Biogerontology

DE-SWAN is a commonly used method to study how large ensembles of omics biomarkers change across the life course. It has been used to demonstrate apparent repeated accelerations and decelerations of aging rates across the life course, including 2-3 peaks of aging-related changes. This result contradicts what is expected based on the demography of aging and known biological mechanisms. Here, we use simulations to study the robustness of DE-SWAN to the age distribution of the study sample and to choice of window size. We show that under many realistic scenarios, DE-SWAN is highly sensitive to factors unrelated to the underlying rates of change in aging biology. This calls into question the results of previous analyses that have attributed DE-SWAN peaks to acceleration and deceleration of aging. We conclude that the method is unreliable for studying rates of change across the life course under most circumstances.

Purpose: The neural retina and retinal pigment epithelium/choroid (RPE/Cho) are metabolically coupled. Metabolic dysfunction of the RPE/Cho contributes to photoreceptor death in age-related macular degeneration (AMD). This study aimed to determine how aging, a major risk factor for AMD, alters the proteome and metabolic pathways in the retina and RPE/Cho. Methods: We performed quantitative proteomics on neural retina and RPE/Cho from young (8-week) and old (73-week) C57BL/6J mice. The differentially expressed proteins between old and young, as well as between the retina and RPE/Cho, were visualized using volcano plots and heatmaps, and functional analyses were assessed by Gene Ontology enrichment tools. Results: Aging altered the expression of 85 retinal proteins and 272 RPE/Cho, with 16 shared between tissues. In the aged retina, proteins associated with NADP(H) metabolism, neurodegeneration, and immunity were mostly upregulated, while proteins in lipid metabolism, transcription, and epigenetic regulation decreased. In the aged RPE/Cho, all 21 significantly altered lysosomal enzymes and transport proteins increased, together with complement components, and photoreceptor outer segment proteins. These changes accompanied increases in proteins associated with lipid metabolism and protection against lipid peroxidation, while several glutathione metabolism enzymes decreased. Seven shared proteins involved in lipid and NADP(H) metabolism, changed in opposite directions between retina and RPE/Cho. Comparison of the retinal and RPE/Cho proteomes identified 3073 differentially abundant proteins, of which 2452 maintained tissue-specific differences across both age groups, while approximately 17% showed age-dependent shifts in tissue enrichment. These shifts involved proteins associated with metabolism, extracellular matrix, visual function, lysosomal pathways, and innate immunity. Within the metabolic proteome, several glycolytic and fatty acid oxidation proteins showed greater relative enrichment in RPE/Cho with age, whereas glucose transporters and mitochondrial complexes shifted toward the retina. Conclusions: Overall, these findings show that aging differentially remodels the retina and RPE/Cho proteome, accompanied by altered metabolic specialization between the two tissues.

The effects of older age on the oxidation of energy substrates (carbohydrates, fats) over 24 hr and during activities of daily living (ADL) may have substantial implications for metabolic health. To examine this issue, we evaluated age-related differences in substrate oxidation for 24 hr and periods of sleep, ADLs, and a 30-min treadmill walk (30MTW, 1.3m{middle dot}s^-1) in 17 young (29 {+/-} 5 yr, mean {+/-} SD, 6F) and 16 older (72 {+/-} 5, 8F) healthy active adults. Oxygen consumption (&VdotO2) and carbon dioxide production were measured using a 32,500 L room calorimeter to quantify substrate oxidation, which was normalized to body mass (kJ{middle dot}kg^-1) and total energy expenditure (%). Separately, &VdotO2peak was measured during an incremental treadmill test to exhaustion. &VdotO2peak (ml{middle dot}kg^-1{middle dot}min^-1) was lower in older adults compared with young adults. Older adults oxidized fewer carbohydrates than young over 24 hr (kJ{middle dot}kg^-1, %), sleep (kJ{middle dot}kg^-1), and ADLs (kJ{middle dot}kg^-1, %); and fat oxidation was greater in older than young over 24 hr (kJ{middle dot}kg^-1, %) and ADLs (kJ{middle dot}kg^-1, %). Carbohydrate oxidation did not differ by group during the 30MTW (kJ{middle dot}kg^-1, %), but fat oxidation was greater in older (kJ{middle dot}kg^-1) despite their walking at a greater relative intensity. These results indicate that older adults derived oxidative energy differently than young over 24 hr and during daily tasks. The lower carbohydrate and greater fat contribution to daily energy requirements may be meaningful in the development of metabolic disease in older adults.

