Fight Aging!

Any sufficiently complex set of biological data assessed in a large population of various ages can be used as a basis to create an aging clock. Machine learning techniques are used to find algorithmic combinations of measurements that map to chronological age or observed mortality risk within the reference population. That algorithm then predicts age or mortality risk when used in people outside the reference population; where a person's predicted age is higher than chronological age this is thought to represent a higher burden of damage and dysfunction, and thus a greater biological age. Aging clocks have been show to work pretty well at a population level, but it remains difficult to establish how the measured parameters are determined by mechanisms of aging, and whether a clock assessment is of any practical use for one individual in the health and medical contexts.

Nonetheless, researchers are creating new clocks at a fair pace. Most omics based clocks use immune cells from a blood sample, and there has been some discussion over the years as to how relevant this is to aging in other tissues. Another point of interest has been how to separate variations in immune function that arise from stress, infection, and other transient causes from those arising from mechanisms of aging. With this background context in mind, today's open access paper reports on the use of a single cell assessment of chromatin accessibility in many different immune cell subtypes. Chromatin is structured nuclear DNA, with different sections either spooled and compact to prevent gene expression, or unspooled and accessible for gene expression. This structure is controlled by epigenetic decorations, and determines the behavior of the cell by determining which proteins are manufactured.

sc-ChromAging: A Single-Cell Chromatin Accessibility-based Clock Decodes Cell-Type-Specific Epigenetic Aging Trajectories

The aging process in humans constitutes a complex progression that exerts widespread effects across various organ systems, with the immune system displaying particularly significant dysregulation. This deterioration of immune integrity, often termed immunosenescence, is intrinsically linked to an attenuated capacity for tissue regeneration, a heightened vulnerability to infectious diseases, and the disruption of systemic homeostasis, all of which facilitate the pathogenesis of age-associated morbidities. While chronological age serves as a rough proxy for these changes, it often fails to capture the substantial heterogeneity in health trajectories among individuals. Consequently, the quantification of biological age through molecular biomarkers has emerged as a pivotal strategy to assess aging status and predict health outcomes. Among the hallmarks of aging, epigenetic remodeling is considered a primary driver of the aging process.

The concept of an epigenetic clock was pioneered using DNA methylation data. However, the majority of existing DNA methylation clocks rely on bulk tissue profiles, which makes it difficult to discern whether observed changes arise from alterations within specific cells. Chromatin accessibility, measured by single-cell assay for transposase-accessible chromatin-sequencing (scATAC-seq), reflects the regulatory potential of the genome. As an upstream layer, chromatin state provides unique mechanistic insights into how the aging process rewires the regulatory network of immune cells, yet high-resolution clocks based on scATAC-seq remain unexplored.

To decode the epigenetic heterogeneity of immune aging, the cell-type-specific chromatin accessibility aging clock sc-ChromAging were constructed using a high-quality scATAC-seq dataset derived from the Chinese Immune Multi-Omics Atlas (CIMA) cohort. The predictive performance of sc-ChromAging was evaluated across five major immune cell types. Significant heterogeneity in predictive performance was observed, and the CD4+ T cells exhibited the highest predictive accuracy. To further investigate the epigenetic signatures of aging at higher granularity, the analysis was extended to 25 immune cell subtypes. Consistent with the lineage-level findings, subtypes within the T cells displayed higher predictive accuracy. Notably, CD4+ naïve T cells showed the highest accuracy among subtypes.

The relatively high predictive accuracy observed in CD4+ naïve T cells suggested that their chromatin landscape may effectively reflect the biological aging process. Mechanistically, this high precision may be related to the intrinsic program of thymic involution. Unlike memory or effector subsets whose epigenomes are mainly remodeled by antigen exposure, naïve T cells may maintain a relatively quiescent state where chromatin accessibility changes are driven primarily by the intrinsic aging program. Notably, although CD8+ naïve T cells also showed relatively good predictive performance, their accuracy remained lower than that of CD4+ naïve T cells. This distinction suggests that a quiescent phenotype alone does not necessarily confer the same degree of age predictability across naïve T-cell compartments. One possible explanation is that the chromatin state of CD8+ naïve T cells may be more susceptible to extrinsic regulatory influences associated with their survival and maintenance, including cytokine-dependent homeostatic signals and other environmental stimuli.

Alongside calorie restriction, exercise represents the gold standard of proof for an intervention to slow degenerative aging. Sadly the research community has demonstrated all too few approaches that can robustly improve on exercise and physical fitness in the matter of aging, and none of those yet have compelling human data to support the extensive animal studies. Rapamycin and senolytics spring to mind as those with the greatest amount of data. Partial epigenetic reprogramming is also interesting but still too new to have gathered a very large body of animal work, despite the vast funding devoted to it in recent years. Thus pharmacological mimicry of the response to exercise continues to interest researchers, and programs in this part of the field continue to emerge.

Global declines in physical activity have contributed to an acceleration in immune aging, characterized by systemic inflammation (inflammaging) and impaired immune regulation (immunosenescence). This narrative review provides an overview of the evidence in both preclinical and clinical models supporting exercise as a critical intervention to counteract immune aging and its related diseases.

