Nature Aging

Frailty reflects declining physiological reserve across multiple organ systems with aging, yet the underlying biological mechanisms contributing to frailty remain poorly understood. We tested whether somatic mutations in the blood were associated with incident frailty and faster progression in 730,088 participants from UK Biobank, All of Us, BioVU and the Womens Health Initiative. We found that clonal hematopoiesis of indeterminate potential (CHIP) and autosomal mosaic chromosomal alterations showed strong associations with frailty, whereas mosaic loss of chromosome X or Y did not. Findings were consistent across survey-based, directly measured and clinically assessed frailty, as well as healthspan phenotypes. A Tet2 mouse model demonstrated multisystem frailty-like functional decline and T-cell remodeling. In humans, T-cell activation-related proteins directly mediated the association between clonal hematopoiesis and frailty. Collectively, these findings support a model in which clonal hematopoiesis accelerates biological aging through immunosenescence.

Clonal hematopoiesis (CH) increases with age, but whether different somatic clones represent an ageing phenotype or exert distinct systemic effects is unclear. In 450,587 UK Biobank participants, including 46,324 with plasma proteomics, we compared clonal hematopoiesis of indeterminate potential (CHIP) and mosaic loss of chromosome Y (mLOY) or X (mLOX) across biological ageing, incident disease, and circulating proteins. Despite shared age dependence, these alterations showed distinct disease spectra: non-DNMT3A CHIP was associated with broad multisystem disease burden, mLOY with a more focused respiratory, musculoskeletal and cardiovascular profile, whereas mLOX lacked broad age-related disease associations. Clone burden mapped to distinct proteomic programs: mLOY to neutrophil degranulation and extracellular-matrix remodeling, non-DNMT3A CHIP to myeloid immune regulation, and mLOX unexpectedly to cytotoxic lymphocyte/NK-cell responses. Mendelian randomization supported selected protein-disease relationships. Thus, age-related hematopoietic clones are not interchangeable markers of ageing but define alteration-specific systemic programs associated with distinct disease vulnerabilities.

Background Phenotypic age acceleration (PhenoAgeAccel), derived from PhenoAge, and MetaboHealth are composite exposures of biological ageing and metabolic health associated with dementia-related outcomes. Whether these associations are causal and reflect the exposures, constituent biomarkers, or both remains unclear. Methods This study included UK Biobank participants of White British genetic ancestry. MetaboHealth was derived from nuclear magnetic resonance (NMR) metabolomics and PhenoAgeAccel from clinical biomarkers and chronological age. Genome-wide association studies (GWAS) were conducted for MetaboHealth (n=272,568) and PhenoAgeAccel (n=274,077). Independent genome-wide significant variants were used as genetic instruments in two-sample Mendelian randomisation (MR) with FinnGen all-cause dementia summary statistics. Inverse-variance weighting was the primary MR method. Causal network analysis estimated relationships among constituent biomarkers and dementia. Findings GWAS identified 126 and 141 independent genome-wide significant variants for MetaboHealth and PhenoAgeAccel, of which 109 and 141 were retained as genetic instruments. MR found no evidence of a causal effect of genetically predicted MetaboHealth (per unit: OR 0.83, 95% CI 0.49-1.42; p=0.51) or PhenoAgeAccel (per year: OR 0.99, 95% CI 0.95-1.02; p=0.44) on all-cause dementia, with consistent findings across sensitivity analyses and robust MR methods. Lower lymphocyte percentage and higher NMR-derived glucose had direct relationships with dementia in the joint constituent-biomarker network. Interpretation MR provided no evidence that either composite exposure causally influenced dementia. The network prioritised lymphocyte percentage and NMR-derived glucose, supporting examination of composite exposures alongside their constituent biomarkers. Funding NIHR, UKRI, MRC, UK Dementia Research Institute, Innovate UK, and European Union. Full funding details are provided in the acknowledgements.