Simulated microgravity provides a controlled perturbation for testing how loss of mechanical load affects human tissues. After 24 hours in rotating-wall vessels, neural, cardiac and tonsil organoids developed tissue-specific transcriptional responses that overlapped published spaceflight datasets, accompanied by higher transcriptomic-age estimates in neural and cardiac models, altered cardiac-organoid contraction dynamics and modified tonsil-organoid antiviral gene-expression signatures. These findings establish a multi-organoid framework for studying acute responses to gravitational unloading.

Background: Epidemiological studies have highlighted an inverse association between cancer and Alzheimers disease (AD), but the mechanisms underlying this association are not currently understood. Amyloid precursor protein (APP) and its cleavage may represent one potential mechanism. Its importance has been heavily researched due to it giving rise to the production of amyloid-beta, a pathological hallmark of AD. APP, however, has not been extensively investigated in cancer. Methods: FFPE prostate tumour and adjacent benign tissue immunohistochemically stained for APP, androgen receptor and the insulin-like growth factor-I receptor (IGF1R). Normal prostate PNT2, androgen sensitive LNCaP and androgen insensitive PC3 in vitro were used to assess the effects of androgen, IGF-I and their inhibitors on APP and its cleavage; changes in protein abundance were measured by western blot; interactions between proteins using co-immunoprecipitation and effects on cell proliferation, apoptosis and cell signalling of APP silenced cells using a BrdU proliferation assay, Muse Cell Analyser and by TMT proteomic analysis respectively. Results: Data showed that APP was upregulated in prostate tumour tissue compared to adjacent benign. Furthermore, in cancer cell models, in contrast to normal prostate epithelial cells, it was observed that APP was critical for prostate cancer cell survival by interacting with androgen and IGF-I signalling pathways. Conclusions: Drugs that target APP have already been developed for AD and our data suggests they offer an exciting opportunity for repurposing in the treatment of prostate cancer.

Individuals with Down syndrome (DS) exhibit accelerated biological aging and unique patterns in disease prevalence. However, empirical characterizations of relative risk and age at onset of disease in this population are not common. Here we aimed to quantify the difference in risk and timing of age-related conditions between individuals with DS when compared to typically developing (TD) matched controls. We used semiparametric Cox proportional hazards models and Restricted Mean Event-Free Age (RMEA) to estimate differences in risk and approximate average age at onset of cataracts, cognitive decline, death, menopause, and osteoporosis. Individuals with DS were at higher risk of all age-related conditions or events and experienced these events at younger ages, excluding menopause. We observed a 24.5-fold higher risk of cognitive decline in individuals with DS (p<0.001), and between a 2- and 4-fold higher risk of the other age-related events or conditions (p<0.01). Cognitive decline and death occurred more than 14 years earlier in individuals with DS and were more likely to co-occur (p<0.001) compared to in TD individuals. These findings have important implications for tailored screening and prevention efforts in aging individuals with DS, as this population experiences a distinct cadence of age-related events.

