GeroScience最新文献

The alarmingly high prevalence of obesity in older adults coupled with the negative health effects of chronic inflammation in both obesity and aging highlight the importance of studies investigating the impacts of obesity on age-related inflammation. Since shifts in peripheral T-cell metabolism and function drive systemic inflammation in both obesity and aging, we hypothesize that obesity impacts the Th17-dominated inflammaging profile we identified in lean subjects and thus modifies the anti-inflammatory effects of geroprotective drugs like metformin. New cytokine profiling data showed that CD4⁺ T cells from older people with obesity generate a profile that specifically excludes Th17 cytokines. Metformin failed to change the age-associated T-cell profile in obesity, despite lowering both mitochondrial respiration and reactive oxygen species (ROS) production. Metformin did not improve macroautophagy in T cells from older people with obesity, in sharp contrast to the ability of metformin to promote autophagy in T cells from older lean subjects. These data indicate that body mass index modifies the mechanisms supporting inflammaging in T cells from older subjects, and that metformin-mediated restoration of redox balance is insufficient to stem obesity-associated inflammaging. We conclude that obesity fundamentally changes the mechanisms that promote inflammaging, and thus obesity becomes a critical consideration for clinical trials of geroprotective agents such as metformin.

Metabolic syndrome (MetS) has been linked to accelerated cognitive decline and Alzheimer’s disease and related dementias (ADRDs) via cerebral small vessel disease (CSVD); however, this relation in MetS without overt cardiometabolic disease comorbidities is unknown and may represent a population amenable to preventative strategies. Our study aimed to determine risk profiles for neurocognitive decline and ADRDs in early-stage MetS with evidence of CSVD using the TriNetX electronic health records (EHR) research network. Patients aged 50 to 80 years old meeting MetS criteria were identified utilizing TriNetX data from 76 healthcare organizations. Propensity score matching controlled for demographic and confounding factors. Cohorts included MetS-only, non-MetS, and a MetS subset with evidence of CSVD (MetS-CSVD) created by clustering relevant ICD-codes for diagnoses, imaging, and lab work. Contingency analyses determined odds of developing neurocognitive decline, ADRDs, and CSVD in MetS vs non-MetS and MetS-CSVD vs. MetS-only, using odd ratios with 95% confidence intervals (p-value < 0.05). After propensity score matching, there were 57,347 men and 52,259 women in each of the MetS and non-MetS cohorts and 2,810 men and 2,862 women in each of the MetS-CSVD and MetS-only cohorts. Compared to non-MetS, the MetS cohort exhibited higher odds of developing neurocognitive decline (men: RR = 1.82, p < 0.001; women: RR = 1.34, p = 0.015) and CSVD (men: RR = 2.83, p < 0.001; women: RR = 2.14, p < 0.001), but only women exhibited significantly higher odds of developing ADRDs (men: RR = 1.13, p = 0.38; women: RR = 1.52, p < 0.001). Compared to MetS-only, the MetS-CSVD showed elevated odds in developing neurocognitive decline (men: RR = 1.81, p = 0.040; women: RR = 1.87, p = 0.018) and ADRDs (men: RR = 2.39, p = 0.009; women: RR = 1.65, p = 0.041). A large, predominantly US, sample of subclinical MetS demonstrated heightened odds for developing neurocognitive decline and ADRDs, with even higher odds when evidence of CSVD was also present. TriNetX facilitated a robust exploration of these associations, and our findings warrant further investigation of interventions that target this subclinical at-risk population.

