The scientific foundation for this work was laid two decades ago. In 2006, Shinya Yamanaka demonstrated that over-expressing just four transcription factors, now universally known as the Yamanaka factors, could reprogram mature cells all the way back to a pluripotent, embryonic-like ground state. The discovery earned a Nobel Prize and reshaped developmental biology. What followed was an even more tantalizing observation for aging researchers: when the Yamanaka factors are expressed only in short, carefully timed bursts, they can partially reprogram old cells into a more youthful condition, reversing multiple hallmarks of aging while the cells retain their specialized functions. The implication was profound. Aging, it seemed, does not have to be a one-way street, and even old cells retain a latent capacity for rejuvenation that modern biology might learn to unlock.

Yet the therapeutic promise of the Yamanaka factors has always been shadowed by a serious risk. Because these factors can drive cells all the way back to a pluripotent state, their over-expression raises the danger of cancer formation, and controlling exactly how far the reprogramming proceeds remains a formidable technical challenge. Alex Plesa, a scientist at the Wyss Institute and first co-author of the new study, framed the dilemma succinctly: in reprogramming, there is a fundamental tradeoff between rejuvenation and cell identity, and achieving one without losing the other requires walking a fine line. That tradeoff has motivated a worldwide search for alternative factors that might rejuvenate aging tissues in safer and more controllable ways, and it is precisely this search that the Harvard-led team set out to systematize.

Their first challenge was measurement. How do you score rejuvenation reliably enough to screen hundreds of candidate genes? The most widely used tool, the epigenetic aging clock, reads chemical modifications to the genome that accumulate with age. But as Plesa explained, that approach does not scale well to screening because of high costs and the difficulty of interpreting its widespread changes. Instead, the team reasoned that any genuine rejuvenation process must ultimately manifest itself in altered gene expression programs that restore more youthful cellular functions. Gene expression, they concluded, was the right readout. Working with Antonio del Sol, an Ikerbasque Research Professor at CIC bioGUNE-BRTA in Spain, and postdoctoral fellow Sascha Jung, the study’s co-first author, they built a machine learning algorithm trained on transcriptomic profiles spanning multiple aging processes in human skin fibroblast cells from donors across a wide age range.

The resulting tool, which the team calls a transcriptomic aging model, functions something like a set of odometers for different parts of a car. It tracks changes in the expression of genes involved in distinct biological processes and integrates them into a single accurate overview of a cell’s age and health. Trained on gene expression data from 464 fibroblast samples, the model could pinpoint the transcriptomic age of skin cells from individual donors. Crucially, it also proved sensitive to real biological change: when the researchers treated fibroblast cell lines derived from donors aged 55, 65, and 79 with experimental lifespan-altering interventions, including the Yamanaka factors, the predictor accurately registered the resulting shifts in transcriptomic age. The team now had a scorable, quantitative yardstick for rejuvenation.

With that yardstick in hand, the researchers assembled a focused library of genes predicted to influence aging processes and over-expressed each one in aged fibroblast cell lines, hunting for candidates that could shift the cells’ aging score toward a more youthful value. One gene rose decisively to the top: SRSF1, which encodes an RNA processing factor. Over-expression of SRSF1 reduced features corresponding to several recognized hallmarks of aging, including cellular senescence, the state in which damaged cells stop dividing but refuse to die; proteostatic stress, a disruption of the normal balance and turnover of proteins; and inflammaging, the chronic low-grade inflammation that accompanies aging. The rejuvenation effects also registered on the conventional epigenetic aging clock and extended to the restoration of DNA repair programs, suggesting a broad and genuine reversal of age-associated molecular damage.

Just as important as what changed was what did not. The rejuvenated fibroblasts maintained their identity throughout the intervention. They kept their characteristic spindle-shaped morphology, continued expressing the genes that encode typical fibroblast functions, and did not activate the pluripotency programs that Yamanaka factors switch on. In other words, SRSF1 appears to rejuvenate cells by working through machinery that all cells already use, rather than overriding their identity, which is exactly the property that makes it a safer candidate for therapy than the pluripotency factors. As Plesa put it, the team worked on the premise that over-expressing a single gene with validated rejuvenation outcomes could eventually be advanced into an organ- or tissue-specific gene therapy if combined with the right delivery system.

The decisive test came in living animals. The researchers packaged the SRSF1 gene into a liver-tropic adeno-associated virus, or AAV, a widely used gene delivery vehicle, and treated aged mice. The gene primarily accumulated in the animals’ livers, and the results were remarkable on two fronts. First, the livers themselves showed signs of rejuvenation. Second, and more strikingly, the benefits were systemic: SRSF1-treated animals grew frail more slowly than controls and lived longer, with median lifespan extended by 14 percent. That a single RNA processing factor, delivered mainly to one organ, could slow the aging of the whole organism positions SRSF1 as what the researchers call a geroprotective target, and it hints that rejuvenation programs initiated in one tissue may be communicated and amplified throughout the body.

