Старение живого организма тесно связано с системными метаболическими изменениями, но из-за многоуровневого и сетевого характера метаболических путей возникает сложность понимания этих связей. Сегодня эту проблему решают с помощью одного из основных подходов метаболомики — ненаправленного метаболомного профилирования. Цель данной работы — систематизировать результаты метаболомных исследований, основанных на таком профилировании и выполненных как на модельных животных, так и на человеке.
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Ключевые слова: метаболомика, метаболомное профилирование, старение, животные модели, человек
Балашова Е.Е. и др. Метаболомное профилирование в изучении процессов старения // Биомедицинская химия. - 2022. - Т. 68. -N 5. - С. 321-338.
Балашова Е.Е. и др., "Метаболомное профилирование в изучении процессов старения." Биомедицинская химия 68.5 (2022): 321-338.
Балашова, Е. Е., Трифонова, О. П., Маслов, Д. Л., Лихтенберг, С. Р., Лохов, П. Г., Арчаков, А. И. (2022). Метаболомное профилирование в изучении процессов старения. Биомедицинская химия, 68(5), 321-338.
Список литературы
Ferrucci L., Giallauria F., Guralnik J.M. (2008) Epidemiology of aging. Radiologic Clinics of North America, 46(4),643-652. CrossRef Scholar google search
Butler R.N., Miller R.A., Perry D., Carnes B.A., Williams T.F., Cassel C., Brody J., Bernard M.A., Partridge L., Kirkwood T., Martin J.M., Olshansky S.J. (2008) New model of health promotion and disease prevention for the 21st century. BMJ, 337(7662), a399. CrossRef Scholar google search
Wijsman C.A., Rozing M.P., Streefland T.C.M., le Cessie S., Mooijaart S.P., Slagboom P.E., Westendorp R.G.J., Pijl H., van Heemst D. (2011) Familial longevity is marked by enhanced insulin sensitivity. Aging Cell, 10(1), 114-121. CrossRef Scholar google search
Kondoh H., Kameda M., Yanagida M. (2021) Whole blood metabolomics in aging research. Int. J. Mol. Sci., 22(1), 175. CrossRef Scholar google search
Karasik D., Demissie S., Cupples L.A., Kiel D.P. (2005) Disentangling the genetic determinants of human aging: Biological age as an alternative to the use of survival measures. J. Gerontol. A Biol. Sci. Med. Sci., 60(5), 574-587. CrossRef Scholar google search
Kerber R.A., O’Brien E., Cawthon R.M. (2009) Gene expression profiles associated with aging and mortality in humans. Aging Cell, 8, 239-250. CrossRef Scholar google search
Deelen J., Beekman M., Uh H.W., Helmer Q., Kuningas M., Christiansen L., Kremer D., van der Breggen R., Suchiman H.E.D., Lakenberg N., van den Akker E.B., Passtoors W.M., Tiemeier H., van Heemst D., de Craen A.J., Rivadeneira F., de Geus E.J., Perola M., van der Ouderaa F.J., Gunn D.A., Boomsma D.I., Uitterlinden A.G., Christensen K., van Duijn C.M., Heijmans B.T., Houwing-Duistermaat J.J., Westendorp R.G.J., Slagboom P.E. (2011) Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited. Aging Cell, 10, 686-698. CrossRef Scholar google search
Phillip J.M., Aifuwa I., Walston J., Wirtz D. (2015) The mechanobiology of aging. Annu. Rev. Biomed. Eng., 17, 113-141. CrossRef Scholar google search
Balashova E.E., Maslov D.L., Lokhov P.G. (2018) A metabolomics approach to pharmacotherapy personalization. J. Pers. Med., 8(3), 28. CrossRef Scholar google search
