Fight Aging!

Aging clocks are produced from machine learning strategies applied to databases of biological data, typically omics data of various sorts, obtained from people of various ages. Patterns that change with age can be identified and an algorithm defined to take any other person's data and predict their age based on comparisons to the reference database. Whether the predicted age is higher or lower than chronological age says something about the individual's biological age, the accumulation of damage and dysfunction in tissues and systems.

The biggest challenge in using these clocks is that the method of production tells us nothing about how exactly the data used in the algorithm is connected to particular processes or dysfunctions of aging. Thus it is hard to trust the outcome, particularly if the intent is to use clock measures to assess potential interventions that might slow or reverse aspects of aging. The clock may underestimate outcomes, overestimate outcomes, or just produce completely irrelevant results for any specific individual, and we have no good way of knowing which of these is the case.

This issue is well understood by the research community, and there are a number of different approaches that might be taken to improve the situation. Researchers have, for example, built clocks based on clinical measures such as blood counts and inflammatory cytokine levels rather than omics data. This is still not ideal, as the details of the connection between clinical measures and mechanisms of aging remain somewhat nebulous in most cases, but one can at least theorize on what is going on under the hood to a greater degree. Another, much harder approach is to start over and develop the means of building new omics clocks that are, from the ground up, manufactured with the intent of providing greater insight into underlying mechanisms. That work continues, but research groups are producing incremental progress along the way, such as the interpretable clock reported in today's open access paper.

DeepStrataAge: an interpretable deep-learning clock that reveals stage- and sex-divergent DNA methylation aging dynamics

Aging is the strongest risk factor for chronic diseases such as cardiovascular disease, Alzheimer's, and cancer. DNA methylation (DNAm) clocks offer a promising measure of biological age, but most rely on linear models that miss non-linear dynamics and CpG interactions. To address this, we developed a deep neural network (DNN)-based DNAm clock trained on 29,167 samples profiled on Illumina EPIC v1.0 and v2.0 arrays. Using 12,234 CpGs selected through sex- and age-stratified correlations, our model achieved high accuracy (1.89 years) and outperformed published deep learning and elastic net based epigenetic clocks in a separate validation cohort.

Using Shapley Additive Explanations (SHAP), we further uncovered phase-structured, wave-like dynamics in age-influential CpGs: an early-life module, a midlife transition, and late-life remodeling, with distinct timings by sex. These epigenetic waves cohere with non-linear, multi-omic "aging waves" reported in proteomics and longitudinal omics. SHAP further enabled interpretable CpG attribution, revealing structured, sex-specific aging phases: early-life male clocks involved developmental pathways, while female clocks emphasized cytoskeletal regulation; late-life divergence included immune activation in males and transcriptional remodeling in females. Our framework thus unites accuracy with mechanistic interpretability, revealing sex-specific windows when molecular aging reconfigures most rapidly.

The gut microbiome changes in composition with age in ways that harm tissue function and provoke chronic inflammation. Among the potential causes of this shift in composition is the age-related dysfunction of the immune system, allowing growth in microbial populations that should be kept in check. Researchers here work in fruit flies to identify a regulatory interaction that can be targeted to restore some of that lost immune function. It remains to be seen as to how applicable this is to the analogous situation in the mammalian immune system and gut microbiome, but one can hope.

The maintenance of immune homeostasis is critical for tissue health and longevity, yet the regulatory mechanisms linking immune modulation to aging remain poorly understood. Here we found that the transcription factor cAMP response element-binding protein (CREB), activated by JNK signaling in aging guts, transcriptionally suppresses peptidoglycan recognition protein SC2 (PGRP-SC2) - a homolog of mammalian anti-inflammatory PGLYRP1-4 with amidase activity. 16S rRNA sequencing revealed that CREB modulates not only microbial load but also microbiota composition. Elevated CREB activity decreased the Firmicutes/Bacteroidetes (F/B) ratio - a hallmark of age-associated dysbiosis in animals.

Genetic enhancement of PGRP-SC2 rescues age-related gut hyperplasia, microbiota imbalance, and lifespan shortening induced by overactivation of CREB or its coactivator CRTC. Notably, CREB's regulation of PGRP-SC2 operates independently of canonical immune pathways such as Imd/Relish, revealing a previously unrecognized layer of immune modulation. Our findings establish CREB as a central player in age-associated immune dysregulation and propose targeting the CREB-PGRP-SC2 axis as a potential therapeutic strategy for mitigating gut aging and its systemic consequences.

