Latest / Gladden Longevity Podcast / The Science Behind Aging and Rejuvenation - Episode 359

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The Science Behind Aging and Rejuvenation - Episode 359 · Gladden Longevity Podcast

0:00
My standard slogan these days is that our goal is to make aging the new COVID.
0:05
I want us to take aging as seriously as we took COVID six years ago.
0:09
You can argue that mistakes were made here and there in terms of
0:11
how this whole thing was done,
0:13
but the point is humanity got its shit together.
0:15
We have this new problem. We're not in favor of COVID.
0:17
We'd like it fixed as soon as possible,
0:19
please. Multiple vaccines were developed and globally distributed in less than
0:22
a year. World record fastest that that had ever been done before for
0:26
any vaccine for anything was 10 years.
0:28
entire digit we've taken off the time frame.
0:30
Hey everyone, Dr. Gladden here.
0:32
I just finished a conversation with Aubrey de Gray,
0:34
and we had a nice chat for about 45 minutes.
0:37
~ he was updating me on his thoughts around longevity,
0:40
some of the new technologies that are coming around,
0:43
studies that he's planning to do,
0:45
how he's seeing the field evolve.
0:46
You're gonna find this a really informative and interesting conversation
0:50
and at the end he's gonna share the things that he's doing for his own longevity.
0:53
He went from saving hearts as a cardiologist to rewriting the entire aging playbook.
0:59
Dr. Jeffrey Gladden believes 100 is the new 30 and he's got the science
1:03
to back it up. This is the Gladden Longevity Podcast.
1:08
Hey Aubrey, so great to see you again here,
1:10
Glad Longevity Podcast. Appreciate you taking the time.
1:13
Glad to be back. Well, great. Bring us up to speed a little bit.
1:17
As I think about the longevity space,
1:19
it seems to be moving at almost an exponential,
1:22
exponential rate at this point in time,
1:24
just in terms of the number of things that are being discussed,
1:27
talked about, data's coming in,
1:28
et cetera. I'm just curious to get your take on on the field and where you
1:32
see it ~ at this point in time.
1:34
Yep.
1:34
Well, I mean, I certainly agree that overall the field is moving a great deal faster
1:40
than before. There's a lot more money,
1:42
a lot more people that are involved.
1:43
So that's all great. Certainly the conversation around the topic has improved a lot.
1:48
Yeah.
1:49
The things that you and I say are no longer ridiculed.
1:52
They are treated with science foreseeable rather than science fiction.
1:55
My, you know, joy at all of that is always a bit tempered by
1:59
the knowledge that the
2:03
increase in interest and money and so on is extremely unevenly distributed.
2:08
There is a huge subset of the field which remains,
2:14
you know, very, very badly underfunded and for which lack of funding
2:19
is undoubtedly slowing it down.
2:21
And if anything, that has actually become worse.
2:25
in the past decade because the kind of people who were,
2:29
you know, trusting people like you and me to know how to spend money
2:33
and who were just basically giving it away,
2:34
you know, giving it to my nonprofits,
2:36
for example.
2:37
are now in the position where they have the option to invest and actually make money
2:41
back. most of those people, you know,
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just like most investors, anyone who wants to make money,
2:47
they tend to want to make it tomorrow.
2:48
And so there's an enormous shift and bias now towards the areas that might
2:53
be described as low hanging fruit at the expense of areas that are more difficult,
2:58
but that are just as vital for getting to the real finishing line.
3:02
Yeah. So I I think I it's a good point that you make.
3:05
There's so many startups now in the long quote unquote longevity space,
3:08
all of them with you know, at least on the surface,
3:12
interesting technologies and some interesting early data
3:14
and some encouraging results and things like that,
3:17
all of which is, you know, helping to fan the flames of the fire of people.
3:20
you know, getting excited about longevity.
3:22
That being said, I think one of the things that you've always been a proponent
3:26
of is is the basic science and the basic understanding,
3:29
you know, essentially how do we slow down this.
3:31
And the way that we've evolved in our thinking,
3:33
which will probably resonate with you,
3:35
is we see it more as a systems biology approach than a particular thing.
3:40
And so in our practice now, with with what we're developing here,
3:44
we're we're developing a systems biology approach to be able
3:47
to deconstruct and understand the individual.
3:50
And from that identify what we're calling the elegant solutions to go
3:54
in and bring the the ecosystem back into harmony,
3:57
youthful harmony, if you will,
3:59
with inputs that have the greatest impact.
4:02
And we're not trying to take eight thousand things or you know that kind of stuff.
4:05
So in order to do that, however,
4:07
the basic science and understanding of what's causing this and driving
4:12
it becomes really critical. And you know,
4:14
you've written quite a bit in this area,
4:16
you've thought a lot about this a ton,
4:18
you've done research in this area.
4:19
Maybe you can outline for the audience how you see these hallmarks of aging
4:23
or other factors that are actually how they're synergizing,
4:27
working together. What's actually driving all of this from your perspective?
4:31
Yeah, big question. So first of let me stress what I fully agree with
4:36
in what you just said, and then some areas where I would give a different emphasis.
4:40
So I fully agree that this is a systems thing,
4:43
that the only way we can make progress here is by acknowledging that
4:47
the body consists of a vast number of processes that interlocking,
4:51
that talk to each other. That
4:53
That's right.
4:54
aging is no different, that the various types of accumulation of damage
4:59
in the body at the molecular and cellular level influence the rate
5:02
of accumulation of each other.
5:04
So the right way to go about this,
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especially these days when we only have rather limited tools to postpone
5:11
the health problems of late life,
5:13
is to optimize those tools for the individual.
5:16
And of course, you and other knowledgeable physicians in this space have been very
5:21
careful to emphasize how important it is to do that personalization.
5:26
This is especially true, would say,
5:27
because of course, anti-aging medicine or longevity medicine or whatever
5:30
we like to call it is overwhelmingly preventative.
5:33
We are seeking to treat people who are not yet sick and who,
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you know, we don't know how soon it's going to be before they get sick,
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but we do things to increase that period,
5:44
to increase health span and of course,
5:45
to increase lifespan as a kind of side effect of increasing health span.