Exactly how SRSF1 accomplishes its multifaceted effects remains an open and actively pursued question. The protein’s best-known role is that of an RNA splicing factor, one that helps include alternative exon sequences in a subset of mature messenger RNA molecules. These alternatively spliced mRNAs are then translated by ribosomes into proteins with altered functions, effectively allowing one gene to produce a repertoire of protein variants. The team observed a strong trend of alternatively spliced mRNAs following SRSF1 over-expression, but as Plesa acknowledged, they are only just beginning to understand how these splicing changes bring about the multi-faceted rejuvenation program in tissues. Unraveling that mechanism could reveal additional targets and open entirely new avenues for intervention.

For George Church, the Wyss Institute core faculty member and Professor of Genetics at Harvard Medical School who led the study, the work represents a step toward a long-standing ambition: devising clinically useful de-aging strategies by identifying genes that, when engineered for under- or over-expression in aging target tissues, extend human health-span. In his view, aging research is transiting an inflection point where exponential progress in biotechnology is beginning to impact the core aging processes that would otherwise kill 90 percent of us. Significant hurdles remain before SRSF1 could reach the clinic, particularly around delivery and dosing, and further research into its systemic effects is clearly needed. But the study demonstrates something once thought impossible: that a precisely targeted gene, measured against a rigorous transcriptomic yardstick, can turn back key aspects of the aging clock in cells and in a living mammal, without sacrificing what those cells are meant to be.

Subject of Research: Gene expression reprogramming to reverse cellular and organismal aging using the RNA splicing factor SRSF1

Article Title: Reversing age by reprogramming gene expression networks

Article References: Reversing age by reprogramming gene expression networks. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: aging, rejuvenation, SRSF1, gene expression, transcriptomic aging clock, Yamanaka factors, cellular senescence, RNA splicing, gene therapy, lifespan extension, machine learning, geroprotection

The study began with a computational foundation. The researchers built an interpretable transcriptomic age predictor specifically calibrated in human fibroblasts, the connective tissue cells that have long served as a workhorse of aging research. Drawing on transcriptomes from 133 donor lines spanning ages 1 to 96 years, the model distilled aging down to 292 genes whose activity tracks the passage of biological time. These genes cluster into recognizable biological processes, including WNT signaling, translation initiation, actin organization, histone methylation, and endoplasmic reticulum stress. Importantly, the model captured distinct kinetic patterns of aging: some processes, such as ER quality control and translation initiation, decline steadily and continuously with age, while others, like histone methylation and actin polymerization, respond late and exponentially, and still others, such as sodium transport, follow a biphasic trajectory. This architecture gave the team a quantitative yardstick for biological age that could be applied to any fibroblast sample.

With the age predictor in hand, the researchers turned to an unbiased search for factors capable of turning back the transcriptomic clock. They assembled a library of 95 plasmids for overexpression screening: 89 candidate genes prioritized through a network-based approach that combined protein-protein interaction data from the STRING database with the strength of age-associated expression changes, plus five known aging modulators including ATG5, CXCR2, HES1, KAT7, and the OSKM reprogramming cocktail, along with a blue fluorescent protein control. Each candidate was introduced into aged fibroblasts, and the resulting transcriptomes were scored by the age predictor. The screen’s standout hit was SRSF1, a well-known splicing factor that binds RNA and controls how messenger RNA transcripts are cut and pasted together before they are translated into protein. When SRSF1 was induced in aged fibroblast lines, the cells’ predicted transcriptomic age dropped by a median of 16.2 years after just three days of expression, a striking and technically reproducible rejuvenation effect.

What makes this result particularly notable is what did not happen. Partial reprogramming with OSKM factors is famously accompanied by dramatic morphological changes: fibroblasts lose their characteristic spindle shape, shrink in size, and drift toward pluripotency programs, raising the specter of uncontrolled cell growth. In the new study, OSKM expression produced exactly these changes by day three of induction, and even short one-to-three-day inductions left lasting positive age shifts of more than 37 to 54 years in some donor lines after the factors were withdrawn. SRSF1-expressing cells, by contrast, retained their spindle-shaped fibroblast morphology and cell body area throughout induction, showed no sustained age shifts after doxycycline withdrawal, and did not activate pluripotency programs. The rejuvenation was also confirmed with an orthogonal measurement: the Skin and Blood DNA methylation clock, an entirely independent biomarker of aging based on chemical tags on the genome rather than gene expression, also registered reduced age in SRSF1-treated cells.

At the functional level, SRSF1 induction produced a multidimensional rejuvenation across molecular hallmarks of aging. In aged fibroblasts, the factor reduced senescence, the state of permanent growth arrest that accumulates in aging tissues and secretes inflammatory signals; it eased proteostatic stress, the burden of misfolded and damaged proteins; and it dampened inflammatory signaling pathways. When delivered as synthetic mRNA rather than DNA, SRSF1 significantly reduced senescence-associated beta-galactosidase activity, a classic marker of cellular aging, in both young and old donor cell cohorts. The factor also improved stress resilience: aged fibroblasts carry roughly 64 percent higher levels of reactive oxygen species after a hydrogen peroxide challenge than young cells, and SRSF1 treatment trended toward reducing this oxidative burden. Collagen synthesis, which declines modestly with age, increased by about 14 percent in aged cells treated with SRSF1, and the treated cells showed a tendency toward faster closure of scratch wounds in vitro, a measure of regenerative capacity.

