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Speaker 1: Hey, you welcome to Stuff to blow your mind. My

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Speaker 1: name is Robert Lamb and I'm Joe McCormick, and it's Saturday.

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Speaker 1: Time to go into the vault for Eternal Youth Part two.

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Speaker 1: If you checked us out last Saturday, it was Eternal

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Speaker 1: Youth Part one. This is going to be the second

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Speaker 1: part of that series. This originally published January. Should we

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Speaker 1: get right into it. Yeah, let's just belly right up

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Speaker 1: to the bar and have a drink from the Fountain

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Speaker 1: of Youth. Welcome to stuff to blow your mind from

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Speaker 1: how stuff weren't dot Com? Hey, you, welcome to stuff

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Speaker 1: to blow your mind. My name is Robert Lamb and

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Speaker 1: I'm Joe McCormick, and we're back for part two of

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Speaker 1: our discussion about where's my eternal youth? Why can't I

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Speaker 1: be young and beautiful forever? Why do we age? I

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Speaker 1: know that's the It's the question we've always wondered. It

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Speaker 1: shows up in our philosophical writings, it shows up in

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Speaker 1: our religion, our mythology. Uh. In researching this topic, I

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Speaker 1: kept thinking back to Genesis six three. This is the

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Speaker 1: King James version, and the Lord said, my spirit shall

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Speaker 1: not always strive with man for that he is also flesh,

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Speaker 1: yet his days shall be a hundred and twenty years.

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Speaker 1: So there's God putting a limit on how old a

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Speaker 1: human can become and saying like, here's the aging process. Uh,

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Speaker 1: these are the rules. Obviously doesn't apply to Highlanders. That's right. Well,

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Speaker 1: you know, maybe they're they're part of the giants in

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Speaker 1: the Earth or something. I don't know, Oh that could be. Yeah,

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Speaker 1: I guess they're not humans. So well, the spoiler for

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Speaker 1: Highlander to certain cuts, they are not from Earth right

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Speaker 1: in the good cuts from Earth. Yet again, we're just

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Speaker 1: trying to throw those seeds down. Highlander two episode it's

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Speaker 1: coming now. Speaking of parts one and two, this episode

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Speaker 1: is a part two. Yeah, so if you haven't listened

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Speaker 1: to part one yet, you should go back check that

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Speaker 1: out first. And that we explored the question of why

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Speaker 1: we age. We look at some animals that don't really

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Speaker 1: age in the same way that humans and other similar

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Speaker 1: mammals do, and we look at historical explanations people have

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Speaker 1: tried to come up with for why we age, and

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Speaker 1: we also explored some reasons to think that those historical

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Speaker 1: explanations were not correct. Today, we're going to try to

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Speaker 1: get into the modern evolutionary synthesis, take on why we age?

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Speaker 1: What's happening and how do you solve this paradox of

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Speaker 1: the fact that aging is a decline over time in

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Speaker 1: our survival and reproduction fitness, and yet evolution should be

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Speaker 1: constantly optimizing our survival and reproduction fitness. Why would it

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Speaker 1: allow us to go into this period where we tend

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Speaker 1: to die and tend to get worse at surviving and

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Speaker 1: tend to not be able to reproduce anymore. Indeed, because

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Speaker 1: I certainly don't want to deify natural selection and say

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Speaker 1: that like natural selection produces perfect forms or ideal forms,

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Speaker 1: But look at the forms the natural selection has produced,

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Speaker 1: Look at all the various engineering problems that that that

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Speaker 1: evolution has managed to solve. Why would there be this

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Speaker 1: be this huge, at least from our perspective, flaw in

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Speaker 1: the design. Yeah. Now, of course, today, as we often

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Speaker 1: do with evolution, just for the ease of communication, we're

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Speaker 1: going to be using a lot of metaphors that offer

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Speaker 1: a kind of like embodied view of evolution, as if

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Speaker 1: like it's making choices. What we, of course know is

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Speaker 1: that evolution is a is an optimization algorithm. It's not

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Speaker 1: a person. It's not a thing. It doesn't really have

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Speaker 1: desires of it of its own. It has a way

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Speaker 1: that it works, and the way that it works is

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Speaker 1: to optimize the success of genes that survived natural selection

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Speaker 1: and reproduce. Now, one of the answers we explored in

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Speaker 1: the last episode is one of the most common things

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Speaker 1: people are going to turn to when they're trying to

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Speaker 1: explain why we age. It's the thing that my brain

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Speaker 1: and immediately went to before I read anything on this subject.

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Speaker 1: I started to think, well, let's see, if everybody just

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Speaker 1: lived forever and nobody naturally aged out and died, then

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Speaker 1: you'd have way too much competition for resources, right, You'd

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Speaker 1: have way too many people trying to live on the

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Speaker 1: same landscape, you have too many people trying to eat

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Speaker 1: from the same food sources. You'd have overpopulation, and and

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Speaker 1: everybody would suffer for it. Overpopulation ties into a number

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Speaker 1: of our different dystopian views of the future, as does

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Speaker 1: the possibility of immortality becoming an option at least a

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Speaker 1: certain privileged people in society. You know, you get this

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Speaker 1: sort of trope of the awful uh Methuselah of the future. Right,

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Speaker 1: some just dreary, old, greedy individual who will not die

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Speaker 1: and let go the reins of life so that others

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Speaker 1: may grasp it. Right, Well, as much as we don't

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Speaker 1: personally want to grow old and die, you can sort

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Speaker 1: of recognize from an impartial standpoint, if you just consider

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Speaker 1: it in other people, that it seems kind of unfair

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Speaker 1: that people should live forever, right, Yeah, unless it's me

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Speaker 1: or someone that I'm invested, and there they should put

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Speaker 1: a limit on that stuff. Yeah. So, but these types

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Speaker 1: of answers, while true, it is true that it's good

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Speaker 1: for the species that we should age and die, and

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Speaker 1: that it's good for future generations. Uh, good of the

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Speaker 1: species and good of the group based explanations come under

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Speaker 1: a lot of fire from evolutionary biologists. There's some biologists

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Speaker 1: to endorse kind of qualified versions of of good of

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Speaker 1: the group and good of the species type explanations, but

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Speaker 1: there I think many more who don't. And here's an

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Speaker 1: example to illustrate one of the big problems in why

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Speaker 1: these good of the group explanations fail to hold up.

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Speaker 1: All right, hit me with it, Okay, Let's imagine a

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Speaker 1: pack of alien space wolves. Okay, and for our warhammer

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Speaker 1: for fans out there. He's not talking about space marines here. Wait,

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Speaker 1: I don't know what space will Is that a thing? Yeah,

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Speaker 1: it's a faction of the space Marines. In the Warhammer

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Speaker 1: Fort K universe, there are wolves. Well, no, they well

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Speaker 1: they wear wolf skins and they're you know, genetically enhanced

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Speaker 1: super soldiers. Okay, so it would really complicate them the

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Speaker 1: analogy you're making here, if if we were to draw

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Speaker 1: them into the discussion. Well, I was just trying to

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Speaker 1: make clear that this is a hypothetical, not like real

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Speaker 1: wolves on Earth. Okay, So alien space wolves living on

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Speaker 1: an asteroid somewhere in hunting space here. Now, let's imagine

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Speaker 1: this pack of alien space wolves has evolved genes that

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Speaker 1: cause them to grow old and become infertile after about

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Speaker 1: ten years of age, after which you know, they usually

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Speaker 1: die within a couple of years. And let's say that

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Speaker 1: each female space wolf has an average of one space

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Speaker 1: wolf pup every year that she remains fertile. So, unless

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Speaker 1: the space wolf is killed by injury or disease or

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Speaker 1: a marauding space explorer, um, the average space wolf female

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Speaker 1: has tin offspring in her life lifespan. Everybody's happy, right,

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Speaker 1: because they don't eat too many of the space dear,

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Speaker 1: they don't become overpopulated. It just works out pretty well.

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Speaker 1: But then suddenly one of these space wolves acquires a

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Speaker 1: mutation that allows her to stay fertile and survive for

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Speaker 1: twelve years instead of ten, so she has twelve space

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Speaker 1: wolf pups, whereas all the other females in the pack

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Speaker 1: are still having ten, and half of her pups carried

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Speaker 1: this extended fertility and longevity gene, so those six pups

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Speaker 1: each have twelve pups, while non carriers of the gene

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Speaker 1: only have ten, and so on and so on down

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Speaker 1: the generations, and eventually this cheater gene for extended life

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Speaker 1: and extended fertility is going to proliferate, even if it

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Speaker 1: might be worse off for everybody in the long run.

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Speaker 1: Even if the long living, long reproducing animals have too

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Speaker 1: many offspring and consume too many resources and suffer die outs,

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Speaker 1: this won't really cause a re selection towards shorter lifespans,

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Speaker 1: because how would it. Instead, what it would do is

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Speaker 1: optimized for whatever genes are possessed by the survivors of

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Speaker 1: those die outs, and that would probably be like those

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Speaker 1: that store fat better or hunt better, or can extract

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Speaker 1: nutrition from space moss in addition to meat. And this

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Speaker 1: is a really common type of argument against good of

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Speaker 1: the group and good to the species explanations and evolution,

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Speaker 1: because any mutation that cheats on the stasius you've created

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Speaker 1: for the good of the group will tend to start

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Speaker 1: to get an edge and then have more offspring than

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Speaker 1: those who don't cheat, and eventually that new gene will

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Speaker 1: become the norm. Right. Yeah, It's kind of like if

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Speaker 1: you have a you know, an academic environment where everybody's

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Speaker 1: cheating on the exam, the exam, the grading becomes that

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Speaker 1: much harder each and every time. It's true. Yeah, it's great.