5:49
One thing I wanted to come
5:49
That's right.
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back
5:51
at you on a little bit here is the role of basic science and of understanding.
5:57
Because if one were to treat the problem of aging as one that one really needed
6:04
to understand well in order to be able to do anything about it,
6:07
then one could not be anywhere near as optimistic as I am in terms
6:13
of timeframes for how soon we might make really dramatic progress
6:17
in extending health span and lifespan.
6:19
I believe that the only reason it's possible to look at this crusade
6:24
as having a good chance of success within the next couple of decades
6:27
is because we are likely to be able to make a really big difference even with
6:34
a very poor level of understanding.
6:36
I always like to look back at what happened 200 years ago with,
6:40
or 150 years ago anyway,
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with the early parts in the invention of modern medicine,
6:46
discovery by, for example, Edward Jenner,
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that you could vaccinate against smallpox,
6:52
the discovery of the germ theory by Pasteur and such like.
6:55
These were people who saved the most insane number of lives.
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But what they were doing was they were manipulating this thing that we
7:03
now call the immune system, which even today we have a really poor understanding of.
7:08
And they had, of course, a tiny fraction of the understanding back then that
7:10
we have today. And yet...
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that we're able to have an impact,
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a huge impact. So we have to ask why.
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And of course the answer is that the body is on our side.
7:19
The body is constantly trying to not get sick and not stay sick and
7:24
to keep us going. And the only reason we get health problems in late life
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is because the tools that the body has with which to do that,
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however extraordinary and impressive those tools may be,
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they are not 100 % comprehensive.
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And there are some types of molecular and cellular damage that accumulate anyway
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because the body doesn't have tools to stop that from happening.
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given that the body is on our side,
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I feel that it is reasonable to expect that we can have
7:54
a pretty big impact, a very big impact in fact,
7:57
on ageing without understanding it all that well.
8:00
In fact, we may already understand it well enough.
8:02
It may be just that we haven't really...
8:05
embraced the possibility that we understand it enough to the extent of using
8:09
all the tools we have. And we can come back in due course to the kind
8:14
of work that we're doing along those lines in an L.A.V.
8:18
But yeah, so I mean, just a month or two ago,
8:20
actually, I was on stage with Jamie Metzl,
8:22
you may know him. He expressed pessimism with regard to the kind
8:25
of timeframes that I talk about,
8:27
know, bringing aging under really comprehensive medical control within
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the next maybe 12 to 15 years from now.
8:33
And the basis for his pessimism was,
8:35
well, we understand very, little about aging,
8:37
you know, maybe a single digit percent of what we could understand in principle.
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And he and the audience were quite surprised when I fully agreed with him.
8:47
But when I pointed out that the timeframes are not based on just that one number,
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but also on two other numbers,
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one being how much do we need to understand?
8:56
The third one being how rapidly are we increasing that understanding?
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And I said basically, well,
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It may be that actually the amount we need to understand is no more than what
9:06
we already understand, therefore we may be quite likely to move forward.
9:10
But of course it remains to be seen.
9:11
We will have to do quite a few studies in order to see whether we really
9:15
can use what we already understand to great effect.
9:19
Yeah, I think it's an interesting point you make.
9:20
We're always working with partial information.
9:23
You know, as a physician, we're always working with partial information.
9:26
And yet, you know, when I was doing the interventional cardiology work,
9:29
I found that when I had more information,
9:32
more precise information, I could always get a better outcome for an individual.
9:35
If I understood the artery better,
9:37
the, you know, the environment,
9:38
the metabolic environment, etc.
9:40
And so that kind of mindset of driving to understand what's going on is,
9:46
you know.
9:47
really at the heart of medical exploration.
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But to your point, we're always going to have partial information to some extent.
9:54
Maybe, maybe 50 years from now,
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we we'll have full information.
9:57
The interesting thing about the body is that there it has a million different
10:01
or millions really of different inputs into it,
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but it has a limited number of responses,
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right? It has it's a finite number of responses.
10:09
And so if we're able to understand what's the status of those responses,
10:13
and we can link that to maybe an input that
10:16
needs to be shut off or turned on or whatever it might be.
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I think that kind of partial information is helpful.
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And then if we do understand what are the the body's responses to things,
10:26
right? It's inflammation, it's oxidative stress,
10:28
it's decreasing mitochondrial output,
10:30
you know, in the face of an infection,
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it's all these different responses that we that we're familiar with,
10:35
then it seems like to your point,
10:37
we may know enough to actually make a big difference.
10:40
And to that end, if
10:43
You know, what are the things that you think we understand well enough to make
10:46
a big difference in now?
10:48
Right. Well, yeah, let me go into a few of the details on that.
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because basically, you know, I agree with what you say.
10:54
Certainly the more we know, the more effective our treatments are going to be.
10:59
that's the question of the extent to which that reaches diminishing returns,
11:03
whether we can get, you know, good enough with a certain amount of knowledge.
11:07
But I do want to distinguish between information and understanding,
11:12
you know, the information part.
11:14
is really important for what we mentioning earlier about
11:17
the personalization of medicine so as to optimize our tools to work
11:21
as well as possible for a given individual.
11:23
But, know, in the same way that scientists often talk about how it's important
11:28
to distinguish between correlation and causation,
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know, mechanistic stuff, causation,
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is what I would call understanding.
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And sometimes we don't need actually,
11:38
you know, a clear mechanistic understanding.
11:41
We can get away with correlation just as long as it's reliable.
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So what do I think? Where do I think we are at this point?
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Well, I mean, the great thing about and well,
11:49
the good thing and the bad thing,
11:50
I guess, about the situation with aging right now is that it is so multifactorial.
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And of course, as has always been the case,
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we have this portfolio of different.
12:03
problems to fix, different types of damage to address.
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And some of them are easier to address than others.
12:08
Way back 25 years ago, when I started talking this way and thinking this way,
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I was really collecting the straws in many cases in terms
12:16
of identifying and describing ways in which we might fix this or that type
12:21
of damage. That is certainly no longer the case.
