Markers of inflammation have been associated with cardiovascular diseases and proposed as other cardiovascular risk factors. Recently, the role of the NLR family pyrin domain containing 3 protein (NLRP3) inflammasome has been studied in cardiovascular diseases. NLRP3 inflammasome is upregulated after myocardial infarction, atherosclerosis, ischemic heart disease, diabetic cardiomyopathy, chronic heart failure, and hypertension, and recently, NLRP3 and IL-1β have also been proposed as new cardiovascular risk biomarkers.

Previous studies have suggested a role for NLRP3 inflammasome in several events associated with aging. Genetic deletion of NLRP3 in mice has been shown to improve healthspan by attenuation of multiple age-related degenerative changes, such as glycemic control, bone loss, cognitive function, and motor performance. Furthermore, the deletion of NLRP3 in old mice increased muscle strength and endurance and prevented from age-related increase in the number of myopathic fibers. However, the role of the NLRP3 inflammasome in lifespan and cardiac aging has not been studied. Hence, we sought to determine whether or not genetic deletion of NLRP3 may have effect on lifespan and potentially prevent cardiac aging.

To evaluate the impact of NLRP3 deletion on survival and metabolic changes during aging, we followed NLRP3 deficient (NLRP3 -/-) and NLRP3 +/+ littermate control wild type (WT) mice throughout the entire lifespan. The survival of NLRP3 -/- mice compared to littermate controls was augmented with an increase in mean lifespan of 34% and in maximum lifespan of 29%, while body weights and food intake did not differ between the two groups during the entire observation period. Fasting blood glucose and circulating IGF-1 levels were reduced in young and old NLRP3-/- mice, indicating that the insulin sensitivity of these animals was considerably higher than sham controls during aging. Reduced levels of glucose and IGF-1 have been associated with stress resistance and an antiaging effect.

Heart weight normalized to body weight was increased in old mice in comparison with young mice, and heart weight was higher in WT in comparison with NLRP3-/-. Cardiac hypertrophy measured by the left ventricular wall thickness was significantly increased in elderly WT when compared to NLRP3-/- mice. From electron microscopic analysis, we corroborated that the numbers of accumulated autophagosomes were reduced in hearts from NLRP3-/- old mice. This could be explained by where NLRP3 inhibition induced improved autophagy quality in the heart during aging.

In a novel study comparing healthy cells from people in their 20s with cells from people in their 80s, researchers say they have documented that cell division rates appear to consistently and markedly slow down in humans at older ages. The researchers say the findings may help explain why cancer - long considered a disease of aging, with incidence highest among people over age 65 - has been found to decelerate in occurrence at the extreme end of human life. The findings, they say, also provide clues about cell biology that might eventually lead to a better understanding of cancer.

Cancer is spurred by an accumulation of genetic mutations caused by mistakes cells make when copying DNA during cell division. Research in the last several decades assumed that such mutations accumulate over time at a steady rate. However, when researchers reanalyzed old data in dozens of published papers, they found that mutations accumulate more slowly in old age. That analysis led researchers to suspect that cell division rates slow down markedly in old age, giving cells fewer chances to accumulate DNA mistakes.

To test this hypothesis, the team analyzed cell replication rates in samples of various healthy tissues collected during biopsies and other medical procedures from more than 300 patients in their 20s and in their 80s. Their findings showed that cell division rates slowed by about 40% in colon tissue samples collected from patients in their 80s compared with those in their 20s. Similarly, in samples of esophageal tissue, the division rate slowed by about 25% in the elderly compared with the younger patients. In the duodenum, at the beginning of the small intestine, the rate slowed by 26% in the elderly, and in posterior ethmoid sinonasal tissue, found near the nose, the rate slowed by 83% in the elderly.

When researchers performed a similar analysis of cell replication using tissue from young and old lab mice, they found no significant differences in the division rate - a considerable distinction between mice and humans that could make it more difficult to use aging mouse data as a proxy for aging humans.

A new evaluation of previously published data suggested to us that the accumulation of mutations might slow, rather than increase, as individuals age. To explain this unexpected finding, we hypothesized that normal stem cell division rates might decrease as we age. To test this hypothesis, we evaluated cell division rates in the epithelium of human colonic, duodenal, esophageal, and posterior ethmoid sinonasal tissues. In all four tissues, there was a significant decrease in cell division rates with age. In contrast, cell division rates did not decrease in the colon of aged mice, and only small decreases were observed in their small intestine or esophagus. These results have important implications for understanding the relationship between normal stem cells, aging, and cancer. Moreover, they provide a plausible explanation for the enigmatic age-dependent deceleration in cancer incidence in very old humans but not in mice.

