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.

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.

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 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.

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.

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.

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.

Antigen-recognition histories accumulate across adult life, but existing human aging resources largely emphasize host-state measurements rather than antigen-resolved humoral memory. We present CHAIR, the Chinese Healthy Aging Immune Resource, which integrates self-antigen, human virome and toxin/virulence-factor PhIP-seq with routine clinical measurements and T/B/NK phenotyping in clinically screened adults aged 20-94 years. The resource framework includes 1,008 unique PhIP-seq samples, 995 clinical records, 977 T/B/NK records and 853 participants with all three layers. Across modeled spaces comprising 23,584 self-antigen targets, 210 virome targets and 1,258 virulence-factor source targets, most measured antibody-reactivity architecture was consistent with broad preservation within domains, whereas age- and sex-associated signals were concentrated in focal targets and modules. Together, CHAIR provides a traceable, antigen-resolved reference framework based on clinically screened adults for investigating focal humoral remodeling across healthy adult aging.

Menopause timing links reproductive lifespan with later life health, motivating investigation of its molecular and hematological correlates. We combined Generation Scotland analyses of women sampled at or after reported menopause (n = 1,444) and initially menstruating women followed for GP ascertained menopause onset (n = 1,725; 251 events) with bidirectional and multivariable Mendelian randomization. Higher age adjusted GrimAge V1, GrimAge V2 and DunedinPACE corresponded to 0.34 to 0.40 years earlier menopause per SD in the retrospective cohort at nominal P < 0.05. Prospective associations were nonsignificant, and cohort and primary bidirectional aging-related genetic associations did not survive multiple-testing correction. Genetically predicted later menopause was associated with higher neutrophil percentage and count and lower lymphocyte percentage in women; these associations and female vs. male contrasts survived correction. CRP conditional on menopause timing was associated with higher GrimAge and PhenoAge acceleration and shorter leukocyte telomere length after correction. None of 36 estimated inflammatory indirect effects reached P < 0.05. These findings highlight blood-cell composition as a prominent correlate of reproductive timing and identify selected methylation-aging signatures for further study. Together, they position reproductive hematological relationships as a specific avenue for understanding the connection between menopause and systemic aging.

Proteomic aging clocks have emerged as biomarkers of aging, but most rely on cross-sectional data. Here, we present a proteomic aging clock based on longitudinal measurements of liquid chromatography-mass spectrometry plasma proteomics at up to three time points in the population-based KORA cohort, comprising 9,105 samples from 4,100 individuals in the final dataset aged 25-88 years. The model predicts chronological age and yields a measure of proteomic age acceleration associated with lifestyle and clinical risk factors. Risk factor-stratified analyses reveal shared proteomic signatures among cardiometabolic exposures and distinct signatures for smoking and physical activity. Within individuals, dyslipidemia and impaired kidney function track transitions to increases in age acceleration, while higher age acceleration is associated with increased all-cause mortality. Mediation analysis suggests that risk factors are linked to mortality indirectly through age acceleration. Affected proteins and pathways highlight extracellular matrix remodeling, complement and coagulation pathways, and liver-derived plasma proteins as key contributors to aging. Mendelian randomization identifies proteins with evidence consistent with a causal role in aging-related traits. Together, these findings are consistent with biological aging being dynamically responsive to changes in modifiable risk factors.

Aging progresses asynchronously across organs, motivating the development of organ-resolved aging clocks. Direct assessment of organ aging in living humans, however, is largely impractical. Here, we construct tissue-specific transcriptomic aging clocks and infer organ biological age from paired whole-blood (blood-organ age) and tissue RNA sequencing data in the GTEx project. We observe high variability both in the strength of aging signatures across organs and in the ability to predict organ age and organ scores from blood. Pathway analysis shows that organ aging clocks are dominated by biological processes that differ across tissues. Age-associated multi-organ modules identified in an aging multi-organ network correlation analysis and organ age features causally mediated through organ-blood-organ transcriptomic interactions support a role for systemic signaling in coupling organ aging processes. Given the established role of cellular senescence as a driver of tissue dysfunction and its tissue-specific accumulation during aging, we extend this framework to estimate burden of organ-level senescence and hallmarks of aging. Using senescence- and hallmark-associated gene sets, we derive tissue-specific senescence and hallmark scores (organ scores) and demonstrate that these burdens across multiple organs can be inferred from blood transcriptomes (blood-organ scores). Finally, in pursuit of extending these models to other blood omics and alternative non-invasive assessments, we evaluate whether blood methylation (methylation-blood-organ age and scores) and facial photographs (facial-blood-organ age and scores) can serve as proxies for blood-organ age and blood-organ scores in independent cohorts (Edifice Health and Health and Retirement Study). The methylation- and facial-blood-organ age and scores were associated with mortality in additional testing cohorts (Framingham Heart Study and IMDB-WIKI dataset). These results establish a cross-modal framework for inferring organ-specific aging and senescence from minimally invasive data.

