Evolution of the rate of biological aging using a phenotype based computational model

Area of Science:

• Evolutionary biology
• Gerontology
• Population dynamics

Background:

• Aging is a fundamental biological process influenced by evolutionary pressures.
• Understanding the interplay between natural selection, mutation, and aging is crucial for evolutionary and demographic studies.

Purpose of the Study:

• To introduce a simplified model investigating how natural selection affects aging based on individual viability.
• To explore the relationship between mutation rates, age at reproductive maturity, and the progression of biological aging.

Main Methods:

• Development of a simple population model focusing on individual viability.
• Analysis of the model's ability to reproduce the Gompertz law of mortality.
• Simulation of varying mutation rates (beneficial, deleterious, neutral) and their impact on population dynamics.

Main Results:

• The model reproduces the Gompertz law of mortality.
• Age at reproductive maturity (R) influences population density stabilization, with low R populations stabilizing at higher densities without mutations.
• Mutation probabilities (P(d), P(b)) and their ratio significantly affect aging speed and population survival, with high R favoring species under certain mutation conditions.

Conclusions:

• Aging is a complex process influenced by the balance of mutation types and selection pressures.
• The age at reproductive maturity (R) is a critical factor for population survival.
• Neutral mutations provide evolutionary flexibility, allowing systems more room to adapt.