Can Aging Develop as an Adaptation to Optimize Natural Selection? (Application of Computer Modeling for Searching Conditions When the “Fable of Hares” Can Explain the Evolution of Aging)

Марков, А. В.; Barg, Mike‐Christoph; Yakovleva, Ekaterina

doi:10.1134/s0006297918120088

Cited by 10 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…AR does not evolve for the sake of accelerating the evolution of other traits (aging is not an adaptation for faster adaptive evolution). Modeling did not confirm that aging can evolve as means to accelerate the evolution of other adaptive traits [67]. The point is that the rate of aging is itself an important adaptive trait that is under the direct and very strict control of natural selection.…”

Section: Discussionmentioning

confidence: 94%

Coevolution of Brain, Culture, and Lifespan: Insights from Computer Simulations

Марков

Markov

2021

Biochemistry Moscow

View full text Add to dashboard Cite

Humans possess a number of traits that are rare or absent in other primates, including large brain size, culture, language, extended lifespan (LS), and long post reproductive period. Here, we use a computer model, TribeSim, originally designed to explore the autocatalytic coevolution of the hominin brain and culture within the framework of the "cultural drive" theory, to find out how culture and brain could coevolve with LS (or aging rate). We show that in the absence of cul ture, the evolution of LS depends on the intensity of the between group competition (BGC): strong BGC results in shorter LS. Culture, however, favors genetic evolution of longer LS even if the BGC is strong. Extended LS, in turn, enhances cul tural development, thus creating positive feedback. Cultural evolution of LS (accumulation of survival enhancing or sur vival impairing knowledge) differs from the genetic evolution of the same trait, partially because "memes" (ideas, skills, and behaviors) that reduce the risk of death tend to spread in the meme pool even if it is not beneficial to genes. Consequently, cultural evolution of aging tends to result in longer LS than genetic evolution of the same trait. If LS evolves both geneti cally and culturally, the typical result is a society in which young individuals, due to their genetic predisposition, lead a riski er lifestyle in exchange for a chance to gain additional resources, but accumulate survival enhancing knowledge with age. Simulations also showed that cultural evolution of adaptive behaviors can contribute to the genetic evolution of a long post reproductive period, e.g., if the presence of knowledgeable long livers increases the competitiveness of the group.

show abstract

Section: Discussionmentioning

confidence: 94%

Coevolution of Brain, Culture, and Lifespan: Insights from Computer Simulations

Марков

Markov

2021

Biochemistry Moscow

View full text Add to dashboard Cite

show abstract

“…In fact, accelerated senescence may increase the effect of genetic drift in response to non-relevant evolutionary challenges and so reduce genetic variability essential for further evolution. Models of accelerated evolution are not convincing as they typically consider only a single selective factor [ 33 , 124 , 151 ]. In natural populations, individuals are exposed to multiple selective pressures.…”

Section: Acceleration Of Evolutionmentioning

confidence: 99%

Is Aging an Inevitable Characteristic of Organic Life or an Evolutionary Adaptation?

Lidsky

Yuan

Rulison

et al. 2022

Biochemistry Moscow

View full text Add to dashboard Cite

Aging is an evolutionary paradox. Several hypotheses have been proposed to explain it, but none fully explains all the biochemical and ecologic data accumulated over decades of research. We suggest that senescence is a primitive immune strategy which acts to protect an individual’s kin from chronic infections. Older organisms are exposed to pathogens for a longer period of time and have a higher likelihood of acquiring infectious diseases. Accordingly, the parasitic load in aged individuals is higher than in younger ones. Given that the probability of pathogen transmission is higher within the kin, the inclusive fitness cost of infection might exceed the benefit of living longer. In this case, programmed lifespan termination might be an evolutionarily stable strategy. Here, we discuss the classical evolutionary hypotheses of aging and compare them with the pathogen control hypothesis, discuss the consistency of these hypotheses with existing empirical data, and present a revised conceptual framework to understand the evolution of aging. Electronic supplementary material The online version contains supplementary material available at 10.1134/S0006297922120021.

show abstract

“…Another theory proposed that genetic basis of aging is adapted to optimize evolutionary passage of selection. By computer modeling (Markov et al, 2018), it was proposed that intrinsic decline of some physiological processes enhances efficacy of natural choices for other processes too. However, they could not elaborate the mechanisms that warrant the spread and sustenance of age-related genes.…”

Section: Computational Modelsmentioning

confidence: 99%

Aging - Oxidative stress, antioxidants and computational modeling

Warraich

Hussain

Kayani

2020

Heliyon

102

View full text Add to dashboard Cite

Aging is a degenerative, biological, time-dependent, universally conserved process thus designed as one of the highest known risk factors for morbidity and mortality. Every individual has its own aging mechanisms as both environmental conditions (75%) and genetics (25%) account for aging. Several theories have been proposed until now but not even a single theory solves this mystery. There are still some queries un-answered to the scientific community regarding mechanisms behind aging. However, oxidative stress theory (OST) is considered one of the famous theories that sees mitochondria as one of the leading organelles which largely contribute to the aging process. Many reactive oxygen species (ROS) are produced endogenously and exogenously that are associated with aging. But the mitochondrial ROS contribute largely to the aging process as mitochondrial dysfunction due to oxidative stress is considered one of the contributors toward aging. Although ROS is known to damage cell machinery, new evidence suggests their role in signal transduction to regulate biological and physiological processes. Moreover, besides mitochondria, other important cell organelles such as peroxisome and endoplasmic reticulum also produce ROS that contribute to aging. However, nature has provided humans with free radical scavengers called antioxidants that protect from harmful effects of ROS. Future predictions regarding aging, biochemical mechanisms involved, biomarkers internal and external factors can be easily done with machine learning algorithms and other computational models. This review explains important aspects of aging, the contribution of ROS producing organelles in aging, importance of antioxidants fighting against ROS, different computational models developed to understand the complexities of the aging.

show abstract

Can Aging Develop as an Adaptation to Optimize Natural Selection? (Application of Computer Modeling for Searching Conditions When the “Fable of Hares” Can Explain the Evolution of Aging)

Cited by 10 publications

References 8 publications

Coevolution of Brain, Culture, and Lifespan: Insights from Computer Simulations

Coevolution of Brain, Culture, and Lifespan: Insights from Computer Simulations

Is Aging an Inevitable Characteristic of Organic Life or an Evolutionary Adaptation?

Aging - Oxidative stress, antioxidants and computational modeling

Contact Info

Product

Resources

About