npj Aging

Background: Accelerated biological aging (BioAgeAccel) has been implicated in type II diabetes (T2D) mellitus development; however, its dynamic changes and their links to T2D incidence, mortality and glycemic traits remain unclear. Methods: Leveraging repeated measures from the UK Biobank, we first calculated two BioAgeAccel metrics (KDMAccel and PhenoAgeAccel) and derived three burdens (slope, cumulative, and relative cumulative change). We then assessed associations of BioAgeAccel transitions and these burdens with incident T2D and mortality. Secondary analyses extended the two primary outcomes by incorporating glucose, HbA1c, and six IR surrogates, which were also evaluated as potential mediators. Results: Among 13,751 included participants, 412 (3.0%) new T2D cases and 609 (4.4%) all-cause deaths were identified within a median follow-up of 9.5 years. Dynamic transition from non-accelerated to accelerated aging was markedly related to elevated T2D risk (KDMAccel: HR=1.65 [1.24~2.20]; PhenoAgeAccel: HR=1.50 [1.12~2.00]) and all-cause mortality risk (KDMAccel: HR=1.32 [1.06~1.64]; PhenoAgeAccel: HR=2.17 [1.73~2.71]). BioAgeAccel burdens demonstrated dose-response effects, with cumulative BioAgeAccel showing the greatest influence on T2D (KDMAccel: HR=1.25 [1.03~1.51]; PhenoAgeAccel: HR=1.26 [1.06~1.49]) and all-cause mortality (KDMAccel: HR=1.25 [1.07~1.47]; PhenoAgeAccel: HR=1.51 [1.31~1.74]). Similar association patterns were observed for all the eight glycemic traits. Mediation analyses revealed that these glycemic traits on average mediated 19~32% of the KDMAccel burden-T2D effect and 16~24% of the PhenoAgeAccel burden-T2D effect. Incorporating BioAgeAccel burden into FINDRISC significantly enhanced prediction accuracy, reaching up to 10.9% improvement in some specific aging transition statuses. Conclusion: Dynamic biological aging trajectories and BioAgeAccel burdens are independently related to elevated risks of T2D and all-cause mortality, partly via glycemic dysregulation, highlighting biological aging as a potential intervention target.

Frailty is an age-related syndrome characterized by biological dysfunction and reduced physiological reserve in response to stressors. Its prevalence is increasing with population aging, resulting in a substantial health burden due to adverse outcomes on health, such as cardiovascular disease and mortality. Ultra-processed foods (UPFs), defined as industrial formulations made primarily from processed ingredients, have received increasing attention due to their potential role in the development and progression of frailty. This systematic review and meta-analysis examined the association between ultra-processed food intake and the risk of frailty in older adults. This study systematically searched for all relevant studies published up to January 2026. Ten observational studies involving 105327 participants, comprising 6 prospective and 4 cross-sectional studies, were included in the systematic review, of which 6 were eligible for meta-analysis. Random-effects models were employed to estimate pooled effect sizes and 95% confidence intervals (95% CIs). Meta-analysis showed that higher consumption of UPFs was significantly associated with an increased risk of frailty (pooled OR = 1.43, 95% CI = [1.02-2.005], p = 0.041). Narrative synthesis further supported a positive association between UPF intake and frailty or related outcomes. Our findings suggest that a higher consumption of ultra-processed foods may contribute to frailty risk, potentially through inflammatory pathways. However, given the high heterogeneity, results should be interpreted with caution. Overall, our findings suggest that reducing UPF consumption may be a promising target for public health strategies to prevent frailty in ageing populations.

