| 1 | The Longevity Forum | The Potential and Realities of Partial Reprogramming | Daniel Ives | 364 | 16 | 2 | 72.4 | neutral | 26:46 | [music] Yeah, thanks for the invitation and uh really excited to uh share some of the work our team's been doing. So um just to begin with, why is uh partial reprogramming reprogramming exciting and it's uh because you know fundamental unit of the body is the cell and where is aging coming from? It's coming from every cell in your body. So if we can get to the bottom of aging in a cell and we can cut across the body and to get to all of your cells, we might do something quite dramatic to lifespan. So that's the idea. This is seems to be a point of leverage. Obviously, we need to prove that, but that's uh sort of behind the excitement. Well, I've broken the presentation. Sorry. [clears throat] Thank you. Let's try this. >> Okay. >> Oh, yeah. >> It is a >> Okay. So, I'm going to switch the t I'm going to switch the title up a bit. So, firstly talk about the realities and then I'm going to talk about the potential. So, realities is sort of summary of of what is known at least what is known uh in my head and sort of more broadly in my team. prefer to use that. Oh, >> thank you. >> Yeah. >> So, Shinyamanaka, Japanese scientist who in the mid 2000s discovered how to turn sematic cells or your skin cells into stem cells. And what we didn't realize at the time is that the biological age of those stem cells at the end of this process was zero. So it actually reversed age and so you looking at these stem cells they were remarkable. They behaved like embryionic stem cells and you know embriionic stem cells do have a age of zero. So there was a little bit of evidence uh this had happened but it wasn't until um a little bit later that uh there was a more definitive result. So um Steve Hall back in 2013 discovered uh the multi-issue DNA methylation clocks a very robust biomark with age highly correlated with age in single tissues works across multiple tissues um you know I could talk a long time about clocks I won't for this presentation but Chandra at University of Edinburgh basically took an data and uh applied the clock algorithm to the methylation data. So this blue line is the methylation age of 62y old fiberglass and over a period of expression of about 50 days of young. So you can see uh between 0 and 20 days the clock reversing from 62 years all the way down to zero which at the time was an astonishing result like slowing down aging or stopping aging was exciting enough let alone reverse aging. So at the time this result was published I just disproved the hypothesis behind my company shift I was looking at mitochondrial DNA damage and the clock was not responding to this damage even though we had a therapeutic approach simultaneously chandra showed that not only could you do something about the clock you could reverse it so it's quite clear at that point there was something really exciting going on under the bonnet of yam factors um so why not why not use factors all across the body. Um, let's see what this does to lifespan. You know, why why try any harder? And uh the reason is obvious in hindsight is because these factors were always designed to make stem cells. That's what Shyamanak was optimizing. How do I turn an adult cell into a stem cell? So that was the feature he was optimizing. The bug was rejuvenation. So you got to remember these are poor potency inducing factors. That's what they were designed for. And one of the qualifying assays for chlorotency factor is when you express it in an animal, it creates a multi-tissue tumor called the terterat. This slightly grizzly picture at the bottom. Uh there's a two arrows pointing to two grows that shouldn't be inside the body cavity of that mouse. So I think the bottom line is this is incredibly exciting that you can reverse the age of cells. Um but clearly there's a lot we don't know. um specifically everything about rejuvenation apart from the amanaka factors that's all we know at the moment there's these four factors never designed for rejuvenation but aren't we lucky that we happen to encounter uh cell rejuvenation in the first place so this reversal in cellular age doesn't mean anything beyond the clocks and does it mean anything beyond hallmarks of aging which are also reversed and the answer is yes. So in 2016 a scientist I think on the west coast to begin with called car mante he showed a proje mouse so this is a mouse where you mutate a nuclear lamin to create a protein called projeran where those mice basically show accelerated aging um even in the presence of that mutation if you overexpress young you can increase uh the lifespan substantially so remember the mutation's still there and then you're using an acopat which don't seem to have any direct uh link to the mechanism of action of this model. So you overexpress the balances and you increase lifespan. So I think synthetic rescue might be the appropriate term. Um and it wasn't until much later that this