Sun N., Youle R.J., Finkel T. (2016) The mitochondrial basis of aging. Mol. Cell, 61(5), 654-666. CrossRef Scholar google search
Franceschi C., Capri M., Monti D., Giunta S., Olivieri F., Sevini F., Panourgia M.P., Invidia L., Celani L., Scurti M., Cevenini E., Castellani G.C., Salvioli S. (2007) Inflammaging and anti-inflammaging: A systemic perspective on aging and longevity emerged from studies in humans. Mech. Ageing Dev., 128, 92-105. CrossRef Scholar google search
Lehmann A.R. (2003) DNA repair-deficient diseases, xeroderma pigmentosum, Cockayne syndrome and t richothiodystrophy. Biochimie, 85(11), 1101-1111. CrossRef Scholar google search
Schriner S.E., Linford N.J., Martin G.M., Treuting P., Ogburn C.E., Emond M., Coskun P.E., Ladiges W., Wolf N., van Remmen H., Wallace D.C., Rabinovitch P.S. (2005) Extension of murine life span by overexpression of catalase targeted to mitochondria. Science, 308, 1909-1911. CrossRef Scholar google search
Sun J., Folk D., Bradley T.J., Tower J. (2002) Induced overexpression of mitochondrial Mn-superoxide dismutase extends the life span of adult Drosophila melanogaster. Genetics, 161, 661-672. CrossRef Scholar google search
Matheu A., Maraver A., Klatt P., Flores I., Garcia-Cao I., Borras C., Flores J.M., Viña J., Blasco M.A., Serrano M. (2007) Delayed ageing through damage protection by the Arf/p53 pathway. Nature, 448, 375-379. CrossRef Scholar google search
McCay C.M., Crowell M.F., Maynard L.A. (1989) The effect of retarded growth upon the length of life span and upon the ultimate body size. Nutrition, 5, 155-171. CrossRef Scholar google search
Sohal R.S., Ku H.H., Agarwal S., Forster M.J., Lal H. (1994) Oxidative damage, mitochondrial oxidant generation and antioxidant defenses during aging and in response to food restriction in the mouse. Mech. Ageing Dev., 74, 121-133. CrossRef Scholar google search
Haigis M.C., Guarente L.P. (2006) Mammalian sirtuins – Emerging roles in physiology, aging, and calorie restriction. Genes Dev., 20(21), 2913-2921. CrossRef Scholar google search
Cantó C., Jiang L.Q., Deshmukh A.S., Mataki C., Coste A., Lagouge M., Zierath J.R., Auwerx J. (2010) Interdependence of AMPK and SIRT1 for metabolic adaptation to fasting and exercise in skeletal Muscle. Cell Metab., 11, 213-219. CrossRef Scholar google search
Stanfel M.N., Shamieh L.S., Kaeberlein M., Kennedy B.K. (2009) The TOR pathway comes of age. Biochim. Biophys. Acta, 1790(10), 1067-1074. CrossRef Scholar google search
Greer E.L., Dowlatshahi D., Banko M.R., Villen J., Hoang K., Blanchard D., Gygi S.P., Brunet A. (2007) An AMPK-FOXO pathway mediates longevity induced by a novel method of dietary restriction in C. elegans. Curr. Biol., 17, 1646-1656. CrossRef Scholar google search
Моршнева А.В. (2020) Транскрипционные факторы FoxO как многофункциональные регуляторы клеточных процессов. Цитология, 62(10), 687-698. CrossRef Scholar google search
Baar M.P., Brandt R.M.C., Putavet D.A., Hoeijmakers J.H.J., Campisi J., de Keizer P.L.J. (2017) Targeted apoptosis of senescent cells restores tissue homeostasis in response to chemotoxicity and aging. Cell, 169, 132-147. CrossRef Scholar google search
Onken B., Driscoll M. (2010) Metformin induces a dietary restriction-like state and the oxidative stress response to extend C. elegans healthspan via AMPK, LKB1, and SKN-1. PLoS One, 5(1), e8758. CrossRef Scholar google search
