1932

Abstract

The process of aging manifests from a highly interconnected network of biological cascades resulting in the degradation and breakdown of every living organism over time. This natural development increases risk for numerous diseases and can be debilitating. Academic and industrial investigators have long sought to impede, or potentially reverse, aging in the hopes of alleviating clinical burden, restoring functionality, and promoting longevity. Despite widespread investigation, identifying impactful therapeutics has been hindered by narrow experimental validation and the lack of rigorous study design. In this review, we explore the current understanding of the biological mechanisms of aging and how this understanding both informs and limits interpreting data from experimental models based on these mechanisms. We also discuss select therapeutic strategies that have yielded promising data in these model systems with potential clinical translation. Lastly, we propose a unifying approach needed to rigorously vet current and future therapeutics and guide evaluation toward efficacious therapies.

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2023-06-08
2024-12-03
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Literature Cited

  1. 1.
    Guyuron B, Rowe DJ, Weinfeld AB, Eshraghi Y, Fathi A et al. 2009. Factors contributing to the facial aging of identical twins. Plastic Reconstr. Surg. 123:41321–31
    [Google Scholar]
  2. 2.
    Min K-J, Lee C-K, Park H-N. 2012. The lifespan of Korean eunuchs. Curr. Biol. 22:18R792–93
    [Google Scholar]
  3. 3.
    Bunning BJ, Contrepois K, Lee-McMullen B, Dhondalay GKR, Zhang W et al. 2020. Global metabolic profiling to model biological processes of aging in twins. Aging Cell 19:1e13073
    [Google Scholar]
  4. 4.
    Tan Q, Christiansen L, Thomassen M, Kruse TA, Christensen K. 2013. Twins for epigenetic studies of human aging and development. Ageing Res. Rev. 12:1182–87
    [Google Scholar]
  5. 5.
    López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. 2013. The hallmarks of aging. Cell 153:61194–217
    [Google Scholar]
  6. 6.
    Moskalev AA, Shaposhnikov MV, Plyusnina EN, Zhavoronkov A, Budovsky A et al. 2013. The role of DNA damage and repair in aging through the prism of Koch-like criteria. Ageing Res. Rev. 12:2661–84
    [Google Scholar]
  7. 7.
    Lebel M, Leder P. 1998. A deletion within the murine Werner syndrome helicase induces sensitivity to inhibitors of topoisomerase and loss of cellular proliferative capacity. PNAS 95:2213097–102
    [Google Scholar]
  8. 8.
    Wang L, Ogburn CE, Ware CB, Ladiges WC, Youssoufian H et al. 2000. Cellular Werner phenotypes in mice expressing a putative dominant-negative human WRN gene. Genetics 154:1357–62
    [Google Scholar]
  9. 9.
    Pendás AM, Zhou Z, Cadiñanos J, Freije JM, Wang J et al. 2002. Defective prelamin A processing and muscular and adipocyte alterations in Zmpste24 metalloproteinase–deficient mice. Nat. Genet. 31:194–99
    [Google Scholar]
  10. 10.
    Kudlow BA, Kennedy BK, Monnat RJ. 2007. Werner and Hutchinson–Gilford progeria syndromes: mechanistic basis of human progeroid diseases. Nat. Rev. Mol. Cell Biol. 8:5394–404
    [Google Scholar]
  11. 11.
    Hayflick L, Moorhead PS. 1961. The serial cultivation of human diploid cell strains. Exp. Cell Res. 25:3585–621
    [Google Scholar]
  12. 12.
    Kirkland J, Tchkonia T. 2020. Senolytic drugs: from discovery to translation. J. Intern. Med. 288:5518–36
    [Google Scholar]
  13. 13.
    Baker DJ, Wijshake T, Tchkonia T, LeBrasseur NK, Childs BG et al. 2011. Clearance of p16Ink4a-positive senescent cells delays ageing-associated disorders. Nature 479:7372232–36
    [Google Scholar]
  14. 14.
    Ellison-Hughes GM. 2020. First evidence that senolytics are effective at decreasing senescent cells in humans. EBioMedicine 56:102473
    [Google Scholar]
  15. 15.
    Thoppil H, Riabowol K. 2020. Senolytics: a translational bridge between cellular senescence and organismal aging. Front. Cell Dev. Biol. 7:367
    [Google Scholar]
  16. 16.
    Amor C, Feucht J, Leibold J, Ho Y-J, Zhu C et al. 2020. Senolytic CAR T cells reverse senescence-associated pathologies. Nature 583:7814127–32
    [Google Scholar]
  17. 17.
    Sayed N, Huang Y, Nguyen K, Krejciova-Rajaniemi Z, Grawe AP et al. 2021. An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging. Nat. Aging 1:7598–615
    [Google Scholar]
  18. 18.
    Chien Y, Scuoppo C, Wang X, Fang X, Balgley B et al. 2011. Control of the senescence-associated secretory phenotype by NF-κB promotes senescence and enhances chemosensitivity. Genes Dev. 25:202125–36
    [Google Scholar]
  19. 19.
    Watanabe S, Kawamoto S, Ohtani N, Hara E. 2017. Impact of senescence-associated secretory phenotype and its potential as a therapeutic target for senescence-associated diseases. Cancer Sci. 108:4563–69
    [Google Scholar]
  20. 20.
