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COMPLEX TIME: Adaptation, Aging, & Arrow of Time

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Difference between revisions of "Hallmarks of Biological Failure/KelleyHarris"

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James challenges the view of aging as random mechanical breakdown in a different way than Barbara does. He mainly focuses on the cancer mode of death and the random accumulation of cancer driver mutations as a particular mechanism of breakdown. In the classical breakdown view of cancer, oncogenes are essentially ticking time bombs that have a constant probability of mutating each time a cell divides. This implies that everyone will eventually get cancer if they live long enough, with an exponentially distribution of ages at incidence. However, James notes that there is no appreciable difference between 20-year-olds and 30-year-olds in their probability of dying of cancer, whereas in the exponential mutation accumulation model, the difference between these age groups should be comparable to the very significant difference between 60- and 70-year-olds. To explain this violation of the simple exponential health decay model, James proposes that a breakdown in the cellular environment occurs during middle age that allows precancerous cells to proliferate in a way the same cells cannot do in younger tissues.
 
James challenges the view of aging as random mechanical breakdown in a different way than Barbara does. He mainly focuses on the cancer mode of death and the random accumulation of cancer driver mutations as a particular mechanism of breakdown. In the classical breakdown view of cancer, oncogenes are essentially ticking time bombs that have a constant probability of mutating each time a cell divides. This implies that everyone will eventually get cancer if they live long enough, with an exponentially distribution of ages at incidence. However, James notes that there is no appreciable difference between 20-year-olds and 30-year-olds in their probability of dying of cancer, whereas in the exponential mutation accumulation model, the difference between these age groups should be comparable to the very significant difference between 60- and 70-year-olds. To explain this violation of the simple exponential health decay model, James proposes that a breakdown in the cellular environment occurs during middle age that allows precancerous cells to proliferate in a way the same cells cannot do in younger tissues.
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Morgan's work on the epigenetic clock outlines one way in which aged tissues are different from young tissues ''en masse''. She has identified a set of CpG sites that are differentially methylated between young and old individuals and whose methylation state predicts mortality slightly better than calendar age does. From her presentation, I couldn't tell whether young individual had less variation in methylation status than old individuals at these sites. In other words, does aging cause decay from a deterministic methylation state toward a random state, or does it look more like a programmed transition from one state to another? To the extent that methylation is decaying toward a random state, mechanical breakdown seems like a better analogy, but if the aged state is as low-variance as the young state, programmed developmental transition seems closer to what's going on.
 
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Latest revision as of 19:24, April 10, 2019

Notes by user Kelley Harris (Univ. Washington) for Hallmarks of Biological Failure

Post-meeting Reflection

1+ paragraphs on any combination of the following:

  • Presentation highlights
  • Open questions that came up
  • How your perspective changed
  • Impact on your own work
  • e.g. the discussion on [A] that we are having reminds me of [B] conference/[C] initiative/[D] funding call-for-proposal/[E] research group

Meeting participants have had some productive disagreement about what exactly defines aging. Is it the entirety of the change that occurs between birth and death or perhaps beyond, or just a subset of the changes that occur during one's life? Two main categories of change occur during life: one category is a sequence of programmed developmental milestones including embryogenesis, puberty and menopause. In semelparous species, even death can be viewed as a programmed developmental milestone. Another category of change is deleterious degradation of function, manifesting as cancer, heart disease, weakening of physical strength and life-sustaining activity such as predation, and even increased susceptibility to infectious disease. Some, including Roz, argue that only the second category of change should really be called aging. However, it can be hard to prove that any type of age-related decline is truly random rather than programmed.

In the classical view of aging as the breaking down of the body, participants make use of analogies involving the breakdown of man-made machines, e.g. the failure of a one-horse shay or Henry Ford Model T. The one-horse shay is a machine rooted in folklore that is perfectly efficient because all components fail at once. To the extent that human bodies fail to disintegrate at once like the one-horse shay, are we maladaptively wasting resources on our slower-to-fail organs? Or is longevity more of a neutral side effect of evolving bodies that are robust to the challenges we may encounter during our reproductive lifespans?

Barbara's work challenges the mechanical breakdown view of aging by comparing physiology between species and showing that age-related "degradation" can sometimes be an adaptive response to a stress that can in theory occur at any age. For example, age-related thickening of the heart ventricle is a rampant cause of human death today, but it is physiologically rooted in a type of phenotypic plasticity that can help a young animal adapt to high blood pressure and still live to reproduce. This suggests that when we die of old age, we are dying of the most severe negatively pleiotropic side effects that inevitably accompany adaptations that outweigh the cost of dying in middle or old age.

James challenges the view of aging as random mechanical breakdown in a different way than Barbara does. He mainly focuses on the cancer mode of death and the random accumulation of cancer driver mutations as a particular mechanism of breakdown. In the classical breakdown view of cancer, oncogenes are essentially ticking time bombs that have a constant probability of mutating each time a cell divides. This implies that everyone will eventually get cancer if they live long enough, with an exponentially distribution of ages at incidence. However, James notes that there is no appreciable difference between 20-year-olds and 30-year-olds in their probability of dying of cancer, whereas in the exponential mutation accumulation model, the difference between these age groups should be comparable to the very significant difference between 60- and 70-year-olds. To explain this violation of the simple exponential health decay model, James proposes that a breakdown in the cellular environment occurs during middle age that allows precancerous cells to proliferate in a way the same cells cannot do in younger tissues.

Morgan's work on the epigenetic clock outlines one way in which aged tissues are different from young tissues en masse. She has identified a set of CpG sites that are differentially methylated between young and old individuals and whose methylation state predicts mortality slightly better than calendar age does. From her presentation, I couldn't tell whether young individual had less variation in methylation status than old individuals at these sites. In other words, does aging cause decay from a deterministic methylation state toward a random state, or does it look more like a programmed transition from one state to another? To the extent that methylation is decaying toward a random state, mechanical breakdown seems like a better analogy, but if the aged state is as low-variance as the young state, programmed developmental transition seems closer to what's going on.

Reference material notes

Some examples:

  • Here is [A] database on [B] that I pull data from to do [C] analysis that might be of interest to this group (insert link).
  • Here is a free tool for calculating [ABC] (insert link)
  • This painting/sculpture/forms of artwork is emblematic to our discussion on [X]!
  • Schwartz et al. 2017 offers a review on [ABC] migration as relate to climatic factors (add the reference as well).

Reference Materials