Hello, everyone. Many of you may know me from Apollo Ventures. Now, from a month or two ago forward, I will be affiliated with Kronos BioVentures. The switch here is not one of particular substance; we had to change an organization, I wanted to do a lot more investments, and do much bigger investments. So we went from Apollo to his grandfather Kronos, when we changed the name.

I am speaking towards the end of this event, so if I were to come up here and talk to you about the aging space or even the investment considerations, it would be a lot of repetition from other presentations today. So I wanted to do something slightly different with my time today, and it is going to be a little data-heavy, and a little bit different. We're going to do three things, that I will call a perspective, a prospect, and an approach. I'll cover, number one, some ways of talking about aging in this longevity biotech space, that I think a lot of us aren't necessarily thinking about, or it isn't the first thing that I usually hear. Then I want to talk about the present situation in biotech venture capital, particularly biopharmaceutical VCs. Then I want to talk about my favorite strategy in this space, both for biopharma VCs and for the longevity biotech space, which is VC-partnered venture building. Which is more than half of what I do - that's my hammer that I'm striking every likely-looking nail with, and then building a VC-backed company around it.

To dive in I have just about a dozen slides which I think are interesting perspectives on the aging space. I'm going to talk here about demographic, economic, and human health problems. I'm not going to touch on social solutions, because I think we're all here for the medical solutions. My first slide: it is important to remember that modern demographics present a new problem. This longevity issue that we're facing is quite a new thing to come to the forefront of people's minds. We are only now entering the fourth stage of what is called the demographic transition - as we go from a situation which is the natural state of humans, where we have very high birth rates and very high death rates. We then evolve through this population explosion that happens in stage two, towards a more stable population distribute in which birth rates and death rates are relatively low. We're just entering that stage.

So this issue of having old people around in large numbers, dying of diseases like cancer and Alzheimer's, and having complications like type 2 diabetes and osteoporosis, is a relatively new situation. One hundred years ago, the three leading causes of death for humanity were influenza, tuberculosis, and pneumonia. Today they are dementias, cancer, and cardiovascular diseases. This is the key thing in understanding the "why now" of the longevity space - that we are in the midst of this demographic transition.

To illustrate this a bit more, here are some projections based on the UN numbers. My favorite statistic in looking at demography is the old-age dependency ratio. This is the number of people 65 and older divided by the number of people younger than 65, the working age adults 15-64. What you can see, both in the developed world and the undeveloped world, is that these ratios are rising dramatically over this century. In 1950 we're at about 12% in the developed world, and we're going to be almost 50% by the end of the century. That is a huge change.

The important thing to remember here is that as we get all of these older people in our society, our society is not set up to support these people. So we come up with this economic problem, which is that, already, in the middle of this graph, the middle of this demographic shift, in the developed world we already have a crisis of underfunded pension obligations as we make commitments to people who can't work in old age - because they are going to get sick. This right now, according to Citibank, is about 78 trillion worldwide in unfunded or underfunded pension liabilities. I think you can make a credible case that they only way to prevent this incredible number from getting even bigger, and causing even more social and economic calamity, is by making people live longer and healthier, so that they can contribute more to society, even in the latter stages of the demographic transition.

Next, from a human health perspective, many of you have seen variants of this graph, but I just wanted to do it with many more diseases, showing the incredible association of aging with all of the leading causes of death. This shows a normalized occurrence rate, so every year you have a chance of getting a heart attack, or getting cancer. So if you plot the chances of getting cancer this year, versus the highest chance you'll ever have in your life, what you'll see - for all of these diseases - is that the older you are, the higher your risk becomes. That is true for cardiovascular disease, Alzheimer's, Parkinson's, diabetes, and kidney disease.

Moving right along, one of the things that we don't talk enough about in the aging space, but is critically important to understand why we think the technologies that the longevity biotech world is developing will be so powerful, is the issue of multimorbidity. That is basically having more than one chronic condition at once that you have to deal with. What you can see here is that as people get older, as you move towards 75, by that age about 41% of all people have at least two chronic conditions - and many of them have more. Then that number goes up and up and up as you get older. So people aren't just dealing with their atherosclerosis, they are dealing with diabetes, with COPD, with senility, all at the same time. For that reason this great analysis, done by Dana Goldman and colleagues in 2013, shows that because there are all of these risks that come up together, if you just reduce risk and prevent one type of disease, let's say reducing cancer risk, or reducing heart disease risk, you get almost no extension in healthy life span. Almost none. Here 75 years is the base case, and 76 years is what you get just by reducing the risk of one type of disease. If, however, you reduce risk of all the age-related diseases together by a smaller amount, only then do you see a huge jump in life span.

