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.

Biological aging is heterogeneous across organ systems, yet whether CT-derived abdominal aging provides prognostic value beyond routine clinical data and whether organ decomposition adds beyond a unified estimate remains untested. We developed and evaluated organ-specific and ensemble biological age models from radiomic features across five abdominal organs in 68,675 CT scans from 32,883 subjects, evaluated on alignment with chronological age of healthy subjects (nested cross validation: MAE=3.68 years, R^2=0.90). In sequential analyses restricted to adults aged 20-60 years which is the stratum of strongest BAG-disease association, ensemble biological age gaps provided incremental prognostic value beyond demographic covariates for all-cause disease and mortality (Delta C-index=0.141, 0.051) and beyond routine blood biomarkers (Delta C-index=0.048), confirming CT-derived aging captures structural information beyond laboratory markers. Organ-specific biological age added incremental prognostic value beyond ensemble selectively for focal diseases: cardiovascular (aorta, Delta C-index=0.091) and hepato-pancreatic (pancreas, Delta C-index=0.096). These findings establish a hierarchical organization of CT-derived biological aging, positioning routine CT as a source that adds prognostic value to existing clinical biomarkers.

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.

Age-related cognitive decline (ARCD) is driven by conserved biological mechanisms of aging, yet no gerotherapeutic directly targets these processes in the brain. Glycyl-L-histidyl-L-lysine complexed with copper (GHK-Cu) is an endogenous peptide with regenerative and anti-inflammatory properties that declines with age. Whether its effects on cognitive aging depend on delivery route or exposure duration remains unclear. Aged C57BL/6J mice (20-21 months) received GHK-Cu (15 mg/kg) via short-term intraperitoneal (IP; 5 days) or longer-term intranasal (IN; 8 weeks) administration. Hippocampal-dependent escape learning was assessed using a spatial navigation task. Molecular effects were evaluated using hippocampal immunohistochemistry and bulk RNA sequencing. Differential gene expression was analyzed using DESeq2 with false discovery rate (FDR) correction, and pathway-level changes were assessed via gene set enrichment analysis (GSEA). IN GHK-Cu improved escape latency across Trials 2-4 in both sexes (P < 0.05), whereas IP dosing produced a transient improvement in males during Trial 2 (P < 0.05) without sustained effects or improvement in females. IN treatment increased synaptophysin in females (P < 0.001) and decreased GFAP in both sexes (P < 0.01), while IP treatment reduced TGF-{beta}, GFAP, and MCP-1 in males (P < 0.05) and decreased p21 in females (P < 0.0001). Transcriptomic analysis revealed distinct molecular programs. IN GHK-Cu induced coordinated suppression of oxidative phosphorylation (male NES -5.44, female NES -4.20; FDR < 0.0001) and MYC target pathways (female NES -4.31, FDR < 0.0001), with additional attenuation of PI3K-AKT-mTOR signaling in females (NES -3.15, FDR = 0.062). In contrast, IP treatment activated oxidative phosphorylation (female NES 4.97, FDR < 0.001), DNA repair (NES 5.58, FDR < 0.001), and MYC targets (NES 4.34, FDR = 0.002), indicating engagement of acute stress-response and repair pathways. GHK-Cu improves hippocampal-dependent learning in aged mice through distinct biological modes: IP exposure activates repair and stress-response pathways, whereas IN delivery induces sustained suppression of growth and mitochondrial metabolic signaling associated with aging biology. These findings demonstrate that functional cognitive improvement can arise from divergent molecular states and identify administrative route and exposure duration as key determinants of gerotherapeutic response.

BackgroundThe continuous rise in life expectancy introduces a central challenge of new longevity, ensuring that the additional years gained are accompanied by the preservation of cognitive function and quality. MethodsWe propose a modeling framework for multi-domain brain age derived from a repertoire of digital cognitive metrics. The model, based on Ridge regression with Leave-One-Out cross-validation, was trained in a cohort of 394 healthy controls (HC; 307 women and 87 men; mean age 30.0 {+/-} 12.5 years; range 17-64). ResultsThe model achieved a correlation between chronological age and predicted age of r = 0.942 with a mean absolute error of 3.05 years. When applied to three additional clinical cohorts, multiple sclerosis (N = 70), traumatic brain injury (N = 23), and depression (N = 18), the model detected significant accelerated cognitive aging across all conditions, with processing speed emerging as the dominant contributor to accelerated aging, albeit with varying degrees of concentration across pathologies. ConclusionsDigital cognitive metrics provide an accessible, non-invasive, and scalable biomarker for tracking brain aging, with strong potential for informing personalized neuropsychological interventions and for integration into active aging frameworks within the context of modern longevity.