Harrison D.E., Strong R., Sharp Z.D., Nelson J.F., Astle C.M., Flurkey K., Nadon N.L., Wilkinson J.E., Frenkel K., Carter C.S., Pahor M., Javors M.A., Fernandez E., Miller R.A. (2009) Rapamycin fed late in life extends lifespan in genetically heterogeneous mice. Nature, 460, 392-395. CrossRef Scholar google search
Mouchiroud L., Molin L., Dallière N., Solari F. (2010) Life span extension by resveratrol, rapamycin, and metformin: The promise of dietary restriction mimetics for an healthy aging. BioFactors, 36, 377-382. CrossRef Scholar google search
Houtkooper R.H., Mouchiroud L., Ryu D., Moullan N., Katsyuba E., Knott G., Williams R.W., Auwerx J. (2013) Mitonuclear protein imbalance as a conserved longevity mechanism. Nature, 497, 451-457. CrossRef Scholar google search
Yang W., Hekimi S. (2010) A mitochondrial superoxide signal triggers increased longevity in Сaenorhabditis elegans. PLoS Biol., 8(12), e1000556. CrossRef Scholar google search
Timblin G.A., Tharp K.M., Ford B., Winchester J.M., Wang J., Zhu S., Khan R.I., Louie S.K., Iavarone A.T., ten Hoeve J., Nomura D.K., Stahl A., Saijo K. (2021) Mitohormesis reprogrammes macrophage metabolism to enforce tolerance. Nat. Metab., 3, 618-635. CrossRef Scholar google search
Bjelakovic G., Nikolova D., Gluud C. (2014) Antioxidant supplements and mortality. Curr. Opin. Clin. Nutr. Metab. Care, 17(1), 40-44. CrossRef Scholar google search
Corrada M.M., Kawas C.H., Mozaffar F., Paganini-Hill A. (2006) Association of body mass index and weight change with all-cause mortality in the elderly. Am. J. Epidemiol., 163, 938-949. CrossRef Scholar google search
Irie J., Inagaki E., Fujita M., Nakaya H., Mitsuishi M., Yamaguchi S., Yamashita K., Shigaki S., Ono T., Yukioka H., Okano H., Nabeshima Y.-I., Imai S.-I., Yasui M., Tsubota K., Itoh H. (2020) Effect of oral administration of nicotinamide mononucleotide on clinical parameters and nicotinamide metabolite levels in healthy Japanese men. Endocr. J., 67, 153-160. CrossRef Scholar google search
Ikeda T., Aizawa J., Nagasawa H., Gomi I., Kugota H., Nanjo K., Jinno T., Masuda T., Morita S. (2016) Effects and feasibility of exercise therapy combined with branched-chain amino acid supplementation on muscle strengthening in frail and pre-frail elderly people requiring long-term care: A crossover trial. Appl. Physiol. Nutr. Metab., 41, 438-445. CrossRef Scholar google search
Nanda T., Das M. (2011) Metabolomics: The future of systems biology. J. Comput. Sci. Syst. Biol., 4(2), S13. CrossRef Scholar google search
Psychogios N., Hau D.D., Peng J., Guo A.C., Mandal R., Bouatra S., Sinelnikov I., Krishnamurthy R., Eisner R., Gautam B., Young N., Xia J., Knox C., Dong E., Huang P., Hollander Z., Pedersen T.L., Smith S.R., Bamforth F., Greiner R., McManus B., Newman J.W., Goodfriend T., Wishart D.S. (2011) The human serum metabolome. PLoS One, 6(2), e16957. CrossRef Scholar google search
Yu Z., Zhai G., Singmann P., He Y., Xu T., Prehn C., Römisch-Margl W., Lattka E., Gieger C., Soranzo N., Heinrich J., Standl M., Thiering E., Mittelstraß K., Wichmann H.-E., Peters A., Suhre K., Li Y., Adamski J., Spector T.D., Illig T., Wang-Sattler R. (2012) Human serum metabolic profiles are age dependent. Aging Cell, 11, 960-967. CrossRef Scholar google search