So this was a little tour of some perspectives that I like when thinking about this space. The last one I'm going to leave you with before we jump to the more technical financing part is this graph of life expectancy in the US over time. These are the UN projections for average life expectancy over the next century. When I went back far enough in the data, these are really clear projections forward of the trend from about 1970, it is almost a straight line. But I think that what we are at the cusp of in in the development of technology around longevity biotech is much less like this period from 1970 to 2020, where we were just starting to understand what the diseases of aging were actually caused by, what molecular characteristics they have, and how to approach them. I think that our new situation is going to be much more like the period from 1910 to 1950, when we were actually conquering many of the infectious diseases that were the leading causes of death at that time. We spend perhaps 50 to 100 years characterizing the germ theory of disease and then developing tools like vaccines and antibiotics, and as a result saw a massive upswing in average life span. So my projection here is that as we conquer the diseases of aging we'll see a slope as new drugs come out that will be more similar to the earlier era in which we were conquering infectious diseases than in the later era when we were not making that much medical progress in treating aging.

Now on to the second part of the presentation. I'm going to show you six slides that will encapsulate what I think of biopharma VC space. We're all in this universe of the startup ecosystem in biotech, and I think that, especially as this little niche industry that hasn't launched many approved drugs, it is important to analyze what this bigger industry actually is, how it works, and what kind of success rates we should be expecting. I want to start with an overview of what the biopharma space is. These are companies that make drugs that go through clinical trials. That is most of what we do in the longevity space. There are a couple of interesting trends that have been happening in the biopharma space generally. The first is that the phase at which acquisitions are happening - most companies will ultimately get acquired by a pharmaceutical company, which will then run the latest stage trials and sell the drug - and those acquisitions have been happening earlier and earlier. You can see in the white line here, these are preclinical and phase I stage companies. Since 2013, the numbers of acquisitions of commercial and phase III stage companies have been going down.

So companies have been acquired earlier, but even though they are being acquired earlier, they are being acquired for larger amounts with less time spend in development of those companies. As an investor, these three facts are really exciting. It means that you are making larger returns, faster, and you have to do less work to get there. On the one hand that means this is a great time to be investing in biotech. On the other hand, it also makes investors worried.

Here is the second graph; most new drugs today come from biotech startups. This is a massive shift from what the world looked like twenty years ago. Twenty years ago you had the pharma companies that would either in-license stuff from academia, or they would do their own research and development to find drugs and approve those drugs. In 2017, 75% of all of the approved drugs came from biotech startups. Many of them were acquired and ultimately did the final trials with Big Pharma, but that is also a hugely defining factor. That means that the vehicle of choice for getting an approved drug is a biopharma startup.

Thirdly: drugs that come from startups do better in the clinic than drugs from Big Pharma. There is something that I find absolutely magical about the ability to take a very dedicated team of founder and founding scientist and throw them into a problem and say, alright, you guys need to get this thing to work. Your company, and everything that comes with it, many times reputation, many times validation of the scientific theory, all rides on getting this question right and answering this question in the right way. That pays off in the long term, because when drugs ultimately launch, it is almost twice as good for a drug to start in a biotech startup and be licensed to Big Pharma when compared to internal development in Big Pharma.

Fourth: total amounts of VC funding per round have been going up enormously in the last couple of years, particularly in 2017 and 2018 - I have the medians and the means graphed here. This chart shows average size per round, and you can see that in 2018 that series A and series B rounds for average biotech companies were around 30 million. That is a lot of funding. Seed rounds, however, are staying relatively small - 2-3 million is the normal there.

Fifth: IPO valuations have been going up and up and up for preclinical and phase I stage assets, but not for phase III. Before I get to my last piece, I want to close on this overview of where we are in the biotech investment space. You can draw two conclusions as you look at these five pieces of data. The first conclusion is that this is absolutely the time to be doing a biotech startup in innovative drug development. The second conclusion is that this looks a lot like a bubble. If you look at the macroeconomic situation, starting from where a lot of my data starts, from 2011 until now, the stock market has been riding high, we've been in this expansionary economy. So a lot of investors who are thinking about, today, where I want to commit my funds for a drug development program, they have to think about how is this market going to look three, four, five, ten years in the future. There are some worrying signs, for us, that we have to be taking this risk of a bubble in biotech very seriously.

