A single factor for safer cellular rejuvenation

In a lab in Cambridge, they dug through the Yamanaka factors looking for something that would rejuvenate cells while avoiding pluripotency (the cancer danger). They found SB000. I want some.

Ageing is a key driver of the major diseases afflicting the modern world. Slowing or reversing the ageing process would therefore drive significant and broad benefits to human health. Previously, the Yamanaka factors (OCT4, SOX2, KLF4, with or without c-MYC: OSK(M)) have been shown to rejuvenate cells based on accurate predictors of age known as epigenetic clocks. Unfortunately, OSK(M) induces dangerous pluripotency pathways, making it unsuitable for therapeutic use. To overcome this therapeutic barrier, we screened for novel factors by optimising directly for age reversal rather than for pluripotency. We trained a transcriptomic ageing clock, unhindered by the low throughput of bulk DNA methylation assays, to enable a screen of unprecedented scale and granularity. Our platform identified SB000, the first single gene intervention to rejuvenate cells from multiple germ layers with efficacy rivalling the Yamanaka factors. Cells rejuvenated by SB000 retain their somatic identity, without evidence of pluripotency or loss of function. These results reveal that decoupling pluripotency from cell rejuvenation does not remove the ability to rejuvenate multiple cell types. This discovery paves the way for cell rejuvenation therapeutics that can be broadly applied across age-driven diseases.

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Wow, thanks for sharing. FWIW, I would consider myself a fairly confident expert in this field, and I have both published and peer-reviewed papers about temporary reprogramming before.

On a quick read, I think this will be a really important paper, with some limitations in its current form. They used a training algorithm to look at biological age and identify this gene, but they have validated it with other clocks (GrimAge2, DunedInPace etc). I’m not sure if those are the modern-day gold standard because I don’t keep up with the clock stuff.

Most of the work is in human dermal fibroblasts, which are a very reasonable model (and often used for iPSC generation). They also did some validation with epidermal keratinocytes. Two skin cell types - maybe they’re going to go after some cosmetic or wound healing applications in the future.

If I was a peer reviewer and they’re trying to go for the Nature/Science/Cell/Cell Stem Cell tier of journals, I’m would be asking them for a couple of other cell assays. All they really show here is DNA methylation and aging clocks, which move in a youthful direction without loss of cell identity, but they don’t show any changes in actual function. I would love to see if there are any changes in cell metabolism (which should occur during reprogramming (switch towards glycolysis), and unknown with this molecule). I’d also love to see some sort of functional assays. For example, with the fibroblasts and keratinocytes, they could grown them in a simple transwell assay, and see whether the barrier function is affected by the drug.

I would also love to see other cell types, including cardiomyocytes where temporary reprogramming has a huge promise to restore cardiac function.

Very cool, but of course delivering a gene is still an obstacle for any human therapeutic use, for now.

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Thanks for your analysis and insight. I looked around a little and came across a few things that Shift Bioscience, the company doing the research, had to say.

They did find function:

SB000’s functional effects – improved collagen production and preserved fibroblast behavior – suggest real potential for reversing tissue aging.

Immediate plans:

With these promising results, Shift is moving quickly to validate SB000 further. The next stage involves:

• Testing across an expanded range of disease-relevant human cell types

• Investigating whether rejuvenated cells functionally behave like their younger counterparts

• Launching proof-of-concept in vivo studies, including in mouse models

From a 2022 interview with Daniel Ives, a co-founder of the company, the expectation was that it was almost certainly going to be a therapy with multiple genes, not the single gene they ended up finding. It has been noted that regulatory approval will be easier than it would be with multiple factors.

The interview with Longevity Technology, done for the purpose of raising funds, is sort of long, but if this development has captured your interest as much as it has mine, time will be suspended:

Using a novel machine learning approach, British startup Shift Bioscience is on the verge of validating drug targets for cellular reprogramming. The company is currently in the process of raising £3.5 million to begin the target validation phase for genes that could become the targets of rejuvenation therapies.

Longevity.Technology: Cellular rejuvenation holds great potential but it is also fraught with challenges. With significant money now flowing into the rejuvenation field, Shift Bioscience is a player with a unique position in this hot investment area: the ability to identify safe targets. We caught up with co-founder and CEO Dr Daniel Ives to learn more.

Ives has been working in the field of aging since 2009, and focused on mitochondrial rejuvenation at the University of Cambridge and the Crick Institute. He co-founded Shift in 2017, initially with the aim of developing mitochondrial drugs for age-related diseases, but then a surprise discovery put the company on a different path.

“What we decided to do was to attempt a CRISPR screen for aging, which would allow us to disrupt the function of any gene across 20,000 genes, and then the data would tell us what’s the best point of leverage,” explains Ives. “To do this, we used machine learning to create a single cell aging clock built out of genes, not out of methylation sites. And we were about to go ahead and do the CRISPR screen, when we realised that we had done a lot more than just create a clock.”

While methylation clocks provide very little information, biologically, about what aging is linked to, Shift’s clock was based on genes, which Ives points out are very rich in data.

