What is aging? Mechanistic answers to this question remain elusive despite decades of research. Here, we propose a mathematical model of cellular aging based on a model gene interaction network. Our model network is made of only non-aging components - the functionality of gene interactions decrease with a constant mortality rate. Death of a cell occurs in the model when an essential gene loses all of its interactions to other genes, equivalent to the deletion of an essential gene. Interactions among genes are modeled to be inherently stochastic due to limited numbers of functional molecules of gene products . We show that characteristics of biological aging, the exponential increase of mortality rate over time, can arise from this gene network model  . Hence, we demonstrate that cellular aging is an emergent property of this model network. Our model predicts that the rate of aging, defined by the Gompertz coefficient, is  proportional to the average number of active interactions per gene in the network and that stochastic heterogeneity of gene interactions is an important factor in shaping the dynamics of the aging process. This theoretic framework offers a mechanistic foundation for the pleiotropic nature of aging and can provide insights on interpretation of experimental data .
What is aging? Mechanistic answers to this question remain elusive despite decades of research. Here, we propose a mathematical model of cellular aging based on a model gene interaction network. Our network model is made of only non-aging components - the biological functions of gene interactions decrease with a constant mortality rate. Death of a cell occurs in the model when an essential gene loses all of its interactions to other genes, equivalent to the deletion of an essential gene. Gene interactions are stochastic based on a binomial distribution . We show that the defining characteristic of biological aging, the exponential increase of mortality rate over time, can arise from this gene network model during the early stage of aging . Hence, we demonstrate that cellular aging is an emergent property of this model network. Our model predicts that the rate of aging, defined by the Gompertz coefficient, is approximately proportional to the average number of active interactions per gene and that the stochastic heterogeneity of gene interactions is an important factor in the dynamics of the aging process. This theoretic framework offers a mechanistic foundation for the pleiotropic nature of aging and can provide insights on cellular aging .
R
model network
network model
R
functionality
biological functions
R
Interactions among genes are modeled to be inherently stochastic due to limited numbers of functional molecules of gene products
Gene interactions are stochastic based on a binomial distribution
R
characteristics
the defining characteristic
A
during the early stage of aging
A
approximately
R
in the network and that
and that the
D
shaping
R
interpretation of experimental data
cellular aging