One of the signs that is most apt is this graph. For those of you who don't know, 2018 was the biggest year ever for IPOs in biotech companies. There were over 60 IPOs. However, something a little bit disturbing came along with these IPOs. On this graph, each company is a bar, and the size of the bar indicates what percentage change their stock has had between their IPO in 2018 and the end of 2018. You can see that more than half of them declined - and a lot of them declined by a lot, in less than a year. What this means to me is that the public markets are really, really harsh on these early stage biotech companies. Because there is an exuberance, many companies are jumping into the public markets without having to show any more data. Now that they are subject to public scrutiny, by people who aren't trading on the potential of the company, but instead on what has the company done, they get hammered. This makes private investors, long term investors to fund clinical development that much more important. Potentially more important than it has ever been. It also means that investment going forward in the next five to six years is probably going to have to be more disciplined. I don't think that this IPO window, with high valuations and freely available funds, is going to last.

That leads me to five quick conclusions about the biotech VC space. Number one, avoid exuberance as much as possible. Number two, focus on seed investments, getting in really early, as round sizes are not increasing there. Getting in early and following things through, the timing and the amounts make a lot sense. Number three, don't plan for the IPO ecosystem to continue the way it has been. Number four, only exit when you have a clear value story, and you are confident that you can actually back away from the project. Don't just throw it out into the world and see how it goes. Number five, and this is important, there are some cautionary things here, but I think that, overall, the trend that we've been seeing in the biotech ecosystem will continue.

I didn't spent time on the data here, but the main reason that a lot of this boom has been so exaggerated is that Big Pharma research and development is changing fundamentally. Resources are going away from the Big Pharma companies doing research and development into biotech startups. That space that is being created, it isn't being filled fast enough. So even though there are a lot of resources going into it, and there is a lot of excitement, Big Pharma companies still desperately need their pipelines to be filled - and filled with good drugs. So this space will continue to grow, as this trend continues in moving to this more efficient method of creating drugs in biotech startup companies.

My last piece that I want to do, very quickly, is just a little bit on my approach to how to play in this world, and how I've been working with scientists and entrepreneurs to do this. This is a venture-led company building process, where I think that there are five key things that a company needs to do in order to pull together their story and become a real biotech company. Number one, you identify exceptional research, and in our case it is longevity research. Number two, you partner with the people who know the science intimately, and never do a company without the scientists that know what they're talking about. Work with the scientists that know the science, because when you run into trouble, and you will always run into trouble when doing basic research, they are the only ones who have run into the same thing ten times before, and know the answers to what is going on. It will slow down a company enormously if you don't have those guys.

Number three, biotech is a bit unique compared to the tech world in how different the different phases of a company are as it progresses through its value chain. The guy who knows how to get toxicology studies done and the guy who knows how to correctly do a phase III clinical trial and the guy who knows how to successfully sell a drug on the marketplace are completely different from the guy who knows how to make a basic discovery in fruit flies. So having a team that comes in at the appropriate time to lead this process at the right time for that company is a characteristic of the best biotech companies that I know. One of the reasons that I want to focus on this VC-led or this company building model, and why I think it works so well, is that you have people in the board of directors or who helped to create the company that exist somehow behind the operational team, and the operational team can be led by a different person, whoever is needed the most for that phase of the company. But the overall mission and vision and science of the company can be supported by the founders all the way through, which is a model I really love.

Number four, you have to design your key value creating experiments, like what is the killer experiment, without this there is nothing. Then do that experiment and fail fast if you are going to fail. Then number five, biotech development is very expensive. You need to have a path to 20 million or 30 million rounds to do clinical trials. If you don't think that you'll be able to raise that funding, then you need to have a partner on board early on who you think can.

Next slide, and I'm not going to spend a lot of time on this, in company building we do things in three phases. My favorite way of looking at building companies is in a hypothesis-led way. Whether you are an entrepreneur or a venture investor this, I think, should be the start: come up with a hypothesis. Then explore, validate the hypothesis, get the people on board, and then create the company. Then my last slide; it is easy to focus in on Silicon Valley and Boston as the two largest biotech hubs in the world. I think that doing so leaves so much on the table. Great basic research can be found everywhere in the world. There are fantastic institutions in Europe, in Southeast Asia, in the center of the United States that are underexplored. So a big part of what I do at Kronos is to look around at where that great research is done, and then move forward wherever it is, with a team that can actually accelerate it.

So anyway, that is a bit of my perspective on the longevity biotech space. Thank you for your attention; hopefully some of you found this useful information.

