npj Aging

Aging involves a progressive decline in bodily functions, underscoring the need for interventions that enhance healthspan. In this study, we screened nine natural products in Caenorhabditis elegans using whole-organism phenotyping to assess mobility endpoints, and subsequently focused on curcumin, sulforaphane, and their combination. In replicated follow-up experiments, all three interventions improved late-adult mobility after Day 2 of adulthood. Sulforaphane and the combination provided the strongest gains, whereas curcumin showed a distinct benefit profile, with more pronounced effects on time active measures than on speed-based metrics. To examine associated molecular changes, we performed transcriptomic profiling on Day 3 adults. Curcumin was associated with lipid and sphingolipid remodeling together with reduced expression of several innate immune effectors, whereas sulforaphane induced glutathione-linked detoxification signatures involving multiple gst genes. The combination retained major features of both single-compound responses while adding combination-specific changes that broadened detoxification-associated signatures and extended repression of lectin-and lysozyme-associated genes. Transcription factor activity inference further supported SKN-1-linked detoxification responses under sulforaphane and the combination. Overall, these results suggest that curcumin and sulforaphane engage distinct yet partially convergent maintenance-related programs, and that their combination broadens the underlying molecular response without producing additive mobility gains. These findings motivate further testing of natural product combinations in healthspan-related contexts.

Type 2 diabetes (T2D) arises from distinct diabetogenic mechanisms, but whether these mechanisms differ in their associations with hallmarks of aging remains unclear. We analyzed 449,505 UK Biobank and 374,973 All of Us participants using an overall T2D polygenic score (oPS) and eight partitioned polygenic scores (pPSs) representing distinct T2D-related mechanisms. Across organ systems, 81 age-related diseases were assigned to nine hallmarks of aging. UK Biobank analyses used Cox regression for incident hallmark-level outcomes, and All of Us analyses used logistic regression for prevalent hallmark-level outcomes. In both cohorts, the oPS was associated with disease burden across hallmarks, whereas pPS associations varied by mechanism. The obesity pPS showed the strongest and most consistent associations, while other insulin-resistance-related pPSs, including the lipodystrophy pPS, showed more modest positive associations. Beta-cell dysfunction pPS associations were close to null across hallmarks. Obesity pPS-hallmark associations were significantly attenuated after adjustment for BMI, and lipodystrophy pPS-hallmark associations after adjustment for triglyceride-to-HDL cholesterol ratio (TG/HDL-C), a marker of insulin resistance. These findings suggest that adiposity and insulin resistance, indexed by BMI and TG/HDL-C, may act as modifiable factors in the T2D genetic burden on aging hallmarks.

Proliferating cells can enter an irreversible state of cell-cycle arrest known as cellular senescence. The accumulation of senescent cells contributes to organismal ageing and age-related pathologies. Consequently, therapeutic strategies have emerged to selectively eliminate senescent cells (senolytics). Our previous work suggested that senescent mouse myoblasts are more susceptible to reductive stress-induced cell death than proliferating cells. Here, we replicated these findings in human LHCN-M2 myoblasts, demonstrating a biphasic dose-response relationship with cell death, wherein low concentrations were associated with reduced cell death in both proliferating and senescent cells, whereas higher concentrations selectively induced cytotoxicity in senescent cells. We propose that many identified natural senolytic compounds may exert their in vitro activity, at least in part, through the induction of reductive stress due to their antioxidant properties. These findings have important implications for understanding senolytic mechanisms and guiding the future development of senescence-targeting therapies.