12:23
There are types of damage that we are now in a position to take not only
12:27
to the laboratory to work on like model organisms like mice,
12:31
but also to take to the clinic.
12:33
I guess.
12:33
The most conspicuous examples right now are first of all stem cell therapies.
12:37
Of course stem cell therapies fall into a number of categories.
12:42
One can use L-genetic stem cells for example,
12:45
or indeed just the exercise of vesicles that they secrete to achieve various types
12:50
of rejuvenation. But the original goal of stem cell therapy was
12:54
to actually replace cells.
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They'll hang out long-term and obviously divide and differentiate
13:00
to replace cells that the body was not replacing on its own.
13:03
And I would say that for sure the most conspicuous example of that right
13:06
now is Parkinson's disease, which has always been kind of the poster child for this,
13:10
because it's definitely caused by the loss of a particular type of neuron.
13:13
There are now five, if I'm not mistaken,
13:16
clinical trials going on around the world using precisely stem cells
13:19
for replacement of dopaminergic neurons and thus restoration of dopamine secretion.
13:24
And everyone's pretty optimistic.
13:26
I don't know if you know the original story of that work started 35 years
13:30
ago or so in Sweden where people tried this.
13:33
Of course, back then they knew zero about how to manipulate stem cells
13:37
in the laboratory in order to have them be the right kind of stem cell.
13:41
So instead, what they did was they got cells out of aborted fetuses that were from
13:45
vaguely the right part of the brain,
13:47
but it was very vaguely. So
13:49
90 or more percent of the time,
13:51
there was no benefit whatsoever.
13:53
But on a few cases that did respond,
13:55
the response was extraordinary.
13:57
Literally, they could go off L-Dopa immediately and no symptoms at all
14:01
for like more than a decade. So now,
14:03
of course, now that we have that technology to manipulate stem cells,
14:07
we are very optimistic.
14:08
The other example I would say is senolytics,
14:11
drugs that selectively remove senescent cells.
14:14
Even the early first generation senolytics like Dysatina and Nib
14:18
and Quercetin are effective enough that they have now moved into clinical trials.
14:23
And a lot of other more sophisticated and more specific alternative senolytics
14:29
are well on the way to that. So I would say,
14:31
you know, we're really looking,
14:32
it's looking awfully good.
14:35
There are other areas that in clinical trials in a more limited way,
14:38
earlier stage, you know, maybe a little more experimental.
14:42
For example, one of the spin outs from my previous foundation has
14:46
a clinical trial going on right now in Australia for atherosclerosis,
14:49
which works, which is a treatment that involves extracting...
14:53
oxidized cholesterol from the arteries and thereby essentially allowing macrophages
14:57
to recover their function and to reverse cholesterol transport in the
15:02
way they used to be able to. It's be very promising,
15:04
so we'll see how that goes. Another trial that's actually also going
15:08
on in Australia, obviously Australia's a fantastic place to do early stage clinical
15:11
trials these days, is on my favorite anti-cancer therapy,
15:14
which is a method that essentially rapidly kills any cell that's expressing
15:20
a high level of telomerase. So of course that means...
15:22
90 % of human cancers. That's also going really well.
15:25
So yeah, I mean, there's plenty of plenty of good news out there.
15:28
But then there are also things that are not even working in mice yet.
15:31
you know, very unevenly distributed in terms of progress and in terms
15:36
of enthusiasm from the people who write checks.
15:39
Yeah, exactly. Yeah, there's things,
15:41
you know, going on with mitochondrial function also.
15:44
I know that that's pretty interesting.
15:46
People are now transplanting mitochondria,
15:48
doing some other things to rejuvenate mitochondrial function.
15:51
And to your point, there seems to be an interplay.
15:53
I I've been impressed in the work that we've done here that rejuvenation
15:58
is not really a procedure or a thing.
16:01
It's actually a process. Right?
16:02
Very good way of putting it.
16:04
Yeah. That you've actually got a
16:06
An individual, then you've got to apply the therapy,
16:08
and then you need to support the therapy afterwards.
16:10
And many times ~ it starts with taking out the things that need to be taken
16:14
out of the environment, so to speak,
16:16
before you clean up the the internal milieu and then go ahead with
16:20
the other procedures. But I think if you're listening to this,
16:23
if you think about optimization longevity itself.
16:26
as an ongoing process and not,
16:29
I'll go get a stem cell injection and then I'll be young again,
16:32
right? I think or I'm gonna take synellics and then I'll be young again.
16:35
All those things actually work together and they work together in sequence
16:38
and they work together in cycles as well,
16:40
right? So you may do it this year,
16:42
you may do it again next year.
16:43
So I don't know if you want to comment on that in terms of what you're seeing
16:46
out there. Well
16:47
completely agree. mean, of course,
16:48
as you know, my work and my team's work in this area focuses on mice,
16:53
not on humans. There we have the very interesting situation in which
16:57
the cross talk between different types of damage accumulation is very substantial.
17:04
That is why we can observe, and many other groups have observed,
17:08
very significant life extension.
17:11
in mice that you do nothing to at all until they're already in middle age,
17:15
but you do a bunch of things and they benefit.
17:18
But the point is even if you do one thing,
17:20
like for example, apply a really effective salolytic,
17:23
you can actually see life extension.
17:25
If you apply Lsk, the amino acid factors to reduce certain tissues,
17:30
then again, significant life extension just from one thing.
17:34
The only reason that that makes any sense,
17:35
the only reason that could be possible is if removing one type of damage,
17:39
if you like, relieves the pressure on the inbuilt anti-aging machinery that
17:44
I was mentioning at the beginning.
17:45
~
17:46
It slows down the flywheel, right?
17:47
It slows down the flywheel of aging.
17:49
Yeah. So we're going to see more and more of that.
17:53
would say, absolutely. need to be applying these things in parallel with each other
17:57
and of course monitoring the impact so that we know which ones to emphasize.
18:02
The only thing that's really missing right now is the comprehensiveness
18:06
of the portfolio of interventions that we have.
