New Study Could Pave the Way for Better Cancer Vaccines

Date Posted: June 10, 2025

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New Study Could Pave the Way for Better Cancer Vaccines

Scientists have found that only about 1% of presented tumor antigens come from oncogenic mutations. The remaining 99%, previously overlooked, may offer better treatment targets [1].

Going after mutations

Cancer arises from a series of mutations that drive abnormal cellular behaviors, such as runaway proliferation. Cancerous cells also normally present abnormal peptides on their surfaces that the immune system detects and targets. This presentation is carried out by major histocompatibility complex (MHC) class I proteins, which are not to be confused with MHC class II proteins that present external peptides ingested by the cell, such as from bacteria or viruses.

Targeting these mutated tumor-specific antigens (mTSAs) has become a strategy behind many experimental treatments, most notably anti-cancer vaccines, which prime the immune system to go after cells that express a particular mTSA. However, since mutations are often tumor-specific, those vaccines must be tailored to each patient, which makes them finicky and prohibitively expensive. Despite all the effort, mTSA-targeting vaccines often do not produce the expected result.

To create a vaccine, scientists sequence the tumor’s genome, identify tumor-specific mutations, and then use algorithms to predict what an antigen derived from the mutated gene would look like. The vaccine is then built based on that predicted sequence.

Looking for what’s actually there

Novel techniques have made it easier to look for antigens that are actually present on the cell’s surface rather than rely on predictions. In a new study published in Nature Cancer, scientists from the Institute for Research in Immunology and Cancer (IRIC) at the University of Montreal catalogued tumor antigens in 505 melanoma and 90 lung cancer samples by using a state-of-the-art multi-omic approach, and they arrived at striking results.

They found that only about 1% of the tumor antigens came from mutations. The remaining 99% came from non-mutated parts of the genome, often from sequences that are normally silent or minimally active in healthy tissues.

These fell into three groups. First were aberrantly expressed tumor-specific antigens (aeTSAs), peptides from unmutated genomic regions that are normally silent in healthy adult tissues but activated in cancer. Their origins varied and often included “non-canonical regions,” such as gene parts that are usually spliced out of the final RNA used to make the protein (introns), intergenic regions, and non-coding RNAs.

The second group consisted of tumor-associated antigens (TAAs): unmutated proteins that are overproduced in cancer but also found in some healthy tissues. Finally, the third group included lineage-specific antigens (LSAs): proteins that are typical of the tissue the cancer came from, such as melanocyte markers in melanoma.

The researchers found that mutated antigens are rare because many mutations don’t get transcribed into RNA, which means the corresponding proteins don’t get made. If there’s no protein, there’s nothing for the immune system to see. Plus, the few mutations that are transcribed often occur in genomic regions that don’t generate peptides that are well suited for presentation to immune cells.

Meanwhile, many aeTSAs are made into proteins, get presented on the cell surface, and can trigger immune responses. The study showed that immune cells from healthy donors can recognize and kill cancer cells presenting these aeTSAs. This suggests that they could be powerful targets for cancer immunotherapy.

Importantly, these aeTSAs were often shared across patients, unlike mutated antigens, which tend to be unique to each person. Therefore, aeTSAs could be used to develop generalized, off-the-shelf cancer vaccines or T cell therapies.

The upshot of this study is that while mutations often initiate cancer, that doesn’t mean the mutated proteins are abundant or relevant as immune targets once the tumor is established. Other aberrant proteins, not derived from the initiating mutations but essential for maintaining cancerous behavior, might be better targets for immunotherapies due to their relative abundance or widespread presentation.

“This is an intriguing study that explores a novel approach to cancer immunotherapy,” said Dr. Anna Barkovskaya, a researcher at Lifespan Research Institute who was not involved in this study. “Previous developments in the field, most notably immune checkpoint blockade in mutation-heavy melanoma and non-small cell lung cancer, were dramatic but were only successful for a subset of patients and not applicable to cancers where mutational load is smaller. Multiple studies that followed focused on trying to identify new mutated tumor-specific antigens, but by their nature, those are patient-specific, rare, and are expressed at a low level.”

“By contrast,” she explained, “the authors of this study used genome-wide sequencing that isn’t limited only to protein-coding regions, to identify non-mutated tumor antigens that were either aberrantly expressed or specific to the lineage of origin of the cancer cells. They found that such antigens are much more common than the mutant ones, tend to be more abundant, and are highly immunogenic, inducing a potent and specific cytotoxic CD8+ T cell-mediated response.”

More evidence from a different study

A complementary study, published almost simultaneously in Science, reinforces these insights by showing that most tumor-presented antigens in human pancreatic cancer arise not from mutations but from noncanonical sources, such as long non-coding RNAs and untranslated regions (UTR) [2]. As in the IRIC study, the team found that these aberrantly expressed peptides, which are absent from normal tissues, can elicit T cell responses and serve as potent immunotherapy targets.

Just like in the first study, some of the cancer-derived peptides were shared by multiple patients, which means they can be used to create off-the-shelf treatments. Some were highly immunogenic and enabled the creation of genetically modified T cells that “could exert robust killing of patient-derived pancreatic cancer organoids both ex vivo and in vivo.” Pancreatic cancer remains one of the most treatment-resistant cancers, making this research particularly important.

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Literature

[1] Apavaloaei, A., Zhao, Q., Hesnard, L., Cahuzac, M., Durette, C., Larouche, J. D., … & Perreault, C. (2025). Tumor antigens preferentially derive from unmutated genomic sequences in melanoma and non-small cell lung cancer. Nature Cancer, 1-19.

[2] Ely, Z. A., Kulstad, Z. J., Gunaydin, G., Addepalli, S., Verzani, E. K., Casarrubios, M., … & Freed-Pastor, W. A. (2025). Pancreatic cancer–restricted cryptic antigens are targets for T cell recognition. Science, 388(6747), eadk3487.

Date Posted: June 9, 2025

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Boyang Wang on Targeting Underfunded Longevity Projects

In this interview, Boyang Wang of Immortal Dragons discusses the kinds of projects he wants to fund, ways in which the industry can be encouraged to develop, relationships between the East and West in longevity research and development, and what got him involved in longevity.

Hello, and welcome to this Lifespan interview, where today, I have the pleasure of interviewing Boyang Wang, who is the founder of Immortal Dragons, a fund operating in the longevity research space in Singapore. Can you start, Boyang, by describing yourself a bit? How did you get into this field, and what led you into founding Immortal Dragons?

Thanks for having me, Keith. This is Boyang, I’m the founder of Immortal Dragons, a purpose-driven longevity fund. We invest in longevity biotech, life extension projects beyond conventional capital investments; we also do advocacy work like translating and publishing books. We do podcasts in Chinese for the Chinese longevity community. We do sponsorship and grants for organizations and events, all to further the research and advancement of the sector.

What got me into longevity? This is actually a recurring theme; it’s not only that I’ve been thinking about why we must age and die, I never figured out the puzzle of existence or consciousness, so I feel like we need more time to think this through. It’s fundamental to extend lifespan and healthspan so that we have more time to figure out the meaning of life, to do whatever you want, to achieve our goals. Also, there is a theme of survival. I’ve had interesting encounters with the healthcare system. I’ve had interesting medical conditions since I was young, so I’ve always witnessed firsthand the limitations and, of course, the marvels of our modern healthcare system, so it’s very natural for me to work on longevity.

It definitely sounds like you have a lot of reasons for entering this field and a lot of passion. Picking up on that point, Immortal Dragons is described as a purpose-driven fund focused on life extension, prioritizing impact over economic returns. How is this different from other funds?

We say we are a purpose-driven fund, and the key implication is that Immortal Dragons values impact over economic returns. This is a more rational, more concrete concept than it sounds; when we say we do not prioritize economic returns, it is pretty practical. I’m coming from a tech entrepreneur background, so I’m not from a biomedical background. If I wanted to maximize economic return, I should have been investing in technology or things that I’m more familiar with, the computer science-related tech sector.

I’m investing in the field of longevity because I want to see things happening: I want to see progress and breakthroughs in the sector. When we make investments, we are less focused on the potential economic returns. For example, if we wanted to invest in a pharma company that could make the most money for us, we might not do a good job, because this is the game that big pharma companies are playing, and they know their games. Rather, we invest in companies that might be working on cutting-edge, moonshot, high-risk technologies that are probably very meaningful for the sector but might not bring the most economic returns.

How do you measure this? Is there a formal, codified investment thesis, where you quantify impact versus economic returns and weigh those things when you’re looking at an investment? Is it more of a feeling based on your due diligence, or are there specific impact metrics that you look at?

Quantifying impact is not easy, but we do have some working themes that we are focused on, such as replacement. We feel like replacement, not repair, is an interesting direction as an anti-aging strategy. There are recent papers on it that we draw this analogy from. One comparison is electrical engineering, where it’s hard to fix a smartphone; if you smash it, even the best engineers might have a hard time fixing the chips and the screen LED, but what the engineers would do is replace the screen, the motherboard, and so on.

In terms of biology, we see replacement as a very promising direction for intervention, so we look at xenotransplant companies. We look at companies that work on cryopreservation, which is related to transplantation. We look at companies that work on 3D bioprinting for tissues and human organs ex vivo, and we even look at companies that work on whole-body replacement. This is one of the working themes, and we then measure the rarity, the importance of the work, to hopefully partially quantify the impact of the investment.

Are there other factors that determine what you might fund? For example, if there was a therapy that was more repair than replacement, are there other elements of a potential project that would bring it into the sphere of things that you might fund? Is anybody else focusing on rarity? You mentioned evangelism in the past; is the ability for a project to inspire the public something that you might factor into potential impact?

Indeed, if there’s a deal that is highly sought after, then we will probably not be so keen to make an investment, because there will be plenty of capital and resources flowing into the project. Rather, if we see a project that’s unique and important, a puzzzle piece that is not getting the required funding, we’ll be more interested in it. If there’s a project that can hopefully inspire the public or at least inspire a few mission-aligned groups of people, that is also interesting for us.

Is this affected by the different kinds of systems in the body? For example, replacement might be a more challenging strategy to pursue in terms of neuroscience. Do you have neuroscience projects that you’re looking to fund as well, or is that something that’s deprioritized? Are you looking at other modalities involved in the neuroscience side of things, because I imagine it’s a little bit more difficult to replace your brain?

Yes, absolutely. The brain is tied to the very existence of our being, so it’s more tricky. When it comes to the brain and neuroscience, we look at other modalities. We look at companies that are working on nurturing brain tissue and then transplanting that created tissue into your brain and integrating it into your existing systems. Hopefully, that will enhance and rejuvenate your brain tissue and your nervous system rather than replacing it. In this area, we look at other modalities more of a gradual enhancement, but when it comes to other body parts, we are more interested in the replacement strategy.

That intersects with some work that the ARPA-H is doing with Jean Hébert’s project. Do you look at any other programs like ARPA-H for inspiration or guidance to see what other funds or other governmental agencies are looking to fund, and is that something that gives you an indication of what you would like to explore or is that something that you would rather deprioritize, because you feel like they are taking care of that side of things?

We are certainly interested in what public sector or other organizations might be sponsoring, ARPA-H being one. Of course, there’s XPRIZE. There are the Middle East, MENA countries, where sovereign funds are looking to fund such efforts as well. We are based in Singapore, so we also see that there have been some initiatives from the Singaporean government and universities. We have the first longevity research center set up in Singapore by the National University of Singapore headed by Professor Brian Kennedy, which has been around for a few years. These are great initiatives.

We have communications with them, but government agencies often have the mission of advancing public health, so they really look at things that improve lifespan on average and impact a large proportion of the population, such as diabetes, metabolic diseases, and neurodegenerative cardiovascular diseases.

I feel like nimble and independent organizations like ours have the responsibility to work on the cutting edge. Instead of improving the average life expectancy, we want to set an example and inspire the sector by making a few people live to 120 or 150. One example would be Larry Ellison. He’s apparently pretty successful, at least seemingly in his anti-aging and longevity effort, in inspiring high-net-worth individuals by showing his achievements and so putting resources to work on this sector.

You’re saying that if you could succeed in having a few significant outliers, that will serve as a powerful signal to the world to say “Hey, we can actually get gains here”, and that would catalyze more funding.

Yes, absolutely. We believe in the power of role models. After the Wright Brothers, there are so many who succeeded in creating powered aircraft; after Tesla, there are so many companies who successfully built very good electric vehicles. The power of role models is invaluable.

Have you received any kind of challenges on that sort of thesis, by people saying “Hey, you should really be working on doing that sort of blanket minimum median raising as opposed to this”? Or, does everyone that you’ve interacted with understand the points that you’ve just made?

The field of longevity can be controversial at times. There are actually criticisms coming from different perspectives, one being that everything that we’re talking about is pretty far-fetched if not pseudoscience. When you talk about creating organs or organoids that will be usable for humans, or you talk about therapeutic plasma exchange, which is also a replacement strategy, many coming from a more traditional background would totally oppose it. There are other times when it’s criticized for being unrealistic or unhelpful for the general public, who might benefit more from statin dosage for their cardiovascular health or less sugar intake. There’s criticism from all different perspectives, but to work on something that’s controversial will be meaningful. If there’s an aligned interest, if there’s already consensus, then it’s more suitable for bigger organizations than a small fund like us.

Given that you’re approaching this from the perspective of moonshots like this, can you speak more about the thesis of being focused on impact more than economic returns, and how does that inform your team? Does everybody feel the same? What is the structure of the fund. What’s your team size, and how many investments have you made?

We are a 40 million AUM fund. Our structure is a bit special in that we are more of a CVC, a corporate VC structure. We only have one external LP, and the majority of our fund is coming from our previous businesses, so we have total flexibility in terms of making investments. We don’t have a stringent LP mandate; we don’t need to call capital, we have our capital ready.

We have five or six teammates who are working full time on our fund. There’s also departments like finance, legal, and human resources, that we share with our larger group of companies. We’ve been investing as an organization for almost two years by now. We have funded more than 10 investment projects so far, and we deployed a few million US dollars. We plan to continue or accelerate as we see more breakthroughs and progress in the sector.

What are your thoughts on the current funding landscape in general? Instead of simply being an LP for other funds, why did you choose to do this yourself? What are the biggest gaps or unmet needs in the field that you hope Immortal Dragons will address?

We do also invest in other funds as an LP, but the reason why I have to work on it myself is because this mission is very important to me, and I have to work on it full time rather than just sit on the sideline and watch others work on it.

We feel like there’s definitely not enough attention, resources, or talent. Everything in this direction is so fundamental, so important, and yet it’s not getting the kind of attention that it deserves. Partially, we feel that he reason is complicated. There’s a mentality shift required, where people have internalized the idea of aging and death. There is an economic flywheel that’s not there yet.

For the past many decades, investing in anti-aging has been a not-so-fruitful endeavor, but we believe it’s now at an inflection point. There is also a moral implication in that the argument for longevity and anti-aging is not established, especially not for the general public, and thought leaders have been working on this as well. Notably, Nick Bostrom is a philosopher influential in this area, and he has famously written The Fable of the Dragon Tyrant to address many of the moral arguments around anti-aging, longevity, and longer lifespans. We also translated the book The Case Against Death by Patrick Linden into Chinese and published it in the Chinese market. It’s also a pretty compelling and comprehensive discussion on the morality of longevity. So many of these need to be addressed, and investors need to see returns, and we need to make our voice heard to move the needle and turn the tide.