The blind mole rat (Spalax) is a wild, long-lived rodent that has evolved mechanisms to tolerate hypoxia and resist cancer. Previously, we demonstrated high DNA repair capacity and low DNA damage in Spalax fibroblasts following genotoxic stress compared with rats. Since the acquisition of senescence-associated secretory phenotype (SASP) is a consequence of persistent DNA damage, we investigated whether cellular senescence in Spalax is accompanied by an inflammatory response.

Spalax fibroblasts undergo replicative senescence and etoposide-induced senescence, evidenced by an increased activity of senescence-associated beta-galactosidase (SA-β-Gal), growth arrest, and overexpression of p21, p16, and p53 mRNAs. Yet, unlike mouse and human fibroblasts, senescent Spalax cells showed undetectable or decreased expression of the well-known SASP factors: interleukin-6 (IL6), IL8, IL1α, growth-related oncogene alpha (GROα), SerpinB2, and intercellular adhesion molecule (ICAM-1). Apparently, due to the efficient DNA repair in Spalax, senescent cells did not accumulate the DNA damage necessary for SASP activation.

Conversely, Spalax can maintain DNA integrity during replicative or moderate genotoxic stress and limit pro-inflammatory secretion. However, exposure to the conditioned medium of breast cancer cells MDA-MB-231 resulted in an increase in DNA damage, activation of the nuclear factor κB (NF-κB) through nuclear translocation, and expression of inflammatory mediators in RS Spalax cells. Evaluation of SASP in aging Spalax brain and intestine confirmed downregulation of inflammatory-related genes. These findings suggest a natural mechanism for alleviating the inflammatory response during cellular senescence and aging in Spalax, which can prevent age-related chronic inflammation supporting healthy aging and longevity.

Over time, cells in the body can be damaged by external exposures, like ultraviolet radiation from the sun, or internal ones like oxidative stress. On the skin this appears as wrinkles, dryness, or age spots. In the skin, changes occur so the outermost layer called the epidermis gets less nourishment, becomes thinner and is easier to breach. To understand this process on a cellular level, researchers began looking at different cell populations in skin to see if any cell type was associated with skin damage more so than another.

The team initially thought that one type of cell that is abundant in skin and divides often, called keratinocytes, would drive senescence. However they report that melanocytes, the cells which produce the pigment responsible for skin color, fit the senescence profile and released pro-inflammatory factors that could affect surrounding cells and induce skin aging. "Melanocytes divide very little throughout our life and constitute 5-10% of the cells in the basal layer of the epidermis. They showed a variety of molecular markers of cellular senescence in the aging skin. We found that melanocytes became senescent without telomere shortening, which is not surprising since they hardly divide. But melanocytes showed DNA damage specifically at telomere regions irrespectively of their length due to oxidative stress."

To confirm that melanocytes were really the driver of skin aging, the team built a 3D human epidermis in the lab, and found that melanocytes alone could induce several features of skin aging in the model. They also reported that the effect of the senescent melanocytes could be moderated by treating the model with the senolytic drug ABT-737 or by the mitochondrially targeted antioxidant MitoQ that protects mitochondria.

There is currently still no effective treatment for Alzheimer's disease. For many experts, this is largely due to the fact that the disease cannot be clinically diagnosed until long after the biological onset of disease when characteristic symptoms such as forgetfulness appear. However, the underlying brain damage may already be advanced and irreversible by this stage. "Everyone is now pinning their hopes on using new treatment approaches during this symptom-free early stage of disease to take preventive steps. In order to conduct studies to test these approaches, we need to identify people who have a particularly high risk of developing Alzheimer's disease."

In patients with Alzheimer's disease, misfolding of the amyloid-β protein may occur 15-20 years before the first clinical symptoms are observed. The misfolded proteins accumulate and form amyloid plaques in the brain. A new technique can determine whether amyloid proteins are misfolded in blood plasma, and researchers have demonstrated that misfolded amyloid-β in the blood correlates with plaque formation in the brain.

Researchers reexamined blood samples collected as part of the ESTHER cohort study, looking at 150 ESTHER participants in whom dementia was subsequently diagnosed during the 14-year follow-up period. These samples were compared with those of 620 randomly selected control participants not known to have been diagnosed with dementia who correlated with the dementia participants in terms of age, sex, and level of education. Participants with amyloid-β misfolding had a 23-fold increased odds of Alzheimer's disease diagnosis within 14 years. In patients with other types of dementia, such as those caused by reduced blood supply to the brain, the study did not demonstrate an increased risk, supporting Alzheimer's disease specificity.