Purpose: Age is the leading factor for age-related macular degeneration (AMD), in which retinal pigmented epithelium (RPE) atrophy is a hallmark. The nuclear factor-erythroid 2-related factor 2 (Nrf2), a major anti-stress transcription factor, decreases in AMD, suggesting bioenergetic stress interacts with age during AMD pathogenesis. We profiled visual function and gene expression of the retina and RPE-choroid with Nrf2 deletion and aging. Methods: We tested 3mo and 14mo Nrf2 null (Nrf2 KO) and Nrf2 WT mice for optokinetic tracking (OKT) and dark-adapted electroretinography (ERG) responses. Eyes were harvested for retina outer nuclear layer (ONL) thickness analysis and retina and RPE-choroid cup RNA isolation for RNAseq profiling. Results: Visual acuity was reduced with aging with lower values in the Nrf2 KO vs Nrf2 WT comparison at 14mo. We observed aged-related reduction of a-, b-, and c-wave ERG amplitudes in both WT and KO mice. Age-related c-wave decline was exacerbated by Nrf2 loss. By RNAseq, two-way ANOVA of RPE-choroid samples revealed differentially expressed genes (DEGs) with age and genotype main effects, as well as DEGs with age and genotype interaction effects. Age DEGs were over-represented in pathways related to inflammation and phagocytosis. Genotype DEGs were associated with alterations in antioxidant and inflammatory processes. Retina RNAseq showed age and genotype DEGs. Conclusions: Ablation of Nrf2 exacerbates age-related declines suggesting that decrease in Nrf2 with aging has functional consequences for inflammation/resiliency. We provide retina and RPE-choroid bulk-RNAseq datasets from the same cohort of mice that can be interrogated to better understand degeneration of retina/RPE-choroid.

Maintenance of neuronal function during aging requires metabolic adaptation, yet how metabolite-sensitive chromatin regulators contribute to this process remains unclear. YEATS-domain proteins, including ENL and AF9, recognize histone acylation marks and are positioned at the interface between cellular metabolism and transcriptional regulation. We previously showed that pan-neuronal suppression of dENL/AF9, the single Drosophila orthologue of mammalian ENL and AF9, extends lifespan, preserves healthspan, and enhances oxidative-stress resistance. Here, we used multi-omics and biochemical analyses to define the molecular state associated with neuronal dENL/AF9 suppression. Transcriptomic profiling revealed a markedly stronger response in aged than young male fly heads, with prominent enrichment of fatty-acid degradation and several intermediary metabolic pathways in the aged dataset. Guided by this age-related transcriptional response, we focused subsequent profiling on aged heads, where independent molecular layers converged on a distinct metabolic and energetic signature. Lipidomics identified reduced abundance of multiple triglyceride-related and fatty acid derivatives, while metabolomics revealed changes in central-carbon/TCA-, nicotinamide-, and purine-associated features. Proteomics implicated mitochondrial and ATP-associated processes, accompanied by increased ATP abundance and a higher NAD/NADH ratio. Matched lipidome-metabolome integration further identified citrate as a cross-omics feature inversely associated with altered triglyceride and ceramide species, linking central-carbon and lipid-associated components of the molecular signature. Together, these findings identify a stronger transcriptional response to neuronal dENL/AF9 suppression in aged flies and a distinct metabolic and energetic molecular signature in aged fly heads, providing candidate molecular correlates of the previously established longevity phenotype and a framework for studies of neuronal aging biology.

Aging is often characterized statically as molecular profiles, but how these profiles may affect the capacity of systems to respond to the external environment remains elusive. We perturbed young and aged mice via transient sleep deprivation and profiled transcriptomes from six organs immediately after stress and following recovery. The same perturbation induced complex temporal dynamics for each gene in an organ- and age- dependent manner. A shape parameter distinguished genes that recovered toward control expression from those that continued to drift away during recovery. Transcriptomic vector fields were inferred from these transitions using neural ordinary differential equations, revealing distinct stability regimes across organ systems. Interestingly, that of testis from the young mice contained a separatrix bounding the region within which perturbed state can return toward control. These findings establish transient perturbation and recovery as a framework for probing age-dependent transcriptomic stability and identifying boundaries that determine whether a perturbed system can return.

