GeroScience最新文献

Biomarkers of biological aging predict health outcomes more accurately than chronological age. This study examines the relationship between aging biomarkers, immune function, and kidney health using the Future of Families and Child Wellbeing Study Biomarker Dataset. Using Wave 5 (year 9) and Wave 6 (year 15), we examined biomarker data from a total of 4898 individuals. The panel of aging biomarkers, comprised of epigenetic clocks (GrimAge, Horvath), immune function markers (CD8 + T cells, plasmablasts), and metabolic indicators (GDF-15, leptin), was evaluated in depth. We used principal component analysis (PCA) and K-means clustering for subtype identification. A random forest regressor was employed to predict kidney function using Cystatin C levels, and the importance of features was assessed. Three clusters with unique biological age and immune function profiles were identified. Cluster 1 had younger biological age markers. In Cluster 2, both GrimAge and GDF-15 levels were significantly increased, indicating an elevated risk for age-related diseases. According to predictive modeling, GrimAge, Pack Years, and immune function markers had the strongest influence on Cystatin C levels (R² = 0.856). The incorporation of immune aging markers enhanced the predictive power, emphasizing the importance of immunosenescence in renal health. Aging biomarkers and immune function significantly impact kidney health prediction. The study results call for the utilization of extensive biomarker tests for individualized elderly care and early recognition of kidney deterioration. Clinical practice can be improved by incorporating biological age assessments for the prevention and management of age-related diseases.

Dual-functional stability (DFS) in cognitive and physical abilities is important for successful aging. This study examines the brain topology profiles that underpin high DFS in older adults by testing two hypotheses: (1) older adults with high DFS would exhibit a unique brain organization that preserves their physical and cognitive functions across various tasks, and (2) any individuals with this distinct brain topology would consistently show high DFS. We analyzed two cohorts of cognitively and physically healthy older adults from the UK (Cam-CAN, n = 79) and the US (CF, n = 48) using neuroimaging data and a combination of cognitive and physical tasks. Variability in DFS was characterized using k-mean clustering for intra-individual variability (IIV) in cognitive and physical tasks. Graph theory analyses of diffusion tensor imaging connectomes were used to assess brain network segregation and integration through clustering coefficients (CCs) and shortest path lengths (PLs). Using support vector machine and regression, brain topology features, derived from PLs + CCs, differentiated the high DFS subgroup from low and mix DFS subgroups with accuracies of 65.82% and 84.78% in Cam-CAN and CF samples, respectively, which predicted cross-task DFS score in CF samples at 58.06% and 70.53% for cognitive and physical stability, respectively. Results showed distinctive neural correlates associated with high DFS, notably varying regional brain segregation and integration within critical areas such as the insula, frontal pole, and temporal pole. The identified brain topology profiles suggest a distinctive neural basis for DFS, a trait indicative of successful aging. These insights offer a foundation for future research to explore targeted interventions that could enhance cognitive and physical resilience in older adults, promoting a healthier and more functional lifespan.

Breast cancer is a leading cause of cancer-related mortality among women worldwide, particularly affecting those in their later years. As the incidence of breast cancer increases with age, understanding the biological mechanisms that link aging and cancer becomes crucial. Cellular senescence, a hallmark of aging, plays a dual role in cancer by inhibiting tumorigenesis while also contributing to tumor progression through the senescence-associated secretory phenotype (SASP). This study aims to investigate the prognostic significance of senescence-related genes in breast cancer. We utilized the SenMayo gene list, a comprehensive set of senescence-related genes, to analyze gene expression data from a large cohort of breast cancer samples. The data was sourced from the Kaplan–Meier plotter, an integrated database that compiles gene expression information from multiple independent cohorts. Cox proportional hazards regression and false discovery rate (FDR) corrections were employed to evaluate the correlation between gene expression and survival outcomes, aiming to establish a prognostic signature. Our findings demonstrate that higher expression levels of senescence-related genes are significantly associated with improved survival, while lower expression levels correlate with shorter survival outcomes. These results suggest that senescence-related pathways play a protective role in breast cancer, potentially serving as valuable prognostic indicators. The identification of a prognostic signature based on senescence-related genes underscores the importance of cellular senescence in breast cancer progression and survival. Our study highlights the potential of senescence-related biomarkers in enhancing patient stratification and informing treatment strategies, contributing to the growing body of literature on the intersection of aging and cancer.