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Speaker 1: So it's like you've got to grade on a curve

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Speaker 1: because everybody's cheating, so everybody's grade goes down. Um. Yeah.

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Speaker 1: And so I just want to remind you though, this

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Speaker 1: doesn't mean that there is not such a thing as

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Speaker 1: the good of the group the good of the species.

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Speaker 1: Those things clearly are true. And it clearly is true

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Speaker 1: that it's good for the next generation that older generations

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Speaker 1: age out and die. I care about the survival of

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Speaker 1: the rest of my group. I care about members of

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Speaker 1: my species and about future generations. But I care because

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Speaker 1: I have a brain and I can recognize what's going on.

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Speaker 1: Ma genes don't care, and your genes don't care. They

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Speaker 1: just chemically proliferate themselves. They don't have a sentimental attachment

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Speaker 1: or or an idea that the next generation should get

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Speaker 1: resources to. All right, So this just brings us back

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Speaker 1: to the question, though, why have we evolved to grow old? Right,

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Speaker 1: it's still unsolved. Why not live and reproduce forever, maintaining

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Speaker 1: perfect youth and vigor until something extrinsic happens, until we

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Speaker 1: get killed by a hemorrhagic fever or tractor accident. All right,

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Speaker 1: We're gonna take a quick break and we come back.

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Speaker 1: We will answer that very question. Thank alright, we're back,

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Speaker 1: all right. So there are a number of modern, well

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Speaker 1: accepted scientific theories trying to answer the question of why

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Speaker 1: we evolved to age. And here's a starting point for

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Speaker 1: several of those theories. Let's go back to the wolves

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Speaker 1: for a second. Imagine the space wolves. Maybe a hypothetical

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Speaker 1: wolf species could breed and stay healthy until about the

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Speaker 1: age of ten, Like we said, why not twenty, Why

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Speaker 1: not thirty? Why not five hundred? Well, here are a

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Speaker 1: few things to consider. Wolves did not evolve in zoos

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Speaker 1: or as domestic pets, where they're guaranteed meals and protection

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Speaker 1: from violence and guaranteed access to veterinary care. The landscape

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Speaker 1: that created the wolf as it exists is one in

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Speaker 1: which there is a constant struggle to get enough meat

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Speaker 1: to survive and to not get sick and die, and

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Speaker 1: to not get injured and become unable to hunt, so

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Speaker 1: you starve. If you are a wolf living in the

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Speaker 1: wild and you survived the first year of your life,

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Speaker 1: one of these things like injury or disease or star ovation,

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Speaker 1: very likely will kill you before you get a chance

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Speaker 1: to reach old age. These causes of death like disease

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Speaker 1: and injury, or what's known as quote extrinsic causes of death,

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Speaker 1: death caused by outside pressures and not by stuff that's

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Speaker 1: in your genes or by old age. And so we

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Speaker 1: can look at the real life example to see how

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Speaker 1: common this is. The actual gray wolf canis lupus lives

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Speaker 1: somewhere around an average of six years or so in

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Speaker 1: the wild, but in captivity it can live for more

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Speaker 1: than fifteen years. So here's the first crucial bit to use.

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Speaker 1: Some more metaphorical language. If there are physical processes that

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Speaker 1: tend to render a wolf progressively less fit every month

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Speaker 1: after it's more than ten years old, evolution almost never

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Speaker 1: sees that. To put it in another metaphor, asking why

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Speaker 1: evolution allows the wolf to grow old to deteriorate with

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Speaker 1: old age is kind of like asking why we don't

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Speaker 1: have laws against time travel. The reason isn't that our

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Speaker 1: legislative bodies have considered and debated the issue of time travel,

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Speaker 1: and in the end they concluded that time travel is good,

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Speaker 1: we better, we better allow it. That's not what happens.

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Speaker 1: What happens is the issue doesn't come up. Yeah. It.

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Speaker 1: It reminds me of some of these various programs that

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Speaker 1: informs you have to do to figure out how you're

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Speaker 1: saving your for your retirement, and they tend not to

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Speaker 1: cover the second century of your life because it's not

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Speaker 1: going to happen. That's a perfect metaphor. Yeah, how come

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Speaker 1: you're not saving enough money for when you're two hundred

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Speaker 1: years old. It's not that you've decided it's better to

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Speaker 1: be broke when you're two hundred. It's just that the

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Speaker 1: the situation of being two hundred does not tend to

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Speaker 1: come up very often. Now, obviously it's not nearly that extreme,

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Speaker 1: because sometimes in some cases animals do live to old

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Speaker 1: age and they face biological siniscence under natural conditions. But

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Speaker 1: for many species it's pretty rare. For species of animals

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Speaker 1: that tend to die from one cause or another before

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Speaker 1: they get the chance to grow old evolution doesn't have

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Speaker 1: many opportunities to test what happens in old age, so

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Speaker 1: it can't optimize the animal for old age very efficiently.

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Speaker 1: And compare this to how strongly evolution tests and optimizes

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Speaker 1: for the effects of genes that manifest in early life.

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Speaker 1: If something affects how likely you are to survive at

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Speaker 1: age twenty or at age ten, evolution is going to

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Speaker 1: be very strongly selecting for or against that gene. Okay,

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Speaker 1: so this is one part of the landscape of explanations today.

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Speaker 1: Most species that show significant aging evolved to their anatomically

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Speaker 1: modern condition in a situation where mortality was high and

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Speaker 1: evolution didn't get a lot of opportunities to see what

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Speaker 1: happens in old age, much less optimize it. Let's introduce

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Speaker 1: another wrinkle into the explanation. Yeah, this one has a

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Speaker 1: wonderful title. This is mutation accumulation, right, So we go

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Speaker 1: to the British biologist Peter B. Meadair. He was one

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Speaker 1: of the primary evolutionary thinkers credited with working out the

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Speaker 1: implications of this model of aging, where the force of

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Speaker 1: selection just declines with old age. So in several works

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Speaker 1: in the middle of the nineteen forties and the nineteen fifties,

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Speaker 1: uh he argued, based on similar logic, that natural selection

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Speaker 1: would often be blind to the effects of mutations that

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Speaker 1: cause negative effects laid in life after reproduction is mostly stopped.

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Speaker 1: So let's use another analogy. Imagine a mutation called the

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Speaker 1: twenty birthday surprise gene, which means that on the day

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Speaker 1: you turn twenty, carriers of this gene suddenly transform into

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Speaker 1: a bucket of fishheads and thus lose all ability to reproduce. Now,

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Speaker 1: this would mean that in order to pass on this gene,

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Speaker 1: a carrier would have to reproduce before their twentieth birthday.

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Speaker 1: So kids they have before they're twenty years old could

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Speaker 1: still carry this gene, but they don't get the chance

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Speaker 1: to have any kids after their twenty years old, when

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Speaker 1: plenty of other members of the piece these would continue

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Speaker 1: having children, all potential reproduction after twenty is canceled, thus

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Speaker 1: giving people with this gene significantly fewer children on average

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Speaker 1: than people without it, and so the gene is unlikely

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Speaker 1: to spread in the population. Now imagine a similar gene.

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Speaker 1: This is the hundredth birthday surprise gene. Carriers of this gene,

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Speaker 1: upon the day of their hundredth birthday, suddenly transform into

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Speaker 1: a VHS copy of Highlander to the Quickening. Okay, and

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Speaker 1: and and therefore becoming immortal. No, not quite No. The

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Speaker 1: problem is, well, I guess you you might get to

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Speaker 1: live somewhat forever on a shelf, but you don't. You

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Speaker 1: definitely don't get to reproduce after that, right, there's very

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Speaker 1: little sexual reproduction between copies of Highlander to the Quickening.

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Speaker 1: But also it doesn't really matter, right because do carriers

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Speaker 1: of this gene have any fewer children the non carriers

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Speaker 1: of this gene. The answer is no, right, because who's

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Speaker 1: still having children at age one hundred Almost nobody. So

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Speaker 1: even if you have this very unhel helpful gene, you

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Speaker 1: don't like it that you transform into a VHS tape

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Speaker 1: on your hundredth birthday. That's not good for you, but

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Speaker 1: it doesn't matter to how many children you have. It

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Speaker 1: has no effect on that. So if you have this gene,

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Speaker 1: you can spread it to all your children, and they

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Speaker 1: can spread it to all of their children and so,

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Speaker 1: and they'll all have just as many kids and grandkids

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Speaker 1: as the neighbors who don't have it. You've already passed

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Speaker 1: it on by the time it matters. So this would

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Speaker 1: be the case. Though we we've we've used the Highlander

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Speaker 1: to transformation as as an example here. But even if

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Speaker 1: it were something seemingly beneficial, like say a gene made

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Speaker 1: you suddenly really excellent and talking to members of the

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Speaker 1: opposite sex at age one hundred, you know, like or

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Speaker 1: the opposite it made you terrible at a speaking to

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Speaker 1: the opposite sex at age one hundred, it would still

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Speaker 1: be the same case, right, yeah, unless the basically the

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Speaker 1: only thing that would matter would be if it's a

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Speaker 1: gene that suddenly makes you able to reproduce again. I mean,

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Speaker 1: if it did that, then that would probably matter. But

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Speaker 1: as long as you're past the age of reproduction and

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Speaker 1: you're not having any more children, mutations good or bad

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Speaker 1: are just going to sort of accumulate randomly without having

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Speaker 1: any effect Onesoever, natural selection just doesn't pay attention to

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Speaker 1: them because it never gets to notice them. Well. But

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Speaker 1: then the other thing too, is that if you're talking

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Speaker 1: about something that would kick in so late in life

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Speaker 1: that even people with that gene might never experience it. Right.