Age is a major risk factor for many diseases, but the biological processes driving aging are heterogeneous across individuals. Efforts to untangle differences between chronological and biological age have focused on identifying age-associated markers, such as omics clocks. Many omics features, including proteins, are strongly associated with age, and genetics contribute to variance in these measures. However, few studies have identified genetic drivers of interindividual variability in omics changes over time. Using longitudinal proteomics data (Olink 3k) from the Multi-Ethnic Study of Atherosclerosis (MESA), we calculated a protein slope for each individual (n=2,007) and protein (n=2,737) across 3 visits spanning 14-18 years, then conducted a genome-wide analysis for each slope, both with and without adjusting for baseline protein level. Subsets in UK Biobank (UKB; n=948) and CARDIA (n=1,328) with longitudinal proteomics data were used for replication. We considered additional methods for modeling of protein change and variability, including linear mixed models, SNP-by-age interactions, and variance quantitative trait loci. Without baseline adjustment, only 19 proteins (20 credible sets) had a slope pQTL in MESA, with poor replication in UKB and CARDIA. With baseline adjustment, 607 proteins (698 credivle sets) had a slope pQTL and over 70% replicated in CARDIA and/or UKB; such baseline adjusted models may, however, be subject to collider bias. Longitudinal and cross-sectional interaction models identified fewer than 14 pQTLs, suggesting they were generally underpowered; but 73% of proteins with a variance pQTL also had a slope pQTL. By examining effect direction concordance, replication rate, directed acyclic graphs, and signal overlap with other models we demonstrate that many baseline-adjusted slope pQTLs may be arising due to model misspecification or regression to the mean. Overall, our results highlight considerations for modeling strategies of change phenotypes and build on understanding of potential genetic mechanisms influencing interindividual proteome changes over time.

Aging is the strongest risk factor for Alzheimer disease (AD), yet existing human neuronal models either erase age-associated features during reprogramming or fail to recapitulate three-dimensional organization of human neuronal tissue. Here, we establish directly induced neuronal spheroids (iSpheroids), a scalable three-dimensional platform generated by direct conversion of primary fibroblasts without pluripotency. iSpheroids generate long-lived, electrophysiologically active neurons from young, unimpaired aged, and sporadic AD donors while preserving donor-specific epigenetic age. Single-nucleus RNA sequencing revealed approximately 96% of cells acquired a neuronal identity and were distributed across multiple neuronal states, including a diversity of neurons. The platform supports incorporation of astrocytes and microglia and generation from non-human primate fibroblasts. AD iSpheroids spontaneously recapitulated neuronal degeneration, amyloid-beta; accumulation, progressive Tau pathology, and metabolic dysfunction. Integrated proteomic, metabolomic, and lipidomic profiling distinguished physiological aging from AD and revealed disease-associated metabolic remodeling. Oxaliplatin shifted AD iSpheroids toward oxidative metabolism, whereas a multi-compound screen identified trametinib as a modulator of inflammatory and age-associated programs.

Aging is a complex phenomenon, yet therapeutic discovery has largely relied on testing individual hypothesis-driven targets. Here, we performed a genome-scale open reading frame (ORF) screen for oxidative-stress resistance in retinal pigment epithelium (RPE) cells, which are vulnerable to oxidative damage during aging. The screen identified nine protective ORFs including antioxidant factors and an epithelial-to-mesenchymal transition regulator. Notably, we also identified three factors that reduce transcriptomic age including the cardiac transcription factor NKX2-5. NKX2-5 conferred robust oxidative resilience in vitro and in vivo. Domain dissection revealed that its homeodomain is dispensable for resilience, enabling development of NKX2-5{Delta}HD, which retained protective activity without detectable toxicity over 14 months. In middle-aged mice, subretinal NKX2-5{Delta}HD restored visual and electrophysiological function, and its systemic delivery improved grip strength and reduced frailty in late-aged mice. These findings highlight the value of unbiased, genome-scale gain-of-function screening, as resilience factors normally expressed in other contexts can be reengineered as potential therapeutics for age-related decline in other tissues.

Reprogramming somatic cells into induced pluripotent stem cells (iPSCs) resets epigenetic age, creating a major challenge for modeling age-associated cellular states and limiting the use of iPSCs in aging research beyond the genetic component. Recent work has shown that healthy organoids can re-accumulate age-associated epigenetic states over extended culture; whether disease-associated genetic states can directionally reshape these trajectories after reprogramming remains unknown. Here, we present a reproducible, in-vitro approach to re-establish epigenetic aging trajectories using iPSC-derived organoid systems, as quantified by multiple epigenetic clock models. We first demonstrate that epigenetic age progressively increases with serial passaging in a lung organoid model (alveolospheres). We then show that disease-associated mutations in multiple models drive additional, cell-intrinsic shifts in epigenetic age, implicating disease state as an independent modulator of epigenetic clocks. Together, these findings reinforce that iPSC-derived organoids recapitulate epigenetic aging trajectories over time, while highlighting disease state as a potent and potentially tractable modulator of epigenetic age in vitro. By enabling more faithful modeling of age-associated cellular states, this approach expands the utility of iPSC-based systems for dissecting the molecular mechanisms that regulate human aging.

