GeroScience最新文献

Age-related declines in neuronal bioenergetic levels may limit vesicular trafficking and autophagic clearance of damaged organelles and proteins. Age-related ATP depletion would impact cognition dependent on ionic homeostasis, but limits on proteostasis powered by GTP are less clear. We used neurons isolated from aged 3xTg-AD Alzheimer's model mice and a novel genetically encoded fluorescent GTP sensor (GEVAL) to evaluate live GTP levels in situ. We report an age-dependent reduction in ratiometric measurements of free/bound GTP levels in living hippocampal neurons. Free GTP colocalized in the mitochondria decreased with age accompanied by the accumulation of free GTP-labeled vesicular structures. The energy dependence of autophagy was demonstrated by depletion of GTP with rapamycin stimulation, while bafilomycin inhibition of autophagy raised GTP levels. Twenty-four-hour supplementation of aged neurons with the NAD precursor nicotinamide and the Nrf2 redox modulator EGCG restored GTP levels to youthful levels and mobilized endocytosis and lysosomal consumption for autophagy via the respective GTPases Rab7 and Arl8b. This vesicular mobilization promoted the clearance of intraneuronal Aβ aggregates, improved viability, and lowered protein oxidative nitration in AD model neurons. Our results reveal age- and AD-related neuronal GTP energy deficits that impair autophagy and endocytosis. GTP deficits were remediated by an external NAD precursor together with a Nrf2 redox modulator which suggests a translational path.

DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. We also failed to predict age using human genotyping arrays, but found that epigenetic clocks were overrepresented near genomic regions whose methylation state is dependent upon sequence variants. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.

Assessing quality of life (QOL) in end-of-life patients is vital for understanding the complex impacts of terminal illnesses on individual well-being. This study aims to compare two widely used QOL assessment tools: the Karnofsky Performance Status Scale (KPSS) and the Short-Form-36 (SF-36) Health Survey among patients with late-stage diseases. KPSS, a clinician-rated scale measuring functional capacity, provides an objective perspective on a patient's clinical status. Conversely, the SF-36 offers a patient-reported overview across eight dimensions, including physical and mental health. The study enrolled 68 patients with an average Karnofsky score of about 37. Results demonstrate a significant interaction between Karnofsky scores and SF-36 dimensions, indicating that patients with higher Karnofsky scores reported better physical, social, and emotional functioning. Strong positive correlations were found between high Karnofsky scores and specific SF-36 components, including Physical Functioning, Role Physical, and Social Functioning, suggesting that these aspects critically influence overall QOL. Notably, no correlation was identified between age and KPSS, highlighting that disease severity rather than age impacts QOL. Findings underscore the complementary roles of KPSS and SF-36 in assessing QOL in terminally ill patients; while some measures in SF-36 aligned closely with KPSS, others offered essential insights into patient experiences. This comprehensive approach emphasizes the need for robust QOL evaluations in palliative care, facilitating more patient-centered care aligned with individuals' values and needs.

The longitudinal directionality between depressive symptoms and biological aging acceleration has yet to be thoroughly investigated. This study included 5442 Chinese adults aged 45-80 years from the 2011 and 2015 survey waves of China Health and Retirement Longitudinal Study. Multiple biomarker-based biological age was estimated using the Klemera and Doubal method, and biologically older was defined as biological age larger than chronological age. Depressive symptoms were identified using a threshold of ≥ 10 on the 10-item Center for Epidemiological Studies Depression Scale. Multivariate logistic regression was employed to explore two unidirectional associations between biological aging and depression. Cross-lagged panel models (CLPM) were also constructed to simultaneously examine the bidirectional relationship and the strength of the association. In the logistic regression model adjusted for potential confounders, biologically older at baseline was associated with a higher risk of subsequent depression (OR = 1.202, 95% CI: 1.020, 1.417) compared with biologically younger; conversely, individuals with baseline depression had a higher risk of being biologically older later (OR = 1.372, 95% CI: 1.148, 1.639) when compared to those without depression. CLPM identified bidirectional relationship over time, with standardized coefficients of 0.03 (P < 0.01) for both longitudinal directional pathways, suggesting an equal contribution of biological aging acceleration and depression to their dynamic interplay. This study reveals a reciprocal interaction between biological aging acceleration and depression in mid-to-late life, suggesting that targeted interventions aimed at decelerating biological aging or alleviating depressive symptoms may confer reciprocal benefits over time.

