The research team, led by Jing Pan and Tzu-Shao Yeh of the Department of Nutrition and Food Hygiene at Nantong University in China, together with Luthfia Dewi of Universitas Muhammadiyah Semarang in Indonesia, focused their experiments on C2C12 cells, a widely used mouse skeletal muscle cell line that recapitulates key stages of muscle formation. These cells can be induced to behave like satellite cells, the resident stem cells of skeletal muscle, and to progress through the full differentiation program that turns undifferentiated myoblasts into mature, multinucleated myotubes, the cellular equivalent of muscle fibers. By treating these cells with boswellic acid and measuring changes at both the RNA and protein levels, the investigators were able to map the compound’s effects across the entire myogenic cascade.

The results were striking at multiple points along this cascade. Boswellic acid treatment produced a 17 percent increase in the number of Pax7-positive cells. Pax7 is the canonical marker of satellite cell identity and quiescent muscle stemness, and an expanded Pax7-positive population suggests that the compound preserves or expands the pool of cells capable of regenerating damaged or aging muscle tissue. This is a critical finding for the muscle aging field, because one hallmark of aged muscle is the depletion and dysfunction of its satellite cell reserve, leaving old muscles increasingly unable to repair themselves after injury, disuse, or disease.

Beyond stemness, the compound appeared to push cells more rapidly through the commitment and differentiation stages of muscle formation. The researchers quantified the relative messenger RNA levels of four master regulators of myogenesis: Pax7, Myf5, MyoD, and MyoG. These myogenic regulatory factors act in a choreographed sequence, with Pax7 maintaining the stem cell state, Myf5 and MyoD committing cells to the muscle lineage, and myogenin driving terminal differentiation and fusion into myotubes. Following boswellic acid treatment, the mRNA and protein levels of Myf5, MyoD, and MyoG were all significantly upregulated, indicating that the treated cells were accelerating through the myogenic differentiation program. The study also documented a two to four hour advancement in the myoblast renewal cycle, suggesting that the compound speeds the temporal rhythm by which muscle precursor cells proliferate and renew themselves before differentiating.

Protein-level confirmation came from Western blotting, a technique that separates proteins by molecular weight and detects them with specific antibodies. The team measured protein expression of Pax7, Myf5, MyoD, and MyoG, alongside loading controls such as beta-actin and GAPDH, and found the upregulation observed at the RNA level faithfully mirrored at the protein level. Immunofluorescence staining was used to visualize Pax7 and MyoD expression within individual cells, providing spatial confirmation that the molecular changes translated into shifts in the cellular populations themselves. Cell viability was assessed with the XTT assay, ensuring that the observed pro-myogenic effects were not simply an artifact of compound toxicity or stress-induced changes in cell behavior.

Perhaps the most translationally intriguing results concern hypertrophy, the enlargement of existing muscle fibers. Boswellic acid treatment significantly enhanced myotube hypertrophy through activation of the canonical hypertrophic signaling axis: the Akt-mTOR-p70S6K pathway. This pathway is the central growth-control circuit of skeletal muscle, integrating signals from insulin-like growth factor 1, mechanical loading, and nutrient availability to drive protein synthesis. Akt, or protein kinase B, phosphorylates and regulates downstream targets including mTOR, the mammalian target of rapamycin, which in turn activates p70S6K, a ribosomal protein S6 kinase that promotes ribosomal biogenesis and translation of muscle proteins. The researchers observed increased phosphorylation of all three nodes, indicating that boswellic acid switches on the same anabolic program engaged by resistance exercise and IGF-1 signaling.

The convergence of two effects, expanded stem cell activity and heightened anabolic signaling, is what distinguishes this study from many single-mechanism nutraceutical investigations. Aging muscle fails on both fronts: satellite cells become less numerous and less responsive, and the Akt-mTOR axis becomes progressively resistant to the anabolic stimuli of food intake and exercise, a phenomenon sometimes called anabolic resistance. A compound that simultaneously supports the regenerative stem cell compartment and re-energizes protein synthesis signaling could, in principle, address both dimensions of sarcopenia. The authors suggest that boswellic acid warrants consideration as a nutraceutical agent to enhance muscle differentiation and hypertrophy, and as a potential novel therapeutic strategy for mitigating muscle aging.