The critical question was whether these cellular effects would translate into benefits in living animals. To test this, the team used inducible viral delivery, packaging the Srsf1 gene into adeno-associated virus vectors under the control of a doxycycline-activated Tet-On system, allowing them to switch expression on and off in aged mice. The results were remarkable: inducible SRSF1 expression reduced the progression of frailty, a composite measure of age-related decline in strength, endurance, and health, by 44 percent, and was associated with a 14 percent extension of median lifespan, with 9 to 10 mice per group. Sustained frailty onset, defined as a frailty index exceeding 0.18, was delayed by approximately 123 days in the SRSF1-treated animals. In skin wound-healing experiments, wounds in aged mice closed significantly faster with SRSF1 expression, reaching a partial restoration of the regenerative capacity seen in young animals, although the effect depended on the delivery regimen and was not observed with all expression strategies.

Molecular analysis of the treated mice revealed that SRSF1’s benefits extended across tissues. In the liver, SRSF1 expression reduced epigenetic age acceleration as measured by an intervention-optimized DNA methylation clock, shaving off about half a year of apparent age. Gene set enrichment analysis across tissues showed that SRSF1 modulated pathways involved in bioenergetics, immune signaling, and cellular homeostasis, and many of these processes were classified as age-opposing when compared against the Tabula Muris Senis reference atlas of mouse aging. Strikingly, a cross-species comparison revealed shared signatures between SRSF1-treated human fibroblasts and mouse liver tissue, including reduced stress response, reduced inflammation, and altered cell adhesion and cell cycle programs, suggesting that the factor acts through conserved longevity pathways rather than species-specific mechanisms.

The evolutionary conservation of this pathway received direct experimental support from studies in the roundworm Caenorhabditis elegans. The worm homolog of SRSF1 is a gene called rsp-3, and when the researchers knocked it down with RNA interference in long-lived raga-1 mutant worms, a strain in which the nutrient-sensing mTOR pathway is dampened, the worms’ characteristic lifespan extension was suppressed. The result, confirmed in independent repeats with 120 to 159 worms per group, places SRSF1 squarely within one of the most intensively studied longevity networks in biology, the same nutrient-sensing axis targeted by rapamycin and dietary restriction. It also connects the new findings to an older body of evidence showing that splicing factor expression changes with age in both mice and humans, and that variations in splicing factor transcripts correlate with lifespan.

SRSF1 is not an obvious anti-aging target. The factor has a well-documented dual personality: it is essential for normal cell function, governing progenitor-specific alternative splicing in epithelial tissues and acting as a master switch of gene expression in the immune system, but it is also a known proto-oncogene whose overexpression is associated with cancer cell biology. The authors and several coauthors are listed as inventors on a patent application covering the therapeutic use of SRSF1 and related factors, and two of them are cofounders of an early-stage company developing therapeutics for age-related diseases, disclosures that underscore the translational ambition behind the work. The tension between geroprotection and oncogenesis will need careful resolution, and the mouse data, while encouraging, come from relatively small groups and a defined delivery system.

Nevertheless, the study represents a conceptual advance in how rejuvenation targets are found. Rather than starting from the Yamanaka factors and trying to make them safer, the team started from a quantitative definition of the aged state and screened for any gene that could reverse it while preserving cell identity. The answer, an RNA-binding splicing factor rather than a transcription factor, suggests that the aging transcriptome may be held in an aged configuration partly at the level of RNA processing, and that correcting the splicing machinery can ripple outward to restore youthful patterns of gene expression, protein homeostasis, and tissue function. If the findings hold up in larger animal studies and can be delivered safely, SRSF1 and the screening platform that uncovered it could open a new chapter in the search for interventions that extend not just lifespan, but the healthy years of human life.

Subject of Research: Identification of the splicing factor SRSF1 as a conserved regulator of aging through transcriptomic reprogramming screens

Article Title: Transcriptomic reprogramming screen identifies SRSF1 as a regulator of aging

Article References: Plesa, A. M., Jung, S., Wang, H. H., Omar, F., Shadpour, M., Choy Buentello, D., Perez-Matos, M. C., Horwitz, N., Cai, G., Ngian, Z. K., Magalhaes, C., Wagers, A. J., Mair, W. B., del Sol, A., & Church, G. M. (2026). Transcriptomic reprogramming screen identifies SRSF1 as a regulator of aging. Nature Aging, 6(10), 2057-2073. https://doi.org/10.1038/s43587-026-01234-8

Image Credits: AI Generated

DOI: 10.1038/s43587-026-01234-8

Keywords: SRSF1, aging, transcriptomic clock, partial reprogramming, splicing factor, senescence, geroprotection, lifespan extension, C. elegans, frailty, gene expression, epigenetic clock

The stakes are considerable. Osteoarthritis affects an estimated 7 to 8 percent of the global population, while rheumatoid arthritis invades roughly 0.2 to 1 percent of people worldwide. Both conditions become more prevalent with age, and researchers increasingly view aging itself as an underlying hallmark of arthritis progression. As life expectancy rises and the aged population grows exponentially across the globe, the search for therapies that can protect aging joints has become a central concern of biomedical research, a field known as geroprotection.