Purpose: This study aimed to investigate neuromuscular adaptations in individuals with pre/sarcopenia during postural balance perturbations, using surface electromyography (sEMG) signal features as potential functional biomarkers of early motor decline.

Methods: Twenty-eight older adults (14 pre/sarcopenic, 14 controls) were subjected to a series of forward balance perturbations while standing on a force platform. sEMG signals were recorded from four lower limb muscles and analyzed across five defined postural epochs established by the perturbation. Six sEMG features were extracted to capture amplitude, frequency, shape, and complexity characteristics of the signals. Linear mixed-effects models were used to evaluate group differences and trial-by-trial adaptation.

Results: The Post-stab epoch (350-2350 ms post-perturbation) revealed the most pronounced differences between groups. The pre/sarcopenic group exhibited significantly lower amplitude and complexity values. Additionally, shape analysis showed a distribution more closely resembling a Laplacian profile in the pre/sarcopenic group, indicative of increased motor unit synchronization and diminished recruitment variability.

Conclusion: This study identifies specific sEMG-derived features, particularly signal shape and complexity metrics, as potential non-invasive biomarkers for neuromuscular decline in sarcopenia. The Post-stab epoch emerges as a sensitive window for detecting deficits in motor control, supporting the use of perturbation-based tasks and sEMG analysis for early detection, monitoring, and intervention planning in aging populations.

Osteoarthritis (OA) is the most common age-induced degenerative joint disease associated with synovial inflammation, subchondral bone remodeling, and cartilage degradation. One of the significant emerging causes of OA progression is senescent cell accumulation within the joint compartment during lifespan. Currently, there are no therapeutic approaches nor stratification tools that rely on the senescence burden in OA. In this study, we identified the b-series ganglioside 3 (GD3) as new senescent cell surface marker associated with OA. Joint RNA sequencing analysis revealed an increase expression of the GD3 synthase, ST8SIA1 in cartilage, synovial tissue, and subchondral bone marrow from OA patients compared to healthy donors. Moreover, we revealed a strong correlative association between the expression of ST8SIA1 and GD3 production with senescence hallmarks in an in vitro-induced 3D organotypic OA cartilage model but also with cartilage histological grading scores in human and preclinical murine OA joints. Anti-GD3 cell sorting showed that GD3-positive human OA chondrocytes or human OA synoviocytes are enriched in senescence and SASP markers compared to GD3-negative counterparts confirming that GD3 is a cell surface marker linked to the senescence stage. Intra-articular anti-GD3 antibody delivery in experimental OA model reduced local expression of senescence and OA markers in association with a protection against OA-induced subchondral bone remodeling. Our research demonstrates a compelling linkage between ST8SIA1 gene, GD3, and senescence in OA pathology, revealing knowledge and perspectives for a better understanding and anti-senescence treatment of OA pathogenesis.

The ability to suppress irrelevant or distracting inputs that interfere with goal-driven behavior is known to decline with increasing age. Although noninvasive stimulation of the motor cortices has been shown to modulate age-related changes in motor activity, the findings remain preliminary, and it is unknown whether this effect extends beyond the motor cortex. In this study, 125 healthy adults, categorized into young (20-35 years) and older groups (55-72 years) underwent three visits (i.e., anodal, cathodal, and sham). During each visit, they received 20 min of high-definition transcranial direct current stimulation (HD-tDCS) applied to their left primary motor cortex (M1) and completed a flanker task during high-density magnetoencephalography (MEG). Statistically significant oscillatory responses were imaged and analyzed using voxel-wise, whole-brain, and point of stimulation approaches. Our results showed increased gamma flanker interference effects within the contralateral M1 in older relative to younger adults following anodal stimulation, and after anodal compared to cathodal HD-tDCS in older adults. We also found polarity-based differences in beta and gamma M1-prefrontal connectivity as a function of age group. Critically, these data indicate distinct spectrally- and polarity-dependent effects of M1 HD-tDCS on the local and network-level neurophysiological responses serving motor performance in young versus older healthy adults.