The relationship between age-related genetic factors and health conditions has become a pivotal focus in aging research, particularly as the World Health Organization (WHO) delineates the leading global causes of mortality. However, the direct impact of age-related genes on the leading cause of death remains poorly understood. To investigate this gene-aging relationship, we analyzed protein-protein interactions using gene set enrichment analysis (GSEA) of a set of 307 age-related genes previously curated. The results indicated significant associations with 113 diverse disease categories, while adhering to a stringent false discovery rate (FDR) threshold of less than 1 x 10-5. Due to the difficulties in aligning the disease categories with WHOs leading causes of death, we reclassified the WHO categories using the more precise nomenclature specified in the 11th Revision of the International Classification of Diseases (ICD-11). The age-related genes account for the leading causes of death, with the exceptions being two infectious communicable diseases, tuberculosis and COVID-19. They impact the cardiovascular system, brain, lungs, and the whole body, while this study could not identify death by aging, which is not a well-defined medical cause of death. Furthermore, we identified a set of 15 recurring genes shared among multiple diseases, including TNF, AKT1, IL6, CDK2A, APOE, and TP53. This gene set was enriched for several disease categories, including cancer, inflammatory diseases, metabolic disorders, and neurodegenerative diseases. Additionally, it shows significant enrichment in various biological categories, with the regulation of nitric oxide activity being the most prominent; other enriched categories include the regulation of microRNA, lipid and carbohydrate metabolism, smooth muscle cell proliferation, insulin signaling, and phosphatidylinositol-3 kinase (PI3K) signaling. The findings suggest that the recurring genes act as pleiotropic hubs, influencing multiple leading causes of death, while other genes are more specific to each disease category.

IntroductionLife expectancy for people with type 1 diabetes has increased due to improved treatment of diabetes and its comorbidities, allowing many to reach old age. Still, we lack knowledge of how individuals with type 1 diabetes age. On one hand, those who reach older age can be considered survivors, but on the other hand their long-standing diabetes might still exhibit negative impacts on their health and functional ability. Healthy ageing is the World Health Organizations priority for this decade. The focus has shifted from chronological age to functional ability, which reflects the ability of individuals to perform meaningful activities. Functional ability is shaped by intrinsic capacity, the environment, and their interaction. Intrinsic capacity encompasses five main domains: cognition, vitality, sensory function, locomotion, and psychological domain. This observational study aims to assess how this vulnerable group of individuals with type 1 diabetes age and to identify factors that contribute to their healthy ageing, intrinsic capacity, and its domains. Methods and analysisThe FinnDiane LifeOne Study is a prospective observational cohort study. We aim to recruit a minimum of 300 individuals with type 1 diabetes from the FinnDiane Study, aged >65, and a minimum of 100 matched controls without insulin-dependent diabetes. The cohort will be comprehensively characterized, including clinical assessment, laboratory tests, questionnaires, and a geriatric assessment of different aspects of functioning ability, with five years intervals. We will compare the individuals with type 1 diabetes to their matched controls. For those with type 1 diabetes, we will further assess which factors from the FinnDiane baseline and trajectories during follow-up predict healthy ageing in above 65-year-olds. Ethics and disseminationThe LifeOne study protocol is approved by the Ethics Committee of HUS Helsinki University Hospital (HUS/4387/2023) and the study adheres to the Declaration of Helsinki. Written informed consent is obtained from each participant. Findings will be published in international peer-reviewed journals with an open access choice. The study is registered at ClinicalTrials.gov with ID NCT07289204. STRENGTHS AND LIMITATIONS OF THE STUDYO_LIThis is a prospective observational cohort study with a matched control group. C_LIO_LIFor the participants with type 1 diabetes, we have unique and comprehensive longitudinal clinical and genetic data available from approximately participants middle age, enabling identification of factors that contribute to their healthy ageing, while accounting for the competing risk of death. C_LIO_LIThe cohort is thoroughly characterised regarding diabetes, cardiometabolic health, lifestyle, psychosocial factors, and includes a geriatric assessment, thereby enabling comparison of impact of ageing between individuals with type 1 diabetes and controls without insulin-dependent diabetes. C_LIO_LIThe cohort is Caucasian with recruitment from Southern Finland, potentially limiting generalisability to other more ethnically diverse populations. C_LI

