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Compression of morbidity by interventions that steepen the survival curve

Yang, Yifan, Mayo, Avi, Levy, Tomer, Raz, Naveh, Shenhar, Ben, Jarosz, Daniel F., Alon, Uri·2025·Nature Communications
DOI 10.1038/s41467-025-57807-5PMC PMC11978790

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  • The SR model was applied in mice to parabiosis, compression of morbidity and combinations of longevity interventions.

    “In mice it was applied to parabiosis33, compression of morbidity and combinations of longevity interventions34.”

    From A damage accumulation model identifies distinct aging regimes across species (2026) · cites this paper as [34]

  • Reducing production alone would stretch the lifespan but also the sickspan (time of poor health at end of life) by the same factor.

    “Recent analysis indicates that reducing production alone would stretch the lifespan but also the sickspan (time of poor health at end of life) by the same factor34.”

    From A damage accumulation model identifies distinct aging regimes across species (2026) · cites this paper as [34]

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  1. Olshansky, S. J., Rudberg, M. A., Carnes, B. A., Cassel, C. K. & Brody, J. A. Trading off longer life for worsening health: the expansion of morbidity hypothesis. J. Aging Health 3, 194–216 (1991). · DOI
  2. Kirkland, J. L. & Peterson, C. Healthspan, translation, and new outcomes for animal studies of aging. J. Gerontol. A. Biol. Sci. Med. Sci. 64, 209–212 (2009). · DOI · Paper page
  3. Seals, D. R., Justice, J. N. & LaRocca, T. J. Physiological geroscience: targeting function to increase healthspan and achieve optimal longevity. J. Physiol. 594, 2001–2024 (2016). · DOI
  4. Blagosklonny, M. V. How to save medicare: the anti-aging remedy. Aging 4, 547–552 (2012). · DOI
  5. Goldman, D. P. et al. Substantial health and economic returns from delayed aging may warrant a new focus for medical research. Health Aff. 32, 1698–1705 (2013). · DOI · Paper page
  6. Harper, S. Economic and social implications of aging societies. Science 346, 587–591 (2014). · DOI
  7. Jagger, C. & Robine, J.-M. Healthy life expectancy. In International Handbook of Adult Mortality (eds Rogers, R. G. & Crimmins, E. M.) 551–568 (Springer Netherlands, 2011). · DOI
  8. Manton, K. G. Changing concepts of morbidity and mortality in the elderly population. Milbank Mem. Fund. Q. Health Soc. 60, 183–244 (1982). · DOI
  9. Longo, V. D. & Anderson, R. M. Nutrition, longevity and disease: from molecular mechanisms to interventions. Cell 185, 1455–1470 (2022). · DOI
  10. Wasko, B. M. & Kaeberlein, M. Yeast replicative aging: a paradigm for defining conserved longevity interventions. FEMS Yeast Res. 14, 148–159 (2014). · DOI
  11. Maglioni, S., Arsalan, N. & Ventura, N. C. elegans screening strategies to identify pro-longevity interventions. Mech. Ageing Dev. 157, 60–69 (2016). · DOI
  12. Tatar, M., Post, S. & Yu, K. Nutrient control of Drosophila longevity. Trends Endocrinol. Metab. 25, 509–517 (2014). · DOI
  13. Weindruch, R., Walford, R. L., Fligiel, S. & Guthrie, D. The retardation of aging in mice by dietary restriction: longevity, cancer, immunity and lifetime energy intake. J. Nutr. 116, 641–654 (1986). · DOI
  14. Fontana, L., Partridge, L. & Longo, V. D. Extending healthy life span—from yeast to humans. Science 328, 321–326 (2010). · DOI · Paper page
  15. Murphy, C. T. & Hu, P. J. in WormBook: The Online Review of C. elegans Biology (ed. The C. elegans Research Community) Ch. 177 (WormBook, 2018).
  16. Lamming, D. W., Ye, L., Sabatini, D. M. & Baur, J. A. Rapalogs and mTOR inhibitors as anti-aging therapeutics. J. Clin. Investig. 123, 980–989 (2013). · DOI · Paper page
  17. Yousefzadeh, M. J. et al. Fisetin is a senotherapeutic that extends health and lifespan. EBioMedicine 36, 18–28 (2018). · DOI · Paper page