A central challenge in computational geroscience is to distinguish molecular quantities that predict mortality from those that causally drive it. Epigenetic clocks and aging biomarkers are increasingly used as if they were that mechanism, yet this is rarely tested directly. This distinction also bears on competing theories of aging: damage/reliability (A), hyperfunction/mTOR-IIS (B-1), and information loss (B-2). Although individual aging proteins have been tested piecemeal, no study has asked, in one framework, what fraction of mortality is measurable, whether it is causal, and whether it is reversible. Using only public, de-identified data, we evaluate this three ways. First, a Markov generator-matrix model of hallmark-load dynamics with death as an absorbing state, fitted by Bayesian inference through a joint biomarker-and-mortality likelihood to NHANES with linked mortality (n=23,844) and replicated in the Health and Retirement Study (HRS), decomposes Gompertz acceleration into visible (measured-biomarker-driven) and latent components. Second, a positive-control-calibrated, two-platform cis-pQTL Mendelian-randomization and colocalization design (UKB-PPP, deCODE) against parental-lifespan GWAS tests whether the latent's measurable components are causal. Third, a clock battery (Horvath, chronological; DamAge, causality-enriched damage) tests reversibility in cellular reprogramming. Within the model, ~92% of Gompertz acceleration is assigned to a latent component not captured by measured blood-biomarker axes (NHANES 92.5%, HRS 91.6%); the latent is partly encoded in DNA-methylation signatures but not transcription. The known causal proteins are detected (LPA p=9x10-12; IL6R p=2.8x10-5), yet the latent's components, across inflammatory, renal and growth-signalling (IGFBP3, IGF-1) axes, are null and do not colocalize on either platform. Reprogramming reverses the chronological clock (-11 to -22 yr) but not the causality-enriched damage clock. The model-inferred mortality-driving component is largely latent to accessible biomarkers; its measurable molecular proxies show no supported causal effect where the design detects known causes; and the causality-enriched damage-clock signal is resistant to partial reprogramming.

Motivational changes are determinants of healthy aging, social engagement, and functional independence, and may signal early neurodegenerative risk. Existing assessment approaches in aging typically treat motivation as a unitary construct. Here, we introduce MotDem, an age-appropriate measure of motivation co-designed with people living with dementia, carers, and clinicians. Across a broad adult lifespan sample (18-80 years), MotDem revealed a robust three-domain motivational architecture encompassing goal-directed behaviour, social reward, and pleasure, with a fourth satiety factor retained as exploratory. This structure was replicated in an independent older cohort (45-80 years) from a different national context. MotDem showed strong convergence with established measures of apathy and anhedonia, alongside more modest associations with depressive symptomatology. Together, these findings show that motivational aging is multifaceted and poorly captured by traditional unitary assessment. MotDem provides a multidimensional framework for measuring distinct motivational drivers of heterogeneous aging trajectories, with implications for resilience, wellbeing, and neurodegenerative risk.

Maximum lifespan varies more than 100-fold across vertebrates, yet within each species aging emerges as a coordinated syndrome spanning metabolism, immunity, endocrine signaling, cognition, and regeneration. We propose the Metabolic Scope Theory of Aging (MSTA), which treats longevity as the time required to exhaust mitochondrial bioenergetic reserve rather than as a consequence of resting metabolic rate alone. The framework decomposes lifespan into three physical axes: Scope, the reserve capacity that buffers cumulative damage; Stability, the resistance of mtDNA-linked OXPHOS architecture to erosion; and Pace, the temperature-dependent kinetics of lesion accumulation. Using body mass as a Scope proxy, mtDNA GC content as a Stability proxy, and body temperature as Pace, the resulting Scope-Stability-Pace relation, lnMLS = lnBM + {beta} GC% -{gamma} Tb + c, explains [~]69% of mammalian maximum-lifespan variance across 379 species. Cross-class comparisons reinforce the same constraint structure: birds offset high thermal Pace through elevated mtDNA Stability, and the SSP temperature coefficient derived from mammals matches the temperature dependence of lifespan observed in ectotherms. The framework further connects comparative lifespan scaling to Gompertz-like mortality acceleration through progressive reserve erosion and threshold crossing. Mechanistically, MSTA models cumulative mtDNA-linked damage as rising impedance within OXPHOS. Increasing internal resistance drives mitochondria toward a high-redox-pressure, low-current regime that preserves basal ATP while restricting NAD+ regeneration, CoQ acceptor availability, and {Delta}p-dependent work. The earliest failure is therefore not energetic collapse but loss of regenerative scope: NAD+-gated TCA flux, aspartate and nucleotide synthesis, one-carbon metabolism, and redox-buffered repair become progressively harder to sustain, and diverse age- related pathologies emerge as tissue-specific projections of this shared upstream constraint. MSTA separates a reversible, operational impedance (redox poise, membrane potential, endocrine tone) from a fixed, informational one (accumulated mtDNA damage) that sets the hard ceiling on lifespan. Because the informational layer cannot be reversed by regulatory means, the framework predicts that until therapies can directly restore mitochondrial conductance, interventions will be most effective when they relieve redox pressure or bypass constrained biosynthetic gates.