In higher organisms, cells age and die by natural processes. What are the molecular mechanisms that drive it? It has been difficult to disentangle causes from effects because aging impacts most cellular biomolecules. Oxidative damage is known to play a key role. Much of what is known about cellular aging comes from "bottom-up" experiments, by perturbing a few genes at a time - by knockouts, knock-ins, or point mutations, or by gene-to-gene comparisons using sequence databases. Our interest here is in the "top-down" question of the aging mechanism, which we take to be a more system-wide failure in the cell. Any single gene cannot reverse aging or abolish life span limits. Oxidative damage is indiscriminate and nonspecific in which class of biomolecule it hits or its spatial location in the cell. We take the mechanism of aging and longevity to be more about a general and stochastic destruction than a pinpoint action.

One view is that aging results from declining protein quality-control systems involved in protein synthesis, degradation, and chaperoning that normally protect the proteins in the cell's proteome. Central to proteostasis, the decline in protein quality control is implicated in more than 50 diseases of abnormal protein deposition (proteinopathies), for which the principal risk factor is advancing age, probably because cell regulation and protein production and disposal becomes increasingly compromised with age. Proteostasis is a natural culprit in aging because it is a front line of response to stress and because proteins are the primary repairers of the cell and sustainers of the genome.

Here, we model how proteostasis - i.e., the folding, chaperoning, and maintenance of protein function -ncollapses with age from slowed translation and cumulative oxidative damage. Irreparably damaged proteins accumulate with age, increasingly distracting the chaperones from folding the healthy proteins the cell needs. The tipping point to death occurs when replenishing good proteins no longer keeps up with depletion from misfolding, aggregation, and damage. The model agrees with experiments in the worm Caenorhabditis elegans that show the following: Life span shortens nonlinearly with increased temperature or added oxidant concentration, and life span increases in mutants having more chaperones or proteasomes. It predicts observed increases in cellular oxidative damage with age and provides a mechanism for the Gompertz-like rise in mortality observed in humans and other organisms. Overall, the model shows how the instability of proteins sets the rate at which damage accumulates with age and upends a cell's normal proteostasis balance.

In addition to driving contraction of skeletal muscles, acetylcholine (ACh) acts as an anti-synaptogenic agent at neuromuscular junctions (NMJs). Previous studies suggest that aging is accompanied by increases in cholinergic activity at the NMJ, which may play a role in neuromuscular degeneration. In this study, we hypothesized that moderately and chronically reducing ACh could attenuate the deleterious effects of aging on NMJs and skeletal muscles. To test this hypothesis, we analyzed NMJs and muscle fibers from heterozygous transgenic mice with reduced expression of the vesicular ACh transporter (VAChT), VKDHet mice, which present with approximately 30% less synaptic ACh compared to control mice.

Because ACh is constitutively decreased in VKDHet, we first analyzed developing NMJs and muscle fibers. We found no obvious morphological or molecular differences between NMJs and muscle fibers of VKDHet and control mice during development. In contrast, we found that moderately reducing ACh has various effects on adult NMJs and muscle fibers. VKDHet mice have significantly larger NMJs and muscle fibers compared to age-matched control mice. They also present with reduced expression of the pro-atrophy gene, Foxo1, and have more satellite cells in skeletal muscles. These molecular and cellular features may partially explain the increased size of NMJs and muscle fibers. Thus, moderately reducing ACh may be a therapeutic strategy to prevent the loss of skeletal muscle mass that occurs with advancing age.

Quercetin (Que) is a natural bioflavonoid. Que (50 mg/kg) in combination with dasatinib (5 mg/kg) (abbreviated as D + Q) has been shown to effectively eliminate senescent cells via induction of apoptosis, thus alleviating senescence-related phenotypes and improving physical function and lifespan in mice. We recently identified Que as a geroprotective agent that counteracts accelerated and natural aging of human mesenchymal stem cells (hMSCs) at a concentration of as low as 100 nmol/L, which is 100 times lower than the concentration of Que (10 μmol/L) previously used in combination with dasatinib.

To explore the geroprotective effect of low-dose Que in rodents, we evaluated the in vivo effect of long-term low-dose Que administration under physiological-aging condition. Que was given to 14-month-old C57BL/6J male mice by weekly oral gavage at a concentration of 0.125 mg/kg body weight, which is 80-400 times lower than that of the previously tested D + Q (10-50 mg/kg body weight) regimens. After eight months of treatment, Que-treated mice showed decreased hair loss with normal food intake, body weight, blood glucose and bone mineral density. Compared to control mice, mice subjected to Que treatment showed markedly improved exercise endurance. However, the lifespan was not prolonged by low-dose Que treatment observed up to the age of 31 months. Taken together, these data indicate that long-term low-dose Que administration alone sufficiently improves multiple aspects of healthspan, but not lifespan, in mice.