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

Ultraviolet-C (UV-C) radiation is a potent environmental stressor that induces DNA damage, accumulation of reactive oxygen species (ROS), and cellular dysfunction. This also initiates coordinated molecular responses to regulate cellular adaptation and recovery. Small extracellular vesicles (sEVs) have emerged as key mediators of intercellular communication through the selective incorporation of microRNAs (miRNAs), proteins, and lipids. However, the temporal changes of sEV-associated cargo during the progression from UV-C-induced damage to recovery remain uncharacterized. We hypothesised that UV-C exposure induces stage-specific changes in sEV cargo (miRNA and proteins) that promote the transition of cells from damage to the response and recovery phases. To examine this, a time-resolved UV-C exposure model was established using Caenorhabditis elegans (C. elegans). In this paper, we studied 2.5 hours of UV-C exposure, including cellular damage, intracellular ROS levels, and DNA integrity, to define the damage and repair state. Based on these temporal variations, samples were collected: i) immediately after exposure, ii) 6 hours post-exposure, and iii) 16 hours post-exposure were designated as damage, response, and recovery conditions, respectively. sEVs isolated from whole-worm preparations were characterised using biophysical and molecular approaches, followed by miRNA sequencing and proteomic analyses. Integrative analysis further identified miRNA-protein associations and associated them with pathways involved in stress adaptation, metabolism, signal transduction, and cellular homeostasis. Collectively, these findings provide a temporal molecular framework of sEV cargo associated with UV-C-induced damage, response, and recovery in C. elegans. Overall, this study identified candidate molecular signatures and miRNA-protein associations that underlie the temporally selective packaging of sEV-associated cargo following UV-C-induced damage, providing a basis for future tissue-specific and mechanistic investigations.

While the influence of microorganisms in the thermal physiology of animals is increasingly recognised, the role of the gut microbiome in enhancing phenotypic plasticity remains underexplored, particularly in ectotherms. Here, we tested the effect of gut microbiomes in modulating the physiological response of lizards to sudden temperature fluctuations. In captivity, we conducted an experiment with wild-caught Podarcis lizards: Mediterranean Podarcis liolepis (n=9) adapted to warm and dry environments, and Atlantic P. muralis (n=18) adapted to cooler and wetter conditions. Animals were assigned to three groups (intervention, control-cold and control-warm) and subjected to microbiota manipulations using antibiotics and faecal microbiota transplants (FMT). In the intervention group, cold-adapted P. muralis received faecal suspension from warm-adapted P. liolepis, while control-cold and control-warm groups received intraspecific transplants. Microbiome variation was analysed through genome-resolved metagenomics of 162 faecal samples, yielding 313 MAGs across 15 phyla, containing almost 1M annotated genes. One week after transplantation, microbiomes of control animals differed from their original state, whereas those of the intervention group (P. muralis), transitioned to a state resembling P. liolepis. After two weeks, both control groups showed trends of reversing their microbiomes to their original states. However, the intervention group displayed a distinct trajectory, resembling the microbial donors'. Although potentially relevant trends were observed, these microbiome alterations did not translate into detectable significant differences in their thermal physiology. Nevertheless, our results provide proof of concept for microbial transplants in lizards, and opportunities to further explore the link between gut microbes and host physiological responses in ectotherms.

