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The brain–body energy conservation model of aging

Nature Aging (2024)Cite this article

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Abstract

Aging involves seemingly paradoxical changes in energy metabolism. Molecular damage accumulation increases cellular energy expenditure, yet whole-body energy expenditure remains stable or decreases with age. We resolve this apparent contradiction by positioning the brain as the mediator and broker in the organismal energy economy. As somatic tissues accumulate damage over time, costly intracellular stress responses are activated, causing aging or senescent cells to secrete cytokines that convey increased cellular energy demand (hypermetabolism) to the brain. To conserve energy in the face of a shrinking energy budget, the brain deploys energy conservation responses, which suppress low-priority processes, producing fatigue, physical inactivity, blunted sensory capacities, immune alterations and endocrine ‘deficits’. We term this cascade the brain–body energy conservation (BEC) model of aging. The BEC outlines (1) the energetic cost of cellular aging, (2) how brain perception of senescence-associated hypermetabolism may drive the phenotypic manifestations of aging and (3) energetic principles underlying the modifiability of aging trajectories by stressors and geroscience interventions.

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Fig. 1: Overview of the BEC model of aging.
Fig. 2: The BEC cascade.
Fig. 3: Accumulating molecular damage triggers stress responses, cellular senescence and systemic signals of hypermetabolism.
Fig. 4: Brain energy sensing and regulation of aging physiology.
Fig. 5: Target sites of action for protective geroscience interventions and stressors that accelerate phenotypic and functional aging.

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References

  1. Kleckner, I. R. et al. Evidence for a large-scale brain system supporting allostasis and interoception in humans. Nat. Hum. Behav. 1, 0069 (2017).

  2. McEwen, B. S. Physiology and neurobiology of stress and adaptation: central role of the brain. Physiol. Rev. 87, 873–904 (2007).

    Article  PubMed  Google Scholar 

  3. Doyle, J. C. & Csete, M. Architecture, constraints, and behavior. Proc. Natl Acad. Sci. USA 108, 15624–15630 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Finkel, T. The metabolic regulation of aging. Nat. Med. 21, 1416–1423 (2015).

    Article  CAS  PubMed  Google Scholar 

  5. Gonzalez, A., Hall, M. N., Lin, S. C. & Hardie, D. G. AMPK and TOR: the yin and yang of cellular nutrient sensing and growth control. Cell Metab. 31, 472–492 (2020).

    Article  CAS  PubMed  Google Scholar 

  6. Huynh, M. K., Kinyua, A. W., Yang, D. J. & Kim, K. W. Hypothalamic AMPK as a regulator of energy homeostasis. Neural Plast. 2016, 2754078 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Pontzer, H. & McGrosky, A. Balancing growth, reproduction, maintenance, and activity in evolved energy economies. Curr. Biol. 32, R709–R719 (2022).

    Article  CAS  PubMed  Google Scholar 

  8. Lopez-Otin, C., Galluzzi, L., Freije, J. M. P., Madeo, F. & Kroemer, G. Metabolic control of longevity. Cell 166, 802–821 (2016).

    Article  CAS  PubMed  Google Scholar 

  9. Moqri, M. et al. Biomarkers of aging for the identification and evaluation of longevity interventions. Cell 186, 3758–3775 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kaeberlein, M., Rabinovitch, P. S. & Martin, G. M. Healthy aging: the ultimate preventative medicine. Science 350, 1191–1193 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Lopez-Otin, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. Hallmarks of aging: an expanding universe. Cell 186, 243–278 (2023).

    Article  CAS  PubMed  Google Scholar 

  12. Wiley, C. D. & Campisi, J. The metabolic roots of senescence: mechanisms and opportunities for intervention. Nat. Metab. 3, 1290–1301 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Jang, J. Y., Blum, A., Liu, J. & Finkel, T. The role of mitochondria in aging. J. Clin. Invest. 128, 3662–3670 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Moldakozhayev, A. & Gladyshev, V. N. Metabolism, homeostasis, and aging. Trends Endocrinol. Metab. 34, 158–169 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Sturm, G. et al. Accelerating the clock: interconnected speedup of energetic and molecular dynamics during aging in cultured human cells. Preprint at bioRxiv https://doi.org/10.1101/2022.05.10.491392 (2022).

  16. Bobba-Alves, N., Juster, R. P. & Picard, M. The energetic cost of allostasis and allostatic load. Psychoneuroendocrinology 146, 105951 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Wordsworth, J., Nielsen, P. Y., Fielder, E., Chandrasegaran, S. & Shanley, D. Metabolic slowdown as the proximal cause of ageing and death. Preprint at bioRxiv https://doi.org/10.1101/2023.08.01.551537 (2023).

  18. Nelson, P. & Masel, J. Intercellular competition and the inevitability of multicellular aging. Proc. Natl Acad. Sci. USA 114, 12982–12987 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Levin, M. Bioelectric signaling: reprogrammable circuits underlying embryogenesis, regeneration, and cancer. Cell 184, 1971–1989 (2021).

    Article  CAS  PubMed  Google Scholar 

  20. Picard, M. & Shirihai, O. S. Mitochondrial signal transduction. Cell Metab. 34, 1620–1653 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Miller, H. A., Dean, E. S., Pletcher, S. D. & Leiser, S. F. Cell non-autonomous regulation of health and longevity. eLife 9, e62659 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fried, L. P. et al. The physical frailty syndrome as a transition from homeostatic symphony to cacophony. Nat. Aging 1, 36–46 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Cohen, A. A. et al. A complex systems approach to aging biology. Nat. Aging 2, 580–591 (2022).

    Article  PubMed  Google Scholar 

  24. Greene, J. A. & Loscalzo, J. Putting the patient back together — social medicine, network medicine, and the limits of reductionism. N. Engl. J. Med. 377, 2493–2499 (2017).

    Article  PubMed  Google Scholar 

  25. López-Otín, C. & Kroemer, G. Hallmarks of health. Cell 184, 33–63 (2021).

    Article  PubMed  Google Scholar 

  26. de Magalhaes, J. P. Cellular senescence in normal physiology. Science 384, 1300–1301 (2024).

