I have two kinds of questions here. The first one is, whether I am understanding it right that you’re working on data from mice? And on fibroblasts that you’ve taken from mice? And if so, why not humans? The reason I’m asking is that I have data that I haven’t published where we took humans and gave them Metformin and placebo or Acarbose and placebo, you know, ITP drugs, and it was a crossover study, and we did the same in animals. So we have transcripts from humans and from animals treated for the same time, equivalent dose of drugs. And to our surprise, the transcripts are not the same, although the upstream regulators are the same, the transcripts are not the same. So I think we have to be careful how we go from animal to human and vice versa. And of course, you know that the clocks are not the same, right. So, I think, from a drug development perspective, you should really base this only on humans, right? Otherwise you might be confused with the experiments.
- Sure. So the data I presented was actually data from human fibroblasts. There was an aging time course and that was human fibroblasts, so human subjects. And the rejuvenation time course was human fibroblasts. So I think Yamanaka basically took them at age 60 and turned them back. But we have done this on mice as well, and it shows similar results. So we did all of the experiments to create our method on the Tabula Muris Senis mouse data, but then we applied it to human cells, and we see really exciting stuff in the human cells.
The second question for you is whether you are putting some positive controls in. Did you also treat some of the fibroblasts with Metformin or Rapamycin or NAD or something that actually has the effect on epigenetics, to get the length field of what you’re doing in relation to general therapeutics?
- (Daniel Ives) Yeah, I think that’s an obvious thing to do that we haven’t done so far. Looking at the gold standard interventions like rapamycin and checking what they do to our clock definitely makes sense. And if it does the expected things, the clocks are meaningful or more meaningful.
- (Karl Pfleger) So the nice thing about this platform with regard to humans versus mice is that they should be able to look at both sets of clocks and actually limit to things that work in both. And of course, we care about them working in humans, but if they go down a clinical path, then working in mice is a good thing, if it’s the same thing that can work in both. But the platform should allow filtering – if there are enough leads – down to things that work in both.
Single cell sequencing is a little biased towards less expressed genes such as transcription factor, which is really important for aging and pathway generation. So how did you solve this problem?
- (Daniel Ives) With respect to the rejuvenation time course, it wasn’t actually single cell data. There were cells that were sorted for a cell surface marker of pluripotency. So it’s actually bulk measurements. And we can use the same method on bulk measurements. So we don’t have this coverage problem, like you said, we would have in single cell data.
- (Brendan Swain, inventor of clock method) I don’t want to reveal too much about the method just because of IP concerns, but the method isn’t just based on the absolute variance of genes, which should be the major contributor to that problem of picking out genes that are the most variable across the dataset, which is kind of how a lot of this kind of analysis is done. We’ve made great efforts to allow genes to contribute equally to the clock, and make sure that we’re not favoring the loudest shouters.
And my second question is whether you are doing a whole methylome analysis for identifying cell biological age, which is coupled with CRISPR? Or are you doing a specific methylation signature?
- (Daniel Ives, mishearing ‘methylome’ as ‘metabolome’). We’ve started on the transcriptome. We were at the mercy of the public datasets to begin with, it’s heavily based on Tabula Muris Senis, and aging time courses in human cells. And we’re just starting to generate our own bespoke datasets to the systems that we’re going to be using to try and validate our genes. And so we will be looking to do beyond transcriptomics when we start doing things ourselves. But in the early days, we were at the mercy of the public datasets, so I don’t think there was anything there at the time.
Is all the data limited to fibroblasts?
- No. So in the Tabula Muris Senis, which is mice, you’ve got a lot of different cell types, certain cell types have richer time courses. So as far as using our clocks is concerned, we’re better off with a richer time course. On the human side, and on the human rejuvenation side specifically, there are reprogramming paradigms from five different cell types. With reprogramming data from endothelial cells and four other cell types, you can train multi-tissue rejuvenation clocks across all of those and see what the rejuvenation biology is. Because obviously it works across lots of tissues, the potential is higher from a translation perspective. So not just fibroblast (rejuvenation), we are shooting a bit higher.
What would actually really help you move this project forward now? If anyone is on the call or even afterwards for those that will watch it on YouTube? What are specific ways in which they can reach out to you, in as actionable a way as possible?