“Genes have annotation, there’s a lot of information linked to them, so when we looked at our clock, which is made out of genes, there were mitochondrial genes, and there were ribosomal genes, and there was even a gene that was sufficient to accelerate aging on its own,” he says. “And so we realised that our clock was not just providing a readout of aging, it was a window into aging.”

The discovery thrilled the team at Shift because it provided an unprecedented view of aging biology that was also completely unbiased.

“It’s completely open because it includes known biology, but it also includes unknown biology, so you’re not blinkered by what you know,” says Ives. “To the extent you can measure things, you can ask the universe what is linked to aging, and you get a collection of genes in an unbiased way.”

Identifying safe genes

The second key thing that Shift realised was that doing a CRISPR screen, as the team had originally planned, was a constrained approach, because it would only disrupt gene functions one by one.

“There might be a way to change aging with one gene, but there’s a strong possibility there isn’t,” says Ives, citing pluripotency, where stem cells are created from normal cells using four factors, not just one.

“So we’ll use a combinatorial approach, where we throw all these genes we’ve identified into cells, capture the cells that rejuvenate, then figure out what single genes or gene combinations drove those cells.”

But perhaps the most important thing to come out of Shift’s approach is the identification of safe cellular reprogramming targets. While cellular reprogramming has been measured by DNA methylation clocks to be one of the most powerful potential interventions against aging, its key challenge to date has been safety.

“What we decided to do was to attempt a CRISPR screen for aging, which would allow us to disrupt the function of any gene across 20,000 genes, and then the data would tell us what’s the best point of leverage,” explains Ives. “To do this, we used machine learning to create a single cell aging clock built out of genes, not out of methylation sites. And we were about to go ahead and do the CRISPR screen, when we realised that we had done a lot more than just create a clock.”

A window into aging

While methylation clocks provide very little information, biologically, about what aging is linked to, Shift’s clock was based on genes, which Ives points out are very rich in data.

“Genes have annotation, there’s a lot of information linked to them, so when we looked at our clock, which is made out of genes, there were mitochondrial genes, and there were ribosomal genes, and there was even a gene that was sufficient to accelerate aging on its own,” he says. “And so we realised that our clock was not just providing a readout of aging, it was a window into aging.”

The discovery thrilled the team at Shift because it provided an unprecedented view of aging biology that was also completely unbiased.

“It’s completely open because it includes known biology, but it also includes unknown biology, so you’re not blinkered by what you know,” says Ives. “To the extent you can measure things, you can ask the universe what is linked to aging, and you get a collection of genes in an unbiased way.”

Identifying safe genes

The second key thing that Shift realised was that doing a CRISPR screen, as the team had originally planned, was a constrained approach, because it would only disrupt gene functions one by one.

“There might be a way to change aging with one gene, but there’s a strong possibility there isn’t,” says Ives, citing pluripotency, where stem cells are created from normal cells using four factors, not just one. “So we’ll use a combinatorial approach, where we throw all these genes we’ve identified into cells, capture the cells that rejuvenate, then figure out what single genes or gene combinations drove those cells.”

But perhaps the most important thing to come out of Shift’s approach is the identification of safe cellular reprogramming targets. While cellular reprogramming has been measured by DNA methylation clocks to be one of the most powerful potential interventions against aging, its key challenge to date has been safety.

“What we decided to do was to attempt a CRISPR screen for aging, which would allow us to disrupt the function of any gene across 20,000 genes, and then the data would tell us what’s the best point of leverage,” explains Ives. “To do this, we used machine learning to create a single cell aging clock built out of genes, not out of methylation sites. And we were about to go ahead and do the CRISPR screen, when we realised that we had done a lot more than just create a clock.”

“The whole problem around reprogramming has been that it’s a Goldilocks approach – too little and you get nothing, but too much and it’s cancer,” says Ives. “It’s an existential problem for a reprogramming therapy – it only takes one premalignant cell in your body to be tipped into malignancy and that’s the beginning of the cancer.”

“We’ve used our approach to predict the genes driving rejuvenation during reprogramming – they don’t look cancerous and our next step is to throw them into a system to see if we can rejuvenate safely. We can show this definitively – we can sort the cells for rejuvenation and for pluripotency, and then we can pinpoint those genes which not only rejuvenate but are also safe.”

De-risking rejuvenation

To complete this pivotal next step, Shift needs to refuel with new funds. Everything to date has been conducted in silico and the company is eager to test its gene predictions in the lab, firstly to align its machine learning systems with what happens in the dish.

“When we get into the dish, it is going to tell us how to improve our bioinformatics until it is as good as it can be,” says Ives. “And then we’ll start patenting based on the genes it identifies, which will include mRNA therapeutics targeting those genes, as well drug targets on the gene products. And that’s the basis for a fully de-risked rejuvenation therapy.

“It’s the best possible foundation for preclinical and clinical development, because you’ve first asked what’s the best biology and then you start where the data tells you to start. We don’t know exactly what we’re going to get up front, it might be a combination of two or three genes, or it could be up to five, but that will dictate what the therapy is going to look like. It’s almost certainly going to be a therapy targeting multiple genes, which will require an innovative approach, but if this is what the biology tells us, we’ve got to listen.”