    Article  PubMed  Google Scholar 

  27. Ferrucci, L., Levine, M. E., Kuo, P. L. & Simonsick, E. M. Time and the metrics of aging. Circ. Res. 123, 740–744 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Wang, A., Luan, H. H. & Medzhitov, R. An evolutionary perspective on immunometabolism. Science 363, eaar3932 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Gladyshev, V. N. et al. Molecular damage in aging. Nat. Aging 1, 1096–1106 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Rattan, S. I. S. Biogerontology: research status, challenges and opportunities. Acta Biomed. 89, 291–301 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Farrell, S., Kane, A. E., Bisset, E., Howlett, S. E. & Rutenberg, A. D. Measurements of damage and repair of binary health attributes in aging mice and humans reveal that robustness and resilience decrease with age, operate over broad timescales, and are affected differently by interventions. eLife 11, e77632 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Gladyshev, V. N. Aging: progressive decline in fitness due to the rising deleteriome adjusted by genetic, environmental, and stochastic processes. Aging Cell 15, 594–602 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Whittemore, K., Vera, E., Martinez-Nevado, E., Sanpera, C. & Blasco, M. A. Telomere shortening rate predicts species life span. Proc. Natl Acad. Sci. USA 116, 15122–15127 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Venteicher, A. S., Meng, Z., Mason, P. J., Veenstra, T. D. & Artandi, S. E. Identification of ATPases pontin and reptin as telomerase components essential for holoenzyme assembly. Cell 132, 945–957 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Cagan, A. et al. Somatic mutation rates scale with lifespan across mammals. Nature 604, 517–524 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Yousefzadeh, M. et al. DNA damage—how and why we age? eLife 10, e62852 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Zhang, R., Wang, Y., Ye, K., Picard, M. & Gu, Z. Independent impacts of aging on mitochondrial DNA quantity and quality in humans. BMC Genomics 18, 890 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Sanchez-Contreras, M. et al. The multi-tissue landscape of somatic mtDNA mutations indicates tissue-specific accumulation and removal in aging. eLife 12, e83395 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Vandiver, A. R. et al. Nanopore sequencing identifies a higher frequency and expanded spectrum of mitochondrial DNA deletion mutations in human aging. Aging Cell 22, e13842 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. De Cecco, M. et al. L1 drives IFN in senescent cells and promotes age-associated inflammation. Nature 566, 73–78 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Lynch, M. & Marinov, G. K. The bioenergetic costs of a gene. Proc. Natl Acad. Sci. USA 112, 15690–15695 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Bourque, G. et al. Ten things you should know about transposable elements. Genome Biol. 19, 199 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Gorbunova, V. et al. The role of retrotransposable elements in ageing and age-associated diseases. Nature 596, 43–53 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Gulen, M. F. et al. cGAS–STING drives ageing-related inflammation and neurodegeneration. Nature 620, 374–380 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Riley, J. S. & Tait, S. W. Mitochondrial DNA in inflammation and immunity. EMBO Rep. 21, e49799 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Vizioli, M. G. et al. Mitochondria-to-nucleus retrograde signaling drives formation of cytoplasmic chromatin and inflammation in senescence. Genes Dev. 34, 428–445 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Victorelli, S. et al. Apoptotic stress causes mtDNA release during senescence and drives the SASP. Nature 622, 627–636 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Miller, K. N. et al. Cytoplasmic DNA: sources, sensing, and role in aging and disease. Cell 184, 5506–5526 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Wei, W. et al. Nuclear-embedded mitochondrial DNA sequences in 66,083 human genomes. Nature 611, 105–114 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhou, W. et al. Somatic nuclear mitochondrial DNA insertions are prevalent in the human brain and accumulate over time in fibroblasts. PLoS Biol. 22, e3002723 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Haghani, A. et al. DNA methylation networks underlying mammalian traits. Science 381, eabq5693 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Yang, J. H. et al. Loss of epigenetic information as a cause of mammalian aging. Cell 186, 305–326 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Lee, J. Y. et al. Misexpression of genes lacking CpG islands drives degenerative changes during aging. Sci. Adv. 7, eabj9111 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Rangaraju, S. et al. Suppression of transcriptional drift extends C. elegans lifespan by postponing the onset of mortality. eLife 4, e08833 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Matsuoka, S. et al. ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage. Science 316, 1160–1166 (2007).

    Article  CAS  PubMed  Google Scholar 

  56. Dekker, C., Haering, C. H., Peters, J. M. & Rowland, B. D. How do molecular motors fold the genome? Science 382, 646–648 (2023).

    Article  CAS  PubMed  Google Scholar 

  57. Suganuma, T. & Workman, J. L. Chromatin and metabolism. Annu. Rev. Biochem. 87, 27–49 (2018).

    Article  CAS  PubMed  Google Scholar 

  58. Victorelli, S. & Passos, J. F. Telomeres: beacons of autocrine and paracrine DNA damage during skin aging. Cell Cycle 19, 532–540 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Schumacher, B., Pothof, J., Vijg, J. & Hoeijmakers, J. H. J. The central role of DNA damage in the ageing process. Nature 592, 695–703 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Picard, M., McEwen, B. S., Epel, E. S. & Sandi, C. An energetic view of stress: focus on mitochondria. Front. Neuroendocrinol. 49, 72–85 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Milanese, C. et al. DNA damage and transcription stress cause ATP-mediated redesign of metabolism and potentiation of anti-oxidant buffering. Nat. Commun. 10, 4887 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Brace, L. E. et al. Increased oxidative phosphorylation in response to acute and chronic DNA damage. NPJ Aging Mech. Dis. 2, 16022 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Robinson, A. R. et al. Spontaneous DNA damage to the nuclear genome promotes senescence, redox imbalance and aging. Redox Biol. 17, 259–273 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Lagger, C. et al. scDiffCom: a tool for differential analysis of cell–cell interactions provides a mouse atlas of aging changes in intercellular communication. Nat. Aging 3, 1446–1461 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Martinez, J., Marmisolle, I., Tarallo, D. & Quijano, C. Mitochondrial bioenergetics and dynamics in secretion processes. Front. Endocrinol. 11, 319 (2020).

    Article  Google Scholar 

  66. Gutierrez, J. M. et al. Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion. Nat. Commun. 11, 68 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Franceschi, C. & Campisi, J. Chronic inflammation (inflammaging) and its potential contribution to age-associated diseases. J. Gerontol. A Biol. Sci. Med. Sci. 69, S4–S9 (2014).

    Article  PubMed  Google Scholar 

  68. Gems, D. The hyperfunction theory: an emerging paradigm for the biology of aging. Ageing Res. Rev. 74, 101557 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Kaspar, S. et al. Adaptation to mitochondrial stress requires CHOP-directed tuning of ISR. Sci. Adv. 7, eabf0971 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Khan, N. A. et al. mTORC1 regulates mitochondrial integrated stress response and mitochondrial myopathy progression. Cell Metab. 26, 419–428 (2017).

