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Evolvability, population benefit, and the evolution of programmed aging in mammals


Programmed aging theories contend that evolved biological mechanisms purposely limit internally determined lifespans in mammals and are ultimately responsible for most instances of highly age-related diseases and conditions. Until recently, the existence of programmed aging mechanisms was considered theoretically impossible because it directly conflicted with Darwin’s survival-of-the-fittest evolutionary mechanics concept as widely taught and generally understood. However, subsequent discoveries, especially in genetics, have exposed issues with some details of Darwin’s theory that affect the mechanics of the evolution process and strongly suggest that programmed aging mechanisms in humans and other mammals can and did evolve, and more generally, that a trait that benefits a population can evolve even if, like senescence, it is adverse to individual members of the population. Evolvability theories contend that organisms can possess evolved design characteristics (traits) that affect their ability to evolve, and further, that a trait that increases a population’s ability to evolve (increases evolvability) can be acquired and retained even if it is adverse in traditional individual fitness terms. Programmed aging theories based on evolvability contend that internally limiting lifespan in a species-specific manner creates an evolvability advantage that results in the evolution and retention of senescence. This issue is critical to medical research because the different theories lead to dramatically different concepts regarding the nature of biological mechanisms behind highly age-related diseases and conditions.

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  1. Darwin, C. (1859) On the Origin of Species by Means of Natural Selection, (John Murray, ed.) 6th Edn., Chap. 7. Miscellaneous Objections to the Theory of Natural Selection, London.

  2. Max Planck Institute (2002) Life Spans of Mammals, Birds, Amphibians, Reptiles, and Fish.

  3. Goldsmith, T. (2014) The Evolution of Aging, 3rd Edn., Annapolis Azinet Press.

    Google Scholar 

  4. Wagner, G., and Altenberg, L. (1996) Perspective: complex adaptations and the evolution of evolvability, Evolution, 50,3.

    Article  Google Scholar 

  5. Goldsmith, T. (2008) Aging, evolvability, and the individual benefit requirement; medical implications of aging theory controversies, J. Theor. Biol., 252, 764–768.

    PubMed  Google Scholar 

  6. Skulachev, V. (2011) Aging as a particular case of phenoptosis, the programmed death of an organism (A response to Kirkwood–Melov “On the programmed/non-programmed nature of aging within the life history”), Aging (Albany, NY), 3, 1120–1123.

    Google Scholar 

  7. Weismann, A. (1892) Uber die Dauer des Lebens, Fischer, Jena.

    Google Scholar 

  8. Harman, D. (1956) Aging: a theory based on free radical and radiation chemistry, J. Gerontol., 11, 298–300.

    CAS  Article  PubMed  Google Scholar 

  9. Bennett, J. T., Boehlert, G. W., and Turekian, K. K. (1982) Confirmation on longevity in Sebastes diploproa (Pisces: Scorpaenidae) from 210Pb/226Ra measurements in otoliths, Marit. Biol., 71, 209–215.

    Article  Google Scholar 

  10. Medawar, P. (1952) An Unsolved Problem of Biology, H. K. Lewis, London.

    Google Scholar 

  11. Williams, G. (1957) Pleiotropy, natural selection and the evolution of senescence, Evolution, 11, 398–411.

    Google Scholar 

  12. Kirkwood, T., and Holliday, F. (1979) The evolution of ageing and longevity, Proc. R. Soc. Lond. B, 205, 531–546.

    CAS  Article  PubMed  Google Scholar 

  13. Loison, A., Festa-Bianchet, M., Gaillard, J.-M., Jorgenson, J. T., and Jullien, J.-M. (1999) Age-specific survival in five populations of ungulates: evidence of senescence, Ecology, 80, 2539–2554.

    Article  Google Scholar 

  14. Goldsmith, T. (2013) Arguments against non-programmed aging theories, Biochemistry (Moscow), 78, 971–978.

    CAS  Article  Google Scholar 

  15. Watson, J., and Crick, F. A. (1953) Structure for deoxyribose nucleic acid, Nature, 4356.

  16. National Center for Biotechnology Information. dbSNP 8 June 2015.

  17. Lewin, B. (2004) Genes VIII, Pearson Prentice Hall.

    Google Scholar 

  18. Wayne-Edwards, V. (1962) Animal Dispersion in Relation to Social Behaviour, Oliver & Boyd, Edinburgh.

    Google Scholar 

  19. Hamilton, W. (1963) The evolution of altruistic behavior, Am. Naturalist, 97, 354–356.

    Article  Google Scholar 

  20. Travis, J. (2004) The evolution of programmed death in a spatially structured population, J. Gerontol., 59, 301–305.

    Article  Google Scholar 

  21. Mitteldorf, J. (2006) Chaotic population dynamics and the evolution of ageing, Evol. Ecol. Res., 8, 561–574.

    Google Scholar 

  22. Libertini, G. (1988) An adaptive theory of increasing mortality with increasing chronological age in populations in the wild, J. Theor. Biol., 132, 145–162.

    CAS  Article  PubMed  Google Scholar 

  23. Olshansky, S., Hayflick, L., and Carnes, B. (2002) No truth to the fountain of youth, Sci. Am., 286, 92–95.

    Article  PubMed  Google Scholar 

  24. Kowald, A., and Kirkwood, T. (2016) Can aging be programmed? A critical literature review, Aging Cell, doi: 10.1111/acel.12510.

    Google Scholar 

  25. Kirkwood, T., and Melov, S. (2011) On the programmed/non-programmed nature of ageing within the life history, Curr. Biol., 21, R701–R707.

    CAS  Article  PubMed  Google Scholar 

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Correspondence to T. C. Goldsmith.

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Published in Russian in Biokhimiya, 2017, Vol. 82, No. 12, pp. 1771-1781.

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Goldsmith, T.C. Evolvability, population benefit, and the evolution of programmed aging in mammals. Biochemistry Moscow 82, 1423–1429 (2017).

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  • aging theory
  • senescence
  • medicine
  • gerontology
  • evolutionary mechanics theories