Abstract
A major unresolved issue in gerontology concerns the evolutionary nature of senescence: Is aging caused by genetically programmed evolved mechanisms because limiting individual lifespan increases a population’s ability to survive and grow? Or is aging non-programmed because aging reduces an individual’s ability to survive and reproduce? There has been little disagreement with the many proposed population benefits of senescence, but evolution theory as described by Darwin and currently taught is very individual-oriented and until recently, programmed aging has been widely thought to be theoretically impossible. However, genetics discoveries have exposed issues with traditional theory that support population-driven evolution and programmed aging. In particular, as described in this article, the discovery that biological inheritance involves the transmission of information in digital form between parent and descendant of any organism strongly supports population-oriented evolution concepts and dependent programmed aging theories. A related issue concerns evolvability. Traditional theory assumes that the ability to evolve (evolvability) and involving mutations and natural selection is an inherent property of life. Evolvability theories suggest that evolvability in complex species is instead mainly itself the result of evolved traits and that such traits can evolve even if individually adverse. Programmed aging theories based on evolvability suggest that aging has evolved because it increases evolvability causing a population benefit. This idea is also strongly supported by the digital nature of inheritance. The programmed vs. non-programmed issue is critical to medical research because the two concepts suggest that very different biological mechanisms are responsible for aging and most instances of age-related disease.
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References
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.
Weismann, A. (1882) Uber die Dauer des Lebens, Fischer, Jena.
Goldsmith, T. (2014) The Evolution of Aging, 3rd Edn., Azinet Press, Annapolis.
Mittledorf, J. (2006) Chaotic population dynamics and the evolution of ageing, Evol. Ecol. Res., 8, 561–574.
Libertini, G. (1988) An adaptive theory of increasing mortality with increasing chronological age in populations in the wild, J. Theor. Biol., 132, 145–162.
Hamilton, W. (1963) The evolution of altruistic behavior, Am. Nat., 97, 354–356.
Wynne-Edwards, V. (1962) Animal Dispersion in Relation to Social Behaviour, Oliver & Boyd, Edinburgh.
Zedalis, J., and Eggebrecht, J. (2018) Biology for AP Courses, OpenStax, Houston.
Olshansky, S., Hayflick, L., and Carnes, B. (2002) No truth to the fountain of youth, Sci. Am., 286, 92–95 (reprinted July 2004, Vol 14, No. 3).
Watson, J. D., and Crick, F. H. (1953) Molecular structure of nucleic acids; a structure for deoxyribose nucleic acid, Nature, 171, 737–738.
Crick, F. H., Barnett, L., Brenner, S., and Watts-Tobin, R. J. (1961) General nature of the genetic code for proteins, Nature, 192, 1227–1232.
Proakis, J., and Salehi, M. (2014) Digital Communications, 5th Edn., McGraw-Hill Education.
Krebs, J., Goldstein, E., and Kilpatrick, S. (2017) Lewin’s GENES XII, 12th Edn., Jones & Bartlett Learning, Burlington.
Salomon, D. (2010) Handbook of Data Compression, 5th Edn., Springer, London.
Darwin, C. (1859) On the Origin of Species, John Murray, London.
Goldsmith, T. C. (2017) Evolvability, population benefit, and the evolution of programmed aging in mammals, Biochemistry (Moscow), 82, 1423–1429.
Williams, G. (1957) Pleiotropy, natural selection and the evolution of senescence, Evolution, 11, 398–411.
Medawar, P. (1952) An Unsolved Problem of Biology, H.K. Lewis & Co., London.
Goldsmith, T. (2013) Arguments against non-programmed aging theories, Biochemistry (Moscow), 78, 971–978, doi: 10.1134/S0006297913090022.
Kirkwood, T. (1977) Evolution of ageing, Nature, 270, 301–304.
De Grey, A. D. (2007) Calorie restriction, post-reproductive life span, and programmed aging: a plea for rigor, Ann. NY Acad. Sci., 1119, 296–305.
De Grey, A. (2015) Do we have genes that exist to hasten aging? New data, new arguments, but the answer is still no, Curr. Aging Sci., 8, 24–33.
Williams, G. (1971) Group Selection, Aldine-Atherton, Chicago.
Travis, J. (2004) The evolution of programmed death in a spatially structured population, J. Gerontol., 59, 301–305.
Goldsmith, T. (2017) Externally regulated programmed aging and the effects of population stress on mammal lifespan, Biochemistry (Moscow), 82, 1430–1434.
Apfeld, J., and Kenyon, C. (1999) Regulation of lifespan by sensory perception in Caenorhabditis elegans, Nature, 402, 804–809.
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Published in Russian in Biokhimiya, 2019, Vol. 84, No. 12, pp. 1792–1800.
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Goldsmith, T.C. Digital Genetics, Variation, Evolvability, and the Evolution of Programmed Aging. Biochemistry Moscow 84, 1451–1457 (2019). https://doi.org/10.1134/S0006297919120046
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DOI: https://doi.org/10.1134/S0006297919120046