Background: Epigenetic clocks based on DNA methylation (DNAm) have emerged as promising biomarkers of biological aging, yet their associations with cognitive performance remain inconsistent. This study investigates the relationship between epigenetic age acceleration and cognitive performance in older adults using 14 DNAm clocks from five generations of development. Methods: We analyzed data from the Berlin Aging Study II (BASE-II) using genome-wide DNAm profiles and cognitive assessments ascertained at baseline (T0) and two follow-up time points (T1, T2) in up to 1,014 individuals. DNAm-based age and age acceleration estimates were calculated using Biolearn and MethylCIPHER. Analyses focused on cross-sectional and longitudinal associations between DNAm clock estimates and cognitive performance, including sex-specific effects and comparisons with frailty as non-cognitive positive control. Results: Among all tested DNAm clocks, DunedinPACE (a third-generation clock) showed the strongest and most consistent associations with cognitive performance. In addition, the fifth-generation SystemsAge framework also demonstrated robust associations with cross-sectional and longitudinal cognitive outcomes. In contrast, second-generation clocks (GrimAge [v2], PhenoAge) showed occasional nominal associations, while first-generation clocks (Horvath [v1], Hannum) and the causally-informed, fourth-generation clocks (e.g. YingCausAge, YingDamAge) showed no noteworthy signals. Likewise, telomere length estimated from DNAm was not strongly associated with cognitive performance in this dataset. Conclusions: Our findings highlight DunedinPACE as a particularly informative biomarker for various aspects of cognitive aging, while other DNAm aging measures showed no consistent associations. Future work should further refine domain-specific epigenetic biomarkers to improve biological aging assessments and achieve a more reliable early detection of cognitive decline.

Purpose: To evaluate whether chest radiograph-derived age acceleration is associated with incident lung cancer and whether it improves discrimination beyond established lung cancer risk factors. Materials and Methods: This retrospective analysis used prospectively collected data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Baseline digitized chest radiographs from the initial screening year were analyzed using a previously validated deep learning model that estimates chest radiograph-derived age (Xp-age). Age acceleration (AgeAccel) was defined as the residual of Xp-age after calibration to chronological age using a regression model from the development dataset. A 1-year landmark design excluded participants diagnosed with lung cancer or censored within 1 year of baseline. Associations with incident lung cancer were assessed using multivariable Cox proportional-hazards models adjusted for prespecified demographic and clinical predictors, including smoking variables used in the PLCOm2012 risk prediction model. Discrimination was evaluated using the concordance index and 6-year time-dependent area under the receiver-operating-characteristic curve. Results: The analytic cohort included 23,213 participants (mean age, 62.5 years); 790 developed incident lung cancer after the landmark (mean follow-up, 16.7 years). Higher AgeAccel was associated with increased lung cancer incidence (hazard ratio, 1.10 per 1-SD increase; 95% confidence interval: 1.03- 1.17); however, addition of AgeAccel to an established risk factor model resulted in minimal change in discrimination (C-index, 0.840 vs. 0.839; time-dependent AUC at 6 years, 0.852 vs. 0.852). Attribution maps emphasized the aortic arch/mediastinal region with similar spatial patterns across smoking and lung cancer strata. Conclusion: Chest radiograph-derived age acceleration was independently associated with future lung cancer incidence.

AbstractAs organisms age, mitochondrial metabolic activity declines, and disrupted gene expression regulation mediated by histone acetylation induces the emergence of senescent physiological phenotypes in tissues. In this study, we found that periodic exposure to red light significantly increased histone H3 Lys9 acetylation (H3K9ac) levels in the tissues and organs of aged mice. Following red light exposure, silent information regulation factor 4 (SIRT4) protein levels in keratinocytes were notably reduced, whereas glycolysis, fatty acid metabolism, and the tricarboxylic acid (TCA) cycle were significantly activated in keratinocytes. The reduction in mitochondrial SIRT4 levels enhances the acetylation of mitochondrial metabolic proteins, particularly malonyl-CoA decarboxylase (MCD), a potent inhibitor of the key rate-limiting enzyme carnitine palmitoyltransferase 1A (CPT1A) in fatty acid oxidation. This process promotes mitochondrial fatty acid oxidation and TCA cycle. Additionally, the decrease in SIRT4 activates SIRT1 through feedback mechanisms, thereby alleviating its inhibition on PPAR- in senescent keratinocytes and comprehensively activating the expression of genes related to lipid metabolism. This lipid metabolism activation ultimately facilitates the accumulation of acetyl-CoA within keratinocytes, increases H3K9ac levels, and reshapes the expression patterns of senescence-related genes. Eventually, cellular aging is effectively mitigated by the synergistic regulation of metabolism, inflammation, and gene expression. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/717004v1_ufig1.gif" ALT="Figure 1"> View larger version (76K): org.highwire.dtl.DTLVardef@a3387dorg.highwire.dtl.DTLVardef@1d1b083org.highwire.dtl.DTLVardef@19ba6f0org.highwire.dtl.DTLVardef@1ecf20e_HPS_FORMAT_FIGEXP M_FIG Mechanism of anti-aging action of red light: Red light can reduce SIRT4 signalling in keratinocytes, thereby reactivating lipid metabolism and increasing levels of acetyl-CoA. This promotes histone acetylation, which in turn reverses the expression of age-related inflammatory factors and genes. C_FIG