    Article  CAS  PubMed  Google Scholar 

  71. Sharma, R. et al. Circulating markers of NADH-reductive stress correlate with mitochondrial disease severity. J. Clin. Invest. 131, e136055 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Mick, E. et al. Distinct mitochondrial defects trigger the integrated stress response depending on the metabolic state of the cell. eLife 9, e49178 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Sercel, A. J. et al. Hypermetabolism and energetic constraints in mitochondrial disorders. Nat. Metab. 6, 192–195 (2024).

    Article  PubMed  Google Scholar 

  74. Sturm, G. et al. OxPhos defects cause hypermetabolism and reduce lifespan in cells and in patients with mitochondrial diseases. Commun. Biol. 6, 22 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Ost, M. et al. Muscle mitochondrial stress adaptation operates independently of endogenous FGF21 action. Mol. Metab. 5, 79–90 (2016).

    Article  CAS  PubMed  Google Scholar 

  76. Han, S. et al. Mitochondrial integrated stress response controls lung epithelial cell fate. Nature 620, 890–897 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Forsstrom, S. et al. Fibroblast growth factor 21 drives dynamics of local and systemic stress responses in mitochondrial myopathy with mtDNA deletions. Cell Metab. 30, 1040–1054 (2019).

    Article  CAS  PubMed  Google Scholar 

  78. Cheng, Y. W., Liu, J. & Finkel, T. Mitohormesis. Cell Metab. 35, 1872–1886 (2023).

    Article  CAS  PubMed  Google Scholar 

  79. Borner, T. et al. GDF15 induces an aversive visceral malaise state that drives anorexia and weight loss. Cell Rep. 31, 107543 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Fejzo, M. et al. GDF15 linked to maternal risk of nausea and vomiting during pregnancy. Nature 625, 760–767 (2024).

    Article  CAS  PubMed  Google Scholar 

  81. Hubens, W. H. G. et al. Blood biomarkers for assessment of mitochondrial dysfunction: an expert review. Mitochondrion 62, 187–204 (2022).

    Article  CAS  PubMed  Google Scholar 

  82. Borner, T. et al. Anorexia–cachexia syndrome in hepatoma tumour-bearing rats requires the area postrema but not vagal afferents and is paralleled by increased MIC-1/GDF15. J. Cachexia Sarcopenia Muscle 8, 417–427 (2017).

    Article  PubMed  Google Scholar 

  83. Borner, T. et al. GDF15 induces anorexia through nausea and emesis. Cell Metab. 31, 351–362 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Quist, J. S. et al. Effects of acute exercise and exercise training on plasma GDF15 concentrations and associations with appetite and cardiometabolic health in individuals with overweight or obesity — a secondary analysis of a randomized controlled trial. Appetite 182, 106423 (2023).

    Article  PubMed  Google Scholar 

  85. Patel, S. et al. GDF15 provides an endocrine signal of nutritional stress in mice and humans. Cell Metab. 29, 707–718 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Tanaka, T. et al. Plasma proteomic signature of age in healthy humans. Aging Cell 17, e12799 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Lehallier, B. et al. Undulating changes in human plasma proteome profiles across the lifespan. Nat. Med. 25, 1843–1850 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. St Sauver, J. L. et al. Biomarkers of cellular senescence and risk of death in humans. Aging Cell 22, e14006 (2023).

    Article  Google Scholar 

  89. Lockhart, S. M., Saudek, V. & O’Rahilly, S. GDF15: a hormone conveying somatic distress to the brain. Endocr. Rev. 41, bnaa007 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Kim, J. Y., Atanassov, I., Dethloff, F., Kroczek, L. & Langer, T. Time-resolved proteomic analyses of senescence highlight metabolic rewiring of mitochondria. Life Sci. Alliance 6, e202302127 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Summer, R. et al. Activation of the mTORC1/PGC-1 axis promotes mitochondrial biogenesis and induces cellular senescence in the lung epithelium. Am. J. Physiol. Lung Cell. Mol. Physiol. 316, L1049–L1060 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Patil, P. et al. Oxidative stress-induced senescence markedly increases disc cell bioenergetics. Mech. Ageing Dev. 180, 97–106 (2019).

    Article  CAS  PubMed  Google Scholar 

  93. Martinez, J. et al. Mitofusins modulate the increase in mitochondrial length, bioenergetics and secretory phenotype in therapy-induced senescent melanoma cells. Biochem. J. 476, 2463–2486 (2019).

    Article  CAS  PubMed  Google Scholar 

  94. Sgarbi, G. et al. Mitochondria hyperfusion and elevated autophagic activity are key mechanisms for cellular bioenergetic preservation in centenarians. Aging 6, 296–310 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  95. Liesa, M. & Shirihai, O. S. Mitochondrial dynamics in the regulation of nutrient utilization and energy expenditure. Cell Metab. 17, 491–506 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Gomes, L. C., Di Benedetto, G. & Scorrano, L. During autophagy mitochondria elongate, are spared from degradation and sustain cell viability. Nat. Cell Biol. 13, 589–598 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Gems, D. & Kern, C. C. Is ‘cellular senescence’ a misnomer? Geroscience 44, 2461–2469 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Sturm, G. et al. A multi-omics longitudinal aging dataset in primary human fibroblasts with mitochondrial perturbations. Sci. Data 9, 751 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Takauji, Y. et al. Restriction of protein synthesis abolishes senescence features at cellular and organismal levels. Sci. Rep. 6, 18722 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Takauji, Y., En, A., Miki, K., Ayusawa, D. & Fujii, M. Combinatorial effects of continuous protein synthesis, ERK-signaling, and reactive oxygen species on induction of cellular senescence. Exp. Cell Res. 345, 239–246 (2016).

    Article  CAS  PubMed  Google Scholar 

  101. Sharifi, S. et al. Reducing the metabolic burden of rRNA synthesis promotes healthy longevity in Caenorhabditis elegans. Nat. Commun. 15, 1702 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Kuehnemann, C. et al. Antiretroviral protease inhibitors induce features of cellular senescence that are reversible upon drug removal. Aging Cell 22, e13750 (2023).