  18. Macchiarini, F., Miller, R. A., Strong, R., Rosenthal, N. & Harrison, D. E. Chapter 10—NIA interventions testing program: a collaborative approach for investigating interventions to promote healthy aging. In Handbook of the Biology of Aging, Ninth Edition (eds Musi, N. & Hornsby, P. J.) 219–235 (Academic Press, 2021). · DOI
  19. Statzer, C., Reichert, P., Dual, J. & Ewald, C. Y. Longevity interventions temporally scale healthspan in Caenorhabditis elegans. iScience 25, 103983 (2022). · DOI
  20. Hahm, J.-H. et al. C. elegans maximum velocity correlates with healthspan and is maintained in worms with an insulin receptor mutation. Nat. Commun. 6, 8919 (2015). · DOI
  21. Papadopoulos, N. T. et al. Dietary effects on sex-specific health dynamics of medfly: support for the dynamic equilibrium model of aging. Exp. Gerontol. 46, 1026–1030 (2011). · DOI
  22. Carnes, B. A., Holden, L. R., Olshansky, S. J., Witten, M. T. & Siegel, J. S. Mortality partitions and their relevance to research on senescence. Biogerontology 7, 183–198 (2006). · DOI · Paper page
  23. Stroustrup, N. et al. The temporal scaling of Caenorhabditis elegans ageing. Nature 530, 103–107 (2016). · DOI · Paper page
  24. Liu, P. & Acar, M. The generational scalability of single-cell replicative aging. Sci. Adv. 4, eaao4666 (2018). · DOI
  25. Karin, O. & Alon, U. Senescent cell accumulation mechanisms inferred from parabiosis. GeroScience 43, 329–341 (2021). · DOI · Paper page
  26. Katzir, I. et al. Senescent cells and the incidence of age-related diseases. Aging Cell 20, e13314 (2021). · DOI · Paper page
  27. Yang, Y. et al. Damage dynamics and the role of chance in the timing of E. coli cell death. Nat. Commun. 14, 2209 (2023). · DOI · Paper page
  28. Swindell, W. R. Accelerated failure time models provide a useful statistical framework for aging research. Exp. Gerontol. 44, 190–200 (2009). · DOI
  29. Liang, Y. et al. Calorie restriction is the most reasonable anti-ageing intervention: a meta-analysis of survival curves. Sci. Rep. 8, 5779 (2018). · DOI
  30. Hughes, B. G. & Hekimi, S. Different mechanisms of longevity in long-lived mouse and Caenorhabditis elegans mutants revealed by statistical analysis of mortality rates. Genetics 204, 905–920 (2016). · DOI
  31. Yashin, A. I., Iachine, I. A. & Begun, A. S. Mortality modeling: a review. Math. Popul. Stud. 8, 305–332 (2000). · DOI
  32. Gaitanidis, A. et al. Longitudinal assessment of health-span and pre-death morbidity in wild type Drosophila. Aging 11, 1850–1873 (2019). · DOI
  33. Oswal, N., Martin, O. M. F., Stroustrup, S., Bruckner, M. A. M. & Stroustrup, N. A hierarchical process model links behavioral aging and lifespan in C. elegans. PLoS Comput. Biol. 18, e1010415 (2022). · DOI · Paper page
  34. Luciano, A. et al. Longitudinal fragility phenotyping contributes to the prediction of lifespan and age-associated morbidity in C57BL/6 and diversity outbred mice. GeroScience 46, 4937–4954 (2024). · DOI
  35. Kane, A. E. et al. Impact of longevity interventions on a validated mouse clinical frailty index. J. Gerontol. A. Biol. Sci. Med. Sci. 71, 333–339 (2016). · DOI
  36. Xie, K. et al. Deep phenotyping and lifetime trajectories reveal limited effects of longevity regulators on the aging process in C57BL/6J mice. Nat. Commun. 13, 6830 (2022). · DOI
  37. Ruby, J. G. et al. An automated, home-cage, video monitoring-based mouse frailty index detects age-associated morbidity in C57BL/6 and diversity outbred mice. J. Gerontol. A. Biol. Sci. Med. Sci. 78, 762–770 (2023). · DOI
  38. Carey, J. R., Liedo, P., MÜller, H.-G., Wang, J.-L. & Vaupel, J. W. A simple graphical technique for displaying individual fertility data and cohort survival: case study of 1000 Mediterranean Fruit Fly females. Funct. Ecol. 12, 359–363 (1998). · DOI