Regular physical activity modulates systemic inflammation, reduces neutrophil extracellular trap (NET) formation, and promotes favorable shifts in immune cell populations, including T cell and natural killer (NK) cell subsets. Exercise interventions have been associated not only with maintaining immune health but also in mitigating autoimmune disease progression, improving metabolic regulation, enhancing tumor immune surveillance, and reducing neuroinflammation. Emerging studies highlight the role of exercise in promoting vascular normalization within the tumor microenvironment, alleviating tumor hypoxia and acidosis, and restoring T and NK cell function.

In the elderly, appropriately prescribed multimodal exercise regimens may lower infection risk without clear evidence of immunodepression, supporting exercise as a potentially safe and effective strategy for immune rejuvenation. Furthermore, novel mechanistic insights, including the modulation of NET burden, IGF-1 signaling, kynurenine metabolism, and microbiome composition, suggest that exercise influences key biological pathways underlying age-related immune decline. While exercise offers broad clinical benefits, future research should prioritize mechanistic studies to optimize exercise prescriptions and inform the development of exercise-mimetic therapeutics.

Link: https://doi.org/10.3389/fragi.2026.1832962

The functional connectome is a map of connections between brain regions, produced via MRI imaging. Features tend to be fairly distinct from individual to individual, and change over time. Researchers here show that the functional connectome can be used to predict handgrip strength in patients exhibiting age-related frailty, which is quite interesting. One tends to think of loss of hand strength as emerging from degeneration of local musculature and local neuromuscular junctions. The results suggests that there is a component of physical frailty localized in the brain, though it is also possible that this reflects downstream issues resulting from the underlying mechanisms of aging occurring distinctly in both locations.

Physical frailty, which refers to a decline in physical strength and energy, is prevalent in older adults and has been attributed to impaired cognitive function and adverse health outcomes. The strength of a contraction on a handgrip, known as isometric handgrip strength, has been used as a marker of physical frailty. While handgrip strength can partially be explained by muscle properties (e.g., cross-sectional area and architecture), it may also be influenced by neural adaptations, such as intermuscular and intramuscular coordination.

There is a growing use of imaging-derived data from different modalities to predict clinical phenotypes and disease risk. In this context, handgrip strength has been attributed to resting-state functional connectivity within motor and salience networks. For example, within healthy older adults, researchers found that higher functional connectivity of the motor cortex to putamen, insula, and cerebellum was associated with higher handgrip strength. Another study investigated whole-brain functional connectivity (i.e., connectome) and observed that higher handgrip strength was associated with greater functional segregation of the salience ventral attention network in older adults at rest.

Because the connectome is unique for each person, akin to a "brain fingerprint", it may also serve as a personalized marker that can be used to predict their individual behavioral measures. A predictive model can be developed using connectomes from tasks involving motor components. Such tasks shift the brain into a more alert, motor-relevant state, offering greater sensitivity to motor-related conditions like frailty compared to resting-state connectivity. In this study, we focused on healthy older adults and had them perform two perceptual discrimination tasks on two different functional MRI sessions, both of which involved a non-dominant handgrip manipulation. We aimed to test the identifiability of the task-based connectomes across the sessions and identify the key functional connections (FCs).

We measured participants' maximum isometric voluntary contraction (MVIC) of their non-dominant hand as an indicator of frailty and neuromuscular health. We identified FCs predictive of MVIC, which may partly explain motor-related impairments in frail older adults. Finding such brain-based biomarkers for grip strength could identify potential target sites for motor rehabilitation programs.

Link: https://doi.org/10.3389/fnins.2025.1697908

Klotho is one of the few robustly longevity-associated genes. The effects of increased klotho expression on life span in mice that are arguably large enough to be interesting even if one prefers more of a focus on damage repair in the treatment of aging. A number of companies are developing therapies based on either the delivery of klotho fragments shown to improve function in aged animals, or using gene therapies to promote klotho expression and secretion. While klotho is important in the aging kidney, it is the ability of circulating klotho to promote function in the aging brain that has attracted greater interest, perhaps in large part because the biochemistry of its influence on the brain is less well understood.

Brain aging is accompanied by progressive disturbances in calcium signaling, mitochondrial function, redox balance, neuroimmune regulation, and barrier-fluid homeostasis, collectively increasing susceptibility to neurodegenerative diseases. Therefore, identifying physiological regulators that stabilize these interconnected processes is central to understanding brain aging. Klotho, an antiaging protein initially characterized by its systemic roles in mineral metabolism and lifespan regulation, has emerged as a key modulator of cellular and tissue homeostasis across multiple organs, including the central nervous system.

In the brain, Klotho is predominantly expressed in the choroid plexus and selectively in neuronal and oligodendroglial populations, positioning it at the interface of barrier physiology and neural function. Experimental studies have indicated that Klotho contributes to cerebrospinal fluid homeostasis, synaptic plasticity, neurogenesis, myelination, and resistance to metabolic and oxidative stress. Rather than acting through disease-specific pathways, Klotho stabilizes the core physiological axes that govern neuronal resilience, including Ca2+ signaling, mitochondrial-redox homeostasis, neuroimmune balance, growth factor signaling, and barrier integrity. Consistent with these physiological roles, reduced Klotho availability is associated with cognitive decline and multiple neurodegenerative disorders.