Biological-age models quantify the physiological aging process by relating biomarker profiles (e.g., blood biochemistry, DNA methylation) to all-cause mortality risk. These models outperform chronological age in predicting disease and mortality, making them useful metrics for preventative health. However, in existing biological-age models, biomarker contributions do not align with the non-linear associations biomarkers exhibit with long-term mortality risk, nor do they account for normative trajectories that occur in healthy aging, limiting their utility in a clinical setting. To address these limitations, we developed a biological-age framework (NiaAge) where biomarker contributions are derived directly from non-linear associations with long-term mortality risk and aligned with normative trajectories observed in healthy aging. As a result, biomarker contributions to NiaAge are consistent with known biomarker risk profiles and normative reference ranges. We trained NiaAge in the 1999-2000 cohort of the US National Health and Nutrition Examination Survey (NHANES; N=2028) on 59 biomarkers spanning multiple physiological domains (e.g., hematology, metabolism, inflammation), then evaluated it in the 2001-2002 cohort (N=2346). NiaAge predicted long-term mortality, physical-health, and cognitive-health significantly better than chronological age. It also outperformed several DNA-methylation age clocks on mortality and physical/cognitive health-span metrics, while performing comparably to leading physiological age clocks. These results position NiaAge as a valuable tool for preventative health.

Background: The role of biological age acceleration (BioAgeAccel) in the dynamic progression from single cardiovascular-kidney-metabolic disease (CKMD) to multimorbidity, and subsequently to dementia and mortality remains elusive. Methods: We conducted a longitudinal study with data of 433,911 UK Biobank participants. Cardiovascular-kidney-metabolic multimorbidity (CKMM) was defined as the coexistence of two or more CKMDs, including cardiovascular disease (CVD), stroke, type 2 diabetes (T2D), and chronic kidney disease. Biological aging was measured via PhenoAge and KDM-BA. Multistate models examined the association between BioAgeAccel and disease transitions, ranging from healthy to the first occurrence of CKMD (FCKMD), then progression to CKMM, dementia, and mortality. Restricted mean survival time estimated the disease transition time or life expectancy between states. Results: BioAgeAccel was significantly associated with increased risks across all disease transitions. Specifically, during CKMM progression, the hazard ratios (HRs) of the transition from healthy to FCKMD were 1.24 [95%CI 1.23-1.25] for PhenoAgeAccel and 1.16 [1.15-1.17] for KDM-BA-Accel. For subsequent transition to CKMM, the HRs were 1.20 [1.18-1.22] and 1.19 [1.17-1.21], respectively. In dementia-related transitions, PhenoAgeAccel showed the higher risk for CKMM to dementia (HR=1.13 [1.04-1.22]) than for the transition from healthy or from FCKMD to dementia. These associations were further moderated by age, physical activity, educational, and lifestyle factors. BioAgeAccel also accelerated disease progression and reduced life expectancy; for example, during CKMM progression, BioAgeAccel shortened the time between disease transitions by about 1.09 years from healthy to FCKMD, and an additional 1.75 years to CKMM. Regarding life expectancy, individuals with CKMM experienced an average reduction of about 1.36 years under PhenoAge, while those with dementia showed a decrease of about 0.77 years. Among individuals with CVD or T2D as the initial diagnosis, the impact of BioAgeAccel on progression to CKMM or dementia was stronger. Conclusions: BioAgeAccel exerts significant promotive role in the onset of CKMD and their subsequent progression to CKMM, dementia, and mortality, helping identify high-risk individuals. Implementing biological age assessments and health lifestyle interventions in middle-aged populations serves as an effective strategy for alleviating the burden of CKMDs and dementia.