Srivastava S. (2019) Emerging insights into the metabolic alterations in aging using metabolomics. Metabolites, 9(12), 301. CrossRef Scholar google search
Gao A.W., Smith R.L., van Weeghel M., Kamble R., Janssens G.E., Houtkooper R.H. (2018) Identification of key pathways and metabolic fingerprints of longevity in C. elegans. Exp. Gerontol., 113, 128-140. CrossRef Scholar google search
Cox J.E., Thummel C.S., Tennessen J.M. (2017) Metabolomic studies in Drosophila. Genetics, 206, 1169-1185. CrossRef Scholar google search
Hoffman J.M., Soltow Q.A., Li S., Sidik A., Jones D.P., Promislow D.E.L. (2014) Effects of age, sex, and genotype on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster. Aging Cell, 13, 596-604. CrossRef Scholar google search
Avanesov A.S., Ma S., Pierce K.A., Yim S.H., Lee B.C., Clish C.B., Gladyshev V.N. (2014) Age- and diet-associated metabolome remodeling characterizes the aging process driven by damage accumulation. Elife, 3, e02077. CrossRef Scholar google search
Sarup P., Pedersen S.M.M., Nielsen N.C., Malmendal A., Loeschcke V. (2012) The metabolic profile of long-lived Drosophila melanogaster. PLoS One, 7(10), e47461. CrossRef Scholar google search
Hoffman J.M., Lyu Y., Pletcher S.D., Promislow D.E.L. (2017) Proteomics and metabolomics in ageing research: From biomarkers to systems biology. Essays Biochem., 61(3),379-388. CrossRef Scholar google search
Parkhitko A.A., Filine E., Mohr S.E., Moskalev A., Perrimon N. (2020) Targeting metabolic pathways for extension of lifespan and healthspan across multiple species. Ageing Res. Rev., 64, 101188. CrossRef Scholar google search
Kristal B.S., Shurubor Y.I. (2005) Metabolomics: Opening another window into aging. Sci. Aging Knowledge Environ., 2005(26), pe19. CrossRef Scholar google search
Patti G.J., Yanes O., Siuzdak G. (2012) Innovation: Metabolomics: the apogee of the omics trilogy. Nat. Rev. Mol. Cell Biol., 13, 263-269. CrossRef Scholar google search
Kotze H.L., Armitage E.G., Sharkey K.J., Allwood J.W., Dunn W.B., Williams K.J., Goodacre R. (2013) A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions. BMC Syst. Biol., 7, 107. CrossRef Scholar google search
Lokhov P.G., Balashova E.E., Voskresenskaya A.A., Trifonova O.P., Maslov D.L., Archakov A.I. (2016) Mass spectrometric signatures of the blood plasma metabolome for disease diagnostics. Biomed. Reports, 4, 122-126. CrossRef Scholar google search
Trifonova O.P., Maslov D.L., Balashova E.E., Lokhov P.G. (2021) Mass spectrometry-based metabolomics diagnostics – myth or reality? Expert Rev. Proteomics, 18, 7-12. CrossRef Scholar google search
Maslov D.L., Zemskaya N.V., Trifonova O.P., Lichtenberg S., Balashova E.E., Lisitsa A.V., Moskalev.A.A., Lokhov P.G. (2021) Comparative metabolomic study of Drosophila species with different lifespans. Int. J. Mol. Sci., 22(23), 12873. CrossRef Scholar google search
Trifonova O.P., Lokhov P.G., Archakov A.I. (2013) Metabolic profiling of human blood. Biochem. Suppl. Ser. B Biomed. Chem., 60(3), 281-294. CrossRef Scholar google search
Lokhov P.G., Archakov A.I. (2009) Mass spectrometry methods in metabolomics. Biochem. Suppl. Ser. B Biomed. Chem., 3(1), 1-9. CrossRef Scholar google search
