Model Of Biological Aging Research Articles

The sex-specific life expectancy and the influence of testosterone in a mathematical aging simulation model and its consequences for prevention

There are many explanations for the sex-specific difference in life expectancy. An important reason for this difference can be found in the genome difference of one sex chromosome. It is obvious that testosterone, as an effective hormonal product of this genome difference, influences not only morphology, physiology and risk profiles of diseases but also social behavior and lifestyle. Statistical simulations are, for physicians, an unusual way to demonstrate differences in human mortality, but they may help to show other, and more abstract, aspects of nature. The Penna model of biological aging is a well-established model for simulating the influence of genetic factors on sex-specific mortality. In this study, the Penna model is explained and modified to take into account the potentially detrimental effects of testosterone on male mortality. This is achieved by a modification of the Verhulst factor, starting with male puberty. We demonstrated that about one-third of the sex-specific difference in life expectancy may be caused by the influence of testosterone in this mathematical aging model. These results do not show that male vices (smoking, drinking, risk-taking behavior, etc.) can be attributed only to testosterone even though it may appear so from the statistics. There are some correlations but not causal relations. It seems, even from the view of a mathematical–statistical simulation, that males are discriminated against regarding mortality and life expectancy. This underlines the need for sex-specific research, social policy and preventive programs (e.g. sports, nutrition) for minimizing the negative impact of male-specific genetic and hormonal factors.

An unusual antagonistic pleiotropy in the Penna model for biological ageing

We combine the Penna Model for biological ageing, which is based on the mutation-accumulation theory, with a sort of antagonistic pleiotropy. We show that depending on how the pleiotropy is introduced, it is possible to reproduce both the humans mortality, which increases exponentially with age, and fruitfly mortality, which decelerates at old ages, allowing the appearance of arbitrarily old Methuselah's.

Justification of sexual reproduction by modified Penna model of ageing

We generalize the standard Penna bit-string model of biological ageing by assuming that each deleterious mutation diminishes the survival probability in every time interval by a small percentage. This effect is added to the usual lethal but age-dependent effect of the same mutation. We then find strong advantages or disadvantages of sexual reproduction (with males and females) compared to asexual cloning, depending on parameters.

Stochastic Penna model for biological aging

A stochastic genetic model for biological aging is introduced bridging the gap between the bit-string Penna model and the Pletcher-Neuhauser approach. The phenomenon of exponentially increasing mortality function at intermediate ages and its deceleration at advanced ages is reproduced for both the evolutionary steady-state population and the genetically homogeneous individuals.

Stochastic Penna model for biological aging

A stochastic genetic model for biological aging is introduced bridging the gap between the bit-string Penna model and the Pletcher-Neuhauser approach. The phenomenon of exponentially increasing mortality function at intermediate ages and its deceleration at advanced ages is reproduced for both the evolutionary steady-state population and the genetically homogeneous individuals.

The sex-specific life expectancy and the influence of testosterone in a mathematical aging simulation model and its consequences for prevention

There are many explanations for the sex-specific difference in life expectancy. An important reason for this difference can be found in the genome difference of one sex chromosome. It is obvious that testosterone,as an effective hormonal product of this genome difference, influences not only morphology, physiology and risk profiles of diseases but also social behavior and lifestyle. Statistical simulations are,for physicians, an unusual way to demonstrate differences in human mortality, but they may help to show other, and more abstract, aspects of nature.The Penna model of biological aging is a well-establishedmodel for simulating the influence of genetic factors on sex-specific mortality. In this study, the Penna model is explained and modified to take into account the potentially detrimental effects of testosteroneon male mortality. This is achieved by a modification of the Verhulst factor, starting with male puberty. We demonstrated that about one-third of the sex-specific difference in life expectancy may be causedby the influence of testosterone in this mathematical aging model. These results do not show that male vices (smoking, drinking, risk-taking behavior, etc.) can be attributed only to testosterone even thoughit may appear so from the statistics. There are some correlations but not causal relations. It seems, even from the view of a mathematical–statistical simulation, that males are discriminated againstregarding mortality and life expectancy. This underlines the need for sex-specific research, social policy and preventive programs (e.g. sports, nutrition) for minimizing the negative impact of male-specificgenetic and hormonal factors.

Diagnosing Aging: I. Problem of Reliability of Linear Regression Models of Biological Age

The problem of the reliability of linear regression models of biological age assessment was studied using an experimental population of patients of a geroprophylactic center. The main factors of the model quality (interpopulation difference, method of approximation of biological age, and methods of approximation of statistical significance of parameters of biological age models) were tested. New equations were derived for calculating biological age. All parameters of these equations meet the requirements of significance. It was shown that if the nonlinear character of age dynamics of biological markers of aging and the statistical significance of model parameter estimates are taken into account, the model of biological age is substantially simplified and its reliability increases.

Penna model of biological aging on a lattice

The Penna bit-string model of biological aging is implemented on a square lattice. Hence, there is no need to manipulate the population size by the Verhulst factor. Instead, the spatial lattice relations between neighboring individuals are considered. Mortality obtained in the lattice asexual Penna model is different from the corresponding feature of the standard Penna model.