    Lopes-Paciencia S, Saint-Germain E, Rowell M-C, Ruiz AF, Kalegari P et al. 2019. The senescence-associated secretory phenotype and its regulation. Cytokine 117:15–22
    [Google Scholar]
  21. 21.
    Kumari R, Jat P. 2021. Mechanisms of cellular senescence: cell cycle arrest and senescence associated secretory phenotype. Front. Cell Dev. Biol. 9:485
    [Google Scholar]
  22. 22.
    Krtolica A, Parrinello S, Lockett S, Desprez P-Y, Campisi J. 2001. Senescent fibroblasts promote epithelial cell growth and tumorigenesis: a link between cancer and aging. PNAS 98:2112072–77
    [Google Scholar]
  23. 23.
    Harley CB, Futcher AB, Greider CW. 1990. Telomeres shorten during ageing of human fibroblasts. Nature 345:6274458–60
    [Google Scholar]
  24. 24.
    Coppé J-P, Desprez P-Y, Krtolica A, Campisi J. 2010. The senescence-associated secretory phenotype: the dark side of tumor suppression. Annu. Rev. Pathol. Mech. Dis. 5:99–118
    [Google Scholar]
  25. 25.
    Ewald CY, Hourihan JM, Bland MS, Obieglo C, Katic I et al. 2017. NADPH oxidase–mediated redox signaling promotes oxidative stress resistance and longevity through memo-1 in C. elegans. eLife 6:e19493
    [Google Scholar]
  26. 26.
    Sirokmány G, Donkó Á, Geiszt M. 2016. Nox/Duox family of NADPH oxidases: lessons from knockout mouse models. Trends Pharmacol. Sci. 37:4318–27
    [Google Scholar]
  27. 27.
    Liguori I, Russo G, Curcio F, Bulli G, Aran L et al. 2018. Oxidative stress, aging, and diseases. Clin. Intervent. Aging 13:757
    [Google Scholar]
  28. 28.
    Junqueira VB, Barros SB, Chan SS, Rodrigues L, Giavarotti L et al. 2004. Aging and oxidative stress. Mol. Aspects Med. 25:1–25–16
    [Google Scholar]
  29. 29.
    Sastre J, Pallardó FV, Viña J. 2003. The role of mitochondrial oxidative stress in aging. Free Radic. Biol. Med. 35:11–8
    [Google Scholar]
  30. 30.
    Dai D-F, Chiao YA, Marcinek DJ, Szeto HH, Rabinovitch PS. 2014. Mitochondrial oxidative stress in aging and healthspan. Longevity Healthspan 3:6
    [Google Scholar]
  31. 31.
    Franceschi C, Capri M, Monti D, Giunta S, Olivieri F et al. 2007. Inflammaging and anti-inflammaging: a systemic perspective on aging and longevity emerged from studies in humans. Mech. Ageing Dev. 128:192–105
    [Google Scholar]
  32. 32.
    Franceschi C, Campisi J. 2014. Chronic inflammation (inflammaging) and its potential contribution to age-associated diseases. J. Gerontol. A 69:Suppl. 14–9
    [Google Scholar]
  33. 33.
    Minciullo PL, Catalano A, Mandraffino G, Casciaro M, Crucitti A et al. 2016. Inflammaging and anti-inflammaging: the role of cytokines in extreme longevity. Arch. Immunol. Ther. Exp. 64:2111–26
    [Google Scholar]
  34. 34.
    Landau M. 2007. Exogenous factors in skin aging. Environ. Factors Skin Dis. 35:1–13
    [Google Scholar]
  35. 35.
    Sohal RS, Mockett RJ, Orr WC. 2002. Mechanisms of aging: an appraisal of the oxidative stress hypothesis. Free Radic. Biol. Med. 33:5575–86
    [Google Scholar]
  36. 36.
    Barja G. 2002. Endogenous oxidative stress: relationship to aging, longevity and caloric restriction. Ageing Res. Rev. 1:3397–411
    [Google Scholar]
  37. 37.
    Heilbronn LK, De Jonge L, Frisard MI, DeLany JP, Larson-Meyer DE et al. 2006. Effect of 6-month calorie restriction on biomarkers of longevity, metabolic adaptation, and oxidative stress in overweight individuals: a randomized controlled trial. JAMA 295:131539–48
    [Google Scholar]
  38. 38.
    Redman LM, Smith SR, Burton JH, Martin CK, Il'yasova D et al. 2018. Metabolic slowing and reduced oxidative damage with sustained caloric restriction support the rate of living and oxidative damage theories of aging. Cell Metab. 27:4805–15.e4
    [Google Scholar]
  39. 39.
    Dai D-F, Santana LF, Vermulst M, Tomazela DM, Emond MJ et al. 2009. Overexpression of catalase targeted to mitochondria attenuates murine cardiac aging. Circulation 119:212789–97
    [Google Scholar]
  40. 40.
    Dai D-F, Rabinovitch PS, Ungvari Z. 2012. Mitochondria and cardiovascular aging. Circ. Res. 110:81109–24
    [Google Scholar]
  41. 41.
