci 2017; 42(4): 274-84.
[] [PMID: 28196646]
Hoffman JM, Lyu Y, Pletcher SD, Promislow DEL. Proteomics and metabolomics in ageing research: from biomarkers to systems biology. Essays Biochem 2017; 61(3): 379-88.
[] [PMID: 28698311]
Jové M, Portero-Otín M, Naudí A, Ferrer I, Pamplona R. Metabolomics of human brain aging and age-related neurodegenerative diseases. J Neuropathol Exp Neurol 2014; 73(7): 640-57.
[] [PMID: 24918636]
Deda O, Gika HG, Taitzoglou I, Raikos N, Theodoridis G. Impact of exercise and aging on rat urine and blood metabolome. An LC-MS based metabolomics longitudinal study. Metabolites 2017; 7(1)E10
[] [PMID: 28241477]
Bell JD, Sadler PJ, Morris VC, Levander OA. Effect of aging and diet on proton NMR spectra of rat urine. Magn Reson Med 1991; 17(2): 414-22.
[] [PMID: 1829498]
Zhao F, Gao L, Qin X, Du G, Zhou Y. The intervention effect of licorice in d-galactose induced aging rats by regulating the taurine metabolic pathway. Food Funct 2018; 9(9): 4814-21.
[] [PMID: 30131986]
Gebara E, Udry F, Sultan S, Toni N. Taurine increases hippocampal neurogenesis in aging mice. Stem Cell Res (Amst) 2015; 14(3): 369-79.
[] [PMID: 25889858]
Qi Q, Liu YN, Jin XM, et al. Moxibustion treatment modulates the gut microbiota and immune function in a dextran sulphate sodium-induced colitis rat model. World J Gastroenterol 2018; 24(28): 3130-44.
[] [PMID: 30065559]
Stein DJ. Massage acupuncture, moxibustion, and other forms of complementary and alternative medicine in inflammatory bowel disease. Gastroenterol Clin North Am 2017; 46(4): 875-80.
[] [PMID: 29173528]
Choi TY, Lee MS, Kim JI, Zaslawski C. Moxibustion for the treatment of osteoarthritis: An updated systematic review and meta-analysis. Maturitas 2017; 100: 33-48.
[] [PMID: 28539175]
Cheng L, Li P, Patel Y, et al. Moxibustion modulates sympathoexcitatory cardiovascular reflex responses through paraventricular nucleus. Front Neurosci 2019; 12: 1057.
[] [PMID: 30718997]
Fan L, Gong J, Fu W, et al. Gender-related differences in outcomes on acupuncture and moxibustion treatment among depression patients. J Altern Complement Med 2015; 21(11): 673-80.
[] [PMID: 26291873]
Choe S, Cai M, Jerng UM, Lee JH. The efficacy and underlying mechanism of moxibustion in preventing cognitive impairment: A systematic review of animal studies. Exp Neurobiol 2018; 27(1): 1-15.
[] [PMID: 29535565]
Zhang T, Wang LP, Wang GL, et al. Effects of moxibustion on symptoms of mild cognitive impairment: Protocol of a systematic review and meta-analysis. BMJ Open 2020; 10(4)e033910
[] [PMID: 32350012]
Liu F, Li ZM, Jiang YJ, Chen LD. A meta-analysis of acupuncture use in the treatment of cognitive impairment after stroke. J Altern Complement Med 2014; 20(7): 535-44.
[] [PMID: 24915606]
Ha L, Yu M, Yan Z, Rui Z. Effects of moxibustion and moxa smoke on behavior changes and energy metabolism in APP/PS1 Mice. 2019. 2019: 9419567
Yi T, Qi L, Li J, Le JJ, Shao L, Du X, et al. Moxibustion upregulates hippocampal progranulin expression. Neural Regen Res 2016; 11(4): 610.
Lian B, Gao J, Sui N, Feng T, Li M. Object, spatial and social recognition testing in a single test paradigm. Neurobiol Learn Mem 2018; 152: 39-49.
[] [PMID: 29778762]
Carmen Peña-Bautista , Marta Roca, David , Hervás , et al. Plasma metabolomics in early Alzheimer’s disease patients diagnosed with amyloid biomarker. J Proteomics 2019; 200: 144-52.
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 Alzheimers disease: A prospective study in eight cohorts. Alzheimers Dement 2018; 14(6): 723-33.
van der Velpen V, Teav T, Gallart-Ayala H, et al. Systemic and central nervous system metabolic alterations in Alzheimer’s disease. Alzheimers Res Ther 2019; 11(1): 93.