To investigate how Que improved healthspan in mice, we collected 11 different kinds of tissues from 10-week young male mice (Y-Ctrl) and control (O-Veh) and low-dose Que-treated 22-month old male mice (O-Que). Given that exercise endurance and diastolic function were improved by Que, we particularly examined the changes in skeletal muscles (SKM), white adipose tissues (WAT), brown adipose tissues (BAT) and hearts. Upon Que treatment, the arrangement of muscle fibers became more regular and compact with less fibrosis and senescence. In WAT, the increases in adipocyte size and senescence-associated β-galactosidase (SA-β-Gal)-positive area during aging were both alleviated upon Que treatment.

We previously observed that Que alleviates hMSC senescence in part through the restoration of heterochromatin architecture in prematurely and physiologically aging hMSCs. Constitutive heterochromatins are predominantly comprised of repetitive elements (REs), including retrotransposable elements (RTEs). The expression of RTEs is repressed via epigenetic regulation under normal conditions but is elevated during physiological aging, eliciting active transposition. Accordingly, mobilization of RTEs is likely to be a key contributor to tissue aging innate immune responseand cell degeneration. To test whether Que treatment may also repress activation of RTEs in a mouse in vivo model, we compared the transcriptional levels of RTEs in multiple tissues of Y-Ctrl, O-Veh, and O-Que mice. Consistently, most RTEs were transcriptionally upregulated in the SKM and BAT of old mice compared to those of young mice and were repressed by Que treatment.

In senescent cells, the activation of RTEs leads to genome instability, which subsequently promotes senescence-associated secretory phenotype (SASP). Consistently, the inflammatory cytokine IL-6 was increased in old mice compared to young mice and Que antagonized the increase of IL-6 in both hMSCs and old mouse SKM and BAT. Thus, our data suggest that Que may block SASP through the axis of heterochromatin-RTEs-innate immune response pathway. Our data provide important evidence supporting the role of low-dose Que in safeguarding genomic stability (i.e. inhibition of retrotransposition), which at least in part contributes to its geroprotective activity in rodents.

Cellular senescence may contribute to aging and age-related diseases and senolytic drugs that selectively kill senescent cells may delay aging and promote healthspan. More recently, several categories of senolytics have been established, namely HSP90 inhibitors, Bcl-2 family inhibitors and natural compounds such as quercetin and fisetin. However, senolytic and senostatic potential of nanoparticles and surface-modified nanoparticles has never been addressed.

In the present study, quercetin surface functionalized Fe3O4 nanoparticles (MNPQ) were synthesized and their senolytic and senostatic activity was evaluated during oxidative stress-induced senescence in human fibroblasts in vitro. MNPQ promoted AMPK activity that was accompanied by non-apoptotic cell death and decreased number of stress-induced senescent cells (senolytic action) and the suppression of senescence-associated proinflammatory response (decreased levels of secreted IL-8 and IFN-β, senostatic action). In summary, we have shown for the first time that MNPQ may be considered as promising candidates for senolytic- and senostatic-based anti-aging therapies.

Multicellular life requires individual cells to cooperate in a way that benefits the organism. Cells that are uncooperative because they are damaged or dysfunctional, and that pose a threat, are either eliminated by cell death or undergo a usually irreversible growth arrest called senescence. Senescent cells typically never divide (although there are some rare examples of cells exiting senescence and resuming division), but they can persist in tissues and contribute to ageing and cancer progression.

Senescent cells are metabolically active6, and this is characterized by their secretion of proinflammatory molecules as part of a phenomenon termed the senescence-associated secretory phenotype (SASP) response. Senescent cells can promote cancer progression and resistance to anticancer therapy in some contexts, as a result of the secretion, through SASP, of growth factors and immune-signalling molecules called cytokines.

Chemotherapy that damages the DNA of cancer cells can result in their death or their entry into senescence. Researchers investigated the effects of chemotherapy-driven senescence in breast cancer cells in mice. Under the microscope, they saw senescent cells eating and digesting entire neighbouring cells. This striking observation was made in breast tumours formed of mixtures of transplanted cancer cells, which were engineered to express red or green fluorescent proteins. It can be difficult to observe a cell being internalized by another cell in cancer tissues. By growing tumours with mixtures of fluorescently labelled cells, the authors could clearly identify red- or green-labelled cells being taken up into neighbouring cells labelled by the other colour.