On that subject, there’s obviously a lot of different steps in the pipeline of realizing healthspan-extending technologies. There’s the research itself, there’s government issues and funding, there’s the ecosystem of investment, and there’s public sentiment. Are any of these a critical bottleneck that needs addressing, or is it an all-of-the-above strategy?

It’s not easy to find the one key factor that’s the most important, and that’s why, from Immortal Dragons’ perspective, we try to work on a few of these factors. We look at the economic flywheel. Currently, it’s not very attractive to fund longevity projects or work on them because there’s fewer success stories, for founders, for large investors, and for the general public to invest in. We are looking to help; we’re really looking forward for a wave of longevity and anti-aging companies to reach a turning point where they get publicly listed, they will generate returns for retail investors in the public market, and that will be a powerful motivational incentive for more people to invest in and to turn the tide.

We don’t emphasize economic return as a fund, but as a mechanism, it’s really one of the most powerful: capitalist, free market return on investment is the most important motivational incentive structures that we have discovered to push the sector further. We have seen this kind of hyper growth in the tech sector in the last few decades. If this can happen in longevity, in anti-aging, that will really accelerate its development.

Is there any room in the fund to support or invest in projects that aren’t strictly biotechnology? For example, there’s a movie project to make Fable of the Dragon Tyrant; that went through our Longevity Investor Network by Protostellar Media, for example. There’s also a Dragon Tyrant blockchain game that’s being built by SkillCap that is working with the Lifespan Research Institute. Would you ever consider funding projects like this that are not biotechnology but related to the overall goal of potential economic return and inspiring the public?

These are very interesting projects, and this kind of effort will be a perfect candidate for sponsorship or grants by Immortal Dragons. We are one of the early major sponsors of Vitalist Bay, and we’re happy to see the team pulled off a pop-up city/conference that attracted the best minds in the sector and individuals from all over the world, and some of them might be new to longevity. That would be a better candidate for sponsorship or grants instead of equity investment.

Can you explain a little bit more about what that looks like operationally? Is there like a separate tranche of funding within the fund that’s allocated for grants, or is it like a separate granting mechanism that functions somehow alongside the primary fund?

We are pretty flexible, so we make decisions as they come. There’s no strict division of the fund into a sponsorship tranche and an equity investment tranche. In general, the ticket size for sponsorship will be less than then an investment check. 50,000-ish is the maximum we go to for sponsorship grants so far, but we are flexible, and we will evaluate projects as they come. Interested parties can approach us: our website is ID.life, and contact@ID.life is the email address where proposals can be sent.

Got it, and speaking of your website, I noticed that there’s you have a project focused on visualizing digital twins on the website. Is the aim of this type of work evangelism-related as well or purely scientific in nature?

This is another demonstration of how our fund is slightly different. We do such a collaborative project with researchers and other companies when we feel that there’s a value proposition and when we feel that there’s an area where we can contribute. Our team is pretty strong in computer graphics, in 3D modeling, so we created this digital twin project where the functionality is to visualize organs, different systems that vessels, neurons, muscle, skeletal structures, especially it will highlight any issue that there might be in the body.

The purpose of this system is multifold; for many who are not coming from biomedical backgrounds, they probably have not seen such a model of themselves, so it’s interesting for them to explore and enhance their understanding of their bodies. According to some clinics that we talk to, this is a valuable tool to keep clients compliant with doctors’ prescriptions, because the moment they step out from the clinic, the connection between patients and doctors can become pretty weak. We are still exploring the possible collaborations and use cases for this system. We probably will open source this soon, when it reaches a certain maturity level. Right now, it’s just our research project.

If patients can see what a healthier version of themselves will look like if they comply with the specific therapy, that will induce them to be more compliant?

We want this to serve as a motivational tool for clients, so they can see a healthier version of themselves already in the system, which drives the patients to work towards that goal.

That kind of technology can intersect with the notion of digital biomarkers, technologies that might be able to non-invasively scan your face, your walking gait, your voice. Are you invested or interested in any such projects? You mentioned the NUS earlier, and I believe some of these technologies and approaches might be of interest to the groups working there.

We have seen a few products that are already out in the market that non-invasively detect biomarkers with pretty high precision and accuracy. So far, we have not invested in this direction. We feel like this is probably more of a improvement over the technology we already have. It’s good to have, but it’s not screaming for investment, and it’s less of a moonshot, but we find it to be meaningful. There are other funds out there interested in such projects.

Just an observation, the traditional blood drawing process has been improved a lot. There are currently gadgets that can draw your blood pretty painlessly. There is also continuous glucose monitoring that is pretty much painless. The progress in this direction seems to be pretty good.

In the past, you’ve spoken about connecting Eastern and Western longevity communities. What do you see as the most significant benefits of East-West collaboration, and what practical steps is Immortal Dragons taking to bridge these ecosystems?

There are many areas where collaborations can happen between the East and the West. I can at least think of four possible directions, one being capital. There’s an enormous amount of wealth generated in the East with economic development and progress in the past few decades.

In bioscience, we’ve already seen plenty of progress made by Eastern researchers and scientists. Without naming a comprehensive list, there’s Professor Yamanaka, who received a Nobel Prize for his iPSC research. There is one Chinese-American scientist, Zhang Feng, who is a pioneer in CRISPR and gene editing. In terms of cloning for mammals and primates, Eastern researchers and scientists are also pretty advanced and have been doing interesting work in the past years. In xenotransplants, both China and the US are leaders in this area. These researchers write in English, they publish in Cell and Nature, but there’s still gaps at times.

Clinical trials and research efforts are pretty expensive and sometimes are hard to organize in some developed countries due to strict regulations and probably bureaucracy and red tape, and that is one area where some Asian countries are more flexible.

With a huge population in the East, there comes market size and market potential. These are all areas where the East and West can collaborate. We feel like such collaboration is not as much as we want it to be, especially in the current geopolitical climate with more bridges getting burnt down. For some organizations and individuals, making that connection is even more important than before.

You’ve also noted in the past that Eastern cultures may be more conceptually open to life extension. How do you see such potential differences in cultural attitudes influencing things like regulatory environments, patient adoption, or investment trends in Asia versus the West?

That’s an interesting topic. Of course, there is criticism, there are people arguing against the idea of longevity, both in the West and the East. These concerns are coming from different angles. In the West, there is a strong religious influence such that there’s worry about playing God and “We probably shouldn’t linger too much on this life but rather live the best life and then go to heaven.” I’m not an expert on theology or these theories, but that’s the cultural connotation that I felt.

Whereas in the East, there’s less of a religious concern but a more practical concern that it might only be for the rich and about the problems that can come from longer lifespan, like limited resources. Societal classes might freeze once you give longer lifespans and healthspans to those who already have resources. There are different issues to be addressed, but I feel like Eastern cultures are more receptive to the idea of longevity. There is a tradition in Taoism, from emperors in history that have pursued longer lives, of course failed attempts, but such an idea has been there all the time. I would say that they’re at least more open to the idea that it’s not unfathomable to think of a future of our civilization where people can live and work for up to a few hundred years and that we’ll be able to achieve great things with our longer lifespans, like traveling to other planets.

I’m assuming that you haven’t imbibed mercury like certain Chinese emperors of legend, but you have personally undergone procedures such as follistatin gene therapy and tissue banking. Would you say that these experiences relate in any way to your investment thesis in terms of risk tolerance, for example?

These are personal attempts, not exactly tied to the fund, but this does reflect on some ideas of risk profile, things that we feel are promising and the actions we think need to be taken. Prototype gene therapy, for example, is experimental. To say that a gene therapy is traditional is a bit weird, because this is a new field, but gene therapies are generally used for very serious medical conditions and are carried by a virus factor, a lentivirus or AAV, and this is often irreversible. The kind of gene therapy that I received is more for general health or anti-aging purposes instead of treating an immediate condition. It is carried by a nanolipid, or in my case, a PEI polymer, which is not as transmittable: it will not go to all my cells and will not be inherited. It’s a one-off shot that will gradually die out.

Many experts in the field are pretty against such a gene therapy, criticizing its efficacy, but they also agree that the possibility for an adverse event is also low because of its low dosage and low efficacy. From my perspective, I feel like this is definitely an early mover in creating gene therapy that’s more transient and more for a larger audience. I want to support the cause. I want to make the pioneers of longevity biotech make money, so that with their role model, there will be more companies that work on this. If you feel like this gene therapy is not efficacious or you feel like this technology isn’t good enough, why not build a company and develop a better therapy? After all, they’re charging a high price, but they also already see some traction.

There are people such as Brian Johnson, who publicly stated that he received a gene therapy, so there’s definitely a market for it. Why not iterate and produce a better product? We want to see such an economic flywheel to attract more resources and talent, so my follistatin gene therapy is also a signal. I don’t believe it had much of a noticeable effect on me, but fortunately, there’s also no side effect or adverse event.

You’ve expressed both enthusiasm and caution about AI’s role in longevity. What specific intersections between those two areas are you most excited about, and what do you think are the greatest risks?

AI is a big trend and is influencing everything that we do; there are a few interesting directions, and there are companies already exploring those. There’s AI drug discovery for smaller molecules as well as biologics. There’s a idea of an AI doctor that can commoditize diagnosis and medical advice to an unprecedented level. There are also worries about hallucination and accountability that an AI doctor really cannot provide at the moment. There are ideas about a clinical intelligence system where AI could really assist a doctor to make a diagnosis and medical decisions, and we can imagine how AI might be more comprehensively knowledgeable than our imperfect but marvelous biological brain, so they can work hand in hand.

These are all very interesting directions, and we feel like funds both from the tech sector and from the pharma or biotech sector are interested in such projects. I would say there’s no better time to start a company, to work on longevity. You have AI at your disposal, you have biotech and longevity research at an inflection point, and more capital, talents, attention, and resources will be drawn into the field.

On your LinkedIn, I noticed that you are a gamer and a dev, and your background is in computer science and being a tech entrepreneur. How do you think that background in other fields has shaped your approach to investing in longevity? Would you say this is a challenge, an advantage, or both?

I’ve been a hardcore gamer growing up, and I do feel that such experiences shaped my work and my perspective in many things. When I was very young, I got my first Game Boy, and then I started to play games like Pokemon. In the first few generations of Pokemon, there are glitches that you can exploit to catch a very rare Pokemon and so on. At first, I didn’t believe in such wild rumors, like you first need to smash your game cassette a few times and blow on it, then you can catch Mew or Mewtwo.

These glitches are real, because at that time, developers had limited RAM space to cram in the data. You can make the game behave unexpectedly to catch the Pokemon you want or duplicate important items in game, and that was a big shock to the young version of myself. I didn’t believe it could be real, but understanding that it is real gave me a sense of believing that we can achieve things.

The world that we live in, a simulation or not, is just another very realistic, very complicated game. It is not without glitches; it all works by code or by some law that we shall discover and conquer in order to make great things happen. We can make advanced science happen that is indistinguishable from magic. That probably gave me the idea that both the game world and the real world are malleable places.

What drives you personally for this mission? You mentioned earlier the various ways in which you’re passionate for this, but is there anything specific that you attribute this passion to? What’s your ‘why’?

Other things are limited: if you have a goal in life, you achieve the goal, and then the prince and the princess live happily ever after. However, at the end of the day, life extension is an infinite game that we might not win immediately. There’s a possibility that we do not win the game in this generation, but we will pass on this torch, and you either win the game and stay in the game or die trying. This gives me motivation to work on this every day. I just want to see how much we can push the boundary. This makes the work that we are working on pretty unique.

Great. Thank you for sharing, Boyang, and thanks for joining us in this Lifespan interview.

Thank you. Thank you so much.

Yes I will donate❤️

Date Posted: June 9, 2025

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Researchers Find Age-Modulatory Perturbations at Scale

Scientists have developed a new open source transcriptomic aging clock and published their work as a pre-print [1]. The newly identified rejuvenating drugs and gene perturbations could be applied in regenerative medicine and longevity therapies, and the aging perturbations could find use for anti-cancer therapies.

Age-shift learning—one model for every platform

Pasta (Predicting age-shift from transcriptomic analyses) was trained on 17,212 healthy profiles from 21 bulk-RNA-seq or microarray studies. A ridge-regularized classifier learned from rank-difference vectors of same-tissue sample pairs ≥40 years apart, capturing the ordering of age-responsive genes rather than their absolute counts. In leave-one-dataset-out (LODO) tests this 40-year age-shift model outperformed the regression baseline and surpassed the previous multi-tissue benchmark, MultiTIMER [2], in 6 / 8 LODO datasets and 5 / 6 independent datasets.

When single-cell data were aggregated into pseudobulks, Pasta retained the highest Pearson correlations, illustrating true cross-platform portability. Because ranks are platform-agnostic, the same coefficients apply, without re-alignment or batch-correction, to raw or normalized bulk, scRNA-seq and L1000 count matrices.

p53-anchored biology linked to senescence, stemness and cancer

Gene-set enrichment placed p53-mediated DNA-damage response at the core of the model: positive weights were dominated by CDKN2A/p16, ZMAT3 and other p53 targets, while miR-29 targets with anti-p53 activity carried the strongest negative weights. Functionally, Pasta separated senescent from proliferative or quiescent cells in 24 / 30 RNA-seq datasets and tracked a 450-day fibroblast passage toward replicative arrest almost linearly (PCC ≈ 0.90). At the opposite extreme it assigned exceptionally “young” scores to embryonic stem cells and to fibroblasts during OSKM reprogramming, while scores rose during directed hepatocyte differentiation, capturing both directions of the stemness-senescence continuum.

Applied to TCGA cancer patient samples, Pasta’s age scores correlated more strongly than chronological age with histological tumor grade and stratified overall survival in adrenal, sarcoma, thymoma and other cancers, underscoring clinical relevance.

Chemical and genetic modulators of cellular age

Screening ~3 million CMAP L1000 profiles [3], the authors flagged 259 Aging and 59 Rejuvenating compounds. Pro-aging hits were highly enriched in FDA-approved chemotherapeutics (e.g., mitoxantrone, gemcitabine, doxorubicin), whereas rejuvenating compounds contained HDAC, MEK and GSK-3 inhibitors, compound classes often used in chemical reprogramming cocktails.

Two predictions were taken to the bench: the antifolate pralatrexate (4th Aging hit) triggered SA-β-gal staining, p21 induction and irreversible arrest in A375 melanoma cells, while the natural product piperlongumine (20th Rejuvenating hit) up-regulated OCT4, SOX2 and NANOG in PC3 prostate cells, confirming a stemness-promoting, age-reversing profile. Extending the same pipeline to CRISPR, shRNA and over-expression constructs uncovered 841 Aging and 54 Rejuvenating gene perturbations. Aging drivers included CCNA2 knockout and KRAS/BRAF over-expression, mirroring cell-cycle arrest and oncogene-induced senescence; while youthful scores included MYC over-expression and TP53 loss, echoing known reprogramming and tumour-suppressor pathways.