Atherosclerosis (AS) is a chronic inflammatory disease closely linked to vascular senescence, yet the specific molecular mechanisms connecting aging processes to AS pathogenesis remain incompletely understood. This study integrated transcriptomic data from GEO datasets (GSE100927 and GSE43292) to identify vascular aging-related differentially expressed genes (VARDEGs). Following batch effect correction, 28 VARDEGs were screened and subjected to functional enrichment, protein-protein interaction (PPI) network analysis, and immune infiltration assessment. Seven hub genes (MMP9, APOE, TNF, ICAM1, PPARG, CYBA, and NCF2) were identified and experimentally validated via qRT-PCR, confirming their significant upregulation in AS samples. Receiver operating characteristic (ROC) analysis demonstrated high diagnostic accuracy for six of these genes (AUC > 0.7), with TNF exhibiting superior performance. Immune infiltration analysis revealed profound alterations in 28 immune cell types, particularly monocytes and T cells, which correlated strongly with hub gene expression. Furthermore, single-cell RNA sequencing analysis (GSE184073) localized the expression of core genes predominantly to monocytes and T cells, highlighting TNF overexpression in T cells as a potential critical driver. Finally, molecular docking simulations suggested that curcumin exhibits strong binding affinity to these hub genes, particularly PPARG, providing a mechanistic basis for its therapeutic potential. Collectively, this study elucidates the landscape of vascular aging-related genes in AS, identifies novel diagnostic biomarkers, and proposes potential therapeutic targets involving immune modulation and natural compounds.

Centenarians exhibit marked heterogeneity in biological aging despite their exceptional longevity. To identify biological factors linked to survival at extreme old age, we examined DNA methylation-based measures of aging in 247 cognitively healthy Dutch centenarians using PacBio long-read methylation sequencing. Age acceleration derived from the DNA methylation clock GrimAge emerged as a robust predictor of mortality (HR = 1.60, 95% CI: 1.28-2.00), independent of markers previously associated with mortality in centenarians, such as Mini-Mental State Examination (MMSE) scores (HR = 0.68, 95% CI: 0.56-0.84) and plasma neurofilament light chain (NfL) levels (HR = 1.29, 95% CI: 1.09-1.53). GrimAge acceleration showed limited association with phenotypes related to brain aging, including cognitive performance, neurodegeneration- and Alzheimers disease-related plasma biomarkers, and neuropathological measures. By contrast, it was associated with hematological markers consistent with age-related myeloid shift, although these did not fully account for its association with survival. Together, these findings suggest that GrimAge reflects a mortality-associated dimension of aging that is distinct from brain aging and remains informative even at extreme old age.

While aging manifests differently across organs and individuals, existing approaches to measure it lack the spatial resolution to capture this complexity. Here, we develop an approach that applies multi-modal imaging, segmentation algorithms, and deep-learning to assess organ-specific aging across 39 anatomical regions in a total of 134K individuals in the UK Biobank. Our analysis reveals significant organ aging heterogeneity across and within individuals and a remarkable prevalence of organ-specific extreme aging. We validate that our imaging measures capture pathophysiologically meaningful aging through correlation with organ-specific biomarkers, revealing biologically coherent patterns. We find that accelerated organ aging is robustly predictive of corresponding organ disease. We identify the cerebrum as one of the strongest predictors of organismal aging. We investigate organ aging patterns underlying disease risk and find that each disease is linked to aging of highly distinct subsets of organs. Exploring lifestyle factors and interventions reveals a range of divergent organ-specific effects. Our work establishes a powerful paradigm for noninvasively evaluating human aging at anatomical resolution and population scale.

