GeroScience最新文献

A significant challenge in multi-omic geroscience research is the collection of high quality, fit-for-purpose biospecimens from a diverse and well-characterized study population with sufficient sample size to detect age-related changes in physiological biomarkers. The Dog Aging Project designed the precision cohort to study the mechanisms underlying age-related change in the metabolome, microbiome, and epigenome in companion dogs, an emerging model system for translational geroscience research. One thousand dog-owner pairs were recruited into cohort strata based on life stage, sex, size, and geography. We designed and built a novel implementation of the REDCap electronic data capture system to manage study participants, logistics, and biospecimen and survey data collection in a secure online platform. In collaboration with primary care veterinarians, we collected and processed blood, urine, fecal, and hair samples from 976 dogs. The resulting data include complete blood count, chemistry profile, immunophenotyping by flow cytometry, metabolite quantification, fecal microbiome characterization, epigenomic profile, urinalysis, and associated metadata characterizing sample conditions at collection and during lab processing. The project, which has already begun collecting second- and third-year samples from precision cohort dogs, demonstrates that scientifically useful biospecimens can be collected from a geographically dispersed population through collaboration with private veterinary clinics and downstream labs. The data collection infrastructure developed for the precision cohort can be leveraged for future studies. Most important, the Dog Aging Project is an open data project. We encourage researchers around the world to apply for data access and utilize this rich, constantly growing dataset in their own work.

The aim of this study is to investigate the association between retinal age gap and multimorbidity. Retinal age gap was calculated based on a previously developed deep learning model for 45,436 participants. The number of age-related conditions reported at baseline was summed and categorized as zero, one, or at least two conditions at baseline (multimorbidity). Incident multimorbidity was defined as having two or more age-related diseases onset during the follow-up period. Linear regressions were fit to examine the associations of disease numbers at baseline with retinal age gaps. Cox proportional hazard regression models were used to examine associations of retinal age gaps with the incidence of multimorbidity. In the fully adjusted model, those with multimorbidity and one disease both showed significant increases in retinal age gaps at baseline compared to participants with zero disease number (β = 0.254, 95% CI 0.154, 0.354; P < 0.001; β = 0.203, 95% CI 0.116, 0.291; P < 0.001; respectively). After a median follow-up period of 11.38 (IQR, 11.26–11.53; range, 0.02–11.81) years, a total of 3607 (17.29%) participants had incident multimorbidity. Each 5-year increase in retinal age gap at baseline was independently associated with an 8% increase in the risk of multimorbidity (HR = 1.08, 95% CI 1.02, 1.14, P = 0.008). Our study demonstrated that an increase of retinal age gap was independently associated with a greater risk of incident multimorbidity. By recognizing deviations from normal aging, we can identify individuals at higher risk of developing multimorbidity. This early identification facilitates patients’ self-management and personalized interventions before disease onset.

Attentional states reflect the changing behavioral relevance of stimuli in one’s environment, having important consequences for learning and memory. Supporting well-established cortical contributions, attentional states are hypothesized to originate from subcortical neuromodulatory nuclei, such as the basal forebrain (BF) and locus coeruleus (LC), which are among the first to change with aging. Here, we characterized the interplay between BF and LC neuromodulatory nuclei and their relation to two common afferent cortical targets important for attention and memory, the posterior cingulate cortex and hippocampus, across the adult lifespan. Using an auditory target discrimination task during functional MRI, we examined the influence of attentional and behavioral salience on task-dependent functional connectivity in younger (19–45 years) and older adults (66–86 years). In younger adults, BF functional connectivity was largely driven by target processing, while LC connectivity was associated with distractor processing. These patterns are reversed in older adults. This age-dependent connectivity pattern generalized to the nucleus basalis of Meynert and medial septal subnuclei. Preliminary data from middle-aged adults indicates a transitional stage in BF and LC functional connectivity. Overall, these results reveal distinct roles of subcortical neuromodulatory systems in attentional salience related to behavioral relevance and their potential reversed roles with aging, consistent with managing increased salience of behaviorally irrelevant distraction in older adults. Such prominent differences in functional coupling across the lifespan from these subcortical neuromodulatory nuclei suggests they may be drivers of widespread cortical changes in neurocognitive aging, and middle age as an opportune time for intervention.