    Stadler K, Jenei V, von Bölcsházy G, Somogyi A, Jakus J. 2003. Increased nitric oxide levels as an early sign of premature aging in diabetes. Free Radic. Biol. Med. 35:101240–51
    [Google Scholar]
  42. 42.
    Kang D, Hamasaki N. 2005. Alterations of mitochondrial DNA in common diseases and disease states: aging, neurodegeneration, heart failure, diabetes and cancer. Curr. Med. Chem. 12:4429–41
    [Google Scholar]
  43. 43.
    Ahima RS. 2009. Connecting obesity, aging and diabetes. Nat. Med. 15:9996–97
    [Google Scholar]
  44. 44.
    Monickaraj F, Aravind S, Gokulakrishnan K, Sathishkumar C, Prabu P et al. 2012. Accelerated aging as evidenced by increased telomere shortening and mitochondrial DNA depletion in patients with type 2 diabetes. Mol. Cell. Biochem. 365:1343–50
    [Google Scholar]
  45. 45.
    Newsholme P, Gaudel C, Krause M. 2012. Mitochondria and diabetes. An intriguing pathogenetic role. In Advances in Experimental Medicine and Biology, Vol. 942: Advances in Mitochondrial Medicineed. R Scatena, P Bottoni, B Giardinapp. 235–47 Springer, Dordrecht
    [Google Scholar]
  46. 46.
    Halim M, Halim A. 2019. The effects of inflammation, aging and oxidative stress on the pathogenesis of diabetes mellitus (type 2 diabetes). Diabetes Metab. Syndr. Clin. Res. Rev. 13:21165–72
    [Google Scholar]
  47. 47.
    Oh J, Lee YD, Wagers AJ. 2014. Stem cell aging: mechanisms, regulators and therapeutic opportunities. Nat. Med. 20:8870–80
    [Google Scholar]
  48. 48.
    Rübe CE, Fricke A, Widmann TA, Fürst T, Madry H et al. 2011. Accumulation of DNA damage in hematopoietic stem and progenitor cells during human aging. PLOS ONE 6:3e17487
    [Google Scholar]
  49. 49.
    Ergen AV, Goodell MA. 2010. Mechanisms of hematopoietic stem cell aging. Exp. Gerontol. 45:4286–90
    [Google Scholar]
  50. 50.
    Ren R, Ocampo A, Liu G-H, Belmonte JCI. 2017. Regulation of stem cell aging by metabolism and epigenetics. Cell Metab. 26:3460–74
    [Google Scholar]
  51. 51.
    Brack AS, Conboy MJ, Roy S, Lee M, Kuo CJ et al. 2007. Increased Wnt signaling during aging alters muscle stem cell fate and increases fibrosis. Science 317:5839807–10
    [Google Scholar]
  52. 52.
    Castilho RM, Squarize CH, Chodosh LA, Williams BO, Gutkind JS. 2009. mTOR mediates Wnt-induced epidermal stem cell exhaustion and aging. Cell Stem Cell 5:3279–89
    [Google Scholar]
  53. 53.
    Boyette LB, Tuan RS. 2014. Adult stem cells and diseases of aging. J. Clin. Med. 3:188–134
    [Google Scholar]
  54. 54.
    Mansilla E, Diaz Aquino V, Zambón D, Marin GH, Mártire K et al. 2011. Could metabolic syndrome, lipodystrophy, and aging be mesenchymal stem cell exhaustion syndromes?. Stem Cells Int 2011:943216
    [Google Scholar]
  55. 55.
    Ju Z, Jiang H, Jaworski M, Rathinam C, Gompf A et al. 2007. Telomere dysfunction induces environmental alterations limiting hematopoietic stem cell function and engraftment. Nat. Med. 13:6742–47
    [Google Scholar]
  56. 56.
    Wagner W, Horn P, Bork S, Ho AD. 2008. Aging of hematopoietic stem cells is regulated by the stem cell niche. Exp. Gerontol. 43:11974–80
    [Google Scholar]
  57. 57.
    Rossi DJ, Bryder D, Zahn JM, Ahlenius H, Sonu R et al. 2005. Cell intrinsic alterations underlie hematopoietic stem cell aging. PNAS 102:269194–99
    [Google Scholar]
  58. 58.
    Butler RN, Sprott R, Warner H, Bland J, Feuers R et al. 2004. Aging: the reality: biomarkers of aging: from primitive organisms to humans. J. Gerontol. A 59:6B560–67
    [Google Scholar]
  59. 59.
    Jylhävä J, Pedersen NL, Hägg S. 2017. Biological age predictors. EBioMedicine 21:29–36
    [Google Scholar]
  60. 60.
    Am. Fed. Aging Res 2016. Biomarkers of Aging: An Introduction to Aging Science Brought to You by the American Federation for Aging Research New York, NY: Am. Fed. Aging Res.
    [Google Scholar]
  61. 61.
    Blackburn EH, Greider CW, Szostak JW. 2006. Telomeres and telomerase: the path from maize, Tetrahymena and yeast to human cancer and aging. Nat. Med. 12:101133–38
    [Google Scholar]
  62. 62.
