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Current Molecular Medicine

Editor-in-Chief

ISSN (Print): 1566-5240
ISSN (Online): 1875-5666

Review Article

Metabolomics to Study Human Aging: A Review

Author(s): Claudia Martins, Sandra Magalhães*, Idália Almeida, Vanessa Neto, Sandra Rebelo and Alexandra Nunes

Volume 24, Issue 4, 2024

Published on: 15 May, 2023

Page: [457 - 477] Pages: 21

DOI: 10.2174/1566524023666230407123727

Price: $65

Abstract

In the last years, with the increase in the average life expectancy, the world’s population is progressively aging, which entails social, health and economic problems. In this sense, the need to better understand the physiology of the aging process becomes an urgent need. Since the study of aging in humans is challenging, cellular and animal models are widely used as alternatives. Omics, namely metabolomics, have emerged in the study of aging, with the aim of biomarker discovering, which may help to uncomplicate this complex process. This paper aims to summarize different models used for aging studies with their advantages and limitations. Also, this review gathers the published articles referring to biomarkers of aging already discovered using metabolomics approaches, comparing the results obtained in the different studies. Finally, the most frequently used senescence biomarkers are described, along with their importance in understanding aging.

[1]
Comfort A. The biology of senescence. Elsevier. 1979; 1979; p. 414.
[2]
Galloway A. The evolutionary biology of aging. By Michael R. Rose. New York: Oxford University Press. 1991. ix + 221 pp. ISBN 0-19-506133-0. $35.00 (cloth). Am J Phys Anthropol 1993; 91(2): 260-2.
[http://dx.doi.org/10.1002/ajpa.1330910217]
[3]
Hamczyk MR, Nevado RM, Barettino A, Fuster V, Andrés V. Biological versus chronological aging: JACC focus seminar. J Am Coll Cardiol 2020; 75(8): 919-30.
[http://dx.doi.org/10.1016/j.jacc.2019.11.062] [PMID: 32130928]
[4]
Foo H, Mather KA, Thalamuthu A, Sachdev PS. The many ages of man. Curr Opin Psychiatry 2019; 32(2): 130-7.
[http://dx.doi.org/10.1097/YCO.0000000000000473] [PMID: 30461440]
[5]
Jylhävä J, Pedersen NL, Hägg S. Biological age predictors. EBioMedicine 2017; 21: 29-36.
[http://dx.doi.org/10.1016/j.ebiom.2017.03.046] [PMID: 28396265]
[6]
Wu L, Xie X, Liang T, et al. Integrated multi-omics for novel aging biomarkers and antiaging targets. Biomolecules 2021; 12(1): 39.
[http://dx.doi.org/10.3390/biom12010039] [PMID: 35053186]
[7]
Gott A, Andrews C, Larriva Hormigos M, Spencer K, Bateson M, Nettle D. Chronological age, biological age, and individual variation in the stress response in the European starling: a follow-up study. PeerJ 2018; 6: e5842.
[http://dx.doi.org/10.7717/peerj.5842] [PMID: 30370189]
[8]
Eurostat Mortality and life expectancy statistics Eurostat - Statistics Explained 2022. Available from: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Mortality_and_life_expectancy_statistics#Life_expectancy_at_birth
[9]
Micó V, Berninches L, Tapia J, Daimiel L. NutrimiRAging: Micromanaging nutrient sensing pathways through nutrition to promote healthy aging. Int J Mol Sci 2017; 18(5): 915.
[http://dx.doi.org/10.3390/ijms18050915] [PMID: 28445443]
[10]
Flint B, Tadi P. Physiology, aging. StatPearls 2020.
[11]
López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. The hallmarks of aging. Cell 2013; 153(6): 1194-217.
[http://dx.doi.org/10.1016/j.cell.2013.05.039] [PMID: 23746838]
[12]
Sidler C. Genomic instability and aging: causes and consequencesKovalchuk I, Kovalchuk O Genome Stability: From Virus to Human Application. (1st ed.). Academic Press 2016; pp. 511-25.
[13]
Shammas MA. Telomeres, lifestyle, cancer, and aging. Curr Opin Clin Nutr Metab Care 2011; 14(1): 28-34.
[http://dx.doi.org/10.1097/MCO.0b013e32834121b1] [PMID: 21102320]
[14]
Aunan JR, Watson MM, Hagland HR, Søreide K. Molecular and biological hallmarks of ageing. Br J Surg 2016; 103(2): e29-46.
[http://dx.doi.org/10.1002/bjs.10053] [PMID: 26771470]
[15]
Jenuwein T, Allis CD. Translating the histone code. Science 2001; 293(5532): 1074-80.
[http://dx.doi.org/10.1126/science.1063127] [PMID: 11498575]
[16]
Gonzalo S. Epigenetic alterations in aging. J Appl Physiol 2010; 109(2): 586-97.
[http://dx.doi.org/10.1152/japplphysiol.00238.2010] [PMID: 20448029]
[17]
Han S, Brunet A. Histone methylation makes its mark on longevity. Trends Cell Biol 2012; 22(1): 42-9.