18:09
But you know, on the more neglected areas of this field.
18:14
They're just as important as the less neglected areas and they need to catch up.
18:19
That's still a big problem.
18:20
So
18:21
when you're working with the mice,
18:22
I know that you're the last time we spoke,
18:25
and maybe this is still true, you were looking for additional funding to bring
18:29
in to run another mouse trial that you've envisioned doing.
18:32
And maybe you could bring the audience up to speed on the first mouse trial
18:36
and kind of what you did there,
18:37
what it showed, what the second one is going to look like,
18:40
and then maybe also comment on what we were just commenting on the fact that,
18:43
you know, stacking together, layering,
18:45
interdigitating, sequencing, whatever terms we want to use,
18:49
different.
18:50
interventions can be sometimes more than additive.
18:53
Yeah, totally. So we're not even really looking for more than additive.
18:56
Additive would be quite enough.
18:58
So, back,
19:01
so of course the whole strategy of addressing aging that I have propounded
19:06
and pursued over the past 25 years or more is a divide and conquer
19:10
one where I classify the various types of damage that the body accumulates into
19:16
a manageable number of categories,
19:17
just seven categories.
19:21
Yeah, I mean, I will rattle because I've talked about those in depth
19:25
on many occasions. But yeah, so loss of cells,
19:28
such as the example I gave earlier with Parkinson's disease,
19:32
of cells, accumulation of cells that divide too much.
19:36
So of course that's a reverse of cancer.
19:40
accumulation of mitochondrial mutations,
19:42
mutations in the special DNA that's inside the mitochondria,
19:45
then accumulation of waste products in the cell,
19:47
such as oxidase cholesterol that I mentioned a moment ago,
19:49
then accumulation of waste products outside the cell,
19:52
typically something called amyloid,
19:54
which comes in various forms in different tissues,
19:56
and then finally the loss of elasticity of the extracellular matrix,
20:00
this lattice of proteins that gives our tissues their physical properties.
20:05
Yeah, so with a divide and conquer strategy for anything,
20:08
there's two phases.
20:09
First of all, you have to develop the ways to ~ the individual components
20:13
and then you have to put them together and get the overall result that
20:16
you were hoping for. And then engineering,
20:18
typically, you know, that second part is the easy part.
20:21
If the bits work, then you can be pretty sure that the assembly is going
20:24
to work overall. But in medicine,
20:26
it's not like that whatsoever because you would,
20:28
we're seeking to manipulate a system that we have,
20:30
as I mentioned earlier, a very poor understanding of.
20:33
And therefore you can expect to get surprises.
20:35
of them bad surprises at that.
20:37
second phase. So I've been desperate to get to that point since forever and ever.
20:42
And of course, you don't necessarily have to get all the components in place
20:44
in the case of medicine because of this crosstalk we mentioned earlier
20:47
and the same applies in mice. So if we get some of them working,
20:51
then it's worth having a gut. So what do I mean by working?
20:53
What I mean is demonstrating life extension individually.
20:57
And as I say, this doesn't happen in mice.
20:59
So come about 2022, we were in a position to do the first ever experiment
21:05
of this nature.
21:06
We took three damage repair interventions.
21:09
Firstly, telomerase gene therapy to extend the telomeres.
21:12
Secondly, acetylalytic, and thirdly,
21:14
heterochronic bone marrow transplant.
21:17
So we gave old mice some bone marrow stem cells from young mice.
21:21
And on top of that, we had a fourth intervention,
21:23
which was really a positive control,
21:24
namely rapamycin. So rapamycin is not a damage repair approach.
21:28
It's a calorie restriction mimetic.
21:30
Basically it tricks the body into thinking it's not getting enough food when it is.
21:33
we know the thing is, think about calorie restriction and therefore
21:37
by extension also, mimetics of calorie restriction is that they're really effective
21:42
in short-lived animals, but they really don't work worth a damn
21:46
in longer-lived species.
21:47
This has been going for very long time,
21:49
so it's definitely not the way to go if we really want,
21:52
not on its own anyway, if we want to make progress.
21:54
But it's a useful, as I say, positive control for laboratory work.
21:58
So, all of these things had been shown to extend lifespan individually a little bit.
22:04
And we thought, well, okay, what we want is to see whether we can
22:07
get an additive effect, whether if we put them all together,
22:09
we can get more benefit. And the great news is that that is what happened.
22:14
The study ended about 18 months ago and we indeed got an additive effect.
22:19
Well,
22:19
How about it affected you guys?
22:21
I'm going to come to that in a moment.
22:22
It was clearer in female mice than in males,
22:25
but it was clear. All right, but you asked the exact right question.
22:28
How big was the effect? And that was where we were disappointed.
22:32
We did not get an effect that exceeded what you can already get with rapid mice
22:37
in our time or in the recurrent section on its own.
22:40
That's what we're aiming
22:40
I see.
22:42
for.
22:42
Many years ago, I actually specified a kind of arbitrary threshold that
22:47
we want to achieve with all of this.
22:49
I call it robust mouse rejuvenation.
22:51
So to put numbers on this for your audience,
22:53
typical mice, healthy mice will live about two and a half years on average.
22:58
So our treatments, as I say, we start in middle age.
23:00
So we start when the mice are already 18 months old.
23:03
So they've got a year to live.
23:04
And my arbitrary threshold was we want them...
23:07
double that. We want to take them out by a whole year,
23:10
whole 12 months more than what they would normally live.
23:12
Now, for kind of context, calorie restriction started at that kind
23:16
of age will typically give you about four months.
23:19
So we're seeking to treble that effect side.
23:22
And rapid-mesting gets more or less the same,
23:23
a little bit less maybe. All right,
23:25
so we did not beat the four months.
23:26
What does that tell us? What does that leave us as the next step?
23:30
Well, to me, it was very clear at once that what we need to do is simply throw more
23:35
of the kitchen sink at the problem.