Boswellic acid itself has a long pharmacological history. It is the principal bioactive component of frankincense, the resin of Boswellia serrata and related species, and has been studied extensively for its anti-inflammatory properties, particularly its inhibition of 5-lipoxygenase and its effects on inflammatory pathways relevant to arthritis and inflammatory bowel disease. This new study extends its potential repertoire into muscle biology, a domain more commonly occupied by compounds such as creatine, leucine, and other branched-chain amino acids, and by pharmaceutical agents under development for sarcopenia. The triterpenoid structure of boswellic acid allows it to interact with multiple signaling proteins, which may explain its pleiotropic effects across the myogenic program and the growth-factor cascade.

The authors are careful to frame the work within its in vitro limits. All experiments were conducted in murine cell cultures, and the physiological concentration, absorption, and tissue distribution of boswellic acid in living organisms remain open questions. Satellite cell behavior in aged muscle is shaped by a complex niche of inflammatory signals, extracellular matrix changes, and vascular decline that a simplified cell culture cannot fully reproduce. The researchers explicitly state that additional in vivo and clinical investigations are warranted before any therapeutic relevance can be established. Human trials would need to establish safe dosing, bioavailability, and whether oral supplementation can achieve tissue concentrations capable of activating the pathways observed in culture.

Even so, the study adds to a growing scientific effort to identify accessible dietary compounds that can bias the balance between muscle loss and muscle regeneration in favor of renewal. With sarcopenia estimated to affect a substantial share of adults over sixty and to drive frailty, falls, and loss of independence, the search for safe, well-tolerated interventions is intensifying. If future animal and human studies confirm the mechanisms reported here, boswellic acid, a molecule that humans have consumed for millennia in the form of frankincense, could emerge as an unusually well-characterized candidate for supporting muscle health across the lifespan. For now, the finding stands as a compelling proof of concept: an ancient resin component, examined with modern molecular tools, appears capable of speaking the native language of regenerating muscle.

Subject of Research: Effects of boswellic acid on myogenic and hypertrophic signaling in skeletal muscle cells as a potential strategy against muscle aging

Article Title: Boswellic acid modulates myogenic and hypertrophic signaling in vitro: implications for muscle aging

Article References: Pan, J., Dewi, L., & Yeh, T.-S. (2026). Boswellic acid modulates myogenic and hypertrophic signaling in vitro: implications for muscle aging. BMC Complementary Medicine and Therapies. https://doi.org/10.1186/s12906-026-05596-9

Image Credits: AI Generated

DOI: 10.1186/s12906-026-05596-9

Keywords: boswellic acid, satellite cells, sarcopenia, muscle aging, myogenesis, skeletal muscle hypertrophy, Akt-mTOR-p70S6K, myogenic regulatory factors, nutraceutical, C2C12 cells, muscle regeneration, frankincense

The research team, led by George Janssens and colleagues, set out to address two persistent questions in the biology of exercise and aging. First, how exactly does regular physical activity mitigate the molecular changes that accumulate in skeletal muscle as people grow older? Second, why do individuals of the same chronological age respond so differently to an acute bout of exercise? Both questions matter because exercise is widely regarded as one of the most effective interventions for healthy aging, yet the molecular mechanisms linking fitness level to exercise responsiveness have remained largely opaque.

To interrogate these questions, the investigators performed transcriptomics, lipidomics and metabolomics on skeletal muscle biopsies taken from young and older adults with differing levels of physical function. Crucially, each participant provided samples at rest and again after an acute bout of submaximal exercise, allowing the researchers to capture both the baseline molecular landscape of aging muscle and the dynamic response it mounts when challenged. This dual design made it possible to distinguish age-related changes that are fixed features of older muscle from those that are modified by long-term training.

At baseline, the comparisons between sedentary or normally active young and older participants told a familiar but important story. Older adults exhibited reduced expression of genes associated with cellular respiration and energy metabolism compared with young adults who maintained comparable levels of everyday physical activity. This transcriptional signature suggests a decline in the muscle’s intrinsic capacity for oxidative energy production, a change long suspected to underlie the reduced endurance and metabolic resilience that accompany aging. Because the young and older comparison groups had similar activity levels, the differences pointed to aging itself, rather than lifestyle alone, as the driver of the energy-metabolism decline.