[http://dx.doi.org/10.1016/j.tcb.2011.11.001] [PMID: 22177962]
[18]
Wilson VL, Jones PA. DNA methylation decreases in aging but not in immortal cells. Science 1983; 220(4601): 1055-7.
[http://dx.doi.org/10.1126/science.6844925] [PMID: 6844925]
[19]
Chiti F, Stefani M, Taddei N, Ramponi G, Dobson CM. Rationalization of the effects of mutations on peptide andprotein aggregation rates. Nature 2003; 424(6950): 805-8.
[http://dx.doi.org/10.1038/nature01891] [PMID: 12917692]
[20]
Stefani M, Dobson CM, Stefani M, Dobson CM. Protein aggregation and aggregate toxicity: new insights into protein folding, misfolding diseases and biological evolution. J Mol Med 2003; 81(11): 678-99.
[http://dx.doi.org/10.1007/s00109-003-0464-5] [PMID: 12942175]
[21]
van der Rijt S, Molenaars M, McIntyre RL, Janssens GE, Houtkooper RH. Integrating the hallmarks of aging throughout the tree of life: A focus on mitochondrial dysfunction. Front Cell Dev Biol 2020; 8: 594416.
[http://dx.doi.org/10.3389/fcell.2020.594416] [PMID: 33324647]
[22]
Hayflick L. The limited in vitro lifetime of human diploid cell strains. Exp Cell Res 1965; 37(3): 614-36.
[http://dx.doi.org/10.1016/0014-4827(65)90211-9] [PMID: 14315085]
[23]
Collado M, Blasco MA, Serrano M. Cellular senescence in cancer and aging. Cell 2007; 130(2): 223-33.
[http://dx.doi.org/10.1016/j.cell.2007.07.003] [PMID: 17662938]
[24]
Oh J, Lee YD, Wagers AJ. Stem cell aging: Mechanisms, regulators and therapeutic opportunities. Nat Med 2014; 20(8): 870-80.
[http://dx.doi.org/10.1038/nm.3651] [PMID: 25100532]
[25]
Lees H, Walters H, Cox LS. Animal and human models to understand ageing. Maturitas 2016; 93: 18-27.
[http://dx.doi.org/10.1016/j.maturitas.2016.06.008] [PMID: 27372369]
[26]
Ferrucci L, Kuchel GA. Heterogeneity of aging: Individual risk factors, mechanisms, patient priorities, and outcomes. J Am Geriatr Soc 2021; 69(3): 610-2.
[http://dx.doi.org/10.1111/jgs.17011] [PMID: 33462804]
[27]
Holtze S, Gorshkova E, Braude S, et al. Alternative animal models of aging research. Front Mol Biosci 2021; 8: 660959.
[http://dx.doi.org/10.3389/fmolb.2021.660959] [PMID: 34079817]
[28]
Mitchell SJ, Scheibye-Knudsen M, Longo DL, de Cabo R. Animal models of aging research: Implications for human aging and age-related diseases. Annu Rev Anim Biosci 2015; 3(1): 283-303.
[http://dx.doi.org/10.1146/annurev-animal-022114-110829] [PMID: 25689319]
[29]
Folch J, Busquets O, Ettcheto M, et al. Experimental models for aging and their potential for novel drug discovery. Curr Neuropharmacol 2018; 16(10): 1466-83.
[http://dx.doi.org/10.2174/1570159X15666170707155345] [PMID: 28685671]
[30]
Lidzbarsky G, Gutman D, Shekhidem HA, Sharvit L, Atzmon G. Genomic instabilities, cellular senescence, and aging: In vitro, in vivo and aging-like human syndromes. Front Med 2018; 5: 104.
[http://dx.doi.org/10.3389/fmed.2018.00104] [PMID: 29719834]
[31]
Zhang S, Li F, Zhou T, Wang G, Li Z. Caenorhabditis elegans as a useful model for studying aging mutations. Front Endocrinol 2020; 11: 554994.
[http://dx.doi.org/10.3389/fendo.2020.554994] [PMID: 33123086]
[32]
Piper MDW, Partridge L. Drosophila as a model for ageing. Biochim Biophys Acta Mol Basis Dis 2018; 1864(9): 2707-17.
[http://dx.doi.org/10.1016/j.bbadis.2017.09.016] [PMID: 28964875]
[33]
Gilbert MJH, Zerulla TC, Tierney KB. Zebrafish (Danio rerio) as a model for the study of aging and exercise: Physical ability and trainability decrease with age. Exp Gerontol 2014; 50: 106-13.
[http://dx.doi.org/10.1016/j.exger.2013.11.013] [PMID: 24316042]
[34]
Rocha A, Magalhães S, Nunes A. Cell culture studies: A promising approach to the metabolomic study of human aging. Curr Metabol Syst Biol 2021; 8(1): 1-26.
[http://dx.doi.org/10.2174/2666338408666210322113713]
[35]
Aged C57Bl/6J Mice for Research Studies. The Jackson Laboratory. In:
[36]
Brayton CF, Treuting PM, Ward JM. Pathobiology of aging mice and GEM: background strains and experimental design. Vet Pathol 2012; 49(1): 85-105.