Characterizing temporal dynamics during aging is crucial to understanding the course of aging-related events. The transcriptome is extensively remodeled with age, but the temporal trajectories of these changes, particularly through midlife, remain poorly defined in many tissues. Here, we address this gap in the male mouse colon. Using a dataset of 83 RNA-Seq samples from five time points during adult mouse lifespan, we show that colon aging is characterized by multiple gene-expression trajectories unfolding in parallel, with a major shift occurring during a mid- to late-life transition marked by a collapse of the unfolded protein response (UPR). Moreover, we report widespread non-monotonic trajectories, including genes that peak or dip in midlife and would be missed by comparisons limited to young versus old ages. We further describe age-dependent dynamics of transposable element-containing transcripts and a nonlinear course of transcriptomic entropy across the lifespan. Importantly, we identify a small set of genes that track chronological age and use only three of them to construct a compact transcriptomic clock, which we validate using an independent RNA-seq dataset and qPCR data. Together, our results indicate that nonlinear patterns dominate the aging colon transcriptome and underscore the value of high temporal resolution for identifying key transitions during aging.

Ectopic lymphoid structures are typically associated with chronic tissue inflammation in autoimmunity and cancer, where they can amplify local immune responses. Similar structures arise spontaneously with age, yet their origin and function remain unclear. Here we identify tissue retention of mature migratory conventional dendritic cells (cDCs) as a driver of age-associated lymphoid organization. Mature cDCs accumulated within lymphoid structures in aged human and mouse tissues. We demonstrate that impaired cDC egress or pharmacological cDC expansion induced de novo structures in mice across multiple otherwise homeostatic organs without associated pathology. Strikingly, senescence-associated tissue cues, which promoted a distinct cDC maturation state, were required for lymphoid niche initiation. Unlike inflammatory structures described in disease, these cDC-driven structures preferentially accumulated tissue-adapted regulatory T cells and protected against inflammatory injury, revealing a previously unrecognized regulatory dimension of age-associated lymphoid organization.

Cellular senescence is a central hallmark of aging, yet its measurement in humans remains invasive, low-throughput and tissue-specific, precluding population-scale study. We developed Methylation-associated Gene Expression (MaGE) predictors: whole-blood DNA methylation proxies of p14ARF, p16INK4A and p21CIP1 expression, plus a composite score, providing the first scalable measure of senescence-marker expression. Deployed across Generation Scotland (n=18,859), MaGE yielded 45 Bonferroni-significant associations spanning 18 incident diseases and all-cause mortality. The two strongest associations recapitulated the established tissue specificity of p21CIP1 and p16INK4A activation, with MaGE-p21 associating with incident alcoholic liver disease and MaGE-p16 with pulmonary fibrosis. In a separate study, MaGE tracked disease severity and treatment response in Crohn's disease. MaGE is a scalable, interpretable biomarker of senescence that enables its study at population scale and offers a route to patient stratification in senolytic trials.