Houtkooper R.H., Argmann C., Houten S.M., Cantó C., Jeninga E.H., Andreux P.A., Thomas C., Doenlen R., Schoonjans K., Auwerx J. (2011) The metabolic footprint of aging in mice. Sci. Rep., 1, 134. CrossRef Scholar google search
Lei Z., Huhman D.V., Sumner L.W. (2011) Mass spectrometry strategies in metabolomics. J. Biol. Chem., 286(29), 25435-25442. CrossRef Scholar google search
Trifonova O., Lokhov P., Archakov A. (2013) Postgenomics diagnostics: Metabolomics approaches to human blood profiling. OMICS J. Integr. Biol., 17, 550-559. CrossRef Scholar google search
Zhao Y.Y., Lin R.C. (2014) UPLC-MSE application in disease biomarker discovery: The discoveries in proteomics to metabolomics. Chemico-Biological Interactions, 215, 7-16. CrossRef Scholar google search
Lokhov P.G., Voskresenskaya A.A., Trifonova O.P., Maslov D.L., Shestakova E.A., Balashova E.E., Lisitsa A.V. (2015) Prediction of classical clinical chemistry parameters using a direct infusion mass spectrometry. Int. J. Mass Spectrom., 388, 53-58. CrossRef Scholar google search
Lokhov P.G., Balashova E.E., Trifonova O.P., Maslov D.L., Archakov A.I. (2021) A decade of russian metabolomics: The history of development and achievements. Biochem. Suppl. Ser. B Biomed. Chem., 15, 1-15. CrossRef Scholar google search
Meier R., Ruttkies C., Treutler H., Neumann S. (2017) Bioinformatics can boost metabolomics research. J. Biotechnol., 261, 137-141. CrossRef Scholar google search
Dunn W.B., Broadhurst D.I., Atherton H.J., Goodacre R., Griffin J.L. (2011) Systems level studies of mammalian metabolomes: The roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chem. Soc. Rev., 40(1), 387-426. CrossRef Scholar google search
Jollife I.T., Cadima J. (2016) Principal component analysis: A review and recent developments. Phil. Trans. R. Soc. A, 374, 20150202. CrossRef Scholar google search
Scholz M., Gatzek S., Sterling A., Fiehn O., Selbig J. (2004) Metabolite fingerprinting: Detecting biological features by independent component analysis. Bioinformatics, 20, 2447-2454. CrossRef Scholar google search
Smilde A.K., Jansen J.J., Hoefsloot H.C.J., Lamers R.J.A.N., van der Greef J., Timmerman M.E. (2005) ANOVA-simultaneous component analysis (ASCA): A new tool for analyzing designed metabolomics data. Bioinformatics, 21, 3043-3048. CrossRef Scholar google search
Vis D.J., Westerhuis J.A., Smilde A.K., van der Greef J. (2007) Statistical validation of megavariate effects in ASCA. BMC Bioinformatics, 8, 322. CrossRef Scholar google search
Sugimoto M., Kawakami M., Robert M., Soga T., Tomita M. (2012) Bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis. Curr. Bioinform., 7, 96-108. CrossRef Scholar google search
Jonsson P., Bruce S.J., Moritz T., Trygg J., Sjöström M., Plumb R., Granger J., Maibaum E., Nicholson J.K., Holmes E., Antti H. (2005) Extraction, interpretation and validation of information for comparing samples in metabolic LC/MS data sets. Analyst, 130, 701-707. CrossRef Scholar google search
Linden A. (2006) Measuring diagnostic and predictive accuracy in disease management: An introduction to receiver operating characteristic (ROC) analysis. J. Eval. Clin. Pract., 12, 132-139. CrossRef Scholar google search