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Speaker 1: It's like if you're playing a role playing game, video

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Speaker 1: game or what have you, and there's some sort of

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Speaker 1: like high level ability and you look at it. It

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Speaker 1: looks great, but you know you're never going to play

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Speaker 1: the game long enough to get it. Yeah, so what's

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Speaker 1: the point. Yeah, the game might as well for you

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Speaker 1: not even have that thing in it. And apparently there

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Speaker 1: are going to be genetic mutations like that. And this

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Speaker 1: was Meta WIRs insight. It came to be known, as

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Speaker 1: you said, as the mutation accumulation hypothesis. Whether reproduction stops

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Speaker 1: because you die of extra ends it causes. This was

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Speaker 1: a big thing Meta or had in mind. It's like

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Speaker 1: we talked about, you know, the wolf gets injured and

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Speaker 1: can't hunt, the wolf gets sick and dies, the wolf

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Speaker 1: gets killed by something, whether that happens or because you

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Speaker 1: age out of your reproductive stage of life for some

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Speaker 1: other biological reasons. Genes that have negative effects that show

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Speaker 1: up mostly after reproduction has stopped, are not subject to

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Speaker 1: the full force of natural selection. So there's not much

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Speaker 1: preventing the proliferation of genes that harm you in old

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Speaker 1: age because there's nothing to weed them out, and they

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Speaker 1: accumulate in the genome over generations by what's known as

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Speaker 1: genetic drift. And the genetic drift is just the random

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Speaker 1: dispersing of genes that don't appear to have a very

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Speaker 1: strong positive or negative effect. So if you've got a

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Speaker 1: mutation that you acquire for a nasty surprise in old age,

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Speaker 1: something bad that happens to your body, and you could

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Speaker 1: look at the process of aging like this, it's just

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Speaker 1: a large plethora of genetic mutations that cause bad things

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Speaker 1: to happen to your body. Later on, you can still

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Speaker 1: pass it on to your kids because you're you've had

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Speaker 1: all your kids by the time it starts affecting you.

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Speaker 1: And so these genes can become common in the gene

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Speaker 1: pool of your species simply because there's nothing stopping them.

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Speaker 1: So simply put it, the force of selection declines with age.

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Speaker 1: Mutations that are neutral early in life when selection is strong,

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Speaker 1: but negative later on, they could accumulate in the population.

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Speaker 1: I like to think of this as the sack of

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Speaker 1: kitty litter scoopings in the closet scenario. Okay, explain. But

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Speaker 1: a friend of mine, when I first met her, she

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Speaker 1: had a cat box, and then she would scoop the

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Speaker 1: cat box and it would accumulate in a garbage bag

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Speaker 1: in the closet. Accumulate me, you mean accumulate as and

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Speaker 1: she would dump it, yes, in a garbage bag in

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Speaker 1: the close. And it was. It was a lot cleaner

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Speaker 1: than this makes it sound, but it was. It was

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Speaker 1: very much a sort of kicking the can down a

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Speaker 1: road scenario, like eventually you're gonna have to take that

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Speaker 1: bag of of of of litter scoopings out, but you're not.

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Speaker 1: The whole situation is not built on what you're going

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Speaker 1: to have to do tomorrow. It's about what's happening to today.

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Speaker 1: But what if you're looking at that closet and you're saying, oh,

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Speaker 1: there's enough space in here that I could keep scooping

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Speaker 1: it into the closet until I die of some of

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Speaker 1: their cause, and then I would never have to take

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Speaker 1: it out. It would be completely irrelevant. So it can

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Speaker 1: accumulate forever, just like these deleterious genes can. Okay, So

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Speaker 1: that's clearly one part of the answer. One part is

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Speaker 1: that stuff that affects you late in life is just

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Speaker 1: less likely to get weeded out by natural selection. But

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Speaker 1: what if there's something more than that. What if maladaptive

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Speaker 1: genes that manifest in old age aren't just allowed to

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Speaker 1: roam wild by sort of the careless shepherd of a

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Speaker 1: natural selection. What if they're positively selected four in some way.

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Speaker 1: And that's what we'll explore when we come back from

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Speaker 1: this break than all right, we're back, So now it's

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Speaker 1: time to talk about antagonistic pleotropy. In a paper in

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Speaker 1: seven and the journal Evolution, the American Evolutionary by alllogist

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Speaker 1: George C. Williams had a breakthrough that made metoirs original

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Speaker 1: hypothesis even stronger and sort of complimented it. And so

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Speaker 1: this was a paper that I mentioned in part one.

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Speaker 1: Actually it's the paper called pleotropy, Natural Selection and the

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Speaker 1: Evolution of sinescence. Williams hypothesis for the evolution of aging

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Speaker 1: came to be known, as I said, as antagonistic pleotropy.

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Speaker 1: And what this means is that well. Pleotropy. The word

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Speaker 1: comes from the Greek roots meaning multiple turns or many effects.

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Speaker 1: Pleotropy happens when a single gene codes for multiple different

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Speaker 1: phenotypic effects, meaning effects on the body or effects on

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Speaker 1: the behavior. So if you had one gene that both

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Speaker 1: gave you black hair and gave you an extremely long,

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Speaker 1: pinky fingernail, that would be pleotropy. Or if you had

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Speaker 1: a gene that made you really tall and also made

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Speaker 1: you better at learning multiple languages, that would be pleotropy.

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Speaker 1: And there are lots of examples of this in animals

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Speaker 1: in the real world. Here's one in chickens. Robert, have

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Speaker 1: you ever seen the frizzle chickens? Who? I don't know.

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Speaker 1: I've seen some pretty funny looking chickens before. I've seen

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Speaker 1: a frizzle chicken. I mean the ones that have like

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Speaker 1: the curly vegas outfits. Uh yeah, well yeah, I have

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Speaker 1: seen some of these. These these chickens that have like

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Speaker 1: a lot of extra feathers around their their talons and all.

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Speaker 1: The frizzle gene is is a gene in chickens that

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Speaker 1: causes the feathers to curl up instead of lying flat,

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Speaker 1: so you get these crazy looking like awesome, beautiful, regal

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Speaker 1: puffy chickens and they look really cool. But it turns

400
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Speaker 1: out this gene also controls several other phenotypic effects. So

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Speaker 1: if you are a chicken with the frizzle gene, you'll

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Speaker 1: also have a different metabolic rate and different body temperature

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Speaker 1: and lay a different number of eggs than the chickens

404
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Speaker 1: who don't have this gene. So if you want the

405
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Speaker 1: gene for the magnificent curl, you're going to be laying

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Speaker 1: fewer eggs, among other things. And these are examples where

407
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Speaker 1: the situation it feels more like a trade off and

408
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Speaker 1: probably has more in common with some of our our myths, right,

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Speaker 1: because the gift of the god often comes with some

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Speaker 1: sort of consequence. Yeah, exactly. So another one, just real quick.

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Speaker 1: In cats, did you know about fort of cats with

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Speaker 1: white fur and blue eyes are also deaf? I have

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Speaker 1: heard this one, yes, yeah, odd, So pleotropy can be

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Speaker 1: like that. It can come in and kind of mixed

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Speaker 1: blessing form, though I guess I don't actually know if

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Speaker 1: blue eyes are good for the cat. Maybe that's double bad.

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Speaker 1: But uh well, you I mean, certainly when you get

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Speaker 1: into the selective breeding of of a species, you get

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Speaker 1: into a situation where appearance has has a has a

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Speaker 1: survival advantage. Yeah, exactly. So pleotropy can go both ways.