Alternative splicing exhibits significant changes during development and aging, affecting the composition and variance in the transcriptome. However, it is unclear whether and how age-associated splicing dysregulation leads to functional consequences. Here, an integrative analysis of transcriptome data across mouse and human tissues revealed that aging is characterized by systematic deterioration of the fidelity of RNA splicing, here termed splicing degeneration, a measure of functional alteration of reading frame and domain configuration of protein products. Genes with higher aging-associated splicing degeneration were more conserved and enriched for processes such as RNA metabolism and antigen presentation. By assessing alternative splicing events associated with functional deterioration, we quantified the degree of splicing degeneration. Its level increased with age but was alleviated following calorie restriction or rapamycin treatment, indicating that it can serve as a new molecular hallmark of aging. Mechanistically, through a comprehensive meta-data analysis, we discovered that splicing degeneration is associated with age-associated changes in specific splicing factors, which in turn showed a strong association with age-related transcriptome changes. Overall, our study demonstrates the intricate relationship between aging and genome-wide splicing degeneration, revealing a promising target for aging interventions acting to reverse splicing degeneration.

Aging is accompanied by widespread metabolic change, but it remains unclear which features are shared across species with different physiology, lifespan, and sampling contexts. To address this, we employed a pathway-centered comparative metabolomics framework to evaluate age-associated metabolic remodeling across wild African savanna elephant, mouse, and Drosophila melanogaster. Drosophila provided a controlled adult time course to map age-associated metabolite trajectories, while mouse and elephant plasma datasets allowed us to test whether these pathway signatures extended to mammalian aging. Adult Drosophila showed extensive metabolomic remodeling, with significant metabolites organizing into distinct temporal trajectory classes. Although individual metabolite overlap across species was limited, robust correspondence at the pathway-level overlap was observed. Pathway scores derived from Drosophila increased progressively with fly age, successfully distinguished young and old mice, and captured age-associated stratification across the elephant lifespan. Notably, lipid metabolism, particularly carnitine and fatty acid metabolism, together with nucleotide-related pathways, consistently emerged as the core features of aging across analyses. These findings suggest pathway-level metabolic remodeling is a recurrent feature of cross-species aging.

Canagliflozin (Cana), an SGLT2 inhibitor prescribed for type 2 diabetes, extends median lifespan by 14% in male but not female UM-HET3 mice at 180 ppm, with male-specific neuroprotective effects, despite females accumulating higher drug concentrations in blood and brain. Here, we tested whether reducing the dose to a subclinical level of 60 ppm could provide neuroprotective benefits in females by reducing drug accumulation. Starting treatment at 7 months of age, Cana at 60 ppm improved glucose tolerance in both sexes at 18 months and increased water and food intake, consistent with SGLT2 inhibition, but produced only a transient reduction in fat mass in males after one month on diet, with no sustained effect on body weight in either sex. At 60 ppm, Cana did not improve cognitive function at 18 months or reduce neuroinflammation in males, whereas females showed reduced hippocampal microgliosis and astrogliosis at 24 months. Pharmacokinetic analysis demonstrated that females accumulated 3- to 5-fold higher Cana concentrations than males across brain regions, blood, and liver. Together, these findings demonstrate that neither dose reduction nor greater drug accumulation drives neuroprotective benefit in females, indicating fundamental sex differences in the biological response to SGLT2 inhibition and suggesting that the sex-specific longevity effects of Cana are not simply a matter of dose.