    Article  CAS  PubMed  Google Scholar 

  103. Monzel, A. S., Levin, M. & Picard, M. The energetics of cellular life transitions. Life Metab. 3, load051 (2024).

    Article  PubMed  Google Scholar 

  104. Peng, M. et al. Inhibiting cytosolic translation and autophagy improves health in mitochondrial disease. Hum. Mol. Genet. 24, 4829–4847 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Frasca, D., Diaz, A., Romero, M., Thaller, S. & Blomberg, B. B. Metabolic requirements of human pro-inflammatory B cells in aging and obesity. PLoS ONE 14, e0219545 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Frasca, D., Diaz, A., Romero, M. & Blomberg, B. B. Metformin enhances B cell function and antibody responses of elderly individuals with type-2 diabetes mellitus. Front. Aging 2, 715981 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  107. Lemons, J. M. et al. Quiescent fibroblasts exhibit high metabolic activity. PLoS Biol. 8, e1000514 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  108. Fuqua, J. D. et al. Impaired proteostatic mechanisms other than decreased protein synthesis limit old skeletal muscle recovery after disuse atrophy. J. Cachexia Sarcopenia Muscle 14, 2076–2089 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  109. Li, X. et al. Inflammation and aging: signaling pathways and intervention therapies. Signal Transduct. Target. Ther. 8, 239 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  110. Moaddel, R. et al. Cross-sectional analysis of healthy individuals across decades: aging signatures across multiple physiological compartments. Aging Cell 23, e13902 (2023).

  111. Zhang, B. et al. Multi-omic rejuvenation and life span extension on exposure to youthful circulation. Nat. Aging 3, 948–964 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Niebel, B., Leupold, S. & Heinemann, M. An upper limit on Gibbs energy dissipation governs cellular metabolism. Nat. Metab. 1, 125–132 (2019).

    Article  CAS  PubMed  Google Scholar 

  113. Hammond, K. A. & Diamond, J. Maximal sustained energy budgets in humans and animals. Nature 386, 457–462 (1997).

    Article  CAS  PubMed  Google Scholar 

  114. Thurber, C. et al. Extreme events reveal an alimentary limit on sustained maximal human energy expenditure. Sci. Adv. 5, eaaw0341 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Semercioz-Oduncuoglu, A. S., Mitchell, S. E., Ozilgen, M., Yilmaz, B. & Speakman, J. R. A step toward precision gerontology: lifespan effects of calorie and protein restriction are consistent with predicted impacts on entropy generation. Proc. Natl Acad. Sci. USA 120, e2300624120 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  116. Yang, X. et al. Physical bioenergetics: energy fluxes, budgets, and constraints in cells. Proc. Natl Acad. Sci. USA 118, e2026786118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Zhao, Z. et al. Body temperature is a more important modulator of lifespan than metabolic rate in two small mammals. Nat. Metab. 4, 320–326 (2022).

    Article  CAS  PubMed  Google Scholar 

  118. Pontzer, H. Constrained total energy expenditure and the evolutionary biology of energy balance. Exerc. Sport Sci. Rev. 43, 110–116 (2015).

    Article  PubMed  Google Scholar 

  119. Careau, V. et al. Energy compensation and adiposity in humans. Curr. Biol. 31, 4659–4666 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Mountjoy, M. et al. 2023 International Olympic Committee’s (IOC) consensus statement on relative energy deficiency in sport (REDs). Br. J. Sports Med. 57, 1073–1097 (2023).

    Article  PubMed  Google Scholar 

  121. Jasienska, G. & Ellison, P. T. Energetic factors and seasonal changes in ovarian function in women from rural Poland. Am. J. Hum. Biol. 16, 563–580 (2004).

    Article  PubMed  Google Scholar 

  122. Pontzer, H. et al. Daily energy expenditure through the human life course. Science 373, 808–812 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Fountain, W. A., Bopp, T. S., Bene, M. & Walston, J. D. Metabolic dysfunction and the development of physical frailty: an aging war of attrition. Geroscience 46, 3711–3721 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  124. Arunachalam, E., Ireland, W., Yang, X. & Needleman, D. Dissecting flux balances to measure energetic costs in cell biology: techniques and challenges. Annu. Rev. Condens. Matter Phys. 14, 211–235 (2023).

    Article  Google Scholar 

  125. Bobba-Alves, N. et al. Cellular allostatic load is linked to increased energy expenditure and accelerated biological aging. Psychoneuroendocrinology 155, 106322 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Lee, W. D. et al. Impact of acute stress on murine metabolomics and metabolic flux. Proc. Natl Acad. Sci. USA 120, e2301215120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Dos Anjos Souza, V. R. et al. Running economy in long-distance runners is positively affected by running experience and negatively by aging. Physiol. Behav. 258, 114032 (2023).

    Article  PubMed  Google Scholar 

  128. Petr, M. A. et al. A cross-sectional study of functional and metabolic changes during aging through the lifespan in male mice. eLife 10, e62952 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Singam, N. S. V., Fine, C. & Fleg, J. L. Cardiac changes associated with vascular aging. Clin. Cardiol. 43, 92–98 (2020).

    Article  PubMed  Google Scholar 

  130. Jang, C. et al. Metabolite exchange between mammalian organs quantified in pigs. Cell Metab. 30, 594–606 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Wang, R. et al. Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging Drosophila. Nat. Commun. 13, 3518 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Sharma, A. K., Khandelwal, R. & Wolfrum, C. Futile cycles: emerging utility from apparent futility. Cell Metab. 36, 1184–1203 (2024).

    Article  CAS  PubMed  Google Scholar 

  133. Gendron, C. M. et al. Neuronal mechanisms that drive organismal aging through the lens of perception. Annu. Rev. Physiol. 82, 227–249 (2020).

    Article  CAS  PubMed  Google Scholar 

  134. Gendron, C. M. et al. Drosophila life span and physiology are modulated by sexual perception and reward. Science 343, 544–548 (2014).

    Article  CAS  PubMed  Google Scholar 

  135. Uhlen, M. et al. Tissue-based map of the human proteome. Science 347, 1260419 (2015).

    Article  PubMed  Google Scholar 

  136. Dantzer, R., O’Connor, J. C., Freund, G. G., Johnson, R. W. & Kelley, K. W. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat. Rev. Neurosci. 9, 46–56 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Docherty, S. et al. The effect of exercise on cytokines: implications for musculoskeletal health: a narrative review. BMC Sports Sci. Med. Rehabil. 14, 5 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  138. Scheu, S. et al. Activation of the integrated stress response during T helper cell differentiation. Nat. Immunol. 7, 644–651 (2006).

    Article  CAS  PubMed  Google Scholar 

  139. Uehara, M., Plank, L. D. & Hill, G. L. Components of energy expenditure in patients with severe sepsis and major trauma: a basis for clinical care. Crit. Care Med. 27, 1295–1302 (1999).