The aging population, defined as individuals 65 years or older, is rapidly increasing, with age as the most significant and independent risk factor for cardiovascular diseases (CVD). Older women show greater susceptibility to cardiac remodeling and dysfunction compared to men. Despite this, the specific molecular drivers of sex differences in cardiac aging remain poorly understood. In this study, cardiac fibrosis and gene expression profiles were investigated in left atrial appendage samples obtained from 24 consecutive patients undergoing cardiac surgery. Using Masson’s trichrome staining, we found that cardiac fibrosis significantly increased with age in females (p = 0.02) but not in males (p = 0.27). A subsequent medium-throughput gene expression analysis targeting approximately 800 cardiovascular genes revealed no differences in overall cardiac gene expression between sexes based on principal component analyses (PCA). However, pathway-specific analyses identified the thrombosis and hemostasis pathway as prominently dysregulated in females. Specifically, older females showed significant upregulation of PTPN1, PTPN11, and RAPGEF4, genes implicated in cardiac remodeling and metabolic health, compared to younger females, while males exhibited no significant changes across the age range. Correlation analyses confirmed significant positive associations between PTPN1, PTPN11, and RAPGEF4 expression and age in females but not in males. These findings suggest that aging in females is associated with cardiac fibrosis, which is likely driven by the sex-specific upregulation of key genes within the thrombosis and hemostasis pathway.

Background

This study aimed to examine the associations between shift work and biological age acceleration (BAA) and to explore potential moderating factors that may influence the associations.

Methods

A population-based study was conducted using data from 195 419 participants in the UK Biobank (mean age: 52.71 years; 49.1% male), all of whom were either in paid employment or self-employed. Biological age was assessed using 2 distinct algorithms, namely, the Klemera-Doubal method Biological Age (KDM-BA) and Phenotypic Age (PhenoAge). BAA was derived by the residuals with regressing biological age on chronological age.

Results

Among 195 419 participants, 31 495 (16.1%) were shift workers, and 15 925 (8.1%) worked night shifts. Shift workers were more likely to have chronic diseases, unhealthy lifestyles, and poor sleep. Shift and night shift work were significantly associated with increased BAA, with higher risks observed in irregular and permanent night shifts. Subgroup analyses showed greater BAA risks in younger workers, males, and those with high BMI or poor sleep. Significant interactions were found between shift work and sex, socioeconomic status, educational level, ethnicity, cancer, lifestyle, and sleep status. Males had higher risks of KDM-BA Acceleration from irregular and permanent night shifts, while females showed increased PhenoAge Acceleration risks with evening/weekend shifts.

Conclusions

The present study underscored the need for better work-hour scheduling and targeted interventions for high-risk populations, which may help mitigate biological age acceleration associated with shift work.

The hypothalamus has been recognized as a regulator of whole-body aging. Neuropeptide Y (NPY), highly abundant in the central nervous system and produced by the hypothalamus, enhances autophagy in this brain region and mediates autophagy triggered by caloric restriction, suggesting a potential role as a caloric restriction mimetic and an aging regulator. Considering that hypothalamic NPY levels decline during aging, we investigated if reestablishment of NPY levels mitigate aging phenotype, using a mouse model of premature aging – Zmpste24^−/− mouse. The results show that reestablishing hypothalamic NPY levels delayed aging-associated features, including lipodystrophy, alopecia, and memory. Moreover, these results suggest that strategies that promote maintenance of hypothalamic NPY levels might be relevant to counteract aging progression and age-related deteriorations.