Importance: Long-term exposure to higher average air pollutant concentrations is associated with poorer cognitive health, but annual averages can obscure substantial differences in day-to-day exposure. Whether recurrent high pollution days are associated with long-term cognitive aging trajectories among people with similar overall air pollution exposure is unclear. Objective: To determine whether the annual number of days exceeding World Health Organization daily guideline values for nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) is associated with subsequent cognitive decline after accounting for annual mean air pollutant exposure. Design: Prospective cohort study using data from waves 1-10 (2002-03 to 2021-23) of the English Longitudinal Study of Ageing. Setting: Population-based cohort of community-dwelling adults in England. Participants: 12,235 adults aged 50+ years at analytic baseline. Exposures: Number of days exceeding World Health Organization daily guideline values ('exceedance days') for NO2, PM2.5, and PM10, derived from residence-linked environmental estimates during the calendar year preceding the analytic baseline. Main Outcomes and Measures: Baseline cognitive performance and model-estimated 14-year cognitive decline (corresponding to the 75th percentile of follow-up duration) in episodic memory and verbal fluency. Results: Exceedance days were not associated with baseline memory or verbal fluency after adjustment for annual mean air pollutant exposure. More NO2 exceedance days were associated with faster cognitive decline: comparing the 75th percentile with the median of NO2 exceedance days, the difference in 14-year decline was -0.09 SD (95% CI, -0.17 to -0.01; p = 0.02) for memory and -0.10 SD (95% CI, -0.19 to 0.00; p = 0.04) for fluency. PM2.5 and PM10 exceedance days were not associated with cognitive decline. Conclusions and Relevance: In this cohort study of older adults, a higher number of NO2 exceedance days was associated with faster subsequent cognitive decline after adjustment for annual mean air pollutant exposure. This suggests that daily exposure to high NO2 concentrations may be related to accelerated cognitive aging even when offset by lower exposure on other days, potentially providing a new rationale for identifying and prioritizing areas with recurrent high NO2 exposure and the local emission sources contributing to it.

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

Background Emerging evidence has linked frailty to individual chronic diseases, but whether it predicts a broad disease spectrum and accelerates multimorbidity accumulation over time remains unknown. This study aimed to systematically evaluate the associations of physical frailty with the burden of incident disease across a wide range of chronic conditions, and with the long-term rates of multimorbidity accumulation. Methods In this prospective cohort study of 466,864 UK Biobank participants , frailty status was assessed using the Fried frailty phenotype and categorized as robust, pre-frailty, or frailty. Chronic diseases were defined based on International Classification of Diseases (ICD)-10 codes, and disease patterns were identified using network analysis. Cox proportional hazards models were used to examine the associations of frailty status with incident chronic diseases, and linear mixed models were used to assess the annual rate of chronic disease accumulation. Results During a median follow-up of 13.8 years (IQR: 13.1-14.5), 536 incident chronic diseases across multiple systems were recorded. Physical frailty was associated with a significantly increased risk of 458 incident diseases (Bonferroni-corrected P < 0.05/536). In the overall cohort, compared with robust participants, those with pre-frailty ({beta} = 0.266, 95% confidence interval [CI]: 0.264-0.267) and frailty ({beta} = 0.941, 95% CI: 0.936-0.946) exhibited significantly faster rates of multimorbidity accumulation. This accelerated multimorbidity accumulation was consistently observed across strata of baseline disease burden, including participant with 0 ({beta} = 0.644, 95% CI: 0.635-0.653), 1 ({beta} =0.748, 95% CI: 0.727-0.768), [&ge;] 2 ({beta} =0.940, 95% CI: 0.933-0.947) chronic conditions at baseline. Similar associations were also found across distinct disease patterns, including neurodegenerative, metabolic, and psychiatric patterns. Conclusions Physical frailty predicts a broad range of incident diseases and is associated with accelerated multimorbidity accumulation. Incorporating frailty assessment into prevention strategies may help mitigate the growing burden of multimorbidity.