    Article  CAS  PubMed  Google Scholar 

  140. Mitsuyama, Y. et al. Sepsis-associated hypoglycemia on admission is associated with increased mortality in intensive care unit patients. Acute Med. Surg. 9, e718 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  141. Grant, R. W. & Stephens, J. M. Fat in flames: influence of cytokines and pattern recognition receptors on adipocyte lipolysis. Am. J. Physiol. Endocrinol. Metab. 309, E205–E213 (2015).

    Article  CAS  PubMed  Google Scholar 

  142. Majd, M., Saunders, E. F. H. & Engeland, C. G. Inflammation and the dimensions of depression: a review. Front. Neuroendocrinol. 56, 100800 (2020).

    Article  PubMed  Google Scholar 

  143. Rozin, P. In Advances in the Study of Behavior Vol. 6 (eds Rosenblatt, J. S. et al.) 21–76 (Academic Press, 1976).

  144. Butte, N. F., Ekelund, U. & Westerterp, K. R. Assessing physical activity using wearable monitors: measures of physical activity. Med. Sci. Sports Exerc. 44, S5–S12 (2012).

    Article  PubMed  Google Scholar 

  145. Du, S., Rajjo, T., Santosa, S. & Jensen, M. D. The thermic effect of food is reduced in older adults. Horm. Metab. Res. 46, 365–369 (2014).

    CAS  PubMed  Google Scholar 

  146. Speakman, J. R. The evolution of body fatness: trading off disease and predation risk. J. Exp. Biol. 221, jeb167254 (2018).

    Article  PubMed  Google Scholar 

  147. Wang, A. et al. Opposing effects of fasting metabolism on tissue tolerance in bacterial and viral inflammation. Cell 166, 1512–1525 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Urlacher, S. S. et al. Tradeoffs between immune function and childhood growth among Amazonian forager-horticulturalists. Proc. Natl Acad. Sci. USA 115, E3914–E3921 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Muehlenbein, M. P., Hirschtick, J. L., Bonner, J. Z. & Swartz, A. M. Toward quantifying the usage costs of human immunity: altered metabolic rates and hormone levels during acute immune activation in men. Am. J. Hum. Biol. 22, 546–556 (2010).

    Article  PubMed  Google Scholar 

  150. Laskow, T. et al. Soluble TNFR1 has greater reproducibility than IL-6 for the assessment of chronic inflammation in older adults: the case for a new inflammatory marker in aging. Geroscience 46, 2521–2530 (2024).

    Article  CAS  PubMed  Google Scholar 

  151. Lu, W. H. et al. Association between aging-related biomarkers and longitudinal trajectories of intrinsic capacity in older adults. Geroscience 17, 3323–3339 (2023).

    Google Scholar 

  152. Fielding, R. A. et al. Biomarkers of cellular senescence predict the onset of mobility disability and are reduced by physical activity in older adults. J. Gerontol. A Biol. Sci. Med. Sci. 79, glad257 (2023).

    Article  Google Scholar 

  153. Furman, D. et al. Chronic inflammation in the etiology of disease across the life span. Nat. Med. 25, 1822–1832 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Ferrucci, L. & Fabbri, E. Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nat. Rev. Cardiol. 15, 505–522 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Nidadavolu, L. S. et al. Interleukin-6 drives mitochondrial dysregulation and accelerates physical decline: insights from an inducible humanized IL-6 knock-in mouse model. J. Gerontol. A Biol. Sci. Med. Sci. 78, 1740–1752 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Maggio, M. et al. Relationship between low levels of anabolic hormones and 6-year mortality in older men: the Aging in the Chianti Area (InCHIANTI) study. Arch. Intern. Med. 167, 2249–2254 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Jimeno, B. & Verhulst, S. Meta-analysis reveals glucocorticoid levels reflect variation in metabolic rate, not ‘stress’. eLife 12, RP88205 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Mullur, R., Liu, Y. Y. & Brent, G. A. Thyroid hormone regulation of metabolism. Physiol. Rev. 94, 355–382 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Cappola, A. R., Xue, Q. L. & Fried, L. P. Multiple hormonal deficiencies in anabolic hormones are found in frail older women: the Women’s Health and Aging studies. J. Gerontol. A Biol. Sci. Med. Sci. 64, 243–248 (2009).

    Article  PubMed  Google Scholar 

  160. Spendiff, S. et al. Denervation drives mitochondrial dysfunction in skeletal muscle of octogenarians. J. Physiol. 594, 7361–7379 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. Poganik, J. R. et al. Biological age is increased by stress and restored upon recovery. Cell Metab. 35, 807–820 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Pham, H. et al. The effects of pregnancy, its progression, and its cessation on human (maternal) biological aging. Cell Metab. 36, 877–878 (2024).

    Article  CAS  PubMed  Google Scholar 

  163. Polsky, L. R., Rentscher, K. E. & Carroll, J. E. Stress-induced biological aging: a review and guide for research priorities. Brain Behav. Immun. 104, 97–109 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Lyons, C. E., Razzoli, M. & Bartolomucci, A. The impact of life stress on hallmarks of aging and accelerated senescence: connections in sickness and in health. Neurosci. Biobehav. Rev. 153, 105359 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  165. Faria, M., Ganz, A., Galkin, F., Zhavoronkov, A. & Snyder, M. Psychogenic aging: a novel prospect to integrate psychobiological hallmarks of aging. Transl. Psychiatry 14, 226 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  166. Cohen, S. et al. Chronic stress, glucocorticoid receptor resistance, inflammation, and disease risk. Proc. Natl Acad. Sci. USA 109, 5995–5999 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  167. Powell, N. D. et al. Social stress up-regulates inflammatory gene expression in the leukocyte transcriptome via β-adrenergic induction of myelopoiesis. Proc. Natl Acad. Sci. USA 110, 16574–16579 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Marsland, A. L., Walsh, C., Lockwood, K. & John-Henderson, N. A. The effects of acute psychological stress on circulating and stimulated inflammatory markers: a systematic review and meta-analysis. Brain Behav. Immun. 64, 208–219 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Rohleder, N. Stimulation of systemic low-grade inflammation by psychosocial stress. Psychosom. Med. 76, 181–189 (2014).

    Article  PubMed  Google Scholar 

  170. Merz, M. P. & Turner, J. D. Is early life adversity a trigger towards inflammageing? Exp. Gerontol. 150, 111377 (2021).

    Article  PubMed  Google Scholar 

  171. Heilbronn, L. K. & Ravussin, E. Calorie restriction and aging: review of the literature and implications for studies in humans. Am. J. Clin. Nutr. 78, 361–369 (2003).