Molecular traits that prime cells to respond to aging or rejuvenating cues

To pinpoint intrinsic features that dictate how a cell responds to age-regulatory cues, the authors computed aging- and rejuvenation-propensity scores, which corresponds to the average response of a given cell line to all identified age-modulatory chemical and genetic perturbations. They then correlated these scores to omics measurements for 19 cell lines in DepMap. Mutation analysis singled out TP53: lines bearing two inactive alleles almost never aged, those with one allele aged moderately, and wild-type lines aged readily (PCC = 0.88). Aging-prone lines were wired for oxidative stress: their proteomes were enriched for mitochondrial-translation and respiratory-chain factors, their transcriptomes echoed the same signature, and their genomes often carried extra copies of TRAF6-IRF7 and IFNA loci—configurations that amplify ROS and interferon-driven SASP signalling. Rejuvenation-prone lines, by contrast, over-expressed spliceosome, histone-acetyltransferase and other chromatin-remodelling proteins and frequently lost PRC2 and HDAC copies, genetic changes known to lower epigenetic barriers to induced pluripotency. These results may help design more personalized and effective rejuvenation and anti-cancer therapies.

Yes I will donate❤️

Literature

[1] Salignon, J. et al. Pasta, an age-shift transcriptomic clock, maps the chemical and genetic determinants of aging and rejuvenation. 2025.06.04.657785 Preprint at https://doi.org/10.1101/2025.06.04.657785 (2025).

[2] Jung, S., Arcos Hodar, J. & del Sol, A. Measuring biological age using a functionally interpretable multi-tissue RNA clock. Aging Cell 22, e13799 (2023).

[2] Subramanian, A. et al. A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. Cell 171, 1437-1452.e17 (2017).

Date Posted: June 6, 2025

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Younger Cohorts Show Less Dementia at the Same Age

While the overall prevalence of dementia might be rising due to population aging, a study has found that today’s older people seem to be less prone to dementia than in the past [1].

Are we having more dementia or less?

While the robust rise in average life expectancy seen in the previous century has largely stopped, and some scientists claim that we are about to reach the limits of longevity possible with today’s therapies, research continuously show that people do live healthier for longer. It is not black and white, with some worrying signs such as the obesity epidemic and rising cancer prevalence among younger people, but, overall, at least in terms of intrinsic capacity and cognition, 70 might indeed be the new 60.

A new large-scale study from the University of Queensland, Australia has followed several cohorts and compared the prevalence of dementia among people of the same age born in different times. That is, it asks such questions as whether people born in 1900 are more likely to have had dementia in 1980 than people born in 1940 had in 2020.

The researchers analyzed data from 62,437 people, including 21,069 from the U.S., 32,490 from Europe, and 8,878 from England. The study classified participants by both birth year and age at the time of assessment.

Birth year was divided into eight cohorts, each covering approximately five years. These ranged from those born between 1890 and 1913 in the earliest cohort to those born between 1944 and 1948 in the latest. Participants’ ages were also grouped into six categories: 71-75, 76-80, 81-85, 86-90, 91-95, and 96 years and above.

A win for those born later

A population’s prevalence of dementia depends on numerous factors, including major events such as war and famine. While specific results were not always clear-cut and sometimes hard to interpret, the overall trend, according to the authors, was clear: the later cohorts saw less dementia at the same age than the earlier ones.

“We often see statistics that show dementia prevalence rates are increasing; our study doesn’t refute that,” said Dr. Sabrina Lenzen from UQ’s Center for the Business and Economics of Health. “As more people live longer, the total numbers of people diagnosed with dementia will grow. What we found was a statistically significant decline in people from more recent birth cohorts having dementia.”

For instance, among respondents aged 81 to 85, dementia rates differed notably by birth cohort and region. In the United States, 25.1% of those born between 1890 and 1913 were diagnosed with dementia, compared to just 15.5% among those born from 1939 to 1943. A similar trend was observed in Europe: 30.2% of individuals born between 1934 and 1938 developed dementia, while the rate dropped to 15.2% for the 1939-1943 birth cohort. The results for England were murkier, possibly due to a much smaller sample size.

Driven by women

According to Lenzen, this trend can likely be attributed to a wide variety of environmental factors. “There has been a lot of improvement in education, particularly for women, if, for example, we compare to the baby boomer generation,” she said. “We’ve seen improvements in cardiovascular health, better control of blood pressure and cholesterol, all risk factors for dementia.”

The trend was indeed mostly driven by improvements in female populations. “The decreasing trends among women in all 3 regions have been significantly higher than that of men,” the paper says. These results suggest that the decreasing trend in prevalence among women plays an important role in explaining the decrease of age-specific dementia incidence rates.”

This lends some support to the idea that rising education levels for women are responsible. However, since these levels are quickly catching up to those of men, this particular driver of change might soon peter out.

Some other factors that might be in play include steadily decreasing smoking rates, less environmental pollution, and more active lifestyles. Changes in diet are probably a double-edged sword: while many people today eat healthier, many others consume increasingly more ultra-processed foods.

One of this study’s strengths is that, unlike some previous ones, it uses comparable data from three different regions, thus mitigating the impact of region-specific factors such as wars and economic crises. However, more rigorous studies are needed to understand what factors are behind this data.

Dr. Lenzen noted that while the results provided some hope, there was a need for continued investment in public health campaigns. “Some of the risk factors have been improving, but we have been seeing a shift in terms of high obesity rates and things like air pollution,” she said. “We know those are also related to dementia, so it’s not certain these trends will continue.”

Yes I will donate❤️

Literature

[1] Dou, X., Lenzen, S., Connelly, L. B., & Lin, R. (2025). Generational Differences in Age-Specific Dementia Prevalence Rates. JAMA Network Open, 8(6), e2513384-e2513384.

Date Posted: June 6, 2025

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Springtime for the Longevity Industry

If you are in the Northern Hemisphere, then spring is well underway and the weather is warming up. This is the season of renewal and growth. With that in mind, let’s take a look at what the Lifespan and LRI team has been up to.

Longevity Investor Network 2024 End of Year Update

The Longevity Investor Network (LIN) is an initiative launched many years ago by LEAF, the precursor organization of the LRI. The LIN is run by Javier Noris and is a platform that connects investors with promising rejuvenation biotech startups.

The LIN has been working hard these past few years to help promising new longevity biotech companies showcase their work in front of investors. This has led to a number of those companies getting the funding they need to move their work towards the clinic.

We are living through a remarkable turning point in biomedical history. The longevity biotechnology industry, once considered speculative, is now entering a phase of real-world traction. Investment is accelerating, driven by a new class of sophisticated funds and visionary investors who recognize both the economic potential and humanitarian promise of targeting the root causes of aging.

We’re seeing a wave of therapies in clinical trials, from senolytics to cellular reprogramming, inch closer to public availability. The pipeline is no longer theoretical—it’s operational. What was once science fiction is quickly becoming science fact, and the commercialization landscape is opening doors not just for patient impact, but for sustainable, scalable business models. It’s an incredibly exciting time to be part of this movement.

As the leader of the Longevity Investor Network, I’m thrilled to be doing my part to support and accelerate this progress. If you’re passionate about investing in early-stage startups shaping the future of healthspan and lifespan, I warmly invite you to reach out and join our growing investment community.

If you would like to learn more about the companies that the LIN has supported, check out the Longevity Investor Network 2024 End of Year report.

LRI will be at the Longevity Summit Dublin

July 2-4 sees the Longevity Summit Dublin at Trinity College in Dublin. This is a large conference and one of the more important events in the longevity calendar. With that in mind, our parent organization, Lifespan Research Institute (LRI), will be speaking at the conference.

There is a significant focus on decentralised science (DeSci) at the Summit this year. Lifespan.io was one of the first organizations in the longevity field to use DeSci to fund research, so, naturally, this was interesting to us.

Keith Comito, LRI President, and Dr. Emily Lillian Fishman, Director of Research and Education, will be presenting on behalf of LRI. The Lifespan.io team will also be on site to bring you the latest longevity news from the event.

Be sure to join our talk to learn about the exciting research we are doing and what we have planned for the future.

Cutting through the information storm

Remember how the internet used to be? There was a flourishing blog and independent media scene. It was possible to find good content about the things you were interested in. Articles were written by people for people and had something the AI content that is served up today doesn’t have: the human touch.

Increasingly, the internet is being flooded with low-effort and low-factuality AI slop. The push for convenience and speed has been exploited by big tech companies and their use of AI. Unfortunately this has led to an information storm, where people are bombarded with so much information it can be hard to find useful content.

In a field as complex as ours, you cannot waste your valuable time reading AI-generated slop that could be misleading or wholly inaccurate. That’s where we can help you.

Lifespan.io news is a small non-profit team of journalists covering this rapidly growing field. We work hard to bring you the latest research news, interviews with leading scientists, and longevity topics. This lets you cut through the storm and stay informed.

While AI isn’t going away anytime soon, and it has a place in content creation, we believe that it must not be used as a shortcut. You can be confident that our articles are well-researched with a focus on accuracy.

One of the things that makes Lifespan.io stand out is the human touch. If you value that and you want to help us to keep creating quality content for you, we would like to ask you to support us in one or more ways:

Stay informed: Keep up to speed about what is happening in the exciting world of rejuvenation research by joining our monthly newsletter.
Bookmark our website and put it on your regular places to visit.
Follow us: We are on Facebook, Instagram, Linkedin, Bluesky, and X.
Donate: No matter how big or small, every little bit helps us to keep creating content for you. Help us by making a donation today.
Be a Hero: The most important way you can support our work is by becoming one of our monthly patrons: the Lifespan Heroes.

With your support, independent journalism can continue to thrive, and we can keep bringing you the best in independent journalism covering aging, longevity, and rejuvenation.

Date Posted: June 5, 2025

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New Insights Into How Neural Stem Cells Age

Researchers publishing in Aging Cell have used single-cell transcriptomics to discover new insights into how neural stem cells (NSCs) change with aging.

Adults do generate neurons

The adult brain does generate new neurons [1], particularly in the hippocampus, the part of the brain responsible for memory formation [2]. Neurogenesis is limited to very specific niches, however, and does not occur across the entire brain [3]. This is accomplished by NSCs, cells that can differentiate into neural progenitors (NPs), which can themselves differentiate into both neurons and astrocytes and have less ability to proliferate [4]. Astrocytes are helper cells that support neurons’ connections and metabolism [5].

NSCs are naturally heterogenous, coming from multiple different cell lineages even within a specific niche [6]. It has become clear that these lineage differences result in differences in function [7]. However, the composition and function of the various types of NSCs, as well as how they change over time, has not been fully elucidated.

By analyzing single-cell transcriptomics derived from multiple studies, these researchers aimed to help change that.

Normally quiescent and hard to identify

NSCs spend most of their time in a quiescent state [8], ready to be activated to replace losses; these researchers suggest that this is likely because they are so long-lived and need to protect themselves against the genetic damage associated with constant replication. However, their ongoing sleep requires energy, and natural processes often find them difficult to awaken [9]. This quiescence also makes them particularly difficult to analyze in many contexts, because instead of being identifiable by proliferation markers, they are normally noted by the absence of such markers instead.

Other markers are shared between cell types. For example, the transcription factor Sox2 (one of the four OSKM reprogramming factors) is expressed in NSCs but is also expressed in astrocytes. Similarly, the astrocyte marker GFAP has also been found in NSCs.

Other methods use morphology rather than biochemistry to identify types. Radial glia-like (RGL) cells have extensions and are slower to cycle than non-radial glia-like (NR) cells. Previous efforts to diffferentiate these types with a biomarker have been unsuccessful. RGL cells can be further divided into alpha and beta types; in younger animals, approximately three-quarters of RGL cells become the alpha type, which can differentiate into neurons and astrocytes, and the remaining quarter immediately become astrocytes. In older animals, however, the beta type predominates [10].

The researchers note that even with the fluorescent reporter proteins used in animal models, the wide variety of possible cell subtypes makes such tools exceptionally difficult to use for precise identification. Even previous attempts at transcriptomics looking for a molecular signature may have conflated astrocytes with RGLs [11].

Finding consistent signals

These researchers base their work on existing RNA sequencing datasets. They sought commonalities between seven different datasets; although the various research groups that created these datasets likely used the same sorts of tissue dissociation, they may have preprocessed their data or sequenced these cells in different ways. There were also differences between some of the animals used, with some studies using wild-type Black 6 mice and others using fluorescent reporters, and the brain regions analyzed were also different.

The team’s first analysis allowed them to readily group cells as being NSCs, NPs, and neuroblasts that form neurons. However, that same analysis also grouped together various other disparately named types of cells; the researchers suggest that this is a nomenclature issue and that the cells are, in fact, similar. One study’s NSCs was more similar to another study’s intermediate stage, while the former study’s cells labeled as astrocytes were determined to be similar to the latter study’s NSCs.

The researchers identified the expression of two genes common between all seven studies that represent NSCs, and another ten gene expressions that represent NPs. Some other genes were judged likely to specifically represent quiescent NSCs. Other genes represent activation, and the researchers expressed concern that some genes previously used to mark NPs were simply representing activated NSCs.

Their analysis linked NSCs to another gene, Ecrg4, whose deficiency was found to promote proliferation and improve cognition in mice [12]. Another linked gene, Tnc, promotes neurogenesis [13].

The link to aging

The exhaustion of NSCs is directly linked to the progressive loss of neurogenesis, and thus memory, with aging [14]. An examination of two studies found that the aging of NSCs begins rapidly, at only 4.5 months old in some mouse cells. This includes both an increase in inflammation along with epigenetic changes.

While senescent cells are highly heterogenous, NSCs become senescent just as many other types do, with increases in p16, p21, and p53 along with the well-known marker SA-β-gal. 83 genes related to the senescence-related SASP phenotype were analyzed, and the researchers found evidence that quiescent NSCs may become senescent or transform into astrocytes with aging. Just like with other cells, the proliferation of the SASP affects the neural stem cell niche [15]. Specifically, senescent NSCs express IL-33 [16] and IL-15 [17], factors that lead to neuroinflammation but may also lead to proliferation; however, further research is needed in this area.

The aged NSC niche was also characterized by a loss of communication. Chemical signals that are being sent in younger brains are not being sent in older ones. These signals were associated with crucial abilities, including the organization of synapses [18].

The researchers acknowledge that they have not fully elucidated all of the various subtypes of NSCs and how they differentiate. However, they may have uncovered useful targets in promoting NSC proliferation and limiting the effects of cellular senescence. They call for a more comprehensive analysis of cell types within the aging brain and the use of more advanced computing tools to gain a better handle on the signals sent by NSCs andhow and why they turn into other cells.

Yes I will donate❤️

Literature

[1] Taupin, P., & Gage, F. H. (2002). Adult neurogenesis and neural stem cells of the central nervous system in mammals. Journal of neuroscience research, 69(6), 745-749.

[2] Surget, A., & Belzung, C. (2022). Adult hippocampal neurogenesis shapes adaptation and improves stress response: a mechanistic and integrative perspective. Molecular psychiatry, 27(1), 403-421.

