Numerical solution of the Penna model of biological aging with age-modified mutation rate

Magdon-Maksymowicz, Maria Stanislawa; Maksymowicz, A.Z.

doi:10.1103/physreve.79.061919

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…Let us mention some examples of the many possible variations of the Penna model. Fluctuations in T, which come from mutations already activated at birth time (Maksymowicz 1999); a learning process which gives an advantage in the life game for more intelligent individuals (He and Pan 2005;He et al 2006); tracing back history to prove divergent evolution paths of different species, which may lead in the evolution process to severe reduction of number of the species (Sitarz and Maksymowicz 2005), birth rate B controlled by already active deleterious mutations (Magdoń-Maksymowicz 2008), and mutation rate M varying with parent's age a (Magdoń- Maksymowicz and Maksymowicz 2009)-they all are based on the Penna model. Also, simple classifications of mutations as deleterious or beneficial may not be so simple as the role and significance of mutations may change with age, showing antagonistic pleiotropy (Westendorp and Kirkwood 1998;Gavrilov and Gavrilova 1999).…”

Section: Introductionmentioning

confidence: 99%

Epigenetic contribution to age distribution of mortality within the Penna model

Magdon-Maksymowicz¹,

Maksymowicz²

2015

Theory Biosci.

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Some modifications of the simple asexual Penna model, enriched by epigenetic contributions, are presented. The standard bit-string Penna model of biological aging and population evolution is based on an inherited DNA structure which defines the future life of a newly born individuals, when genes are activated by the biological clock, and the predefined genetic death is fully controlled by the number of defected genes. Epigenomes allow to introduce additional mechanism of gene activation or silencing without affecting the DNA genome itself. It may be either inherited or may reflect external, environmental factors. In the presented model, information read from the introduced epigenome may alter gene expression that may be stopped or re-activated. We concentrate on the influence of epigenetics on the age a distribution of genetic mortality m(a). Changes in m(a) are strong for the case of inherited epigenetic contribution with nearly perfect inheritance and 'positive' epigenome that partly ignores the 'bad' mutations. We conclude that the epigenetic contribution may influence population structure m(a) and could be, at least partly, responsible for deviation of m(a) distribution from the Gompertz law. In short, we claim that proposed epigenetic contribution may be seen as a candidate for possible explanation of observed deviation from the Gompertz law, also among senior members of society. A very simple model was used in this paper and many crucial mechanisms of biological aging were omitted. Therefore, further work based on a more realistic models is necessary.

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Section: Introductionmentioning

confidence: 99%

Epigenetic contribution to age distribution of mortality within the Penna model

Magdon-Maksymowicz¹,

Maksymowicz²

2015

Theory Biosci.

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Greater organ involution in highly proliferative tissues associated with the early onset and acceleration of ageing in humans

Richardson

Allan

2014

Experimental Gerontology

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Domination of cell proliferation over cell death is a driving force for carcinogenesis, whereas reduced cell proliferation and increased cell death are characteristic of ageing. We employed published data to estimate representative mean values of cell turnover times for 31 different organs and tissues in adult humans and animals (when data in humans were lacking) as well as functional mass loss for 5 organs, accounting for actual mass loss and tissue conversion to fat, in humans over the adult period, age 25 to 70. We found that greater actual and functional mass loss was significantly associated (P=0.001 and P<0.0001, respectively) with the log of shorter cell turnover times. We propose that this is characteristic of stem cell exhaustion and replicative senescence. In addition, we provide quantitative evidence that, in many organs, involution is evident even in young adults. On the basis of published mass measurements of major organs, by analysis of covariance, we identified examples of significant (P≤0.05), accelerated actual or functional mass loss and ageing from early to late adulthood. We hypothesise and quantitatively demonstrate that functional mass loss accelerates with ageing by incorporating the contribution of actual mass loss, tissue conversion to fatty or fibrous tissue, and the presence of apoptotic, necrotic and senescent cells. We propose that mass loss, linked to replicative senescence, is an evolutionary adaptation that effectively limits cancer in young adults, as mass loss is first apparent soon after the end of the growth period, accelerating in the more elderly as biological conditions deviate away from those prevailing in youth, when the selective pressure on pleiotropic genes is greatest.

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Numerical solution of the Penna model of biological aging with age-modified mutation rate

Cited by 2 publications

References 16 publications

Epigenetic contribution to age distribution of mortality within the Penna model

Epigenetic contribution to age distribution of mortality within the Penna model

Greater organ involution in highly proliferative tissues associated with the early onset and acceleration of ageing in humans

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