Aging can alter macrophage functions through changes in intracellular processing, mitochondrial activity, and chronic inflammatory activation; however, whether aging-associated macrophage deregulation contributes to tumor-associated multinucleated syncytial formation remains poorly understood. Here, we investigated the role of aging macrophages in promoting tumor-like multinucleated syncytia and explored the underlying metabolic mechanisms. Immunohistochemical analyses of metastatic tissue sections from patients with prostate, breast, and lung cancers demonstrated enrichment of CD68+/panCK+ multinucleated tumor-like osteoclast syncytia in elderly patients. Using ex vivo co-culture systems, aged bone marrow-derived macrophages exhibited significantly increased propensity to generate multinucleated syncytia containing proliferative Ki67-positive cancer-associated nuclei. These syncytia displayed attenuated mitochondrial oxidative phosphorylation (OXPHOS) programs characterized by reduced oxygen consumption rates and decreased expression of mitochondrial respiratory proteins, such as ATP5a and SDHB. Pharmacologic inhibition of STAT6 further enhanced syncytial formation and suppressed OXPHOS-associated programs, whereas treatment with the EP2 antagonist C52 partially restored mitochondrial gene expression and reduced syncytial formation. Together, these findings identify a previously unrecognized aging-associated mechanism linking macrophage deregulation, attenuated STAT6-associated mitochondrial programs, and tumor-like multinucleated syncytial formation.

The short-lived annual fish Nothobranchius furzeri (Nfu) is a powerful vertebrate model for aging research due to its rapid lifespan and accelerated development of age-associated phenotypes, including gliosis and lipofuscin accumulation. Here, we investigated the effects of dietary 1,3-1,6 {beta}-glucans (BGs), natural polysaccharides derived from Saccharomyces cerevisiae, on aging-related processes across multiple tissues, with particular focus on the brain. Chronic treatment with BG-fortified food reduced several hallmarks of aging in multiple organs. Mechanistically, BG treatment modulated pathways associated with autophagy, lysosomal function, protein oxidation, and inflammation. Both acute and chronic BG administration increased autophagic activity in the aging brain, although lipofuscin accumulation was not affected. To assess whether BGs act directly on neural tissue, we established an ex-vivo Nfu brain culture system that recapitulates the age-dependent decline in autophagy observed in vivo. In this model, acute BG treatment restored impaired autophagy and promoted mitochondrial and lysosomal biogenesis in aged brains. Proteomic analyses revealed increased mitochondrial respiration and modulation of V-ATPase components involved in autophagosome acidification. Depletion of microglia reduced but not eliminated this effect, suggesting direct action of BGs on neurons. To verify the validity of these findings in humans, we performed BG treatment in human iPSC-derived neurons under conditions of impaired autophagy and found an increase in survival. Together, these findings identify {beta}-glucans as modulators of autophagy, mitochondrial function, and inflammation, highlighting their potential to promote healthy aging.

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.

Brain age models - machine-learning predictions of chronological age from brain imaging - are widely interpreted as markers of accelerated brain aging. Here we show that this interpretation cannot be supported. Because these models are trained to predict chronological age, they prioritize features that change similarly across people and actively downweight features that capture differences in individual trajectories, precisely the property an aging-rate biomarker must have. In effect, brain age models are optimized to ignore the very signal they are used to study, thereby risking converting stable between-person differences into apparent accelerated aging. Using theoretical analysis, simulations, and longitudinal MRI, we confirm both predicted failure modes: brain age models indicated "accelerated aging" in participants with low birth weight despite no longitudinal evidence, while a single hippocampal volume measurement was more sensitive than the brain age gap to tau-related neurodegeneration. Across much of the brain age literature, it is therefore not possible to determine whether reported effects reflect brain aging or stable anatomical differences, and the brain age gap should not be interpreted as a marker of brain aging or brain health. We propose alternative strategies that reorient prediction targets from shared age-related patterns to individual differences in change.

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSDeclines in function occur in both "normal" aging (in the absence of disease) and age-related pathological contexts, like Alzheimers disease (AD). Whether "anti-aging" interventions (that extend lifespan) also promote cognitive function in aging and AD remains unexplored. METHODSWe assessed the effect of acarbose (1000 ppm from 4 months of age) on spatial learning and memory using the Morris water maze in young adult (6 mo), mid-aged (12 mo), or aged (24 mo) cohorts of normal aging (Ntg-HET3) and AD-relevant (5xFAD-HET3) genetically heterogeneous mice. RESULTSIn mid-aged and aged Ntg-HET3 mice, acarbose treatment resulted in performance equivalent to young adults. Conversely, acarbose failed to ameliorate age-related deficits in 5xFAD-HET3 mice. DISCUSSIONThis work demonstrates that anti-aging interventions can also promote cognitive longevity in normal aging. Further, it reinforces that AD is not simply accelerated aging and requires therapies beyond anti-aging interventions that target its unique molecular and cellular drivers.