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Speaker 1: One effect of a gene could be good while the

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Speaker 1: other effect could be bad. And here's where we get

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Speaker 1: the idea of quote antagonistic pleotropy. A pleotropy that's pulling

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Speaker 1: in both directions, but usually it'll pull a bit stronger

425
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Speaker 1: in one direction than another. So if the good effect

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00:24:04,359 --> 00:24:07,000
Speaker 1: outweighs the bad effect, the gene will spread through the

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00:24:07,040 --> 00:24:09,879
Speaker 1: gene pool. But if the bad effect outweighs the good effect,

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Speaker 1: the gene will tend to go extinct. That we should

429
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Speaker 1: be clear again what's meant by good and bad genes here, Because,

430
00:24:16,800 --> 00:24:21,040
Speaker 1: for example, a gene that caused the carrier to experience

431
00:24:21,080 --> 00:24:25,760
Speaker 1: intense pain and misery throughout life, but somehow also caused

432
00:24:25,840 --> 00:24:29,000
Speaker 1: the carrier to have more healthy children than the average

433
00:24:29,040 --> 00:24:32,520
Speaker 1: member of their species would also spread. So it's not

434
00:24:32,600 --> 00:24:35,560
Speaker 1: optimizing for like you to have a long life, for

435
00:24:35,680 --> 00:24:38,399
Speaker 1: you to have a fun life. It's optimizing for number

436
00:24:38,400 --> 00:24:43,120
Speaker 1: of offspring and the success of those offspring. Now, William's

437
00:24:43,160 --> 00:24:46,639
Speaker 1: theory of antagonistic pleotropy picks up from this fact, he

438
00:24:46,760 --> 00:24:50,040
Speaker 1: hypothesizes that some of the genes that cause aging are

439
00:24:50,080 --> 00:24:54,520
Speaker 1: selected for because they have other separate effects that maximize

440
00:24:54,560 --> 00:24:58,639
Speaker 1: fitness and reproduction earlier in life, which, like Metawir showed,

441
00:24:58,920 --> 00:25:02,200
Speaker 1: is more strongly select did foreign nature. The same genes

442
00:25:02,240 --> 00:25:05,480
Speaker 1: that make your skin sag and give you heart disease

443
00:25:05,520 --> 00:25:09,920
Speaker 1: in old age might also make you extremely reproductively competitive

444
00:25:10,119 --> 00:25:13,479
Speaker 1: when you're young. So here's a really broad example. How

445
00:25:13,480 --> 00:25:18,320
Speaker 1: about genes that control the rate of cell division. Yeah,

446
00:25:18,320 --> 00:25:21,600
Speaker 1: so a hypothetical gene might be selected for because it

447
00:25:21,640 --> 00:25:25,879
Speaker 1: makes cells divide more efficiently. And if cells divide more efficiently,

448
00:25:25,880 --> 00:25:29,119
Speaker 1: it means you can rejuvenate tissues and heal wounds and

449
00:25:29,320 --> 00:25:32,760
Speaker 1: grow faster when you're young. But the same gene that

450
00:25:32,800 --> 00:25:37,360
Speaker 1: causes prolific cell division could potentially be a problem later

451
00:25:37,400 --> 00:25:39,879
Speaker 1: in life, because what happens when cells are prone to

452
00:25:39,960 --> 00:25:43,400
Speaker 1: divide a whole lot you could be prone to cancer

453
00:25:43,520 --> 00:25:47,240
Speaker 1: cancer is runaway cell division. Cells that are not useful

454
00:25:47,280 --> 00:25:50,560
Speaker 1: for the body are suddenly being created in great abundance,

455
00:25:51,000 --> 00:25:53,159
Speaker 1: which brings us back to the hydrosaur example that we

456
00:25:53,240 --> 00:25:56,199
Speaker 1: touched on earlier. Yeah, back in the first episode. Or

457
00:25:56,400 --> 00:25:58,600
Speaker 1: you could think about something going exactly the reverse. You

458
00:25:58,600 --> 00:26:02,080
Speaker 1: could have a gene that could increase apoptosis signaling, and

459
00:26:02,160 --> 00:26:06,360
Speaker 1: apoptosis is programmed cell death, so a gene that causes

460
00:26:06,440 --> 00:26:09,760
Speaker 1: cell lines to die off more frequently, and this would

461
00:26:09,800 --> 00:26:13,520
Speaker 1: help prevent runaway cell lines from turning into cancer while

462
00:26:13,560 --> 00:26:17,399
Speaker 1: you're young. Natural selection obviously would love this because it

463
00:26:17,440 --> 00:26:20,560
Speaker 1: would select against organisms that get cancer when they're young

464
00:26:20,600 --> 00:26:24,600
Speaker 1: and can't reproduce much. But the exact same gene would

465
00:26:24,640 --> 00:26:28,320
Speaker 1: cause tissues to deteriorate more with age because they undergo

466
00:26:28,400 --> 00:26:31,679
Speaker 1: more and earlier cell death. And in fact, something like

467
00:26:31,720 --> 00:26:35,120
Speaker 1: what I just described has actually been studied. The example

468
00:26:35,160 --> 00:26:38,480
Speaker 1: would be the gene at P fifty three. The P

469
00:26:38,640 --> 00:26:42,119
Speaker 1: fifty three gene has been implicated in antagonistic pleotropy, and

470
00:26:42,160 --> 00:26:46,120
Speaker 1: it's thought that P fifty three protects young animals, including humans,

471
00:26:46,119 --> 00:26:49,359
Speaker 1: but I think it's mostly been researched in mice. It

472
00:26:49,400 --> 00:26:54,240
Speaker 1: protects these young animals against cancer by interrupting cell proliferation.

473
00:26:54,280 --> 00:26:56,840
Speaker 1: It says, now, don't cells don't divide too much now,

474
00:26:57,320 --> 00:26:59,680
Speaker 1: But in doing this it can also have the effect

475
00:26:59,680 --> 00:27:04,080
Speaker 1: of erupting the proliferation of normal, non cancerous cells like

476
00:27:04,160 --> 00:27:06,639
Speaker 1: stem cells, which are the cells the body uses to

477
00:27:06,680 --> 00:27:11,680
Speaker 1: rejuvenate tissues over time. So the same gene that play

478
00:27:11,800 --> 00:27:14,760
Speaker 1: some role in helping protect against cancer when you're young

479
00:27:15,359 --> 00:27:18,840
Speaker 1: also helps play some role in the physical deterioration of

480
00:27:18,880 --> 00:27:22,000
Speaker 1: the body with age by preventing it from making new

481
00:27:22,080 --> 00:27:26,679
Speaker 1: cells and rejuvenating your tissues and detaining eternal youth. So

482
00:27:26,720 --> 00:27:29,680
Speaker 1: the takeaway from this, obviously is that anytime you see

483
00:27:29,680 --> 00:27:32,679
Speaker 1: a story about eternal youth in fiction or in a

484
00:27:32,720 --> 00:27:36,280
Speaker 1: movie or something like that, imagine these these characters who

485
00:27:36,280 --> 00:27:40,120
Speaker 1: are eternally youthful riddled with cancer. It's not really nothing

486
00:27:40,119 --> 00:27:42,920
Speaker 1: hard to imagine when you think about all the various

487
00:27:43,080 --> 00:27:46,520
Speaker 1: uh uh side effects and caveats that come with eternal

488
00:27:46,600 --> 00:27:48,919
Speaker 1: youth in most of our myths and legends, right well,

489
00:27:49,040 --> 00:27:51,080
Speaker 1: I mean, yeah, you've got uh. I guess it's not

490
00:27:51,160 --> 00:27:53,480
Speaker 1: applicable in the tiffan A story because he doesn't get

491
00:27:53,480 --> 00:27:56,359
Speaker 1: eternal youth. He wants to live forever. But you imagine

492
00:27:56,400 --> 00:27:58,879
Speaker 1: the equivalent of the tiffan A story where you ask

493
00:27:58,960 --> 00:28:01,720
Speaker 1: for eternal youth. So Tiffannus ask for eternal life, or

494
00:28:01,760 --> 00:28:05,040
Speaker 1: he doesn't ask Aos ask for eternal life for Titness,

495
00:28:05,040 --> 00:28:07,520
Speaker 1: he gets eternal life, but not eternal youth. So it's

496
00:28:07,560 --> 00:28:10,399
Speaker 1: the monkeys Paul coming back to bite him. In this story,

497
00:28:10,520 --> 00:28:13,000
Speaker 1: you would ask for eternal youth and they say, okay,

498
00:28:13,040 --> 00:28:15,320
Speaker 1: here is your eternal youth. But you get lots of

499
00:28:15,359 --> 00:28:17,840
Speaker 1: cancer with it. And I think actually have read in

500
00:28:17,880 --> 00:28:21,840
Speaker 1: the past that some of these experimental youth extension techniques

501
00:28:21,880 --> 00:28:26,000
Speaker 1: that people do research on initially look promising but sometimes

502
00:28:26,119 --> 00:28:29,840
Speaker 1: turn out to appear to increase cancer risk. Now here's

503
00:28:29,880 --> 00:28:34,560
Speaker 1: another example of a potential antagonistic pleotropy inflammation. So I

504
00:28:34,600 --> 00:28:37,119
Speaker 1: want to cite one paper from two thou eight in

505
00:28:37,280 --> 00:28:41,120
Speaker 1: Bioscience Trends by Makoto Goto, And in this paper, the

506
00:28:41,160 --> 00:28:43,640
Speaker 1: author explores the idea that a lot of the signs

507
00:28:43,680 --> 00:28:48,320
Speaker 1: of physical deterioration associated with aging are driven by inflammation.