[http://dx.doi.org/10.1177/0300985811430696] [PMID: 22215684]
[37]
Cristofalo VJ, Beck J, Allen RG, Smith JR. Cell senescence: An evaluation of replicative senescence in culture as a model for cell aging in situ. J Gerontol A Biol Sci Med Sci 2003; 58(9): B776-9.
[http://dx.doi.org/10.1093/gerona/58.9.B776] [PMID: 14528030]
[38]
Brunet A. Old and new models for the study of human ageing. Nat Rev Mol Cell Biol 2020; 21(9): 491-3.
[http://dx.doi.org/10.1038/s41580-020-0266-4] [PMID: 32572179]
[39]
Wang Y, Chen S, Yan Z, Pei M. A prospect of cell immortalization combined with matrix microenvironmental optimization strategy for tissue engineering and regeneration. Cell Biosci 2019; 9(1): 7.
[http://dx.doi.org/10.1186/s13578-018-0264-9] [PMID: 30627420]
[40]
Fleischer JG, Schulte R, Tsai HH, et al. Predicting age from the transcriptome of human dermal fibroblasts. Genome Biol 2018; 19(1): 221.
[http://dx.doi.org/10.1186/s13059-018-1599-6] [PMID: 30567591]
[41]
Phipps SMO, Berletch JB, Andrews LG, Tollefsbol TO. Aging cell culture: Methods and observations. Methods Mol Biol 2007; 371: 9-19.
[http://dx.doi.org/10.1007/978-1-59745-361-5_2] [PMID: 17634570]
[42]
Tigges J, Krutmann J, Fritsche E, et al. The hallmarks of fibroblast ageing. Mech Ageing Dev 2014; 138(1): 26-44.
[http://dx.doi.org/10.1016/j.mad.2014.03.004] [PMID: 24686308]
[43]
Lago JC, Puzzi MB. The effect of aging in primary human dermal fibroblasts. PLoS One 2019; 14(7): e0219165.
[http://dx.doi.org/10.1371/journal.pone.0219165] [PMID: 31269075]
[44]
Hu JL, Todhunter ME, LaBarge MA, Gartner ZJ. Opportunities for organoids as new models of aging. J Cell Biol 2018; 217(1): 39-50.
[http://dx.doi.org/10.1083/jcb.201709054] [PMID: 29263081]
[45]
Torrens-Mas M, Perelló-Reus C, Navas-Enamorado C, et al. Organoids: An emerging tool to study aging signature across human tissues. Modeling aging with patient-derived organoids. Int J Mol Sci 2021; 22(19): 10547.
[http://dx.doi.org/10.3390/ijms221910547] [PMID: 34638891]
[46]
Srivastava S. Emerging insights into the metabolic alterations in aging using metabolomics. Metabolites 2019; 9(12): 301.
[http://dx.doi.org/10.3390/metabo9120301] [PMID: 31847272]
[47]
Gomase V, Changbhale S, Patil S, Kale K. Metabolomics. Curr Drug Metab 2008; 9(1): 89-98.
[http://dx.doi.org/10.2174/138920008783331149] [PMID: 18220576]
[48]
Zhang X, Zhu X, Wang C, Zhang H, Cai Z. Non-targeted and targeted metabolomics approaches to diagnosing lung cancer and predicting patient prognosis. Oncotarget 2016; 7(39): 63437-48.
[http://dx.doi.org/10.18632/oncotarget.11521] [PMID: 27566571]
[49]
Roberts LD, Souza AL, Gerszten RE, Clish CB. Targeted metabolomics. Curr Protoc Mol Biol 2012; 98(1): 2.1-4.
[http://dx.doi.org/10.1002/0471142727.mb3002s98] [PMID: 22470063 ]
[50]
Rocha A, Magalhães S, Nunes A. Study aging by fibroblasts metabolome. Curr Mol Med 2021; 21(4): 300-17.
[http://dx.doi.org/10.2174/1566524020999200831120852] [PMID: 32867636]
[51]
Magalhães S, Almeida I, Martins F, et al. FTIR spectroscopy as a tool to study age-related changes in cardiac and skeletal muscle of female C57BL/6J mice. Molecules 2021; 26(21): 6410.
[http://dx.doi.org/10.3390/molecules26216410] [PMID: 34770818]
[52]
Petr MA, Alfaras I, Krawcyzk M, et al. A cross-sectional study of functional and metabolic changes during aging through the lifespan in male mice. eLife 2021; 10: e62952.
[http://dx.doi.org/10.7554/eLife.62952] [PMID: 33876723]
[53]
Zhou Q, Kerbl-Knapp J, Zhang F, et al. Metabolomic profiles of mouse tissues reveal an interplay between aging and energy metabolism. Metabolites 2021; 12(1): 17.
[http://dx.doi.org/10.3390/metabo12010017] [PMID: 35050139]
[54]
Houtkooper RH, Argmann C, Houten SM, et al. The metabolic footprint of aging in mice. Sci Rep 2011; 1(1): 134.