[3] Llorente, V., Velarde, P., Desco, M., & Gómez-Gaviro, M. V. (2022). Current understanding of the neural stem cell niches. Cells, 11(19), 3002.

[4] Yoo, S. J., Ryu, S., Kim, S., Han, H. S., & Moon, C. (2017). Reference module in neuroscience and biobehavioral psychology.

[5] Schneider, J., Weigel, J., Wittmann, M. T., Svehla, P., Ehrt, S., Zheng, F., … & Beckervordersandforth, R. (2022). Astrogenesis in the murine dentate gyrus is a life‐long and dynamic process. The EMBO journal, 41(11), e110409.

[6] DeCarolis, N. A., Mechanic, M., Petrik, D., Carlton, A., Ables, J. L., Malhotra, S., … & Eisch, A. J. (2013). In vivo contribution of nestin‐and GLAST‐lineage cells to adult hippocampal neurogenesis. Hippocampus, 23(8), 708-719.

[7] Bottes, S., Jaeger, B. N., Pilz, G. A., Jörg, D. J., Cole, J. D., Kruse, M., … & Jessberger, S. (2021). Long-term self-renewing stem cells in the adult mouse hippocampus identified by intravital imaging. Nature neuroscience, 24(2), 225-233.

[8] Urbán, N., Blomfield, I. M., & Guillemot, F. (2019). Quiescence of adult mammalian neural stem cells: a highly regulated rest. Neuron, 104(5), 834-848.

[9] Urbán, N., & Cheung, T. H. (2021). Stem cell quiescence: the challenging path to activation. Development, 148(3), dev165084.

[10] Gebara, E., Bonaguidi, M. A., Beckervordersandforth, R., Sultan, S., Udry, F., Gijs, P. J., … & Toni, N. (2016). Heterogeneity of radial glia-like cells in the adult hippocampus. Stem cells, 34(4), 997-1010.

[11] Tosoni, G., Ayyildiz, D., Bryois, J., Macnair, W., Fitzsimons, C. P., Lucassen, P. J., & Salta, E. (2023). Mapping human adult hippocampal neurogenesis with single-cell transcriptomics: Reconciling controversy or fueling the debate?. Neuron, 111(11), 1714-1731.

[12] Nakatani, Y., Kiyonari, H., & Kondo, T. (2019). Ecrg4 deficiency extends the replicative capacity of neural stem cells in a Foxg1-dependent manner. Development, 146(4), dev168120.

[13] Tucić, M., Stamenković, V., & Andjus, P. (2021). The extracellular matrix glycoprotein tenascin C and adult neurogenesis. Frontiers in Cell and Developmental Biology, 9, 674199.

[14] Encinas, J. M., Michurina, T. V., Peunova, N., Park, J. H., Tordo, J., Peterson, D. A., … & Enikolopov, G. (2011). Division-coupled astrocytic differentiation and age-related depletion of neural stem cells in the adult hippocampus. Cell stem cell, 8(5), 566-579.

[15] Kalamakis, G., Brüne, D., Ravichandran, S., Bolz, J., Fan, W., Ziebell, F., … & Martin-Villalba, A. (2019). Quiescence modulates stem cell maintenance and regenerative capacity in the aging brain. Cell, 176(6), 1407-1419.

[16] Gasperini, C., Tuntevski, K., Beatini, S., Pelizzoli, R., Lo Van, A., Mangoni, D., … & De Pietri Tonelli, D. (2023). Piwil2 (Mili) sustains neurogenesis and prevents cellular senescence in the postnatal hippocampus. EMBO reports, 24(2), e53801.

[17] Gasperini, C., Tuntevski, K., Beatini, S., Pelizzoli, R., Lo Van, A., Mangoni, D., … & De Pietri Tonelli, D. (2023). Piwil2 (Mili) sustains neurogenesis and prevents cellular senescence in the postnatal hippocampus. EMBO reports, 24(2), e53801.

[18] Südhof, T. C. (2017). Synaptic neurexin complexes: a molecular code for the logic of neural circuits. Cell, 171(4), 745-769.

Date Posted: June 5, 2025

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Rejuve.AI: Just Another App or a Longevity Research Network?

On its website, Rejuve.AI, a company co-founded by its dynamic CEO, Jasmine Smith, and a renowned AI researcher, Ben Goertzel, promises a lot of things: to “democratize longevity, globally,” to enable you to “take control of your data, and harness its earning potential,” and to “unite against aging.” We have been following the company for a while, and now that its app has been made available, we thought it was a good moment to sit with Jasmine and Ben for a talk and try to understand what’s behind these bold claims. Spoiler alert: Ben thinks that we’ll probably defeat aging quite soon.

So, Rejuve.AI just launched its app. However, it’s touted as something bigger than just a health app, as a longevity research network. Please explain that to me.

Ben: We want to help people in the immediate term by giving them tools to track their own lives and health better, but there’s a limit to what you can do that way. We’re interested in going even further. We want to encourage people to opt in to contribute the data from the app to a decentralized research commons. With luck, we can use our AI tools to discover new things about how to prolong healthy life and then roll back those discoveries to our first experimental test subjects, the app users, even before they’re rolled out to the public at large.

I think it’s a bit of a chicken-and-egg situation with human data in longevity research and biology in general. Data is the key element. You want to entice people to give you their health data and then use it. How?

Jasmine: The data is being used firstly to help the user improve their own health, but then to contribute to a wider body of knowledge, particularly internationally. We’re building a dataset that’s aiming to be better than NHANES, UK Biobank, and other regionally focused ones because it’s international and hopefully including more women and different minority groups.

We’re also tracking people’s personal self-experimentation journeys. Maybe somebody has something they swear by that really works for them: a certain diet, a supplement stack. Instead of being dismissive and saying, “That’s just an n=1” or “You can’t prove that,” we can actually see what types of people it works for and what the underlying biological mechanisms are. We can aggregate and expand those insights to help people save time and money on things that aren’t going to work.

Users can earn rewards in that same ecosystem, being incentivized to provide data accurately and on a regular basis. They can also be connected to trusted providers of services and consultations with clinicians to really implement these further and take it to the next level.

Ben: We don’t know how much data we actually need to fuel which AI discoveries about longevity. One focus of my own AI R&D has been to find approaches that can do more with less data, which is very critical in the biology domain. The successes we’ve seen with transformer neural nets and LLMs have been predicated on having massive amounts of data. That’s great when you have many variations of essentially the same English sentence, so an LLM can get a sense of its meaning from a large corpus.

With biology data, we’re in the opposite situation. There’s tremendous complexity within each human body and among human bodies, and the samples that we have, even if the world opened up all its medical data for open research, which is not the case, the samples would still be incredibly small compared to the depth and variety of the systems involved.

A lot of my work with the Rejuve.AI team has been on how to go beyond standard neural net methods. We’re looking at ensembles of neural nets helping each other learn, at neural-symbolic or evolutionary methods, even quantum computing approaches. How do you use more advanced techniques to make interesting imaginative leaps beyond the relatively small amounts of data to make the right generalizations about human longevity?

We need to be working from both directions. We need to make modern AI’s data requirements fewer, given the realities of gathering data from human bodies and their diversity. But we also need to increase the breadth and depth of available data and try to get the two to meet in the middle.

Like you said, even the types of data in biology are very diverse, so what are we after?

The nature of the data is as important as the amount. When you look at the research Big Pharma does, it’s more for economic reasons than anything else. They want to pick one disease, ideally one target, and pile resources on that one thing. This has sometimes yielded amazing results, such as statins, which are great for heart disease.

On the other hand, we all know aging is a holistic phenomenon. It’s about many different body systems, many different levels of the body working together. You do need drill-down data on very specific disease pathways, but you also need holistic data about what human bodies are doing during their lives, their overall health condition, diet, exercise, mood, and state of mind.

The mainstream biomedical world hasn’t been great at holistic approaches. Part of what we’re doing with the app is aiming to accumulate, over several years, the world’s largest corpus of holistic data about human bodies across their whole lifespan, both very healthy ones and less healthy ones.

We want both genomic data and clinical medical data, and lifestyle and psychological data; health knows no boundaries. By getting all this data conglomerated together and feeding it into machine learning systems, machine reasoning systems, proto-AGI systems, and then AGI systems, we hope that AI can make creative leaps beyond this data and generate interesting new hypotheses for prolonging human life.

The app we’ve launched now is a milestone because it’s the result of a lot of research. On the other hand, it’s certainly just step one. I live near Seattle, home of Amazon and Microsoft. So, to use an appropriate analogy, our app isn’t quite Windows 1.0, but maybe Windows 3.1; it’s decent, it does something, but there’s a long way to go.

I bet a lot of people in our age group can relate to this analogy. When you say, “it does something,” what exactly do you mean?

Ben: The app is very worthwhile now. I’m a user, we should all be users, but we’ll be adding more features step by step so that within a year, this will be a much more powerful tool. I think we could be 2-4 years away from a human-level AGI. The goal would be that once we get there, one of the first things this human-level AGI does is help us cure aging and death, and data like we’re gathering with the Rejuve app is going to help it do this trick.

Even if you have an AGI with slightly greater than human intelligence, it’s going to need data, and data takes time. Taking a therapy from an initial prototype through something considered safe enough for people to use takes time. Gathering data from a diversity of people over time also… takes time.

We want to ensure the AI has this data. I’m especially interested in a feature we’ll launch probably later this year or early next year, which lets app users launch their own clinical trials. You’d have groups of people trying something, maybe a paleo diet, maybe NAD supplements, and measuring the effects. These groups would agree to gather data about themselves in a certain way, creating a subset of more rigorously structured data that gives the AI more to work with.

The AI could also suggest clinical trials, saying “Do we have 200 people willing to try this supplement while not doing these other things and willing to provide this amount of data?” The AI itself can treat the world as its ethical opt-in laboratory and suggest trials.

It can generate hypotheses.

Ben: Right. Currently we’re using deep neural nets together with OpenCog Hyperon to generate hypotheses. We’re constrained by the slow pace of setting up collaborations with biology labs to test these hypotheses, but some experiments can be done by gathering data from app users and having people do standard lab tests rather than needing specialized biology lab equipment.

For hypotheses that can be tested “in the wild,” AI and people can brainstorm together, then groups can volunteer for trials. They’re doing good for the world and themselves. If therapies are discovered through a trial, participants could be early adopters when the therapy reaches the appropriate evaluation stage. These are features on our roadmap.

The current version of the app already provides significant value by structuring the process of capturing basic data about your life. You can get judgments on that data from the probabilistic AI model inside the app; that’s the basic platform we’re starting from. There are many other features coming: smarter AI, of course, but these flexible mechanisms for allowing the user community to self-organize and gather more targeted data are equally important as the AI advances.

This fits into the concept of citizen science, which is rapidly gaining traction, really well. It’s hard to do right, for instance, due to lack of randomization, but even though, the benefits can be huge.

Ben: It should get easier because even before we have AGI, we have AI now that can help with the science, which is interesting. As we integrate our OpenCog Hyperon with LLMs, we’ll get AI that’s better at experimental design, statistical data analysis, and hypothesis generation.

So much lab work can be outsourced now: you can send DNA, RNA, or metabolomic data and get a report back in your email. It is getting easier, but as you alluded to earlier, gathering appropriate data is still one of the weak points. That’s what makes biology such a challenge compared to AI work. With self-modifying AI, the AI is running and watching itself, and there’s the data. In biology, we’re dealing with all these biological bodies that aren’t properly instrumented for data collection.

There’s been a lot of activity lately in the field of experiment automation. Are you planning to test your hypotheses in animal models?

We’ve been working through our partner company, Rejuve Biotech, and SingularityNet, with a company based in Irvine, California that has fruit flies experimentally evolved over 45 years to live five to eight times longer.

The “Methuselah” flies.

Yes, but we have flies that are much better than the published Methuselah flies. We have a pipeline where we can take hypotheses from data analysis on the Rejuve network of human longevity enthusiasts and evaluate them on these long-lived fruit flies.

We can see whether feeding a combination of herbs or lifestyle modifications to the flies prolongs their life. Previously, we tried supplements in flies and then in people and found compounds that could roll back moderate or mild Alzheimer’s and decrease inflammation. You can also go the other way, using flies as a testbed for interventions discovered in humans.

As to automation, we can collect some data automatically from flies. You can put a camera above the cage and identify individual flies from their movement patterns, studying them using automated vision analysis, but I’ve been impressed by how manual some of the work still is. If you need a DNA sample from the nervous system of a fly, you’ve got a human looking through a microscope using tweezers. This seems very simple, but it’s a niche, so no one has bothered to automate it.

This relates to the acceleration we’ll get from even an early-stage AGI: not just amazing insights about aging but having an AGI that could synthesize new robots to wield the tweezers to extract the fly’s brain.

This would be groundbreaking.

Many things in biology could be sped up by a human-level AI operating robots and lab equipment. You should be able to speed up animal model experiments very rapidly and get much more accurate simulation models than we have now.

I’ve been working on this with Debbie, Rejuve.AI’s chief scientist, since around 2000. Right now, we could put together a thorough simulation model of the human body on different levels by combining all the simulation models from research literature with available datasets and using AI inference to fill the gaps. I think you could create a very nice holistic systems biology simulation of the human body at any point in time and as it ages.

No one seems to be doing that because systems biology isn’t in vogue. The pharma and academic worlds tend to micro-focus on particular subsystems of the body.

The data we’re gathering from the app will be critical because for a holistic simulation model of the human body, you need more holistic data about human bodies carrying out their lives alongside the micro-level data the biopharma industry provides. The data can help with specific therapeutics discovery and for configuring holistic systems biology simulation models of aging bodies. These simulation models, together with machine learning and reasoning, could drive significant discovery.

We have a partner project, NuNet, building decentralized computing infrastructure. In a future version of the app, users could donate processing power from their laptops, phones or company compute networks to run some of these simulations. App users would not only be contributing data but also idle processing cycles and memory, like a distributed longevity supercomputer.

Decentralized AI. Do you think it can work?

Ben: Absolutely. You can run evolutionary learning genetic algorithms for analyzing biomedical data, for example, very nicely in a widely decentralized way on heterogeneous compute infrastructure. One lesson from DeepSeek earlier this year is that you can scale down the processing power needed to train deep neural models. It’s becoming more evident that you can do a lot of AI work in a decentralized way, and even if some things still need server farms, you can do quite a lot of processing across a small number of edge devices. This is another way people can contribute.

We’re giving people multiple reasons to contribute. As we roll out future versions of the app, we’ll implement more sophisticated token incentivization mechanisms. You’re rewarded with RJV tokens for the data you provide, for insights toward discovery, and for contributing processing power.

It’s an interesting incentive mechanism. Can you tell me more about the idea of tokens and what you can buy with them?

Jasmine: We’ve spent a lot of time building essential partnerships to make this pipeline work. A few companies have been quick to adopt cryptocurrency; there’s this connection forming between crypto and longevity in this emerging DeSci space, which is exciting. We have GlycanAge, a peptide company, Travala for booking flights, hotels, and experiences with RJV tokens, a recent partnership for lab tests within the app, and a longevity and aesthetics clinic in Singapore onboarding RJV.