508
00:28:48,880 --> 00:28:51,880
Speaker 1: But inflammation is a defense mechanism for the body. It

509
00:28:52,000 --> 00:28:55,560
Speaker 1: helps you survive the redness, the swelling. It's not pleasant,

510
00:28:55,800 --> 00:28:58,800
Speaker 1: but all that's part of a primitive immune system response

511
00:28:58,840 --> 00:29:03,880
Speaker 1: that protects you against antigens and parasites. So inflammation responses

512
00:29:03,920 --> 00:29:07,720
Speaker 1: can help you survive when you're young, but later in life,

513
00:29:07,800 --> 00:29:11,600
Speaker 1: inflammation related aging effects cause widespread damage to the body,

514
00:29:11,920 --> 00:29:15,240
Speaker 1: including all kinds of diseases from type two diabetes to

515
00:29:15,320 --> 00:29:22,080
Speaker 1: rheumatoid arthritis. Also, the kind of military reaction to invasion

516
00:29:22,120 --> 00:29:25,160
Speaker 1: that is helpful for the young organism can be a

517
00:29:25,160 --> 00:29:28,840
Speaker 1: detriment to the older organism. Correct, exactly right, And so

518
00:29:29,000 --> 00:29:31,800
Speaker 1: it's believed now by scientists that there are tons of

519
00:29:31,840 --> 00:29:34,480
Speaker 1: things like this in the body. There are genes that

520
00:29:34,640 --> 00:29:38,560
Speaker 1: have these antagonistic pleotropy effects. They're good for you when

521
00:29:38,560 --> 00:29:42,080
Speaker 1: you're young. They help you survive young adulthood and childhood

522
00:29:42,320 --> 00:29:46,240
Speaker 1: and help you have more children early on. But the same,

523
00:29:46,400 --> 00:29:50,320
Speaker 1: very same genes having the very same effects also cause

524
00:29:50,440 --> 00:29:54,120
Speaker 1: you to age and become sick and reduce your fitness

525
00:29:54,200 --> 00:29:57,040
Speaker 1: later on in life, when, as we established earlier, the

526
00:29:57,120 --> 00:30:01,040
Speaker 1: force of selection is diminished. So one theory that is

527
00:30:01,120 --> 00:30:04,520
Speaker 1: pretty similar to these ones we've just discussed, we've got

528
00:30:04,520 --> 00:30:09,360
Speaker 1: metairs mutation accumulation hypothesis, which says, you know, uh, natural

529
00:30:09,400 --> 00:30:12,640
Speaker 1: selection doesn't pay much attention to what happens later in life,

530
00:30:12,880 --> 00:30:15,600
Speaker 1: so negative mutations can kind of just hang out there

531
00:30:15,680 --> 00:30:19,320
Speaker 1: without really being weeded out. Then you've got antagonistic pleotropy,

532
00:30:19,400 --> 00:30:21,960
Speaker 1: which says that some of the things that cause negative

533
00:30:21,960 --> 00:30:25,640
Speaker 1: effects later in life are positively selected for because those

534
00:30:25,680 --> 00:30:29,080
Speaker 1: negative effects later are much outweighed by positive effects early

535
00:30:29,160 --> 00:30:32,920
Speaker 1: in life and uh enhancing reproductive fitness early on. So

536
00:30:32,920 --> 00:30:36,480
Speaker 1: there's a very similar theory along the same lines called

537
00:30:36,560 --> 00:30:39,680
Speaker 1: the disposable soma theory, And this is a theory on

538
00:30:39,720 --> 00:30:42,400
Speaker 1: the evolution of aging that was put forward in nineteen

539
00:30:42,480 --> 00:30:46,160
Speaker 1: seventy seven by the English biologist Thomas Kirkwood. And this

540
00:30:46,320 --> 00:30:50,840
Speaker 1: reframes it as a question of resource investment in the body.

541
00:30:51,400 --> 00:30:54,800
Speaker 1: Here's the basic premise. The body has a finite amount

542
00:30:54,840 --> 00:30:59,200
Speaker 1: of resources that it can spend on various projects. And

543
00:30:59,240 --> 00:31:03,520
Speaker 1: these projects would include things like speeding up reproduction in

544
00:31:03,600 --> 00:31:08,840
Speaker 1: the youth and maintaining body tissues. And so if you've

545
00:31:08,880 --> 00:31:11,120
Speaker 1: got both of these things and you've got a limited

546
00:31:11,200 --> 00:31:15,240
Speaker 1: budget to spend on them, you're gonna need to make choices, right,

547
00:31:15,760 --> 00:31:18,240
Speaker 1: how much goes to each one, and indeed which one

548
00:31:18,320 --> 00:31:22,640
Speaker 1: is the most important for the biological mission at hand. Right.

549
00:31:22,680 --> 00:31:25,080
Speaker 1: And so, drawing on the same logic we looked at earlier,

550
00:31:25,120 --> 00:31:28,040
Speaker 1: if you live in a scenario where you don't tend

551
00:31:28,080 --> 00:31:32,520
Speaker 1: to live to you know, your natural end of life age,

552
00:31:32,560 --> 00:31:35,120
Speaker 1: you tend to get weeded out by things happening to

553
00:31:35,280 --> 00:31:38,680
Speaker 1: you in the wild, you know, predation or starvation or

554
00:31:39,720 --> 00:31:43,880
Speaker 1: or a disease or injury, anything like that, It will

555
00:31:43,880 --> 00:31:46,920
Speaker 1: obviously look to your body like you need to invest

556
00:31:47,000 --> 00:31:50,880
Speaker 1: way more in those earlier stages in maximizing reproduction early on,

557
00:31:51,240 --> 00:31:53,840
Speaker 1: and so drawing on metawar evolution is going to tend

558
00:31:53,840 --> 00:32:00,120
Speaker 1: to favor pouring finite resources into early reproduction optimization instead

559
00:32:00,320 --> 00:32:04,800
Speaker 1: of maintaining tissues for an infinite natural lifespan. So I'm

560
00:32:04,840 --> 00:32:08,440
Speaker 1: trying to think of a human equivalent. Uh, it sounds

561
00:32:08,480 --> 00:32:11,360
Speaker 1: kind of silly, but basically like, should the body spend

562
00:32:11,400 --> 00:32:16,680
Speaker 1: its precious limited energy resources keeping your artery walls from

563
00:32:16,720 --> 00:32:22,920
Speaker 1: thickening over time or spending them on making you super sexy? Well,

564
00:32:22,960 --> 00:32:25,600
Speaker 1: you know, I God knows. I am not an economist,

565
00:32:25,800 --> 00:32:29,440
Speaker 1: but I find that when we discussed life cycles of organisms,

566
00:32:29,520 --> 00:32:33,400
Speaker 1: or or life cycles of of stars, even I think

567
00:32:33,440 --> 00:32:36,360
Speaker 1: of companies and how they work. So it comes down

568
00:32:36,360 --> 00:32:38,720
Speaker 1: to a question as as say that the CEO or

569
00:32:38,760 --> 00:32:41,480
Speaker 1: even the founder of a company, are you running the

570
00:32:41,520 --> 00:32:44,840
Speaker 1: company like you want to retire from it and watch

571
00:32:44,840 --> 00:32:48,640
Speaker 1: it continue to prosper as you in your retirement, or

572
00:32:48,720 --> 00:32:51,800
Speaker 1: are you running the company like you intend to sell it?

573
00:32:52,680 --> 00:32:55,040
Speaker 1: You know or we know what the answer is. In

574
00:32:55,120 --> 00:32:58,400
Speaker 1: most cases, yeah, you're you. In many cases you're running

575
00:32:58,440 --> 00:33:01,840
Speaker 1: the company because in a way that benefits the short

576
00:33:02,000 --> 00:33:05,440
Speaker 1: term sale of the company, or you're leaving this company

577
00:33:05,480 --> 00:33:08,160
Speaker 1: for another company. Yeah. I mean people like to have,

578
00:33:08,760 --> 00:33:11,560
Speaker 1: you know, sort of like long term investment type rhetoric.

579
00:33:11,720 --> 00:33:14,440
Speaker 1: But a lot of people have realized that the smart

580
00:33:14,520 --> 00:33:17,880
Speaker 1: strategy for themselves is grab and go, you know, optimize

581
00:33:17,880 --> 00:33:20,640
Speaker 1: whatever you can get out of a system for yourself

582
00:33:20,680 --> 00:33:23,160
Speaker 1: as soon as possible, and then be on your way.

583
00:33:23,440 --> 00:33:25,520
Speaker 1: And that's the equivalent here that this is to say

584
00:33:25,560 --> 00:33:28,200
Speaker 1: that you can't even meet guaranteed that it will matter

585
00:33:28,360 --> 00:33:32,360
Speaker 1: whether you've got a gene that optimizes against atherosclerosis or not.

586
00:33:32,880 --> 00:33:36,600
Speaker 1: But if you can optimize for being real sexy and

587
00:33:36,720 --> 00:33:41,280
Speaker 1: having lots of successful reproductive strategies early on in life,

588
00:33:41,440 --> 00:33:44,520
Speaker 1: you're pretty much guaranteed a better chance at having more children.

589
00:33:44,760 --> 00:33:46,840
Speaker 1: And we have so many different adages that back up

590
00:33:46,880 --> 00:33:50,239
Speaker 1: this kind of like personal philosophy and life. Right, you know,

591
00:33:50,320 --> 00:33:52,360
Speaker 1: burn it like you've stole it, I believe, not burn

592
00:33:52,400 --> 00:33:54,120
Speaker 1: it like you still drive it, like you sto it.

593
00:33:54,360 --> 00:33:57,200
Speaker 1: Burn the candle at both ends of his combining the

594
00:33:57,240 --> 00:33:59,280
Speaker 1: two there, you know, or burn it like you stole it.