Hallmarks of biological ageing are closely interconnected with neurodegenerative diseases. Deoxyribonucleic acid methylation (DNAm) clocks quantify biological age and may serve as peripheral biomarkers of neurodegenerative diseases. This systematic review and meta-analysis aim to examine associations between DNAm-based biological age metrics and neurodegenerative diseases. Six databases were systematically searched from 1st January 2011 to 15th April 2026 for studies reporting associations between DNAm-based ages and neurodegenerative diseases including all-cause dementia, Parkinson's Disease, Multiple Sclerosis, and Amyotrophic Lateral Sclerosis. Correlated-and-hierarchical-effects meta-analyses were fitted using restricted maximum likelihood with Knapp-Hartung adjustment. Of 42,023 records screened, 37 observational studies (n=46365; 60.5% female; median of mean age 69.4 years [IQR 62.5-73.3)) and seven Mendelian randomization studies met inclusion criteria. In longitudinal meta-analyses, higher GrimAge epigenetic age acceleration (EAA) was significantly associated with higher dementia risk (HR per SD 1.11 [95% CI 1.02-1.20]; I^2 = 0.0%; p = 0.018), whereas Horvath1 EAA, Hannum EAA, PhenoAge EAA, and DunedinPACE were not significantly associated with dementia risk. Evidence for other neurodegenerative diseases were heterogeneous across clock generations and study designs. Mendelian randomization provided limited evidence for causality. Higher GrimAge EAA was the only DNAm age measure consistently predictive of higher all-cause dementia risk. Overall, however, DNAm age clocks show limited and inconsistent associations with neurodegenerative diseases, providing insufficient support for their use as disease biomarkers. These findings highlight the need to develop and independently validate disease-specific DNAm clocks and undertake pathway analyses to identify methylation changes associated with neurodegeneration and the biological processes they reflect.

The female reproductive system is one of the first major organ systems to show signs of age-related decline, and menopause is associated with increased risk of several diseases, including osteoporosis and cardiovascular disease. Menstrual fluid contains a mixture of blood and endometrial tissue and is a noninvasive biological sample type that has immense potential for diagnostics related to female reproductive aging. However, existing epigenetic aging clocks show limited performance in hormone-dependent tissues such as the endometrium. At Xella Health, we collected menstrual fluid (MF) samples, from a diverse patient cohort (n=66) and quantified genome-wide 5mC methylation levels. We then developed a novel, deep learning-based epigenetic aging clock that is optimized for performance in menstrual fluid and endometrial tissue. Our model, the Xella Clock, outperforms other widely used epigenetic aging clocks at predicting chronological age from MF data and on endometrial tissue. The model is a useful tool for advancing the study of female reproductive aging and can be used to examine associations between endometrial age acceleration and clinical factors.

Environmental conditions experienced early in life have profound consequences for vertebrate health, yet the molecular pathways linking developmental stress to aging and reduced lifespan remain poorly understood. Through a novel highly accurate epigenetic clock, developed from RRBS-based blood DNA methylation profiles, we show that experimental lifespan-reducing early-life stress rapidly accelerates epigenetic age in zebra finch chicks (Taeniopygia guttata). Corticosterone-treated 29-day-old chicks share differentially methylated loci with non-treated aged birds and cluster with 6-month-old birds. The transcriptional repressor ZBTB16 emerges as an epigenetically top age-correlated gene and is strongest affected by corticosterone. Elevated developmental corticosterone causes rapid epigenetic remodelling of metabolic pathways well-established in aging and longevity. Our results demonstrate epigenetic rewiring of the aging trajectory through conserved stress-survival mechanisms immediately following elevated early-life stress exposure.