This review positions Klotho as a central determinant of cognitive reserve and neuro-resilience, providing a unifying physiological framework that links systemic homeostasis to brain aging and explains how disruption of Klotho signaling amplifies vulnerability to neurodegenerative disease, whereas its preservation supports lifelong brain integrity.

Link: https://doi.org/10.4196/kjpp.26.015

Senescent cells accumulate with age, a situation that appears more a result of the aging immune system failing to achieve timely clearance of newly senescent cells rather than a significant increase in the pace at which cells become senescent. Senescence occurs in response to cellular damage and stress, but also when somatic cells reach the Hayflick limit on replication. A senescent cell becomes larger, ceases replication, and devotes its energies to the secretion of pro-growth, pro-inflammatory signals. In the short term and in youth this is usually beneficial, helping to coordinate tissue maintenance, regeneration, and suppression of potentially cancerous cells. When sustained for the long term, the signaling of senescent cells is disruptive to tissue structure and function, however, contributing to the damaging chronic inflammation of aging.

In principle, clearing out lingering senescent cells should improve the ability of other classes of rejuvenation therapy to produce benefits. This is particularly thought to be case for stem cell and exosome therapies that rely upon generating favorable signals to improve the behavior of a patient's cells, thereby dampening chronic inflammation and hopefully enhancing regeneration and tissue maintenance. Senescent cells and signaling therapies stand in opposition, and it makes sense that a reduced burden of senescent cells should improve outcomes for signaling therapies.

This has to be tested, of course. Today's open access paper reports on the results from one example of this sort of study. Unfortunately the researchers involved chose to employ accelerated aging mouse models rather than naturally aged mice, so one can't take the results entirely at face value. Still, it is supportive of the consensus view on the opposition between senescent cells and signaling therapies. Interestingly, the researchers used a senolytic vaccine rather than a small molecule; you might recall an earlier study that employed this specific vaccine to slow cancer progression in mice.

Synergistic senolytic-regenerative therapy significantly extends healthspan and lifespan

Regenerative medicine, particularly through stem cell-based therapies, holds immense potential for treating chronic diseases and mitigating the effects of aging by restoring tissue function and homeostasis. Mesenchymal stem cells (MSCs), have been extensively investigated for their paracrine effects, immunomodulatory properties, and capacity to promote tissue repair via secretion of growth factors. Personalized MSC (pMSC) are a type of autologous stem cells developed by Immorta Bio which can be produced in an "age-specific" manner by controlling the extent of differentiation during generation from pluripotent stem cells. MSC are attractive from an anti-aging perspective because of the studies showing young MSC can suppress and in some cases even inhibit characteristics of aging.

Despite promising preclinical outcomes, and one FDA approval for an orphan disease, clinical translation of MSC therapeutics remains limited, with many trials demonstrating modest efficacy in conditions characterized by fibrosis, inflammation, and organ failure. A key barrier to successful regeneration is the accumulation of senescent cells, a hallmark of aging and chronic pathology that actively impedes stem cell function. Senescent cells, induced by stressors such as oxidative damage, telomere attrition, or chemotherapeutic agents, enter a state of irreversible cell cycle arrest and secrete a constellation of pro-inflammatory cytokines, chemokines, and matrix-degrading proteins collectively known as the senescence-associated secretory phenotype (SASP). SASP components not only perpetuate local inflammation but also directly antagonize regenerative processes by inhibiting stem cell proliferation, differentiation, and survival.

Experimental models of organ failure and accelerated aging, including carbon tetrachloride (CCl4)-induced hepatotoxicity and doxorubicin chemotherapy, reliably recapitulate this senescent environment, manifesting as increased aging markers and impaired physical capacity alongside biochemical evidence of tissue damage. Here, we investigate the hypothesis that senescent cells and their SASP directly impair pMSC-mediated regeneration in models of liver failure and accelerated aging. Using SenoVax, a novel senolytic immunotherapy, in combination with pMSCs, we evaluate synergistic effects on biochemical markers of liver function, aging and regenerative biomarkers, survival, and physical fitness attributes of aging. Combined senolytic and pMSC therapy outperformed monotherapies and produced clear synergistic benefits, including significant biochemical improvement of liver failure parameters, reversal of accelerated aging features, and restoration of regenerative signaling pathways. These findings support the concept that clearance of senescent cells can act as a critical adjuvant to regenerative therapies for chronic disease and aging.

Producing new aging clocks is easier than overcoming the hurdles to the practical use of existing aging clocks, so the research community is generating new clocks at a fair pace while failing to make much concrete progress on the challenging problem of how to use clocks to assess novel potential rejuvenation therapies. An aging clock measures some combination of parameters that at least appears to reflect biological age. Given that clocks are reverse engineered from epidemiological data via machine learning techniques and the research community has not established clear links between biological age and any of the specific parameters used in a clock, it is entirely unclear as to whether any given clock will accurately reflect the outcome of an actual rejuvenation therapy. Will it understate or overstate the effects of repairing some form of cell and tissue damage? Will its predictions regarding mortality risk turn out to be correct? They only way to find out at present is qualify a specific clock for a specific intervention via the slow and expensive life span studies that everyone wants to avoid. Some way to fix this present situation is needed, and building more clocks seems unlikely to achieve that goal.