23:36
In other words, see whether we can get to 12 months or even eight months
23:41
by putting a lot more things together,
23:43
not just three. And the thing is back in 2022 or so,
23:47
when we were first formulating this study,
23:49
that was just not possible. Or rather it was possible only if we were more relaxed
23:55
about the criteria for inclusion of a particular component.
23:59
We just didn't have enough interventions that had been shown by anybody
24:03
to extend lifespan individually.
24:06
What's about for a study that changed a lot.
24:08
A whole avalanche of new studies came out with new ways to do this
24:14
and ways that were not coloristic or genetic.
24:16
And I say we kind of want to avoid those because they're not going to translate.
24:19
And so now, yeah, we're almost spoiled for choice.
24:22
The study that we have currently designed that's been waiting for funding
24:25
is with eight interventions. Again,
24:28
not including Rappamycin. We're going to use Rappamycin again as
24:31
a positive control in broadly the same way that we did last time.
24:34
What are the agent adventures you're looking at?
24:37
Well then,
24:37
so first of all, ~ we could of course reuse some of the original ones,
24:42
but we're so spoiled for choice that we're deliberately not doing that.
24:44
We're going to use new ones. All right,
24:47
so the first one is OSK that Yabunaka factored.
24:49
So Yamanaka Factors is epigenetic reprogramming of cells that was developed by Dr.
24:54
Yamanaka and somebody else actually in Japan.
24:57
I think they got the Nobel Prize in 2008 or 12 or somewhere in that ballpark.
25:02
The study was published in 2006 and the Nobel Prize was 2012.
25:05
That's right. Incidentally, coming back to one of our earlier topics,
25:09
the first author on that, it was just a two author paper for just
25:13
an enormous amount of work. Completely astonishing.
25:15
The first author on that, John Takahashi,
25:17
is actually the PI on one of the Parkinson's trials that I was mentioning.
25:22
Okay.
25:23
This is where just for the audience's sake,
25:24
this is where the induced pluripotent stem cells showed up,
25:28
where you could take a skin cell and turn it back into a stem cell
25:30
by using the amino que factors to to make it young again,
25:33
so to speak.
25:34
Yeah, actually, know, paradoxically,
25:36
Takahashi is not using iPS cells,
25:39
even though he's doing genetic treatment.
25:41
There's only one of these, I think,
25:42
five trials that are going on right now that is doing an autologous approach,
25:46
that's Gene Loing's approach to Aspen Neurosciences.
25:49
Anyway, back to the topic. So,
25:50
what are our interventions with AFK?
25:52
We're using exosomes derived from MSCs,
25:56
and there actually we still have a bunch of choice.
25:58
We have not firmly decided what source we're going to use,
26:02
but we've...
26:03
There's plenty of reports of really good results there.
26:05
So we're definitely going to use something along those lines.
26:07
Then we have a senolytic, but not the same one.
26:10
We have a senolytic that we believe is a lot better than the first generation
26:13
one that we used last time.
26:14
What did you use last time?
26:16
We're using a vitaclax. Actually,
26:18
not exactly a vitaclax. There's a Spanish group that we're able to modify
26:21
a vitaclax so that it's no longer toxic to platelets.
26:24
Right. is what it's going be. This
26:26
What are you using this time?
26:27
time we're using something that comes from an Austrian company named Rockfish Bio.
26:31
and it works by a very different means.
26:33
It essentially messes up arachidonic acid metabolism in a way that
26:37
the nascent cells seem to be very,
26:38
very sensitive to. Yes,
26:41
it is. It's fascinating. They've got really cool results.
26:44
We've got a few others, of course.
26:46
We've got, let's see, so people showed that you could use antibodies against
26:49
an interleukin, IL-11 specifically,
26:52
and that would give life extension,
26:54
even if you started relatively late.
26:55
Then another thing that you can inhibit,
26:58
and this time with a small molecule,
27:00
something called CDC 42, a cell cycle gene.
27:02
There's a small molecule called casein that modifies that.
27:07
Sorry, that inhibits...
27:08
Explain that a little bit. That's a little garbled,
27:10
I think, for the audience.
27:12
Probably shouldn't try to explain the mechanisms of all of this because as I say,
27:16
all of this is published and it would be better for the audience to go
27:20
to the things that I can show you.
27:21
But I have a slide in most of my talks these days,
27:23
which gives the PubMed IDs for all of the key studies.
27:26
Okay. Just so that everybody could do that.
27:29
I'll send you that slide so you can stick it in the show notes
27:31
or something like that.
27:32
Beautiful. Yeah, let's do that.
27:33
And then the very top, oxytocin is another one that we're going to
27:36
use combined with an inhibitor of something called ALK5.
27:39
But that again has been shown to give no slice extension.
27:42
You get the idea. It's a wide variety of things that work in very different.
27:47
So you're combining oxytocin with what again?
27:50
It's something called AI5, which is an inhibitor of a gene called ALK5.
27:54
And again, this has been done before.
27:56
This was not our idea.
27:58
And why leave off the things that are going to improve telomerase activity
28:02
or some of those kinds of things?
28:04
To be perfectly honest, the main reason why we have made the choices
28:07
we have is because we're focused on getting as much knowledge as possible
28:12
per dollar and per unit time, of course.
28:14
And the last study cost about three and a half million dollars.
28:17
This study, we've got a few cost savings,
28:20
it's twice the size. So it's going to be probably six million dollars.
28:23
If somebody dropped 30 million dollars on me today,
28:25
then I would totally do two, eight intervention studies in parallel,
28:29
maybe three, because we can.
28:31
you know, because there's enough options out there.
28:34
And for that matter, because there are questions about dosage.
28:37
Yeah, it seems like it seems like there's lots of questions around that,
28:40
right? Like what combination, what sequence,
28:43
what dosing, what duration, what frequency.
28:47
~ there could be many, many
28:48
The
28:48
horrifying thing is that nobody's doing it.
28:51
There's billions of dollars floating around being used for just
28:53
a small proportion of the things that are interesting like Yamanaka factors
28:58
or so on and so much more knowledge could be gained by doing this kind
29:04
of work.