Sarcopenia increases the risk of frailty, morbidity, and mortality in older adults. Resistance exercise training improves muscle size and function; however, the response to exercise training is variable in older adults. The objective of our study was to determine both the age-independent and age-dependent changes to the transcriptome following progressive resistance exercise training. Skeletal muscle biopsies were obtained before and after 12 weeks of resistance exercise training in 8 young (24 ± 3.3 years) and 10 older (72 ± 4.9 years) men. RNA was extracted from each biopsy and prepared for analysis via RNA sequencing. We performed differential mRNA expression, gene ontology, and gene set enrichment analyses. We report that when comparing post-training vs pre-training 226 mRNAs and 959 mRNAs were differentially expressed in the skeletal muscle of young and older men, respectively. Additionally, 94 mRNAs increased, and 17 mRNAs decreased in both young and old, indicating limited overlap in response to resistance exercise training. Furthermore, the differential gene expression was larger in older skeletal muscle. Finally, we report three novel findings: 1) resistance exercise training decreased the abundance of ATF4-activated and senescence-associated skeletal muscle mRNAs in older men; 2) resistance exercise-induced increases in lean mass correlate with increased mRNAs encoding mitochondrial proteins; and 3) increases in muscle strength following resistance exercise positively correlate with increased mRNAs involved in translation, rRNA processing, and polyamine metabolism. We conclude that resistance exercise training elicits a differential gene expression response in young and old skeletal muscle, including reduced ATF-4 activated and senescence-associated gene expression.

Most adults experience age-related cognitive decline. However, “Positive-Agers” exhibit superior cognition compared to their age-matched peers. Distinguishing between those with superior cognitive performance and those with cognitive decline over time could better inform treatment therapies in older adults. We developed an algorithm called Optimal Cognitive Scoring (OptiCS) that accurately differentiates “Positive-Agers” from “Cognitive Decliners.” This study draws on a cohort of 5797 participants longitudinally enrolled in the UK Biobank. Using a predictive pipeline, OptiCS could strongly differentiate Positive-Agers versus Cognitive Decliners (area under the curve, or AUC of 83%). The top diffusion MRI attributes highlighted tracts implicated in pathological aging, including the fornix from the hippocampus, the tapetum from the splenium of the corpus callosum, and other key tracts. This study provides three key insights: (I) The proposed algorithm offers a robust cognitive scoring system for subtle cognitive changes, (II) OptiCS can use diffusion MRI to accurately gauge cognitive performance, and (III) OptiCS provides a predictive framework for early detection of cognitive decline.

As the population continues to age, nursing homes will increasingly play a key role in caring for dependent individuals. To enhance the well-being of the elderly, it is crucial to focus on the language skills used during care interactions. However, issues such as the taboo surrounding dependency, scandals involving private nursing home management, the pressure for caregiver efficiency, and the variety of care contexts make monitoring these skills challenging. One way to address this is by collecting in situ data, supervised by language researchers and caregivers specialized in elderly care. This is the approach we have followed: the data collected was then analyzed using machine learning models to provide caregivers with crucial insights for improving care outcomes. Our research highlights the importance of specific factors in language-based interactions, especially in varied care situations. Notably, we emphasize the careful use of humor and the impact of caregiver experience on the success of care sessions. Consequently, we advocate for caregiver training that is grounded in real-life practice, focusing on context adaptation, active listening, and dialogue with residents.

Cellular senescence gene sets have been leveraged to overcome the inadequate sensitivity or specificity of single markers. However, growing evidence of heterogeneity among tissues in senescent cell phenotypes and gene expression profiles has highlighted the need for tissue-specific gene sets. SenSkin™ was curated by an expert review of literature on cellular senescence in the skin and characterized with pathway analysis. To validate SenSkin™, it was evaluated for enrichment with chronological aging in a bulk RNA-sequencing (RNA-seq) dataset and a pseudobulk RNA-seq dataset. Further, changes to SenSkin™ in different skin cell types with photoaging were evaluated in two single-cell RNA-seq datasets. SenSkin™ predominantly included genes related to the senescence-associated secretory phenotype (SASP), which were associated with metabolism and multiple aspects of immune responses. SenSkin™ was more enriched in chronologically aged skin than other commonly used cellular senescence and aging gene sets. In scRNA-seq, SenSkin™ displayed significant upregulation due to photoaging in ten skin cell types. In conclusion, SenSkin™ is a human skin-specific senescence gene set validated in chronological aging and photoaging, which may be more effective at detecting senescent cells in the skin than non-tissue-specific gene sets.