The most striking result emerged when the researchers examined older adults who had undertaken sustained physical training. In these trained older participants, approximately 50 percent of the age-related molecular differences observed at baseline were simply absent. Their muscle profiles resembled those of young adults across a substantial portion of the transcriptome and metabolome, indicating that long-term training does not merely slow functional decline but measurably rewrites the molecular age of the tissue. The authors describe this phenomenon as delayed molecular aging, and the preservation of energy-metabolism gene expression appears to be a central component of it.

Exercise training, in other words, seems to buffer the aging muscle against some of its most consequential losses. The genes that code for components of the respiratory chain, mitochondrial function and associated metabolic pathways—those most diminished in untrained older muscle—were maintained at levels much closer to those seen in young tissue. This suggests that the well-documented benefits of lifelong physical activity, from preserved strength to improved metabolic health, are rooted in a durable molecular reprogramming of the muscle itself rather than in compensatory mechanisms elsewhere in the body.

The study also captured what happens in muscle in the hours immediately following an acute bout of exercise. All participants, young and old, trained and untrained, displayed a clear transcriptional immune and stress response after the submaximal exercise challenge. This reaction, which involves the activation of stress-response pathways and immune-related signaling, is thought to be part of the adaptive process through which muscle remodels itself in response to exertion. What differed between individuals was the magnitude of that response: in older adults, the strength of the transcriptional reaction was positively correlated with their physical fitness. Fitter older individuals mounted a more vigorous molecular response to the same relative workload than their less fit peers.

This finding carries significant implications for understanding how exercise acts as a biological stimulus. Each bout of exercise is, in essence, a controlled perturbation that triggers repair and remodeling programs in muscle. If a fit older adult’s muscle responds more robustly to each bout, then over months and years of training the cumulative effect could compound, creating a feedback loop in which fitness begets stronger molecular responses, which in turn drive further adaptation. The results provide a molecular explanation for why maintaining training status into older age appears to preserve not just muscle function but the muscle’s very capacity to keep adapting.

Beyond the transcriptome, the integrated multiomic analyses uncovered a web of relationships connecting mitochondrial respiration, lipid metabolism, cellular stress responses and NAD+ biology. NAD+, a central coenzyme in cellular redox reactions and energy transfer, has become a major focus of aging research because its tissue concentrations decline with age, and the new data tie these NAD+-dependent processes directly to the exercise-responsive molecular programs in human muscle. The lipidomic and metabolomic layers of the dataset similarly linked shifts in fat metabolism to both mitochondrial performance and the stress response, reinforcing the idea that aging muscle is shaped by tightly coupled metabolic networks rather than isolated pathways.

Taken together, these findings demonstrate that sustained physical training transforms the age-related molecular profile of human skeletal muscle, and they establish what the authors describe as a molecular atlas for the study of fitness-dependent aging mechanisms. Such a resource gives researchers a reference map against which future interventions—new exercise regimens, nutritional strategies or pharmacological agents aimed at mimicking the benefits of training—can be benchmarked. If the molecular signature of the trained older muscle can be defined, it becomes a measurable target, not merely an abstraction.

The work also sharpens a message that has been emerging from epidemiology and physiology alike: chronological age and biological age are not the same thing, and lifestyle exerts a powerful influence over the gap between them. Half of the molecular hallmarks of aging measured in this study were erased by training, which is a remarkably large fraction given the multi-tissue, multi-decade nature of the aging process. While the study was observational in the sense that trained participants were compared across groups rather than randomly assigned to exercise interventions, the scale and depth of the molecular data make the association between long-term training and delayed muscle aging difficult to dismiss.

For clinicians and public health researchers, the correlation between fitness and exercise responsiveness adds a practical dimension. Physical fitness is not only an outcome of training but also, apparently, a determinant of how the body reads and responds to each new exercise stimulus. This supports the idea that preserving fitness through middle and older age has value that goes beyond current capacity—it maintains the machinery that allows future activity to keep delivering molecular benefit.