[http://dx.doi.org/10.1038/srep00134] [PMID: 22355651]
[55]
Ding J, Ji J, Rabow Z, et al. A metabolome atlas of the aging mouse brain. Nat Commun 2021; 12(1): 6021.
[http://dx.doi.org/10.1038/s41467-021-26310-y] [PMID: 34654818]
[56]
Varshavi D, Scott FH, Varshavi D, et al. Metabolic biomarkers of ageing in C57BL/6J wild-type and flavin-containing monooxygenase 5 (FMO5)-knockout mice. Front Mol Biosci 2018; 5: 28.
[http://dx.doi.org/10.3389/fmolb.2018.00028] [PMID: 29686991]
[57]
Adav SS, Wang Y. Metabolomics signatures of aging: Recent advances. Aging Dis 2021; 12(2): 646-61.
[http://dx.doi.org/10.14336/AD.2020.0909] [PMID: 33815888]
[58]
Wishart DS, Feunang YD, Marcu A, et al. HMDB 4.0: The human metabolome database for 2018. Nucleic Acids Res 2018; 46(D1): D608-17.
[http://dx.doi.org/10.1093/nar/gkx1089] [PMID: 29140435]
[59]
Johnson LC, Parker K, Aguirre BF, et al. The plasma metabolome as a predictor of biological aging in humans. Geroscience 2019; 41(6): 895-906.
[http://dx.doi.org/10.1007/s11357-019-00123-w] [PMID: 31707594]
[60]
Teruya T, Goga H, Yanagida M. Aging markers in human urine: A comprehensive, non‐targeted LC‐MS study. FASEB Bioadv 2020; 2(12): 720-33.
[http://dx.doi.org/10.1096/fba.2020-00047] [PMID: 33336159]
[61]
Nagpal R, Mainali R, Ahmadi S, et al. Gut microbiome and aging: Physiological and mechanistic insights. Nutr Healthy Aging 2018; 4(4): 267-85.
[http://dx.doi.org/10.3233/NHA-170030] [PMID: 29951588]
[62]
Maffei VJ, Kim S, Blanchard EIV, et al. Biological aging and the human gut microbiota. J Gerontol A Biol Sci Med Sci 2017; 72(11): 1474-82.
[http://dx.doi.org/10.1093/gerona/glx042] [PMID: 28444190]
[63]
Teruya T, Goga H, Yanagida M. Human age-declined saliva metabolic markers determined by LC–MS. Sci Rep 2021; 11(1): 18135.
[http://dx.doi.org/10.1038/s41598-021-97623-7] [PMID: 34518599]
[64]
Gey C, Seeger K. Metabolic changes during cellular senescence investigated by proton NMR-spectroscopy. Mech Ageing Dev 2013; 134(3-4): 130-8.
[http://dx.doi.org/10.1016/j.mad.2013.02.002] [PMID: 23416267]
[65]
Chan M, Yuan H, Soifer I, et al. Novel insights from a multiomics dissection of the Hayflick limit. eLife 2022; 11: e70283.
[http://dx.doi.org/10.7554/eLife.70283] [PMID: 35119359]
[66]
Zwerschke W, Mazurek S, Stöckl P, Hütter E, Eigenbrodt E, Jansen-Dürr P. Metabolic analysis of senescent human fibroblasts reveals a role for AMP in cellular senescence. Biochem J 2003; 376(2): 403-11.
[http://dx.doi.org/10.1042/bj20030816] [PMID: 12943534]
[67]
Yoon YS, Yoon DS, Lim IK, et al. Formation of elongated giant mitochondria in DFO-induced cellular senescence: Involvement of enhanced fusion process through modulation of Fis1. J Cell Physiol 2006; 209(2): 468-80.
[http://dx.doi.org/10.1002/jcp.20753] [PMID: 16883569]
[68]
James EL, Michalek RD, Pitiyage GN, et al. Senescent human fibroblasts show increased glycolysis and redox homeostasis with extracellular metabolomes that overlap with those of irreparable DNA damage, aging, and disease. J Proteome Res 2015; 14(4): 1854-71.
[http://dx.doi.org/10.1021/pr501221g] [PMID: 25690941]
[69]
Tatone C, Carbone MC, Falone S, et al. Age-dependent changes in the expression of superoxide dismutases and catalase are associated with ultrastructural modifications in human granulosa cells. Mol Hum Reprod 2006; 12(11): 655-60.
[http://dx.doi.org/10.1093/molehr/gal080] [PMID: 17005595]
[70]
González-Fernández R, Hernández J, Martín-Vasallo P, Puopolo M, Palumbo A, Ávila J. Expression levels of the oxidative stress response gene ALDH3A2 in granulosa-lutein cells are related to female age and infertility diagnosis. Reprod Sci 2016; 23(5): 604-9.
[http://dx.doi.org/10.1177/1933719115607996] [PMID: 26449735]
[71]
Delfarah A, Parrish S, Junge JA, et al. Inhibition of nucleotide synthesis promotes replicative senescence of human mammary epithelial cells. J Biol Chem 2019; 294(27): 10564-78.