    Meyer DH, Schumacher B. 2021. BiT age: a transcriptome-based aging clock near the theoretical limit of accuracy. Aging Cell 20:3e13320
    [Google Scholar]
  63. 63.
    Horvath S. 2013. DNA methylation age of human tissues and cell types. Genome Biol. 14:3156
    [Google Scholar]
  64. 64.
    Hannum G, Guinney J, Zhao L, Zhang L, Hughes G et al. 2013. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol. Cell 49:2359–67
    [Google Scholar]
  65. 65.
    Johnson AA, Shokhirev MN, Lehallier B. 2021. The protein inputs of an ultra-predictive aging clock represent viable anti-aging drug targets. Ageing Res. Rev. 70:101404
    [Google Scholar]
  66. 66.
    McCrory C, Fiorito G, O'Halloran AM, Polidoro S, Vineis P et al. 2022. Early life adversity and age acceleration at mid-life and older ages indexed using the next-generation GrimAge and Pace of Aging epigenetic clocks. Psychoneuroendocrinology 137:105643
    [Google Scholar]
  67. 67.
    Xia X, Wang Y, Yu Z, Chen J, Han J-DJ. 2021. Assessing the rate of aging to monitor aging itself. Ageing Res. Rev. 69:101350
    [Google Scholar]
  68. 68.
    Galkin F, Mamoshina P, Kochetov K, Sidorenko D, Zhavoronkov A. 2021. DeepMAge: a methylation aging clock developed with deep learning. Aging Dis. 12:51252
    [Google Scholar]
  69. 69.
    Noroozi R, Ghafouri-Fard S, Pisarek A, Rudnicka J, Spólnicka M et al. 2021. DNA methylation–based age clocks: from age prediction to age reversion. Ageing Res. Rev. 68:101314
    [Google Scholar]
  70. 70.
    Earls JC, Rappaport N, Heath L, Wilmanski T, Magis AT et al. 2019. Multi-omic biological age estimation and its correlation with wellness and disease phenotypes: a longitudinal study of 3,558 individuals. J. Gerontol. A 74:Suppl. 152–60
    [Google Scholar]
  71. 71.
    Rahman SA, Adjeroh DA. 2019. Deep learning using convolutional LSTM estimates biological age from physical activity. Sci. Rep. 9:111425
    [Google Scholar]
  72. 72.
    Sanders JL, Newman AB. 2013. Telomere length in epidemiology: a biomarker of aging, age-related disease, both, or neither?. Epidemiol. Rev. 35:1112–31
    [Google Scholar]
  73. 73.
    Vaiserman A, Krasnienkov D. 2021. Telomere length as a marker of biological age: state-of-the-art, open issues, and future perspectives. Front. Genet. 11:1816
    [Google Scholar]
  74. 74.
    Lehallier B, Shokhirev MN, Wyss-Coray T, Johnson AA. 2020. Data mining of human plasma proteins generates a multitude of highly predictive aging clocks that reflect different aspects of aging. Aging Cell 19:11e13256
    [Google Scholar]
  75. 75.
    Baylis D, Bartlett DB, Patel HP, Roberts HC. 2013. Understanding how we age: insights into inflammaging. Longevity Healthspan 2:8
    [Google Scholar]
  76. 76.
    Franceschi C, Garagnani P, Parini P, Giuliani C, Santoro A. 2018. Inflammaging: a new immune–metabolic viewpoint for age-related diseases. Nat. Rev. Endocrinol. 14:10576–90
    [Google Scholar]
  77. 77.
    Varadhan R, Yao W, Matteini A, Beamer BA, Xue Q-l et al. 2014. Simple biologically informed inflammatory index of two serum cytokines predicts 10 year all-cause mortality in older adults. J. Gerontol. A 69:2165–73
    [Google Scholar]
  78. 78.
    Morrisette-Thomas V, Cohen AA, Fülöp T, Riesco É, Legault V et al. 2014. Inflamm-aging does not simply reflect increases in pro-inflammatory markers. Mech. Ageing Dev. 139:49–57
    [Google Scholar]
  79. 79.
    Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A et al. 2019. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging 11:2303
    [Google Scholar]
  80. 80.
    Belsky DW, Caspi A, Arseneault L, Baccarelli A, Corcoran DL et al. 2020. Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm. eLife 9:e54870
    [Google Scholar]
  81. 81.
    Zhang B, Trapp A, Kerepesi C, Gladyshev VN. 2022. Emerging rejuvenation strategies—reducing the biological age. Aging Cell 21:1e13538
    [Google Scholar]
  82. 82.
    Gialluisi A, Santoro A, Tirozzi A, Cerletti C, Donati MB et al. 2021. Epidemiological and genetic overlap among biological aging clocks: new challenges in biogerontology. Ageing Res. Rev. 72:101502
    [Google Scholar]
  83. 83.
    Soriano-Tárraga C, Giralt-Steinhauer E, Mola-Caminal M, Ois A, Rodríguez-Campello A et al. 2018. Biological age is a predictor of mortality in ischemic stroke. Sci. Rep. 8:14148
    [Google Scholar]
  84. 84.
    Cao X, Li W, Wang T, Ran D, Davalos V et al. 2022. Accelerated biological aging in COVID-19 patients. Nat. Commun. 13:2135
    [Google Scholar]
  85. 85.