The geroscience hypothesis proposes that underlying biological processes, such as the accumulation of senescent cells, have deleterious effects on multiple tissues and increase the risk of many chronic conditions with aging. Senescent cells produce heterogenous biomarkers, also called senescence-associated secretory phenotype (SASP). Circulating concentrations of senescence biomarkers may reflect an underlying burden of senescent cells in various tissues. Plasma levels of these proteins have been associated with increased mortality and poorer physical function. The associations of them with the incidence of major age-related conditions including heart failure, cardiovascular disease, stroke, and dementia, have not been studied. We measured 35 senescence biomarkers in baseline plasma samples from 1678 participants aged 70–79 years old in the longitudinal Health ABC cohort study. Clinical outcomes were ascertained and validated over an average 11.5 year follow-up. In models adjusted for age, sex, and race, higher levels of most of senescence biomarkers were associated with increased risk of all-cause mortality, mobility limitation, and heart failure. Several were also associated with an increased risk of coronary heart disease, stroke, and dementia. Very few were associated with the risk of cancer. Proteins that were selected by Lasso regression for each outcome that commonly included GDF15 and IL6, significantly improved the prediction of mortality, mobility limitation, and heart failure compared with age, sex, and race alone. These results indicate that levels of senescence biomarkers predict an increased risk of several age-related clinical outcomes and may identify individuals most likely to benefit from senotherapeutics.

Extracellular vesicles (EVs) play crucial roles in aging. In this National Institutes on Aging-funded study, we sought to identify circulating extracellular vesicle (EV) biomarkers indicative of longevity. The plasma EV proteome of 48 older adults (mean age 77.2 ± 1.7 years [range 72–80]; 50% female, 50% Black, 50% < 2-year survival, 50% ≥ 10-year survival) was analyzed by high-resolution mass spectrometry and flow cytometry. The ability of EV peptides to predict longevity was evaluated in discovery (n = 32) and validation (n = 16) datasets with areas under receiver operating characteristic curves (AUCs). Longevity-associated large EV (LEV) plasma subpopulations were mainly related to immune cells (HLA-ABC⁺, CD9⁺, and CD31⁺) and muscle cells (MCAD⁺ and RyR2⁺). Of 7960 identified plasma EV peptides (519 proteins), 46.4% were related to the immune system and 10.1% to muscle. Compared with short-lived older adults, 756 EV peptides (131 proteins) had a higher abundance, and 130 EV peptides (78 proteins) had a lower abundance in long-lived adults. Among longevity-associated peptides, 437 (58 proteins) were immune system related, and 12 (2 proteins) were muscle related. Using just three to five plasma EV peptides (mainly complement components C2-C6), we achieved high predictive accuracy for longevity (AUC range 0.91–1 in a hold-out validation dataset). Our findings suggest that immune cells produce longevity-associated plasma EVs and elucidate fundamental mechanisms regulating aging and longevity. EV longevity predictors suggest there may be merit in targeting complement pathways to extend lifespan, for instance, with any one of the multiple complement inhibitors currently available or in clinical development.

Digital technology interventions (DTIs) are seen as promising interventions to prevent or delay cognitive decline in older adults, yet evidence from reviews is not conclusive. The aim of this study is to explore the effectiveness of DTIs in improving older adults’ cognitive function while taking study design and intervention characteristics as moderators. We searched the PubMed, Embase, CINAHL, PsycINFO, and Scopus databases up to May 26, 2023. Only randomized controlled trials examined the effects of DTIs on cognitive function were included in our study. Standardized mean difference (SMD) and 95% confidence interval for outcomes were applied in meta-analyses and subgroup analyses. A risk of bias assessment was also conducted. Overall, 23 eligible studies with a total sample size of 1454 participants were included. We found that DTIs significantly improved global cognitive function (SMD = 0.479), attention and processing speed (SMD = 0.488), executive function (SMD = 0.287), immediate recall (SMD = 0.266), and working memory (SMD = 0.307). Our subgroup analyses revealed that DTIs were more effective for cognitively impaired subjects, and DTIs with specific intervention characteristics, such as the inclusion of cognitive standard tasks, virtual reality-based interventions, specialized settings, professional guidance, low/medium-density training, > 24 sessions, and sessions lasting > 30 min, were more effective for different cognitive domains. This study supported the effectiveness of DTIs in improving cognitive function in older adults aged 60 years old and over, which may be influenced by study design and intervention characteristics. These findings have important implications for clinical dementia prevention and treatment strategies targeted at specific cognitive domains.

