A Quantitative Model for Age-Dependent Expression of the p16INK4a Tumor Suppressor

Recent work has shown that expression of the $p16^{INK4a} $ tumor suppressor increases with chronological age. Expression is accelerated by gerontogenic behaviors such as tobacco use and physical inactivity, and is also influenced by allelic genotype of a polymorphic single nucleotide polymorphism (...

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Veröffentlicht in:Proceedings of the National Academy of Sciences - PNAS 2009-09, Vol.106 (39), p.16562-16567
Hauptverfasser: Tsygankov, Denis, Liu, Yan, Sanoff, Hanna K., Sharpless, Norman E., Elston, Timothy C., Fraumeni, Joseph F.
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container_end_page 16567
container_issue 39
container_start_page 16562
container_title Proceedings of the National Academy of Sciences - PNAS
container_volume 106
creator Tsygankov, Denis
Liu, Yan
Sanoff, Hanna K.
Sharpless, Norman E.
Elston, Timothy C.
Fraumeni, Joseph F.
description Recent work has shown that expression of the $p16^{INK4a} $ tumor suppressor increases with chronological age. Expression is accelerated by gerontogenic behaviors such as tobacco use and physical inactivity, and is also influenced by allelic genotype of a polymorphic single nucleotide polymorphism (SNP) rs10757278 that is physically linked with the $p16^{INK4a} $ ORF. To understand the relationship between $p16^{INK4a} $ expression, chronologic age, subject characteristics and host genetics, we sought to develop a mathematical model that links $p16^{INK4a} $ expression with aging. Using an annotated dataset of 170 healthy adults for whom $p16^{INK4a} $ expression and subject genotypes were known, we developed two alternative stochastic models that relate $p16^{INK4a} $ expression to age, smoking, exercise and rs10757278 genotype. Levels of $p16^{INK4a} $ increased exponentially and then saturated at later chronologic ages. The model, which best fit the data, suggests saturation occurs because of $p16^{INK4a} $-dependent attrition of subjects at older chronologic ages, presumably due to death or chronic illness. An important feature of our model is that factors that contribute to death in a non $p16^{INK4a} $-dependent manner do not affect our analysis. Interestingly, tobacco-related increases in $p16^{INK4a} $ expression are predicted to arise from a decrease in the rate of $p16^{INK4a} $-dependent death. This analysis is most consistent with the model that $p16^{INK4a} $ expression monotonically increases with age, and higher expression is associated with increased subject attrition.
doi_str_mv 10.1073/pnas.0904405106
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Expression is accelerated by gerontogenic behaviors such as tobacco use and physical inactivity, and is also influenced by allelic genotype of a polymorphic single nucleotide polymorphism (SNP) rs10757278 that is physically linked with the $p16^{INK4a} $ ORF. To understand the relationship between $p16^{INK4a} $ expression, chronologic age, subject characteristics and host genetics, we sought to develop a mathematical model that links $p16^{INK4a} $ expression with aging. Using an annotated dataset of 170 healthy adults for whom $p16^{INK4a} $ expression and subject genotypes were known, we developed two alternative stochastic models that relate $p16^{INK4a} $ expression to age, smoking, exercise and rs10757278 genotype. Levels of $p16^{INK4a} $ increased exponentially and then saturated at later chronologic ages. The model, which best fit the data, suggests saturation occurs because of $p16^{INK4a} $-dependent attrition of subjects at older chronologic ages, presumably due to death or chronic illness. An important feature of our model is that factors that contribute to death in a non $p16^{INK4a} $-dependent manner do not affect our analysis. Interestingly, tobacco-related increases in $p16^{INK4a} $ expression are predicted to arise from a decrease in the rate of $p16^{INK4a} $-dependent death. 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subjects Age
Aging
Biological Sciences
Cellular senescence
Cyclin-Dependent Kinase Inhibitor p16 - genetics
Cyclin-Dependent Kinase Inhibitor p16 - metabolism
Exercise
Genotype
Genotype & phenotype
Genotypes
Mathematical models
Modeling
Models, Theoretical
Mortality
Parametric models
Polymorphism
Polymorphism, Single Nucleotide
Stochastic models
Tobacco
Tobacco smoking
Tumor Suppressor Proteins - genetics
Tumor Suppressor Proteins - metabolism
Tumors
title A Quantitative Model for Age-Dependent Expression of the p16INK4a Tumor Suppressor
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