Current treatment options leave much to be desired. Non-steroidal anti-inflammatory drugs, the mainstay of symptomatic relief, are widely regarded as a secondary treatment option because of their high cost, inadequate pharmacological action in many patients, and well-documented adverse effects ranging from gastrointestinal bleeding to kidney damage. There is no cure for either osteoarthritis or rheumatoid arthritis, and despite decades of research into their pathogenesis, efficient curable approaches remain challenging. This therapeutic gap has driven a demographic shift toward polyherbal medicines, particularly formulations designed to inhibit pro-inflammatory cytokines, the signaling molecules that drive joint destruction.

Triphalaguggul is precisely such a formulation. Triphala, a balanced combination of the fruits of three plants, has long been used in Indian systems of medicine as a rejuvenating tonic, and prior studies have shown that Triphala herbal extract can suppress inflammatory responses in macrophages and in arthritic rats by inhibiting the NF-κB pathway. Guggul, the resin of Commiphora wightii, contributes guggulsterones and other phytochemicals with documented anti-inflammatory properties. The research team hypothesized that combining these ingredients would target the downregulation of pro-inflammatory cytokines and their signaling pathways, addressing the molecular engine of arthritis rather than merely its symptoms.

To test this, the researchers ran two complementary disease models in rats. Osteoarthritis was induced by intra-articular injection of monosodium iodoacetate, a compound that selectively kills chondrocytes, the cartilage-producing cells of the joint, and thereby mimics the progressive cartilage degradation seen in human osteoarthritis. Rheumatoid arthritis was modeled using complete Freund’s adjuvant, an immunological challenge that triggers chronic, systemic joint inflammation resembling the autoimmune attack characteristic of rheumatoid arthritis. Alongside these efficacy studies, the team conducted toxicological evaluations to establish the safety profile of the formulation.

The results were dramatic. In the osteoarthritis model, Triphalaguggul reduced inflamed knee measurements by 96.15 percent and paw edema by 95.18 percent. Perhaps more importantly, histological examination showed that the treatment helped chondrocytes regrow and rearrange themselves properly within the damaged cartilage, suggesting genuine structural repair rather than simple suppression of swelling. In the rheumatoid arthritis model, blood chemistry markers that typically spike during active disease were brought back into line. Elevated levels of the liver enzymes SGPT and SGOT, alkaline phosphatase, C-reactive protein, and rheumatoid factor were all reinstated to their normal ranges after treatment, with statistical significance at p < 0.05.

The molecular story behind these outcomes centers on three cytokines: interleukin-6, tumor necrosis factor-alpha, and interleukin-1 beta. These pro-inflammatory messengers are central to the pathology of both joint diseases. In osteoarthritis, they drive the catabolic cascade that degrades cartilage matrix; in rheumatoid arthritis, they orchestrate the autoimmune inflammation that erodes bone and synovium. Using enzyme-linked immunosorbent assays, the team showed that levels of all three cytokines, which had risen sharply in the arthritic animals, fell significantly after Triphalaguggul treatment.

Downstream of these cytokines lie two of the most important signaling highways in inflammation biology: the JAK/STAT pathway and the NF-κB pathway. When interleukin-6 or related cytokines bind their receptors, they activate Janus kinase 2, which in turn phosphorylates the transcription factor STAT3, sending it into the nucleus to switch on inflammatory genes. In parallel, the p65 subunit of nuclear factor kappa B translocates to the nucleus to activate another battery of inflammatory genes, including those encoding cytokines themselves, creating a self-amplifying loop. The researchers found that the enhanced expression of phosphorylated JAK2, phosphorylated STAT3, and NF-κB p65 seen in arthritic rats was significantly downregulated after treatment. These findings were validated by two independent techniques, western blotting, which quantifies protein abundance, and immunohistochemistry, which maps protein localization within tissue sections, lending robustness to the conclusion.

By demonstrating that a single polyherbal formulation can simultaneously quiet cytokine production and dampen both major inflammatory signaling cascades, the study positions Triphalaguggul as a candidate geroprotective therapy, one that targets pro-inflammatory cytokines and the JAK/STAT and NF-κB pathways as therapeutic biomarkers of aging-related joint disease. The framing matters: rather than treating osteoarthritis and rheumatoid arthritis as separate problems, the work treats chronic low-grade inflammation as a shared molecular thread running through aging and arthritis alike, and proposes that pulling that thread with a well-characterized herbal mixture could protect against geriatric disease more broadly.

Substantial caveats remain before this ancient formula reaches modern pharmacies. The evidence comes entirely from chemically induced rat models, which reproduce key features of human joint disease but do not capture its full complexity, and dose translation between laboratory animals and humans is a well-known hurdle in preclinical drug development. Human clinical trials, standardization of the formulation, and pharmacokinetic characterization of its active constituents will all be required. Still, the study adds rigorous molecular data to a growing body of literature on traditional herbal medicines, from curcumin to guggulsterones, that modulate exactly the inflammatory pathways targeted by modern biologics. For the millions of people whose aging joints ache with inflammation, the possibility that a validated, affordable, and safe botanical alternative could emerge from a millennium-old prescription is a prospect worth watching closely.