Accurate quantification of biological age is essential for early risk stratification and intervention of chronic diseases. Here, we present StackAge, an ensemble-based biological aging clock that integrates large-scale plasma proteomic and metabolomic profiles from 30,376 participants in the UK Biobank. StackAge demonstrated high accuracy in age prediction (Pearson r ≈ 0.93 with chronological age) and substantially enhanced risk prediction for 12 chronic diseases, achieving area under the curve (AUC) exceeding 0.90 for type 2 diabetes, Alzheimer's disease, and chronic kidney disease. Notably, the incorporation of estimated aging rates consistently improved disease prediction beyond conventional omics and demographic features.

Feature interpretation and pathway enrichment analyses revealed that aging-associated biomarkers were enriched in inflammation, metabolic stress, and extracellular matrix remodeling pathways. Mediation analysis further indicated that modifiable lifestyle factors may accelerate biological aging, thereby increasing susceptibility to cardiovascular, neurological, immune, and musculoskeletal disorders. Together, these findings establish a robust multi-omics framework for quantifying individual aging trajectories and highlight biological age as a clinically actionable indicator for precision prevention and health management of age-related diseases.

Link: https://doi.org/10.1093/bib/bbag271

Adjusting the operation of metabolism to modestly slow aging has long formed the bulk of fundamental research into intervention in aging. All living organisms exhibit some plasticity of life span when subject to mild stresses, such as lack of nutrients, heat, cold, and so forth. Unfortunately this strategy seems unlikely to lead to therapies that greatly improve upon the effects of exercise and lifestyle choice, particularly given the evidence for metabolic adjustment to produce ever smaller gains in longevity as species life span increases. Nonetheless, this form of research persists, driven by the scientific urge to obtain complete understanding of the way in which aging progresses in detail. Here, for example, researchers provide evidence for there to be multiple options for the adjustment of metabolism to slow aging, not just one path.

While aging is the greatest risk factor for the development of neurodegenerative disease, the role of aging in these diseases is poorly understood. Our previous work has shown that targeting aging pathways can be neuroprotective in animal models of neurodegenerative disease. Based on these findings, we believe that by gaining insight into the aging process, that knowledge can be applied to identify novel therapeutic targets for neurodegenerative disease. To advance our understanding of aging, we used a genomics approach to identify genes regulated by multiple lifespan-extending pathways. We performed RNA sequencing on nine long-lived C. elegans mutants representing seven longevity pathways: insulin/IGF-1 signaling, dietary restriction, germline deficiency, impaired chemosensation, reduced translation, elevated mitochondrial reactive oxygen species (ROS), and mild mitochondrial impairment.

We found that most pairs of long-lived mutants exhibited a significant overlap in differentially expressed genes. Comparing gene expression across the entire panel of long-lived mutants revealed three distinct longevity groups that could be clearly distinguished by gene expression. Interestingly, two of these groups showed modulation of specific genetic pathways in opposite directions, suggesting that there are multiple alternative strategies to achieving long life. Filtering for genes similarly modulated in at least six mutants identified 196 upregulated and 62 downregulated aging genes. Upregulated genes were enriched in immunity, defense, and metabolism, while many downregulated genes impacted translation and gene expression. To assess the ability of these genes to enhance longevity individually, we knocked down the commonly upregulated genes in long-lived mutants and evaluated the resulting effect on lifespan. Using this approach, we identified several genes that affect lifespan individually. Upregulation of at least some of these genes was sufficient to enhance stress resistance and extend lifespan in wild-type worms.

Overall, the shared longevity genes identified in this work offer potential targets to promote healthy aging and decrease age-onset disease.

Link: https://doi.org/10.64898/2025.12.29.696944

Macrophages are innate immune cells found throughout the body, important not just for their ability to defend against infectious pathogens, but also deeply involved in tissue maintenance and regeneration. Macrophages can adopt different packages of behaviors - known as polarizations - in response to circumstances. The simple model, which likely glosses over many lesser differences that are important in some contexts, divides the macrophage population into M1 and M2 polarizations, distinguished by surface features as well as by behaviors. M1 macrophages generate inflammation and aggressively hunt down pathogens. M2 macrophages resolve inflammation and engage in tissue maintenance activities, such as ingesting cellular debris and waste products. Both polarizations are necessary, but aging brings imbalance, often characterized as too many M1 macrophages where M2 macrophages are what is needed.

Thus the research community is interested in developing the means to adjust macrophage polarization for therapeutic benefit. At the outset, this involves better understand the regulation of polarization, and the many distinct influences that contribute to a macrophage adopting one state or another. Today's research materials focus on an aspect of the regulation of circadian rhythm that is known to influence macrophage behavior, and the authors report on their efforts to dig more deeply into how this actually works. This sort of fundamental research is necessary to identify possible points of intervention for the later development of therapies.