Broeckling C.D., Reddy I.R., Duran A.L., Zhao X., Sumner L.W. (2006) MET-IDEA: Data extraction tool for mass spectrometry-based metabolomics. Anal. Chem., 78, 4334-4341. CrossRef Scholar google search
Baran R., Kochi H., Saito N., Suematsu M., Soga T., Nishioka T., Robert M., Tomita M. (2006) MathDAMP: A package for differential analysis of metabolite profiles. BMC Bioinformatics, 7, 530. CrossRef Scholar google search
Luedemann A., Strassburg K., Erban A., Kopka J. (2008) TagFinder for the quantitative analysis of gas chromatography – mass spectrometry (GC-MS)-based metabolite profiling experiments. Bioinformatics, 24, 732-737. CrossRef Scholar google search
Denkert C., Budczies J., Weichert W., Wohlgemuth G., Scholz M., Kind T., Niesporek S., Noske A., Buckendahl A., Dietel M., Fiehn O. (2008) Metabolite profiling of human colon carcinoma – deregulation of TCA cycle and amino acid turnover. Mol. Cancer, 7, 72. CrossRef Scholar google search
Bucaciuc Mracica T., Anghel A., Ion C.F., Moraru C.V., Tacutu R., Lazar G.A. (2020) MetaboAge DB: A repository of known ageing-related changes in the human metabolome. Biogerontology, 21, 763-771. CrossRef Scholar google search
Nevedomskaya E., Meissner A., Goraler S., de Waard M., Ridwan Y., Zondag G., van der Pluijm I., Deelder A.M., Mayboroda O.A. (2010) Metabolic profiling of accelerated aging ERCC1d/– mice. J. Proteome Res., 9, 3680-3687. CrossRef Scholar google search
Taormina G., Ferrante F., Vieni S., Grassi N., Russo A., Mirisola M.G. (2019) Longevity: Lesson from model organisms. Genes (Basel), 10(7), 518. CrossRef Scholar google search
Toth M.J., Tchernof A. (2000) Lipid metabolism in the elderly. Eur. J. Clin. Nutr., 54, S121-S125. CrossRef Scholar google search
Dennis J.W., Nabi I.R., Demetriou M. (2009) Metabolism, cell surface organization, and disease. Cell, 139(7), 1229-1241. CrossRef Scholar google search
Feltes B.C., de Faria Poloni J., Bonatto D. (2011) The developmental aging and origins of health and disease hypotheses explained by different protein networks. Biogerontology, 12, 293-308. CrossRef Scholar google search
Partridge L., Thornton J., Bates G. (2011) The new science of ageing. Philos. Trans. R Soc. Lond. B Biol. Sci., 366(1561), 6-8. CrossRef Scholar google search
Piper M.D.W., Partridge L. (2018) Drosophila as a model for ageing. Biochim. Biophys. Acta Mol. Basis Dis., 1864(9 Pt A), 2707-2717. CrossRef Scholar google search
Allard J.B., Duan C. (2011) Comparative endocrinology of aging and longevity regulation. Front. Endocrinol. (Lausanne), 2, 75. CrossRef Scholar google search
Barré-Sinoussi F., Montagutelli X. (2015) Animal models are essential to biological research: issues and perspectives. Futur. Sci. OA, 1, FSO63. CrossRef Scholar google search
Ball H.C., Levari-Shariati S., Cooper L.N., Aliani M. (2018) Comparative metabolomics of aging in a long-lived bat: Insights into the physiology of extreme longevity. PLoS One, 13, e0196154. CrossRef Scholar google search
Hoffman J.M., Poonawalla A., Icyuz M., Swindell W.R., Wilson L., Barnes S., Sun L.Y. (2020) Transcriptomic and metabolomic profiling of long-lived growth hormone releasing hormone knock-out mice: Evidence for altered mitochondrial function and amino acid metabolism. Aging (Albany NY), 12, 3473-3485. CrossRef Scholar google search