Aging is associated with a progressive loss of skeletal muscle function, known as sarcopenia; however, the molecular mechanisms coordinating cellular stress responses and structural adaptations permissive of sarcopenia remain incompletely understood. In our previous studies, we found aging differentially impacted mitochondrial networks by muscle, suggesting unique stress thresholds and response activation. Here, we investigate the role of activating transcription factor 4 (ATF4), a master regulator of the integrated stress response (ISR), in aged quadriceps muscle using complementary patient and aging mouse models. Older adults exhibited a marked decrease in aerobic capacity, muscle strength, and endurance when compared with young participants. These results paralleled findings in aged mice, with significant loss of muscle mass across multiple hindlimb muscles. Ultrastructural analysis revealed substantial age-related changes in mitochondrial morphology, including increased volume, surface area, and branching index, as well as a shift toward larger, more complex mitochondria. Our data indicate that ATF4 binds directly to the promoter region of the gene encoding TFAM, suggesting a transcriptional regulatory relationship to support DNA stability. These structural and transcriptional changes likely impair oxidative capacity and drive a feed-forward cycle of mitochondrial dysfunction and ISR activation. Our findings indicate that ATF4 coordinates transcriptomic and structural adaptations in aging muscle, identifying the ISR pathway as a potential therapeutic target for preserving muscle function in older adults.

BackgroundOlder adulthood is often accompanied by declines in auditory processing and cognitive functioning, increasing the risk of reduced autonomy and quality of life. Multidomain lifestyle interventions have shown potential to counteract these changes, and choir-based activities represent a promising approach by simultaneously engaging auditory, cognitive, physical, and social domains. However, evidence regarding their feasibility and neurophysiological impact in community-dwelling older adults, particularly those without formal musical training, remains scarce. MethodsThis 9-month quasi-experimental feasibility study involved 54 community-dwelling older adults (mean age = 72.9 years) with no formal musical background. Participants self-selected into a choir-based intervention group, an active control group engaging in non-musical leisure activities, or a passive control group; however, some participants in the control groups were selected from the waiting list for the choir. Assessments were conducted at baseline and follow-up and included measures of global cognition, cognitive reserve, psychological well-being (Flourishing Scale), multidimensional frailty (Selfy-MPI), music perception, pure-tone audiometry, and auditory evoked potentials recorded using a standardized clinical oddball paradigm. ResultsThe choir-based intervention was feasible in a community setting. At the neurophysiological level, choir participation was associated with a bilateral, significant shortening of the N2-P3 inter-peak latency, indicating faster auditory-cortical processing. Additionally, through explorative analyses multidimensional frailty, as assessed by the Selfy-MPI, showed a significant reduction in individuals engaging in a higher number of activities, irrespective of group allocation. Similarly, psychological well-being revealed a decrease in flourishing scores in the passive control group relative to the choir group. No changes were observed in audiometric thresholds or music perception measures. ConclusionChoir-based multidomain participation is a feasible intervention for community-dwelling older adults without formal musical training and is associated with selective benefits in cognitive reserve, psychological well-being, auditory-cortical processing speed, and multidimensional frailty. These findings provide a foundation for a larger randomized controlled trial aimed at clarifying the cognitive, psychosocial, and neural mechanisms underlying choir-based interventions in ageing. Trial RegistrationThe upcoming trial has been prospectively registered on ClinicalTrials.gov (ID: NCT06767410; registration date: January 9, 2025).

Age-related cognitive decline and depressive symptoms are prevalent in later life, yet the genetic determinants of vulnerability remain unclear. Here, we investigated how genetic and epigenetic regulation of the serotonin transporter gene SLC6A4 contributes to susceptibility to these age-related conditions in later life. In community-dwelling older adults in Japan (N = 1,317), functional stratification of the serotonin transporter-linked polymorphic region (5-HTTLPR) revealed that participants with low-activity genotypes showed a robust co-occurrence of cognitive decline and depressive symptoms, whereas this comorbid pattern was not observed in those with the high-activity genotype. The genotype-dependent co-occurrence was consistently replicated across seven independent population-based cohorts (total N = 7,889). DNA methylation at a functional promoter CpG site increased with age and partially mediated age-related cognitive decline specifically among low-activity genotypes. In contrast, the high-activity genotype was associated with relative resistance to these functional declines, partly mediated by a protective effect on hippocampal volume during aging. Notably, genotype-dependent effects on hippocampal volume were absent in adolescence, indicating that the influence of SLC6A4 emerges in an aging-specific manner. Together, these findings identify SLC6A4 promoter activity as a key genetic factor modulating vulnerability and resilience in later life.