Ingested cells are broken down in a digestive organelle called the lysosome. Crucially, senescent cells that ate their neighbours survived longer in vitro than those that did not. This finding suggests that metabolic building blocks retrieved from the lysosomal digestion of neighbouring cells were being used by senescent cells to promote their survival. The authors tested chemotherapy-induced senescent cells of other types of cancer, including lung cancer and a bone cancer called osteosarcoma, and found that these cells also cannibalize neighbouring cells. Together, these findings suggest that cell cannibalism might be an activity that is broadly associated with the induction of senescence, rather than being linked to particular types of cancer or to the status of proteins such as p53.

Mice live longer and are healthier in old age if they are given 40 percent less to eat after reaching adulthood than animals who are allowed to eat as much as they want. The dieting mice are fed with food enriched with vitamins and minerals to prevent malnutrition. But if food intake is first reduced in mice first start eating less food when they are already seniors, the researchers observe little or no effect on the life expectancy of the mice. On the other hand, when mice are allowed to eat as much as they like after a period of reduced food intake, they have no long-term protection, so reduced food intake has to be sustained for mice to reap the benefits. Reduced food intake must therefore be implemented early and be sustained until the end of their lives to have positive effects on health in old age.

But why do older mice no longer react to the change in diet? Researchers investigated gene activity in different organs. While the gene activity in the liver quickly adapted when mice are transferred to a restricted diet, the scientists observed a 'memory effect' in the fat tissue of older animals. Although the mice lose weight, the activity of the genes in the fat tissue is similar to that of the mice that continue to eat as much as they want. In addition, the fat composition in old mice does not change as much as in young mice.

This memory effect mainly affects mitochondria, the cells' power houses, which play an important role in the ageing process. Usually, reduced food intake leads to increased formation of mitochondria in fatty tissue. But the study showed that this is no longer the case when older mice are switched to a lower calorie diet. This inability to change at the genetic and metabolic levels may contribute to the shortened lifespan of these animals.

Tissue accumulation of p16INK4a-positive senescent cells is associated with age-related disorders, such as osteoarthritis (OA). These cell-cycle arrested cells affect tissue function through a specific secretory phenotype. The links between OA onset and senescence remain poorly described. Using experimental OA protocol and transgenic mice, we found that the senescence-driving p16INK4a is a marker of the disease, expressed by the synovial tissue, but is also an actor: its somatic deletion partially protects against cartilage degeneration.

We test whether by becoming senescent, the mesenchymal stromal/stem cells (MSCs), found in the synovial tissue and sub-chondral bone marrow, can contribute to OA development. We established an in vitro p16INK4a-positive senescence model on human MSCs. Upon senescence induction, their intrinsic stem cell properties are altered. When co-cultured with OA chondrocytes, senescent MSC show also an impairment favoring tissue degeneration.

To evaluate in vivo the effects of p16INK4a-senescent MSC on healthy cartilage, we rely on the SAMP8 mouse model of accelerated senescence that develops spontaneous OA. MSCs isolated from these mice expressed p16INK4a. Intra-articular injection in 2-month-old C57BL/6JRj male mice of SAMP8-derived MSCs was sufficient to induce articular cartilage breakdown. Our findings reveal that senescent p16INK4a-positive MSCs contribute to joint alteration.

Histopathological features of Alzheimer's disease (AD) are extracellular amyloid-β (Aβ) plaques and intracellular aggregation of hyperphosphorylated tau protein in a form of neurofibrillary tangles (NFTs). The disease is also characterized by loss of neurons and synapses and elevated levels of inflammatory factors. Neuroinflammation occurs in many neurodegenerative diseases, including AD. Several studies confirmed elevated levels of pro-inflammatory cytokines and stronger microglial activation during disease progression. Activated microglia have been found near NFT-bearing neurons. There is also a better correlation between numbers of activated microglia and NFT than between microglial cells' activation and amyloid plaques distribution.

Uncontrolled microglial response in the brain contributes to the progression of many neurodegenerative diseases and several lines of evidence suggest that inflammation may even precede the development of tau pathology in AD. Exosomes could be an important link between tau propagation and microglial activation. Reduction of microglial cells number and exosome synthesis inhibition reduces tau propagation. Further, phagocytosed tau seeds induce inflammasome activation inside microglia causing an overactive microglia state. That could be one of the mechanisms that promote the constant inflammatory response in AD.