Williams R.E., Lenz E.M., Lowden J.S., Rantalainen M., Wilson I.D. (2005) The metabonomics of aging and development in the rat: An investigation into the effect of age on the profile of endogenous metabolites in the urine of male rats using 1H NMR and HPLC-TOF MS. Mol. Biosyst., 1, 166-175. CrossRef Scholar google search
Wang Y., Lawler D., Larson B., Ramadan Z., Kochhar S., Holmes E., Nicholson J.K. (2007) Metabonomic investigations of aging and caloric restriction in a life-long dog study. J. Proteome Res., 6, 1846-1854. CrossRef Scholar google search
Trifonova O.P., Maslov D.L., Mikhailov A.N., Zolotarev K.V., Nakhod K.V., Nakhod V.I., Belyaeva N.F., Mikhailova M.V., Lokhov P.G., Archakov A.I. (2018) Comparative analysis of the blood plasma metabolome of negligible, gradual and rapidly ageing fishes. Fishes, 3(4), 46. CrossRef Scholar google search
Maslov D.L., Trifonova O.P., Mikhailov A.N., Zolotarev K.V., Nakhod K.V., Nakhod V.I., Belyaeva N.F., Mikhailova M.V., Lokhov P.G., Archakov A.I. (2019) Comparative analysis of skeletal muscle metabolites of fish with various rates of aging. Fishes, 4(2), 25. CrossRef Scholar google search
Laye M.J., Tran V., Jones D.P., Kapahi P., Promislow D.E.L. (2015) The effects of age and dietary restriction on the tissue-specific metabolome of Drosophila. Aging Cell, 14, 797-808. CrossRef Scholar google search
Zhao X., Golic F.T., Harrison B.R., Manoj M., Hoffman E.V., Simon N., Johnson R., MacCoss M.J., McIntyre L.M., Promislow D.E.L. (2022) The metabolome as a biomarker of aging in Drosophila melanogaster. Aging Cell, 21(2), e13548. CrossRef Scholar google search
Ma Z., Wang H., Cai Y., Wang H., Niu K., Wu X., Ma H., Yang Y., Tong W., Liu F., Liu Z., Zhang Y., Liu R., Zhu Z.-J., Liu N. (2018) Epigenetic drift of H3K27me3 in aging links glycolysis to healthy longevity in Drosophila. Elife, 7, e35368. CrossRef Scholar google search
Tomás-Loba A., Bernardes de Jesus B., Mato J.M., Blasco M.A. (2013) A metabolic signature predicts biological age in mice. Aging Cell, 12, 93-101. CrossRef Scholar google search
Lu Y., A J., Wang G., Hao H., Huang Q., Yan B., Zha W., Gu S., Ren H., Zhang Y., Fan X., Zhang M., Hao K. (2008) Gas chromatography/time-of-flight mass spectrometry based metabonomic approach to differentiating hypertension- and age-related metabolic variation in spontaneously hypertensive rats. Rapid Commun. Mass Spectrom., 22, 2882-2888. CrossRef Scholar google search
Han Q., Li H., Jia M., Wang L., Zhao Y., Zhang M., Zhang Q., Meng Z., Shao J., Yang Y., Zhu L. (2021) Age-related changes in metabolites in young donor livers and old recipient sera after liver transplantation from young to old rats. Aging Cell, 20(7), e13425. CrossRef Scholar google search
Puurunen J., Ottka C., Salonen M., Niskanen J.E., Lohi H. (2022) Age, breed, sex and diet influence serum metabolite profiles of 2000 pet dogs. R Soc. Open Sci., 9(2), 211642. CrossRef Scholar google search
Lawton K.A., Berger A., Mitchell M., Milgram K.E., Evans A.M., Guo L., Hanson R.W., Kalhan S.C., Ryals J.A., Milburn M.V. (2008) Analysis of the adult human plasma metabolome. Pharmacogenomics, 9, 383-397. CrossRef Scholar google search