Link: https://doi.org/10.1038/s41420-026-02955-w

Quality of sleep tends to decline with age for reasons both physical and neurological; sleep apnea is a concern for many older people. A broad body of literature connects sleep issues with risk of neurodegenerative conditions. Thus researchers can plausibly expect to take sleep assessment data from a population of people at various ages, and employ machine learning strategies to develop an aging clock derived from that data. Any sufficiently complex data set that changes with age can be used in this way. Researchers here report on an implementation of this approach to measuring the aging of the brain, and produce an aging clock that can predict dementia risk based on sleep electroencephalography results recorded during a sleep study.

Sleep disturbances are increasingly recognized as early indicators and potential modifiable risk factors for dementia. However, the macrolevel sleep architecture has shown inconsistent associations with cognitive impairment and incident dementia. These broad sleep metrics do not fully capture the complex and multidimensional nature of sleep physiology. In contrast, the microstructure of sleep electroencephalography (EEG) directly reflects the neural processes with explicit functional implications. To capture these complex patterns, we developed a sleep EEG-based brain age using a novel, interpretable machine learning approach that integrates multiple age-dependent EEG microstructures into a single agelike number. The difference between brain age and chronological age is termed the brain age index (BAI).

For this individual participant data meta-analysis, sleep study data from 5 community-based longitudinal cohorts were pooled. These cohorts included the Multi-Ethnic Study of Atherosclerosis (MESA; 2010-2013), the Atherosclerosis Risk in Communities (ARIC) study (1987-1989), the Framingham Heart Study-Offspring Study (FHS-OS; 1995-1998), the Osteoporotic Fractures in Men Study (MrOS; 2003-2005), and the Study of Osteoporotic Fractures (SOF; 2002-2004). This meta-analysis included 7,105 participants.

The median time to dementia was 4.8 years in the MESA cohort (n = 119 [6.6%]), 16.9 years in the ARIC cohort (n = 354 [19.7%]), 13.1 years in the FHS-OS cohort (n = 59 [9.6%]), 3.6 years in the MrOS cohort (n = 470 [17.8%]), and 4.6 years in the SOF cohort (n = 86 [34.3%]). Across the cohorts, each 10-year increase in BAI was associated with a 39% higher risk of incident dementia (hazard ratio [HR] 1.39) after adjustment for covariates. These associations remained after additional adjustment for comorbidities and apnea-hypopnea index scores (HR 1.31) and apolipoprotein E ε4 (HR 1.22), and they were consistent across sex and age groups.

Link: https://doi.org/10.1001/jamanetworkopen.2026.1521

Researchers have identified many contributing issues leading to the characteristic loss of muscle mass and strength that takes place with age. Arguably the central problems are (a) the disruptions of cell behavior caused by chronic inflammation, (b) damage to neuromuscular junctions, depriving muscle tissue of signals it relies upon for normal maintenance to take place, and (c) loss of muscle stem cell activity, and thus a reduced supply of somatic muscle cells to replace losses. These central problems likely interact with one another, but in principle could be addressed distinctly to produce benefits in patients.

Past studies have shown, rather convincingly, that muscle stem cells in older individuals retain their function when moved from an old environment to a young environment. The problem is not so much damage to these cell populations, but rather their growing lack of activity. Stem cells spend most of their time quiescent, only activating to produce daughter somatic cells when needed. With age, activation of stem cells diminishes for reasons that are only partially explored, and may differ considerably in their details from tissue to tissue. In principle, a greater knowledge and control over stem cell activation could be employed to reduce the age-related loss of muscle tissue, but that requires progress in uncovering specifics of the regulatory systems involved that might be targeted by novel therapeutics.

MG53 in Early Skeletal Muscle Stem Cell Activation: Implications for Aged Muscle Regeneration

Skeletal muscle regeneration declines with age despite the persistence of satellite cells (muscle stem cells, MuSCs), suggesting that regenerative impairment reflects functional dysregulation rather than MuSC depletion. Increasing evidence identifies early MuSC activation during the immediate post-injury period as a stress-sensitive, rate-limiting transition that is particularly vulnerable in aged muscle. Aged MuSCs exhibit elevated stress responses and reduced membrane remodeling capacity, accompanied by weakened activation-associated transcriptional induction. In contrast, proliferative and differentiation programs remain largely intact once activation is successfully initiated.