Inhalation of airborne per- and polyfluoroalkyl substances (PFAS) represents an important yet understudied exposure route. While volatile organic compounds (VOCs) have been widely explored as biomarkers of toxicant exposure, their potential for early detection of PFAS-induced pulmonary toxicity remains largely unexplored. This study investigated VOC profiles in human alveolar (A549) and bronchial (BEAS-2B) epithelial cells following exposure to environmentally relevant PFAS concentrations (1, 5, and 10 ppb) for 12, 24, and 48 h. VOCs were analyzed using headspace solid-phase microextraction coupled with gas chromatography-Orbitrap mass spectrometry. We observed significant concentration- and time-dependent alterations in VOC profiles in both cell models. The principal VOCs associated with PFAS exposure include butanal, acetone, 2-butanone, 2-nonanone, (E)-2-nonenal, (E)-2-octenal, (E)-2-heptenal, 2,4-heptadienal, 2,4-nonadienal, 2,4-decadienal, 1-pentanol, and 1-hexanol. Cell type-specific regulations were observed, reflecting differential metabolic responses between transformed and non-transformed lung epithelial cells. Metabolite set enrichment analysis indicated perturbations in ketone body metabolism, consistent with altered cellular energy metabolism. Complementary qPCR analysis revealed altered expressions of CYP1A1, CYP2E1, ALDH1A1, and ALDH2, supporting a mechanistic link between PFAS exposure and oxidative stress, lipid peroxidation, and impaired aldehyde detoxification. These findings demonstrate that VOC profiling, combined with transcriptional analysis, can reveal PFAS-induced metabolic perturbations in pulmonary epithelial cells.

Despite recent evidence of the ability of systemic and organ-specific proteomic aging clocks to predict a large range of age-related diseases, their utility in cancer research remains largely underexplored. In this study, we evaluated the predictive ability of systemic and organ-specific proteomic aging clocks for (i) all-cause mortality, (ii) cancer-related mortality, and (iii) cancer incidence in a sample of Finnish twins (N = 401, mean age at baseline 62.3 years) with Olink proteomic data. Participants were followed for a mean of 10.6 years (SD +- 1.6), with estimates from four systemic and 18 organ-specific proteomic aging clocks calculated at baseline. Cox proportional hazards regression models adjusted for sex and age at baseline identified 15 proteomic aging clocks as significant predictors of all-cause mortality (Ncases = 28) after multiple testing correction (FDR < 0.05), with 11 remaining significant after lifestyle adjustment (Ncases = 27). For several clocks, effect sizes were large, with hazard ratios (HR) approximately doubling per one standard deviation (SD) increase in clock estimates. In predicting cancer-related deaths among participants without a prior cancer diagnosis at baseline (Ncases = 9), only the Immune clock showed a significant positive association after multiple testing correction in basic (HR = 2.94, 95% CI: 1.88-4.59) and lifestyle-adjusted models (HR = 3.31, 95% CI: 1.78-6.17). No associations with cancer incidence (Ncases = 34 basic, Ncases = 31 adjusted) survived multiple testing correction, although several nominal associations were observed. In conclusion, our findings suggest that proteomic aging clocks are strong predictors of all-cause and cancer-specific mortality, independent of lifestyle factors. Proteomic aging clocks may further serve as valuable tools for stratifying cancers by mortality risk.

BackgroundAlcohol use disorder (AUD) is an established contributor to neurocognitive impairment and a major modifiable risk factor for dementia. However, the extent to which lifetime AUD interacts with aging to accelerate subtle cognitive trajectories prior to overt clinical dementia remains unclear. ObjectiveTo investigate whether a lifetime history of DSM-5 AUD and correlated indices of alcohol consumption are associated with accelerated age-related cognitive decline in middle-aged and older adults. MethodsParticipants (N = 1,421) were drawn from the Collaborative Study on the Genetics of Alcoholism (COGA) prospective longitudinal study. Lifetime AUD status (defined as 2 or more DSM-5 criteria endorsed at peak drinking) and drinking patterns were derived from the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA). Cognitive performance across multiple domains was evaluated using the NIH Toolbox Cognition Battery to yield Total, Fluid, and Crystallized Composite Scores. Linear mixed-effects models examined main effects of AUD and age, as well as an AUD-by-age interaction, controlling for testing site. ResultsAt the time of cognitive assessment, the overall sample had a mean age of 52.5 years (SD = 14.5) with a mean longitudinal observation period of 25.0 years (SD = 4.7). The sample was 60% female, 40% male, 7% Hispanic, 23% non-Hispanic Black, 68% non-Hispanic White, 2% other race/ethnicity. 64% met lifetime criteria for AUD (n = 908). While baseline mean cognitive composite scores were similar between those with and without AUD, lifetime AUD was significantly associated with steeper age-related decline for both the Total Composite score (interaction estimate = -0.092, 95% CI [-0.173, -0.010], p = 0.03) and Fluid Composite score (interaction estimate = -0.13, 95% CI [-0.220, -0.040], p = 0.005). No significant AUD-by-age interaction was observed for Crystallized Composite scores (interaction estimate = -0.026, 95% CI [-0.092, 0.041], p = 0.449). Based on model projections, the AUD-associated cognitive deficit on Total Composite scores was equivalent to 7.1 additional years of cognitive aging at age 60 (95% CI [-0.5, 14.7]) and 13.8 additional years at age 75 (95% CI [0.2, 27.3]). Measures of current (past-year) drinking status and current drinks per week showed no significant interaction with age. ConclusionsA lifetime history of AUD acts as a catalyst for cognitive aging, significantly steepening the trajectory of age-related decline in total and fluid cognitive functioning well before the onset of clinical dementia. Cross-sectional measures of current drinking failed to capture these effects, demonstrating that evaluating cumulative lifetime drinking history is important for assessing alcohol-related cognitive decline.