Body clock found to control inflammatory responses in macrophages

When our body encounters an injury or infection, the immune system sends out cells known as macrophages to initiate an inflammatory response that begins the healing process. These macrophages can exist in two different states: a pro-inflammatory (M1) state, which promotes inflammation, and an anti-inflammatory (M2) state, which helps resolve inflammation and repairs the tissue. The balance between these two states is important, as disruptions can lead to uncontrolled inflammation, which in turn can give rise to chronic inflammation-associated diseases, including cancer, liver disease, diabetes, and autoimmune disorders.

Previous studies have revealed that macrophage activity is closely linked to the circadian clock, with BMAL1 playing a central role in regulating this process. Researchers have now found that BMAL1 drives macrophages toward a pro-inflammatory M1 state by activating inflammatory signaling pathways in the cell nucleus. Researchers observed that normal mice showed a marked increase in pro-inflammatory M1 macrophages along with elevated inflammatory signals after exposure to a chemical carcinogen. In contrast, mice lacking BMAL1 in their macrophages showed significantly reduced inflammation and suppressed liver tumor development.

Experiments revealed that BMAL1 binds to multi-functional protein 2 (MFP2), a fatty acid-oxidation enzyme normally found in cellular compartments called peroxisomes, and transports it into the cell nucleus. Notably, nuclear MFP2 levels fluctuate according to the time of day in a BMAL1-dependent manner. Once inside the nucleus, MFP2 increases acetyl-CoA levels, which drives acetylation of key proteins including p65, a component of the transcription factor NF-κB, a key regulator of inflammatory genes. This activates NF-κB, which functions as a switch for inflammatory genes, thereby driving macrophages into the pro-inflammatory M1 state. These findings suggest that targeting or blocking nuclear MFP2 and administering drugs at an optimal time of the day could become a new therapeutic strategy for chronic inflammatory diseases and enhance treatment efficacy while minimizing side effects.

The circadian clock component BMAL1 enhances macrophage inflammation by nuclear translocation of peroxisomal β-oxidation enzyme MFP2

The circadian clock regulates diverse immune functions, yet the role of clock components in macrophage inflammation remains controversial, with both pro- and anti-inflammatory effects reported. Here, we identify a previously unrecognized mechanism by which the core circadian clock component BMAL1 enhances the inflammatory response of macrophages through the nuclear translocation of the peroxisomal β-oxidation enzyme multi-functional protein 2 (MFP2). BMAL1 drives MFP2 accumulation in the nucleus, where MFP2 contributes to acetyl-CoA production and acetylation of the NF-κB subunit p65, thereby facilitating M1 polarization and inflammatory chemokine expression. Nuclear MFP2 levels oscillate in a diurnal manner in the liver, but this rhythmicity is abolished in Bmal1-deficient mice. Macrophage-specific deletion of BMAL1 alleviates diethylnitrosamine-induced hepatic inflammation and tumorigenesis, concomitant with reduced inflammatory gene expression. These findings uncover a BMAL1-dependent nuclear metabolic pathway that links circadian regulation of macrophage inflammation and suggest that targeting nuclear MFP2 may offer a therapeutic approach for inflammatory diseases and tumorigenesis.

Researchers here report on an interesting in vitro exercise in the comparative biology of aging. They took fibroblast cells from ten difference mammalian species with widely divergent life spans and chemically induced DNA damage in the cells. Modern DNA sequencing approaches allow an accurate measure of the amount of mutational damage produced by this chemical treatment, which in turn allows a comparison of the degree to which cells from different species can resist such damage via the operation of DNA repair systems. Long-lived species have more efficient DNA repair mechanisms, as determined by this approach.

We test the hypothesis that excess mutations induced in primary fibroblasts by a low dose of N-ethyl-N-nitrosourea (ENU) are inversely correlated with species-specific maximum life span. To measure excess mutations induced by ENU we treated primary cells of 10 mammalian species, greatly differing in life span. We treated all cells with a low dose, non-toxic dose of ENU (20 ug/ml). We then extracted DNA from all treated and untreated cells and quantified somatic mutation burden by single-molecule sequencing. We measured excessive mutations by calculating the increase in single nucleotide variants (ΔSNVs) and we analyzed this across species with linear regression.

The average values for ΔSNV were found to range from 0.773 in mice to 0.367 in whale, resulting in a modest inverse correlation with species-specific maximum life span (R^2 = 0.2067). We conclude that DNA repair accuracy, the main determinant of genome sequence integrity, modestly correlates with life span suggesting that longer lived species have better repair capacities compared to shorter-lived species, which is in keeping with genome instability being a primary hallmark of aging and highlights its important role for longevity.

Link: https://doi.org/10.70401/Geromedicine.2026.0023

Researchers here identify mechanisms downstream of faulty calcium metabolism that drive the harmful signaling of senescent cells that accumulate in aged tissues. Calcium metabolism is well studied in a number of contexts, and various drugs exist to adjust its operation in one way or another. Applying one of those drugs to aged mice results in a reduction in the harms done by senescent cells, improved health, and a 17% extension of life span. There will be many ways in which the presence of senescent cells in aged tissues could be made less harmful. At present most efforts are focused on the development of new drugs to selectively destroy senescent cells, but it seems likely that these research groups and companies will soon be joined by those seeking to alter the behavior of these cells instead.