Ives expects the new funding round will support Shift through the next couple of years, taking the company through the identification of a spectrum of safe rejuvenation genes, narrowing down to a preferred set of genes, then patenting the therapeutic options around those genes.

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Rejuvenation without pluripotency called the holy grail of longevity research by some. Generally, reviewers are cautiously positive, noting that there’s a long way to go. This is the most negative review I’ve found, mostly related to the paucity of information the paper provides:

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I asked OpenAI’s Deep Research to read the paper and then to guess what the secret gene is, and it guessed KDM2B:

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KDM2B is Bad! No, wait, it’s Good! No, wait, “Obviously, more research is required …”

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Even cartoon characters are getting enthused:

Elsewhere - I can’t find it at the moment - David Sinclair says OSK won’t induce pluripotency. However, the picture in the video showing colonization seems to dispute that claim - not nearly as much of it as OSKM, but still there.

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more

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The CpG methylation level in binding sites for both AP-1 (previously implicated as a driver of age-associated chromatin opening [48]) and PRC2 (binding of which is thought to protect against ageing [49]) increased alongside the global hypermethylation with SB000 when compared to eGFP (Figures S3A, S3B). This suggests that SB000 does not act via differential methylation activity at the binding sites of either complex.

I found the above paragraph and accompanying data very intriguing, but unfortunately they don’t show that it’s anything more than a trend. It would be nice to know if SB000 led to a statistically significant methylation increase across the top AP-1 binding LMRs.

Anyways, the above data especially relates to a 2024 paper in Cell Metabolism: The activity of early-life gene regulatory elements is hijacked in aging through pervasive AP-1-linked chromatin opening. This paper reported that chromatin regions which become more accessible with age are enriched for AP-1 binding motifs, while suggesting that these age-opening regions act to siphon away cell-identity transcription factors from age-closing regions (which are also relatively depleted with respect to AP-1 binding sites).

This 2024 paper also briefly examined DNA methylation dynamics within these regions:

An additional layer of regulation that may work in tandem with AP-1 to drive chromatin opening is DNA methylation, which is lost in age-opening regions in HSCs.23 We confirmed through reanalysis of published datasets that age-opening DARs in aged mouse beta-cells91 and maturation-opening DARs in human T cells92also exhibited significant DNA methylation loss in aging

Another paper (Examining age-dependent DNA methylation patterns and gene expression in the male and female mouse hippocampus) reported:

Motif enrichment analysis revealed the AP-1 complex (including the proteins JUN and cFOS), a major regulator of gene expression, as the most commonly associated transcription factor binding sites within hypomethylated regions in aged mice when compared to young animals in our results (Fig. 2G).

SB000 appears to reduce DNA methylation in AP-1 enriched regions, although possibly in a nonspecific way (“SB000 does not act via differential methylation activity at the binding sites of either complex”), which is the opposite of what aging seems to do. DNA methylation generally inhibits transcription factor binding, so might SB000 act to slow AP-1 colonization of age-opening DARs? Also, what are the implications of reduced DNA methylation at PRC2 binding sites?

The data from Patrick, et al. suggests that this increased accessibility (and reduced DNA methylation?) at high AP-1 regions can be induced not only by overexpression of the AP-1 subunit Fosl2, but also by inhibition of PRC2’s catalytic subunit EZH2. There was a statistically significant overlap in both of the regions made less accessible by AP-1 overexpression and EZH2i, while also a trend towards overlap in the regions made more accessible. Likewise, when they examined H3K27me3-enriched regions (the trimethylated lysine residues that we expect EZH2i to target), the accessibility changes produced by both EZH2i and AP-1 overexpression are correlated:

Screenshot 2025-06-17 at 10.27.45 AM

In essence, AP-1 overexpression and PRC2/EZH2 loss-of-function both seem to promote a similar “aging-like” program of chromatin dynamics.

While there’s no known small molecule activators of EZH2, inhibition of KDM6A/6B would likely have a similar effects (EZH2 deposits H3K27me3 while KDM6A/6B removes them). GSKJ4 is an interesting inhibitor of KDM6A/6B, see below:

Intl Journal of Cancer - 2023 - Dalpatraj - GSK‐J4 An H3K27 histone demethylase inhibitor as a potential anti‐cancer.pdf (1.7 MB)

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I did the deep research with the o3 model and it said FOXM1 was its best guess.

Deep Research FOXM1

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AI fight! Make the first round winners duke it out. I’ll buy a ticket.

However, lurking in the shadows are all the unknown genetic variants : “It’s completely open because it includes known biology, but it also includes unknown biology, so you’re not blinkered by what you know,” says Ives. “To the extent you can measure things, you can ask the universe what is linked to aging, and you get a collection of genes in an unbiased way.”

Roko’s Basilisk just got complicated.

Had to look that one up. Brings to mind the movie line, “The issue’s not whether you’re paranoid … the issue is whether you’re paranoid enough.”