Aging is a progressive decline in biological function that is proposed to be driven by the accumulation of epigenetic noise and the loss of epigenetic information. Among epigenetic readouts, DNA methylation has been extensively used to develop aging clocks, machine learning models that predict age from molecular data. However, DNA methylation clocks are relatively difficult to interpret and remain distant from gene regulatory networks, a gap that can be complemented by clocks built from another epigenetic layer: chromatin accessibility profiled by ATAC-seq. Existing chromatin accessibility clocks predict age from bulk ATAC-seq data, thereby averaging over the epigenetic heterogeneity across cells that drives aging. We hypothesized that a chromatin accessibility clock trained at the level of individual cell types, using pseudobulk profiles derived from single-nucleus ATAC-seq (snATAC-seq) data, would be particularly useful for characterizing cell type-specific aging. We focused on the brain, a highly heterogeneous tissue whose diverse cell types age asynchronously, and assessed how well cell type-specific accessibility clocks can predict chronological age, capture rejuvenation from genetic perturbation, and detect age acceleration in age-associated neurodegenerative disease. To this end, we introduce a set of cell type-specific and all-cell aging clocks built from snATAC-seq profiles of the prefrontal cortex (PFC) of 357 human donors (15 to 100 years), which generalize to accurately predict age across brain regions and species. Beyond healthy aging, these PFC clocks captured the rejuvenating effects of SIRT6 overexpression in mouse liver and cell type-specific age acceleration in Alzheimer's disease (AD) and Parkinson's disease, with microglial age acceleration correlating most strongly with pathology among major cell types, and with female oligodendrocytes and OPCs showing the largest sex differences in age acceleration. Interpreting the clocks further revealed the regulatory elements, genes, pathways, and motifs underlying these signals across species, disease, and perturbation, including repression of the NF-kB pathway in SIRT6 transgenic mice, upregulation of immune and inflammatory pathways in severe AD, and conserved age-predictive peaks related to histone regulation, metabolism, and neuronal survival across brain regions and species. Together, these results establish PFC snATAC-seq aging clocks as a generalizable tool that accurately predicts age and captures cell type-specific perturbation effects of rejuvenation and disease on the epigenetic landscape, providing both a means to evaluate perturbations and insight into the epigenetic mechanisms of aging and disease.

Aging populations face a growing burden of neurodegenerative disease and behavioral decline. The microbiota is increasingly implicated in host physiology, highlighting an urgent need to understand how gut microbes modulate brain function and late life health. Here, we develop a high-throughput microbe-host screening platform to systematically dissect how bacterial genes shape organismal behavior. Using the Escherichia coli Keio library of 3,985 distinct non-essential single-gene deletion mutants in combination with Caenorhabditis elegans, we quantitatively profiled 768 behavioral features per bacterial clone and uncovered a coherent module of bacterial genes involved in iron homeostasis that robustly reprogrammed host behavior. Bacterial omics analyses revealed that alterations in iron homeostasis amplify siderophore production in a TCA cycle-dependent manner, and loss of enterobactin biosynthesis abolished the bacteria-induced changes in worm movement. Transcriptional, molecular and functional studies demonstrated that bacterial enterobactin activates host neuromuscular responses to shape both lifespan and healthspan in a manner dependent on the mitochondrial unfolded protein response. Thermal proteome profiling identified mitochondrial glutaryl-CoA dehydrogenase and the electron-transfer flavoproteins A and B as enterobactin-binding targets that control mitochondrial function. Finally, genetic manipulation of neuronal mitochondrial and cytosolic reactive oxygen species via superoxide dismutase and catalase revealed that redox state modulates enterobactin-driven changes in movement and lifespan through the secretin-family GPCR neuropeptide receptor PDFR-1. Together, these findings establish microbial enterobactin as a non-canonical neurotransmitter regulating neuronal mitochondrial function, behavior and aging, defining a gut bacteria-brain axis with broad implications for maintaining late-life health.

Biological age estimates are increasingly used to study aging, disease risk, and mortality, yet their predictive uncertainty is rarely quantified. Consequently, conventional age-gap measures can treat deviations as equally informative even when the underlying biological age predictions differ substantially in reliability. We developed a framework for uncertainty-aware biological aging that generates calibrated prediction intervals and individualized probabilities of accelerated or decelerated aging alongside point estimates. We applied this framework to the UK Biobank Pharma Proteomics Project, evaluating three composite and eleven organ-specific biological age clocks. Predictive uncertainty varied substantially both within and across clocks, revealing that apparently extreme age gaps can differ markedly in the strength of evidence supporting accelerated or decelerated aging. In particular, low-accuracy clocks, including many organ-specific clocks, provided little evidence for confidently accelerated or decelerated aging. Beyond biological age gaps, prediction-interval width was independently associated with disease risk and mortality, particularly for composite, brain, and immune clocks, suggesting that predictive uncertainty captures an additional dimension of biological aging that may reflect increased molecular heterogeneity and dysregulation associated with aging and disease. We replicated these findings in Biobank Japan and an independent clinical cohort from Stanford. By incorporating individual-specific predictive uncertainty, our framework provides a more informative characterization of biological aging and enables improved individual-level risk stratification for disease prevention and longitudinal monitoring.