Background: This study investigates whether proteomic aging clocks (PACs) are associated with cerebral small vessel disease (CSVD). Methods: We included participants from two US community-based cohorts: the Atherosclerosis Risk in Communities (ARIC) Study and the Multi-Ethnic Study of Atherosclerosis (MESA) Study. These analyses leveraged PACs that were developed in ARIC using proteomics measured by SomaScan in midlife (Visit 2; mean age 56 y; n=1,486) and late-life (Visit 5; mean age 76 y; n=1,496), trained on chronological age. Proteomic age acceleration (PAA) was calculated as residuals from regressing PACs on chronological age. 3T brain MRI data were collected in late-life. We examined associations of PAA with log-transformed white matter hyperintensity (WMH) volume using linear regression and with the presence of microbleeds, and subcortical, lacunar, and cortical infarcts using logistic regression. Associations of PACs with WMH volume and microbleeds were tested in MESA using proteins measured at Exam 1 (mean age 57 y; n=932) and Exam 5 (mean age 66 y; n=934). All associations were quantified per 5-year increase in PAA. All models were adjusted for demographics and cardiovascular risk factors. Results: In ARIC, higher midlife PAA was associated with greater WMH volume (percent difference: 25% [95% CI: 13%, 39%]) and higher odds of subcortical infarcts (OR: 1.24 [1.02, 1.51]). Late-life PAA was associated with all CSVD markers: WMH volume (percent difference: 20% [8%, 34%]), cerebral microbleeds (OR: 1.40 [1.15, 1.69]), subcortical (OR: 1.80 [1.47, 2.22]), lacunar (OR: 1.80 [1.46, 2.23]), and cortical infarcts (OR: 1.39 [1.07, 1.82]). In MESA, higher late-life PAA was associated with greater WMH volume (28% [3%, 58%]) but not with microbleeds. Conclusion: Accelerated proteomic aging is associated with a higher prevalence of MRI markers of CSVD, most predominantly in late-life. Understanding this relationship may help stratify those at higher risk of CSVD at an early stage.

Declining spatial navigation abilities are a critical hallmark of aging, where the loss of spatial abilities precedes global cognitive impairment. While navigational decline is traditionally attributed to deficits in higher-order cognitive functions, emerging cognitive-motor frameworks suggest that age-related sensorimotor alterations play a significant, yet previously overlooked, role. Here, we investigate the coupling between locomotor integrity and navigation by combining an immersive virtual-reality path-integration paradigm with systematic manipulations of landmark availability and reliability, while recording gait kinematics alongside neural dynamics using high-density mobile-EEG from 30 young and 32 older adults. We demonstrate that older adults accumulate angular homing error more rapidly than younger adults, a deficit linked to altered gait dynamics. These age-dependent differences are reflected in increased mid-frontal theta activity, highlighting a robust coupling between gait-related sensorimotor alterations and decline in navigation. Older adults also exhibited increased reliance on visual landmarks, and particularly those with degraded gait, yet this compensatory reweighting of navigational cues remained less efficient and less precise than in younger adults. These findings highlight sensorimotor gait alterations as a central determinant of age-related navigation deficits, challenging the traditional separation of motor and cognitive domains and identifying locomotor integrity as a critical target for preserving spatial navigation abilities.