SELECTION EXPERIMENTS IN THE PENNA MODEL FOR BIOLOGICAL AGING

We consider the Penna model for biological aging to investigate correlations between early fertility and late life survival rates in populations at equilibrium. We consider inherited initial reproduction ages together with a reproduction cost translated in a probability that mother and offspring die at birth, depending on the mother age. For convenient sets of parameters, the equilibrated populations present genetic variability in what regards both genetically programmed death age and initial reproduction age. In the asexual Penna model, a negative correlation between early life fertility and late life survival rates naturally emerges in the stationary solutions. In the sexual Penna model, selection experiments are performed where individuals are sorted by initial reproduction age from the equilibrated populations and the separated populations are evolved independently. After a transient, a negative correlation between early fertility and late age survival rates also emerges in the sense that populations that start reproducing earlier present smaller average genetically programmed death age. These effects appear due to the age structure of populations in the steady state solution of the evolution equations. We claim that the same demographic effects may be playing an important role in selection experiments in the laboratory.

SCALING IN A CONTINUOUS TIME MODEL FOR BIOLOGICAL AGING

In this paper, we consider a generalization to the asexual version of Penna model for biological aging, where we take a continuous time limit. The genotype associated to each individual is an interval of real numbers over which Dirac δ-functions are defined, representing genetically programmed diseases to be switched on at defined ages of the individual life. We discuss two different continuous limits for the evolution equation and two different mutation protocols, to be implemented during reproduction. Exact stationary solutions are obtained and scaling properties are discussed.

Evolution and ageing

The idea of this review is to connect the different models of evolution to those of biological ageing through Darwin's theory. We start with the Eigen model of quasispecies for microevolution, then introduce the Bak–Sneppen model for macroevolution and, finally, present the Penna model for biological ageing and some of its most important results. We also explore the concept of coevolution using this model.

Simulating inbreeding depression through the mutation accumulation theory

Using the Penna model for biological aging, which is based on the mutation accumulation theory, we show that the number of homozygous loci corresponding to deleterious mutations is higher in small populations than in large ones. This decrease of heterozygosity may drive small populations to extinction even when no drastic change of the environment occurs.

SEARCHING FOR SCALING IN THE PENNA BIT-STRING MODEL OF BIOLOGICAL AGING

In this paper the Penna bit-string model of biological aging with different lengths of bit-strings genome is considered. We show from computer simulation that changes in genome length may be crucial for determining population characterization and seem to be irreversible by scaling the other model control parameters.

Penna ageing model and improvement of medical care in 20th century

In Penna's model for biological ageing we reduce after equilibration the influence of acquired diseases and get, similar to reality, the observed increase of the Gompertz slope for the human mortality curves.

The Eve effect in the Penna model of biological ageing

In the present work we qualify and quantify the process of extinction of family diversity in Penna asexual model. To qualitatively characterize irregularity of landscapes of time series we apply the methods proposed by Peng et al. [Phys. Rev. Lett. 70 (1993) 1343, Chaos 5 (1995) 82]. We have found that the fluctuations of the volume of the total population scales as 1/ f noise while the volume of a family perform the Brownian motion. This observation allows us to propose a model where the “Eve” effect is absent. We also consider the difference equations for which the effect is present.

Consequences of parental care on population dynamics

We review the results obtained using the Penna model for biological ageing (T.J.P. Penna, J. Stat. Phys. 78 (1995) 1629) when different strategies of parental care are introduced into evolving populations. These results concern to: longevity of semelparous populations; self-organization of female menopause; the spatial distribution of the populations and finally, sexual fidelity.

PROBABILISTIC GENERALIZATION OF PENNA AGEING MODEL AND THE OLDEST OLD

Using a 1995 method of Thoms et al., the traditional Penna model of biological ageing is modified such that there is no more absolute maximum life span; instead, our Monte Carlo data are similar to real demographic data collected by Thatcher et al., for rich countries.

High reproduction rate versus sexual fidelity

We introduce fidelity into the bit-string Penna model for biological ageing and study the advantage of this fidelity when it produces a higher survival probability of the offspring due to paternal care. We attribute a lower reproduction rate to the faithful males but a higher death probability to the offspring of non-faithful males that abandon the pups to mate other females. The fidelity is considered as a genetic trait which is transmitted to the male offspring (with or without error). We show that nature may prefer a lower reproduction rate to warrant the survival of the offspring already born.

VIRGINIA OPOSSUMS, MINIMUM REPRODUCTION AGE AND PREDATORS IN THE PENNA AGING MODEL

Age-specific predators are introduced into the Penna model of biological aging. It is shown that populations with a variable minimum reproduction age find a stable state with an earlier onset of reproduction, if older ages are eaten by the predators. This behavior agrees with the demographic data of the Virgina opossum.

The Penna model for biological ageing on a lattice: spatial consequences of child-care

We introduce a square lattice into the Penna bit-string model for biological ageing and study the evolution of the spatial distribution of the population considering different strategies of child-care. Two of the strategies are related to the movements of a whole family on the lattice: in one case the mother cannot move if she has any child younger than a given age, and in the other case if she moves, she brings these young children with her. A stronger condition has also been added to the second case, considering that young children die with a higher probability if their mothers die, this probability decreasing with age. We show that a highly non uniform occupation can be obtained when child-care is considered, even for an uniform initial occupation per site. We also compare the standard survival rate of the model with that obtained when the spacial lattice is considered (without any kind of child-care).