[http://dx.doi.org/10.1074/jbc.RA118.005806] [PMID: 31138644]
[72]
Mai S, Klinkenberg M, Auburger G, Bereiter-Hahn J, Jendrach M. Decreased expression of Drp1 and Fis1 mediates mitochondrial elongation in senescent cells and enhances resistance to oxidative stress through PINK1. J Cell Sci 2010; 123(6): 917-26.
[http://dx.doi.org/10.1242/jcs.059246] [PMID: 20179104]
[73]
Marjańska M, Emir UE, Deelchand DK, Terpstra M. Faster metabolite 1H transverse relaxation in the elder human brain. PLoS One 2014; 9(3)
[http://dx.doi.org/10.1371/journal.pone.0077572] [PMID: 24098589]
[74]
Lind A, Boraxbekk CJ, Petersen ET, et al. Do glia provide the link between low‐grade systemic inflammation and normal cognitive ageing? A 1H magnetic resonance spectroscopy study at 7 tesla. J Neurochem 2021; 159(1): 185-96.
[http://dx.doi.org/10.1111/jnc.15456] [PMID: 34142382]
[75]
Shibata M, Lu T, Furuya T, et al. Regulation of intracellular accumulation of mutant Huntingtin by Beclin 1. J Biol Chem 2006; 281(20): 14474-85.
[http://dx.doi.org/10.1074/jbc.M600364200] [PMID: 16522639]
[76]
Driscoll I, Hamilton DA, Petropoulos H, et al. The aging hippocampus: Cognitive, biochemical and structural findings. Cereb Cortex 2003; 13(12): 1344-51.
[http://dx.doi.org/10.1093/cercor/bhg081] [PMID: 14615299]
[77]
Kaiser LG, Schuff N, Cashdollar N, Weiner MW. Age-related glutamate and glutamine concentration changes in normal human brain: 1H MR spectroscopy study at 4 T. Neurobiol Aging 2005; 26(5): 665-72.
[http://dx.doi.org/10.1016/j.neurobiolaging.2004.07.001] [PMID: 15708441]
[78]
McIntyre DJO, Charlton RA, Markus HS, Howe FA, Howe FA. Long and short echo time proton magnetic resonance spectroscopic imaging of the healthy aging brain. J Magn Reson Imaging 2007; 26(6): 1596-606.
[http://dx.doi.org/10.1002/jmri.21198] [PMID: 17968966]
[79]
Reyngoudt H, Claeys T, Vlerick L, et al. Age-related differences in metabolites in the posterior cingulate cortex and hippocampus of normal ageing brain: A 1H-MRS study. Eur J Radiol 2012; 81(3): e223-31.
[http://dx.doi.org/10.1016/j.ejrad.2011.01.106] [PMID: 21345628]
[80]
Gruber S, Pinker K, Riederer F, et al. Metabolic changes in the normal ageing brain: Consistent findings from short and long echo time proton spectroscopy. Eur J Radiol 2008; 68(2): 320-7.
[http://dx.doi.org/10.1016/j.ejrad.2007.08.038] [PMID: 17964104]
[81]
Schubert F, Gallinat J, Seifert F, Rinneberg H. Glutamate concentrations in human brain using single voxel proton magnetic resonance spectroscopy at 3 Tesla. Neuroimage 2004; 21(4): 1762-71.
[http://dx.doi.org/10.1016/j.neuroimage.2003.11.014] [PMID: 15050596]
[82]
Chang L, Jiang CS, Ernst T. Effects of age and sex on brain glutamate and other metabolites. Magn Reson Imaging 2009; 27(1): 142-5.
[http://dx.doi.org/10.1016/j.mri.2008.06.002] [PMID: 18687554]
[83]
Gao F, Edden RAE, Li M, Puts NAJ, Wang G, Liu C. Edited magnetic resonance spectroscopy detects an age-related decline in brain GABA levels. Neuroimage 2013; 78: pp. 75-82.
[http://dx.doi.org/10.1016/j.neuroimage.2013.04.012]
[84]
Čuperlović-Culf M, Barnett DA, Culf AS, Chute I. Cell culture metabolomics: Applications and future directions. Drug Discov Today 2010; 15(15-16): 610-21.
[http://dx.doi.org/10.1016/j.drudis.2010.06.012] [PMID: 20601091]
[85]
Nunes A, Lopes J, Silva R, Rosa IM, Henriques AG, Delgadillo I. FTIR spectroscopy - a potential tool to identify metabolic changes in dementia patients. Alzheimer’s &. Neurodegenerative Disease 2016; 2(2): 1-9.
[http://dx.doi.org/10.24966/AND-9608/100007]
[86]
Ellis DI, Goodacre R. Metabolic fingerprinting in disease diagnosis: Biomedical applications of infrared and Raman spectroscopy. Analyst (Lond) 2006; 131(8): 875-85.