    Shireby GL, Davies JP, Francis PT, Burrage J, Walker EM et al. 2020. Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex. Brain 143:123763–75
    [Google Scholar]
  86. 86.
    Bonab MM, Alimoghaddam K, Talebian F, Ghaffari SH, Ghavamzadeh A et al. 2006. Aging of mesenchymal stem cell in vitro. BMC Cell Biol. 7:114
    [Google Scholar]
  87. 87.
    Shay JW, Wright WE. 2000. Hayflick, his limit, and cellular ageing. Nat. Rev. Mol. Cell Biol. 1:172–76
    [Google Scholar]
  88. 88.
    Baxter MA, Wynn RF, Jowitt SN, Wraith JE, Fairbairn LJ et al. 2004. Study of telomere length reveals rapid aging of human marrow stromal cells following in vitro expansion. Stem Cells 22:5675–82
    [Google Scholar]
  89. 89.
    Liu H, Fergusson MM, Castilho RM, Liu J, Cao L et al. 2007. Augmented Wnt signaling in a mammalian model of accelerated aging. Science 317:5839803–6
    [Google Scholar]
  90. 90.
    Campos PB, Paulsen BS, Rehen SK. 2014. Accelerating neuronal aging in in vitro model brain disorders: a focus on reactive oxygen species. Front. Aging Neurosci. 6:292
    [Google Scholar]
  91. 91.
    Azman KF, Zakaria R. 2019. d-Galactose-induced accelerated aging model: an overview. Biogerontology 20:6763–82
    [Google Scholar]
  92. 92.
    Sejersen H, Rattan SI. 2009. Dicarbonyl-induced accelerated aging in vitro in human skin fibroblasts. Biogerontology 10:2203–11
    [Google Scholar]
  93. 93.
    Caldwell R, Street MG, Sharma R, Takmakov P, Baker B et al. 2020. Characterization of Parylene-C degradation mechanisms: in vitro reactive accelerated aging model compared to multiyear in vivo implantation. Biomaterials 232:119731
    [Google Scholar]
  94. 94.
    Cheng X, Yao H, Xiang Y, Chen L, Xiao M et al. 2019. Effect of Angelica polysaccharide on brain senescence of Nestin-GFP mice induced by d-galactose. Neurochem. Int. 122:149–56
    [Google Scholar]
  95. 95.
    Shen Y, Gao H, Shi X, Wang N, Ai D et al. 2014. Glutamine synthetase plays a role in d-galactose-induced astrocyte aging in vitro and in vivo. Exp. Gerontol. 58:166–73
    [Google Scholar]
  96. 96.
    Golden TR, Hinerfeld DA, Melov S. 2002. Oxidative stress and aging: beyond correlation. Aging Cell 1:2117–23
    [Google Scholar]
  97. 97.
    Soria-Valles C, López-Otín C. 2016. iPSCs: on the road to reprogramming aging. Trends Mol. Med. 22:8713–24
    [Google Scholar]
  98. 98.
    Baker DJ, Dawlaty MM, Wijshake T, Jeganathan KB, Malureanu L et al. 2013. Increased expression of BubR1 protects against aneuploidy and cancer and extends healthy lifespan. Nat. Cell Biol. 15:196–102
    [Google Scholar]
  99. 99.
    Sullivan T, Escalante-Alcalde D, Bhatt H, Anver M, Bhat N et al. 1999. Loss of A-type lamin expression compromises nuclear envelope integrity leading to muscular dystrophy. J. Cell Biol. 147:5913–20
    [Google Scholar]
  100. 100.
    Nikolova V, Leimena C, McMahon AC, Tan JC, Chandar S et al. 2004. Defects in nuclear structure and function promote dilated cardiomyopathy in lamin A/C–deficient mice. J. Clin. Investig. 113:3357–69
    [Google Scholar]
  101. 101.
    Conboy MJ, Conboy IM, Rando TA. 2013. Heterochronic parabiosis: historical perspective and methodological considerations for studies of aging and longevity. Aging Cell 12:3525–30
    [Google Scholar]
  102. 102.
    Conboy IM, Conboy MJ, Wagers AJ, Girma ER, Weissman IL et al. 2005. Rejuvenation of aged progenitor cells by exposure to a young systemic environment. Nature 433:7027760–64
    [Google Scholar]
  103. 103.
    Carlson ME, Hsu M, Conboy IM. 2008. Imbalance between pSmad3 and Notch induces CDK inhibitors in old muscle stem cells. Nature 454:7203528–32
    [Google Scholar]
  104. 104.
    Sinha M, Jang YC, Oh J, Khong D, Wu EY et al. 2014. Restoring systemic GDF11 levels reverses age-related dysfunction in mouse skeletal muscle. Science 344:6184649–52
    [Google Scholar]
  105. 105.
    Koellhoffer EC, Morales-Scheihing D, d'Aigle J, McCullough LD. 2017. Heterochronic parabiosis reverses the epigenetic imbalance of the aged central nervous system. Stroke 48:Suppl. 1AWP122
    [Google Scholar]
  106. 106.
