Network theory of aging

From Wikipedia, the free encyclopedia
Jump to: navigation, search

The network theory of aging supports the idea that multiple connected processes contribute to the biology of aging. Kirkwood and Kowald helped to establish the first model of this kind by connecting theories and predict specific mechanisms. In departure of investigating a single mechanistic cause or single molecules that lead to senescence, the network theory of aging takes a systems biology view to integrate theories in conjunction with computational models and quantitative data related to the biology of aging.


  • The free radical theory, describing the reactions of free radicals, antioxidants and proteolytic enzymes, was computationally connected with the protein error theory to describe the error propagation loops within the cellular translation machinery.[1]
  • The study of gene networks revealed proteins associated with aging to have significantly higher connectivity than expected by chance.[2]
  • Investigation of aging on multiple levels of biological organization contributed to a physiome view, from genes to organisms, predicting lifespans based on scaling laws, fractal supply networks and metabolism as well as aging related molecular networks.[3]
  • The network theory of aging has encouraged the development of data bases related to human aging. Proteomic network maps suggest a relationship between the genetics of development and the genetics of aging.[4]

See also[edit]

DNA damage theory of aging


  1. ^ Kowald A, Kirkwood TB. Towards a network theory of ageing: a model combining the free radical theory and the protein error theory J Theor Biol. 1994 May 7;168(1):75-94
  2. ^ Promislow DE. Protein networks, pleiotropy and the evolution of senescence. Proc Biol Sci. 2004 Jun 22;271(1545):1225-34
  3. ^ Kriete A, Sokhansanj BA, Coppock DL, West GB. Systems approaches to the networks of aging. Ageing Res Rev. 2006 Nov;5(4):434-48 PMID 16904954
  4. ^ de Magalhaes JP, Costa J, Toussaint O. HAGR. The Human Ageing Genomic Resources. Nucleic Acids Res. 2005 Jan 1;33(Database issue):D537-43