We’re seeing adoption, and we’re always trying to get our network partners to onboard so users can have that direct experience. The idea is that you earn tokens in exchange for providing data, then use them in a health and wellness ecosystem. We want to make the RJV token the currency for the longevity economy, for wearables, supplements, tests, consultations with clinicians, travel to therapies not available in your region, and so on.

We’re creating a circular economy, with tokens incentivizing more data provision to build up the database and eventually rewarding contributions to new products and therapies. That gets into our NFT program.

This sounds exciting, but when I downloaded and logged into the app, honestly, it felt a bit like a commercial gimmick. I wonder whether you’re concerned that you’ve created a too commercial image for the app, with all these collaborations pushing products and services.

Jasmine: These are all actual partners listed on our website too. We want a wide network with a variety of offerings, not favoring one over another. It’s about “Here are trusted sources if you’re looking for these things.” If you’re looking for NAD supplements, for example, this is a partner working with us in our network. We’re encouraging more partners to join and care about clinical validation, ethical standards, and certification of the products offered.

Ben: We’re trying to be careful, more so than many others in the longevity space. We’re only directly offering things we believe have actual value according to the science we know. There is a commercial aspect, but I take supplements and pay for them; that’s commercial reality. As we evolve the app, we’ll fine-tune the presentation.

My friend Bill who runs Life Extension Foundation faced a similar issue. He wants to help us all live forever, and they’re also selling supplements. He’s tried hard in Life Extension Magazine to present the scientific data behind each supplement. They won’t accept something for sale unless there’s peer-reviewed data showing it does what it claims. We’re aiming to position ourselves similarly: if someone wants to sell through us, it doesn’t mean we know it will definitely prolong life, but there’s scientific evidence making it a reasonable hypothesis.

Jasmine: And also a way for users to find and input data more easily, rather than wondering “Where do I go? Where do I get these tests?”

Your app offers an assessment of the user’s biological age, which means you’ve created a biological age clock. How was it done in terms of training and validation?

Jasmine: I wouldn’t call it a clock, more like a calculator at this point, though we’re continually enhancing it. We started with the NHANES dataset, the same one we’re using for our neural network model. We isolated about 150 variables that were closely correlated, using that as the ground state to gather more data and fine-tune. We want to augment it with DNA methylation data as well, since right now it’s based on blood biomarkers and survey metrics. We’re headed toward a multimodal approach.

The biological age feature itself is very attention-grabbing, and users love it. There was a debate because there’s not even a clinical standard for what biological age means or how to measure it. It’s more representative of whether you’re aging faster or slower compared to an average, and what you can do to improve. That’s where all biological age tests are right now.

I’ve been taking many of these tests myself recently, and the results are pretty congruent with what I could already imagine based on my lifestyle and metrics. Aggregating these numbers and seeing the different factors is valuable, but we want to move beyond just a number to something more informative.

Ben: It is statistically meaningful. Using these ML-based predictors, you can get a prediction that’s much better than noise about someone’s likely demise. It’s interesting to get this statistical indicator, but of course, there are error bars. It’s not like the Twilight Zone where someone could predict you’ll die on January 3, 2047. The risk is that people will over-interpret it, but we’ve tried to include safeguards in the app.

What will be most interesting is giving people the ability to inspect why the prediction was what it was, which relates to transparency in AI models. That’s limited in the current version, but we’re actively working on it. I’m 58; if I were told I’m biologically 75, I would certainly like to know why. The challenge, as with everything else, is data. We took data from the NHANES study.

I think NHANES is about 15 thousand people, but it’s a lot of data points because they tested many things.

Ben: The challenge is that most variables from that dataset aren’t available for the average app user. If someone had enough blood tests and all the information needed for the most informative NHANES-based model, you’d get a better statistical prediction. With the average person, you have only a few data points, resulting in an estimate with wider error bars due to lack of data.

The frustrating thing is that people often have a lot of data gathered about their bodies, but it’s sitting in databases of hospitals or clinical centers. Because we don’t own our own data, it’s easier to get all tests done again than to extract it from the databases of different medical facilities you’ve visited over your life.

This aspect of data sovereignty ties in with the blockchain underpinning. We talked about token incentivization and the potential use of decentralized processing power, but another interesting aspect of blockchain technology is that you own your data, have access to it, control who else can access it, and can trace it. This data can be stored in a decentralized cloud facility rather than wherever a doctor’s office or pharma company put it.

It’s insane that the medical world doesn’t work this way. Ideally, anytime you get a medical test, or a doctor writes a report on your condition, there would be a QR code you could scan to securely send that information to your account on a decentralized data repository. You could go online and see an index of all your uploaded data, encrypted by your private keys, and share whatever aspects you choose with whatever networks you want.

This would even simplify operations for the mainstream medical establishment. When you visit a new doctor, you’d just show your QR code, and they could scan whatever pieces of your data you thought appropriate to share. Currently, they have to go through all kinds of procedures to get information from out-of-network doctors. It would help the mainstream medical system work better while also giving projects like Rejuve tremendous amounts of data and enabling citizen science and decentralized science to work much better.

If we could just liberate the data, this in itself would be revolutionary. Ben, you’re a visionary. Do you have a timeline for how AI might help us solve aging?

Ben: I’m a fairly hardcore singularitarian. I think my friend Ray Kurzweil was probably roughly correct about AI reaching human-level intelligence around 2029. I’m hoping we can do it by 2027 or so, or it could even be next year.

But I think Ray was pessimistic about the timeline between human-level AGI and ASI. Once you have human-level AGI, it could be months to a few years before you have superintelligence. I don’t see why it would take 16 years as he thought, from 2029 to 2045, unless the AGI itself wanted to slow things down out of caution or because it liked Ray and wanted to make him correct. Looking at it that way, it’s unlikely we’ll come up with a definitive solution to human super-longevity before 2029-2031. We can make progress, but the major breakthroughs will likely come after that.

I’ll take that.

Ben: The question is what we can do now. You could say, “Just wait until AGI comes and let it solve longevity,” but an AGI isn’t magic. Just as humans are much smarter than most animals but aren’t magic—we still get sick and die, and I’d still lose a one-on-one fight with a tiger without weapons—an AGI will still have limitations.

The more data we can gather and intelligently organize to feed the AGI when it emerges, the faster it can progress on solving human aging. Even if an AGI gives us some magic pill, we’ll still want safety testing, trying it on small groups first, and so on.

By and large, if our singularitarian view is right, we’ll probably all be approximately immortal, barring freak accidents, by around 2035. If you get AGI in 2029, some progress toward ASI, and then five years for the AGI to solve things and create gene therapy clinics, that’s the optimistic timeline.

If this is overly optimistic and we don’t get human-level AGI until, say, 2040, which isn’t how I think things will go, but it’s not irrational, perhaps because it turns out human-level AGI needs quantum computing (which I don’t think it does) or because the global sociopolitical system goes even crazier in the wrong sort of way, then the scenario changes. If AGI arrives in 2040, then proto-AGI systems might make huge progress toward solving aging based on data from Rejuve and other sources before we reach human-level intelligence.

Assuming our own lives are important to us, we can hedge our bets. The same data is useful in either case. We can gather data, build longevity-based AI models, try out therapies, and if we get superintelligent AGI faster, all the better. If AGI development stalls, our proto-AGI may still make major longevity breakthroughs.

One conclusion I’ve reached after being in the future technology space for a while is that the problem isn’t whether to allocate resources to AGI versus longevity versus nanotech versus uplifting human consciousness. The problem is the total amount of resources spent on all this important stuff versus resources spent on destruction and selling useless junk. We need more AGI research, more super-longevity research, and to advance our longevity app. The more we can focus people’s energy on these things rather than on useless and destructive endeavors, the better off we’ll be.

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Date Posted: June 4, 2025

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Educated ‘Night Owls’ Might Have More Cognitive Decline Risk

A recent analysis of over 20,000 middle-aged and older adults showed an association between a later chronotype (‘night owls’) and cognitive decline among highly educated people [1].

Early birds and night owls

One risk factor linked to dementia is a disrupted circadian rhythm, the natural 24-hour cycle of sleep and activity patterns. Common disruptions in that rhythm include shift work and frequent jet lag, which have been reported to contribute to neurodegeneration [2, 3].

Chronotype is a natural preference regarding when sleep and activity occur. For some people (‘early birds’), it is to wake up and go to sleep early. Others, ‘night owls’, experience more energy later in the day, which encourages them to stay up late.

In this study, the researchers aimed “to investigate the longitudinal association between chronotype and cognitive decline among adults of the general population.” It included data from 23,798 participants in the Lifelines population-based cohort study from the northern Netherlands; the participants were at least 40 years old with a median age of 49 years.

The researchers assessed the participants’ chronotypes and cognition, specifically non-verbal fluency and executive functioning, which were evaluated at the beginning of the study and again after a 10-year follow-up. Cognitive decline was calculated by subtracting the two values, resulting in a score between 0 and 175.

Bad news for ‘night owls’ with degrees

Based on previous research, the researchers hypothesized that the relationship between chronotype and cognitive health is U-shaped in nature; however, this was not the case, as the assessment revealed an association between a late chronotype and cognitive decline.

Such an association was not observed for the early birds. The authors explain that the lack of association between an early chronotype and cognitive decline may be due to the fact that individuals with extremely early chronotypes constituted only 0.11% of the study population. Future research would need to investigate it further.

Based on previously reported links between increased dementia risk and lower educational attainment, older age, and female sex, the researchers included these variables in the analysis of factors that moderate the association between chronotype and cognitive decline.

Among the tested variables, only educational attainment moderated the association between chronotype and cognitive decline. Therefore, the researchers divided the participants based on their education level and re-analyzed the data.

In the high educational attainment group, a negative association was found between chronotype and cognitive change. Specifically, “for every one-hour increase in chronotype, cognition declined by 0.80 points among the high-educational attainment group over a 10-year follow-up.”

In contrast, the middle-educational attainment group showed a borderline significant effect, and there was no association in the low-educational attainment group.

The study’s lead author, Ana Wenzler, thinks that this may be related to the types of work that people in those groups perform. When it comes to highly educated people, “that probably has to do with their sleep rhythm. They are often people who have to go back to work early in the morning and are therefore more likely to sleep too short, giving their brains too little rest.”

“We suspect that lower- or middle-educated people are more likely to have a job that allows them to take their sleep rhythm into account, such as a job in the hospitality industry or one with night shifts. If this is not possible, your brain does not get enough rest and you are more likely to adopt bad habits. It would be nice if more consideration was given to evening people who now have to work early: for example, by giving them the option of starting later, “ Wenzler continues.

There is also the possibility that this association was observed only in the highly educated group because more people in the low- and middle-educational attainment groups were lost to follow-up. As the researchers discuss, the baseline cognitive functions measured in the people who were lost to follow-up were lower, suggesting that they may not have continued participating due to cognitive difficulties. This would result in an underestimated cognitive decline in this group.

Better sleep, better brain

In further analysis, the researchers focused on highly educated people, aiming to understand the potential pathways linking chronotype to cognition. They focused their study on whether sleep quality and health behaviors such as alcohol intake, physical activity, and smoking mediate the association.

They learned that poorer sleep quality and current smoking status were partially mediating the association by 13.52% and 18.64%, respectively. Other lifestyle choices, such as physical activity, past smoking, and alcohol consumption, didn’t explain the association.

Those results go along with previous observations that linked a later chronotype to poorer sleep quality, including shorter sleep duration, which in itself is associated with a loss of brain volume [4] and disturbances in the various sleep phases [5], potentially disrupting the clearance of Aβ, which is associated with Alzheimer’s disease.

Late chronotype was also linked to increased smoking risk, and chronic smoking is linked to brain aging and white matter degeneration [6].

Social jetlag compared to chronotype

The researchers note that their study does not address whether the chronotype itself or social jetlag plays a role in cognitive decline. Social jetlag results from a misalignment between a person’s chronotype and daily activities, leading to a reduction in sleep duration and quality. For ‘night owls,’ it might mean needing to get up early to attend work in the morning, while ‘early birds’ might stay late due to social activities.

There are variations in the definition and measurement methods of social jetlag, making it more challenging to study and excluding it from this analysis. However, the study’s authors encourage future research to improve the standardization of social jetlag measurement methods and address the relationship between chronotype and cognitive decline, independent of social jetlag.

An open question

The authors summarize that current knowledge about the relationship between chronotype and cognition remains unsettled. They suggested that differences in study populations, chronotype definitions, cognitive measurements, and follow-up times, which vary across studies, contribute to the differences in results. Their study is a step towards a better understanding of this issue.

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Literature

[1] Wenzler, A. N., Liefbroer, A. C., Voshaar, R. C. O., & Smidt, N. (2025). Chronotype as a potential risk factor for cognitive decline: The mediating role of sleep quality and health behaviours in a 10-year follow-up study. The journal of prevention of Alzheimer’s disease, 100168. Advance online publication.

[2] Lee, K. W., Yang, C. C., Chen, C. H., Hung, C. H., & Chuang, H. Y. (2023). Shift work is significantly and positively associated with dementia: A meta-analysis study. Frontiers in public health, 11, 998464.

[3] Musiek E. S. (2015). Circadian clock disruption in neurodegenerative diseases: cause and effect?. Frontiers in pharmacology, 6, 29.

[4] Montaruli, A., Castelli, L., Mulè, A., Scurati, R., Esposito, F., Galasso, L., & Roveda, E. (2021). Biological Rhythm and Chronotype: New Perspectives in Health. Biomolecules, 11(4), 487.

[5] Di, T., Zhang, L., Meng, S., Liu, W., Guo, Y., Zheng, E., Xie, C., Xiang, S., Jia, T., Lu, L., Sun, Y., & Shi, J. (2024). The impact of REM sleep loss on human brain connectivity. Translational psychiatry, 14(1), 270.

[6] Yu, R., Deochand, C., Krotow, A., Leão, R., Tong, M., Agarwal, A. R., Cadenas, E., & de la Monte, S. M. (2016). Tobacco Smoke-Induced Brain White Matter Myelin Dysfunction: Potential Co-Factor Role of Smoking in Neurodegeneration. Journal of Alzheimer’s disease : JAD, 50(1), 133–148.

Date Posted: June 3, 2025

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Blunting an Inflammatory Pathway Slows Alzheimer’s in Mice

Scientists have demonstrated that knocking out part of the cGAS-STING DNA-sensing pathway slows disease progression in a mouse model of Alzheimer’s, calming down microglia and protecting neurons [1].

STING operation

Inflammation is central to the pathogenesis of Alzheimer’s disease [2], which is accompanied by the accumulation of extracellular plaques of the misfolded protein amyloid beta (Aβ), soluble and insoluble Aβ oligomers (short chunks), and tangles of tau protein. Some oligomers and tau tangles accumulate inside cells, causing stress.

Chronic amyloid/tau stress is thought to damage nuclear DNA and mitochondria, causing DNA to spill into the cytosol. This, in turn, leads to the activation of a DNA-sensing inflammatory pathway with the protein STING as its major regulator. When activated, the brain’s resident immune cells (microglia) amplify inflammation, further damaging neurons and their surrounding environment.