  39. Carey, J. R. et al. Life history response of Mediterranean fruit flies to dietary restriction. Aging Cell 1, 140–148 (2002). · DOI
  40. Carey, J. R. et al. Stochastic dietary restriction using a Markov-chain feeding protocol elicits complex, life history response in medflies. Aging Cell 4, 31–39 (2005). · DOI
  41. Spiridonova, O., Kriukov, D., Nemirovich-Danchenko, N. & Peshkin, L. On standardization of controls in lifespan studies. Aging 16, 3047–3055 (2024). · DOI
  42. Nadon, N. L., Strong, R., Miller, R. A. & Harrison, D. E. NIA interventions testing program: investigating putative aging intervention agents in a genetically heterogeneous mouse model. eBioMedicine 21, 3–4 (2017). · DOI
  43. Harrison, D. E. et al. 17-a-estradiol late in life extends lifespan in aging UM-HET3 male mice; nicotinamide riboside and three other drugs do not affect lifespan in either sex. Aging Cell 20, e13328 (2021). · DOI
  44. Harrison, D. E. et al. Acarbose, 17-α-estradiol, and nordihydroguaiaretic acid extend mouse lifespan preferentially in males. Aging Cell 13, 273–282 (2014). · DOI · Paper page
  45. Harrison, D. E. et al. Acarbose improves health and lifespan in aging HET3 mice. Aging Cell 18, e12898 (2019). · DOI
  46. Miller, R. A. et al. Canagliflozin extends life span in genetically heterogeneous male but not female mice. JCI Insight 5, e140019 (2020). · DOI
  47. Strong, R. et al. Evaluation of resveratrol, green tea extract, curcumin, oxaloacetic acid, and medium-chain triglyceride oil on life span of genetically heterogeneous mice. J. Gerontol. A. Biol. Sci. Med. Sci. 68, 6–16 (2013). · DOI · Paper page
  48. Kowald, A. & Kirkwood, T. B. L. Senolytics and the compression of late-life mortality. Exp. Gerontol. 155, 111588 (2021). · DOI
  49. Grunewald, M. et al. Counteracting age-related VEGF signaling insufficiency promotes healthy aging and extends life span. Science 373, eabc8479 (2021). · DOI · Paper page
  50. Strong, R. et al. Lifespan benefits for the combination of rapamycin plus acarbose and for captopril in genetically heterogeneous mice. Aging Cell 21, e13724 (2022). · DOI · Paper page
  51. Wilmoth, J. R. & Horiuchi, S. Rectangularization revisited: variability of age at death within human populations. Demography 36, 475–495 (1999). · DOI
  52. Robine, J.-M., Jagger, C., Crimmins, E. M., Saito, Y. & Van Oyen, H. Trends in Health Expectancies. In International Handbook of Health Expectancies (eds Jagger, C. et al.) 19–34 (Springer International Publishing, Cham, 2020). · DOI
  53. Makeham, W. M. On the law of mortality and the construction of annuity tables. Assur. Mag. J. Inst. Actuar. 8, 301–310 (1860). · DOI · Paper page
  54. Yang, Y. et al. Temporal scaling of aging as an adaptive strategy of Escherichia coli. Sci. Adv. 5, eaaw2069 (2019). · DOI
  55. Vaupel, J. W. Biodemography of human ageing. Nature 464, 536–542 (2010). · DOI · Paper page
  56. Zhang, Y.-B. et al. Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: two prospective cohort studies. BMJ 373, n604 (2021). · DOI
  57. Andersen, S. L., Sebastiani, P., Dworkis, D. A., Feldman, L. & Perls, T. T. Health span approximates life span among many supercentenarians: compression of morbidity at the approximate limit of life span. J. Gerontol. Ser. A 67A, 395–405 (2012). · DOI · Paper page
  58. Ismail, K. et al. Compression of morbidity is observed across cohorts with exceptional longevity. J. Am. Geriatr. Soc. 64, 1583–1591 (2016). · DOI
  59. Tang, B. et al. Longitudinal associations between use of antihypertensive, antidiabetic, and lipid-lowering medications and biological aging. GeroScience 45, 2065–2078 (2023). · DOI
  60. Prattichizzo, F. et al. Organ-specific biological clocks: ageotyping for personalized anti-aging medicine. Ageing Res. Rev. 96, 102253 (2024). · DOI
  61. Goeminne, L. J. E. et al. Plasma-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems. Cell Metab. 37, 205–222.e6 (2025). · DOI