These findings underscore that impaired coordination during early activation contributes to long-term regenerative decline in aging. Within this framework, MG53 (tripartite motif-containing protein 72, TRIM72), a muscle-enriched TRIM family E3 ubiquitin ligase originally identified as a mediator of sarcolemmal membrane repair, may also function as a stress-responsive regulator that stabilizes the early activation environment. Rather than directly determining cell fate, MG53 is proposed to facilitate activation by mitigating stress-associated membrane disruption and maintaining programmatic coordination under age-related physiological constraints.

However, direct experimental evidence defining the role of MG53 in the early activation of aged MuSCs remains limited. Current data primarily support its functions in membrane stabilization, oxidative stress mitigation, and inflammatory modulation. Whether these stress-buffering properties directly influence the early activation transition in aging muscle has not yet been formally tested. In this review, we suggest that MG53 may contribute to the regulation of early MuSC activation under conditions of elevated cellular stress in aged muscle. Clarifying this potential role represents an important direction for future mechanistic investigation.

It has been fifteen years since the first compelling demonstration of clearance of senescent cells in mice. That study paved the way for the transformation of the research community into one convinced of the relevance of cellular senescence to degenerative aging. It also helped to change the culture of aging research more generally, one of the important contributions to a shift in attitudes that has led to a research and development community that understands the treatment of aging as a medical condition to be a practical, desirable goal. Here, discuss the role of cellular senescence in muscle aging specifically; how it contributes to harm and lost function, and what might be done about it.

Cellular senescence is increasingly recognized as a pivotal mechanism driving skeletal muscle aging and the development of sarcopenia, a condition characterized by the progressive loss of muscle mass, strength, and function. This review synthesizes recent evidence detailing the accumulation of senescent cells in aged skeletal muscle, including muscle stem cells (MuSCs), fibro-adipogenic progenitors (FAPs), immune cells, endothelial cells, and even post-mitotic myofibers. Senescence in these cell types impairs regenerative signaling, disrupts niche homeostasis, and propagates chronic inflammation.

Emerging therapeutic strategies, termed senotherapeutics, aim to counteract these effects through senolytics (which eliminate senescent cells) and senomorphics (which modulate the senescence-associated secretory phenotype), as promising interventions to restore muscle function and delay sarcopenia. We will also discuss the remaining challenges and future directions for studying senescence in skeletal muscle.

Link: https://doi.org/10.3803/EnM.2025.2816

There is a reasonable consensus in the research community on the broad categories of issue that lead to and are associated with the aging of the immune system. One can start by dividing immune aging into immunosenescence, a loss of capacity, versus inflammaging, a continual state of unresolved inflammatory signaling, and look at the various contributions to each state, for example. This paper is chiefly interesting for the attempt to propose classes of intervention to address immune aging based on the categorization of issues provided. This would not have been the case twenty years ago; the paper would have outlined what was known of immune aging and possible causes and then stopped. It is a reminder that we now live in an era in which the treatment of aging as a medical condition is widely accepted as an aspirational goal for the life sciences.

Immune aging is best understood not as a collection of isolated defects, but as a complex, interconnected reconfiguration of immune and tissue networks that alters how the body responds to internal and external stressors. Aging causes coordinated changes in innate and adaptive immunity, metabolic pathways, and inter-organ communication, creating a web of interactions whose emergent properties differ fundamentally from those of younger systems. Therapeutic targeting of immune aging aims to rebalance dysregulated inflammatory networks, restore immune adaptability, and improve tissue repair capacity. Current approaches range from mechanistically targeted pharmacological agents to regenerative, metabolic, lifestyle, and precision strategies. Evidence strength varies considerably, with some interventions supported by early clinical data and others remaining primarily experimental.

Interventions directed at fundamental drivers of immune aging, including chronic inflammatory signaling and cellular senescence, represent the most mechanistically advanced therapeutic class. Modulation of the mechanistic target of rapamycin (mTOR) pathway - through agents such as rapamycin and its analogs - has been shown to recalibrate immune metabolism, attenuate excessive inflammatory signaling, mitigate components of the senescence-associated secretory phenotype (SASP), and enhance antiviral responses in older adults, with early-phase clinical trials providing supportive evidence of immunological benefit. However, potential risks include metabolic dysregulation, impaired wound healing, and dose-dependent immunosuppression, emphasizing the need for intermittent or low-dose regimens.

Targeting intracellular inflammatory signaling represents a complementary strategy to rebalance immune network activity. Inhibitors of p38 mitogen-activated protein kinase (p38 MAPK) can restore macrophage functionality, enhance efferocytosis, and promote pro-resolving phenotypes in aging models. While mechanistically attractive, long-term systemic kinase inhibition may carry risks related to host defense impairment and unintended metabolic effects.

