### Abstract

OBJECTIVES: Body fatness is widely assumed to be regulated by a lipostatic set-point system, which has evolved in response to trade-offs in the risks of mortality. Increasing fatness makes the risk of starvation lower but increases the risk of predation. Yet other models are available. The aim of this work is to evaluate using mathematical modeling whether set-point systems are more likely to evolve than the alternatives.

METHODS: I modeled the trade-off in mortality risks using a simple mathematical model, which generates an optimum level of fatness that is presumed to be the driver for the evolution of a set-point. I then mimicked the likely errors in this optimum level, that derive from the variation in the component parameters of the mortality curves using Markov Chain Monte Carlo (MCMC) simulation by Bayesian inference Using Gibbs Sampling (BUGS).

RESULTS: The error propagation generated by the simulations showed that even very small errors in the model parameters were magnified enormously in the location of the optimum fatness level. If the model parameters had coefficients of variation of just 1% then the coefficient of variation in the optimum level of fatness was between 20 and 90%. In that situation, a set-point centered at the mathematical optimum from the component curves would be at the correct level of fatness that minimizes mortality, and hence maximizes fitness, on less than 8% of occasions.

CONCLUSIONS: Set-point regulation of body fatness is hence highly unlikely to evolve where there is any realistic level of variation in the parameters that define mortality risks. Using further MCMC modeling, I show that a dual-intervention point system is more likely to evolve. This mathematical simulation work has important implications for how we interpret molecular work concerning regulation of adiposity.

Original language | English |
---|---|

Pages (from-to) | 147-154 |

Number of pages | 8 |

Journal | Molecular Metabolism |

Volume | 7 |

Early online date | 21 Oct 2017 |

DOIs | |

Publication status | Published - Jan 2018 |

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### Keywords

- mathematical modelling
- Body fat regulation
- Lipostat
- Leptin
- Leptin resistance
- Feedback control

### Cite this

**Why lipostatic set point systems are unlikely to evolve.** / Speakman, John R.

Research output: Contribution to journal › Article

*Molecular Metabolism*, vol. 7, pp. 147-154. https://doi.org/10.1016/j.molmet.2017.10.007

}

TY - JOUR

T1 - Why lipostatic set point systems are unlikely to evolve

AU - Speakman, John R

N1 - My work on body weight regulation has been generously supported by the Chinese Academy of Sciences Xiandao B eGPS project (XDB13030100), the National Science Foundation of China microevolution program (NSFC91431102), the 1000 talents program and a Wolfson merit Professorship from the UK Royal Society.

PY - 2018/1

Y1 - 2018/1

N2 - OBJECTIVES: Body fatness is widely assumed to be regulated by a lipostatic set-point system, which has evolved in response to trade-offs in the risks of mortality. Increasing fatness makes the risk of starvation lower but increases the risk of predation. Yet other models are available. The aim of this work is to evaluate using mathematical modeling whether set-point systems are more likely to evolve than the alternatives.METHODS: I modeled the trade-off in mortality risks using a simple mathematical model, which generates an optimum level of fatness that is presumed to be the driver for the evolution of a set-point. I then mimicked the likely errors in this optimum level, that derive from the variation in the component parameters of the mortality curves using Markov Chain Monte Carlo (MCMC) simulation by Bayesian inference Using Gibbs Sampling (BUGS).RESULTS: The error propagation generated by the simulations showed that even very small errors in the model parameters were magnified enormously in the location of the optimum fatness level. If the model parameters had coefficients of variation of just 1% then the coefficient of variation in the optimum level of fatness was between 20 and 90%. In that situation, a set-point centered at the mathematical optimum from the component curves would be at the correct level of fatness that minimizes mortality, and hence maximizes fitness, on less than 8% of occasions.CONCLUSIONS: Set-point regulation of body fatness is hence highly unlikely to evolve where there is any realistic level of variation in the parameters that define mortality risks. Using further MCMC modeling, I show that a dual-intervention point system is more likely to evolve. This mathematical simulation work has important implications for how we interpret molecular work concerning regulation of adiposity.

AB - OBJECTIVES: Body fatness is widely assumed to be regulated by a lipostatic set-point system, which has evolved in response to trade-offs in the risks of mortality. Increasing fatness makes the risk of starvation lower but increases the risk of predation. Yet other models are available. The aim of this work is to evaluate using mathematical modeling whether set-point systems are more likely to evolve than the alternatives.METHODS: I modeled the trade-off in mortality risks using a simple mathematical model, which generates an optimum level of fatness that is presumed to be the driver for the evolution of a set-point. I then mimicked the likely errors in this optimum level, that derive from the variation in the component parameters of the mortality curves using Markov Chain Monte Carlo (MCMC) simulation by Bayesian inference Using Gibbs Sampling (BUGS).RESULTS: The error propagation generated by the simulations showed that even very small errors in the model parameters were magnified enormously in the location of the optimum fatness level. If the model parameters had coefficients of variation of just 1% then the coefficient of variation in the optimum level of fatness was between 20 and 90%. In that situation, a set-point centered at the mathematical optimum from the component curves would be at the correct level of fatness that minimizes mortality, and hence maximizes fitness, on less than 8% of occasions.CONCLUSIONS: Set-point regulation of body fatness is hence highly unlikely to evolve where there is any realistic level of variation in the parameters that define mortality risks. Using further MCMC modeling, I show that a dual-intervention point system is more likely to evolve. This mathematical simulation work has important implications for how we interpret molecular work concerning regulation of adiposity.

KW - mathematical modelling

KW - Body fat regulation

KW - Lipostat

KW - Leptin

KW - Leptin resistance

KW - Feedback control

U2 - 10.1016/j.molmet.2017.10.007

DO - 10.1016/j.molmet.2017.10.007

M3 - Article

VL - 7

SP - 147

EP - 154

JO - Molecular Metabolism

JF - Molecular Metabolism

SN - 2212-8778

ER -