Previous research has found that inhibiting STING with a small molecule, H-151, lowers amyloid burden but also hits multiple off-target receptors. In this new study published in Alzheimer’s & Dementia, a team at the University of Virginia has delivered the first clean genetic test of whether the cGAS-STING DNA-sensing pathway actively drives amyloid pathology in Alzheimer’s.

The researchers crossed a popular mouse model of Alzheimer’s (5xFAD), which exhibits early amyloid accumulation, with another strain in which STING was genetically knocked out. They then subjected the progeny to various tests. Unfortunately, the scientists only used female mice, which might impact the study’s generalizability.

Calmer microglia, healthier neurons

At four months old, a stage when soluble Aβ is high in this model but plaques have only begun to spread, these mice underwent the Morris water maze test. STING-deficient 5xFAD animals found the hidden platform faster and lingered longer in the target quadrant during the probe, pointing to an early cognitive rescue, even before the appearance of clear Alzheimer’s symptoms.

Further tests showed that soluble and insoluble Aβ42, a particularly harmful Aβ species, fell by roughly 30-40% in STING-deficient brains. Plaque counts and coverage dropped in three brain regions: cortex, hippocampus, and subiculum.

Activated microglia are linked to a stronger and neuron-damaging immune response. In mice lacking STING, microglia were more subdued, covering less tissue and clustering less tightly around plaques. Their morphology also suggested a “resting” rather than an “attack” phenotype. Single-nucleus RNA sequencing of about 6,000 cortical cells showed that STING-null microglia turned off some pro-inflammatory genes while boosting markers of homeostasis.

These results strongly suggest that STING deletion tones down microglial activation. The researchers note that “many of the top genetic risk factors linked to late-onset AD are immune genes and/or are expressed predominantly by microglia in the brain.”

Neurons, too, were in better shape in STING-deficient animals, showing healthier neurites, less oxidative stress, and less cell death at both five and nine months. That sustained drop means that removing STING not only cools inflammation but also protects neurons from structural and oxidative harm over time.

Relevant to other diseases

“Our findings demonstrate that the DNA damage that naturally accumulates during aging triggers STING-mediated brain inflammation and neuronal damage in Alzheimer’s disease,” said Dr. John Lukens, director of UVA’s Harrison Family Translational Research Center in Alzheimer’s and Neurodegenerative Diseases. “These results help to explain why aging is associated with increased Alzheimer’s risk and uncover a novel pathway to target in the treatment of neurodegenerative diseases.”

“We found that removing STING dampened microglial activation around amyloid plaques, protected nearby neurons from damage, and improved memory function in Alzheimer’s model mice,” said researcher Jessica Thanos, part of UVA’s Department of Neuroscience and Center for Brain Immunology and Glia (BIG Center). “Together, these findings suggest that STING drives detrimental immune responses in the brain that exacerbate neuronal damage and contribute to cognitive decline in Alzheimer’s disease.”

cGAS-STING pathway has been linked to other neurodegenerative diseases, such as amyotrophic lateral sclerosis [3] and Parkinson’s, as well as to many inflammatory diseases, making this study’s findings potentially even more important. However, more rigorous research will be needed. Along with numerous strengths, this study also had several limitations, apart from using only female mice. For instance, the researchers did not assess cognitive function later in life, possibly due to the technical difficulties of breeding an additional cohort.

“We are only beginning to understand the complex role of innate immune activation in the brain, and this is especially true in both normal and pathological aging,” Thanos said. “If we can pinpoint which cells and signals sustain that activation, we will be in a much better position to intervene effectively in disease.”

“Our hope is that this work moves us close to finding safer and more effective ways to protect the aging brain, as there is an urgent need for treatments that can slow or prevent neuronal damage in Alzheimer’s,” Lukens added. “Shedding light on how STING contributes to that damage may help us target similar molecules and ultimately develop effective disease-modifying treatments.”

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Literature

[1] Thanos, J. M., Campbell, O. C., Cowan, M. N., Bruch, K. R., Moore, K. A., Ennerfelt, H. E., … & Lukens, J. R. (2025). STING deletion protects against amyloid β–induced Alzheimer’s disease pathogenesis. Alzheimer’s & Dementia, 21(5), e70305.

[2] Kinney, J. W., Bemiller, S. M., Murtishaw, A. S., Leisgang, A. M., Salazar, A. M., & Lamb, B. T. (2018). Inflammation as a central mechanism in Alzheimer’s disease. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 4, 575-590.

[3] Yu, C. H., Davidson, S., Harapas, C. R., Hilton, J. B., Mlodzianoski, M. J., Laohamonthonkul, P., … & Masters, S. L. (2020). TDP-43 triggers mitochondrial DNA release via mPTP to activate cGAS/STING in ALS. Cell, 183(3), 636-649.

Date Posted: June 2, 2025

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Rejuvenation Roundup May 2025

May was a substantial month in the rejuvenation biotechnology world, including nanomedical advancements, T cells to fight senescence, a transcription factor with multiple potential uses, and the Hallmarks of Aging lab discussing two more hallmarks.

LEAF News

Longevity Investor Network 2024 End of Year Update: Developing technologies to defeat age-related diseases by keeping people biologically younger is the goal of the rejuvenation biotechnology field. LRI created the Longevity Investor Network (LIN) to connect promising longevity tech companies with investors to get this technology to the clinic.

Interviews

Michael Levin on Bioelectricity in Development and Aging: Michael Levin, professor at Tufts University and director of Allen Discovery Center, has been working for years on how bioelectrical patterns affect development and aging. His research proves that this often-overlooked part of biology is immensely important and that mastering its mechanisms might one day do wonders for human health and longevity.

Advocacy and Analysis

Playing the Long Game Towards Radical Life Extension: As Peter Fedichev explains in this op-ed, current techniques can only extend life and health to a limited extent. Slightly more advanced therapies may lead to somewhat more healthspan. For radical life extension, entirely new approaches are needed.

Well-Known Researchers Discuss Personalized Aging Treatments: The Hallmarks of Aging team has returned to Cell, publishing a detailed review discussing how future methods of dealing with aging might be highly personalized and adding two more hallmarks in the process.

Is Aging Part of the Immune System?: In this op-ed, Peter Lidsky suggests that aging evolved to stop the spread of chronic pathogens and that without aging, such pathogens would infect the whole population.

SENS vs. the hallmarks of aging: competing visions, shared challenges: The authors examine their definitions of aging, perspectives on health and disease, approaches to scientific evidence and causal interventions, and communications strategies.

Research Roundup

Limiting One Protein Maintenance Pathway Enhances Another: In one Aging Cell paper, researchers have explored how transcription factor EB (TFEB) promotes proteostasis in a common aging model.

TFEB Lets Cells Live Long Enough to Become Senescent: In a different Aging Cell paper, researchers have explained how TFEB is related to cellular senescence and keeps stressed cells alive.

Young Microbiota Transfer Reduces Aging Aspects in Mice: In a recent study, lifelong, repeated microbiota transfer from young mice to old mice improves intestinal permeability, coordinative ability, and metabolic profiles while reducing pro-inflammatory responses.

A New Approach to Treating Aging Skin: Researchers publishing in Aging Cell have found a biochemical pathway that leads skin cells to become senescent along with a potential target for future therapies.

Gamma Delta T Cells Show Promise Against Cellular Senescence: Scientists from the Lifespan Research Institute have discovered that a subset of T cells effectively targets senescent cells and improves outcomes in a mouse model of idiopathic pulmonary fibrosis.

How Apigenin May Reduce Senescence and Cancer: Screening of a natural compounds library has revealed the senomorphic properties of apigenin. This natural flavonoid also demonstrated rejuvenating effects on many aging-associated molecular features as well as physical and cognitive performance, and it has a beneficial impact on cancer treatment in mice and cells.

Results of a Phase 1 Trial of Senolytics for Alzheimer’s: The results of a Phase 1 trial of the well-known senolytic combination of dasatinib and quercetin (D+Q) in patients with Alzheimer’s disease have been published in Neurotherapeutics.

Nanostructures Trap Amyloid Beta, Rescuing Neurons: Scientists have created engineered nanostructures that bind monomers and oligomers of harmful amyloid beta protein, preventing them from entering neurons and drastically increasing the cells’ survival in vitro.

Dietary Methionine Restriction Improves Healthspan in Mice: In a recent study, researchers investigated how restricting dietary methionine and inhibiting the tyrosine degradation pathway affects healthspan in aged mice. While affecting tyrosine didn’t show any benefits, methionine restriction improved many, but not all, measures of healthspan, including frailty, pathological disease burden, and neuromuscular function.

Common Laboratory Mice Age Faster in a Natural Environment: In Aging Cell, researchers have found that exposing ordinary Black 6 mice to a more natural environment accelerates rather than slows the aging of their livers.

Vitamin D Rescues Telomere Attrition in Leukocytes: A sub-study, which was part of the large-scale VITAL trial, determined that vitamin D supplementation slows telomere attrition in leukocytes almost to a halt. This could have real-life clinical implications.

Caloric Restriction Slows Ovarian Aging in Monkeys: In Aging, researchers have published their discovery that three years of caloric restriction in rhesus macaques that are beginning to enter menopause slows their ovarian aging.

DNA Methylation Patterns Trace Blood Aging Dynamics: Scientists have created a new, highly effective method of tracing blood cells’ lineage. This can improve our understanding of clonal hematopoiesis and its impact on an aging organism.

Why Some Mammals Live Much Longer Than Others: A recent study investigated differences in maximum lifespan potential among different mammalian species. The researchers found associations between gene family size expansion, maximum lifespan potential, and relative brain size. They also studied genomic features linked to lifespan evolution.

How Plasma Exchange Affects Aging in Older People: A placebo-controlled clinical trial, with results published in Aging Cell, has determined that therapeutic plasma exchange has beneficial effects when combined with immunoglobulin, according to multiple epigenetic clocks and -omics biomarkers.

A Drug Combo Increases Lifespan in Mice by Over 30%: Combining rapamycin with the anti-cancer drug trametinib produced a synergistic effect and robust life extension in a new study. Rapamycin, which was first widely used as an immunosuppressant for transplant patients and is also used in oncology, is considered one of the most powerful geroprotectors.

Association between dietary diversity and healthy aging: a systematic review: Enhancing healthy dietary behaviors for older people is suggested to increase their awareness and, consequently, dietary diversity.

Spicy food consumption and biological aging across multiple organ systems: These findings highlight that spicy foods may slow comprehensive and organ-specific biological aging, especially metabolic and kidney biological aging.

Lifetime walking and Alzheimer’s pathology: A longitudinal study in older adults: Long-duration, high-intensity walking may reduce brain Aβ accumulation, potentially lowering AD risk, particularly when initiated before late life.

Effects of cannabidiol (CBD) treatment on age-related cognitive decline in C57 mice: The findings of this study indicate that CBD reduces inflammatory response in the brain and improves cognitive decline associated with aging.

Intermittent Supplementation With Fisetin Improves Physical Function and Decreases Cellular Senescence in Skeletal Muscle With Aging: Taken together, these findings provide proof-of-concept support for fisetin as a senolytic strategy to improve physical function with aging.

Quercetin Reduces Vascular Senescence and Inflammation in Symptomatic Male but Not Female Coronary Artery Disease Patients: Short-term quercetin treatment effectively targeted vascular senescence in male CAD patients, improving inflammatory and functional outcomes. However, these benefits were not observed in female patients.

Supplementation with Bioactive Compounds Improves Health and Rejuvenates Biological Age in Postmenopausal Women: The results suggest that these bioactive compounds may be a beneficial strategy for promoting healthier aging in postmenopausal women by enhancing immune function, reducing biological age, improving redox balance, and regulating stress hormones.

Co-administration of vitamin D and N-acetylcysteine to modulate immunosenescence in older adults with vitamin D deficiency: A high dose of vitamin D significantly attenuates senescence in some cells of older adults. However, co-administration of N-acetylcysteine with both the standard and high doses of Vitamin D further enhances these beneficial effects.

Systematic transcriptomics analysis of calorie restriction and rapamycin unveils their synergistic interaction in prolonging cellular lifespan: The transcriptional synergistic interaction of CR + RM is validated in extending the lifespan of both yeast and human cells.

Analysis of lifespan across diversity outbred mouse studies identifies multiple longevity-associated loci: Collectively, these loci explained over half of the estimated heritable variation in lifespan across these studies and provided insight into the genetic architecture of lifespan in DO mice.

ElixirSeeker: A Machine Learning Framework Utilizing Fusion Molecular Fingerprints for the Discovery of Lifespan-Extending Compounds: This study demonstrates that ElixirSeeker effectively accelerates the identification of viable anti-aging compounds, potentially reducing costs and increasing the success rate of drug development in this field.

Baricitinib and Lonafarnib Synergistically Target Progerin and Inflammation, Improving Lifespan and Health in Progeria Mice: This preclinical study demonstrates the synergistic potential of this combination therapy in addressing progeria-related systemic and tissue-specific pathologies, offering a promising strategy for enhancing both lifespan and health.

Unveiling the Anti-Aging Potential of 3HB: Lifespan Extension and Cellular Senescence Delay: These findings highlight the promising therapeutic potential of 3HB as an anti-aging intervention and provide novel insights into its underlying mechanisms.

Low-frequency ultrasound reverses insulin resistance and diabetes-induced changes in the muscle transcriptome in aged mice: LFU demonstrates potential as a noninvasive therapy for reducing inflammation and altering immune cell function in skeletal muscle in insulin-resistant and diabetic populations.

News Nuggets

2060 Longevity Forum: Future Health Meets Smartest Capital: The south of France will host the first edition of the 2060 Longevity Forum, a groundbreaking event designed to position longevity as the greatest investment opportunity of our time.

Longevity Investment More Than Doubled to $8.5bn in 2024: Industry analysts at Longevity.Technology today published the 2024 Annual Longevity Investment Report, a full-year report on the state of investment in the longevity sector, with total financing reaching USD $8.49 billion across 331 deals.

Grant Award Announcement: Rejuvenating the Aging Brain Study: The Longevity Science Foundation (LSF), a nonprofit organization dedicated to funding research aimed at extending the healthy human lifespan, is proud to announce a grant award to the University of Copenhagen’s Center for Healthy Aging within the Department of Cellular and Molecular Medicine, for the study “Rejuvenating the Aging Brain.”

Circulate Health Publishes Results of Multiomics Study: Circulate Health, the company dedicated to harnessing the potential of therapeutic plasma exchange (TPE) to advance human healthspan and lifespan, today announces the publication of a single-blind, human clinical trial in Aging Cell.

Foundations and Strategic Vision of the Canadian Translational Geroscience Network: With a clear roadmap for future growth, the CTGN aims to position Canada at the forefront of geroscience, fostering evidence-based innovation that improves the health and quality of life for aging populations.

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Date Posted: May 30, 2025

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A Drug Combo Increases Lifespan in Mice by Over 30%

Combining rapamycin with the anti-cancer drug trametinib produced a synergistic effect and robust life extension in a new study [1].

A multi-node approach

Rapamycin, which was first widely used as an immunosuppressant for transplant patients and is also used in oncology, is considered one of the most powerful geroprotectors. In the “gold standard” Interventions Testing Program (ITP) trial, rapamycin increased median lifespan in mice by 23% for males and 26% for females [2].