Cellular and regenerative interventions aim to restore immune architecture and adaptive capacity. Mesenchymal stem cells (MSCs)-based therapies exhibit immunomodulatory and tissue-repair properties, with encouraging preclinical and early clinical data suggesting benefits for inflammatory dysregulation and impaired regeneration. However, heterogeneity in cell preparations, uncertain durability of effects, and potential tumor-promoting signals remain key concerns. Reconstitution of adaptive immune output through thymic and hematopoietic rejuvenation represents an emerging but strategically important avenue. Beyond IL-7 supplementation, several molecular regulators are under investigation. Forkhead box N1 (FOXN1)-associated pathways, keratinocyte growth factor (KGF), and fibroblast growth factor (FGF) 21 contribute to thymic epithelial integrity and naive T-cell production, with preclinical evidence indicating delayed thymic involution and improved immune function.

Modulation of the gut microbiome through dietary fiber, prebiotics, probiotics, and microbiome-directed therapies can influence systemic inflammation and immune regulation. Diets rich in fiber and prebiotics, targeted probiotic supplementation, and microbiome-directed interventions can enhance gut barrier integrity, promote beneficial microbial taxa, and reduce translocation-induced inflammaging, thereby influencing systemic immune function and inflammatory set points. Improvements in barrier integrity and microbial metabolite production may reduce translocation-driven inflammatory activation. While mechanistically promising and supported by observational studies, variability between individuals and limited standardized clinical trials currently restrict therapeutic generalization.

Link: https://doi.org/10.3390/cells15050414

Myostatin is a circulating inhibitor of muscle growth. It has been an area of research interest for some time, long enough for myostatin loss of function mutants to have been identified or engineered in a range of mammalian species: mice, dogs, cows, and so forth. Complete loss of function in the myostatin gene throughout life is accompanied by exceptional muscle growth and strength, alongside a lesser amount of visceral fat tissue. All told it seems a benefit with little to no downside.

Since muscle mass and strength is lost with advancing age, there have been efforts to develop therapies based on inhibition of myostatin, such as via monoclonal antibodies. The popularity of GLP-1 receptor agonist drugs that produce loss of muscle mass in addition to visceral fat tissue by reducing calorie intake has resulted in an even greater pharmaceutical industry interest in developing ways to avoid this loss of muscle.

There are many possible points of intervention beyond direct inhibition of myostatin expression, circulating levels, or activity. One possibility presently in clinical trials is the inhibition of myostatin receptors. Another example is the upregulation of follistatin, a circulating molecule that acts in opposition to myostatin, and comes with a similar body of work in mouse studies, where genetic engineering or gene therapies have produced heavily muscled mice. A number of therapies claim to improve follistatin levels, and follistatin gene therapies are now used to some degree in the medical tourism industry. Data on human efficacy is thin to non-existent, however.

Meanwhile, research into myostatin continues as the range of possible muscle growth therapies expands. Today's open access paper is a very interesting tour of what can be learned from the very large genetic databases that now exist. Only the one convincing human myostatin mutant with very evident effects is known to the scientific community, but these large databases allow the discovery of other individuals with mutations that produce a weaker loss of function in the myostatin gene. Since genetic data is coupled with a large amount of other health data in the UK Biobank, one can actually map mutation to muscle strength and other characteristics known to be affected by myostatin.

Humans with function-disrupting variants in the myostatin gene (MSTN) have increased skeletal muscle mass and strength, and less adiposity

Myostatin negatively regulates skeletal muscle size in multiple species, and therefore, myostatin blockade has been therapeutically explored to promote muscle growth in humans, including to counter the muscle loss seen in obese humans using GLP1R agonists. In this study, we present results from a large multi-cohort genetic association analysis, using data from 1.1 million individuals to examine the effects of function-disrupting mutations in the myostatin gene (MSTN) on traits relevant to body composition and cardiometabolic health.

Carriers of function-disrupting variants display decreased adiposity, an increase in lean mass, and increased grip strength and creatinine levels. We further characterize the effects of these variants on body composition using whole-body MRI data from UK Biobank, leveraging deep learning models to perform automated image segmentation for 77,572 individuals. Among mutation carriers increased muscle mass is observed across multiple muscle groups, with heterozygote carriers of loss-of-function-like mutations exhibiting increases in excess of 10%.