Dehydroascorbic acid (DHA), the oxidized form of vitamin C, exhibits specific toxicity against KRAS-mutant cancer cells; however, the early metabolic reprogramming mechanisms leading to cell death remain incompletely understood. In this study, we reveal the non-linear, dose-dependent response of the intracellular metabolome during the ultra-early phase of 1-hour DHA exposure. Under 1 mM DHA exposure, an early significant accumulation of the primary catabolite erythrulose (p = 0.030) and moderate consumption of glutamate (p = 0.0086) were observed, while core TCA cycle homeostasis and cell viability were preserved. In contrast, under 10 mM DHA exposure, an acute and profound alteration of the metabolic profile was observed. Along with the significant accumulation of glycerate, indicative of a glycolytic blockade, and the terminal peroxidation product oxalate, core TCA cycle intermediates such as -ketoglutarate and malate showed rapid depletion (Log2FC < -2.0, p < 10-7). Furthermore, coupled with this acute energy depletion, a statistically significant accumulation of free methionine (Log2FC = 1.14, p = 0.011), which was below the limit of detection in the control, was identified alongside profound depletions of glutamate (p < 0.001) and cysteine (p = 0.0027). These results strongly suggest that the initial response to high-dose DHA is not merely a linear accumulation of oxidative stress, but rather an "abrupt metabolic switch" characterized by rapid TCA cycle dysfunction followed by the early signature of a methionine trap.

Estimating the postmortem submersion interval (PMSI) remains challenging due to complex biological and environmental interactions during aquatic decomposition. This study proposes a reduced mechanistic ordinary differential equation (ODE) model linking tissue degradation, microbial activity, and dissolved oxygen dynamics. Calibrated against the total aquatic decomposition score (TADS) trajectory for Northern Adriatic Sea cases, the model preserves a strictly monotone TADS--time relationship, ensuring unique numerical inversion from observed TADS to PMSI. Synthetic observation experiments evaluated how data selection influences parameter recovery, practical identifiability, and robustness under measurement uncertainty. Microbial measurements improved parameter recovery for microbial dynamics, whereas dissolved oxygen measurements constrained oxygen-consumption and renewal processes. Combining both types of observation optimized the recovery of coupled parameters. Trajectory reconstruction, profile likelihood analysis, boundary-hit frequencies, and Monte Carlo simulations confirmed these findings. Importantly, while all observation strategies reproduced TADS with comparable accuracy, they differed substantially in recovering underlying biological parameters and latent-state dynamics. Thus, accurately reproducing decomposition scores alone is insufficient for reliable parameter inference. This framework provides a transparent and biologically interpretable foundation for the mechanistic estimation of PMSI. Future applications to case-level and multi-site datasets may enable site-specific recalibration and improved predictive evaluation across diverse aquatic environments.