[http://dx.doi.org/10.1039/b602376m] [PMID: 17028718]
[87]
Magalhães S, Goodfellow BJ, Nunes A. FTIR spectroscopy in biomedical research: How to get the most out of its potential. Appl Spectrosc Rev 2021; 56(8-10): 869-907.
[http://dx.doi.org/10.1080/05704928.2021.1946822]
[88]
Richer BC, Salei N, Laskay T, Seeger K. Changes in neutrophil metabolism upon activation and aging. Inflammation 2018; 41(2): 710-21.
[http://dx.doi.org/10.1007/s10753-017-0725-z] [PMID: 29322364]
[89]
Magalhães S, Almeida I, Pereira CD, Rebelo S, Goodfellow BJ, Nunes A. The long-term culture of human fibroblasts reveals a spectroscopic signature of senescence. Int J Mol Sci 2022; 23(10): 5830.
[http://dx.doi.org/10.3390/ijms23105830] [PMID: 35628639]
[90]
Chaleckis R, Murakami I, Takada J, Kondoh H, Yanagida M. Individual variability in human blood metabolites identifies age-related differences. Proc Natl Acad Sci 2016; 113(16): 4252-9.
[http://dx.doi.org/10.1073/pnas.1603023113] [PMID: 27036001]
[91]
Zoia CP, Tagliabue E, Isella V, et al. Fibroblast glutamate transport in aging and in AD: correlations with disease severity. Neurobiol Aging 2005; 26(6): 825-32.
[http://dx.doi.org/10.1016/j.neurobiolaging.2004.07.007] [PMID: 15718040]
[92]
Canfield CA, Bradshaw PC. Amino acids in the regulation of aging and aging-related diseases. Transl Med Aging 2019; 3: 70-89.
[http://dx.doi.org/10.1016/j.tma.2019.09.001]
[93]
Borack MS, Volpi E. Efficacy and safety of leucine supplementation in the elderly. J Nutr 2016; 146(12): S2625-9.
[http://dx.doi.org/10.3945/jn.116.230771] [PMID: 27934654]
[94]
Eberhardt K, Matthäus C, Marthandan S, Diekmann S, Popp J. Raman and infrared spectroscopy reveal that proliferating and quiescent human fibroblast cells age by biochemically similar but not identical processes. PLoS One 2018; 13(12): e0207380.
[http://dx.doi.org/10.1371/journal.pone.0207380] [PMID: 30507927]
[95]
Eberhardt K, Beleites C, Marthandan S, Matthäus C, Diekmann S, Popp J. Raman and infrared spectroscopy distinguishing replicative senescent from proliferating primary human fibroblast cells by detecting spectral differences mainly due to biomolecular alterations. Anal Chem 2017; 89(5): 2937-47.
[http://dx.doi.org/10.1021/acs.analchem.6b04264] [PMID: 28192961]
[96]
Windler C, Gey C, Seeger K. Skin melanocytes and fibroblasts show different changes in choline metabolism during cellular senescence. Mech Ageing Dev 2017; 164: 82-90.
[http://dx.doi.org/10.1016/j.mad.2017.05.001] [PMID: 28476532]
[97]
James EL, Lane JAE, Michalek RD, Karoly ED, Parkinson EK. Replicatively senescent human fibroblasts reveal a distinct intracellular metabolic profile with alterations in NAD+ and nicotinamide metabolism. Sci Rep 2016; 6(1): 38489.
[http://dx.doi.org/10.1038/srep38489] [PMID: 27924925]
[98]
Pucciarelli S, Moreschini B, Micozzi D, et al. Spermidine and spermine are enriched in whole blood of nona/centenarians. Rejuvenation Res 2012; 15(6): 590-5.
[http://dx.doi.org/10.1089/rej.2012.1349] [PMID: 22950434]
[99]
Almeida I, Magalhães S, Nunes A. Lipids: biomarkers of healthy aging. Biogerontology 2021; 22(3): 273-95.
[http://dx.doi.org/10.1007/s10522-021-09921-2] [PMID: 33837874]
[100]
Gonzalez-Covarrubias V. Lipidomics in longevity and healthy aging. Biogerontology 2013; 14(6): 663-72.
[http://dx.doi.org/10.1007/s10522-013-9450-7] [PMID: 23948799]
[101]
da Silva IDCG, Marchioni DML, Carioca AAF, Bueno V, Colleoni GWB. May critical molecular cross-talk between indoleamine 2,3-dioxygenase (IDO) and arginase during human aging be targets for immunosenescence control? Immun Ageing 2021; 18(1): 33.
[http://dx.doi.org/10.1186/s12979-021-00244-x] [PMID: 34389039]
[102]
Bogner-Strauss JG, Weindl D, Zentrum H, Germany M, Ende G, Bogner-Strauss JG. N-Acetylaspartate metabolism outside the brain: Lipogenesis, histone acetylation, and cancer. Front Endocrinol 2017; 8: 240.
[http://dx.doi.org/10.3389/fendo.2017.00240] [PMID: 28979238]
[103]
Kirov II, Fleysher L, Fleysher R, Patil V, Liu S, Gonen O. Age dependence of regional proton metabolites T2 relaxation times in the human brain at 3 T. Magn Reson Med 2008; 60(4): 790-5.