Alzheimer's disease (AD) presents a growing societal challenge, driven by an aging population. It is characterized by neurodegeneration linked to β-amyloid (Aβ) and tau protein aggregation. Reactive glial cell-mediated neuroinflammation exacerbates disease progression by facilitating the accumulation of Aβ and impairing its clearance, thus highlighting potential therapeutic targets. Aerial parts of Artemisia iwayomogi (AIH), a kind of mugwort, has been consumed as a medicinal herb in East Asia for relieving inflammation-related diseases. Previously, AIH was found to exert potent inhibitory effects on neuroinflammation. This study aimed to examine whether AIH mitigates AD pathogenesis by regulating neuroinflammation and reducing Aβ deposition. AIH treatment to primary mixed glial cultures attenuated the pro-inflammatory responses evoked by Aβ stimulation. When treated to 5 × familial AD (5xFAD) mice, AIH improved learning and cognitive ability and reduced Aβ burden in the brain. AIH suppressed glial overactivation, as well as inhibited the expressions of pro-inflammatory mediators in the brain. Moreover, AIH regulated AKT signaling and elevated the expression of autophagy-lysosomal mediators in vitro. It was confirmed that lysosome-associated membrane protein 1 (LAMP1) was increased in the Aβ-associated microglia in the mouse hippocampus. Finally, it was observed that tau phosphorylation was alleviated, and synaptic protein expression was increased in AIH-treated 5xFAD mice. Overall, this study demonstrated that AIH ameliorated excessive neuroinflammation and Aβ accumulation by regulating microglial activation and autophagy-lysosomal pathway, thereby suggesting AIH as a promising therapeutic candidate for AD treatment.

Frailty is common among older patients with heart failure (HF). The efficacy of coronary artery bypass grafting (CABG) on the risk of mortality among frail patients with ischemic cardiomyopathy and HF is uncertain, and whether frailty burden modifies the treatment benefits of CABG among these patients is unknown. We performed a post hoc analysis of the STICHES trial, a randomized trial of CABG with medical therapy vs medical therapy alone among participants with ischemic cardiomyopathy with ejection fraction ≤ 35%. Baseline frailty was assessed through a Rockwood Frailty Index (FI), and based on FI cut-offs from prior HF studies, participants with FI ≥ 0.311 were classified as more frail, and those with FI < 0.311 were classified as less frail. A multivariable Cox proportional hazard model with multiplicative interaction terms was constructed to evaluate whether frailty status modified the treatment effect of CABG on mortality in the overall trial cohort and among those < 60 vs ≥ 60 years of age. Of 1187 participants (12.4% female, 2.6% Black, median FI = 0.33 [IQR 0.27–0.39]), 678 were characterized as more frail. Frailty burden did not modify the efficacy of CABG on the risk of all-cause death in the overall cohort (P_int CABG × frailty = 0.2). In age stratified analysis, Baseline frailty status did not modify the treatment effect of CABG on the risk of all-cause mortality among younger (< 60 years, P_int CABG × frailty = 0.2) as well as older participants (≥60 years, P_int CABG × frailty = 0.6). In this post hoc analysis of the STICHES trial, baseline frailty status did not modify the efficacy of CABG in the overall cohort as well as among younger or older participants. Frailty alone should not be used as a criterion to determine the utilization of CABG among patients with ischemic cardiomyopathy.

Two themes are coming to the forefront in this decade: Cognitive impairment of an aging population and the quantum leap in developing artificial intelligence (AI). Both can be described as growing exponentially and presenting serious challenges. Although many questions have been addressed about the dangers of AI, we want to go beyond the fearful aspects of this topic and focus on the possible contribution of AI to solve the problem of chronic disorders of the elderly leading to cognitive impairment, like Alzheimer’s disease, Parkinson’s disease, and Lewy body dementia. Our second goal is to look at the ways in which modern neuroscience can influence the future design of computers and the development of AI. We wish to honor the memory of Dr. John von Neumann, who came up with many breakthrough details of the first electronic computer. Remarkably, Dr. von Neumann dedicated his last book to the comparison of the human brain and the computer as it stood in those years of the mid-1950s. We will point out how his ideas are more relevant than ever in the age of supercomputers, AI and brain implants.

Background: Glycated haemoglobin (HbA1c) is a well-established biomarker for diabetes diagnosis and management and is linked to risk of cardiovascular death. However, among adults without cardiovascular disease (CVD) and diabetes, the value of HbA1c in predicting distinct signatures of myocardial ageing has not been explored. Methods: Subjects, from among older adults without CVD, underwent comprehensive cardiovascular and metabolic assessment. Transthoracic echocardiography measured left ventricular structure and function. Longitudinal left atrial (LA) strain comprising reservoir strain (Ɛs), conduit strain (Ɛe) and booster strain (Ɛa) and their corresponding peak strain rates (SRs, SRe, SRa) were measured using cardiac magnetic resonance (CMR). Blood sampling for biomarkers and cardiovascular examinations were performed. Results: 247 subjects (mean age 71 years, 44.1% female, mean HbA1c 6.0%) were included. HbA1c was significantly associated with E/A ratio (p < 0.0001), conduit strain (Ɛe) (p < 0.0001), conduit strain rate SRe (p < 0.0001), and conduit strain rate to booster strain rate SRe:SRa ratio (p < 0.0001). Multivariate models adjusting for clinical variables such as body mass index, blood pressure, heart rate, diabetes mellitus, smoking, and associated cardiac parameters, demonstrated a persistent independent association. Each unit increase in HbA1c was associated with lower E/A ratio, lower Ɛe, higher SRe and lower SRe:SRa ratio. These associations remained significant after diabetic subjects were excluded. Conclusion: Distinct associations were found between HbA1c and myocardial functions of interest in the ageing heart. HbA1c may be useful biomarker for stratifying risks associated with myocardial ageing, independent of diabetes status.

Trial registration: ClinicalTrials.gov Identifier: NCT02791139.