    Article  CAS  PubMed  Google Scholar 

  172. Cahill, G. F. Jr. Starvation in man. N. Engl. J. Med. 282, 668–675 (1970).

    Article  CAS  PubMed  Google Scholar 

  173. Civitarese, A. E. et al. Calorie restriction increases muscle mitochondrial biogenesis in healthy humans. PLoS Med. 4, e76 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  174. Willette, A. A. et al. Interleukin-8 and interleukin-10, brain volume and microstructure, and the influence of calorie restriction in old rhesus macaques. Age 35, 2215–2227 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  175. Hughes, D. C., Ellefsen, S. & Baar, K. Adaptations to endurance and strength training. Cold Spring Harb. Perspect. Med. 8, a029769 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  176. Conley, K. E. et al. Higher mitochondrial respiration and uncoupling with reduced electron transport chain content in vivo in muscle of sedentary versus active subjects. J. Clin. Endocrinol. Metab. 98, 129–136 (2013).

    Article  CAS  PubMed  Google Scholar 

  177. Pontzer, H. Energy constraint as a novel mechanism linking exercise and health. Physiology 33, 384–393 (2018).

    Article  CAS  PubMed  Google Scholar 

  178. Loprinzi, P. et al. Objectively measured physical activity and C-reactive protein: National Health and Nutrition Examination Survey 2003–2004. Scand. J. Med. Sci. Sports 23, 164–170 (2013).

    Article  CAS  PubMed  Google Scholar 

  179. Caplin, A., Chen, F. S., Beauchamp, M. R. & Puterman, E. The effects of exercise intensity on the cortisol response to a subsequent acute psychosocial stressor. Psychoneuroendocrinology 131, 105336 (2021).

    Article  CAS  PubMed  Google Scholar 

  180. Nabkasorn, C. et al. Effects of physical exercise on depression, neuroendocrine stress hormones and physiological fitness in adolescent females with depressive symptoms. Eur. J. Public Health 16, 179–184 (2006).

    Article  PubMed  Google Scholar 

  181. Kempermann, G. et al. Why and how physical activity promotes experience-induced brain plasticity. Front. Neurosci. 4, 189 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  182. O’Reilly, C. L., Bodine, S. C. & Miller, B. F. Current limitations and future opportunities of tracer studies of muscle ageing. J. Physiol. https://doi.org/10.1113/JP285616 (2023).

    Article  PubMed  Google Scholar 

  183. Xu, M. et al. Senolytics improve physical function and increase lifespan in old age. Nat. Med. 24, 1246–1256 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  184. Farr, J. N. et al. Targeting cellular senescence prevents age-related bone loss in mice. Nat. Med. 23, 1072–1079 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  185. Saxton, R. A. & Sabatini, D. M. mTOR signaling in growth, metabolism, and disease. Cell 168, 960–976 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  186. Lee, D. J. W., Hodzic Kuerec, A. & Maier, A. B. Targeting ageing with rapamycin and its derivatives in humans: a systematic review. Lancet Healthy Longev. 5, e152–e162 (2024).

    Article  PubMed  Google Scholar 

  187. Fontana, L., Nehme, J. & Demaria, M. Caloric restriction and cellular senescence. Mech. Ageing Dev. 176, 19–23 (2018).

    Article  CAS  PubMed  Google Scholar 

  188. Wang, R. et al. Rapamycin inhibits the secretory phenotype of senescent cells by a Nrf2-independent mechanism. Aging Cell 16, 564–574 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  189. Conboy, I. M. & Rando, T. A. Aging, stem cells and tissue regeneration: lessons from muscle. Cell Cycle 4, 407–410 (2005).

    Article  CAS  PubMed  Google Scholar 

  190. Conboy, I. M. & Rando, T. A. Heterochronic parabiosis for the study of the effects of aging on stem cells and their niches. Cell Cycle 11, 2260–2267 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  191. Villeda, S. A. et al. Young blood reverses age-related impairments in cognitive function and synaptic plasticity in mice. Nat. Med. 20, 659–663 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  192. Horvath, S. et al. Reversal of biological age in multiple rat organs by young porcine plasma fraction. Geroscience 46, 367–394 (2024).

    Article  CAS  PubMed  Google Scholar 

  193. Mehdipour, M. et al. Plasma dilution improves cognition and attenuates neuroinflammation in old mice. Geroscience 43, 1–18 (2021).

    Article  CAS  PubMed  Google Scholar 

  194. Mehdipour, M. et al. Rejuvenation of three germ layers tissues by exchanging old blood plasma with saline-albumin. Aging 12, 8790–8819 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  195. Widjaja, A. A. et al. Inhibition of IL-11 signalling extends mammalian healthspan and lifespan. Nature 632, 157–165 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  196. Mehdipour, M. et al. Attenuation of age-elevated blood factors by repositioning plasmapheresis: a novel perspective and approach. Transfus. Apher. Sci. 60, 103162 (2021).

    Article  PubMed  Google Scholar 

  197. Kent, S. et al. Different receptor mechanisms mediate the pyrogenic and behavioral effects of interleukin 1. Proc. Natl Acad. Sci. USA 89, 9117–9120 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  198. Bluthe, R. M., Michaud, B., Kelley, K. W. & Dantzer, R. Vagotomy attenuates behavioural effects of interleukin-1 injected peripherally but not centrally. Neuroreport 7, 1485–1488 (1996).

    Article  CAS  PubMed  Google Scholar 

  199. Jumpertz, R. et al. Higher energy expenditure in humans predicts natural mortality. J. Clin. Endocrinol. Metab. 96, E972–E976 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  200. Ruggiero, C. et al. High basal metabolic rate is a risk factor for mortality: the Baltimore Longitudinal Study of Aging. J. Gerontol. A Biol. Sci. Med. Sci. 63, 698–706 (2008).

    Article  PubMed  Google Scholar 

  201. Cohen, A. A. et al. Balancing the promise and risks of geroscience. Preprint at OSF https://doi.org/10.31219/osf.io/uf25z (2024).

  202. Jin, H., Li, M., Jeong, E., Castro-Martinez, F. & Zuker, C. S. A body–brain circuit that regulates body inflammatory responses. Nature 630, 695–703 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  203. Padamsey, Z. & Rochefort, N. L. Paying the brain’s energy bill. Curr. Opin. Neurobiol. 78, 102668 (2023).

    Article  CAS  PubMed  Google Scholar 

  204. Brown, R. M., Gruijters, S. L. K. & Kotz, S. A. Prediction in the aging brain: merging cognitive, neurological, and evolutionary perspectives. J. Gerontol. B Psychol. Sci. Soc. Sci. 77, 1580–1591 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  205. Christie, S. T. & Schrater, P. Cognitive cost as dynamic allocation of energetic resources. Front. Neurosci. 9, 289 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  206. Ko, F. et al. Inflammation and mortality in a frail mouse model. Age 34, 705–715 (2012).