Chronological-age clocks reconstruct age from biological measurements, yet their outputs are interpreted as biological age, gaps as ageing acceleration and intervention-associated decreases as rejuvenation. We show that age supervision identifies an age-task statistic, not a biological-age construct, and establish how this distinction changes biomarker construction and validation. Even at the population optimum, the same observable distribution and age-prediction performance admit incompatible biological-age interpretations. Resolving this ambiguity requires assumptions or evidence beyond the age task. Squared-error age loss penalizes within-age output dispersion without defining its biological direction. Given age and background, a gap re-expresses the compressed score; exact age recovery eliminates it even when heterogeneity remains in the measurements. Shared biological covariance permits genuine prognostic value without establishing construct identity. After allogeneic haematopoietic stem-cell transplantation, recipient-blood scores showed excess donor-lineage affiliation under a score-pairing null. In NHANES, age-trained scores improved held-out five-year mortality prediction beyond age and background, yet direct modelling of source measurements and mortality supervision at matched scalar capacity yielded further gains. The intended biological object must therefore guide study design, measurement selection and representation; validation must establish the claimed measurement relation rather than rely on age-prediction success alone.

Cognitively normal older adults are often regarded as a homogeneous population in preventive and disease-modifying clinical trials for dementia. However, longer-term cognitive aging outcomes vary substantially in this population, and this variability remains poorly understood. Here, we leveraged rich multimodal, multi-domain biomarker profiles from a large prospective cohort (N=1,136), and Deep Embedded Clustering, to cluster cognitively normal older adults into biologically distinct subgroups. Input data included cortical thickness derived from MRI, plasma Alzheimer's disease (AD) biomarkers, plasma inflammatory biomarkers, and vascular measures. The deep clustering algorithm identified three biologically distinct subgroups within the sample, stratified along a gradient of neurobiological burden (low, intermediate, and high). Cortical thinning and inflammatory burden were the primary drivers of clustering assignments. The High-Burden subgroup showed significantly worse memory and executive function, elevated cardiometabolic comorbidity, and markedly higher rates of conversion to mild cognitive impairment or dementia within two years. The results were validated in an independent external sample. The study reveals marked variability among individuals who are otherwise all defined as cognitively normal, and provides a data-driven stratification framework for enriching disease-modifying and preventive trials by identifying cognitively normal individuals at high risk for future cognitive decline.

Aging is characterized by highly reproducible alterations across multiple layers of the epigenetic landscape, including DNA methylation, chromatin accessibility, and histone modifications. However, it remains unclear to what extent these age-associated changes are interconnected and coordinated coherently. To investigate the genome-wide distribution and interplay of age-associated epigenetic alterations, we generated whole-genome bisulfite sequencing (WGBS) data from blood samples of 120 healthy donors. Integration with ATAC-seq data revealed no clear relationship between age-related changes in DNA methylation and chromatin accessibility. We further examined the association of these alterations with age-dependent changes in CTCF occupancy and histone modifications, including H3K27ac, H3K27me3, H3K4me1, H3K4me3, and H3K9me3, but observed very little corresponding changes in chromatin states. Collectively, our integrative genome-wide analysis revealed only limited association between age-associated epigenetic alterations in DNA methylation, chromatin accessibility, and histone modifications, arguing against a broadly coordinated remodeling of the aging epigenome.