[http://dx.doi.org/10.1002/mrm.21715] [PMID: 18816831]
[104]
Gasiorowska A, Wydrych M, Drapich P, et al. The biology and pathobiology of glutamatergic, cholinergic, and dopaminergic signaling in the aging brain. Front Aging Neurosci 2021; 13: 654931.
[http://dx.doi.org/10.3389/fnagi.2021.654931] [PMID: 34326765]
[105]
Nakazaki E, Mah E, Sanoshy K, Citrolo D, Watanabe F. Citicoline and memory function in healthy older adults: a randomized, double-blind, placebo-controlled clinical trial. J Nutr 2021; 151(8): 2153-60.
[http://dx.doi.org/10.1093/jn/nxab119] [PMID: 33978188]
[106]
Wang CH, Wu SB, Wu YT, Wei YH. Oxidative stress response elicited by mitochondrial dysfunction: Implication in the pathophysiology of aging. Exp Biol Med 2013; 238(5): 450-60.
[http://dx.doi.org/10.1177/1535370213493069] [PMID: 23856898]
[107]
Pain S, Dezutter C, Reymermier C, Vogelgesang B, Delay E, André V. Age-related changes in pro-opiomelanocortin (POMC) and related receptors in human epidermis. Int J Cosmet Sci 2010; 32(4): 266-75.
[http://dx.doi.org/10.1111/j.1468-2494.2009.00569.x] [PMID: 20384899]
[108]
Bocheva G, Slominski RM, Janjetovic Z, et al. Protective role of melatonin and its metabolites in skin aging. Int J Mol Sci 2022; 23(3): 1238.
[http://dx.doi.org/10.3390/ijms23031238] [PMID: 35163162]
[109]
Ávila J, González-Fernández R, Rotoli D, Hernández J, Palumbo A. Oxidative stress in granulosa-lutein cells from in vitro fertilization patients. Reprod Sci 2016; 23(12): 1656-61.
[http://dx.doi.org/10.1177/1933719116674077] [PMID: 27821562]
[110]
Kozakiewicz M, Kornatowski M, Krzywińska O, Kędziora-Kornatowska K. Changes in the blood antioxidant defense of advanced age people. Clin Interv Aging 2019; 14: 763-71.
[http://dx.doi.org/10.2147/CIA.S201250] [PMID: 31118597]
[111]
Ouda L, Profant O, Syka J. Age-related changes in the central auditory system. Cell Tissue Res 2015; 361(1): 337-58.
[http://dx.doi.org/10.1007/s00441-014-2107-2] [PMID: 25630878]
[112]
Ke Y, Li D, Zhao M, et al. Gut flora-dependent metabolite Trimethylamine-N-oxide accelerates endothelial cell senescence and vascular aging through oxidative stress. Free Radic Biol Med 2018; 116: 88-100.
[http://dx.doi.org/10.1016/j.freeradbiomed.2018.01.007] [PMID: 29325896]
[113]
Tan JK, Jaafar F, Makpol S. Proteomic profiling of senescent human diploid fibroblasts treated with gamma-tocotrienol. BMC Complement Altern Med 2018; 18(1): 314.
[http://dx.doi.org/10.1186/s12906-018-2383-6] [PMID: 30497457]
[114]
Waldera-Lupa DM, Kalfalah F, Florea AM, et al. Proteome-wide analysis reveals an age-associated cellular phenotype of in situ aged human fibroblasts. Aging 2014; 6(10): 856-72.
[http://dx.doi.org/10.18632/aging.100698] [PMID: 25411231]
[115]
Boraldi F, Bini L, Liberatori S, et al. Proteome analysis of dermal fibroblasts cultured in vitro from human healthy subjects of different ages. Proteomics 2003; 3(6): 917-29.
[http://dx.doi.org/10.1002/pmic.200300386] [PMID: 12833515]
[116]
Wang AS, Dreesen O. Biomarkers of cellular senescence and skin aging. Front Genet 2018; 9: 247.
[http://dx.doi.org/10.3389/fgene.2018.00247] [PMID: 30190724]
[117]
Dechat T, Pfleghaar K, Sengupta K, et al. Nuclear lamins: major factors in the structural organization and function of the nucleus and chromatin. Genes Dev 2008; 22(7): 832-53.
[http://dx.doi.org/10.1101/gad.1652708] [PMID: 18381888]
[118]
Scaffidi P, Misteli T. Lamin A-dependent nuclear defects in human aging. Science 2006; 312(5776): 1059-63.
[http://dx.doi.org/10.1126/science.1127168] [PMID: 16645051]
[119]
Pereira CD, Serrano JB, Martins F. da Cruz e Silva OAB, Rebelo S. Nuclear envelope dynamics during mammalian spermatogenesis: new insights on male fertility. Biol Rev Camb Philos Soc 2019; 94(4): 1195-219.
[http://dx.doi.org/10.1111/brv.12498] [PMID: 30701647]
[120]
Martins F, Sousa J, Pereira CD, Cruz e Silva OAB, Rebelo S. Nuclear envelope dysfunction and its contribution to the aging process. Aging Cell 2020; 19(5): e13143.