A growing body of literature has investigated the relationship between age and biomolecular changes, leading to conclusions that aging occurs in discrete molecular "waves." Data summary tools such as LOESS and sliding window analyses like DE-SWAN are common approaches that have gained acceptance in recent years. We demonstrate via simple simulations that these tools can identify non-linear patterns of aging where they do not exist. Specifically, we show that (i) clustering of molecular trajectories using LOESS can lead to artifactual characteristic patterns of molecular aging, (ii) "waves" of aging identified using the combination of LOESS and DE-SWAN in real data are not robust to changes in the underlying age distribution and are not supported by valid permutation testing, and (iii) DE-SWAN alone can generate pronounced "waves" of nonlinear molecular aging in linear data due to differences in statistical power along the age continuum. Our results specifically challenge the statistical support for discrete aging crests inferred in the literature, but do not rule out nonlinear molecular aging or age-associated transitions that may be detectable using other cohorts and statistical models.

Background. Randomized controlled trials (RCTs) remain the reference standard for establishing clinical efficacy for candidate drugs, but their restrictive eligibility criteria limit generalizability, and for dietary supplements the body of well-powered RCTs is small relative to the number of proposed health claims. Self-reported real-world data (RWD) by patients in social media are increasingly recognized as a complementary evidence source, yet their value in the nutraceutical domain is largely uncharacterized. Objective. To test whether benefits that users positively report for natural ingredients on Reddit are statistically associated with benefits demonstrated for those ingredients in the clinical-trial literature, and to characterize what a community corpus can reveal about application areas and side effects. Methods. We assembled a cross-sectional corpus of 216,350 distinct comments from 86 supplement-related subreddits (January 2022 - April 2026), covering 329 canonical ingredients and a shared, MeSH/MedDRA-aligned vocabulary of 581 benefit terms. Comment-level directionality (benefit/no-effect/irrelevant) was assigned by a natural-language-inference model. The independence of clinical efficacy and Reddit endorsement was tested with 2x2 chi-squared and Fisher exact tests across a sweep of endorsement thresholds, plus per-ingredient tests with Bonferroni correction. Results. Of 31,359 unique (ingredient, benefit) pairs, 2,508 were efficacy-demonstrated under the primary definition. The two signals were statistically associated. The association strengthened monotonically with endorsement volume, reaching OR 3.06 at [≥]20 comments and 7.14 at [≥]100. Among heavily-endorsed benefits ([≥]100 comments) 38% were RCT-demonstrated, versus ~9% overall. Community attention concentrated on sleep, skin and anxiety, whereas the trial literature concentrated on cardiovascular, pain, metabolic and mood indications. The most discussed and clinically validated nutraceutical-health claim pairs include melatonin-sleep cycle and quality, ginger with gastrointestinal relief and zinc with skin conditions. The concordance analysis revealed that 81% (573/711) of clinically proved nutraceutical-health claim pairs were in agreement with the reported experience of the Reddit community. Conclusions. Community endorsement and clinical efficacy are independent at the single-comment noise floor but positively concordant once a benefit is endorsed by multiple users, with concordance rising with consensus. Reddit-derived RWD is a useful hypothesis-generating prior for nutraceutical efficacy and a complementary, though not confirmatory, signal for prioritizing ingredients and indications for formal clinical study taking into consideration personalized characteristics.