Our findings demonstrate that lifelong reduction in myostatin function enhances muscle size and strength in humans while decreasing body adiposity, providing insights into the potential benefits and safety of long-term therapeutic blockade of myostatin signaling.

The dominant amyloid cascade hypothesis for Alzheimer's disease broadly states that amyloid-β aggregation occurs early in the progression of the condition, setting the stage for later and much more damaging neuroinflammation and tau aggregation. There remains a great deal of room to debate the details of this progression, how exactly amyloid-β and tau aggregation are linked. Is it as simple as a matter of chronic inflammation generated by amyloid-β aggregation slowly rising to the level of inciting a feedback loop between tau aggregation and further inflammatory signaling? Or some other more direct connection between the biochemistry of amyloid-β aggregation and tau aggregation? Here, researchers advance a novel theory on this topic.

Alzheimer's disease (AD) is defined by cognitive decline in conjunction with accumulation of aggregated amyloid β (Aβ) and tau, yet existing models of AD fail to provide a simple connection between Aβ and tau. However, microtubules provide an intriguing nexus for pathological interactions between the two. Tau binds to microtubules and is critical to maintaining their proper function. We demonstrate that Aβ also binds to microtubules with affinity comparable to that of tau itself.

We hypothesize that displacement of tau by Aβ leads to microtubule dysfunction and facilitates tau phosphorylation and aggregation. Importantly, in this model, aggregation of Aβ is not the primary cause of toxicity, which allows many of the apparent contradictions between Aβ pathology and cognition to be rationalized. This model highlights the importance of both tau and Aβ and enables additional therapeutic and intervention strategies to be considered.

Link: https://doi.org/10.1093/pnasnexus/pgag034

There has been a surge of interest in the potentially beneficial effects of late life vaccination in recent years. The challenge in looking at correlations between health and adult vaccination status is that we don't know the degree to which it reflects biological mechanisms, such as trained immunity effects reducing the chronic inflammation of aging, versus selecting for people who generally take better care of their health and thus tend towards better outcomes across the board. Causation is hard to derive from human epidemiological data.

Previous studies suggest that a shingles infection can cause blood clots to form around the brain and heart, raising the risk of events such as heart attacks, strokes, and venous thromboembolism. By preventing the infection, the shingles vaccine is thought to also help prevent the formation of these dangerous clots. For the current study, researchers used TriNetX, a database that includes health records of millions of Americans, to assess rates of serious cardiac events in people age 50 years or older with atherosclerotic disease between 2018-2025. The study included 123,411 people who had received at least one dose of either the Shingrix or Zostavax shingles vaccine and the same number of people who had not received any doses of shingles vaccine. Demographics and other health conditions were similar between the two groups.

When researchers examined cardiac events occurring between one month and one year after shingles vaccination (or the same time period for unvaccinated individuals), they found that vaccination was associated with a lower risk across all outcomes studied. Vaccinated individuals were 46% less likely to suffer any major adverse cardiac event and 66% less likely to die from any cause. They were also 32% less likely to suffer a heart attack, 25% less likely to suffer a stroke and 25% less likely to develop heart failure. These levels of risk reduction are substantial, comparable to what would be expected from quitting smoking.

The study focused only on outcomes during the first year after shingles vaccination, so researchers noted that the lifetime impacts may differ from those observed during this time period. A previous study released in 2025 found getting the shingles vaccine was associated with a 23% lower risk of cardiovascular events in a healthy general population, and the vaccine's cardioprotective effects may last for up to eight years.

Link: https://www.acc.org/About-ACC/Press-Releases/2026/03/16/19/33/Shingles-Vaccine-Drastically-Cuts-Risk-of-Serious-Cardiac-Events

As the treatment of aging as a medical condition became more mainstream, there was a tendency for advocates and researchers to avoid talking about extending life span. They instead talked about pushing back the onset of poor health and even said explicitly that the goal of research and development was not to lengthen overall human life. From the perspective of aging as an accumulation of cell and tissue damage and potential rejuvenation therapies as repair of that damage, this view is incoherent. A priori, we know that repairing damage will extend both the overall life span and the period of good function in machinery, including biology. This is well studied under the heading of reliability theory, modeling how damaged systems fail.

In medicine, however, we observe that about half of the upward trend in life expectancy over the past century or more arises from an extension to health without an extension to life span. How can that be? A common explanation is that some forms of late-life damage are relatively little affected by any advance in public health or medical technology. One possibility is that transthyretin amyloidosis is the mechanism of interest, an accumulation of harmful amyloid that contributes to cardiovascular disease, and is now thought to be much more prevalent than previously assumed. Since that is now a treatable condition, albeit one that is only actually treated in the rare very severe cases, it will be interesting to observe what happens when the therapies become generic and thus potentially widely used.

