title: Aging in complex interdependency networks.
abstract: Although species longevity is subject to a diverse range of evolutionary forces, the mortality curves of a wide variety of organisms are rather similar. Here we argue that qualitative and quantitative features of aging can be reproduced by a simple model based on the interdependence of fault-prone agents on one other. In addition to fitting our theory to the empiric mortality curves of six very different organisms, we establish the dependence of lifetime and aging rate on initial conditions, damage and repair rate, and system size. We compare the size distributions of disease and death and see that they have qualitatively different properties. We show that aging patterns are independent of the details of interdependence network structure, which suggests that aging is a many-body effect, and that the qualitative and quantitative features of aging are not sensitively dependent on the details of dependency structure or its formation.
authors.affiliation: School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.
authors.forename: Dervis C
authors.initials: DC
authors.lastname: Vural
authors.affiliation: School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA and Department of Economics, IMT Institute for Advanced Studies, Lucca 55100, Italy and Department of Physics, Harvard University, Cambridge, Massachusetts, USA.
authors.forename: Greg
authors.initials: G
authors.lastname: Morrison
authors.affiliation: School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA and Department of Physics, Harvard University, Cambridge, Massachusetts, USA and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA.
authors.forename: L
authors.initials: L
authors.lastname: Mahadevan
mesh_terms: D000375:Aging / Q000502:physiology*; D000818:Animals; D003198:Computer Simulation; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D008136:Longevity; D008954:Models, Biological; D015233:Models, Statistical; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D020543:Proteome