The complexity of epigenetic changes that accompany aging has been distilled into a number of molecular timepieces-termed epigenetic clocks-that characterize the pace of biological aging to differing degrees. Here, we develop and validate a DNA methylation-based Physiological health Age (PhysAge) score, comprised of eight DNA methylation surrogates to represent multi-system physiology and developed from commonly measured clinical biomarkers: CRP, peak flow, pulse pressure, HDL-cholesterol, Hba1c, waist-to-height ratio (WHR), cystatin C, and dehydroepianrosterone sulphate (DHEAS). We use data from the population-representative US Health and Retirement Study (HRS), split into a training (n = 1589) and test sample (n = 1588) and corroborate findings in two independent cohorts: The Irish Longitudinal Study of Aging (TILDA; n = 488) and the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA; n = 1830). PhysAge and the predominant second-generation epigenetic clocks, PhenoAge, GrimAge2, and DunedinPACE, were tested for their prediction of mortality and multiple age-related clinical measures (i.e., grip strength, gait speed, cognitive function, disability, frailty). PhysAge was comparable to extant clocks in predicting health measures and was indistinguishable from GrimAge2 in predicting mortality, despite not being trained on mortality. Moreover, the eight individual surrogates comprising PhysAge predicted health outcomes better than the measured values in many instances. The established clinical relevance of the biomarkers from which surrogates were derived opens up new opportunities for cross-study and cross-country comparisons of population health. Findings suggest that the DNA methylation PhysAge can be leveraged as a single biomarker to represent multiple physiological systems and offers utility in the context of clinical monitoring.

Patterns of brain aging are generally conserved among primates; however, there is marked variation in the observed rate among individuals, species, and brain regions. The hippocampus is a region particularly susceptible to the aging process. To better understand how the hippocampus changes over the lifespan, we measured gene expression in 96 banked hippocampus samples from adult male and female rhesus macaques aged 3-35 years old. Importantly, our dataset included representation across adulthood allowing us to characterize age-related patterns in gene expression during midlife, a period often underrepresented in studies of aging. We used autoregressive integrated moving average models to examine age-associated changes in gene expression to identify 2679 differentially expressed genes (FDR < 0.05) that fit four broad patterns of expression: linearly upregulated or downregulated across age, and two clusters with nonlinear patterns. Importantly, the nonlinear clusters highlight transitions in expression trajectories centered around ~ 10 years of age (~ 30 years of age in humans) indicating an important period that may have a critical impact on hippocampal aging. Changes in gene expression variance across age found that genes in individuals > 20 years of age (> 50 years of age in humans) have greater variance in expression than individuals aged 10-20 years (FDR < 0.05). Collectively, our results highlight molecular changes occurring during midlife which may shape brain aging in longer lived primates and may offer insight into increased susceptibility to neurodegenerative disease in humans.

The aim of this study was to establish reference values for the Five-Times-Sit-to-Stand Test (FTSST) in a large, population-representative sample from 14 European countries. Data were collected among 45,470 participants aged 50 + years, as part of the 5th wave of the Survey of Health, Ageing and Retirement in Europe. The reference values for the FTSST were calculated as the 5th, 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th, 90th, and the 95th weighted percentile. The analyses were stratified by age and sex. For females, the best performance on the FTSST was observed among the 50-54-year-olds (5th percentile = 18 s; 50th percentile = 10 s; 95th percentile = 6 s) and the worst among 85-89-year-olds and ≥ 90-year-olds (5th percentile = 28 s; 50th percentile = 15 s; 95th percentile = 9 s). For males, the best performance was observed among the 55-59-year-olds (5th percentile = 18 s; 50th percentile = 9 s; 95th percentile = 5 s). The worst performance for males was observed among ≥ 90-year-olds (5th percentile = 26 s; 50th percentile = 15 s; 95th percentile = 9 s), even though the 10th percentile was higher (poorer performance) among 85-89-year-olds. The reference values indicate poorer performance on the test among females and in older age groups. The provided reference values for FTSST can be used for health screening, surveillance, and intervention planning, as they enable an interpretation of test results according to sex and age.