Healthy life extension: Geroscience's north star

Mikhail Blagosklonny was right to say out loud: the goal of geroscience is life extension. Not "vitality" or a polite euphemism for better late-life care, but life extension. He also insisted on disciplined evidence: if we claim we are modifying aging, we should demand hard outcomes in mammals rather than an endless parade of biomarkers. Where I would extend his argument, as a longevity physician, is: the field must stop treating "lifespan vs. healthspan" as a fork in the road. In medicine, and in the lives our patients actually live, they are not competitors. The only mission that is both scientifically coherent and clinically meaningful is healthy life extension: more years in full health.

The "healthspan, not lifespan" framing makes geroscience sound as though it is not about longevity, when longevity is what emerges from delaying the biology that drives multimorbidity. World Health Organization (WHO) data show that from 2000 to 2019, life expectancy increased more than healthy life expectancy, meaning we added years lived with disease or disability. A cross-national analysis quantified the global "healthspan to lifespan gap" at approximately 9.6 years. Modern systems deliver more years, but not more good years. That is precisely why geroscience must be more ambitious. We should treat healthy life extension as the goal and define success as health-adjusted longevity: extending lifespan while proportionally expanding function, resilience, and independence.

If we agree that the goal is healthy life extension, incrementalism becomes a choice rather than a constraint. Consider the balance sheet: within the National Institute on Aging (NIA) budget, the Division of Aging Biology is funded at roughly $346 million, whereas neuroscience-related research is funded in the billions. We have not resourced basic aging biology in proportion to its theoretical leverage: the possibility of delaying many diseases at once. This is not a call to rob disease programs. It is a call to stop pretending a civilization-scale problem can be solved with niche-scale funding.

It isn't surprising to find that epigenetic clocks predict mortality more effectively than simple clinical measures such as individual biomarkers of age-related chronic inflammation. Epigenetic clocks are derived from many more data points, and at least some clocks, such as the Dunedin Pace of Aging clock, were constructed with the intent of predicting mortality. Nonetheless, one has to run the numbers. Here, researchers look at the ability of various measures and combinations of measures to predict mortality in a large database of human epidemiological data, and find that the epigenetic clock outperforms other options, but is still better augmented with a few clinical measures.

We used data from the Berlin Aging Study II (BASE-II, 60-80 years of age at baseline, average follow-up 7.4 ± 1.5 years, range 3.9-10.4, n = 1,083) to compare 14 biomarkers of aging recently consented by an expert panel for the use as outcome measures in intervention studies: physiological (insulin-like growth factor 1 (IGF-1), growth-differentiating factor-15 (DNA methylation derived, DNAmGDF15)), inflammatory (high sensitivity C-reactive protein (CRP), interleukin-6 (IL-6)), functional (muscle mass, muscle strength, hand grip strength (HGS), Timed-Up-and-Go (TUG), gait speed, standing balance test, frailty phenotype (FP), cognitive health, blood pressure), and epigenetic (epigenetic clock, DunedinPACE). Cox proportional hazard regression analyses were performed to investigate their role in prediction of all-cause as well as cause-specific mortality. Results were adjusted for age, sex, lifestyle factors, and genetic ancestry.

In adjusted models of all-cause mortality, HGS, IL-6, standing balance, cognitive health, and the epigenetic clock (DunedinPACE) statistically significantly predicted mortality, with the epigenetic clock (DunedinPACE) emerging as the strongest predictor. CRP, gait speed, IGF-1, blood pressure, muscle mass, DNAmGDF15, FP and TUG were not associated with mortality in this study. These results were corroborated in subgroup analyses stratified by cause of death. Feature selection identified a minimal biomarker set consisting of muscle mass, standing balance, and epigenetic clock (DunedinPACE) that predicted mortality with nearly the same discriminative accuracy (C-index = 0.63) as the full model including all biomarkers (C-index = 0.65).

In conclusion, among the fourteen investigated biomarkers of aging, DunedinPACE emerged with the strongest and most consistent association with mortality.