result was reproduced in just physiologically aged mice. So not special projuroid mice that age faster but just mice black 6 J mice that have lived 2 years. Um and it was rejuvenated by it's actually a commercial initiative not scientist or scientists within a commercial initiative. the overexpressed OSK. So this is three out of the four factors but minus the oa gene cate those those three fats were put into an ada virus with quite a broad tropism meaning it can go across lots of the body the idea being try and rejuvenate lots of cells and that would have greater impact on lifespan and they were able to double remaining lifespan according to median lifespan so this was a result that was conspicuous by its absence for quite some time but that result finally came in I think it was two two or three years ago now So these factors can have an impact on lifespan. Uh there are other interventions that impact lifespan more significantly. Um but this does show you there's a proof of concept like if we reverse age we can also impact lifespan and then for any reprogramming these are some of the latest studies. So this is uh again a publication by John Carlos Bonte and he what characterizes a new hallmark of aging which is most of well the identity of most of the cells across your body seems to drift towards fiberglass identity specifically activated fiberglass identity as you get older. So it's quite an interesting phenomenon like this loss of self at least at the cellular level and he shows that partial reprogramming pulls that back. So you've got this new hallmark of aging. He hasn't called it a hallmark, but for the sake of argument, there's a new hallmark of aging and reprogramming is reversing that as well. So I talked about the clock, but here's a new feature and that's reversed. Um David Sincler in collaboration with Jonathan Weissman. He's one of the scientists behind single cell bombing technology. So I take this quite seriously. And he characterizes a downstream pathway of the amateurs which is sort of resilience pathway and basically shows that reprogramming is activating this resilience pathway and that might have something to do with uh benefits in vision loss which is one of these early applications for matters. So that's some of the latest papers. Um so moving on to the potential of partial reprogramming. So um to begin with I just want to describe the technologies we use to find um some new rejuvenation genes. I won't be able to uh discuss this in a lot of detail today. We have a much longer talk. So I'll just discuss those at high level but um I will then move on to the findings which sort of uh they they make the tools more credible. The fact we actually found something in the first place otherwise they just be some interesting tools but they they did actually come together and do something useful. So there's tool two tools and and these are both products of machine learning that I want to discuss. So one is a single cell aging clock. So you might have heard of epigenetic agent clocks. This is a a way to robustly measure biological age but at a bulk level in a like a whole petri dish of cells. You can't look at the single cell level and what's going on with aging. Um so yeah, one of the things I spend a lot of time with my team doing is uh building a big data set of uh lots of different uh fibroblasts of different ages collecting the methylone collecting the single cell transcriptto and with machine learning finding a way to predict methylation age at a single cell level from the transcriptto. So we we have like a proxy of the methylation clock um within gene gene expression. Um so that's tool number one. This is a this that's a product of machine learning a single cell agent clock. Um the second tool is actually uh sort of blows my mind this exists but it does exist. So so we call it a virtual cell. There's other labels for this uh I think self activation model cell simulation but just describe where this thing comes from. So if you take a machine learning model like a transformer or graph neuron there and you feed it single cell data. to single cell transcript data from tens of millions of cells. It learns the relationships between the genes. You know, by looking at enough cells, it can establish if gene A is up, Gene B is down, gene C is up, gene A and Z are down, right? You can look at enough cells and now it understands how genes impact each other. And you can put that in a computer and in silicon you can say, oh, I overexpressed two genes. What's the impact on the rest of the genes? And when you have a single cell aging clock, you can comp you can convert that gene signature into an age. So you're able to do these vast campaigns of experiments. So this on the right hand side is a campaign of virtual experiments. It's about 350,000 experiments would have taken 5 years to complete in the web. Even with a single cell clock, it's about one week of compute. So you can see the the power of having these uh virtual cells. You can basically