Cellular calcium (Ca2+)-regulating systems are compromised during aging-related disorders. Here, we show that disruption of Ca2+ homeostasis leads to the cytoplasmic accumulation of Ca2+ binding protein S100A6, which promotes Hutchinson-Gilford progeria syndrome (HGPS) and natural aging. S100A6 recruits CacyBP to facilitate the ubiquitination and degradation of PARP1, leading to DNA damage and the formation of cytoplasmic chromatin fragments (CCF), activing cGAS-STING-NF-κB pathway and the secretion of senescence-associated secretory phenotype (SASP) factors.

Mianserin (MIA), a tetracyclic antidepressant, attenuates senescence in cells derived from HGPS patients and naturally aging humans by antagonizing serotonin receptors HTR2B/2 C to lower Ca2+ concentrations. MIA also improves a range of aging phenotypes and significantly extends the lifespan of both progeroid and naturally aging mice. Together, our findings uncover the mechanism of Ca2+ homeostasis disruption during premature and natural aging, and suggest MIA as a potential therapeutic strategy to extend healthy lifespan by augmenting Ca2+ homeostasis.

Link: https://doi.org/10.1038/s41467-026-74021-z

As yet the life sciences have provided no way to definitively, robustly measure biological age in an individual. In part this stems from a lack of consensus as to a useful definition of biological age, or indeed of aging more broadly. Researchers have long agreed upon sensible definitions at the high level, such as that aging is an increase with time in the risk of mortality due to intrinsic causes. That definition is validated, measurable over populations, but helps little when it comes to assessing the mortality risk or age of any given individual. At the low level, there are many specific forms of damage and dysfunction that can be measured, albeit not always without invasive sampling. Burden of senescent cells, loss of mitochondrial function, reduced average telomere length, slowed pace of cell replication, reduced grip strength, changes in a thousand biomarkers relating to immune function, and so forth. We have the general sense of trends, but again one cannot use these measures to say definite things about biological age and mortality risk for any given individual.

We live in a world in which measurements and algorithmic combinations of measurements that reflect aging in populations are proliferating alongside the interest in treating aging as a medical condition. This is particularly true for the aging clocks, such as epigenetic clocks, derived from machine learning techniques applied to large bodies of biological data. A slow, incremental ongoing process is underway to find out whether this landscape forms a suitable foundation for the discovery and development of a true consensus measure of biological age that can be applied usefully to individuals. At present that largely involves assessing as many people as possible using as many different measurement approaches as possible, and searching for patterns in the data. Data informs the way in which researchers think about definitions of aging, which inspires new approaches to measurement of biological age, and use of those approaches produces new data. It is a circular road.

Today's open access paper is a snapshot of part this ongoing dialog between theory and data. It is well known that socioeconomic status correlates with life expectancy across populations. Does this mean that low socioeconomic status produces accelerated aging? By what mechanisms, and how does the relative importance of these mechanisms inform our definitions of aging? Looking at epigenetic clock data derived from study populations with different socioeconomic circumstances doesn't answer these questions, but having that data is one step further towards a future in which those answers do exist.

The mediating role of DNA methylation clocks in associations of race, ethnicity, education, income, and occupation with mortality: findings from NHANES 1999-2002

For most documented contexts and time periods, there is a strong association between lower socioeconomic position and risk of higher mortality. The theory of social stratification posits that social stratification caused by a combination of factors, particularly race, ethnicity, and socioeconomic position, would influence health outcomes through differential access to resources, power, and opportunities. These adverse effects even can undermine the beneficial effects from other social exposures such as social cohesion and social resistance. These health disparities are reflected in key social stratification factors such as race and ethnicity, educational attainment, income, and occupation. Studies report notable differences in life expectancy across these dimensions. For instance, according to recent estimates, White Americans who reach age 15 have a life expectancy of 63 years, compared to 59 years for Black Americans and 66 years for Hispanic Americans. Likewise, individuals with an income at or above 400% of the poverty threshold have a life expectancy of 60 years at age 18, while those living below the poverty line have just 49 years. Similar disparities are also observed across different education levels and occupational groups

Aiming to systematically examine the mediating role of DNA methylation clocks in the associations between race, ethnicity, education, income, and occupation and mortality, this study uses nationally representative data to demonstrate that DNA methylation clocks, particularly GrimAge2 and DunedinPoAm, mediate a substantial proportion of racial/ethnic and socioeconomic disparities in mortality. GrimAge2 exhibited significant mediation on all-cause mortality disparities, accounting for 21% of the difference between participants with a high school diploma or GED and those with a college degree or higher, up to 52% of the difference between individuals in high-skilled blue-collar occupations and those in white-collar and professional positions. Similarly, the DunedinPoAm pace of aging mediated 11% of the mortality disparity between high school graduates and individuals with a college degree or above, and 28% of the disparity between Hispanic and White participants. Notably, these mediation results, particularly for GrimAge2, were greater than those observed for traditional clinical biomarkers. These findings suggest that DNA methylation clocks and biomarkers could serve as valuable tools for future research investigating the mechanisms underlying health disparities.