Subject of Research: Anti-arthritic and geroprotective effects of the polyherbal formulation Triphalaguggul on cytokine signaling in rat models of osteoarthritis and rheumatoid arthritis

Article Title: Geroprotective efficacy of Triphalaguggul: a polyherbal formulation against inflammatory disorders through inhibition of pro-inflammatory cytokines as therapeutic biomarkers

Article References: Dey, A., Datta, S., Gupta, M., Chattapadhyay, H., & Sahoo, P. K. (2026). Geroprotective efficacy of Triphalaguggul: a polyherbal formulation against inflammatory disorders through inhibition of pro-inflammatory cytokines as therapeutic biomarkers. Biogerontology, 27(5), Article 176. https://doi.org/10.1007/s10522-026-10519-9

Image Credits: AI Generated

DOI: 10.1007/s10522-026-10519-9

Keywords: Triphalaguggul, osteoarthritis, rheumatoid arthritis, pro-inflammatory cytokines, JAK/STAT pathway, NF-κB, Ayurveda, guggul, Triphala, geroprotection, rat models, IL-6

The discovery did not begin with a hypothesis about any particular bacterium. Instead, the researchers built AURORA, a generative artificial intelligence framework that integrates multiple data modalities, including metagenomic sequences, plasma metabolomics, gene expression and physiological measurements, into a unified model of human aging. Within this framework, the team constructed multi-modality aging clocks, statistical models that estimate a person’s biological age from molecular and phenotypic features, and then used the model to perform in silico screening: systematically simulating thousands of potential interventions to identify which changes would most effectively reduce the gap between predicted biological age and chronological age.

That computational screen produced an unexpected front-runner. When the abundance of Neisseria flavescens was virtually increased in the model, the predicted age gap shifted in a favorable direction, and the simulated perturbation also produced beneficial changes in physiological signatures, promoted the abundance of known health-associated gut taxa and enhanced the biosynthesis of metabolites with documented benefits. In a natural human aging cohort, individuals classified as slow agers, whose biological clocks ran younger than their chronological years, carried significantly more of this oral species than fast agers. The association was replicated in longitudinal data tracking one-year changes in bacterial abundance against changes in the aging measure.

To move beyond correlation, the team isolated two live strains of N. flavescens, designated a11 and e5, from human donors and sequenced their genomes, which have been deposited under the accessions GWHHOEZ01000000 and GWHHOEA01000000. Laboratory analysis confirmed that both strains actively produce vitamins and other beneficial metabolites predicted by the computational framework. Targeted mass spectrometry of bacterial culture supernatants verified the metabolic output, providing a mechanistic bridge between the human association data and the biological activity of the organism itself.

The first functional test took place in Caenorhabditis elegans, the transparent roundworm that has long served as a workhorse of aging research. When worms were fed live N. flavescens instead of their standard laboratory diet of Escherichia coli OP50, their lifespans lengthened and their healthspans, the portion of life spent in good condition, improved. Supplementation also attenuated the age-related decline in mobility during early adulthood and altered body size, with independent replication experiments confirming the lifespan extension for both strains. Heat-killed bacteria likewise preserved worm mobility, hinting that structural components of the microbe, rather than only its living metabolic activity, may contribute to the effect.

In aged mice, the researchers turned to heat-killed N. flavescens, a form of supplementation that avoids the safety considerations of administering a live organism. After ten weeks of treatment, the animals’ serum metabolome, liver transcriptome and gut microbiome all shifted measurably toward younger profiles. Principal-component analyses showed that the metabolic and transcriptional states of treated twenty-month-old mice moved closer to those of young two-month-old controls, and regression analysis demonstrated that treatment-associated fold changes across metabolites, microbial species, microbial pathways and liver transcripts tended to oppose the changes normally driven by aging itself. The effect was partial rather than a wholesale reversal, but the consistent directional rescue across three distinct molecular layers is striking.

The study also addressed how an oral bacterium could plausibly influence systemic aging. Paired analyses of oral and gut microbiome data, including paired samples from the Human Microbiome Project, revealed links between N. flavescens abundance and the composition of the gut ecosystem, including associations with Akkermansia muciniphila, a gut bacterium widely studied for its beneficial effects on metabolic health and barrier function. Predicted downstream effects included changes in immune signaling pathways in peripheral blood mononuclear cells, suggesting a route by which oral microbial signals propagate through host metabolism and immunity rather than acting locally in the mouth alone.

Technically, the work represents a notable advance in how candidate interventions are identified. Traditional microbiome-aging studies typically search for correlations between individual taxa and chronological age or survival, an approach that the authors note would not have singled out N. flavescens as a top hit in their own data. By instead simulating perturbations within a generative model trained on multi-omics data, AURORA can prioritize organisms whose expansion is predicted to shift the entire aging state favorably, a logic closer to a causal intervention than a population association. The framework and all analysis code are freely available, and the underlying sequencing datasets have been deposited in public repositories under BioProject PRJCA057750 and associated accessions.