595
00:33:59,320 --> 00:34:03,240
Speaker 1: Really you like it's hot, do it? It behooves you

596
00:34:03,320 --> 00:34:04,920
Speaker 1: to go ahead and burn it so that they don't

597
00:34:04,960 --> 00:34:07,880
Speaker 1: figure out who stole it. Yeah, sees the day. Spend

598
00:34:08,000 --> 00:34:11,360
Speaker 1: like there's no tomorrow exactly because sometimes well sometimes there isn't,

599
00:34:11,760 --> 00:34:14,840
Speaker 1: or there's there's a finite amount of tomorrow. Sometimes a

600
00:34:14,920 --> 00:34:17,880
Speaker 1: leopard will bite your face off. You should just operate

601
00:34:17,960 --> 00:34:21,080
Speaker 1: on the assumption that a leopard might bite your face off.

602
00:34:21,200 --> 00:34:23,680
Speaker 1: So spend what you've got today. Well, that's good. I

603
00:34:23,680 --> 00:34:25,120
Speaker 1: don't know if we'll fit that on a bumper stick

604
00:34:25,160 --> 00:34:28,560
Speaker 1: or Now. What we've described so far are I think

605
00:34:28,600 --> 00:34:31,880
Speaker 1: what's known as the classical theories of aging. And in

606
00:34:31,920 --> 00:34:34,600
Speaker 1: recent years, we should point out some scientists have proposed

607
00:34:34,680 --> 00:34:38,640
Speaker 1: various kinds of updates to accommodate new experimental findings. Maybe

608
00:34:38,640 --> 00:34:40,880
Speaker 1: in the future we could come back to this topic

609
00:34:40,960 --> 00:34:44,719
Speaker 1: again and and explore the most recent developments in in

610
00:34:44,880 --> 00:34:48,160
Speaker 1: aging theory. But these are basically I would say, these

611
00:34:48,160 --> 00:34:51,319
Speaker 1: classical theories are still pretty much intact. There. You know,

612
00:34:51,400 --> 00:34:54,760
Speaker 1: you might need to modify them in some ways to

613
00:34:54,760 --> 00:34:57,800
Speaker 1: to update them for newest experimental findings. But for example,

614
00:34:58,160 --> 00:35:02,560
Speaker 1: an antagonistic pleotropy. People still basically think that this is

615
00:35:02,560 --> 00:35:06,280
Speaker 1: a good explanation for why a lot of the aging

616
00:35:06,280 --> 00:35:09,200
Speaker 1: effects we experience take place, and it gives us room

617
00:35:09,280 --> 00:35:12,840
Speaker 1: on which to build uh further analysis, Yeah, of course,

618
00:35:12,960 --> 00:35:16,680
Speaker 1: and it gives us room to say, if we understand

619
00:35:16,680 --> 00:35:19,600
Speaker 1: how a process happens and why it happens, I wonder

620
00:35:19,640 --> 00:35:23,399
Speaker 1: if it could be reversed or undone. And of course

621
00:35:23,400 --> 00:35:25,200
Speaker 1: there's a lot of that. There's a lot of interest

622
00:35:25,239 --> 00:35:32,200
Speaker 1: in this, given that medical research is uniform universally funded

623
00:35:32,400 --> 00:35:37,000
Speaker 1: by mortals who and many of them are are interested

624
00:35:37,000 --> 00:35:42,520
Speaker 1: and possibly having more life to live or if possible,

625
00:35:42,880 --> 00:35:45,560
Speaker 1: you know, an infinite amount, right, So, of course, because

626
00:35:45,640 --> 00:35:48,240
Speaker 1: we don't want to age and grow old and sag

627
00:35:48,360 --> 00:35:52,000
Speaker 1: and wrinkle and and eventually die, scientists are always working

628
00:35:52,000 --> 00:35:56,680
Speaker 1: on ways to beat aging, and some broad evolutionary mechanisms

629
00:35:56,719 --> 00:35:59,920
Speaker 1: based on things like fruit fly research are actually known.

630
00:36:00,520 --> 00:36:03,520
Speaker 1: But unfortunately they're not the kind of simple medical fixes

631
00:36:03,560 --> 00:36:06,799
Speaker 1: that could like be ethically applied to humans. They're they're

632
00:36:06,840 --> 00:36:11,120
Speaker 1: evolutionary fixes that you couldn't really implement on purpose. I

633
00:36:11,200 --> 00:36:14,440
Speaker 1: mean you could in fruit flies, and researchers have so

634
00:36:14,560 --> 00:36:18,920
Speaker 1: what are they, Well, one would be low adult mortality

635
00:36:19,080 --> 00:36:22,400
Speaker 1: and high juvenile mortality. If you get a bunch of

636
00:36:22,440 --> 00:36:27,880
Speaker 1: fruit flies and you create a scenario such that adults

637
00:36:28,000 --> 00:36:31,040
Speaker 1: tend to survive longer than they would in the wild,

638
00:36:31,600 --> 00:36:37,200
Speaker 1: while juveniles die very often. What actually happens is that

639
00:36:37,320 --> 00:36:41,040
Speaker 1: the life span and the reproductive lifespan of the fruit

640
00:36:41,080 --> 00:36:45,640
Speaker 1: flies increases over generations of evolution. And this kind of

641
00:36:45,640 --> 00:36:47,800
Speaker 1: makes sense, right if the if the mating pool is

642
00:36:47,920 --> 00:36:52,840
Speaker 1: limited to older individuals, genes that favor fitness in later

643
00:36:52,960 --> 00:36:58,759
Speaker 1: life will be selected for, and thus these would be

644
00:36:58,840 --> 00:37:03,240
Speaker 1: genes that prevent or lay aging, and they'll become more successful. Normally,

645
00:37:03,320 --> 00:37:06,319
Speaker 1: evolution wouldn't care about those types of genes very much.

646
00:37:07,000 --> 00:37:09,279
Speaker 1: But of course we can't do this to stop human

647
00:37:09,320 --> 00:37:11,880
Speaker 1: aging unless we're prepared to like implement a policy that

648
00:37:12,000 --> 00:37:15,080
Speaker 1: only people over a certain age can have children and

649
00:37:15,120 --> 00:37:18,120
Speaker 1: then keep pushing the minimum age upwards. Obviously we don't

650
00:37:18,120 --> 00:37:21,560
Speaker 1: want to do that. Well, even in scenarios like you know,

651
00:37:23,000 --> 00:37:26,080
Speaker 1: periods of history in which there is a high mortality

652
00:37:26,200 --> 00:37:29,759
Speaker 1: rate for younger people, such as during wars, uh, it's

653
00:37:29,800 --> 00:37:32,400
Speaker 1: still I don't think there's any data to back of

654
00:37:32,480 --> 00:37:35,000
Speaker 1: the idea. That this would definitely interfere with reproduction because

655
00:37:35,000 --> 00:37:39,480
Speaker 1: obviously there there are children that grow up in the

656
00:37:39,520 --> 00:37:43,440
Speaker 1: in the wake of war. Now perhaps the father is

657
00:37:43,480 --> 00:37:47,920
Speaker 1: not there anymore, but reproduction has been initiated. But then

658
00:37:47,920 --> 00:37:49,920
Speaker 1: that's a whole different area of study, like the effects

659
00:37:49,920 --> 00:37:53,520
Speaker 1: of war on reproduction and the health of the resulting

660
00:37:53,560 --> 00:37:57,000
Speaker 1: offspring um, something we've touched on before on the show,

661
00:37:57,080 --> 00:38:00,840
Speaker 1: and we could easily revisit. Oh yeah, that's all interesting stuff.

662
00:38:01,239 --> 00:38:03,320
Speaker 1: Another thing to point out about what I just mentioned

663
00:38:03,320 --> 00:38:07,200
Speaker 1: about low adult mortality and high juvenile mortality contributing to

664
00:38:07,280 --> 00:38:10,279
Speaker 1: extended lifespans. We know this works in fruit flies, but

665
00:38:10,360 --> 00:38:15,040
Speaker 1: we can't predict other complicating factors that might stop this

666
00:38:15,120 --> 00:38:18,319
Speaker 1: from working another species. Though it does appear to be

667
00:38:18,520 --> 00:38:23,840
Speaker 1: pretty general that species that have lower extrinsic mortality evolve

668
00:38:23,920 --> 00:38:27,760
Speaker 1: longer lifespans. Like if you've got good defense mechanisms against

669
00:38:27,800 --> 00:38:30,719
Speaker 1: predators and disease, or if you just happen to, say,

670
00:38:30,840 --> 00:38:33,399
Speaker 1: end up on an island where you don't have many

671
00:38:33,440 --> 00:38:37,279
Speaker 1: predators or diseases, you will probably evolve over a long

672
00:38:37,320 --> 00:38:41,120
Speaker 1: period of time to breed longer and live longer. Think

673
00:38:41,160 --> 00:38:44,359
Speaker 1: about the Great Wizzen tortoises of the Galapagos. They've got

674
00:38:44,360 --> 00:38:47,919
Speaker 1: a shell, they don't have really natural predators, and they've

675
00:38:47,960 --> 00:38:51,000
Speaker 1: got these long, long lifespans because the adults and the

676
00:38:51,080 --> 00:38:54,480
Speaker 1: old adults can just keep on breeding. And they probably

677
00:38:54,520 --> 00:38:58,160
Speaker 1: had a fair amount of moisture. I think Aristotle would

678
00:38:58,520 --> 00:39:01,600
Speaker 1: Aristotle was onto something. Yeah, No, they don't have moisture

679
00:39:01,600 --> 00:39:04,480
Speaker 1: at all. They look so dry. Those tortoises are like

680
00:39:04,520 --> 00:39:06,879
Speaker 1: the driest looking creatures I can think of, But they

681
00:39:06,880 --> 00:39:10,279
Speaker 1: live in a moist environment. Maybe that's it. That is true,

682
00:39:10,840 --> 00:39:15,240
Speaker 1: But okay, So looking at more like potentially ethical medical fixes,

683
00:39:15,480 --> 00:39:18,640
Speaker 1: are there things researchers are working on in order to

684
00:39:18,719 --> 00:39:22,160
Speaker 1: beat aging and humans? Well, the answer is obviously yes.

