Life Fast, Die Young: The Evolution of Aging

Originally posted on the LIFE Apps science blog…

By Jordan Pennells

To take care of your health is to delay the inevitable biological deterioration of your body, to fight against the unyielding aging process. But there’s another way to view the process of aging, if we expand the time frame from an individual’s lifetime to evolutionary time.

It’s clear that looking after your health and fitness will improve your evolutionary fitness: your likelihood for reproductive success. It’s also clear that aging has a significant effect on your reproductive success; a shorter lifespan gives you less time to reproduce, alongside side-effects such as diminished physical flexibility and menopause. So, if aging has such a profound effect on evolutionary fitness, why hasn’t the process been wiped out completely by natural selection? Why haven’t we evolved towards immortality?

Your body’s cells get “worn out” over time due to oxidative stress from metabolic by-products and the breakdown of cellular signaling. However, these mechanistic contributions to aging over an individual’s lifetime are “proximate” causes of disease, distinct from the “ultimate” evolutionary causes of aging. That’s like saying that (*insert favorite sports team*) lost the game because they didn’t score enough goals/points. But why? Maybe they came out too hard at the start of the match and ran out of gas towards the end, because they knew the other team were fast-starters and needed to counteract this.

While this apparent paradox has puzzled evolutionary biologists for decades, we now have a few models that explain it.

“While medical practitioners and public health specialists are familiar with the proximate causes of disease, that is, the physiological basis of how they develop, an understanding of the general principles of evolutionary medicine would assist in gaining a fuller understanding and appreciation of why human diseases arise—that is, the ultimate causes.” – Gluckman et al., 2011

The Mutation Accumulation Model of Aging

There’s a reason that early-onset mutations are rare. Genetic diseases that affect children and young adults are reduced to a very low frequency within the population because they severely impact fitness and reproductive capability. However, natural selection is relatively “blind” to late-onset mutations (like those that contribute to neurodegenerative diseases) that contribute to aging. Once an individual has reproduced, they have fulfilled their evolutionary goal. Inherited genetic mutations that take effect and impact their health in later life aren’t selected against with their offspring.

To test this model, researchers devised a study on two populations of fruit flies to determine if one would live longer if they were experimentally selected to breed at a young or old life stage. After many generations of breeding each population separately, the results showed that older-reproducing flies were able to delay aging and had a longer lifespan (Rose & Charlesworth, 1981).

But why? The answer lies in the fact that counteracting the process of aging was under strong positive selection in the old-reproducing population of fruit flies, as they needed to survive until the point of reproduction being granted to them. Aging isn’t a factor when you reproduce early, on the other hand.

Mating of Drosophila couple. Credit: DERO2084
Mating of Drosophila couple. Credit: DERO2084

While Mutation Accumulation is a passive mechanism that explains how evolution condones the enrichment of late-acting mutations that accelerate the process of aging, an extrapolation of this model shows us how late-acting mutations could be actively selected for.

Antagonistic Pleiotropy (AP) Model of Aging

Generally speaking, antagonistic pleiotropy is a genetic phenomenon that refers to a gene/mutation that positively affects one trait while negatively affecting another trait that contributes to an organism’s fitness. Think about it like buying a new car. You might purchase a flashy new sports car that goes from 0-100km/h in 2.7 seconds, extremely enjoy the thrill and maybe catch the eye of some prospective partners in the process. But the acceleration and speed this car possesses may consequently lower the safety of the driver.

In the context of aging, the AP model holds that deleterious late-onset mutations are more likely to accumulate in the population if they are beneficial in early life; for example, a gene that increases reproductive rate at the cost of cellular maintenance later in life (Medawar, 1952). The AP model of aging may explain several late-onset human diseases, including:

  1. High levels of testosterone production that increase sex drive and reproductive success in young men, but is associated with an increased risk of prostate cancer in later life (Gann et al., 1996)
  2. Huntington’s disease, a severe late-onset neurodegenerative condition that has also been characterized by a decreased risk of certain types of cancers and increased fertility in earlier life (Eskenazi et al., 2007)
  3. A mutation (ALOX15) that was found to increase the efficiency of bone remodeling during youth but becomes dysfunctional later in life and is associated with osteoporosis severity (Carter & Nguyen, 2011)

Further development of these models underpinning the evolution of aging elucidated that there is a fundamental balance that must be struck for allocation of finite resources between cellular maintenance and sexual reproduction.

“In their natural environment, animals do not survive environmental hazards (predators, disease, starvation, and drought) to reach a long life span. There is thus a trade-off between the investment of resources in reproduction, and the survival time of the soma. At a stroke, this solves the problem of different rates of aging in different species, because those that develop and reproduce fast also have short life spans, and those that develop and reproduce slowly have long life spans. […] There is now much evidence that long-lived mammals have much more efficient maintenance mechanisms than short-lived mammals. Thus, aging can be defined as the eventual failure of maintenance. […] aging cannot be reversed, although it may be modulated, as, for example, by calorie restriction.” – Aging is No Longer an Unsolved Problem in Biology, 2006

Disposable Soma Model of Aging

This model of aging states that a finite amount of nutrients can be extracted from the food we eat and the environment we live in, which must be allocated effectively to optimize our evolutionary fitness (Kirkwood, 1977). In nature, reproduction is energetically costly and risky for survival. There are time, energy and monetary (for humans) costs of searching for a viable partner. There are disease risks when interacting with others as well as mating injury risks that must be considered, including the strange phenomenon of female consumption of unsuspecting males post-copulation, or more relevantly domestic violence for humans.