Frailty, defined by progressive loss of physiological resilience, neuromuscular function, and cognitive capacity, is a central manifestation of biological aging yet remains difficult to quantify in scalable experimental systems. Here, we introduce a Composite Frailty Index (CFI) in the house cricket (Acheta domesticus) that integrates automated measures of locomotion, exploratory behavior, and freezing into a unified, quantitative framework of functional decline. Ten behavioral parameters derived from automated open-field tracking, including locomotor performance, exploratory behavior, and freezing were integrated into the CFI. Locomotor states were classified using k-means clustering (k = 2) of velocity distributions, and all features were normalized to age- or treatment-matched reference populations, discretized into quintiles, and summed to generate a 0-40 frailty score. Aging cohorts (young adult: 4-6 weeks; geriatric: 10-12 weeks, N = 103) and pharmacological cohorts treated at mid-life (8-10 weeks) with rapamycin (14 ppm), acarbose (1000 ppm), or phenylbutyrate (1000 ppm) were evaluated (N = 122). Across chronological aging cohorts, CFI increased from young adults to geriatrics in both females (d = 1.14 [95% CI: 0.53, 1.76], P = 0.0003) and males (d = -1.17 [95% CI: -1.75 to -0.59], P < 0.0001). Using pharmacological intervention cohorts, mid-life rapamycin treatment reduced late-life frailty relative to controls in both females (d = -1.31 [95% CI: -2.09, -0.53], P = 0.0017) and males (d = -1.33 [95% CI: -2.09, -0.58], P = 0.0004), whereas acarbose and phenylbutyrate produced inconclusive effects (ds = -0.54 to -0.03; Ps > 0.05). Together, these findings establish the cricket CFI as a scalable, high-throughput platform for quantifying multidimensional functional aging and prioritizing candidate geroprotective interventions based on clinically relevant endpoints beyond lifespan.

Sulfide:quinone oxidoreductase (SQR) is a critical enzyme that maintains sulfur metabolism by oxidizing sulfide to supersulfides, currently defined as sulfur metabolites with six valence electrons and no charge that are covalently catenated with other sulfur atoms and excludes disulfides. While SQR is known to contribute to mitochondrial electron transport, its physiological impact on systemic energy metabolism and longevity remains largely undefined. In this study, we investigated the role of SQR in mitochondrial bioenergetics and aging using SQR-deficient Schizosaccharomyces pombe ({Delta}hmt2) and a mitochondria-selective SQR-deficient (Sqrdl{Delta}N/{Delta}N) mice model. Functional analysis demonstrated that{Delta} hmt2 grew normally in glucose but not in glycerol, indicating impaired mitochondrial respiration. It showed reduced membrane potential, ATP, and lifespan. Consistent with the yeast findings, Sqrdl{Delta}N/{Delta}N mice exhibited accumulated levels of hydrogen sulfide and persulfides, and demonstrated impaired mitochondrial energy metabolism. Furthermore, supersulfide donor supplementation selectively conferred lifespan extension in wild-type yeast, but not in SQR-deficient strain, and similarly improved mitochondrial function exclusively in wild-type mouse embryonic fibroblasts, with no benefit observed in SQR-mutant counterparts. Together, our findings demonstrate that mitochondrial SQR plays an essential role in sulfur respiration, critically supporting mitochondrial function and organismal longevity across eukaryotes. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=175 SRC="FIGDIR/small/716515v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@16d4da7org.highwire.dtl.DTLVardef@10514cdorg.highwire.dtl.DTLVardef@98b9ecorg.highwire.dtl.DTLVardef@d6667f_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDeveloped an SQR-deficient S. pombe ({Delta}hmt2) model that exhibits sulfur metabolism, mitochondrial dysfunction, and shortened chronological lifespan C_LIO_LISulfide and supersulfide donors prolong yeast lifespan in a SQR-dependent manner C_LIO_LIMitochondrial SQR is essential for membrane potential formation and ATP production in yeast and mammals C_LI