[] [PMID: 31779690]
Kim M, Snowden S, Suvitaival T, et al. Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer’s Disease biomarker discovery cohort. Alzheimers Dement 2019; 15(6): 817-27.
[] [PMID: 31078433]
Zhang YQ, Tang YB, Dammer E, et al. Dysregulated urinary arginine metabolism in older adults with amnestic mild cognitive impairment. Front Aging Neurosci 2019; 11: 90.
[] [PMID: 31105552]
González-Domínguez R, García-Barrera T, Vitorica J, Gómez-Ariza JL. Application of metabolomics based on direct mass spectrometry analysis for the elucidation of altered metabolic pathways in serum from the APP/PS1 transgenic model of Alzheimer’s disease. J Pharm Biomed Anal 2015; 107: 378-85.
[] [PMID: 25656489]
González-Domínguez R, García-Barrera T, Vitorica J, Gómez-Ariza JL. High throughput multiorgan metabolomics in the APP/PS1 mouse model of Alzheimer’s disease. Electrophoresis 2015; 36(18): 2237-49.
[] [PMID: 25641566]
González-Domínguez R, García-Barrera T, Vitorica J, Gómez-Ariza JL. Metabolomic screening of regional brain alterations in the APP/PS1 transgenic model of Alzheimer’s disease by direct infusion mass spectrometry. J Pharm Biomed Anal 2015; 102: 425-35.
[] [PMID: 25459942]
Karlíková R, Mičová K, Najdekr L, et al. Metabolic status of CSF distinguishes rats with tauopathy from controls. Alzheimers Res Ther 2017; 9(1): 78.
[] [PMID: 28934963]
Fernstrom JD, Fernstrom MH. Tyrosine, phenylalanine, and catecholamine synthesis and function in the brain. J Nutr 137(6)(1): 1539S-47S..2007;
[] [PMID: 17513421]
Jiao Y, Chen Y, Ma C, et al. Phenylalanine as a nitrogen source induces root growth and nitrogen-use efficiency in Populus × canescens. Tree Physiol 2018; 38(1): 66-82.
[] [PMID: 29036367]
Zhou C, Li G, Li Y, et al. A high-throughput metabolomic approach to explore the regulatory effect of mangiferin on metabolic network disturbances of hyperlipidemia rats. Mol Biosyst 2015; 11(2): 418-33.
[] [PMID: 25406416]
Al Rajabi A, Castro GS, da Silva RP, et al. Choline supplementation protects against liver damage by normalizing cholesterol metabolism in Pemt/Ldlr knockout mice fed a high-fat diet. J Nutr 2014; 144(3): 252-7.
[] [PMID: 24368431]
Trushina E, Nemutlu E, Zhang S, et al. Defects in mitochondrial dynamics and metabolomic signatures of evolving energetic stress in mouse models of familial Alzheimer’s disease. PLoS One 2012; 7(2)e32737
[] [PMID: 22393443]
Barba I, Fernandez-Montesinos R, Garcia-Dorado D, Pozo D. Alzheimer’s disease beyond the genomic era: nuclear magnetic resonance (NMR) spectroscopy-based metabolomics. J Cell Mol Med 2008; 12(5A): 1477-85.
[] [PMID: 18554316]
Jonczyk R, Ronconi S, Rychlik M, Genschel U. Pantothenate synthetase is essential but not limiting for pantothenate biosynthesis in Arabidopsis. Plant Mol Biol 2008; 66(1-2): 1-14.
[] [PMID: 17932772]
Snowden SG, Ebshiana AA, Hye A. Association between fatty acid metabolism in the brain and Alzheimer disease neuropathology and cognitive performance: A nontargeted metabolomic study 2017; 14(3)e1002266
Bogie JFJ, Haidar M, Kooij G, Hendriks JJA. Fatty acid metabolism in the progression and resolution of CNS disorders. Adv Drug Deliv Rev S0169-409X(20): 30006-5.2020;
[] [PMID: 31987838]
Zhang M, Liu Y, Liu M, et al. UHPLC-QTOF/MS-based metabolomics investigation for the protective mechanism of Danshen in Alzheimer's disease cell model induced by Aβ(1-42). 2019; 15(2): 5.
Ansoleaga B, Jové M, Schlüter A, et al. Deregulation of purine metabolism in Alzheimer’s disease. Neurobiol Aging 2015; 36(1): 68-80.
[] [PMID: 25311278]
Kaddurah-Daouk R, Zhu H, Sharma S, et al. Pharmacometabolomics Research Network. Alterations in metabolic pathways and networks in Alzheimer’s disease Transl Psychiatry 2013; 3(4): e244.
[] [PMID: 23571809]

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