Link: https://doi.org/10.1186/s40364-026-00909-z

Collagen molecules of various sorts are a vital component of the extracellular matrix, a complex supporting structure in tissues that is maintained by the cells that reside within it. Aging produces changes in this maintenance, in addition to a growing burden of alterations and damage to the molecules making up the extracellular matrix. Extracellular matrix aging is not as well studied as the aging of cells; this research exists at the intersection of the two, assessing age-related changes in the production of collagens needed for extracellular matrix maintenance in a short-lived laboratory species.

Collagens, long regarded as structural molecules, also regulate stress responses and longevity. In this study, we analyzed our RNA sequencing data and publicly available gene expression data to define their role in Caenorhabditis elegans aging. Collagen expression broadly declined with age, with 16 collagen genes consistently downregulated across independent studies, establishing collagen downregulation as a genetic hallmark of aging. In contrast, meta-analysis of 66 datasets (128 comparisons between normal and long-lived animals) showed collagen upregulation in 84% of long-lived conditions, identifying collagen induction as a conserved signature of lifespan extension.

Using collagen gene expression data, we applied K-means clustering and identified clusters that captured functional, tissue-associated subsets of collagens. Notably, aging-associated collagens were strongly enriched in Cluster 1, which overlapped with hypodermal collagens, while Cluster 2 significantly intersects with lifespan-extension and intestine-enriched subsets, and Cluster 3 likely represents structural collagens contributing to cuticle and muscle integrity. These results indicate that collagen genes grouped by expression-based clustering are not randomly distributed but instead reflect tissue-specific patterns and functionality.

Together, our findings suggest that collagens are dynamic regulators of aging and longevity in C. elegans. Given the conservation of extracellular matrix biology across species, collagens represent candidate biomarkers and targets for promoting healthy aging in both C. elegans and higher animals.

Link: https://doi.org/10.1016/j.mbplus.2026.100192

If the activities of a cell appear precisely engineered and highly efficient, it is because every layer of cellular activity is monitored by some form of quality control mechanism. A cell is a collection of molecules moving at incredible speeds, where every possible collision happens countless times per second. All of the damaging, unwanted reactions that can occur between molecular structures in the cell do in fact happen constantly. Breakage happens constantly. Manufacture of new structures produces flawed outcomes constantly. But all of these issues are cleaned up as they occur. The processes of quality control and maintenance that undertake this cleanup work are collectively vital to cell health and cell function.

Messenger RNA is manufactured as the first stage of gene expression. The transcriptional machinery of the cell nucleus assembles messenger RNA molecules based on their genetic blueprints before sending them off to be translated into proteins. Following the remarks above, many flawed messenger RNA molecules result from the constant transcriptional activity in the cell nucleus and must be dealt with by a layer of messenger RNA quality control. As is the case for most of the processes involved in gene expression, this quality control is fairly well understood by the research community, likely becomes meaningfully less effective with advancing age, but measuring specific aspects of this quality control process can be challenging, leading to debate.

The function of mRNA quality control in aging and age-related diseases

Aging is accompanied by a gradual decline in physiological functions and an exponential increase in susceptibility to multiple age-associated diseases. Aging is caused by the impairment of biological systems at multiple levels. At the cellular level, the accumulation of senescent cells, which stably stop proliferation, is considered as a major cause of aging. At the molecular level, genomic instability and reduced proteostasis contribute to accelerating both cellular senescence and organismal aging. Recent studies also suggest important roles of messenger RNA (mRNA) quality control systems in aging. Studies using the nematode Caenorhabditis elegans demonstrated the important function of mRNA quality control and homeostatic regulation of splicing in organismal aging. In addition, age-dependent accumulation of stalled ribosomes, which are closely associated with co-translational mRNA quality control systems, contributes to aging and longevity in the budding yeast Saccharomyces cerevisiae and C. elegans.

Eukaryotic cells are equipped with multiple mRNA surveillance systems that eliminate abnormal transcripts. Nonsense-mediated mRNA decay (NMD), a key RNA surveillance process, targets mRNA transcripts that contain premature termination codons (PTCs). Nonstop decay (NSD) eliminates mRNAs without stop codons that cause ribosome stalling at the poly(A) tail, and conventionally no-go decay (NGD) removes mRNAs with internal stem-loop structures or rare codons that cause internal ribosome stalling. Although poly(A)-mediated ribosome stalling has been classically associated with NSD, recent studies showed that poly(A) stretches can also trigger ribosome collisions and activate NGD, indicating a partial mechanistic overlap between the two pathways. Slow elongation caused by non-optimal or rare codons activates a noncanonical mRNA surveillance pathway, codon-optimality-mediated decay, rather than NGD, and the decay of such mRNAs is mechanistically distinct from NGD.