Based on this model of aging, species that experience a higher extrinsic mortality rate (i.e. high levels of predation or a harsher environment – nutrient scarcity and extreme weather) will exhibit reproduction-centric adaptation. To visualize this idea, consider two mammals with similar body weights but very different lifespans: mice and bats. [Check out a plot of longevity vs body weight for a range of animals here.]

Bats are unusually long-lived for their body weight. Credit: CraigRJD

Mice will typically expend their energy reproducing at the earliest possible stage before they die or are killed. This occurs at the expense of cellular maintenance later in life. The latter isn’t much of an evolutionary concern because of the likelihood that mice will have been killed before they reach late life anyway. Mice having an average lifespan of 2-3 years (even when taken out of the wild and grown in a controlled environment).

Meanwhile, bats have very few natural predators. They have much lower selection pressure to reproduce as soon as possible early in life, but rather have evolved their genetic machinery to allocate resources towards survival, having an average lifespan of approximately 30 years! [Editor’s DYK: Bats are also resistant or immune to many viruses that are deadly to humans, like Ebola.]

The ‘Live Fast, Die Young’ Experiment

To attract potential partners, male crickets rub their hind legs against their abdomen to produce a mating call that we have become accustomed to hearing in the evenings. This call is not only metabolically costly, but alerts the presence of male crickets to predators. A Nature study (Hunt et al., 2004) found that male crickets ‘live fast and die young’. The energy-intensive night calling efforts of male crickets result in lower longevity even in the absence of predation. However, if this resource allocation results in finding a mate to reproduce with, this represents a successful strategy and their shorter lifespan becomes evolutionarily beneficial!

“[N]ymphs and adult females [field crickets] reared on a high-protein diet lived longer than those on a low-protein diet. In contrast, adult males reared on a high-protein diet died sooner than those on low-protein diets because they invested more energy in calling during early adulthood. Our findings uphold the theoretical prediction that the relationship between longevity and sexual advertisement may be dynamic (that is, either positive or negative), depending on local conditions such as resource availability.” – High-quality male field crickets invest heavily in sexual display but die young, 2004

Moving forward, evolutionary medicine has the potential to deepen our understanding of disease development and prevention, by combining individual genetic information with broad evolutionary hypotheses.

“Coupled with complementary insights offered by advances in genomic, epigenetic, and developmental biology research, evolutionary perspectives offer an important addition to understanding disease.” – How evolutionary principles improve the understanding of human health and disease, 2011

References:

Austad, S. N. (2005). Diverse aging rates in metazoans: targets for functional genomicsMechanisms of Ageing and Development, 126(1), 43-49. doi.org/10.1016/j.mad.2004.09.022

Carter, A. J., & Nguyen, A. Q. (2011). Antagonistic pleiotropy as a widespread mechanism for the maintenance of polymorphic disease allelesBMC Medical Genetics, 12(1), 160. doi:10.1186/1471-2350-12-160

Eskenazi, B. R., Wilson-Rich, N. S., & Starks, P. T. (2007). A Darwinian approach to Huntington’s disease: Subtle health benefits of a neurological disorderMedical Hypotheses, 69(6), 1183-1189. doi.org/10.1016/j.mehy.2007.02.046

Gann P.H.; Hennekens C.H.; Ma J.; Longcope C.; Stampfer M.J. (1996). Prospective Study of Sex Hormone Levels and Risk of Prostate CancerJournal of the National Cancer Institute. 88(16), 1118–1126. doi.org/10.1093/jnci/88.16.1118

Gluckman, P. D., Low, F. M., Buklijas, T., Hanson, M. A., & Beedle, A. S. (2011). How evolutionary principles improve the understanding of human health and diseaseEvolutionary Applications4(2), 249–263. doi.org/10.1111/j.1752-4571.2010.00164.x

Hunt, J., Brooks, R., Jennions, M.D., Smith, M.J., Bentsen, C.L., & Bussière, L.F. (2004). High-quality male field crickets invest heavily in sexual display but die youngNature, 432, 1024-1027. doi.org/10.1038/nature03084

Kirkwood, T. B. L. (1977). Evolution of ageing. Nature, 270, 301. doi:10.1038/270301a0

Medawar P.B. (1952). An Unsolved Problem of Biology. 1970, London: H.K. Lewis & Co

Rose, M. R., & Charlesworth, B. (1981). Genetics of Life History in DROSOPHILA MELANOGASTER. II. Exploratory Selection Experiments. Genetics, 97(1), 187–196.

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