Background Reduced muscle strength is associated with cognitive decline and Alzheimer's disease (AD), suggesting that skeletal-muscle aging and AD-related neurodegeneration may share biological mechanisms. Vascular dysfunction, immune activation, and extracellular-matrix remodeling have been implicated in both tissues, but the extent of shared cellular and molecular programs remains unclear. We investigated cross-tissue transcriptional programs in aging skeletal muscle and AD-related brain tissue and evaluated whether related signals are detectable in peripheral blood. Methods We analyzed independent, unpaired human transcriptomic datasets from skeletal muscle (23 donors), the SEA-AD middle temporal gyrus atlas (84 donors), and peripheral blood. Donor-aware models identified age-associated changes in muscle and transcriptomic changes across continuous pseudoprogression score (CPS) in brain. Cross-tissue comparisons focused on 30 brain donors within an early CPS window. Shared tissue-derived programs were assessed in peripheral blood mononuclear cells and independently tested in frailty bulk-blood and Alzheimer's Disease Neuroimaging Initiative (ADNI) whole-blood datasets. CellOracle simulations were used to prioritize candidate transcriptional regulators. Results Aging muscle showed increased inflammatory, extracellular-matrix, and stromal communication programs. During early AD-related brain progression, vascular and immune populations showed increasing inflammatory and matrix-associated activity together with shifts in intercellular communication. Cross-tissue analysis identified six concordantly enriched pathways comprising 109 leading-edge genes in endothelial populations and four pathways comprising 51 genes in myeloid populations. Related peripheral-blood signatures varied across cohorts and cell types. However, in independent frailty and ADNI mild cognitive impairment and AD datasets, 23 of 30 predefined tissue-derived pathway-subset tests showed significant positive enrichment after false-discovery-rate correction, whereas individual gene-level bulk-blood associations did not survive correction. CellOracle analyses prioritized ETS2 and BHLHE40 as exploratory endothelial regulators whose simulated perturbation consistently reduced selected shared program scores across tissues. Conclusions Aging skeletal muscle and AD-related brain tissue exhibit convergent endothelial and myeloid inflammatory programs, with related pathway-level signals detectable in peripheral blood. These cross-tissue programs and candidate endothelial regulators provide testable hypotheses for mechanisms linking systemic aging, muscle dysfunction, and AD-related neurodegeneration.

Aging reshapes the human body at the cellular level, yet how cell identity, morphology, and spatial organization remodel across organs and the adult lifespan remains poorly mapped, at a scale and lifespan coverage that molecular spatial assays cannot yet reach. Treating the GTEx histopathology archive as a population-scale, lifespan-resolved resource for spatial biology, we detected over 3.5 billion single cells across 16 human organs from nearly one thousand individuals. Cell density declined pervasively but organ-specifically, and vision-language phenotyping resolved epithelial cells into nine subtypes with divergent aging trajectories, including loss of ovarian granulosa cells at ~45% per decade. Community detection on spatial cell graphs identified functional tissue units, over a quarter of which remodeled with age along a shared trajectory from dense, specialized units toward sparser, stromal- and immune-enriched structures. Critically, this architectural remodeling was largely decoupled from cell composition (R2=0.07), showing that human tissues age along two partly independent axes, a pervasive loss of cells and a distinct remodeling of the architecture they form, with structural decline exceeding what cellular composition alone predicts.

Vascular senescence is a central driver of whole-body ageing, yet rescue strategies remain limited. Here we show that hydrogen sulfide (H2S) bioavailability declines in ageing and atherosclerosis and is associated with endothelial senescence. Developing a novel remote-control, endothelial-specific, mitochondria-targeted chemogenetic system, we spatiotemporally controlled H2S generation and thereby mitigated endothelial senescence-driven programs and reversed vascular remodeling in aged mice.

Lysosomal dysfunction is a hallmark of aging, yet whether microbial components actively regulate this organelle to influence longevity remains unknown. Here, we identify bacterial peptidoglycan (PGN), a major cell wall component degraded by host lysozyme, as an evolutionarily conserved activator of lysosomal function that extends lifespan in both C. elegans and mice. We show that aging leads to an intestinal decline in lysozyme expression, which impairs bacterial cell-wall digestion and results in systemic PGN deficiency. Late-life PGN supplementation (starting at 18 months of age) significantly prolongs mouse lifespan and improves healthspan. Mechanistically, PGN localizes to lysosomes and directly binds V-ATPase subunits, enhancing ATP hydrolysis activity and promoting lysosomal acidification. This effect is abolished by V-ATPase inhibition (bafilomycin A1) or genetic disruption of lysosomal components (cup-5 and vha-12 mutants), confirming that functional V-ATPase is strictly required for lysosomal function and the longevity benefit. Importantly, PGN restores lysosomal acidification in aged cells, alleviates cellular senescence markers, and improves multiple hallmarks of aging including locomotion and muscle integrity. Collectively, these findings reveal an evolutionarily conserved mechanism whereby hosts exploit bacterial cell wall components to maintain cellular homeostasis, establishing a gut microbiome-lysosome-longevity axis with implications for microbiome-based anti-aging interventions.