Impairments of NMD, NSD, and NGD contribute to physiological defects such as premature aging and neurodegeneration, highlighting the importance of proper maintenance of mRNA quality control in organismal health. Here, we discuss the critical roles of these pathways in maintaining mRNA quality and preventing the accumulation of aberrant transcripts, which can contribute to aging and age-related disorders. Specifically, we discuss the function of NMD in aging processes and age-related diseases, including cancer and neurodegenerative disorders. We also review the safeguarding roles of NSD and NGD in preventing the accumulation of faulty mRNAs and proteins associated with various diseases. We explore the potential functions of additional mRNA surveillance and the associated signaling pathways, such as ribosome-associated quality control (RQC), in aging and age-related diseases. Understanding the intricate relationship between mRNA surveillance mechanisms and aging may provide key information for developing potential therapeutics that boost these pathways for delaying aging and treating age-related diseases.

Aging can be split up into specific categories in many different ways; age-related diseases as collections of symptoms, specific forms of cell and tissue damage that accumulate, dysfunctions separated by organ, and so forth. None of these categories exist in isolation from the others, however. All aspects of aging interact with one another. Kidney dysfunction affects the brain. Mitochondrial dysfunction influences the burden of cellular senescence. There are a hundred other interactions one might consider that blur the lines of any attempt at categorization of the progression of aging. Nothing is neat and contained, everything interacts.

Aging is accompanied by conserved hallmarks including genomic instability, epigenetic alterations, loss of proteostasis, and mitochondrial dysfunction, but how these processes emerge and become mechanistically linked remains unclear. Here we leverage a proteome-wide, single-cell, subcellular atlas of protein expression, localization, and aggregation across yeast replicative aging to map hallmark-linked remodeling in its spatial context.

We identify hundreds of previously unappreciated molecular changes that underlie major hallmarks of aging and show that hallmark phenotypes frequently manifest as compartment-specific erosion of spatial confinement, relocalization, and aggregation. 91.6% human orthologs of these hallmark-linked yeast proteins also change during human aging. Integrating these spatial phenotypes reveals many molecular connections linking different hallmarks. Temporal analysis suggests that disorganization of nucleolar ribosome biogenesis, proteostasis decline, and mitochondrial dysfunction precede other hallmarks. Together, our findings substantially deepen the molecular underpinnings of aging hallmarks and provide a framework for linking them into a hierarchical sequence of cellular failures.

Link: https://doi.org/10.64898/2026.02.26.708335

Sarcopenia is the name given to the characteristic age-related loss of muscle mass and strength, once the process enters more severe stages. The loss of strength and resilience is an important contribution to frailty, but muscle is also a metabolically active tissue and loss of muscle negatively affects metabolism as well as physical capacity. Chronic inflammation is a feature of aging, as the immune system reacts to cell and tissue dysfunction in maladaptive ways. That chronic inflammation contributes to all of the common age-related conditions by interfering in the maintenance of tissues; this includes muscle tissue and the development of sarcopenia.

Sarcopenia is a syndrome characterized by an age-related progressive decline in skeletal muscle mass, strength, and function. It represents a significant public health concern because of its adverse impact on the quality of life and prognosis of older adults. Chronic low-grade inflammation contributes to the pathophysiology of sarcopenia through multiple pathways, including cellular senescence, immunosenescence, oxidative stress, mitochondrial dysfunction, hormonal alterations, and gut microbiota dysbiosis. Moreover, obesity, a chronic inflammatory condition, is associated with sarcopenia, leading to sarcopenic obesity, which further exacerbates muscle loss and functional impairment.

In terms of interventions, exercise, nutritional supplementation, and combined approaches have demonstrated efficacy in improving muscle mass and function, as well as conferring demonstrable anti-inflammatory benefits. In addition to conventional hormonal therapies, pharmacological strategies, particularly anti-inflammatory agents and treatments targeting inflammatory pathways, show considerable therapeutic promise.

This review examines the central role of chronic inflammation in the development and progression of sarcopenia, as well as its underlying mechanistic basis. It also elaborates on the roles of key inflammatory cytokines, such as C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α), in regulating muscle protein metabolic balance and their potential utility as biomarkers. A deeper understanding of the relationship between inflammation and sarcopenia will not only help elucidate its complex pathogenesis but also offer critical directions for the future development of early diagnostic tools and targeted anti-inflammatory interventions.

Link: https://doi.org/10.3389/fphar.2026.1733798