In humans, aging is associated with an increased risk of developing neurodegenerative diseases such as Parkinsons disease and Alzheimers disease. In neurons, the effect of aging on intrinsic molecular processes, and how they tie to age-related neurodegeneration remains unclear. Animal studies have shown that mitochondrial function decline, autophagy impairment and defective elimination of damaged mitochondria by mitophagy are all central features of neuronal aging. However, very few studies have investigated such events in human neurons, due to a lack of models showing aging features, therefore leaving a crucial need for a better understanding of the effect of aging on neuronal health. Here, we use direct neuronal reprogramming, which maintains signatures of cellular aging, to study the effect of aging on mitochondrial health and mitophagy in human neurons. We show age-related mitochondrial impairment, as well as accumulation of mitochondria targeted for degradation in autophagosomes and unacidified autolysosomes following mitophagy induction in neurites of induced neurons (iNs) derived from older donors. These impairments culminate into incomplete elimination of damaged mitochondria. By showing age-dependant mitophagy impairment in human neurons, this study paves the way for more in-depth mechanistic studies that would allow for the identification of therapeutic targets for anti-aging treatment and in the context of age-associated neurodegenerative diseases.

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.

Risky decision-making under uncertainty reflects complex cognitive processes supported by distributed brain networks that are vulnerable to aging. However, it remains unclear whether risk-taking behavior can serve as a behavioral marker of brain aging. In the present study, we combined behavioral tasks, computational modeling, and structural magnetic resonance imaging to investigate the relationship between risky decision-making, chronological age, and brain age. A total of 55 young adults and 112 healthy older adults completed the Iowa Gambling Task (IGT) and the Balloon Analogue Risk Task (BART), along with neuropsychological assessments and neuroimaging scanning. Decision processes were quantified using computational models, including the Value-Plus-Perseveration model and Exponential-Weight Mean-Variance. Brain age was estimated from gray matter volume. The results showed significant age-related alterations in parameters reflecting feedback sensitivity, learning rate, and loss aversion in both tasks. Within older adults, several decision parameters were significantly associated with both chronological age and brain age. Regression analyses further showed that computational parameters significantly predicted chronological age and brain age, whereas traditional cognitive screening measures did not show significant predictive effect. Structural brain analyses indicated that IGT-related parameters were primarily associated with the basal ganglia, while BART-related parameters were linked to a broader network including prefrontal, cingulate, and temporal regions. These findings suggest that computational markers of risk-taking behavior capture subtle age-related changes in cognitive processes and brain deterioration. Therefore, risk-taking parameters may serve as reliable functional markers of brain aging, providing critical insights into the mechanisms underlying successful aging.

Autophagy is widely proposed to decline with age; however, direct evidence for this across cell and tissue types in humans remains limited. Furthermore, it remains unknown whether interventions that improve physiological health during aging can modify autophagic activity in humans. Here, we performed transcriptomic and functional autophagy analyses across subject-matched human cell types from a healthy aging cohort spanning the adult lifespan. RNA-seq of primary dermal fibroblasts and induced neurons (iNs) revealed increased transcription of many autophagy-related genes with age, most markedly in fibroblasts. The impact of age on autophagic activity, measured using autophagy flux assays, was cell type- and sex-dependent, and uncoupled from autophagy-gene transcription. Autophagy flux decreased with age in male fibroblasts, was unchanged in female fibroblasts, and increased in female iNs. In freshly isolated peripheral blood mononuclear cells (PBMCs), autophagy flux became more heterogeneous with age and trended higher in older individuals, independent of sex. Although autophagy flux levels did not match across different cell types, higher autophagy flux in all cell types was associated with reduced physical function in older adults ([&ge;]70 years). Importantly, autophagy flux decreased following 12 weeks of mild exercise in parallel with improved physical function. These findings indicate that autophagy is regulated in a cell type-, sex-and physiological function-dependent manner during human aging, and highlight PBMC autophagy flux as a potentially modifiable, blood-accessible readout of physiological state in older adults.

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