Future studies built on this atlas will likely explore how quickly these molecular changes reverse when training stops, which specific components of the response are driven by NAD+ availability, and whether the same patterns hold in other metabolically active tissues. For now, the study stands as one of the clearest demonstrations to date that the aging muscle is not on a fixed molecular timetable. With enough sustained training, a substantial share of the molecular decay of aging can be postponed, and the muscle of a 70-year-old can, in measurable ways, look and behave more like that of someone decades younger.

Aging, the authors emphasize, is not a single number. Chronological age tells us little about how quickly any one tissue or organ system is deteriorating, which is why researchers have increasingly turned to organ-specific “biological clocks.” Epigenetic clocks, which estimate biological age from patterns of DNA methylation, have dominated this field. But muscles—the largest organ in the body and the engine of functional autonomy—follow their own nonlinear trajectory, heavily influenced by lifestyle, nutrition, and physical activity. To capture this, the research team, led by Federico Frasca, Chiara Pappalettera, Alessia Cacciotti, and Fabrizio Vecchio of the Brain Connectivity Laboratory at IRCCS San Raffaele in Rome, together with colleagues at the University of Sassari, employed a previously developed “muscle phenotypic clock.” This regression-based model quantifies muscle age (MA) from the battery of functional assessments recommended by the revised European consensus on sarcopenia, EWGSOP-2, including anthropometric estimates of muscle mass, measurements of muscle strength, and motor performance tests such as gait and mobility evaluations.

The key derived quantity is muscle age acceleration (MAA)—the difference between a person’s estimated muscle age and their chronological age. A negative value signals decelerated muscle aging, meaning muscles functionally younger than expected; a positive value signals accelerated aging, a potential early warning sign on the road to sarcopenia, the age-related loss of muscle mass and function that affects a growing share of the world’s aging population. In the new study, participants—all healthy, neurologically intact older adults screened for cognitive impairment and other exclusion criteria—were stratified into three groups based on their MAA: decelerated, normal, and accelerated muscle aging.

To probe the brain side of the equation, each participant underwent eyes-closed resting-state EEG, a century-old technique whose spontaneous rhythms have proven remarkably informative about network-level brain health. The researchers computed magnitude-squared coherence (MSCoh), a frequency-resolved measure of how strongly oscillatory activity at pairs of cortical regions fluctuates in tandem, effectively an index of functional connectivity between brain areas. They then applied graph-theoretical analysis, computing node strength—the sum of a node’s connectivity weights across the whole network—to identify which cortical regions carried the largest differences between muscle-aging groups. Statistical testing used nonparametric permutation-based procedures of the kind standard in modern EEG network science, guarding against spurious findings across the many electrodes, frequency bands, and pairwise comparisons involved.

The results were striking in both direction and topography. Participants with decelerated muscle aging—those with the biologically youngest muscles—showed significantly lower coherence than both the normal and accelerated groups in the Alpha 1 (roughly 8–10 Hz), Alpha 2 (10–12 Hz), and Beta 1 (13–20 Hz) frequency bands. In other words, the parietal and frontal networks that generate these rhythms were less tightly synchronized in people whose muscles were aging slowly. Alpha oscillations are classically associated with the brain’s attentional gating and the efficient allocation of cognitive resources, while beta rhythms are deeply involved in sensorimotor control and the maintenance of the motor status quo; both bands are known to be altered in dementia and in normal aging, where coherence typically increases, a pattern interpreted by many groups as a sign of reduced neural flexibility or compensatory neural “crosstalk.”

The node strength analysis sharpened the picture further. The decelerated MA group showed lower node strength in the right frontal area across the Alpha 1, Beta 1, and Beta 2 bands, while the normal MA group showed lower values in the right temporal region compared with the accelerated MA group. The consistent involvement of right-hemispheric frontal and temporal hubs is noteworthy. Right frontal regions are central to attentional control and executive function, and their connectivity patterns change in characteristic ways with aging and neurodegeneration. The findings align with established models of age-related network reorganization, such as the HAROLD model of hemispheric asymmetry reduction, in which older adults recruit additional homotopic regions to sustain performance. In this framework, the increased synchronization seen in people with accelerated muscle aging may represent a less efficient, more rigid network configuration—perhaps an early neural correlate of the same processes that stiffen muscles and slow gait.