29:05
So is it do you think there's any ~ possibility to do some preliminary work
29:09
now with the advent of AI and things like that in terms of like in silico kinds
29:14
of conceptualization of what you're trying to get to or?
29:17
There is, but at end of the day,
29:19
it's not a substitute for these laborious and relatively expensive studies.
29:23
Because the fact is, you know,
29:25
people can get this wrong, but AI does not create knowledge out of thin air.
29:28
creates insights out of data. so you have to start somewhere.
29:33
And certainly, you know, the work that has been done,
29:35
including especially by IntelliCo Medicine,
29:38
Alex Over Rodkoff's company, has been extremely valuable and impressive
29:42
and it will continue to get better.
29:43
But at the end of the day, you know,
29:45
they are working towards clinical trials for particular drugs based
29:49
on data that they can, especially omic data that they can,
29:52
they can analyze. My goal is to get results that
29:58
the public will resonate with.
30:01
Now, you know, that's something that bears some
30:04
So what do you what do you mean by that?
30:06
Results that the public will resonate with?
30:08
What do you what are you looking for?
30:09
People can look at and intuitively understand it or
30:12
So
30:12
not exactly, no. The ultimate thing that I'm looking for is mobilization
30:16
of society in general. So my standard slogan these days is that
30:22
our goal is to make aging the new COVID.
30:25
I want us to be able to take aging as seriously as we took COVID six years ago.
30:30
Of course, you can argue that mistakes were made here and there in terms
30:33
of how this whole thing was done,
30:35
but the point is humanity got its shit together.
30:38
And so we have this new problem.
30:40
We're not in favor of COVID. We'd like it fixed as soon as possible,
30:43
please. you know, I mean, the standard example that I often point out
30:47
is the sheer time frame that was involved in developing and distributing vaccines.
30:52
Multiple vaccines were developed and globally distributed in less than a year.
30:55
And as I'm sure you know, the world record fastest that had ever been done before
31:00
for any vaccine for anything was 10 years.
31:03
an entire digit was taken off the time frame.
31:06
And the way that that happened,
31:08
of course, was the governments around the world just tore up all
31:12
of the regulations and the institutional inertia and everything that they
31:15
had written at the behest of their electorate,
31:18
right? Just because they sensed that the electorate didn't want that to
31:22
be a barrier this time. So we did the same thing again.
31:25
question is how? And, you know,
31:28
my personal belief is it's a kind of domino effect that in order
31:31
to get governments to do what you want,
31:33
that's the easy part. They will do whatever they think is going
31:35
to get them re-elected.
31:36
So we have to change pub. have to get the public mobilized.
31:38
How do you do that? I say that the right way to do it is through
31:42
the world's leading influencers,
31:45
know, Joe Rogan, Kim Kardashian,
31:46
Mr. Beast, people like that. Now the good news is that these people
31:49
are already really interested in longevity and they don't mind people knowing it.
31:53
You know, I've been on Rogan a couple of times,
31:54
think I've been on Rogan a few times and so on.
31:56
So that's great. They're one step away from going out and doing
32:00
the equivalent of Oprah saying buy this book.
32:02
All they need to do is say, right boys and girls.
32:05
~ We seem to be at a point where we could bring aging under medical control
32:08
and save a lot of lives and alleviate a vast amount of suffering.
32:12
We really ought to do that as quickly as we can.
32:14
And once they say it, game over.
32:16
So the question is what is stopping them from saying it today?
32:19
And to my mind, that's completely clear.
32:21
The thing that's stopping them from saying it is that with the sole exception of me,
32:25
the experts in the community that go on these shows are
32:29
not giving actual numerical
32:33
time frame predictions of how soon they think we've got a good chance
32:37
of bringing aging under control.
32:38
That's really important. I've been complaining about it for 20 years that
32:41
my colleagues won't do that. Because the fact is,
32:44
know, my colleagues go out all the time and they're terribly breathless
32:47
on camera and on stage about this or that recent breakthrough that they made.
32:51
But if they don't actually, if they're unwilling,
32:55
if they refuse to give any kind of time frame prediction,
32:58
then there's no credibility whatsoever.
33:00
You know, everyone just thinks that they're just no...
33:03
being breathless in order to seduce somebody or other into letting them carry
33:07
on playing with their test tubes and they don't really believe it's going
33:09
to get anywhere ever. So I believe that that's got to change.
33:12
And here's the important thing.
33:14
Governments don't give a flying fuck about mice,
33:17
right? The public don't care about mice either.
33:19
To be perfectly honest, the influencers don't care about mice either,
33:22
but the experts do. And here's what I mean by the experts.
33:26
There are probably several hundred people around the world
33:30
who are perfectly entitled to
33:31
describe themselves as experts on the biology of aging.
33:34
But I don't know several hundred people.
33:37
There are only literally less than a dozen of us who do all that much outreach,
33:41
who actually, you know, give, for example,
33:44
a general audience podcast more than once a month.
33:47
You know, I do about two a week,
33:49
right? There's literally less than a dozen of us.
33:51
There's me and David Sinclair and Eric Verdon and Neil Basile and Brian Kennedy
33:55
and Matt Cabley and Andrea Meyer and Eva Bischoff and...
34:01
I can't think of any others. You know,
34:02
it's insanely few. And of course we're all good friends.
34:06
We know each other really well.
34:07
So I feel justified in my confidence that I know what it takes
34:12
for them to switch and to say,
34:15
okay, boys and girls, we are in a different world suddenly as a result
34:18
of of X breakthrough. And that would kind of give them feel,
34:24
make them feel safe in going out and doing production for time frames.
34:27
which might not be the same predictions as mine,
34:29
but that's okay. Any prediction is farther than that.
34:32
And I believe that the thing that will make that happen is reaching RMR,
34:35
Reaching Robust Mass Rejuvenation.
34:37
So that's why I'm focused entirely on trying to make that happen.
34:40
Yeah. Well it's it's interesting perspective and good points.
34:44
I tend to be very optimistic about being able to link these different procedures
34:48
together. I think the studies are very important.