Introduction: The accumulation of senescent cells is a recognized hallmark of biological aging and is associated with the onset of multiple chronic medical conditions. Senescent cells exhibit a distinct secretory profile, known as the senescence-associated secretory phenotype (SASP), which can propagate cellular senescence to neighboring and distant tissues. Measuring SASP factors in blood serves as a practical proxy for cellular senescence burden and may help track disease states and intervention outcomes. Methods: We developed and validated a composite SASP Score by integrating large-scale population proteomics data with a semi-supervised deep learning framework. The analytical workflow included: (1) selection of biologically curated SASP proteins; (2) development of a Guided autoencoder with Transformer (GAET) model using data from the UK Biobank Pharma Proteomics Project (UKB-PPP); (3) internal evaluation and association analyses within the UK Biobank; and (4) external validation and longitudinal assessment in an independent randomized clinical trial cohort. Results: The deep learning-based SASP Score was a strong, independent predictor of mortality risk and incident serious, chronic medical conditions (e.g., dementia, COPD, myocardial infarction, stroke). In an independent cohort, multimodal exercise significantly changed the SASP Score trajectory over 18 months. Discussion: Our findings support the potential of a deep learning-derived SASP Score as a biomarker for systemic cellular senescence burden. Our statistical approach can offer enhanced interpretability and cross-platform utility, providing a valuable tool for aging research and the evaluation of geroscience-guided interventions.

Heart rate variability (HRV) is widely used to assess autonomic regulation, but its interpretation in older adults is influenced by age, sex, body composition, and hemodynamic status, particularly in underrepresented populations living in geographically extreme environments. We analyzed 530 community-dwelling older adults from the Magallanes region in southern Chile using an integrated framework that combined HRV indices with demographic, anthropometric, and cardiovascular descriptors. After quality-controlled preprocessing, we characterized the distribution and association structure of autonomic and physiological variables and then performed a large-scale unsupervised clustering benchmark across multiple feature spaces, dimensionality-reduction strategies, and clustering algorithms. Conventional descriptors explained only a limited proportion of HRV variability, whereas integrated multivariate analysis revealed a structured continuum of autonomic heterogeneity. A six-cluster solution provided the best compromise between separation, balance, and physiological interpretability, identifying profiles that differed in HRV magnitude, blood pressure burden, body composition, sex distribution, and age structure. These findings indicate that autonomic regulation in older adults cannot be adequately summarized by isolated descriptors such as age, body mass index, or blood pressure alone. Instead, it is better represented as a multidimensional physiological organization that supports future hypothesis generation for risk stratification and longitudinal monitoring in aging populations.

{Delta}133p53 is a naturally occurring isoform of the human p53 protein that inhibits p53-mediated cellular senescence. We recently reported that transgenic expression of this senescence-inhibitory p53 isoform counteracts aging-associated pathological changes and extends lifespan in progeria model mice (heterozygous LmnaG609G/+). The anti-aging effect of {Delta}133p53 was attributed in part to reduced levels of the proinflammatory cytokine IL-6. To comprehensively profile {Delta}133p53-induced changes in cytokines and chemokines, we in this study performed a Luminex-based multiplex quantitative assay of mouse sera collected from transgenic {Delta}133p53-expressing LmnaG609G/+ mice and non-expressing controls. This assay not only confirmed the {Delta}133p53-mediated repression of IL-6 but also showed that {Delta}133p53 reduced the levels of CXCL1 (also known as KC), IL-1, and CXCL10 (also known as IP-10). Among these factors, we further characterized CXCL10, which has not previously been associated with progeria in mice or humans. Consistent with reduced serum CXCL10 levels, both young (15-week-old) and old (10-month-old) {Delta}133p53-expressing LmnaG609G/+ mice showed reduced Cxcl10 expression, compared with age-matched non-expressing controls, in the liver, spleen, and brain, major organs known to produce CXCL10. In naturally aged wild-type mice (2-year-old), Cxcl10 expression was also significantly repressed by transgenic {Delta}133p53 in the spleen and brain. Analysis of gene expression datasets from human tissues demonstrated an inverse association between CXCL10 and {Delta}133p53 levels, suggesting physiological relevance to human aging. This study defines CXCL10 as a proinflammatory chemokine elevated in both accelerated and natural aging and as a potential target of the anti-inflammatory activity of {Delta}133p53.

Biological brain aging is a major determinant of cognitive decline and neurodegenerative disease, yet scalable and intervention-ready brain aging biomarkers remain limited. Here, we develop an electroencephalography (EEG)-based brain age clock using machine learning trained on high-dimensional neural features across the adult lifespan. Using 643 features captured from a Sens.ai headset and controller device, the model predicts chronological age with high accuracy (Pearson r = 0.92; MAE = 4.43 years) and yields an interpretable set of age-informative neural features capturing functional signatures of brain aging. Unlike MRI-based approaches, this EEG-based clock is non-invasive, transportable, cost- effective and suitable for repeated at-home longitudinal measurement. Furthermore, in a longitudinal neuromodulation program, BrainYears-predicted brain age decreased by a mean of -5.18 years in the intervention group whereas a minimal-exposure comparison group showed no change on average (+0.07 years). Together, this work introduces a functional brain aging biomarker and an intervention-ready platform for quantifying brain age modulation.