[http://dx.doi.org/10.1111/acel.13143] [PMID: 32291910]
[121]
Freund A, Laberge RM, Demaria M, Campisi J. Lamin B1 loss is a senescence-associated biomarker. Mol Biol Cell 2012; 23(11): 2066-75.
[http://dx.doi.org/10.1091/mbc.e11-10-0884] [PMID: 22496421]
[122]
Dreesen O, Ong PF, Chojnowski A, Colman A. The contrasting roles of lamin B1 in cellular aging and human disease. Nucleus 2013; 4(4): 283-90.
[http://dx.doi.org/10.4161/nucl.25808] [PMID: 23873483]
[123]
Dreesen O, Chojnowski A, Ong PF, et al. Lamin B1 fluctuations have differential effects on cellular proliferation and senescence. J Cell Biol 2013; 200(5): 605-17.
[http://dx.doi.org/10.1083/jcb.201206121] [PMID: 23439683]
[124]
Shimi T, Butin-Israeli V, Adam SA, et al. The role of nuclear lamin B1 in cell proliferation and senescence. Genes Dev 2011; 25(24): 2579-93.
[http://dx.doi.org/10.1101/gad.179515.111] [PMID: 22155925]
[125]
Shah PP, Donahue G, Otte GL, et al. Lamin B1 depletion in senescent cells triggers large-scale changes in gene expression and the chromatin landscape. Genes Dev 2013; 27(16): 1787-99.
[http://dx.doi.org/10.1101/gad.223834.113] [PMID: 23934658]
[126]
Kristiani L, Kim M, Kim Y. Role of the nuclear lamina in age-associated nuclear reorganization and inflammation. Cells 2020; 9(3): 718.
[http://dx.doi.org/10.3390/cells9030718] [PMID: 32183360]
[127]
Wang AS, Ong PF, Chojnowski A, Clavel C, Dreesen O. Loss of lamin B1 is a biomarker to quantify cellular senescence in photoaged skin. Sci Rep 2017; 7(1): 15678.
[http://dx.doi.org/10.1038/s41598-017-15901-9] [PMID: 29142250]
[128]
González-Gualda E, Baker AG, Fruk L, Muñoz-Espín D. A guide to assessing cellular senescence in vitro and in vivo. FEBS J 2021; 288(1): 56-80.
[http://dx.doi.org/10.1111/febs.15570] [PMID: 32961620]
[129]
Aird KM, Zhang R. Detection of senescence-associated heterochromatin foci (SAHF). Methods Mol Biol 2013; 965: 185-96.
[http://dx.doi.org/10.1007/978-1-62703-239-1_12] [PMID: 23296659]
[130]
Sharpless NE, Sherr CJ. Forging a signature of in vivo senescence. Nat Rev Cancer 2015; 15(7): 397-408.
[http://dx.doi.org/10.1038/nrc3960] [PMID: 26105537]
[131]
Debacq-Chainiaux F, Erusalimsky JD, Campisi J, Toussaint O. Protocols to detect senescence-associated beta-galactosidase (SA-βgal) activity, a biomarker of senescent cells in culture and in vivo. Nat Protoc 2009; 4(12): 1798-806.
[http://dx.doi.org/10.1038/nprot.2009.191] [PMID: 20010931]
[132]
Kohli J, Wang B, Brandenburg SM, et al. Algorithmic assessment of cellular senescence in experimental and clinical specimens. Nat Protoc 2021; 16(5): 2471-98.
[http://dx.doi.org/10.1038/s41596-021-00505-5] [PMID: 33911261]
[133]
Liu JY, Souroullas GP, Diekman BO, et al. Cells exhibiting strong p16INK4a promoter activation in vivo display features of senescence. Proc Natl Acad Sci 2019; 116(7): 2603-11.
[http://dx.doi.org/10.1073/pnas.1818313116] [PMID: 30683717]
[134]
Yang N, Hu M. The limitations and validities of senescence associated-β-galactosidase activity as an aging marker for human foreskin fibroblast Hs68 cells. Exp Gerontol 2005; 40(10): 813-9.
[http://dx.doi.org/10.1016/j.exger.2005.07.011] [PMID: 16154306]
[135]
Salmonowicz H, Passos JF. Detecting senescence: A new method for an old pigment. Aging Cell 2017; 16(3): 432-4.
[http://dx.doi.org/10.1111/acel.12580] [PMID: 28185406]
[136]
von Zglinicki T, Nilsson E, Döcke WD, Brunk UT. Lipofuscin accumulation and ageing of fibroblasts. Gerontology 1995; 41(2): 95-108.
[http://dx.doi.org/10.1159/000213728] [PMID: 8821324]
[137]
Kumari R, Jat P. Mechanisms of cellular senescence: Cell cycle arrest and senescence associated secretory phenotype. Front Cell Dev Biol 2021; 9: 645593.
[http://dx.doi.org/10.3389/fcell.2021.645593] [PMID: 33855023]

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