    Article  CAS  PubMed  Google Scholar 

  207. Ma, L. et al. Targeted deletion of interleukin-6 in a mouse model of chronic inflammation demonstrates opposing roles in aging: benefit and harm. J. Gerontol. A Biol. Sci. Med. Sci. 76, 211–215 (2021).

    Article  CAS  PubMed  Google Scholar 

  208. Poganik, J. R. & Gladyshev, V. N. We need to shift the focus of aging research to aging itself. Proc. Natl Acad. Sci. USA 120, e2307449120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  209. Bieri, G., Schroer, A. B. & Villeda, S. A. Blood-to-brain communication in aging and rejuvenation. Nat. Neurosci. 26, 379–393 (2023).

    CAS  PubMed  Google Scholar 

  210. Belsky, D. W. & Baccarelli, A. A. To promote healthy aging, focus on the environment. Nat. Aging 3, 1334–1344 (2023).

    Article  PubMed  Google Scholar 

  211. Arosio, B. et al. Sarcopenia and cognitive decline in older adults: targeting the muscle–brain axis. Nutrients 15, 1853 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  212. Nishimura, E. K., Granter, S. R. & Fisher, D. E. Mechanisms of hair graying: incomplete melanocyte stem cell maintenance in the niche. Science 307, 720–724 (2005).

    Article  CAS  PubMed  Google Scholar 

  213. O’Sullivan, J. D. B. et al. The biology of human hair greying. Biol. Rev. Camb. Philos. Soc. 96, 107–128 (2021).

    Article  PubMed  Google Scholar 

  214. Zhang, B. et al. Hyperactivation of sympathetic nerves drives depletion of melanocyte stem cells. Nature 577, 676–681 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  215. Rosenberg, A. M. et al. Quantitative mapping of human hair greying and reversal in relation to life stress. eLife 10, e67437 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  216. Clayton, Z. S. et al. Cellular senescence contributes to large elastic artery stiffening and endothelial dysfunction with aging: amelioration with senolytic treatment. Hypertension 80, 2072–2087 (2023).

    Article  CAS  PubMed  Google Scholar 

  217. Schnabel, F., Kornak, U. & Wollnik, B. Premature aging disorders: a clinical and genetic compendium. Clin. Genet. 99, 3–28 (2021).

    Article  CAS  PubMed  Google Scholar 

  218. Trifunovic, A. et al. Premature ageing in mice expressing defective mitochondrial DNA polymerase. Nature 429, 417–423 (2004).

    Article  CAS  PubMed  Google Scholar 

  219. Mattson, M. P. & Arumugam, T. V. Hallmarks of brain aging: adaptive and pathological modification by metabolic states. Cell Metab. 27, 1176–1199 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  220. Jin, M. & Cai, S. Q. Mechanisms underlying brain aging under normal and pathological conditions. Neurosci. Bull. 39, 303–314 (2023).

    Article  PubMed  Google Scholar 

  221. Marsland, A. L., Gianaros, P. J., Abramowitch, S. M., Manuck, S. B. & Hariri, A. R. Interleukin-6 covaries inversely with hippocampal grey matter volume in middle-aged adults. Biol. Psychiatry 64, 484–490 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  222. McCarrey, A. C. et al. Interleukin-6 is linked to longitudinal rates of cortical thinning in aging. Transl. Neurosci. 5, 1–7 (2014).

    Article  PubMed  Google Scholar 

  223. Warren, K. N. et al. Elevated markers of inflammation are associated with longitudinal changes in brain function in older adults. J. Gerontol. A Biol. Sci. Med. Sci. 73, 770–778 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  224. Larson, E. D., St Clair, J. R., Sumner, W. A., Bannister, R. A. & Proenza, C. Depressed pacemaker activity of sinoatrial node myocytes contributes to the age-dependent decline in maximum heart rate. Proc. Natl Acad. Sci. USA 110, 18011–18016 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  225. Birnbaumer, P. et al. Heart rate performance curve is dependent on age, sex, and performance. Front. Public Health 8, 98 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  226. Mick, E., McManus, D. D. & Goldberg, R. J. Meta-analysis of increased heart rate and blood pressure associated with CNS stimulant treatment of ADHD in adults. Eur. Neuropsychopharmacol. 23, 534–541 (2013).

    Article  CAS  PubMed  Google Scholar 

  227. Westover, A. N. et al. Exercise outcomes in prevalent users of stimulant medications. J. Psychiatr. Res. 64, 32–39 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  228. Hackney, A. C. Hypogonadism in exercising males: dysfunction or adaptive-regulatory adjustment? Front. Endocrinol. 11, 11 (2020).

    Article  Google Scholar 

  229. Pawelec, G. Age and immunity: what is ‘immunosenescence’? Exp. Gerontol. 105, 4–9 (2018).

    Article  CAS  PubMed  Google Scholar 

  230. Guerrieri, M., Di Mauro, R., Di Girolamo, S. & Di Stadio, A. Hearing and ageing. Subcell. Biochem. 103, 279–290 (2023).

    Article  PubMed  Google Scholar 

  231. Wolpe, N. et al. Ageing increases reliance on sensorimotor prediction through structural and functional differences in frontostriatal circuits. Nat. Commun. 7, 13034 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  232. Wredenberg, A. et al. Increased mitochondrial mass in mitochondrial myopathy mice. Proc. Natl Acad. Sci. USA 99, 15066–15071 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  233. Ravera, S. et al. Discrete changes in glucose metabolism define aging. Sci. Rep. 9, 10347 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  234. Chaleckis, R., Murakami, I., Takada, J., Kondoh, H. & Yanagida, M. Individual variability in human blood metabolites identifies age-related differences. Proc. Natl Acad. Sci. USA 113, 4252–4259 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  235. Markov, N. T. et al. Age-related brain atrophy is not a homogenous process: different functional brain networks associate differentially with aging and blood factors. Proc. Natl Acad. Sci. USA 119, e2207181119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  236. Beydoun, H. A. et al. Mediating and moderating effects of plasma proteomic biomarkers on the association between poor oral health problems and incident dementia: the UK Biobank study. Geroscience 46, 5343–5363 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  237. Guo, Y. et al. Plasma proteomic profiles predict future dementia in healthy adults. Nat. Aging 4, 247–260 (2024).