685
00:39:22,280 --> 00:39:26,120
Speaker 1: There are plenty of questions about whether these projects are

686
00:39:27,160 --> 00:39:29,520
Speaker 1: actually a good idea, and even if they are a

687
00:39:29,520 --> 00:39:33,360
Speaker 1: good idea, whether they could be successful in principle, but

688
00:39:33,719 --> 00:39:36,200
Speaker 1: there are plenty people working on it. One example, of course,

689
00:39:36,280 --> 00:39:38,920
Speaker 1: is the gerontologist and author Aubrey de Gray. He's made

690
00:39:38,920 --> 00:39:41,320
Speaker 1: a whole career out of the idea, going around promoting

691
00:39:41,360 --> 00:39:45,040
Speaker 1: that we can and should be trying to completely defeat

692
00:39:45,080 --> 00:39:48,200
Speaker 1: the process of aging, and that we can do it

693
00:39:48,239 --> 00:39:52,239
Speaker 1: within the next few decades. Yeah, he's everyone's probably seen

694
00:39:52,440 --> 00:39:55,440
Speaker 1: images of de Gray before he has his big wizard's beard,

695
00:39:55,560 --> 00:39:57,759
Speaker 1: and he's resputant. Yeah, he shows up in all sorts

696
00:39:57,800 --> 00:39:59,719
Speaker 1: of He doesn't hate respute if he shows up in

697
00:39:59,800 --> 00:40:03,200
Speaker 1: very it's a documentary is about this topic all the time. Uh.

698
00:40:03,480 --> 00:40:06,560
Speaker 1: And his his basic argument is, I think rather ingenious.

699
00:40:06,600 --> 00:40:11,520
Speaker 1: It's instead of viewing aging and death as this unbeatable war,

700
00:40:11,719 --> 00:40:15,879
Speaker 1: you know, this this unbeatable um problem, it's like, break

701
00:40:15,920 --> 00:40:19,399
Speaker 1: it up into smaller battles, smaller problems that you can win,

702
00:40:19,560 --> 00:40:22,279
Speaker 1: that you can solve. Yeah, and I think this is

703
00:40:22,360 --> 00:40:25,319
Speaker 1: the key appeal of his approach. He says, aging is

704
00:40:25,360 --> 00:40:29,560
Speaker 1: not one thing, it's maybe seven things. Yes. For instance,

705
00:40:29,600 --> 00:40:31,920
Speaker 1: the problem might be cells die off and are naturally

706
00:40:31,960 --> 00:40:34,839
Speaker 1: replaced in the heart or in the brain, and he says, well,

707
00:40:34,880 --> 00:40:39,160
Speaker 1: you stem cell replacement for dying cells. Or another example

708
00:40:39,160 --> 00:40:41,960
Speaker 1: would be the body undergoes a proliferation of unwanted cells,

709
00:40:41,960 --> 00:40:44,600
Speaker 1: such as fat cells that replace muscle and lead to diabetes.

710
00:40:44,640 --> 00:40:47,640
Speaker 1: He says, we'll trick the problem cells into self destruction

711
00:40:47,680 --> 00:40:50,600
Speaker 1: through suicide, gene therapy, this sort of thing. So it's

712
00:40:50,840 --> 00:40:54,799
Speaker 1: it's taking taking the overall problem breaking it down into

713
00:40:54,920 --> 00:40:58,920
Speaker 1: little individual problems that you could potentially solve through medical

714
00:40:58,920 --> 00:41:02,839
Speaker 1: intervention and genetic engineering, etcetera. Now, for people who are

715
00:41:02,880 --> 00:41:06,800
Speaker 1: interested in avoiding aging, obviously this message is very appealing. Yes,

716
00:41:07,239 --> 00:41:10,480
Speaker 1: but there are also we should mention many researchers who

717
00:41:10,560 --> 00:41:15,439
Speaker 1: find degrees program unrealistic. Like he has plenty of critics. Well,

718
00:41:15,440 --> 00:41:18,120
Speaker 1: on one level, it's kind of the basic trans anti

719
00:41:18,120 --> 00:41:21,520
Speaker 1: transhumanist argument, right like if okay, if you break down

720
00:41:23,080 --> 00:41:26,759
Speaker 1: essentially immortality into a number of different treatment options that

721
00:41:26,800 --> 00:41:30,319
Speaker 1: are available, than then who are they available to? Who

722
00:41:30,400 --> 00:41:34,080
Speaker 1: has access to these treatments? And then it becomes this, uh,

723
00:41:34,120 --> 00:41:38,000
Speaker 1: this this inequality situation where you have the very dystopian

724
00:41:38,160 --> 00:41:41,279
Speaker 1: idea of the super rich individuals who can afford all

725
00:41:41,280 --> 00:41:44,440
Speaker 1: of the various treatments that that keep their unnatural lives

726
00:41:44,480 --> 00:41:47,120
Speaker 1: going while the rest of us simply live and die

727
00:41:47,120 --> 00:41:49,719
Speaker 1: as always. I would say the answer to that critique

728
00:41:49,840 --> 00:41:53,080
Speaker 1: is not that you shouldn't develop the medical technologies, but

729
00:41:53,120 --> 00:41:55,960
Speaker 1: that you should find ways to make them available to everyone.

730
00:41:56,680 --> 00:41:59,319
Speaker 1: Then again, you do have that intrinsic question of whether

731
00:41:59,360 --> 00:42:02,400
Speaker 1: it's actual good to allow any member of a species

732
00:42:02,480 --> 00:42:05,840
Speaker 1: to be biologically immortal. Uh, to keep on living in

733
00:42:05,920 --> 00:42:09,600
Speaker 1: consuming resources beyond what would what would normally be allotted

734
00:42:09,640 --> 00:42:12,399
Speaker 1: to them in a normal lifespan, because, as we talked

735
00:42:12,400 --> 00:42:15,160
Speaker 1: about earlier on, there's this whole good of the species argument.

736
00:42:15,160 --> 00:42:17,440
Speaker 1: Your genes might not care about the good of the species,

737
00:42:17,480 --> 00:42:20,759
Speaker 1: but you should, right, we should. Well, it's an easy

738
00:42:20,840 --> 00:42:22,919
Speaker 1: argument for for for us to make. But then again,

739
00:42:22,960 --> 00:42:26,040
Speaker 1: we're not a hundred and fifty years old and hooked

740
00:42:26,120 --> 00:42:29,000
Speaker 1: up to the immortality machine. Right. Well, once your time comes,

741
00:42:29,040 --> 00:42:31,160
Speaker 1: you will probably change your tune. Right, It's like, no,

742
00:42:31,280 --> 00:42:33,600
Speaker 1: give me a little more. I just need a little more,

743
00:42:34,000 --> 00:42:38,239
Speaker 1: one more year. Um. But then again, yeah, so that's

744
00:42:38,320 --> 00:42:40,279
Speaker 1: like the question of whether we should be trying to

745
00:42:40,320 --> 00:42:44,800
Speaker 1: achieve biological immortality. There's also this question that many scientists

746
00:42:44,800 --> 00:42:48,200
Speaker 1: have have brought up, which is that his program is unrealistic,

747
00:42:48,200 --> 00:42:51,160
Speaker 1: not necessarily that it's a bad idea, but that you

748
00:42:51,160 --> 00:42:54,360
Speaker 1: you can't extend aging for or not extend. You can't

749
00:42:54,360 --> 00:42:58,160
Speaker 1: extend youth forever. They're just gonna be hard physical limits

750
00:42:58,200 --> 00:43:00,839
Speaker 1: that you're going to hit within the human body. Just

751
00:43:01,040 --> 00:43:03,680
Speaker 1: one example of that strain of thinking as a paper

752
00:43:03,800 --> 00:43:08,000
Speaker 1: that came out earlier this year in published by the

753
00:43:08,000 --> 00:43:11,360
Speaker 1: Proceedings of the National Academy of Science is called Intercellular

754
00:43:11,360 --> 00:43:15,440
Speaker 1: Competition and the Inevitability of Multicellular Aging. So this study

755
00:43:15,560 --> 00:43:20,160
Speaker 1: was conducted by scientists Joanna Massel and Paul Nelson, and

756
00:43:20,239 --> 00:43:24,320
Speaker 1: Massel and Nelson use mathematical models to argue that essentially,

757
00:43:24,360 --> 00:43:27,839
Speaker 1: no matter what you do, you will be faced with

758
00:43:28,000 --> 00:43:31,960
Speaker 1: one facet of aging or another, and the main tension

759
00:43:32,000 --> 00:43:37,319
Speaker 1: they highlight is tissue deterioration or cancer, one or the other.