Across mammalian species, resting metabolic rate roughly inversely correlates with species life span and body weight. Larger species are on average longer lived and have lower metabolic rates. There are, of course, a number of interesting outliers that exhibit very long lives relative to similarly sized mammalian species, such as a few bat species and the naked mole-rats that are the subject of this paper. The prevalent thinking on the matter of metabolic rate and longevity is that this relationship says something about the amount of oxidative damage an individual's cells can sustain, or the capacity of those cells to resist that form of damage. Greater metabolic rate implies greater generation of oxidative molecules by mitochondria. The membrane pacemaker hypothesis on species life span suggests that the degree to which the lipid composition of cell membranes can resist oxidative damage is important. There is a great deal of complexity under the hood here, however, and every neat and compact theory on important mechanisms in this matter has its exceptions and outlier species.

This study offers a detailed analysis of resting metabolic rate (RMR) in naked mole-rats, incorporating individual, social, and colony-level factors to clarify how energy expenditure is organised within a eusocial mammal. Body mass consistently emerged as the primary predictor of RMR, aligning with the well-established allometric scaling of metabolic rate across mammals. This follows widely accepted convention that body mass explains the majority of variation in mammalian metabolic rates.

Notably the absolute RMR values recorded here are substantially lower than those predicted for mammals of similar size, further supporting the characterisation of naked mole-rats as possessing an unusually low metabolic profile. Predicted RMR values from 10 different studies and their associated approaches show a range of RMRs from 51.6 ml O2/hr to 71.1 ml O2/hr, compared to an average RMR of 45.5 ml O2/hr in the present study. This metabolic depression is commonly viewed as an adaptation to their subterranean environment, where relatively stable burrow temperatures lessen thermoregulatory demands, and energetic efficiency is advantageous given the high energetic and water costs of excavation alongside constrained resource availability. Within this ecological framework, reducing maintenance energy expenditure is likely to contribute both to colony stability and to the species' exceptional longevity.

Age did not significantly predict RMR once body mass was accounted for. The absence of an age effect is particularly notable given the exceptional lifespan of naked mole-rats. In many mammals, aging is accompanied by measurable shifts in metabolic maintenance; here, basal metabolism appears remarkably stable across age classes. This stability is consistent with the species' negligible senescence phenotype and suggests that aging does not impose detectable energetic costs at the level of resting metabolism.

Link: https://doi.org/10.1242/bio.062586

Thrombospondin-1 is a component of the senescence-associated secretory phenotype (SASP) produced by senescent cells. It has been shown in the past to induce blood-brain barrier dysfunction, but here researchers show that it also degrades mitochondrial function in macrophages, biasing those cells into the inflammatory M1 state. This in turn contributes to chronic inflammation and dysfunctional bone regeneration. The accumulation of senescent cells with age is known to be an important aspect of degenerative aging, and the SASP is known to change bystander cell behavior for the worse. There are likely countless mechanisms of this nature taking place in the aging body, all of which could be suppressed via reduction of the burden of senescent cells.

The aging bone marrow microenvironment is characterized by chronic low-grade inflammation ("inflammaging"), which disrupts skeletal homeostasis and impairs bone regeneration. However, the stromal-immune crosstalk mechanisms sustaining this pathological state remain poorly defined. Here, transcriptomic analysis identified thrombospondin-1 (Thbs1) as a key upregulated component of the senescence-associated secretory phenotype (SASP) in aged bone mesenchymal stromal cells (BMSCs).

We demonstrate that BMSC-derived Thbs1 drives pro-inflammatory M1 macrophage polarization by suppressing PINK1/Parkin-mediated mitophagy. Mechanistically, Thbs1 binds to the TGF-β type II receptor (Tgfbr2) on macrophages to activate Smad3 signaling, which transcriptionally represses the mitophagy regulator Pink1. This repression leads to mitochondrial superoxide accumulation and redox imbalance, thereby skewing macrophages toward an M1-like phenotype.

These Thbs1-activated M1 macrophages, in turn, secrete IL-6, which activates the JAK/STAT3 pathway in BMSCs to inhibit osteogenic differentiation. Crucially, activated Stat3 directly binds the Thbs1 promoter, establishing a self-amplifying loop that perpetuates inflammaging and osteogenic decline. In vivo, AAV9-mediated Thbs1 knockdown in aged rat bone defects restored mitochondrial homeostasis, promoted an M2 macrophage transition, and significantly enhanced bone repair.

In summary, our study reveals a vicious cycle involving the Thbs1/TGF-β/Smad3/PINK1-IL-6/JAK/STAT3 axis that sustains inflammaging and osteogenic decline, highlighting Thbs1 as a promising therapeutic target for age-related bone regeneration.

Link: https://doi.org/10.1111/acel.70575

A cell becomes senescent given sufficient stress, molecular damage, or on reaching the Hayflick limit on replication. A senescent cell ceases replication, grows in size, and secretes a potent mix of pro-growth, pro-inflammatory signals. In a young individual, senescent cells are rapidly removed by the immune system, but this clearance slows with age. Senescent cells accumulate as a result in tissues throughout the aging body. The greater the number of senescent cells, the more disruptive their signaling becomes, changing the behavior of surrounding cells for the worse, degrading tissue structure, and rousing the immune system into a harmful state of constant inflammatory behavior. Studies have shown that selective clearance of senescent cells in older mice improves health, extends life, and turns back many aspects of age-related disease.