Sex differences influence the incidence, timing, clinical presentation, and outcomes of cardiovascular disease (CVD), yet the molecular programs through which aging interacts with biological sex remain insufficiently understood. To address this gap, we integrated basal gene expression profiles from multiomics data across 981 donors and 17 CVD-relevant tissues with regulatory, genetic, network, disease-expression, and druggability information to characterize sex-dimorphic aging patterns in 1,176 candidate CVD genes. Using a two-step expression analysis, we identified 4,404 genes with significant age-associated expression trends (BH-FDR < 0.05), including 2,718 male-specific, 202 female-specific, and 742 shared trends. Concordant evidence across complementary statistical approaches highlighted 35 high-confidence sex-dimorphic genes, including REN, APOE, GUCY1A2, and SRD5A2. Regulatory analysis showed that most CVD genes were influenced by nearby genetic variants, with 96.2 Network-based analyses further suggested that CVD genes are organized within hierarchical biological structures, with curated protein-interaction data showing stronger geometric organization than broader interaction resources. Integration with Open Targets identified 289 genes already linked to approved drugs and 48 of the top 50 biomarker candidates supported by GWAS-eQTL colocalisation evidence. A final composite ranking prioritized NTRK1, TUBB4A, PTGS2, IL6, and PDE5A, and identified 19 actionable biomarkers supported by convergent expression, regulatory, genetic, and therapeutic evidence. Among these, a dedicated sex-specific evidence score nominated GUCY1A2, CACNA1D, PGR, PDE5A, and LEPR as the strongest candidates for sex-stratified validation, with GUCY1A2 and PDE5A converging on a nitric oxide-cGMP signaling axis. This study provides an integrative framework for discovering sex-dependent molecular signatures of cardiovascular aging and for prioritizing biologically supported, potentially actionable targets for precision cardiovascular medicine.

Aging is caused, fully in large part, by the progressive accumulation of damage, yet quantifying age-related damage across tissues and conditions remains a challenge. Here, we present a computational framework to quantify damage from standard RNA-sequencing data. It captures four classes of aberrant transcript structures, including premature termination upon intron retention, domain-disrupting splice variants, repeat elements, and gene fusion events, each reflecting distinct forms of RNA integrity loss. Using this method, we revealed a robust age-associated increase in transcriptomic damage across tissues. To integrate these measurements into a unified biomarker, we constructed a transcriptomic damage-based aging (tDamAge) clock using machine learning models trained across mouse tissues or human peripheral blood. It could predict age and detect transcriptomic shifts under both pro-aging and anti-aging conditions. Progeroid models exhibited accelerated tDamAge, whereas interventions such as caloric restriction, rapamycin, and methionine restriction lowered tDamAge. Cross-dataset analysis showed that diverse anti-aging interventions converge on shared transcriptomic signatures, particularly RNA processing and chromatin organization pathways, and these age-associated patterns could be reversed by interventions. We further identified elevated damage age acceleration in Alzheimers disease and observed rejuvenation-like reductions during embryonic development. Together, our findings establish transcriptomic damage as a causal, quantifiable and biologically interpretable feature of aging and demonstrate that tDamAge could detect age progression, acceleration, deceleration, and reversal.

Automated, accurate, and fast developmental-stage classification of C. elegans from microscopy-based morphological images is essential for aging research, drug screening, and disease modeling. However, it remains challenging due to morphological similarities between stages and the limited annotated data. In this work, we propose HyperDev, a hyperbolic few-shot learning framework that addresses these limitations by directly encoding developmental hierarchies in the embedding space, unlike conventional Euclidean approaches that treat stages as independent classes. HyperDev uses Poincare ball geometry, combined with a biologically informed developmental prior, to naturally represent stage relationships. We introduce our self-curated C. elegans dataset spanning seven developmental stages (Egg, L1-L4, Adult, Dauer) with extreme class imbalance (6-8 samples per minority class). HyperDev achieves competitive classification accuracy (76.9-88.3%) while providing intrinsic explainability across nine 7-way few-shot evaluation settings. The learned embeddings exhibited strong biological alignment (Pearson r = 0.669, p < 0.001), while significantly outperforming ProtoNet (r = 0.187), MatchingNet (r = 0.235), and RelationNet (r = 0.464). These results establish hyperbolic geometry as a principled approach to explainable few-shot learning in biological imaging, where understanding learned representations is as critical as predictive performance. Clinical RelevanceBy enabling explainable, data-efficient developmental staging from scarce samples, HyperDev supports improved phenotype quantification for aging research, disease modeling, and drug screening.