Rapamycin works by inhibiting mTOR, a key regulator of nutrient sensing. Very broadly, rapamycin treatment reroutes the body’s resources from growth to maintenance, including by increasing autophagy, the process of intracellular junk disposal.

mTOR is part of a bigger nutrient sensing network, and a growing number of studies indicate that affecting other nodes in this network might create a synergistic effect with rapamycin. Previous successes include a combination of rapamycin and the anti-diabetes drug acarbose, which increased median lifespan by 28% for females and by 34% for males [2].

We reported on this study last year, when it was published as a preprint. Now, peer-reviewed and published in Nature Aging, it is worth revisiting. This study reports on a combination of rapamycin and trametinib, another oncology drug that inhibits the nutrient-sensing Ras/MEK/ERK pathway, which is upregulated in many cancers. Co-authored by the renowned geroscientist Linda Partridge of the UCL Institute of Healthy Aging and the Max Planck Institute for Biology of Aging, this study had a large sample size and included extensive phenotypic and histological testing.

The researchers had 100-120 mice of each sex in each one of the four arms (control, rapamycin only, trametinib only, and combination) for a total of 800+ animals. The treatment started at the age of 6 months. While trametinib treatment was continuous, the mice only received rapamycin every other week, as previous research indicates it’s safer and just as effective as continuous administration.

The combo reigns supreme

Trametinib treatment alone caused a mild but statistically significant increase in median lifespan of 7% for females and 10% for males. This is the first study to establish this drug as a lifespan extender in mice, although previous research showed effectiveness in other animal models such as Drosophila flies. Interestingly, the drug caused a massive 16% increase in maximal lifespan in male mice but not in females.

Rapamycin performed as expected, while the combination produced the biggest effect, increasing median lifespan by 35% in females and 27% in males along with maximal lifespan by 32% in females and 26% in males. Maximal lifespan was measured as the point in time when only 10% of the mice remain alive.

“While we do not expect a similar extension to human lifespans as we found in mice,” said Linda Partridge, “we hope that the drugs we’re investigating could help people to stay healthy and disease-free for longer late in life. Further research in humans in years to come will help us to elucidate how these drugs may be useful to people, and who might be able to benefit.”

Improved healthspan and cancer burden

The combination treatment also improved various functional outcomes. Rapamycin alone, and even more so the combo, kept the heart’s electrical timing youthful by averting the usual QT-interval stretch in males, while trametinib helped slow the age-related drop in resting heart rate. All treatments nudged older male mice to burn a little more fat at night with an improved respiratory exchange ratio. The combination treatment had a considerable effect on inflammation by lowering the levels of pro-inflammatory cytokines and the number of activated microglia, pro-inflammatory immune cells, in the brain.

Cancer is a major cause of death in lab mice. Since both drugs are used in oncology, the researchers wanted to know whether the pro-longevity effect was mostly due to cancer reduction. Only the combination treatment significantly lowered liver and splenic tumor prevalence (35% to 45% compared to at least 60% in controls), suggesting that reduced cancer burden accounted for part of the added lifespan. Yet, most combo-treated mice still died of cancer and their survival advantage remained when cancer deaths were excluded from the analysis. This means that other benefits must also be at play.

Rapamycin has known side effects, which include increased blood glucose (hyperglycemia), increased liver fat (lipidosis), and gonadal pathology. The good news is that adding trametinib did not exacerbate those symptoms, but the bad news is that it did not fix them. Rapamycin also caused a significant shift toward fat mass at the expense of lean mass in females.

“Trametinib, especially in combination with rapamycin, is a good candidate to be tested in clinical trials as a geroprotector,” suggested Sebastian Grönke, another senior author. “We hope that our results will be taken up by others and tested in humans. Our focus is on optimizing the use of trametinib in animal models.”

Yes I will donate❤️

Literature

[1] Gkioni, L., Nespital, T., Baghdadi, M., Monzó, C., Bali, J., Nassr, T., Cremer, A. L., Beyer, A., Deelen, J., Backes, H., Grönke, S., & Partridge, L. (2025). The geroprotectors trametinib and rapamycin combine additively to extend mouse healthspan and lifespan. Nature aging, 10.1038/s43587-025-00876-4. Advance online publication.

[2] Strong, R., Miller, R. A., Cheng, C. J., Nelson, J. F., Gelfond, J., Allani, S. K., … & Harrison, D. E. (2022). Lifespan benefits for the combination of rapamycin plus acarbose and for captopril in genetically heterogeneous mice. Aging Cell, 21(12), e13724.

Date Posted: May 29, 2025

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How Plasma Exchange Affects Aging in a Human Trial

A placebo-controlled clinical trial, with results published in Aging Cell, has determined that plasma replacement has beneficial effects when combined with immunoglobulin, according to multiple epigenetic clocks and -omics biomarkers.

Looking for a signal

Therapeutic plasma exchange (TPE), the practice of extracting and replacing a person’s blood plasma with a saline solution containing albumin [1], has been studied for over a hundred years. Alongside plenty of mouse studies that have yielded positive results, it has been found to be effective against certain medical conditions in humans, including the long-term ramifications of COVID-19 [2].

Epigenetic clocks are a way to measure biological age.

Epigenetic Clocks - What are they?

An epigenetic clock is a biochemical test that uses DNA methylation levels and accumulation of methyl groups on DNA to determine biological age. There are many different kinds of clocks, and these clocks are often considered to be the gold standard in aging biomarkers. Researchers are currently examining them as potential tools for uncovering the underlying mechanisms of aging, as biomarkers for anti-aging interventions, and as predictors of patient risk for morbidity and mortality.
Read More

These researchers used a wide variety of clocks, 36 in total, in order to determine what effects TPE has on older people. These included most of the major and well-known clocks, including GrimAge along with the Hannum and Horvath clocks, in addition to more recent inventions such as DamAge and clocks that evaluate particular bodily systems.

Four groups and surprising results

The participants were divided into four groups: one receiving plasma once a week for six months, another receiving TPE twice a week for three months, one receiving TPE along with immunoglobulin (IVIG) twice a week for three months, and a placebo group receiving shams of either treatment. The average age of each group was in the 60s. A total of 44 people completed this study.

As expected, there were significant differences at baseline in biological clocks, and not all of them agreed with one another. For example, the sham group, before the experiment had begun, reported decelerated aging on the Horvath clock and very decelerated aging on a metabolic clock. However, they were relatively more age accelerated when measured by the mortality clock GrimAge.

This work used different time points for different groups. Time point 1 represented baseline for all groups, but for the biweekly groups, time point 2 was at one month and time point 3 was at two months. For the once-weekly group, time point 2 was at three months and time point 3 was at five months.

Due to the relatively low number of participants and the large number of clocks, the significance of the differences between baseline and the other time points within any group, within any individual clock, did not survive the statistical correction process. However, there were significant differences between groups even after this correction process.

Combining TPE with IVIG appeared to yield far stronger effects at time point 2 than time point 3, particularly in the clocks that evaluate particular organs and systems. Age acceleration, according to most of the clocks in this category, became much worse in the sham group.

Is immunoglobulin more effective than plasma?

The researchers also combined their clocks into a single metric of age acceleration, which yielded statistically significant results at time point 2. The TPE + IVIG group experienced a reduced average biological age of 2.61 years, while this number was 1.32 for the monthly TPE group. Unfortunately, this benefit did not carry over until time point 3; the researchers suggest that this is due to “potential compensatory mechanisms that mitigate the anti-aging effects after multiple sessions.”

A broader multi-omics examination revealed that the TPE+IVIG group received significant benefits, particularly in the immune system. This group’s proportions of T cells, along with natural killer (NK) cells and monocytes, became more like those of younger people. Proteomics revealed similar correlations, with more proteomic changes in the TPE+IVIG group aligning with biological rejuvenation than in the other groups. These proteomic changes were also found to be related to other hallmarks of aging, such as loss of proteostasis, senescence, and inflammaging.

Interestingly, there appeared to be a correlation between response to this treatment and overall health, as measured by monocytes and platelets. People in poorer health were stronger responders; people in good health did not receive such a strong benefit.

This study had a few limitations. First, the clock differences between groups at baseline somewhat muddied the results, a problem exacerbated by the relatively low number of participants. Second, there was no IVIG-only group, which would have provided more evidence for or against the synergy of combining TPE and IVIG. As it stands, these results suggest that IVIG is possibly more potent than TPE in reducing biological age according to multiple established metrics.

Yes I will donate❤️

Literature

[1] Sviercovich, A., Mei, X., Xie, G., Conboy, M. J., & Conboy, I. M. (2024). The dominance of old blood, and age-related increase in protein production and noise. Ageing Research Reviews, 102641.

[2] Kiprov, D. D. (2023). A Paradigm Shift in the Utilization of Therapeutic Plasmapheresis in Clinical Practice. Ann Clin Med Case Rep, 12(5), 1-7.

Date Posted: May 28, 2025

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Circulate Health Publishes Results of Multiomics Study

Circulate Health, the company dedicated to harnessing the potential of therapeutic plasma exchange (TPE) to advance human healthspan and lifespan, today announces the publication of a single blind, human clinical trial in Aging Cell. This groundbreaking study, led by researchers from Circulate and the Buck Institute for Research on Aging provides promising early data on the impact of TPE on biological age, supporting its potential for new disease and longevity applications.

Therapeutic plasma exchange is a procedure that separates, removes, and replaces patient plasma to treat certain diseases. Multi-omics Analysis Reveals Biomarkers that Contribute to Biological Age Rejuvenation in Response to Therapeutic Plasma Exchange, investigated how TPE impacts biomarkers associated with biological age, including changes across the epigenome, proteome, metabolome, glycome, and immune system, alongside physical measures like balance and strength. Research participants were assigned one of four different treatment groups: 1) biweekly TPE, 2) biweekly TPE with intravenous immunoglobulin (IVIG) 3) monthly TPE or 4) a control group.

The study found:

All patients receiving TPE showed a reduction in biological age, as measured by multi-omics biomarkers, with the most significant reductions in those patients that received TPE with IVIG. Participants undergoing biweekly TPE-IVIG treatment exhibited an average biological age reduction of 2.61 years, compared to 1.32 years for those receiving TPE alone.
Patients receiving TPE with IVIG experienced changes in immune cells associated with reversed age-related immune decline. This intervention modulated cellular senescence-associated proteins and restored age-associated shifts in immune cell composition. This indicates that TPE with IVIG may improve the body’s ability to fight infections and other age-related diseases, particularly those related to inflammation.
Individuals with biomarkers associated with poorer baseline health status, including higher baseline levels of circulating bilirubin, glucose, and liver enzymes, saw the greatest reduction in biological age and improvement in biomarkers. The treatment also showed a benefit for healthy individuals, including in balance and strength.
While the observed treatment effects were strongest after the initial three sessions, subsequent treatments showed diminishing returns, suggesting that spacing out treatments or combining them with other interventions may enhance long-term benefits.

“This is the first interventional multi-omics study to examine the effectiveness of therapeutic plasma exchange modalities,” said Brad Younggren, MD, CEO and Co-founder of Circulate. “Our findings show that plasma exchange and intravenous immunoglobulin are a powerful tool for biological age rejuvenation and provide compelling evidence that targeted plasma interventions can impact age-related molecular changes.”

“In this study, we examined thousands of molecular signatures to pinpoint key drivers of rejuvenation. Our characterization builds a better understanding of which baseline biomarkers are predictive of treatment response and lays a foundation upon which we can build personalized intervention plans for patients in the future,” said Eric Verdin, MD, President and CEO of the Buck Institute and Co-founder of Circulate. “We are excited to expand our research to larger populations, increase access to these treatments for eligible patients, and continue to identify areas of unmet need where these therapies can make a meaningful difference.”

Clinicians can learn more about Circulate at www.circulate.health.

About Circulate Health

Backed by Khosla Ventures, Circulate Health is pioneering technologies to reverse aging and improve health outcomes.

Media Contact

Kristen Mondshein

press@circulate.health

Date Posted: May 28, 2025

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Why Some Mammals Live Much Longer Than Others

A recent study investigated differences in maximum lifespan potential among different mammalian species. The researchers found associations between gene family size expansion, maximum lifespan potential, and relative brain size. They also studied genomic features linked to lifespan evolution [1].

Maximum lifespan potential

Maximum lifespan potential can be defined as “the age at death (longevity) of the longest-lived individual ever recorded in a species,” both in the wild and in captivity, where such risks of death from predation or limited resources are not present.

Intrinsic biological factors determine maximum lifespan potential, and it varies widely among mammals, from less than a year for some of the shrew species to even two hundred in bowhead whales. These species’ genetic differences have been studied in order to examine the underlying biological processes that lead to such differences in lifespan. Previous work has identified changes in genes related to DNA repair, cell-cycle regulation, cancer, and aging in bowhead whales [2] along with expansion in gene families associated with DNA repair and tumour suppression in elephants [3]. This study of genetic differences and related molecular processes may be useful for the development of longevity interventions.

Some studies have explored how maximum lifespan potential is impacted by gene expression differences, gene family size, and similar genomic measures [4, 5]. These studies have pointed to the evolution of gene family size as an essential player in maximum lifespan potential.

Gene families are created when a single gene is duplicated. In such an event, the extra copy has more freedom to evolve, as the original copy produces the protein needed for the organism. The second copy can become a pseudogene, one that has accumulated so many mutations that it ceases to work correctly. Alternatively, it can mutate into a protein similar to the original but with a slightly different function, giving an organism a potential evolutionary advantage. This process can be repeated multiple times, creating a gene family of similar, but somewhat different, genes. Studies of bowhead whales and naked mole rats suggest that some of these duplications are linked to the increased longevity of those animals [2, 6].

In this study, the researchers built on those observations and compared the impact of gene family size on maximum lifespan potential in multiple mammalian species.

Brain size matters

The researchers conducted the bioinformatics analysis of 4,136 gene families in 46 fully sequenced mammalian species. They found an association between maximum lifespan potential and the expansion of 236 gene families.

Next, they tested potential confounders, which can affect the results. They tested relative brain size, body mass, gestation time, and age at sexual maturity. Only relative brain size was found to influence the association of gene family expansion with maximum lifespan potential. These results are in line with previous research suggesting that the evolution of larger brains is related to maximum lifespan potential. The researchers also observed that gene groups related to maximum lifespan potential and gene groups related to brain size were also more likely to contain genes related to immune functions.

The researchers discuss that the immune system can positively impact a longer lifespan in multiple ways, such as through removing senescent cells, infectious agents, and potentially cancerous cells.

However, these results do not have a straightforward interpretation, as the researchers’ sensitivity analysis indicated that most species included in the study have a negligible effect on the results. Larger effects were observed for a few species, suggesting that while one species does not drive the results, they can be impacted by animal groups (taxa) that have extreme values.

More gene diversity

The researchers hypothesized that the expansion of gene families associated with the evolution of maximum lifespan potential might be related to the amount of gene product available in the cell (gene dosage) or the diversity of gene transcripts.