760
00:43:37,440 --> 00:43:40,960
Speaker 1: It's a mathematical inevitability. They say. If you find a

761
00:43:41,000 --> 00:43:45,520
Speaker 1: way to prevent cancer, tissues deteriorate and cells become less efficient,

762
00:43:45,600 --> 00:43:48,480
Speaker 1: you get the body breaking down. If you find a

763
00:43:48,480 --> 00:43:52,200
Speaker 1: way to rejuvenate tissues, beef them up, make them youthful again,

764
00:43:52,520 --> 00:43:55,359
Speaker 1: you get cancer. Age is going to get you one

765
00:43:55,360 --> 00:43:58,759
Speaker 1: way or another. It's like we're in that trolley car, right.

766
00:43:59,640 --> 00:44:03,640
Speaker 1: We have attracts diverging to two unwanted fates in a

767
00:44:03,680 --> 00:44:06,080
Speaker 1: sense equally unwanted fates, and we have to try and

768
00:44:06,120 --> 00:44:08,040
Speaker 1: figure out, well, which way we're gonna go, What are

769
00:44:08,080 --> 00:44:10,200
Speaker 1: we going to plow into. I feel like this should

770
00:44:10,200 --> 00:44:13,560
Speaker 1: be reimagined as a myth, like going back to Tiffanus,

771
00:44:13,600 --> 00:44:18,719
Speaker 1: like I want the gods gods that represent one represents

772
00:44:18,760 --> 00:44:23,239
Speaker 1: cancer and one represents the deterioration of body tissues. And

773
00:44:23,400 --> 00:44:26,240
Speaker 1: they're like at war and you have to choose between

774
00:44:26,280 --> 00:44:29,800
Speaker 1: your fate with one or the other. Yeah. I like that. Yeah,

775
00:44:29,840 --> 00:44:32,160
Speaker 1: this is this is where our modern day gods can

776
00:44:32,239 --> 00:44:35,319
Speaker 1: jump in and and provide us the story to make

777
00:44:35,400 --> 00:44:38,360
Speaker 1: sense of our our doom. Okay, well, I guess that

778
00:44:38,360 --> 00:44:40,880
Speaker 1: wraps it up for for part two of this episode

779
00:44:40,880 --> 00:44:44,399
Speaker 1: about why we age and why we can't have eternal youth. Yeah. Well,

780
00:44:44,440 --> 00:44:45,839
Speaker 1: and I don't want to leave it on too dark

781
00:44:45,840 --> 00:44:49,719
Speaker 1: of a note there with the doom talk, because I mean, ultimately,

782
00:44:50,440 --> 00:44:54,280
Speaker 1: I guess here's the here's the silver lining. Uh, Aging,

783
00:44:54,520 --> 00:44:58,120
Speaker 1: even dying, everybody does it. It can be. It couldn't

784
00:44:58,120 --> 00:45:00,680
Speaker 1: be that much to it, right, look at the people

785
00:45:00,680 --> 00:45:02,800
Speaker 1: who do it. It It couldn't be. It couldn't be that difficult,

786
00:45:02,800 --> 00:45:04,719
Speaker 1: It couldn't be that hard to go through. Well, I mean,

787
00:45:05,040 --> 00:45:06,920
Speaker 1: it's easy to get down when you spend a lot

788
00:45:06,920 --> 00:45:09,800
Speaker 1: of time thinking about the inevitability of aging and death.

789
00:45:09,880 --> 00:45:13,320
Speaker 1: But um, I mean the thing to think about is, yeah,

790
00:45:13,640 --> 00:45:15,719
Speaker 1: it comes to everybody. It's a part of life, and

791
00:45:15,840 --> 00:45:18,799
Speaker 1: there's a lot of life to love. Yeah, and it

792
00:45:18,840 --> 00:45:20,560
Speaker 1: bears your minding that there is a lot of stuff

793
00:45:20,600 --> 00:45:23,600
Speaker 1: you can do in the in the near future to

794
00:45:23,640 --> 00:45:27,440
Speaker 1: make your your far future a little more easy going.

795
00:45:27,520 --> 00:45:30,200
Speaker 1: You know, you can look after the body you have.

796
00:45:30,480 --> 00:45:33,799
Speaker 1: You can uh, you know, exercise and try to eat right.

797
00:45:34,440 --> 00:45:36,120
Speaker 1: I think I saw a study saying you need to

798
00:45:36,120 --> 00:45:38,640
Speaker 1: eat a bunch of chocolate to make it. I think

799
00:45:38,640 --> 00:45:41,319
Speaker 1: that's what it was. Well, then that's the other side too,

800
00:45:41,440 --> 00:45:44,080
Speaker 1: is like you're gonna grow a hold, You're going to die.

801
00:45:44,160 --> 00:45:49,680
Speaker 1: You can't just spend your whole time worrying over that inevitability,

802
00:45:49,719 --> 00:45:51,759
Speaker 1: So you might as well have some chocolate, you might

803
00:45:51,760 --> 00:45:53,799
Speaker 1: as Oh no, I mean I was joking about those

804
00:45:53,880 --> 00:45:56,400
Speaker 1: articles that actually say chocolate will make you live longer.

805
00:45:56,560 --> 00:45:58,640
Speaker 1: Oh okay, not just the ones where there's like a

806
00:45:58,680 --> 00:46:02,080
Speaker 1: new study out that points to uh some beneficial quality

807
00:46:02,120 --> 00:46:05,839
Speaker 1: of like pure unsweetened chocolate. Uh yeah, I mean it's

808
00:46:05,920 --> 00:46:09,239
Speaker 1: it's always couched in, like eat chocolate to be healthier. Well,

809
00:46:09,320 --> 00:46:11,160
Speaker 1: if it's not couched in it, That's how I think

810
00:46:11,160 --> 00:46:13,760
Speaker 1: sometimes we interpret it. We read the study and we're like, well, good,

811
00:46:13,800 --> 00:46:15,719
Speaker 1: I like chocolate, or I like red wine or I

812
00:46:15,760 --> 00:46:18,760
Speaker 1: like coffee, and now I can just continue to enjoy

813
00:46:18,840 --> 00:46:22,440
Speaker 1: the things that make my life more bearable and uh,

814
00:46:22,480 --> 00:46:24,200
Speaker 1: and not worry about what they might be doing too.

815
00:46:24,400 --> 00:46:27,120
Speaker 1: Anytime you read an article about the one silver bullet

816
00:46:27,160 --> 00:46:30,200
Speaker 1: thing to eat or to drink that will make you

817
00:46:30,280 --> 00:46:34,520
Speaker 1: live forever, don't believe it. I agree, unless that one

818
00:46:34,560 --> 00:46:37,640
Speaker 1: silver bullet thing is the quickening which will work? Can

819
00:46:37,680 --> 00:46:40,959
Speaker 1: the quickening be transferred to another though I'm a little

820
00:46:41,000 --> 00:46:45,879
Speaker 1: shaky on my my quickening science. I don't know. We'll

821
00:46:45,880 --> 00:46:48,479
Speaker 1: have to come back to that. What's the quickening conversion rate?

822
00:46:48,640 --> 00:46:49,880
Speaker 1: I don't know. I think you just have to be

823
00:46:49,880 --> 00:46:54,040
Speaker 1: from the planet's ice, right remember? Hold? All right, Well

824
00:46:54,040 --> 00:46:56,600
Speaker 1: there you go. Uh again, this was a two parter.

825
00:46:56,800 --> 00:46:58,560
Speaker 1: If somehow you made it through all the parts two

826
00:46:58,560 --> 00:47:00,680
Speaker 1: without listening to part one, go back and listen to

827
00:47:00,680 --> 00:47:02,920
Speaker 1: part one. You will find it in all other episodes

828
00:47:02,920 --> 00:47:04,759
Speaker 1: of Stuff to Blow your Mind at Stuff to Blow

829
00:47:04,800 --> 00:47:07,480
Speaker 1: your Mind dot Com, and you'll get our moisture jokes.

830
00:47:07,640 --> 00:47:10,239
Speaker 1: That's right, and hey, while you're stuff to Blow your

831
00:47:10,239 --> 00:47:11,880
Speaker 1: Mind dot Com, you will also find links out to

832
00:47:11,920 --> 00:47:16,320
Speaker 1: our various social media accounts such as Facebook, Twitter, tumbler, et, cetera.

833
00:47:16,480 --> 00:47:18,480
Speaker 1: And if you want to support our show, you can

834
00:47:18,560 --> 00:47:20,799
Speaker 1: visit that website and you can also just leave us

835
00:47:21,000 --> 00:47:24,600
Speaker 1: a rating star rating UH textual rating at wherever you

836
00:47:24,640 --> 00:47:27,719
Speaker 1: get your podcasts. Of course, as always big thanks to

837
00:47:27,760 --> 00:47:31,440
Speaker 1: Alex Williams and Tory Harrison are excellent audio producers, and

838
00:47:31,520 --> 00:47:33,759
Speaker 1: if you want to get in touch with us directly

839
00:47:33,880 --> 00:47:37,000
Speaker 1: the old fashioned way, you can email us at blow

840
00:47:37,120 --> 00:47:50,600
Speaker 1: the Mind at how stuff works dot com for moralness

841
00:47:50,640 --> 00:47:53,160
Speaker 1: and thousands of other topics. Does it how stuff works

842
00:47:53,160 --> 00:48:13,120
Speaker 1: dot com, The busy, many past four foot fo