do every experiment you ever want to do and take the most exciting results effectively from the future by sort of reaching into the future picking out the best result and that's what you get to test. So I think my favorite my favorite line is you can compress three centuries of future experiments into less than one year compute. So it's like getting into the Delorean going to the 2300s running down the gene combination bringing it back home testing it. Those are the interventions we're testing at the moment. So for the whole guide of view um we have change in age of virtual cell along the bottom. So what was you know when we overexpress different combinations of genes what what impact does that have on the age of the virtual cell? So you actually see this peak of 2 and 1/2 years which is an artificial shift to the right hand side because we electrocute the cells in the training data. So we think there feature of acute electrocution. So don't put your finger [clears throat] in the socket. you'll be two and a half years older and but it's a normal distribution on each side of that. So in the green box are pairs of genes that rejuvenate the virtual cell. In the red box there are pairs of genes that age the virtual cell both of which are interesting from a intervention perspective. We might want to overexpress a rejuvenation gene uh or combination of genes or we might want to inhibit proaging genes that might be good for us as well. And clearly inhibition is much easier to do as a drug. Like most drugs are inhibitors. Um and there's just more options in terms of getting to the whole body. So is this useful? Right? That's that's the question. Is it useful? And yeah, the answer is yes. And the great irony of having a virtual cell and a single cell agent clock is that the whole reason we built those tools was to explore combinatorial space. before we have to explore all combinations of two genes, three genes, four genes because the acts are four genes overexpressed together. That's what we know. So we're trying to find something better. Let's stick with what works. Um and the first thing the virtual cell told us were there were single gene drivers across different combinations. So the same gene would feature across different combinations of genes that rejuvenate the virtual cell. And this gene um initially this was a speculative experiment. said let's take this gene called sp0 that's a coping and on its own so this graph in the middle is the change in epigenetic age now these are real cells now in the dish using epigenetic clocks I'm just showing you the most robust clock that we use called the principal components going clock from Steve can with Morgan uh doing a principal component transformation on top of it again I could talk about clocks a long time but it's this is the rob most robust one that we rely on and you can see that GFP we have no change in age over the duration of the experiment which was 6 weeks. So this is constitutive expression over 6 weeks and OSK this is in a bulk population not in a sorted population. Um we rejuvenate 2 and 12 years a single gen trip0 rejuvenating 5 years. So we're it's roughly double the velocity of rejuvenation. Um on your right hand side um this was a key result for us which is we're trying to find safer rejuvenation. So again factors they have this chlor potency inducing feature with that feature. Can we get away from that dangerous activity and uh the answer is yes doesn't come out very well um on this on this screen but uh you have four panels um you see OSK and OSKM you see this white dotted line that's the boundary between white glass on the outside and a colony induced forent stem cells growing outwards. So you see with OSK after 42 days you do see colonies grow OSKM you see lots of colonies as expected but SP0 control you don't see the colonies so we very excited to identify a single gene sufficient to reverse the epigenetic clocks it's not reversing aging right that comes later but at least this is our screening system reverse those clocks and not induce latency so the next question for us was can we rejuvenate different cell types because these are just fiberglass and ultimately we want to rejuvenate as many cell types as possible go across your body and yeah see what happens after that and uh there is a lot of good news in this presentation it's not all good news though um so um I'm showing you two cell types each with four different epigenetic clocks just to show you how robust this single gene is so uh we've got principal component skin blood principal component multi tissue generation H2 and you see GFP OSKS0 and you can just see like robustly we're rejuvenating across those different uh clocks and carrot insights were also robustly rejuvenating across those clocks but a much higher velocity. It's very interesting. This whole discovery system was built for fiberglass. When we try in a different cell type, we were worried about not rejuvenating that cell type. We actually see more rejuvenation in the