    Koellhoffer EC, d'Aigle J, Morales-Scheihing D, McCullough LD. 2019. Circulating peripheral factors induce age-related epigenetic changes in microglia which induces a primed phenotype. Stroke 50:Suppl. 1A23
    [Google Scholar]
  107. 107.
    Villeda SA, Plambeck KE, Middeldorp J, Castellano JM, Mosher KI et al. 2014. Young blood reverses age-related impairments in cognitive function and synaptic plasticity in mice. Nat. Med. 20:6659–63
    [Google Scholar]
  108. 108.
    Yousefzadeh MJ, Wilkinson JE, Hughes B, Gadela N, Ladiges WC et al. 2020. Heterochronic parabiosis regulates the extent of cellular senescence in multiple tissues. Geroscience 42:3951–61
    [Google Scholar]
  109. 109.
    Pálovics R, Keller A, Schaum N, Tan W, Fehlmann T et al. 2022. Molecular hallmarks of heterochronic parabiosis at single-cell resolution. Nature 603:7900309–14
    [Google Scholar]
  110. 110.
    Gonzalez-Armenta JL, Li N, Lee R-L, Lu B, Molina AJ. 2021. Heterochronic parabiosis: Old blood induces changes in mitochondrial structure and function of young mice. J. Gerontol. A 76:3434–39
    [Google Scholar]
  111. 111.
    Yang C, Liu Z-L, Wang J, Bu X-L, Wang Y-J et al. 2021. Parabiosis modeling: protocol, application and perspectives. Zool. Res. 42:3253
    [Google Scholar]
  112. 112.
    Dayoub JC, Cortese F, Anžič A, Grum T, de Magalhães JP 2018. The effects of donor age on organ transplants: a review and implications for aging research. Exp. Gerontol. 110:230–40
    [Google Scholar]
  113. 113.
    Rebo J, Mehdipour M, Gathwala R, Causey K, Liu Y et al. 2016. A single heterochronic blood exchange reveals rapid inhibition of multiple tissues by old blood. Nat. Commun. 7:13363
    [Google Scholar]
  114. 114.
    Liu L, Rando TA. 2011. Manifestations and mechanisms of stem cell aging. J. Cell Biol. 193:2257–66
    [Google Scholar]
  115. 115.
    De Magalhães JP, Stevens M, Thornton D. 2017. The business of anti-aging science. Trends Biotechnol. 35:111062–73
    [Google Scholar]
  116. 116.
    Anderson RM, Weindruch R. 2010. Metabolic reprogramming, caloric restriction and aging. Trends Endocrinol. Metab. 21:3134–41
    [Google Scholar]
  117. 117.
    Broughton S, Partridge L. 2009. Insulin/IGF-like signalling, the central nervous system and aging. Biochem. J. 418:11–12
    [Google Scholar]
  118. 118.
    Pawlikowska L, Hu D, Huntsman S, Sung A, Chu C et al. 2009. Association of common genetic variation in the insulin/IGF1 signaling pathway with human longevity. Aging Cell 8:4460–72
    [Google Scholar]
  119. 119.
    Kenyon C. 2005. The plasticity of aging: insights from long-lived mutants. Cell 120:4449–60
    [Google Scholar]
  120. 120.
    Bjedov I, Toivonen JM, Kerr F, Slack C, Jacobson J et al. 2010. Mechanisms of life span extension by rapamycin in the fruit fly Drosophila melanogaster. Cell Metab. 11:135–46
    [Google Scholar]
  121. 121.
    Andersen SL, Sebastiani P, Dworkis DA, Feldman L, Perls TT. 2012. Health span approximates life span among many supercentenarians: compression of morbidity at the approximate limit of life span. J. Gerontol. A 67:4395–405
    [Google Scholar]
  122. 122.
    Sebastiani P, Solovieff N, DeWan AT, Walsh KM, Puca A et al. 2012. Genetic signatures of exceptional longevity in humans. PLOS ONE 7:1e29848
    [Google Scholar]
  123. 123.
    Sebastiani P, Bae H, Sun FX, Andersen SL, Daw EW et al. 2013. Meta-analysis of genetic variants associated with human exceptional longevity. Aging 5:9653
    [Google Scholar]
  124. 124.
    Willcox BJ, Donlon TA, He Q, Chen R, Grove JS et al. 2008. FOXO3A genotype is strongly associated with human longevity. PNAS 105:3713987–92
    [Google Scholar]
  125. 125.
    Anselmi CV, Malovini A, Roncarati R, Novelli V, Villa F et al. 2009. Association of the FOXO3A locus with extreme longevity in a southern Italian centenarian study. Rejuvenation Res. 12:295–104
    [Google Scholar]
  126. 126.
    McCay CM, Crowell MF, Maynard LA. 1935. The effect of retarded growth upon the length of life span and upon the ultimate body size: one figure. J. Nutr. 10:163–79
    [Google Scholar]
  127. 127.
    Anderson RM, Weindruch R. 2012. The caloric restriction paradigm: implications for healthy human aging. Am. J. Hum. Biol. 24:2101–6
    [Google Scholar]
  128. 128.
    Miller KN, Burhans MS, Clark JP, Howell PR, Polewski MA et al. 2017. Aging and caloric restriction impact adipose tissue, adiponectin, and circulating lipids. Aging Cell 16:3497–507
    [Google Scholar]
  129. 129.