Important caveats remain. The human evidence is associative, the mouse experiments used heat-killed preparations whose active components have not yet been identified, and no human intervention trial has been conducted. A patent covering N. flavescens and its applications is pending, filed by two of the authors, which signals commercial interest but also that translational development is still at an early stage. Even so, the convergence of computational prediction, human cohort data, worm lifespan experiments and mouse molecular rescue makes a compelling case that the mouth, a microbiome site routinely dismissed as merely a gateway to dental disease, deserves far more attention in geroscience. If the findings hold up in further studies, the next geroprotective intervention might not come from a laboratory-synthesized molecule but from a common commensal already living between our teeth.

Subject of Research: Identification of the oral commensal Neisseria flavescens as a geroprotective microbe linked to decelerated human aging

Article Title: Multi-modality profiling identifies Neisseria flavescens as a central geroprotective oral commensal in humans

Article References: Chen, J., Ren, Y., Zhou, Y., Wang, Z., Li, J., Guo, X., Xu, H., Wang, Y., Tang, H., & Han, J.-D. J. (2026). Multi-modality profiling identifies Neisseria flavescens as a central geroprotective oral commensal in humans. Nature Aging. https://doi.org/10.1038/s43587-026-01220-0

Image Credits: AI Generated

DOI: 10.1038/s43587-026-01220-0

Keywords: aging, oral microbiome, Neisseria flavescens, AURORA, geroprotection, aging clocks, multi-omics, Caenorhabditis elegans, gut microbiome, probiotics, longevity, metabolomics

Immunosenescence is far more than a simple decline in immune vigor. It is a sweeping remodeling of both the innate and adaptive arms of immunity, marked by a shrinking pool of naive T cells, an accumulation of exhausted memory cells, a narrowing of T-cell receptor diversity, and a chronic, low-grade inflammatory state often called inflammaging. These changes are closely tied to impaired immunometabolism, mitochondrial dysfunction, and shifts in key signaling networks, including the AMPK/mTOR axis, the NF-kappaB pathway, autophagy, and the NLRP3 inflammasome. Because no single molecular defect drives the process, the authors contend that a multi-target agent may be better suited to intervene than highly specific drugs aimed at one pathway at a time.

Berberine, an isoquinoline alkaloid extracted from plants such as Berberis vulgaris, has been used in traditional Chinese and Ayurvedic medicine for centuries. Modern pharmacology has mapped an impressive array of its molecular actions: it activates AMP-activated protein kinase (AMPK) partly by inhibiting mitochondrial respiratory complex I, suppresses mTOR signaling, modulates NF-kappaB-driven inflammation, promotes autophagy, and inhibits NLRP3 inflammasome activation. Each of these targets sits squarely at the intersection of the pathways that go awry during immunosenescence. Clinical evidence already supports berberine’s benefits in cardiometabolic disease, including type 2 diabetes, nonalcoholic fatty liver disease, and metabolic syndrome, and a phase 2 trial of berberine ursodeoxycholate showed proof of concept in patients with non-alcoholic steatohepatitis and type 2 diabetes.

The review assembles evidence from cellular, animal, and early human studies that speaks directly to immune aging. In cell culture, berberine suppresses gero-conversion, the transition from reversible cell-cycle arrest to full senescence, and protects cells from oxidative stress-induced senescence through AMPK activation, restoration of autophagic flux, and elevation of intracellular NAD+. In mice, the compound ameliorates cellular senescence and extends lifespan by regulating p16 and cyclin protein expression. In simpler organisms, berberine prolongs lifespan and stimulates locomotor activity in Drosophila melanogaster and extends lifespan in Caenorhabditis elegans through multi-target antioxidant effects and ROS-dependent activation of the PMK-1/SKN-1 stress-response pathway.

Particularly relevant to immune aging are berberine’s documented effects on inflammatory signaling. The compound inhibits LPS-induced inflammatory responses through the NF-kappaB pathway, blocks NLRP3 inflammasome activation in macrophages by triggering autophagy and regulating the mTOR/mitochondrial ROS axis, and reduces SASP-related inflammation through the RXRalpha/PPARgamma/NEDD4 pathway in models of atherosclerosis. It also modulates sirtuin 1 activity, a deacetylase implicated in immune cell longevity, and enhances innate antiviral defenses via the p38 MAPK pathway, with demonstrated anti-influenza activity in mice. Because the senescence-associated secretory phenotype, or SASP, is a major driver of chronic age-related inflammation, a drug that dampens SASP output while simultaneously supporting autophagy and mitochondrial quality control addresses several hallmarks of immune aging at once.