Aging is associated with a progressive decline in cognitive function, including the ability to adapt behavior based on its consequences. While classical conditioning in Drosophila melanogaster has provided key insights into reinforcement learning, how aging impacts operant learning and adjusting behavior based on action outcomes remains unclear. Here, we used a closed-loop optogenetic paradigm to test how aging affects operant learning and the role of dopaminergic neurons (DANs; PPL1 and PAM) in this process. Activation of distinct DAN subsets revealed that both young and aged flies retain PPL1-dependent avoidance learning, indicating preserved action-outcome learning with age. However, learning in aged flies depended on prolonged reinforcement: unlike young flies, they failed to learn under shorter optogenetic stimulation durations, suggesting an aging-associated reduced dopaminergic reinforcement rather than a loss of learning capacity. Moreover, reducing mitochondrial antioxidant capacity via SOD2 knockdown in PPL1 neurons phenocopied the aging-related deficit, implicating oxidative stress in impaired reinforcement signaling. In contrast, broad PAM neuron activation drove robust learning across ages and stimulation regimes. Nevertheless, functional dissection of PAM subpopulations revealed subtype-specific aging-associated vulnerability within dopaminergic circuits. In line with the behavioral data, PPL1 but not PAM neurons exhibited age-dependent reductions in cell size. Together, our findings suggest that aging selectively reduces dopaminergic reinforcement in a DAN subtype-dependent manner while preserving the capacity for operant learning. Increasing reinforcement length rescues this deficit, indicating that altered dopaminergic signaling, rather than impaired learning capacity, is a key driver of age-related cognitive decline.

Mitochondrial diseases (MDs) are clinically heterogeneous rendering ascertainment challenging. Estimates of pathogenic mitochondrial DNA (mtDNA) variants in the population range from 1 in 200 to 1 in 4,000 individuals. Inclusion of mtDNA sequencing in genomic databases facilitates comprehensive estimation of mtDNA variation. However, interpretation of low heteroplasmy variation is complex, due in part to misalignment of nuclear mitochondrial DNA transcripts (NUMTs), whilst conservative heteroplasmy thresholds likely omit relevant variation. Cumulative burden of mtDNA variation contributes to aging and neurodegeneration, and recent characterisation of mitochondrial genome constraint allows quantitation of this burden. We analysed whole genome sequencing of blood DNA from 3,500 healthy older individuals in the Medical Genome Reference Bank using mity, considering pathogenic mtDNA variants [&ge;]1% heteroplasmy. We identified 34 distinct pathogenic mtDNA variants in 62 individuals, giving a combined population allele frequency of 1.77% (95% CI 1.36-2.27) or 1 in 56 individuals. We evaluated inclusion of false positive (FP) calls due to two common NUMTs, which accounted for up to 16% of variants. Increasing heteroplasmy thresholding to eliminate all NUMT-FPs also eliminated much of the total variation, including pathogenic variants. We propose a sample-specific, scaled heteroplasmy threshold to maximise variant retention and mitigate NUMT-FPs. Finally, we characterised measures of mitochondrial constraint in this healthy older cohort, observing an association between variant burden and summed constraint, whilst mean constraint was higher in pathogenic variant carriers. These findings suggest pathogenic mtDNA variation is more common in the population than is currently appreciated. Findings are comparable to larger genomic databases when heteroplasmy thresholding is adjusted, and support earlier population-based estimates. Incorporation of low heteroplasmy variation is relevant, but interpretation is nuanced, and optimising variant retention requires consideration of NUMT-FP rates.