BackgroundAgeing is associated with reduced resilience to physiological stressors such as infection and surgery. This reduced resilience is believed to be underpinned by the hallmarks of ageing, the key biological mechanisms driving the aged phenotype. Geroprotectors are drugs that are proposed to slow down the ageing process and promote longevity and healthspan. Despite this, mechanistic studies in healthy older adults are lacking. Methods and AnalysisThis trial will test the hypothesis that geroprotectors targeted towards biological mechanisms associated with poor resilience can reverse these pathways within a three-week period. Three geroprotectors with a good safety profile in older adults and evidence of effect on the hallmarks of ageing will be administered to 60 (30 female; 30 male) adults 70+. Participants will be randomised to one of three arms (Metformin MR 1500mg, Fisetin 100mg or Spermidine 15mg). Participants will be extensively clinically characterised at baseline. Blood, abdominal adipose tissue and stool samples will be taken at baseline and following the three-week intervention. The primary research question will answer whether a three-week course of Metformin, Spermidine, or Fisetin reduce the number of senescent cells as measured by SA-{beta}-GAL in adipose biopsies in healthy older volunteers. Additionally, there will be assessment of the effect of the geroprotectors on other hallmarks of ageing, including autophagy, immunosenescence, chronic inflammation, dysregulated mTOR signalling, epigenetic age, DNA damage, dysregulated metabolism, stem cell exhaustion and microbial composition. Ethics and DisseminationEthical approval is in place (24/LO/0549). The main trial report and any sub-studies will be published in high impact peer-reviewed gerontology journals, presented at academic conferences and through a series of public engagement events. Participants enrolled in the study will be informed of the results by a written summary. Trial RegistrationREPROGRAM was registered with ISRCTN on 10/09/24. ISRCTN47919839. Available at https://www.isrctn.com/search?q=47919839. Trial Registration Data Set O_TBL View this table: org.highwire.dtl.DTLVardef@1db6074org.highwire.dtl.DTLVardef@1997837org.highwire.dtl.DTLVardef@a39a11org.highwire.dtl.DTLVardef@d7e6eforg.highwire.dtl.DTLVardef@7a5b7f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1C_FLOATNO O_TABLECAPTIONTrial Registration Data Set C_TABLECAPTION C_TBL

Cardiovascular diseases remain the leading cause of global mortality, and early risk stratification is critical for improving prognosis. Artificial intelligence-derived electrocardiography (AI-ECG) provides a promising approach to derive cardiac biological age as a non-invasive digital biomarker. This study developed an AI-ECG framework based on the ECGFounder foundation model to quantify cardiac biological aging and predict cardiovascular risk. A total of 67,824 ECGs from 63,512 UK Biobank participants were included. The model was trained on the development cohort (n = 26,871), comprising healthy individuals, and evaluated in an independent clinical evaluation cohort (n = 40,953). The AI-ECG Age Gap was assessed for its association with MACCE and other secondary outcomes using Cox models. The model demonstrated good agreement between predicted and chronological age in the development cohort (r = 0.646; MAE = 4.61 years). In the clinical cohort, after adjusting for clinical comorbidities, each 1-year increase in the age gap was associated with a significant 13 percent higher risk of (HR = 1.13, 95 percent CI: 1.11-1.14) Individuals with an overestimated age gap (> 6 years) exhibited substantially elevated risks of MACCE (HR = 4.51) and other major cardiovascular outcomes, whereas those with an underestimated age gap (< -6 years) showed a significantly lower risk of MACCE (HR = 0.46) alongside protective effects across other outcomes. The AI-ECG age gap effectively quantifies occult accelerated cardiac aging. As a non-invasive digital biomarker, it exhibits immense potential for cardiovascular risk stratification in broad populations.