  62. Campos, C. Chronic hyperglycemia and glucose toxicity: pathology and clinical sequelae. Postgrad. Med. 124, 90–97 (2012). · DOI
  63. Maeda, M., Hayashi, T., Mizuno, N., Hattori, Y. & Kuzuya, M. Intermittent high glucose implements stress-induced senescence in human vascular endothelial cells: role of superoxide production by NADPH oxidase. PLoS ONE 10, e0123169 (2015). · DOI
  64. Mann, S. N. et al. Health benefits attributed to 17α-estradiol, a lifespan-extending compound, are mediated through estrogen receptor α. eLife 9, e59616 (2020). · DOI
  65. Stout, M. B. et al. 17α-Estradiol alleviates age-related metabolic and inflammatory dysfunction in male mice without inducing feminization. J. Gerontol. Ser. A 72, 3–15 (2017). · DOI · Paper page
  66. Miller, R. A. et al. Rapamycin, but not resveratrol or simvastatin, extends life span of genetically heterogeneous mice. J. Gerontol. Ser. A 66A, 191–201 (2011). · DOI · Paper page
  67. Wilkinson, J. E. et al. Rapamycin slows aging in mice. Aging Cell 11, 675–682 (2012). · DOI · Paper page
  68. Strong, R. et al. Rapamycin-mediated mouse lifespan extension: late-life dosage regimes with sex-specific effects. Aging Cell 19, e13269 (2020). · DOI · Paper page
  69. Wikby, A. et al. The immune risk phenotype is associated with IL-6 in the terminal decline stage: findings from the Swedish NONA immune longitudinal study of very late life functioning. Mech. Ageing Dev. 127, 695–704 (2006). · DOI
  70. Franceschi, C., Garagnani, P., Parini, P., Giuliani, C. & Santoro, A. Inflammaging: a new immune–metabolic viewpoint for age-related diseases. Nat. Rev. Endocrinol. 14, 576–590 (2018). · DOI · Paper page
  71. Coppé, J.-P., Desprez, P.-Y., Krtolica, A. & Campisi, J. The senescence-associated secretory phenotype: the dark side of tumor suppression. Annu. Rev. Pathol. 5, 99–118 (2010). · DOI · Paper page
  72. Westendorp, R. G. & Kirkwood, T. B. Human longevity at the cost of reproductive success. Nature 396, 743–746 (1998). · DOI · Paper page
  73. Marmot, M. G. et al. Health inequalities among British civil servants: the Whitehall II study. Lancet 337, 1387–1393 (1991). · DOI
  74. Anderson, R. T., Sorlie, P., Backlund, E., Johnson, N. & Kaplan, G. A. Mortality effects of community socioeconomic status. Epidemiology 8, 42–47 (1997). · DOI
  75. Stringhini, S. et al. Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1·7 million men and women. Lancet 389, 1229–1237 (2017). · DOI · Paper page
  76. Tomaka, J., Thompson, S. & Palacios, R. The relation of social isolation, loneliness, and social support to disease outcomes among the elderly. J. Aging Health 18, 359–384 (2006). · DOI
  77. Nyberg, S. T. et al. Association of healthy lifestyle with years lived without major chronic diseases. JAMA Intern. Med. 180, 760–768 (2020). · DOI
  78. Doblhammer, G. & Kytir, J. Compression or expansion of morbidity? Trends in healthy-life expectancy in the elderly Austrian population between 1978 and 1998. Soc. Sci. Med. 52, 385–391 (2001). · DOI · Paper page
  79. Jagger, C. et al. A comparison of health expectancies over two decades in England: results of the Cognitive Function and Ageing Study I and II. Lancet 387, 779–786 (2016). · DOI
  80. Fleming, T. R., O’Fallon, J. R., O’Brien, P. C. & Harrington, D. P. Modified Kolmogorov-Smirnov test procedures with application to arbitrarily right-censored data. Biometrics 36, 607–625 (1980). · DOI

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Metadata

Authors
Yang, Y., Mayo, A., Levy, T., Raz, N., Shenhar, B., Jarosz, D. F., & Alon, U.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2025-04-08
Volume
16
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-025-57807-5
PMC
PMC11978790
Cited by
18
References
19
Language
en
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