Chaleckis R., Murakami I., Takada J., Kondoh H., Yanagida M. (2016) Individual variability in human blood metabolites identifies age-related differences. Proc. Natl. Acad. Sci. USA, 113, 4252-4259. CrossRef Scholar google search
Bunning B.J., Contrepois K., Lee-McMullen B., Dhondalay G.K.R., Zhang W., Tupa D., Raeber O., Desai M., Nadeau K.C., Snyder M.P., Andorf S. (2020) Global metabolic profiling to model biological processes of aging in twins. Aging Cell, 19(1), e13073. CrossRef Scholar google search
Contrepois K., Jiang L., Snyder M. (2015) 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, 14, 1684-1695. CrossRef Scholar google search
Darst B.F., Koscik R.L., Hogan K.J., Johnson S.C., Engelman C.D. (2019) Longitudinal plasma metabolomics of aging and sex. Aging (Albany NY), 11, 1262-1282. CrossRef Scholar google search
Menni C., Kastenmüller G., Petersen A.K., Bell J.T., Psatha M., Tsai P.C., Gieger C., Schulz H., Erte I., John S., Brosnan M.J., Wilson S.G., Tsaprouni L., Mun L.E., Stuckey B., Deloukas P., Mohney R., Suhre K., Spector T.D., Valdes A.M. (2013) Metabolomic markers reveal novel pathways of ageing and early development in human populations. Int. J. Epidemiol., 42, 1111-1119. CrossRef Scholar google search
Krumsiek J., Mittelstrass K., Do K.T., Stückler F., Ried J., Adamski J., Peters A., Illig T., Kronenberg F., Friedrich N., Nauck M., Pietzner M., Mook-Kanamori D.O., Suhre K., Gieger C., Grallert H., Theis F.J., Kastenmüller G. (2015) Gender-specific pathway differences in the human serum metabolome. Metabolomics, 11, 1815-1833. CrossRef Scholar google search
Clark A.G., Eisen M.B., Smith D.R., Bergman C.M., Oliver B., Markow T.A., Kaufman T.C., Kellis M., Gelbart W., Iyer V.N., Pollard D.A., Sackton T.B., Larracuente A.M., Singh N.D., Abad J.P., Abt D.N., Adryan B., Aguade M., Akashi H., Anderson W.W., Aquadro C.F., Ardell D.H., Arguello R., Artie M.I. (2007) Evolution of genes and genomes on the Drosophila phylogeny. Nature, 450, 203-218. CrossRef Scholar google search
Ma S., Avanesov A.S., Porter E., Lee B.C., Mariotti M., Zemskaya N., Guigo R., Moskalev A.A., Gladyshev V.N. (2018) Comparative transcriptomics across 14 Drosophila species reveals signatures of longevity. Aging Cell, 17, e12740. CrossRef Scholar google search
Patnaik B.K., Mahapatro N., Jena B.S. (1994) Ageing in fishes. Gerontology, 40(2-4), 113-132. CrossRef Scholar google search
Anderson R.M., Shanmuganayagam D., Weindruch R. (2009) Caloric restriction and aging: Studies in mice and monkeys. Toxicol. Pathol., 37(1), 47-51. CrossRef Scholar google search
Schumacher B., van der Pluijm I., Moorhouse M.J., Kosteas T., Robinson A.R., Suh Y., Breit T.M., van Steeg H., Niedernhofer L.J., van Ijcken W., Bartke A., Spindler S.R., Hoeijmakers J.H.J., van der Horst G.T.J., Garinis G.A. (2008) Delayed and accelerated aging share common longevity assurance mechanisms. PLoS Genet., 4(8), e1000161. CrossRef Scholar google search
Radakovich L.B., Pannone S.C., Truelove M.P., Olver C.S., Santangelo K.S. (2017) Hematology and biochemistry of aging – evidence of “anemia of the elderly” in old dogs. Vet. Clin. Pathol., 46, 34-45. CrossRef Scholar google search
Xenoulis P.G., Steiner J.M. (2010) Lipid metabolism and hyperlipidemia in dogs. Vet. J., 183(1), 12-21. CrossRef Scholar google search