Rapamycin extends lifespan across species, yet its cell-type-specific benefits and vulnerabilities remain unclear at whole-organism scale. Here, we present the Rapamycin Fly Cell Atlas (Rapa-FCA), a whole-organism single-nucleus transcriptomic atlas of Drosophila spanning both sexes, multiple ages, 18 cell classes, and 181 cell types. Rapamycin elicited a highly heterogeneous response, with prominent effects in reproductive, digestive, and neuromuscular systems and modest responses in most neuronal populations. Across diverse tissues, we identified a rapamycin-sensitive Convergent Aging Trajectory (CAT), marked by Fkbp12 enrichment and mTORC1-linked metabolic programs, including glycolysis and lipid synthesis. CAT-high nuclei accumulated with age and were preferentially reduced by rapamycin, especially in females, consistent with stronger female lifespan extension. By integrating CAT abundance, aging-clock predictions, and nucleus-ratio changes, we mapped sex- and cell-type-specific geroprotection effects of rapamycin. Together, the Rapa-FCA provides an organism-wide framework for resolving how rapamycin reshapes cellular aging across sex, tissue, and cellular state.

Geroscience clinical trials need biomarker surrogate endpoints for healthspan. Leading candidates are omics-based composites developed from machine learning analysis of aging phenotypes including calendar age, survival, functional capacity, and Pace of Aging. Existing Pace of Aging biomarkers were developed in the Dunedin Longitudinal Study, limiting inference about strengths/weaknesses of the method as distinct from the Study, a unique single-year birth cohort followed through midlife with near-perfect retention and uniform measurement of multi-organ-system function across two decades of follow-up. We adapted our Pace of Aging method for mixed-age cohorts with variable follow-up of organ-function measures and applied it to develop a novel DNA methylation biomarker of Pace of Aging in data from the Framingham Heart Study Offspring Cohort, FraminghamPACE. Validation analyses across four independent cohorts and one clinical trial establish advantages for the Pace of Aging method in developing biomarkers that are both predictive of healthspan and responsive to geroprotective intervention.

Aging is associated with progressive tissue dysfunction and impaired repair after injury. In the retinal pigment epithelium (RPE), these changes contribute to age-related macular degeneration (AMD), yet the mechanisms limiting repair remain incompletely understood. Here, we establish a longitudinal human embryonic stem cell (hESC)-derived RPE aging model that recapitulates key features of aged human donor RPE and combine it with mosaic cell ablation to assess injury-responsive repair. Although aged RPE cells initiate DNA synthesis after injury, they exhibit impaired mitotic progression, uncoupling S-phase entry from epithelial repopulation. Transcriptomic profiling links this defect to a senescence-associated program marked by inflammatory signaling and suppressed mitotic networks. Pharmacologic reduction of senescent cells with Navitoclax shifts aged RPE toward a younger transcriptional profile but does not induce repopulation by itself. Instead, senolytic treatment primes aged RPE for repair, improving epithelial density and homeostatic function only in response to injury, a strategy we term "senolytic priming." These findings establish a human stem-cell-derived platform for investigating age-associated epithelial repair failure and show that aged human RPE retains latent repair capacity that can be re-enabled by targeting cellular senescence.

Cell size is a critical morphological parameter determining cellular functional homeostasis, yet existing large-scale transcriptomic databases lack direct cell size measurement data. By integrating high-resolution immunofluorescence images with transcriptomics, we identified 457 genes significantly correlated with cell area. Based on these findings, we developed an algorithm, Cell Size Score (CSS), to predict cell size from gene expression profiles. Validation across multiple independent datasets, including human cell lines, mouse models, and single-cell spatial transcriptomics, confirmed that CSS accurately predicts cell size. Furthermore, we observed a significant positive correlation between CSS and broad-spectrum chemotherapy drug resistance, suggesting that increased cell volume confers survival advantages to cancer cells. Moreover, CSS analysis of aging revealed sex-dependent, tissue-specific patterns of change, wherein male adipose and cardiac tissues exhibited progressive hypertrophy with age, while female reproductive organs showed significant atrophy. Additionally, CSS significantly increased in skeletal muscle after exercise, indicating that this metric can capture dynamic physiological adaptation processes. This study establishes a bridge between transcriptomics and cell morphology, providing novel insights into retrospectively analyzing the role of cell size in pathological and physiological processes such as cancer and aging using existing omics data, as well as understanding the molecular mechanisms underlying cell size regulation.