Interpretable computational pathology is constrained by a trade-off between scalable learned representations and biologically explicit phenotypes. Here we present NucXplore, a nuclear phenomics framework that converts each hematoxylin-and-eosin (H&E)-stained nucleus into 129 explicitly defined features spanning morphology, chromatin, intensity, texture, color, and spatial context. A Rust-based implementation accelerates extraction 17.6-fold over the Python reference implementation. Across three histopathology cohorts, NucXplore outperformed classical descriptors and larger deep-learning embeddings while retaining feature attribution. Applied to human skin, hierarchical multiple-instance models resolved eight cellular compartments and decoded age and sun-exposure states, revealing a largely shared aging program with age and cell-specific exposure-dependent recalibration. Conditional flow matching and neural ODE integration transformed cross-sectional phenotypes into model-implied trajectories, uncovering a midlife velocity minimum, late-life re-acceleration, and cell-specific changes in trajectory magnitude and direction. Source-free domain adaptation enabled preliminary transfer of age-associated predictions to an independent hospital cohort. NucXplore thus unifies interpretable representation, high-performance computing, and dynamical modeling for cellular phenotyping from routine histology.

Aging is associated with progressive neuroinflammation and cognitive decline, yet the cellular sources that sustain this process and whether they can be targeted peripherally remain unclear. Here, we identify inflammatory border-associated macrophages (BAMs) as key drivers of neuroinflammation in aging and show that their therapeutic and prophylactic elimination through intrathecal CAR T cell therapy restores cognitive performance in mouse models of aging and Alzheimer's disease. Furthermore, targeting of aged inflammatory bone marrow myeloid progenitors through either intravenous CAR T cells, which do not infiltrate the brain, or through transplantation of CAR T-treated progenitors is sufficient to reduce neuroinflammation and cognitive impairment. These findings reveal that bone marrow myeloid progenitors harbor a heritable inflammatory transcriptional state that is transmitted to their BAM progeny, driving neuroinflammation and cognitive deterioration, and conserved in human aging. Critically, this proinflammatory state is marked by the upregulation of surface proteins, enabling precise peripheral CAR T cell targeting of these progenitors for long-lasting therapeutic effects in cognitive aging.

Background. Blood-based biological age clocks predict mortality well, but they are statistical composites. They do not say which physiological systems make a person biologically older, and they cannot say how an intervention would move the clock or whether moving it would change risk. Methods. We built IQN-BIOAGE-01, a quantitative systems pharmacology (QSP) model of mortality-referenced biological age. A systemic senescent load follows saturating-removal stochastic dynamics and drives eight latent organ/hallmark axes, which are observed through 13 routine blood, blood pressure and body size measurements. Death is the first passage of the load over a threshold lowered by poor organ reserve, and biological age (BAmech) is the age at which the reference population has the same 10year risk. The model was calibrated on NHANES III (14,049 adults; 2,736 deaths in 20 years) and tested on a locked NHANES IV 1999 2010 holdout (24,650 adults; 1,867 deaths). Two later versions were accepted or rejected by rules written before their validation results. We confronted the inflammation axis with three anti-inflammatory outcome trials, audited common implementations of the comparator clock, and locked a registration-ready external validation. Results. On the hold-out, Harrell's C was 0.842 for BAmech, 0.842 for PhenoAge and 0.823 for chronological age. The hazard ratio per SD of the biological age gap was 1.55 (1.48 1.62) for BAemech and 1.45 (1.40 1.50) for PhenoAge. Risk ordering transferred across eras (calibration slope 1.01 1.03), but absolute 10year risk was overpredicted (10.4% against 7.4% observed); life-table recalibration moved observed-to-expected from 0.72 to 0.81. The inflammation axis carried most of the gap. A joint re-estimate did not converge and a converged, biological-variation-anchored version narrowly failed its pre-written identifiability criterion, so v1.0 remains the locked primary. The outcome evidence available so far, chiefly topline results from one anti-inflammatory trial, suggested that only a small fraction of a pharmacological CRP fall may carry the risk implied by the model's cross-sectional structure (posterior median pass-through 0.22). Common software implementations of PhenoAge differed from the published formula by 0.7 2.0 years. Conclusions. A mechanistic model can match a leading statistical blood clock in discrimination while adding an organ-level decomposition, explicit statements of what the data can and cannot identify, and a structure in which interventions can be simulated. Because inflammation dominates blood-based biological age while lowering CRP with drugs may carry little of the implied risk, a change in a blood clock should not be read as a change in mortality risk without outcome evidence. Validation is Tier 1 (internal and temporal, within one survey programme); the external test is locked and awaiting data access.