The review also highlights a newer generation of berberine derivatives engineered to overcome the parent compound’s most stubborn limitation: poor oral bioavailability. Berberine is poorly absorbed from the gut, relies partly on gut microbiota transformation into the intestine-absorbable form dihydroberberine, and is subject to efflux by P-glycoprotein. Chemists have responded with 8,8-dimethyldihydroberberine, 9-O-substituted and 9-N-alkyl derivatives, liposomal and nanoparticle formulations, and self-microemulsifying delivery systems, all of which improve absorption in animal or human studies. Some derivatives add entirely new capabilities: a 13-decyl berberine derivative has been described as a novel mitochondria-targeted antioxidant and potent inhibitor of ferroptosis, while tetrahydroberberrubine retards heart aging in mice by promoting PHB2-mediated mitophagy, and berberrubine-based mitorubin compounds improve mitochondrial function and protect against age-related cardiac dysfunction.

Yet the authors are careful to temper enthusiasm with critical caveats. Much of the immunosenescence-relevant evidence comes from in vitro work or from animal models whose immune systems differ substantially from aged humans. Direct clinical trials testing berberine specifically against immunosenescence biomarkers, such as T-cell receptor repertoire diversity, p16INK4a expression in peripheral blood T cells, senescence-associated beta-galactosidase in CD8+ T cells, or inflammatory aging clocks like iAge, have not been performed. Safety considerations also warrant attention: berberine inhibits cytochrome P450 enzymes in humans, raising drug-interaction risks, and it has been shown to alter blood levels of immunosuppressants such as cyclosporin A in transplant recipients. Its interaction with the adenine nucleotide translocator and complex I inhibition, while mechanistically central to AMPK activation, could be a double-edged sword in metabolically stressed immune cells.

To move the field forward, the review proposes a framework for future studies. The authors call for properly designed experiments in aged animal models that measure established immunosenescence biomarkers rather than generic inflammation endpoints, followed by carefully monitored human trials in older populations. They emphasize the value of modern immune-aging metrics, including single-cell immune aging clocks that capture inter-individual heterogeneity during infection and vaccination, and suggest that derivatives with improved bioavailability and mitochondrial targeting should be prioritized. Vaccine responsiveness in the elderly, which is notoriously blunted and linked to T-cell autophagy decline, is identified as a clinically meaningful outcome that a berberine-based intervention could plausibly improve.

The broader significance of the analysis lies in its reframing of an old herbal medicine as a systems-level geroprotector. Where most anti-aging pharmacology pursues single targets, berberine’s pleiotropy, acting simultaneously on energy sensing, inflammatory transcription, autophagy, inflammasome activity, and mitochondrial function, mirrors the interconnected nature of immune aging itself. Whether that pleiotropy translates into safe and measurable rejuvenation of the human immune system remains an open question, but the review provides the mechanistic rationale and the experimental roadmap needed to find out. If subsequent trials validate the promise, a compound once confined to traditional apothecaries could become a cornerstone of interventions designed to keep aging immune systems, and the aging populations they protect, healthier for longer.

Subject of Research: Evaluation of berberine and its derivatives as multi-target modulators of age-related immune system decline (immunosenescence).

Article Title: Berberine and its derivatives as candidate modulators of immunosenescence: a critical evaluation

Article References: Zinovkin, R. A., Lyamzaev, K. G., Churov, A., Maltseva, O., & Wu, Z. (2026). Berberine and its derivatives as candidate modulators of immunosenescence: a critical evaluation. Biogerontology, 27(5), Article 153. https://doi.org/10.1007/s10522-026-10504-2

Image Credits: AI Generated

DOI: 10.1007/s10522-026-10504-2

Keywords: berberine, immunosenescence, aging, AMPK, mTOR, NF-kappaB, autophagy, NLRP3 inflammasome, inflammaging, mitochondria, berberine derivatives, geroprotection

The logic behind the approach rests on a decade of progress in proteomics, the large-scale study of the protein complement of biological systems. Unlike the genome, which is essentially fixed at conception, the proteome is dynamic: it shifts with infection, stress, exercise, disease, and, crucially, with age itself. Researchers have shown that machine-learning models trained on thousands of plasma protein measurements can predict chronological age with remarkable accuracy, and that the difference between predicted and actual age—sometimes called proteomic age acceleration—correlates with frailty, multimorbidity, and mortality risk. These proteomic clocks are conceptually analogous to the epigenetic clocks based on DNA methylation that transformed aging research in the 2010s, but they offer distinct advantages for interventional trials: blood proteins are readily sampled repeatedly, they respond to physiological change on shorter timescales than DNA methylation marks, and many of the proteins involved are themselves drug targets or biomarkers already familiar to the pharmaceutical industry.

What the new study demonstrates is that this technology can survive contact with the realities of clinical trial design. The researchers integrated multiple proteomic aging clocks into the analytical framework of a phase 2a trial, the earliest stage at which a therapeutic candidate is tested in patients or at-risk volunteers to gather preliminary evidence of biological activity. Rather than treating biological age estimation as an exploratory afterthought, the team built the clocks into the statistical evaluation plan from the outset, defining in advance how changes in proteomic age would be measured, how measurement noise would be handled, and how multiple clock outputs could be combined to give a coherent picture of whether an intervention was shifting the biology of aging in a favorable direction.