- Beyonds the wish list, which is maybe a little bit farther in the future, immediately we just want to test these genes (putative safe rejuvenation genes) as fast as possible. And we’re doing a lot of these things for the first time. So we’re looking for people, preferably in Cambridge UK, that can help us. We need a lab scientist at the very minimum. And we’re raising a certain amount of capital. It’s not a ridiculous amount, but it’s a lot more than we’ve raised before. So if there’s anybody out there that’s very passionate about clocks, and trying to go beyond Yamanaka factors (for safe cellular rejuvenation), explore the unknown, see what’s there, let us know. It’s just exciting to have an approach where you can reach some of that. If any of that sounds exciting to you, and you want to help move this forward, then please get in touch. The support now would be so much more appreciated than say, in six months time. We really need to get going now. Because they’re (the genes) are just sitting on the list. It would be a tragedy if the lead genes were sitting on that list for any longer than necessary. So we just want to start testing them.
Where do you see this if it is successful? I mean, you already talked a little bit about immediate next steps. Where do you see this going in potentially like 5 to 10 years? Are there any very high hanging fruits that you hope to be able to eventually get to?
- Drug development is a very long and painstaking process, so you’ve got to set expectations, but at the same time, the whole COVID response, the goalposts were moved for that. I’ve got a feeling that if there was something really exciting and safe moving forwards, there would be a certain amount of energy pushing that forwards faster than expected. In 5 to 10 years time, I’d expect something (a safe rejuvenation drug) to be in the late clinical stages. There’s so many steps in between, and I think getting things right is more important than the timeline. But obviously, the faster the better, because if you get these drugs to work, we’d rather have these drugs sooner. I think even before that, it would be really great if we could find a list of safe rejuvenation genes and engineer these into a mouse embryonic stem cell, so that you can just induce these genes in a whole mouse and not worry about getting drugs to every part of the body. J ust induce the mouse and then watch the ageing clocks. Do the clocks go down? And can you keep resetting biological age to infinity, having the first mouse where you can do that. That would be really eye opening, to see what would happen there. So I think generating that mouse embryonic stem cell will be a really exciting thing that isn’t so far in the future. But you’d have to give that a bit of time. There’ll be people that aren’t specialists, or Longevity enthusiasts, and they would just want to see the mouse live longer.
You already talked a little bit about the race at the beginning of the talk, do you have any ideas and potential collaborations going forward even with other folks in that race? Because I think what’s so cool about you and Nathan who’s on this call is that you really try to pull the whole ecosystem together, you’ve been doing quite a lot of work on this. I think it’s really interesting how you position yourself really in this ecosystem like a rising tide?
- Yeah, I think Steve Horvath’s Clock Foundation, just developing these clocks, to basically speed the drug development. That’s great. I think Morgan Levine is doing some really cool stuff enhancing the clocks. That’s an obvious one. And I think it’s very hard for me to analyze what’s out there and try and connect that to what I’m doing. So if you think you can help what we’re doing, obviously I’m going to take the time to listen to you and see if that is a good fit. And so I’m just keeping an open door, and it served me well.
Do you think that there’s any potential risks or downsides that you see, any potential reasons why this might not work that you could falsify in the next few years or so? Like is there anything that keeps you up at night? You’re already testing this right, is there anything else where you see a potential bottleneck that we need to overcome that maybe people in this call could even advise on?
- Yeah, the thing that keeps me up at night is translatability. We could get very excited about what we’re doing in our specific system and then we don’t have a connection to all the other systems. So, Steve Horvath’s mammalian clock is a really great way to try and dispel some of these fears, because it’s connected to so many different contexts of aging. When you move that clock, you’ve really moved something. So that’s one way to do it. But yeah, it’s just making sure we’re not system specific. So if we do find a minimal set of safe rejuvenation genes, we just want to broaden from our first cell type to multiple cell types and make sure that it works in mice. We have to go through mice to get to humans, whether we like it or not. Maybe organoids can also help.. Basically we should test all of the systems. There’s no reason to go narrow and try and save pennies (or cents) when we could just increase the breadth and translatability. So I think translatability is the biggest worry. And then the safety side, can we fully deconvolute from pluripotency. That’s not a foregone conclusion. So we just need to complete the study. There are stil discovery elements to what we’re attempting but there’s a lot of promise from what we’ve done so far. The opportunity is there and we just have to make the most of it.