Today's open access paper reviews what is know of the bidirectional relationship between the burden of cellular senescence and state of the aging immune system. Senescent cells degrade the performance of the immune system, while the aging of the immune system allows greater numbers of senescent cells to accumulate. Like many of the interacting aspects of aging, each side exacerbates the other in a feedback loop that accelerates over time. Under the hood, the details are far more complex than this simple summary of the situation, of course, and there much is yet to be mapped and understood. Still, what is known more than justifies a far greater level of attention and funding to be given to clinical trials of senolytic therapies to clear senescent cells.

Immunological consequences of senescence in physiology and pathology

Cellular senescence is a sublethal stress response characterized by a durable cell-cycle arrest and the acquisition of a complex secretory program known as the senescence-associated secretory phenotype (SASP), which can profoundly influence local and systemic immunity. In physiological contexts - including embryonic development, tissue repair, and acute tumour suppression - senescent cells coordinate the recruitment and activation of immune cells, enabling their timely immune-mediated clearance and facilitating tissue remodelling and restoration of homeostasis. However, during aging and chronic disease, immune surveillance mechanisms frequently become compromised, allowing senescent cells to accumulate and persist within tissues.

The persistence of senescent cells results in sustained SASP signalling that promotes chronic inflammation, immune dysfunction, and tissue remodelling processes linked to fibrosis, metabolic impairment, tumour progression, and defective tissue repair. In parallel, increasing evidence indicates that immune cells themselves can acquire senescent or senescence-like states, thereby weakening immunosurveillance and generating self-reinforcing feedback loops that further amplify senescent cell accumulation and tissue dysfunction.

The relationship between senescent cells and the immune system is reciprocal. Immune surveillance governs whether the senescence response is resolved or persists, yet immune cells themselves can adopt senescence-associated features that remodel tissue environments and propagate senescence systemically. Age-related decline or dysfunction within immune compartments can amplify inflammatory signalling, shift immune tolerance and generate niches that favour senescent-cell persistence, establishing feedback loops between immune aging and cellular senescence. Together, these observations position senescence not as an isolated cell-intrinsic programme but as a process shaped by continuous dialogue with the immune system. The strength of this senescence-immune crosstalk is shifting the therapeutic paradigm from classical senolytics toward immuno-senolytic strategies aimed at reactivating endogenous immune surveillance or deploying engineered immune cells to selectively eliminate senescent populations.

Machine learning approaches can be used to create aging clocks from near any set of biological data collected from people of various ages. The techniques are well established and many new clocks are published every year. A clock is really an age predictor (or a mortality predictor, or a predictor of some other outcome) trained on a single dataset. When the clock algorithm is applied to any given individual not in that data set, it is thought that the predicted age or mortality risk or other outcome is some reflection of biological age. It is hard to validate this proposition, as there is very little concrete connection between any easily measured biomarker and mechanisms of aging, and indeed all too little consensus on how to measure biological age in the first place. To my eyes more effort should go towards understanding the clocks we have and less to producing new clocks.

Biological aging is a key determinant of liver disease and mortality, but there is little evidence on noninvasive index for assessment of liver biological aging. We developed the Liver Aging Index (LAI) in the China Kadoorie Biobank (CKB, N = 21,629) using Cox-Gompertz proportional hazards model. The LAI incorporated three clinical factors (body mass index, systolic and diastolic blood pressure), eight plasma biomarkers (glucose, total cholesterol, triglycerides, high-density and low-density lipoprotein cholesterol, alanine aminotransferase, aspartate aminotransferase, and γ-glutamyl transpeptidase), and two imaging biomarkers (fat attenuation parameter and liver stiffness measurement).

External validation was conducted in the National Health and Nutrition Examination Survey (NHANES; N = 3412) and the VCTE-Prognosis cohort (N = 12,170, 16 global centers). Across all cohorts, the LAI demonstrated strong discrimination for all-cause mortality (area under the receiver operating characteristic curve: 0.764 in NHANES; 0.759 in VCTE-Prognosis), outperforming chronological age. Liver aging acceleration (LAA), defined as the difference between LAI and chronological age, was associated with substantially elevated risks: each 1 standard deviation increase in LAA conferred a 22%-85% higher risk of all-cause mortality and a 34%-170% higher risk of liver-related event or mortality.

Using genetic instruments identified in CKB, we found genetic predisposition to accelerated liver aging was associated with higher risks of cirrhosis and liver cancer (hazard ratios = 3.94 and 7.82), further validated in Biobank Japan. Integrating genetics and proteomics revealed novel pathophysiological involvement of amyloid-beta clearance pathway and amyloid precursor protein in liver aging. These findings demonstrate the feasibility of a noninvasive, liver-specific biological aging index and provide new insights into mechanisms underlying liver aging.

Link: https://doi.org/10.1111/acel.70565