The emphasis on simultaneous assessment is the study’s most distinctive contribution. Different aging clocks, trained on different protein sets and different cohorts, capture partly overlapping and partly distinct facets of the aging process—one model may be more sensitive to inflammatory pathways, another to metabolic or hepatic changes, a third to renal or cardiovascular decline. By deploying a suite of clocks in parallel rather than betting on a single algorithm, the trial design allows investigators to ask not merely whether an intervention changes a number, but whether it changes the underlying biology in a way that is consistent across independent measures of aging. Convergence across multiple clocks provides a form of internal replication that a single biomarker cannot offer, while divergence among clocks can itself be informative, pointing to organ-specific or pathway-specific effects that would otherwise be invisible.

Technically, the integration demanded solutions to several stubborn problems. Proteomic measurements are sensitive to pre-analytical variables: the choice of assay platform, the timing of blood draws, fasting status, and even the season of sample collection can shift protein concentrations. Longitudinal interpretation requires that the analytical pipeline distinguish true within-person change from batch effects and ordinary biological fluctuation. The study addressed these challenges by anchoring the clocks to repeated baseline sampling, applying rigorous quality control to the proteomic data, and using statistical models that estimate change within individuals rather than relying solely on comparisons between treatment and control groups at a single time point. This within-person framing is essential for short trials, because it dramatically increases statistical power when each participant serves as their own reference for the direction and magnitude of biological aging.

The broader significance of the work lies in what it could do to the economics of geroscience. Developing drugs that target aging has long been caught in a regulatory and commercial Catch-22: regulators generally approve treatments for diseases, not for aging itself, because aging lacks an agreed clinical endpoint; without approved indications, investment in geroprotective therapies has lagged. Biomarkers that can credibly demonstrate a slowing of biological aging over months rather than decades offer a path through this impasse. If proteomic clocks can be validated as surrogate endpoints or at least as robust pharmacodynamic markers, early-phase trials of candidate geroprotectors—whether repurposed drugs such as rapamycin and its analogues, senolytic agents that clear senescent cells, or novel molecules designed around aging pathways—become faster, smaller, and far cheaper to run.

The phase 2a setting is precisely where such markers earn their keep. Phase 2a studies are designed to detect signals of biological activity, not to prove clinical benefit, and a biomarker that reliably responds to an intervention’s mechanism of action is exactly the kind of signal these trials exist to find. Embedding proteomic clocks at this stage creates a screening funnel: interventions that show consistent effects across multiple aging measures can be advanced to larger trials with confidence, while those that leave the proteome untouched can be deprioritized before expensive late-stage development. In effect, the clocks function as a biological readout of geroprotection, analogous to how viral load measurements transformed the early development of antiretroviral therapies.

Important caveats remain, and the authors and the field are careful to acknowledge them. A change in a proteomic aging clock is not yet proof that a therapy extends healthspan or lifespan; the clocks are validated against age-related outcomes in observational data, and demonstrating that an intervention moves the biomarker is only the first step toward showing that it changes disease trajectories. Calibration across diverse populations is another open question, since proteomic aging signatures can vary with ancestry, sex, socioeconomic factors, and baseline health status, and a clock optimized in one cohort may miscalibrate in another. Standardization across assay platforms and laboratories will also be necessary before proteomic age becomes a measure that regulators and clinicians can compare across studies. The new work does not resolve these issues single-handedly, but it establishes a concrete, tested framework within which they can be addressed trial by trial.

Even so, the moment feels like an inflection point. The geroscience field has spent years generating compelling animal data on interventions that delay aging, only to face a translational bottleneck at the human frontier. The integration of proteomic aging clocks into a real phase 2a clinical trial shows that the measurement problem—long the field’s most fundamental limitation—is tractable with current technology. If subsequent trials replicate and extend this framework, the result could be a virtuous cycle in which better biomarkers enable faster trials, faster trials attract greater investment, and greater investment produces the interventions that finally move the needle on human healthspan. Aging, for the first time, is being measured in the clinic on the timescale of a clinical trial, and that change may prove as important as any single therapeutic candidate now in development.

Subject of Research: Proteomic aging clocks integrated into a phase 2a clinical trial for geroprotective assessment

Article Title: Integration of proteomic aging clocks in a phase 2a clinical trial supports simultaneous geroprotective assessment

Article References: Zhavoronkov, A., Galkin, F., Chen, S., Ren, F., Aliper, A., Durymanov, M., Sidorenko, D., Cui, H., Han, J.-D. J., Xu, H., Liu, X., Xu, Z., Kuppe, C., Austin Argentieri, M., Ying, K., Goeminne, L. J. E., Moqri, M., Tyshkovskiy, A., & Gladyshev, V. N. (2026). Integration of proteomic aging clocks in a phase 2a clinical trial supports simultaneous geroprotective assessment. Nature Biotechnology. https://doi.org/10.1038/s41587-026-03286-y

Image Credits: AI Generated

DOI: 10.1038/s41587-026-03286-y

Keywords: proteomic aging clocks, biological age, geroprotection, phase 2a trial, geroscience, biomarkers, plasma proteomics, aging interventions, healthspan, clinical trial design, machine learning, surrogate endpoints