    Gensous N, Franceschi C, Santoro A, Milazzo M, Garagnani P et al. 2019. The impact of caloric restriction on the epigenetic signatures of aging. Int. J. Mol. Sci. 20:82022
    [Google Scholar]
  130. 130.
    Fontana L, Klein S. 2007. Aging, adiposity, and calorie restriction. JAMA 297:9986–94
    [Google Scholar]
  131. 131.
    Sohal RS, Forster MJ. 2014. Caloric restriction and the aging process: a critique. Free Radic. Biol. Med. 73:366–82
    [Google Scholar]
  132. 132.
    Ravussin E, Redman LM, Rochon J, Das SK, Fontana L et al. 2015. A 2-year randomized controlled trial of human caloric restriction: feasibility and effects on predictors of health span and longevity. J. Gerontol. A 70:91097–104
    [Google Scholar]
  133. 133.
    Caristia S, De Vito M, Sarro A, Leone A, Pecere A et al. 2020. Is caloric restriction associated with better healthy aging outcomes? A systematic review and meta-analysis of randomized controlled trials. Nutrients 12:82290
    [Google Scholar]
  134. 134.
    Flanagan EW, Most J, Mey JT, Redman LM. 2020. Calorie restriction and aging in humans. Annu. Rev. Nutr. 40:105–33
    [Google Scholar]
  135. 135.
    Anton S, Leeuwenburgh C. 2013. Fasting or caloric restriction for healthy aging. Exp. Gerontol. 48:101003–5
    [Google Scholar]
  136. 136.
    Lee C, Longo V. 2011. Fasting versus dietary restriction in cellular protection and cancer treatment: from model organisms to patients. Oncogene 30:303305–16
    [Google Scholar]
  137. 137.
    Pak HH, Haws SA, Green CL, Koller M, Lavarias MT et al. 2021. Fasting drives the metabolic, molecular and geroprotective effects of a calorie-restricted diet in mice. Nat. Metab. 3:101327–41
    [Google Scholar]
  138. 138.
    Sun J, Tower J. 1999. FLP recombinase–mediated induction of Cu/Zn–superoxide dismutase transgene expression can extend the life span of adult Drosophila melanogaster flies. Mol. Cell. Biol. 19:1216–28
    [Google Scholar]
  139. 139.
    Mockett RJ, Sohal RS, Orr WC. 1999. Overexpression of glutathione reductase extends survival in transgenic Drosophila melanogaster under hyperoxia but not normoxia. FASEB J. 13:131733–42
    [Google Scholar]
  140. 140.
    Parkes TL, Elia AJ, Dickinson D, Hilliker AJ, Phillips JP et al. 1998. Extension of Drosophila lifespan by overexpression of human SOD1 in motorneurons. Nat. Genet. 19:2171–74
    [Google Scholar]
  141. 141.
    Dröge W, Schipper HM. 2007. Oxidative stress and aberrant signaling in aging and cognitive decline. Aging Cell 6:3361–70
    [Google Scholar]
  142. 142.
    Ingram DK, Roth GS. 2015. Calorie restriction mimetics: Can you have your cake and eat it, too?. Ageing Res. Rev. 20:46–62
    [Google Scholar]
  143. 143.
    Zhang M, Wang P, Luo R, Wang Y, Li Z et al. 2021. Biomimetic human disease model of SARS-CoV-2-induced lung injury and immune responses on organ chip system. Adv. Sci. 8:32002928
    [Google Scholar]
  144. 144.
    Martel J, Chang S-H, Wu C-Y, Peng H-H, Hwang T-L et al. 2021. Recent advances in the field of caloric restriction mimetics and anti-aging molecules. Ageing Res. Rev. 66:101240
    [Google Scholar]
  145. 145.
    Fahy GM, Brooke RT, Watson JP, Good Z, Vasanawala SS et al. 2019. Reversal of epigenetic aging and immunosenescent trends in humans. Aging Cell 18:6e13028
    [Google Scholar]
  146. 146.
    Justice JN, Nambiar AM, Tchkonia T, LeBrasseur NK, Pascual R et al. 2019. Senolytics in idiopathic pulmonary fibrosis: results from a first-in-human, open-label, pilot study. EBioMedicine 40:554–63
    [Google Scholar]
  147. 147.
    Barzilai N, Crandall JP, Kritchevsky SB, Espeland MA. 2016. Metformin as a tool to target aging. Cell Metab. 23:61060–65
    [Google Scholar]
  148. 148.
    Mullard A. 2018. Anti-ageing pipeline starts to mature. Nat. Rev. Drug Discov. 17:9609–13
    [Google Scholar]
  149. 149.
    Kulkarni AS, Gubbi S, Barzilai N. 2020. Benefits of metformin in attenuating the hallmarks of aging. Cell Metab. 32:115–30
    [Google Scholar]
  150. 150.
    Dolgin E. 2020. Send in the senolytics. Nat. Biotechnol. 38:121371–78
    [Google Scholar]
  151. 151.
    Colman A. 2013. Profile of John Gurdon and Shinya Yamanaka, 2012 Nobel laureates in medicine or physiology. PNAS 110:155740–41
    [Google Scholar]
  152. 152.