keratinosite surprisingly. And that seems to be more robust than OSK and keratinosites in the one in two of the clocks. You're seeing a sort of abnormal result with OSK. We don't have an explanation for that. Um, and at this point we've discovered uh 190 genes that impact our single cell aging clock. So 40 in the proaging direction, 150 in the rejuvenation direction. Clearly some of them are more significant than others. Um, and S0 is highlighted on this plot. So this this is basically a way to represent single cell data. Uh, each dot is a single cell. If the dots are close together, that means the gene expression is similar. They're far apart. that gene expression was different. The color of the doll is how uh the age of the cell changed during the experiment. So it's very blue, it got younger. It's very red, it got older. And so in total, we found 190 interventions. We actually we ran a poll internally like how many do you think we'll find? Some crazy guy 150. He wasn't crazy enough. It's great when that happens. You know, it's so so hard to get anything to work fromology. And when when this, you know, when this came in, this was sort of a moment of celebration. Um we found at this point around 30 genes that reverse epigenetic clocks significantly 10 of which outperform RSK. So you see this red dotted line is OSK and 10 genes but individually it's sufficient to rejuvenate the excess OSK. So it looks like rejuvenation is more distributed than we expected and it's not just um exclusive to matter. It seems to be we don't know what the mechanism is, right? But it seems to be more distributed than we expected to begin with. Okay, let me get back to the right slide. And yes, I I'm just going to highlight go back here. So I've highlighted two genes. One is SP0, but one is a proaging gene called SP 101, which originally we overlooked because, you know, we're not interested in making people older, but I sort of talked about maybe we might want to inhibit pro-aging genes because that's more druggable, right? We could develop we're more likely to develop something like a small molecule that can go across your body and impact that type of gene. So, this gene is very special because SP 101 is is widely expressed across the whole body. So this is exciting because if we could do something with this gene, we could impact it across the body. It's only expressed in a few cell types. We can only impact it in the cell types, but this gene is expressed across the body. And more than that, it's actually been used outside shift to impact lifespan and reverse fibrosis. This was the first time the data took us to a specific disease target. Some sort of a big question for a company. How do you birth this new type of therapeutic through a disease focused regulatory path? So yeah, this gene to histo fibrosis and so we brought uh we brought this intervention into our own systems and we tried to inhibit this gene now because when you overexpress it ages itself but is it reciprocal if we knock it down can we rejuvenate and the answer is yes and so we're able to get about one year uh rejuvenation per month velocity by sRNA knockdown of this gene. So it's roughly a third of the velocity of sp0 when you overexpress it. So there does seem to be some compromise. Um and more than this you can sorry this is an 8we experiment so 2 years across um 2 months and we're also able to prevent fibrosis. So we pre-treat cells with an sRNA and we induce fibrosis with tga um uh this this sRNA completely prevents prevents fibrosis when we get it. [laughter] Um >> we just we just intercepted um some external data where some investigators completely um for other reasons looking at SP 101 SRNA in fibrosis showed you you can reverse uh mesh and eroded model. So I've recreated the data otherwise you can trace it back to the author. My company's out of business but but it's it's incredible. So these you know these investigators went into a mouse they reverse fibrosis. Little do they know this is actually a rejuvenative gene. So that's I guess that's the difference between when we're looking at this and say when this investigators are looking at it. So um this this you know this gives us this development path. We were looking for this mouse data. We're actually funding to do the mouse data and then we it's like a gift from the universe, right? Somebody's done it for other reasons and so we're sort of getting a little bit on the back foot. It's like well now what right? We're there. Um so we're going to sort of try sort of mix up what we're doing in the next few months. Um you can also impact this gene target by small molecule. Um so there's a binding partner as a nice pocket and there are molecules that can interrupt the binding of that partner to sp 101 and you rejuvenate slightly less than the sRNA and prevent fibrosis. Unfortunately this molecule is toxic to the second cell type. So as it's not ready not ready for prime time but it does show you small molecules are within the realm of the possible