What mechanism could connect the biological age of muscle to the topology of brain networks? The authors and the broader literature point to several converging pathways. Skeletal muscle is not merely a mechanical engine; it is an endocrine organ that secretes myokines during contraction, molecules such as irisin and interleukin-6 variants that influence neuroplasticity, inflammation, and metabolism. Conversely, the corticospinal drive from the motor cortex shapes the very muscle activity that maintains muscle mass, and recent work has suggested that deteriorating corticospinal control may itself be a determinant of sarcopenia. Chronic low-grade inflammation—termed “inflammaging”—is a shared driver of both muscle wasting and cognitive decline, and clinical studies have repeatedly linked sarcopenia to white matter hyperintensities, cognitive impairment, and dementia risk. The new study is distinctive in that it avoids the confounding presence of diagnosed disease: all participants were healthy, meaning the brain-network differences reflect a graded, subclinical gradient of body-brain aging within the normal older population.

Methodologically, the study is notable for its attempt to quantify an organ’s biological age using purely phenotypic, clinically accessible measures. The muscle phenotypic clock, developed by the Sassari group in earlier cross-sectional work on middle-aged and older adults, was built with regularized regression techniques—the elastic net of Zou and Hastie, implemented in machine-learning toolchains such as scikit-learn—combining anthropometrics, bioelectrical estimates of skeletal muscle mass, grip strength and other strength measures, and standardized motor tests including the timed Up-and-Go and the six-minute walk protocol. Because these measures can be gathered in any geriatric clinic, the approach sidesteps the cost and invasiveness of epigenetic sequencing, raising the prospect that a routine functional assessment could one day yield both a muscle age score and, if corroborated by future work, a noninvasive window into brain network health.

The clinical implications cut in both directions. First, MAA could serve as a low-cost screening variable that flags older adults whose brain networks may already be drifting toward the hyper-synchronous patterns associated with cognitive vulnerability, well before symptoms appear. Second, and perhaps more provocatively, the findings suggest that interventions designed to slow muscle aging—progressive resistance training, adequate protein intake, physical activity programs—might do double duty by favorably reshaping brain connectivity. Previous EEG studies have shown that resting-state connectivity predicts motor skill learning and responds to rehabilitation after stroke, and integrated motor-cognitive training programs are increasingly advocated for frail older adults. If muscle age acceleration truly shapes brain network topography, then redirecting that trajectory becomes not merely a matter of preserving mobility but of protecting the brain itself.

The authors are careful to frame the study as hypothesis-generating. It is cross-sectional, so causality cannot be established: accelerated muscle aging might drive brain changes, brain changes might drive muscle decline, or a third factor such as systemic inflammation might drive both. The cohort, while carefully characterized, is limited in size, and EEG coherence reflects only cortical, predominantly radial, current sources rather than the full three-dimensional complexity of brain network dynamics. Longitudinal studies tracking MAA and EEG networks in the same individuals over years, ideally combined with measures of cognitive trajectory and blood-based biomarkers, will be needed to determine whether the muscle clock can predict future brain decline and whether interventions that decelerate muscle aging produce measurable, beneficial shifts in resting-state connectivity.

Even with those caveats, the study lands at a moment of intense interest in biological age clocks and in the muscle–brain axis. The idea that “muscle age” is not just a poetic phrase but a quantifiable, clinically meaningful variable—one that leaves an electrical signature in the resting brain—is likely to energize both the geroscience and neurorehabilitation communities. For a global population aging at unprecedented speed, the promise of a single clinic visit that yields a muscle age, an early read on brain network health, and a personalized prescription of exercise and nutrition is an alluring one. This study offers the first EEG-based evidence that the trajectory of muscle aging and the architecture of resting brain networks are systematically intertwined in healthy older people, and it points toward an era in which keeping the body’s largest organ young may be among the most effective strategies for keeping the brain young too.