Hacking Aging


What would you say if I told you that aging happens not because of accumulation of stresses, but rather because of the intrinsic properties of the gene network of the organism? I’m guessing you’d be like: o_0.

So, here’s the deal. My biohacker friends led by Peter Fedichev and Sergey Filonov in collaboration with my old friend and the longevity record holder Robert Shmookler Reis published a very cool paper. They proposed a way to quantitatively describe the two types of aging – negligible senescence and normal aging. We all know that some animals just don’t care about time passing by. Their mortality doesn’t increase with age. Such negligibly senescent species include the notorious naked mole rat and a bunch of other critters like certain turtles and clams to name a few. So the paper explains what it is exactly that makes these animals age so slowly – it’s the stability of their gene networks.

What does network stability mean then? Well, it’s actually pretty straightforward – if the DNA repair mechanisms are very efficient and the connectivity of the network is low enough, then this network is stable. So, normally aging species, such as ourselves, have unstable networks. This is a major bummer by all means. But! There is a way to overcome this problem, according to the proposed math model.

The model very generally describes what happens with a gene network over time – the majority of the genes are actually working perfectly, but a small number doesn’t. There are repair mechanisms that take care of that. Also, there are mechanisms that take care of defected proteins like heat shock proteins, etc. Put together all of this in an equasion and solve it, and bam! here’s an equasion that gives you the Gompertz law for all species that have normal aging, and a time independent constant for the negligibly senescent ones.

What’s the difference between those two aging regimes? The model suggests it’s the right combination of DNA repair efficiency and the combined efficiency of proteolysis and heat shock response systems, mediating degradation and refolding of misfolded proteins. So, it’s not the the accumulation of damages that is responsible for aging, but rather the properties of the gene network itself. The good news is that even we are playing with a terrible hand at first, there is a chance we can still win by changing the features of our network and making it stable. For example, by optimizing misfolded protein response or DNA repair.

So what does this paper mean to all of us? It means that if we analyze transcriptome data theoretically would be able to understand how we can transform a normally aging organism into a negligibly aging one. We can start experiments right away to implement the main idea – to hack aging.

Read the paper here – http://www.nature.com/articles/srep13589


Filed under Biology of Aging

11 responses to “Hacking Aging

  1. Pingback: Lifeboat News: The Blog

  2. sergey

    awesome! thanks for sharing!

  3. Pingback: Genes Out of Thin Air, and Other Wonders | al fin next level

  4. Ah, utopianism. It always discounts human behaviour. We know that safety features in automobiles tend to cause drivers to drive more recklessly, on average. Unless for eg something/one inside is perceived as vulnerable. I have never driven so carefully as when I drove my wife and newborn eldest home from the hospital.

    So, if there are treatments that enhance gene network stability as you call it, then a lot of people will simply use that as an excuse for relaxing on the other front and living the Good Life of booze, junk food and the high life. This is seatbelts, ABS, airbags.

    As we see with the sometimes wild dietary changes etc of those diagnosed with cancers or other diseases (vulnerable occupant).

    You assume that people will react like vulnerable occupants but read the comments under any article warning of say the dangers of sugar or the wrong dietary facts and you will see how a lot of people will react: Great! pass the bacon and the beers!

    Yours Muscleguy BSc, PhD (Physiol)

  5. Vladimir Poponin

    It is important to know how to achieve Genome stability to make this discovery practical

  6. I am trying to figure out if humans are born with negligible senescence, but around reproductive age “suicide genes” turn on crippling their damage repairing systems, which later leads to normal senescence that we see exhibited in the human model now.


    “According to the study, this genetic switch is automatically flipped when a worm reaches reproductive maturity. Stress responses that originally protect its cells by keeping vital proteins folded and functional are switched off at this point, and the ageing process begins in earnest – with the switch disabled, the cells kept up their earlier level of resistance, making the worm better able to handle the wear and tear of growing older…The key moment is associated with reproduction, because it’s at this point that the future of the species has been guaranteed – once the next generation is born, the current generation can get out of the way.”

    • This concept jives with contemporary human evolutionary theory regarding programmed senescence and its effect on intergenerational scarcity, resource management and civilization success.

      Very interesting.

  7. I really like your writing style. It’s like words written on a piece of unfurling paper.

    The idea is strong and reminiscent of telomeric stability and replenishment as a component of healthy aging and longevity. The idea has been repeated a few times in various studies. I’ll have to read the OP to see if they cite the paper trail.

    Then, like said, there’s the proteolytic system – misfolded protein response – and its failure during autophagy to mediate protein errors. This is one of my personal foils regarding the fasting debate that Aubrey De Grey has written about. If you know why, you can be my friend, no questions asked.

    Finally, the heat shock response system is a well known mediator of cellular stress and disease resistance. I didn’t realize that it played a role in genomic stability outside of this. The craziness of the recursive potential is not as bad as I thought initially. It ties up a lot of loose ends.

    I guess what I’m getting at is a more general question of “how much” as it pertains to the effect size of the OP network stability alteration/remodeling variable alteration relative to the neglible senescence. How many players are at work? Where do you hit hardest and first?

    These are the questions I intend to ask as I read the paper. Someday :\

    p.s. goddamn you’re fine af 😀

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