which is exciting right cuz a molecule can get across your body. Uh yeah got got to go fast and there are multiple family members in this triple0 family. Some of some of these family members all of which have very similar protein sequence and many are regenative. One is not regenative. So it's this this pink arrow at the bottom. Um it's it's a very similar protein sequence. It's very different levels of rejuvenation. So we've identified the sequence specific to the rejuvenative family members absent in the non-re rejuvenative family members and we're co-folding every other protein in the genome to that sequence using like an alpha fold type algorithm and we're actually finding a bunch of candidates that we're about to test. I think I'll be shut down. Uh okay just yeah just some feelood stuff at the end. Um next year for us is year of the mouse. So we want to rejuvenate liver want to impact fibrosis although that's happened externally. We want to go into hearing loss. There's lots of evidence that that will be useful to rejuvenation. And we want to impact lifespan but see you know we're outperforming these early assays. What can we do in a lifespan setting? And I just wanted to oh yeah we're going to make these special mice that they're born with the gene inside their body. And the the purpose is if we express this gene across the body is it safe? Because if we developed the molecule and it wasn't safe to get across the body, that would be a tragic way to find out. You know, it's better to say prove prove the safety of this gene immediately. Then there's a reason to develop the molecule and get across the body with a drug. Um so just just some uh notes on the guiding mission. So enrich these gene targets with systemic efficacy and safety, right? So we can get across the whole body. Uh link those systemic compatible drug modality. So we got maximum effect size and then gain maximum traction lifespan. I just yeah I wanted to end on the feel good. So I mean ultimately we want to make this a mundane scenario where it's like the obvious thing to do. These pharmaceuticals exist. Why wouldn't you take them and keep yourself in good shape? You know it's socially irresponsible to do so. Your loved ones would be telling you to do this. What are you doing? Not taking your medicine. Um so this is you know this is on the later half but this is something very exciting and you know one of the reasons we do this. we get up every day and also, you know, just I want that amount of energy and I want to, you know, see these things happen and I want to be able to get, you know, into orbit and you're going to need really good biology to do that. It's a rough ride getting into space and coming back, let alone being old, right? You can actually do some terrible things. So, I think these types of technologies give us the ability to do very new things. We shouldn't forget that and how exciting this is. So, I just wanted to end on that. >> [applause] >> THANK YOU SO MUCH. Wait a minute. Sorry. One quick thing I was going to say is your um your transgenic um expressor um or the don't be put off if you do see something fun or bad dose. So there are lots of things for you over I suppose particularly is it conditional the the transgenic would you be able to switch your body? Yes, it'll be an inducible questioning data. Come on. >> Thank you for that. Um, it's obly really interesting to see stuff getting, you know, down the lineinical maybe at some point. Um I understand the protecting the commercial interests. I'm curious if there is already research out there maybe not looking direct directly at this gene target for rejuvenation purposes but why haven't you filed for some kind of property protection and then you can say what gene target is just to give a bit more scientific validation what you are doing. So do >> yeah I can I can I'll speak loudly. Um so yeah we do we do try to cover our footsteps so we can be um share as much as possible. Um so we do we do have IP on that but there are certain you know sort of meta data around that where someone can there's lots of uh loopholes people can get around things. So it's it's I guess it's in in our interest toocate for the foreseeable future. Um but I can give you some details. So this gene sp0 very conserved almost almost perfectly conserved in mammals also highly conserved all the way to worms. So that's interesting. It flashes in and out well very rarely expressed across the body with the exception of the germ line in early development. So it flashes on and off uh in the germ line in early development. So we don't know what that means but maybe it's maybe maybe it's something to do with this natural rejuvenation event. We can't prove this is causation. it might just be correlation. Um so yeah some interesting features like the conservation and the fat is sort of you know expressed specifically in part of the body which is responsible for resetting age for the next generation. >> Thank you. Thanks. Thanks very much. [music] | ↗ |