Skip to main content
Log in

Evolution of aging theories: Why modern programmed aging concepts are transforming medical research

  • Phenoptosis (Special Issue)
  • Published:
Biochemistry (Moscow) Aims and scope Submit manuscript


Programmed aging refers to the idea that senescence in humans and other organisms is purposely caused by evolved biological mechanisms to obtain an evolutionary advantage. Until recently, programmed aging was considered theoretically impossible because of the mechanics of the evolution process, and medical research was based on the idea that aging was not programmed. Theorists struggled for more than a century in efforts to develop non-programmed theories that fit observations, without obtaining a consensus supporting any non-programmed theory. Empirical evidence of programmed lifespan limitations continued to accumulate. More recently, developments, especially in our understanding of biological inheritance, have exposed major issues and complexities regarding the process of evolution, some of which explicitly enable programmed aging of mammals. Consequently, science-based opposition to programmed aging has dramatically declined. This progression has major implications for medical research, because the theories suggest that very different biological mechanisms are ultimately responsible for highly age-related diseases that now represent most research efforts and health costs. Most particularly, programmed theories suggest that aging per se is a treatable condition and suggest a second path toward treating and preventing age-related diseases that can be exploited in addition to the traditional disease-specific approaches. The theories also make predictions regarding the nature of biological aging mechanisms and therefore suggest research directions. This article discusses developments of evolutionary mechanics, the consequent programmed aging theories, and logical inferences concerning biological aging mechanisms. It concludes that major medical research organizations cannot afford to ignore programmed aging concepts in assigning research resources and directions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others


  1. Olshansky, S., Hayflick, L., and Carnes, B. (2002) No truth to the fountain of youth, Sci. Am. (reprinted July 2004, 14).

    Google Scholar 

  2. Weismann, A. (1882) Uber die Dauer des Lebens, Fischer, Jena.

    Google Scholar 

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

    Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  6. Dawkins, R. (1986) The Selfish Gene, Oxford University Press.

    Google Scholar 

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

    Article  PubMed  Google Scholar 

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

    Google Scholar 

  9. Skulachev, V. (1997) Aging is a specific biological function rather than the result of a disorder in complex living systems: biochemical evidence in support of Weismann’s hypothesis, Biochemistry (Moscow), 62, 1191–1195.

    CAS  Google Scholar 

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

    Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  12. Williams, G. (1966) Adaptation and Natural Selection: A Critique of Some Current Evolutionary Thought, Princeton.

    Google Scholar 

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

    Google Scholar 

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

    Article  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  18. Wodinsky, J. (1977) Hormonal inhibition of feeding and death in octopus: control by optic gland secretion, Science, 198, 948–951.

    Article  CAS  PubMed  Google Scholar 

  19. Apfeld, J., and Kenyon, C. (1999) Regulation of lifespan by sensory perception in Caenorhabditis elegans, Nature, 402, 804–809.

    Article  CAS  PubMed  Google Scholar 

  20. 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 

  21. Bateson, W., Saunders, E., and Punnett, R. (1904) Report II. Experimental studies in the physiology of heredity, Rep. Evol. Com. R Soc., 2, 1–154.

    Google Scholar 

  22. Valdez, R., and Krausman, P. (1999) Mountain Sheep of North America, The University of Arizona Press, Tucson.

    Google Scholar 

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

    Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  25. 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 N. Y.), 3, 1120–1123.

    Google Scholar 

  26. Goldsmith, T. (2016) Emerging programmed aging mechanisms and their medical implications, Med. Hypotheses, 86, 92–96.

    Article  PubMed  Google Scholar 

  27. Weindruch, R., Walford, R., Fligiel, S., and Guthrie, D. (1986) The retardation of aging in mice by dietary restriction: longevity, cancer, immunity and lifetime energy intake, J. Nutr., 116, 641–654.

    CAS  PubMed  Google Scholar 

  28. American Academy of Anti-Aging Medicine (A4M), website, 6/2016.

  29. Darwin, C. (1872) The Origin of Species, 6th Edn., Murray, London.

    Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Theodore C. Goldsmith.

Additional information

Published in Russian in Biokhimiya, 2016, Vol. 81, No. 12, pp. 1675–1684.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Goldsmith, T.C. Evolution of aging theories: Why modern programmed aging concepts are transforming medical research. Biochemistry Moscow 81, 1406–1412 (2016).

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI:

Key words