34:51
You know, you're working in the areas that that you elucidated early on
34:55
and now have been, you know, kind of expanded further right into to
34:59
the hallmarks of aging and things like that.
35:01
I should probably say something about the hallmarks,
35:03
since you mentioned them, because people do often misunderstand this a bit.
35:07
The original hallmarks paper came out in 2013.
35:09
And to me, it was extremely gratifying because to a first approximation,
35:14
it was a restatement of what I'd written more than a decade earlier.
35:18
But I had done the hard work and its time had come.
35:22
And so people were ~ willing to accept this divide and conquer approach,
35:27
this classification.
35:29
Since that time, I have never once had to actually justify that approach
35:33
to my colleagues. Whereas this decade was quite a fight,
35:37
to be honest. But here's the thing.
35:38
The hallmarks do not really classify the same thing that my Seven Deadly Things
35:44
classify. I was classifying types of damage that accumulate.
35:47
This was to, of course, align those individual categories with particular approaches
35:52
to intervention, to repairing the type of damage.
35:54
What the hallmarks do is they classify something that's kind of
35:57
one step downstream of that.
35:59
they classify the decline in this or that molecular or cellular process that arises
36:05
from the accumulation of damage.
36:07
So for example, I will talk about the accumulation of waste products inside
36:11
the cell, whereas the whole might talk about loss of proteostasis.
36:14
In other words, the function of protein turnover.
36:17
And this actually turns out to matter because the classification
36:22
of what happens downstream of damage is very soft.
36:26
It's like...
36:28
constantly having to change. And so it's no surprise at all that
36:31
the hallmarks have had to be constantly updated,
36:34
know, first it was nine, then it was twelve,
36:35
then it was fourteen and so on.
36:36
Whereas my seven deadly things have very much stood the test of time.
36:40
Yeah, I think I think that's an interesting point too.
36:43
The way I think about the hallmarks is that they're phenotypic expressions
36:47
of aging and then they also play together to accelerate aging.
36:52
Yeah, exactly. That's certainly true.
36:53
Yeah. However, the the damage that you're referring to,
36:57
what do you see as being the mechanism underlying that then?
37:01
This is the beauty of the whole science approach is that I don't really have
37:07
an opinion about that and I don't need to have one.
37:09
Essentially, because damage accumulation is this kind of mediator,
37:14
it's kind of intermediary between being alive and being dead.
37:17
In other words, you know, the network of processes of metabolism
37:20
and the various pathologies that happen later in life.
37:23
Because it's sitting in the middle,
37:24
kind of, if we're repairing that damage,
37:28
then we don't need to have much understanding of the mechanisms of how
37:31
the damage is created because we're not seeking to slow down that process.
37:36
The whole of gerontology before me basically constituted that.
37:40
It constituted looking at the living world,
37:42
seeing well, know, some species age more slowly than others.
37:45
They kind of run more cleanly and accumulate damage more slowly.
37:49
Maybe if we understand that really,
37:50
really well, then we'll be able to translate that understanding into some kind
37:54
of therapy. And it was all completely unsuccessful.
37:57
But if you're repairing the damage,
37:59
if you're intervening one step beyond that,
38:01
then you can let damage accumulate at the natural rate,
38:05
which means you don't need to understand how it accumulates.
38:08
Yeah, I see what you're saying.
38:09
However, I can't help quite honestly,
38:12
I I I just can't help myself but to to go wanna look behind the curtain
38:17
and think about things like oxidative stress and ~ you know,
38:21
other things that are actually causing the damage,
38:24
you know. It's ~
38:25
Yeah,
38:25
I don't object to understanding.
38:27
But the thing is, if you are seeking to intervene at the level of
38:32
the mechanisms of damage creation,
38:34
then the fundamental reason why it hasn't worked is that those mechanisms,
38:39
whatever they are, and to whatever extent we actually understand them,
38:43
those mechanisms are just too inextricably intertwined with the things that
38:48
we need the body to do to keep us alive.
38:50
Fine example here, because, you know,
38:51
of course, way back...
38:52
In the 1950s, when Denham Harmon first suggested the free radical theory of aging,
38:57
he promptly got into the lab and started giving antioxidants
38:59
to mice because antioxidants were already,
39:02
that was already a thing back then,
39:04
knew what antioxidants were, free radical scavengers and so on.
39:06
And they made mice live a bit longer on average,
39:10
but he couldn't extend maximum lifespan at all.
39:13
And something that is very much neglected that Harmon did after that in 1972
39:19
was he was the first person to identify
39:21
possibility that mitochondrial mutations could be important in aging as
39:25
a way to explain what he was seeing.
39:27
However, a huge part of the explanation which came along later
39:32
was the understanding that reactive oxygen species are actually,
39:36
know, evolution has made the best of a bad job.
39:38
It's got this ghastly thing called oxidative phosphorylation that creates free
39:41
radicals. There's nothing that we've done about it because,
39:43
you know, extracting energy from nutrients with oxygen in the very,
39:46
very hairy chemical process.
39:48
So you're going to make free radicals,
39:49
you you're just going to live with them.
39:50
And so what's happened is that reactive oxygen species have become woven into
39:55
metabolism as signaling molecules,
39:57
especially hydrogen peroxide. And that means that if you chuck in
40:02
a bolus of something that scavenges hydrogen peroxide or other free radicals,
40:07
then the body will not be happy about this.
40:09
It will want to do something and it will actually down-regulate
40:12
the enzymatic antioxidant machinery that it already has.
40:15
And everything will stay the same.
40:16
Essentially metabolism lasts in your face.
40:18
So that was the kind of thing that led me to,
40:21
mean, because this is not new ideas,
40:23
right? This is something that was generally accepted in the nineties.
40:26
So this is one of the kind of ways of thinking that led me to the idea that,
40:29
you know, we shouldn't be intervening in this.
40:31
We shouldn't be trying to mess with metabolism.
40:33
We should go one step further down the street.
40:35
Well, it's an interesting point.
40:37
~ putting on my engineering hat,
40:38
I always kind of feel like the metabolism can always be kind of fine tuned,
40:43
right? Kind of like getting your car to run better.