    Article  CAS  PubMed  Google Scholar 

  238. Makarieva, A. M. et al. Mean mass-specific metabolic rates are strikingly similar across life’s major domains: evidence for life’s metabolic optimum. Proc. Natl Acad. Sci. USA 105, 16994–16999 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  239. Kempes, C. P., Wolpert, D., Cohen, Z. & Perez-Mercader, J. The thermodynamic efficiency of computations made in cells across the range of life. Philos. Trans. A Math. Phys. Eng. Sci. 375, 20160343 (2017).

    PubMed  PubMed Central  Google Scholar 

  240. Medzhitov, R. Origin and physiological roles of inflammation. Nature 454, 428–435 (2008).

    Article  CAS  PubMed  Google Scholar 

  241. Wang, B., Han, J., Elisseeff, J. H. & Demaria, M. The senescence-associated secretory phenotype and its physiological and pathological implications. Nat. Rev. Mol. Cell Biol. https://doi.org/10.1038/s41580-024-00727-x (2024).

    Article  PubMed  Google Scholar 

  242. Bryant, S. J. & Machta, B. B. Physical constraints in intracellular signaling: the cost of sending a bit. Phys. Rev. Lett. 131, 068401 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  243. Mehta, P. & Schwab, D. J. Energetic costs of cellular computation. Proc. Natl Acad. Sci. USA 109, 17978–17982 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  244. Kafri, M., Metzl-Raz, E., Jona, G. & Barkai, N. The cost of protein production. Cell Rep. 14, 22–31 (2016).

    Article  CAS  PubMed  Google Scholar 

  245. Buttgereit, F. & Brand, M. D. A hierarchy of ATP-consuming processes in mammalian cells. Biochem. J. 312, 163–167 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  246. Wang, T.-L., Kuznets-Speck, B., Broderick, J. & Hinczewski, M. The price of a bit: energetic costs and the evolution of cellular signaling. Preprint at bioRxiv https://doi.org/10.1101/2020.10.06.327700 (2022).

  247. Lan, G., Sartori, P., Neumann, S., Sourjik, V. & Tu, Y. The energy–speed–accuracy tradeoff in sensory adaptation. Nat. Phys. 8, 422–428 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  248. Jeong, J. K., Dow, S. A. & Young, C. N. Sensory circumventricular organs, neuroendocrine control, and metabolic regulation. Metabolites 11, 494 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  249. Watts, A. G., Kanoski, S. E., Sanchez-Watts, G. & Langhans, W. The physiological control of eating: signals, neurons, and networks. Physiol. Rev. 102, 689–813 (2022).

    Article  CAS  PubMed  Google Scholar 

  250. Bruning, J. C. & Fenselau, H. Integrative neurocircuits that control metabolism and food intake. Science 381, eabl7398 (2023).

    Article  PubMed  Google Scholar 

  251. Nampoothiri, S., Nogueiras, R., Schwaninger, M. & Prevot, V. Glial cells as integrators of peripheral and central signals in the regulation of energy homeostasis. Nat. Metab. 4, 813–825 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  252. Yoon, N. A. & Diano, S. Hypothalamic glucose-sensing mechanisms. Diabetologia 64, 985–993 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  253. Varela, L. & Horvath, T. L. Leptin and insulin pathways in POMC and AgRP neurons that modulate energy balance and glucose homeostasis. EMBO Rep. 13, 1079–1086 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  254. Jais, A. & Bruning, J. C. Arcuate nucleus-dependent regulation of metabolism—pathways to obesity and diabetes mellitus. Endocr. Rev. 43, 314–328 (2022).

    Article  PubMed  Google Scholar 

  255. Ravussin, E., Smith, S. R. & Ferrante, A. W. Jr. Physiology of energy expenditure in the weight-reduced state. Obesity 29, S31–S38 (2021).

    Article  PubMed  Google Scholar 

  256. Grill, H. J. & Hayes, M. R. Hindbrain neurons as an essential hub in the neuroanatomically distributed control of energy balance. Cell Metab. 16, 296–309 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  257. Jones, T. H. & Kennedy, R. L. Cytokines and hypothalamic–pituitary function. Cytokine 5, 531–538 (1993).

    Article  CAS  PubMed  Google Scholar 

  258. Bluthe, R. M. et al. Lipopolysaccharide induces sickness behaviour in rats by a vagal mediated mechanism. C. R. Acad. Sci. III 317, 499–503 (1994).

    CAS  PubMed  Google Scholar 

  259. Maier, S. F., Goehler, L. E., Fleshner, M. & Watkins, L. R. The role of the vagus nerve in cytokine-to-brain communication. Ann. N. Y. Acad. Sci. 840, 289–300 (1998).

    Article  CAS  PubMed  Google Scholar 

  260. Wang, D. et al. GDF15: emerging biology and therapeutic applications for obesity and cardiometabolic disease. Nat. Rev. Endocrinol. 17, 592–607 (2021).

    Article  CAS  PubMed  Google Scholar 

  261. Reyes, J. & Yap, G. S. Emerging roles of growth differentiation factor 15 in immunoregulation and pathogenesis. J. Immunol. 210, 5–11 (2023).

    Article  CAS  PubMed  Google Scholar 

  262. Melvin, A., Lacerda, E., Dockrell, H. M., O’Rahilly, S. & Nacul, L. Circulating levels of GDF15 in patients with myalgic encephalomyelitis/chronic fatigue syndrome. J. Transl. Med. 17, 409 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We are grateful to the members of the Mitochondrial Psychobiology Laboratory, M. Yousefzadeh, J. Wanagat, R. Musci, J. McNamara, J. Carroll, D. Leake and the Columbia Science of Health group for input on parts of the manuscript. Our research is supported by NIH grants R01MH119336, R01MH122706, R01AG066828 and RF1AG076821, the Wharton Fund and the Baszucki Group (to M.P.).

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Authors and Affiliations

  1. Department of Psychiatry, Division of Behavioral Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA

    Evan D. Shaulson & Martin Picard

  2. Robert N. Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA

    Alan A. Cohen & Martin Picard

  3. Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA

    Alan A. Cohen

  4. Department of Neurology, H. Houston Merritt Center for Neuromuscular and Mitochondrial Disorders, Columbia Translational Neuroscience Initiative, College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA

    Martin Picard

  5. New York State Psychiatric Institute, New York, NY, USA

    Martin Picard

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  1. Evan D. Shaulson
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E.D.S., A.A.C. and M.P. contributed to the literature review and revised the final version of the figures and manuscript.

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Correspondence to Martin Picard.

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Shaulson, E.D., Cohen, A.A. & Picard, M. The brain–body energy conservation model of aging. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00716-x

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