    Alle Q, Le Borgne E, Milhavet O, Lemaitre J-M 2021. Reprogramming: emerging strategies to rejuvenate aging cells and tissues. Int. J. Mol. Sci. 22:83990
    [Google Scholar]
  153. 153.
    Mahmoudi S, Brunet A. 2012. Aging and reprogramming: a two-way street. Curr. Opin. Cell Biol. 24:6744–56
    [Google Scholar]
  154. 154.
    Ocampo A, Reddy P, Belmonte JCI. 2016. Anti-aging strategies based on cellular reprogramming. Trends Mol. Med. 22:8725–38
    [Google Scholar]
  155. 155.
    Topart C, Werner E, Arimondo PB. 2020. Wandering along the epigenetic timeline. Clin. Epigenet. 12:97
    [Google Scholar]
  156. 156.
    Mosteiro L, Pantoja C, Alcazar N, Marión RM, Chondronasiou D et al. 2016. Tissue damage and senescence provide critical signals for cellular reprogramming in vivo. Science 354:6315aaf4445
    [Google Scholar]
  157. 157.
    Rando TA, Chang HY. 2012. Aging, rejuvenation, and epigenetic reprogramming: resetting the aging clock. Cell 148:1–246–57
    [Google Scholar]
  158. 158.
    Abad M, Mosteiro L, Pantoja C, Cañamero M, Rayon T et al. 2013. Reprogramming in vivo produces teratomas and iPS cells with totipotency features. Nature 502:7471340–45
    [Google Scholar]
  159. 159.
    Ohnishi K, Semi K, Yamamoto T, Shimizu M, Tanaka A et al. 2014. Premature termination of reprogramming in vivo leads to cancer development through altered epigenetic regulation. Cell 156:4663–77
    [Google Scholar]
  160. 160.
    Chen Y, Lüttmann FF, Schoger E, Schöler HR, Zelarayán LC et al. 2021. Reversible reprogramming of cardiomyocytes to a fetal state drives heart regeneration in mice. Science 373:65621537–40
    [Google Scholar]
  161. 161.
    Ocampo A, Reddy P, Martinez-Redondo P, Platero-Luengo A, Hatanaka F et al. 2016. In vivo amelioration of age-associated hallmarks by partial reprogramming. Cell 167:71719–33.e12
    [Google Scholar]
  162. 162.
    Rodríguez-Matellán A, Alcazar N, Hernández F, Serrano M, Ávila J. 2020. In vivo reprogramming ameliorates aging features in dentate gyrus cells and improves memory in mice. Stem Cell Rep. 15:51056–66
    [Google Scholar]
  163. 163.
    Chondronasiou D, Gill D, Mosteiro L, Urdinguio RG, Berenguer-Llergo A et al. 2022. Multi-omic rejuvenation of naturally aged tissues by a single cycle of transient reprogramming. Aging Cell 21:3e13578
    [Google Scholar]
  164. 164.
    Lu Y, Brommer B, Tian X, Krishnan A, Meer M et al. 2020. Reprogramming to recover youthful epigenetic information and restore vision. Nature 588:7836124–29
    [Google Scholar]
  165. 165.
    Eisenstein M. 2022. Rejuvenation by controlled reprogramming is the latest gambit in anti-aging. Nat. Biotechnol. 40:144–46
    [Google Scholar]
  166. 166.
    De Magalhães JP, Ocampo A. 2022. Cellular reprogramming and the rise of rejuvenation biotech. Trends Biotechnol. 40:6639–42
    [Google Scholar]
  167. 167.
    Sarkar TJ, Quarta M, Mukherjee S, Colville A, Paine P et al. 2020. Transient non-integrative expression of nuclear reprogramming factors promotes multifaceted amelioration of aging in human cells. Nat. Commun. 11:1545
    [Google Scholar]
  168. 168.
    Ashapkin VV, Kutueva LI, Vanyushin BF. 2020. The effects of parabiosis on aging and age-related diseases. Adv. Exp. Med. Biol. 1260:107–22
    [Google Scholar]
  169. 169.
    Mahmoudi S, Xu L, Brunet A. 2019. Turning back time with emerging rejuvenation strategies. Nat. Cell Biol. 21:132–43
    [Google Scholar]
  170. 170.
    Mehdipour M, Skinner C, Wong N, Lieb M, Liu C et al. 2020. Rejuvenation of three germ layers tissues by exchanging old blood plasma with saline-albumin. Aging 12:108790
    [Google Scholar]
  171. 171.
    Katsimpardi L, Litterman NK, Schein PA, Miller CM, Loffredo FS et al. 2014. Vascular and neurogenic rejuvenation of the aging mouse brain by young systemic factors. Science 344:6184630–34
    [Google Scholar]
  172. 172.
    Lai T-P, Wright WE, Shay JW. 2018. Comparison of telomere length measurement methods. Philos. Trans. R. Soc. B 373:174120160451
    [Google Scholar]
  173. 173.
    Palano G, Foinquinos A, Müllers E. 2021. In vitro assays and imaging methods for drug discovery for cardiac fibrosis. Front. Physiol. 12:697270
    [Google Scholar]
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