Transcript diversity is related to a process called alternative splicing. Mammalian genes are built from coding DNA sequences (exons) interspaced by non-coding DNA sequences (introns). When DNA is transcribed into RNA during protein production, introns are removed and exons are connected. However, exons are not always spliced in the same order, and, sometimes, some exons are skipped, creating alternative protein versions that originate from the same gene.

Comparing human maximum lifespan potential-associated genes with other background genes revealed higher gene expression levels and a higher number of unique transcripts among maximum lifespan potential-associated genes.

However, the authors warn that these results must also be interpreted with caution as they are only based on human data, and such observations might not be accurate for other species; future studies need to dive deeper into the evolutionary significance of this observation.

Functional, but not a single gene overlap

The researchers gathered data from previous studies that identified different aging-associated genes. They divided them into groups of genes related to aging-associated processes, genes whose expression is age-dependent, manually curated genes associated with ageing or longevity, targets of longevity-modifying interventions, and lifespan-associated genes.

Comparing age-related process genes with maximum lifespan potential-associated genes showed that the latter group is significantly enriched in genes related to DNA repair and inflammation; however, autophagy-associated genes were underrepresented.

Among the genes with age-dependent expression, researchers observed either underrepresentation among maximum lifespan potential-associated genes or didn’t find under- or over-representation, depending on the database and whether their activity increased or decreased with age.

The manually curated genes for cellular senescence and longevity, as well as genes that respond to longevity-modifying interventions such as caloric restriction and life-extending drugs, were significantly underrepresented among maximum lifespan potential-associated genes.

Only genes that have human centenarian-associated genetic variants and genes with faster protein evolution in species with higher maximum lifespan potential were over-represented among maximum lifespan potential-associated genes.

In general, there was a limited overlap between single gene lists from this and previous studies. However, there is an overlap regarding the functions and processes in which those genes are involved. The researchers identified this overlap in immune system functions, DNA damage and repair, apoptosis, autophagy, senescence, and life-extending drug targets, They conclude that “while different studies may identify distinct gene sets, they often highlight the same biological pathways, reinforcing the importance of these processes in longevity.”

While this study does not allow for establishing causality but only associations, its results help in understanding the evolutionary basis of a longer lifespan and identify the genetic and molecular processes that increase maximum lifespan potential.

Yes I will donate❤️

Literature

[1] Kilili, H., Padilla-Morales, B., Castillo-Morales, A., Monzón-Sandoval, J., Díaz-Barba, K., Cornejo-Paramo, P., Vincze, O., Giraudeau, M., Bush, S. J., Li, Z., Chen, L., Mourkas, E., Ancona, S., Gonzalez-Voyer, A., Cortez, D., Gutierrez, H., Székely, T., Acuña-Alonzo, A. P., & Urrutia, A. O. (2025). Maximum lifespan and brain size in mammals are associated with gene family size expansion related to immune system functions. Scientific reports, 15(1), 15087.

[2] Keane, M., Semeiks, J., Webb, A. E., Li, Y. I., Quesada, V., Craig, T., Madsen, L. B., van Dam, S., Brawand, D., Marques, P. I., Michalak, P., Kang, L., Bhak, J., Yim, H. S., Grishin, N. V., Nielsen, N. H., Heide-Jørgensen, M. P., Oziolor, E. M., Matson, C. W., Church, G. M., … de Magalhães, J. P. (2015). Insights into the evolution of longevity from the bowhead whale genome. Cell reports, 10(1), 112–122.

[3] Chusyd, D. E., Ackermans, N. L., Austad, S. N., Hof, P. R., Mielke, M. M., Sherwood, C. C., & Allison, D. B. (2021). Aging: What We Can Learn From Elephants. Frontiers in aging, 2, 726714.

[4] de Magalhães, J. P., Curado, J., & Church, G. M. (2009). Meta-analysis of age-related gene expression profiles identifies common signatures of aging. Bioinformatics (Oxford, England), 25(7), 875–881.

[5] Fushan, A. A., Turanov, A. A., Lee, S. G., Kim, E. B., Lobanov, A. V., Yim, S. H., Buffenstein, R., Lee, S. R., Chang, K. T., Rhee, H., Kim, J. S., Yang, K. S., & Gladyshev, V. N. (2015). Gene expression defines natural changes in mammalian lifespan. Aging cell, 14(3), 352–365.

[6] Kim, E. B., Fang, X., Fushan, A. A., Huang, Z., Lobanov, A. V., Han, L., Marino, S. M., Sun, X., Turanov, A. A., Yang, P., Yim, S. H., Zhao, X., Kasaikina, M. V., Stoletzki, N., Peng, C., Polak, P., Xiong, Z., Kiezun, A., Zhu, Y., Chen, Y., … Gladyshev, V. N. (2011). Genome sequencing reveals insights into physiology and longevity of the naked mole rat. Nature, 479(7372), 223–227.

Date Posted: May 27, 2025

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DNA Methylation Patterns Trace Blood Aging Dynamics

Scientists have created a new, highly effective method of tracing blood cells’ lineage. This can improve our understanding of clonal hematopoiesis and its impact on an aging organism [1].

Hostile takeover

In the human body, a relatively small pool of hematopoietic stem cells (HSCs) sustains a system that produces 100-200 billion mature blood cells each day. Tracing descendant cells back to their ancestral stem cells is key to understanding aging and some diseases. With age, some stem cells acquire traits, through mutations or other mechanisms, that give them a reproductive edge. Their progeny multiply faster and gradually take over the blood system.

Many of these dominant clones skew toward producing pro-inflammatory cells, which are often less immunocompetent. This process, called clonal hematopoiesis, may be an important contributor to chronic age-related inflammation (inflammaging) [2]. It has been linked to cancer, cardiovascular diseases, and increased mortality [3].

“Our blood stem cells compete for survival,” explained Dr. Lars Velten, Group Leader at the Center for Genomic Regulation (CRG) in Barcelona and co-corresponding author of this new study published in Nature. “In youth, this competition produces a rich, diverse ecosystem, while in old age, some drop out entirely. A few stem cells take over, and these work extra hard to compensate. This reduces diversity, which is bad for the blood system’s resilience. Diverse stem cells can respond to different stresses, so the dominance of a handful of clones makes the whole system more fragile.”

The new method

Current lineage-tracing methods, such as introducing artificial mutations that are inherited by cellular descendants, are time-consuming and have key limitations. They cannot be used in humans because they require genetic engineering, and they often fail to provide information about the cell’s functional state, such as when it has terminally differentiated. In model organisms, most clonal hematopoiesis experiments are done using transplantation, in which the animal’s blood system is wiped out by irradiation and artificially rebuilt so that researchers can observe clonal dynamics “from scratch.”

This creates the need for methods that rely on endogenous markers, such as naturally occurring mutations or epigenetic changes, and can perform high-throughput, single-cell analysis across large cell populations. The authors of this study propose using epigenetic changes, specifically somatic methylation patterns, as such a marker.

DNA methylation is the addition of a methyl group to a nucleotide in a DNA molecule. Multitudes of those markers create a unique epigenetic landscape that is inherited by the cell’s progeny. Crucially, the researchers showed that different methylation sites carry different types of information: some reflect a cell’s differentiation state, since methylation controls gene expression at various stages, while more static sites preserve inherited patterns that act as molecular tracers of clonal identity.

“Our cells carry genetic alterations which collectively make us unique individuals,” said Dr. Alejo Rodriguez-Fraticelli, co-corresponding author of the study and Group Leader at IRB Barcelona. “But we’re also a mosaic of epigenetic alterations. Groups of cells, even if they end up doing different jobs, carry shared methylation marks which tie them back to a common ancestor stem cell. We’ve been finally able to construct the epigenetic family tree by reading information written directly into the DNA of each cell.”

For this purpose, the researchers developed EPI-Clone, a high-throughput single-cell methylation analysis method. Their first test utilized HSCs that were labeled with traditional genetic barcodes and transplanted into irradiated mice. After five months, they profiled these cells with EPI-Clone. This method successfully reconstructed the known clonal structures, confirming that methylation patterns alone could trace lineages.

“DNA methylation works like a kind of binary code. At each position in the genome, a site is either methylated or not, like a 1 or a 0,” explained Dr. Michael Scherer, bioinformatician and co-first author of the study. “This simple on-off information can be transformed into a natural barcode. Five years ago, I wouldn’t have thought this possible at single-cell resolution, across tens of thousands of cells. It’s been a huge leap forward in technology.”

“After 60, it becomes almost inevitable”

Having validated the tool, the scientists turned to native, unmanipulated mouse hematopoiesis; this is a key step, since transplantation experiments impose artificial stress and regenerative demands that do not reflect normal aging. Analyzing young and old mice, they found that young bone marrow maintained a diverse clonal structure, with many small clones contributing to blood production. In contrast, old mice showed a shift toward oligoclonality, with a few expanded clones dominating the system.

Strikingly, some of the largest aged clones were filled with undifferentiated HSCs that appeared stuck in a self-renewing state, producing few mature progeny. The team transplanted aged bone marrow into new recipients and found that these dominant old clones engrafted poorly while smaller, non-expanded clones drove successful regeneration. This suggests a tradeoff: some clones gain a replicative edge at the price of reduced functional output, consistent with current understanding of clonal hematopoiesis and its harmful effects.

The researchers next applied EPI-Clone to human bone marrow samples from donors of different ages and observed a similar pattern: with age, larger clones begin to take over. “The change from diversity to dominance isn’t random but clock-like,” said Indranil Singh, co-first author of the study and a final-year PhD student at IRB Barcelona. “By age 50, you can already see it starting, and after 60, it becomes almost inevitable.”

While scientists have already identified several mutations that induce clonal hematopoiesis, EPI-Clone was able to detect both these known driver-driven expansions and large driver-negative clones, which are clonal expansions with no known genetic trigger. These novel clones shared features with known ones, such as a bias toward myeloid over lymphoid progeny. The findings suggest that age-driven clonal expansion is not just about known driver mutations in genes like DNMT3A or TET2 but is part of a broader, clock-like process of clonal selection and drift involving both genetic and non-genetic mechanisms.

“If we want to move beyond generic anti-aging treatments and into real precision medicine for aging, this is exactly the kind of tool we need,” says Dr. Velten. “We can’t fix what we can’t see and for the first time, EPI-Clone can facilitate this for humans.”

Yes I will donate❤️

Literature

[1] Scherer, M., Singh, I., Braun, M. M., Szu-Tu, C., Sanchez Sanchez, P., Lindenhofer, D., … & Velten, L. (2025). Clonal tracing with somatic epimutations reveals dynamics of blood ageing. Nature, 1-10.

[2] Winter, S., Götze, K. S., Hecker, J. S., Metzeler, K. H., Guezguez, B., Woods, K., … & Platzbecker, U. (2024). Clonal hematopoiesis and its impact on the aging osteo-hematopoietic niche. Leukemia, 38(5), 936-946.

[3] Zink, F., Stacey, S. N., Norddahl, G. L., Frigge, M. L., Magnusson, O. T., Jonsdottir, I., … & Stefansson, K. (2017). Clonal hematopoiesis, with and without candidate driver mutations, is common in the elderly. Blood, The Journal of the American Society of Hematology, 130(6), 742-752.

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The Blog

Building a Future Free of Age-Related Disease

Going after mutations

Looking for what’s actually there

More evidence from a different study

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It definitely sounds like you have a lot of reasons for entering this field and a lot of passion. Picking up on that point, Immortal Dragons is described as a purpose-driven fund focused on life extension, prioritizing impact over economic returns. How is this different from other funds?

How do you measure this? Is there a formal, codified investment thesis, where you quantify impact versus economic returns and weigh those things when you’re looking at an investment? Is it more of a feeling based on your due diligence, or are there specific impact metrics that you look at?

You’re saying that if you could succeed in having a few significant outliers, that will serve as a powerful signal to the world to say “Hey, we can actually get gains here”, and that would catalyze more funding.

Have you received any kind of challenges on that sort of thesis, by people saying “Hey, you should really be working on doing that sort of blanket minimum median raising as opposed to this”? Or, does everyone that you’ve interacted with understand the points that you’ve just made?

What are your thoughts on the current funding landscape in general? Instead of simply being an LP for other funds, why did you choose to do this yourself? What are the biggest gaps or unmet needs in the field that you hope Immortal Dragons will address?

Can you explain a little bit more about what that looks like operationally? Is there like a separate tranche of funding within the fund that’s allocated for grants, or is it like a separate granting mechanism that functions somehow alongside the primary fund?

Got it, and speaking of your website, I noticed that there’s you have a project focused on visualizing digital twins on the website. Is the aim of this type of work evangelism-related as well or purely scientific in nature?

If patients can see what a healthier version of themselves will look like if they comply with the specific therapy, that will induce them to be more compliant?

In the past, you’ve spoken about connecting Eastern and Western longevity communities. What do you see as the most significant benefits of East-West collaboration, and what practical steps is Immortal Dragons taking to bridge these ecosystems?

You’ve also noted in the past that Eastern cultures may be more conceptually open to life extension. How do you see such potential differences in cultural attitudes influencing things like regulatory environments, patient adoption, or investment trends in Asia versus the West?

You’ve expressed both enthusiasm and caution about AI’s role in longevity. What specific intersections between those two areas are you most excited about, and what do you think are the greatest risks?

On your LinkedIn, I noticed that you are a gamer and a dev, and your background is in computer science and being a tech entrepreneur. How do you think that background in other fields has shaped your approach to investing in longevity? Would you say this is a challenge, an advantage, or both?

What drives you personally for this mission? You mentioned earlier the various ways in which you’re passionate for this, but is there anything specific that you attribute this passion to? What’s your ‘why’?

Great. Thank you for sharing, Boyang, and thanks for joining us in this Lifespan interview.

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So, Rejuve.AI just launched its app. However, it’s touted as something bigger than just a health app, as a longevity research network. Please explain that to me.

I think it’s a bit of a chicken-and-egg situation with human data in longevity research and biology in general. Data is the key element. You want to entice people to give you their health data and then use it. How?

Like you said, even the types of data in biology are very diverse, so what are we after?

I bet a lot of people in our age group can relate to this analogy. When you say, “it does something,” what exactly do you mean?

It can generate hypotheses.

This fits into the concept of citizen science, which is rapidly gaining traction, really well. It’s hard to do right, for instance, due to lack of randomization, but even though, the benefits can be huge.

There’s been a lot of activity lately in the field of experiment automation. Are you planning to test your hypotheses in animal models?

The “Methuselah” flies.

This would be groundbreaking.

Decentralized AI. Do you think it can work?

It’s an interesting incentive mechanism. Can you tell me more about the idea of tokens and what you can buy with them?

This sounds exciting, but when I downloaded and logged into the app, honestly, it felt a bit like a commercial gimmick. I wonder whether you’re concerned that you’ve created a too commercial image for the app, with all these collaborations pushing products and services.

Your app offers an assessment of the user’s biological age, which means you’ve created a biological age clock. How was it done in terms of training and validation?

I think NHANES is about 15 thousand people, but it’s a lot of data points because they tested many things.

If we could just liberate the data, this in itself would be revolutionary. Ben, you’re a visionary. Do you have a timeline for how AI might help us solve aging?

I’ll take that.

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