40:46
Well, I mean, actually, no. mean,
40:47
I use cars as an analogy all the time,
40:49
as you know. Yes, let's look at rust.
40:52
know, mean, rust happens. It happens faster in some cars than others,
40:57
but that's a function of how the car was built and designed.
41:00
If you want to maintain a car to last longer than how it was built
41:04
and designed to last, then you don't need to understand the chemistry of rusting.
41:08
All you need to do is scrape off the rust and get rid of it every so often
41:12
so that there's never enough rust to make the doors fall off.
41:15
Right. Well, yes, or you could use,
41:17
you know, something that would protect the door from rust developing
41:20
in the first place. Right.
41:21
Well, that's right. That's how you would build the thing.
41:24
You know, if you were building the car from scratch.
41:26
Yeah,
41:27
what you're saying is we don't the option to build a de novo.
41:30
Yeah, it's it's it's really an interesting interplay of prevention and repair,
41:34
right? Because we do know that there are choices we can make that accelerate damage,
41:40
right? And decrease repair. And so yeah.
41:45
And that's where today's medicine comes in.
41:48
The area that you're the expert in and I'm not.
41:51
What we can do today can somewhat optimize what people have.
41:56
Everyone's got their own weak links.
41:57
I've got the variant of MTHFR that gives you high hemocysteine,
42:01
things like that. And optimizing for those things with tools that exist today,
42:06
that example, of course, is a particularly easy one because methylcobalamin just
42:10
does it. It just fixes the problem.
42:13
~ I'm all over that. But of course we all know that there's a limit to
42:19
how much we can do that. What we really want is something that works
42:22
far better than anything that works today,
42:24
however optimized it may be.
42:26
I wonder with this repair model that you're working with,
42:28
if you go back to the mice, if intermittently treating them with muse cells
42:34
or muse cells and exosomes and some peptides,
42:37
you know, kind of a nice combination.
42:39
Maybe start with some synellics and then,
42:41
you know, kind of clean the system to some extent,
42:43
put in these things. I it seems to me that
42:46
Just like taking care of a car is an ongoing process.
42:49
It seems like maintaining youthfulness is a process of returning
42:53
to youthfulness and then maintaining it.
42:55
And so there's gonna be maintenance,
42:57
right? Yeah.
42:58
Absolutely. Periodic is the word.
43:00
Then of course it's slightly more than that because the reason I,
43:04
well, the thing that led me to come up with this concept
43:06
of longevity escape velocity was the understanding that at first when
43:12
we get treatments that are only fairly comprehensive,
43:16
but not a hundred percent, it won't really matter how often we apply them.
43:20
There will still be the, let's call it the difficult damage,
43:23
the damage that the therapies just don't repair.
43:25
~
43:26
progressively accumulated and eventually on its own,
43:28
however frequently we are repairing the easy damage,
43:32
we're going to end up having enough damage to make us sick and eventually
43:36
to kill us. So the whole LEV idea revolves around the recognition that if
43:41
we can get maybe 20 years of additional healthy life for people with version
43:46
1.0 of this portfolio, of this panel.
43:49
That will be enough time for the researchers to hack away at
43:53
the difficult damage and to shift some of it into the easy category,
43:56
the category that can be ~ repaired,
43:58
so that when someone comes in 20 years later and they need to be rejuvenated,
44:02
we can actually do it and give them another 20 years.
44:04
Sure.
44:05
Now, this, of course, leads to the rather paradoxical conclusion that
44:09
we have a pretty good chance of reaching longevity escape velocity
44:12
for humans fairly soon, but it'll be touch and go whether we ever reach
44:16
it for ~ cats and dogs.
44:18
And we definitely will never reach it for mice because repairing most
44:23
of the damage just doesn't buy enough time to figure out what to do.
44:27
Interesting. That's interesting.
44:28
So I'm curious about a couple of things here.
44:31
One is what year were you born?
44:33
1963.
44:35
Sixty three. Okay. And what are you doing for yourself at this point
44:39
in time with regards to your own longevity program?
44:42
I'm doing two big things. First of all,
44:44
avoiding dying of anything stupid.
44:46
One thing I've said for quite a long time when people ask me that question
44:50
is I don't accept seminar invitations to dangerous countries.
44:53
Yeah.
44:54
Things like that. But the other thing is I get checked up really,
44:57
really well, partly because of who I am.
44:59
I've been able to access for free treatments that are really high end
45:04
for the past 20 odd years to measure various aspects of my biological age.
45:07
You the usual things measuring 150 different things in your blood and know,
45:11
cognitive.
45:12
physical things and Dexam CT scans and MRIs.
45:15
I now get that from human longevity,
45:17
which is a fantastic organization.
45:19
We're the very best who do this kind of thing.
45:21
And yeah, I mean, it's really important.
45:23
It's like, if you, this is one thing that I believe is the number
45:27
one thing that Brian Johnson has brought to the table in in the few years he's been
45:31
so prominent is he's so strong on measurements.
45:33
Obviously he's, he spends $2 million a year on his own.
45:37
mean, he has an MRI machine in his house.
45:39
Right.
45:41
The point is even if you've only got $2,000 a year to spend,
45:44
you can still use it very effectively to give yourself more knowledge about what
45:48
your weak links are and what kind of things that are available today
45:53
you can do about those things.
45:54
And most people, let's face it,
45:56
will probably only be able to gain a year or two at most relative to just living
46:02
the way their mother told them to and not smoking and
46:04
not getting seriously overweight and so on.
46:06
But some people can gain more than that because they've got serious weak links that
46:09
can be addressed.
46:10
And also some people refuse to live the way their mother told them to anyway.
46:14
Sure. Yeah, no, I get that. Well,
46:16
cool. Well, Aubrey, it's been a pleasure chatting with you.
46:19
~ appreciate coming back on. Yeah,
46:21
always always good stuff. I'm sure our paths will cross again,
46:23
but thank you so much for taking the time.
46:25
Totally.
46:26
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46:28
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46:30
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