Mosaic loss of Y chromosome (mLOY) is an acquired condition wherein a sizeable proportion of an organ’s cells have lost their Y. Large-scale cohort studies have shown that mLOY is age-dependent and a strong risk factor for all-cause mortality and adverse outcomes of age-related diseases. Emerging multi-omics approaches that combine gene expression, epigenetic and mutational profiling of human LOY cell populations at single-cell levels, and contemporary work in in vitro cell and preclinical mouse models have provided important clues into how mLOY mechanistically contributes to disease onset and progression. Despite these advances, what has been missing is a system-level insight into mLOY. By integrating the most recent advances in wide-ranging aspects of mLOY research, we summarize a unified model to understanding the cause and consequence of mLOY at the molecular, cellular, and organismal levels. This model, referred to as the “Unstable Y Cascade model,” states that (i) the rise and expansion of LOY result from interaction by the inherently unstable Y, germline genetic and epigenetic variants, and numerous cell-intrinsic and external factors; (ii) LOY initiates genomic, epigenomic, and transcriptomic alterations in X and autosomes, thereafter induces a cascade of tissue-specific cellular alterations that contribute locally to the onset and progression of diseases; and (iii) LOY cells exert paracrine effects to non-LOY cells, thereby amplifying LOY-associated pathological signaling cascades to remote non-LOY cells. This new model has implications in the development of therapeutic interventions that could prevent or delay age-related diseases via mitigating mLOY burden.

Ovarian aging is characterized by declines in follicular reserve and the emergence of mitochondrial dysfunction, reactive oxygen species production, inflammation, and fibrosis, which eventually results in menopause. Menopause is associated with increased systemic aging and the development of numerous comorbidities; therefore, the attenuation of ovarian aging could also delay systemic aging processes in women. Recent work has established that the anti-diabetic drug Canagliflozin (Cana), a sodium-glucose transporter 2 inhibitor, elicits benefits on aging-related outcomes, likely through the modulation of nutrient-sensing pathways and metabolic homeostasis. Given that nutrient-sensing pathways play a critical role in controlling primordial follicle activation, we sought to determine if chronic Cana administration would delay ovarian aging and curtail the emergence of pathological hallmarks associated with reproductive senescence. We found that mice receiving Cana maintained their ovarian reserve through 12 months of age, which was associated with declines in primordial follicles FoxO3a phosphorylation, a marker of activation, when compared to the age-matched controls. Furthermore, Cana treatment led to decreased collagen, lipofuscin, and T cell accumulation at 12 months of age. Whole ovary transcriptomic and proteomic analyses revealed subtle improvements, predominantly in mitochondrial function and the regulation of cellular proliferation. Pathway analyses of the transcriptomic data revealed a downregulation in cell proliferation and mitochondrial dysfunction signatures, with an upregulation of oxidative phosphorylation. Pathway analyses of the proteomic data revealed declines in signatures associated with PI3K/AKT activity and lymphocyte accumulation. Collectively, we demonstrate that Cana treatment can delay ovarian aging in mice and could potentially have efficacy for delaying ovarian aging in women.

Many aspects of inflammation increase with aging in mice and humans. Transcriptomic analysis revealed that many murine anti-aging interventions produce lower levels of pro-inflammatory proteins. Here, we explore the hypothesis that different longevity interventions diminish NF-κB levels, potentially mediating some of the anti-inflammatory benefits of lifespan-extending interventions. We found that the NF-κB protein p65 is significantly downregulated in the liver of several kinds of slow-aging mice. These included both sexes of GHRKO and Snell Dwarf mutant mice, and in females only of PAPPA KO mice. P65 is also lower in both sexes of mice treated with rapamycin, canagliflozin, meclizine, or acarbose, and in mice undergoing caloric restriction. Two drugs that extend lifespan of male mice, i.e. 17α-estradiol and astaxanthin, however, did not produce lower levels of p65. We also measured other canonical NF-κB signaling regulators, including the activators IKKα and IKKβ and the inhibitor IκB-α. We found that those regulators do not consistently change in a direction that would lead to of NF-κB inhibition. In contrast, we found that NCoR1, an HDAC3 cofactor and a transcription co-repressor that regulates p65 activity, was also downregulated in many of these mouse models. Finally, we report downregulation of three p65 target proteins that regulate the metabolic and inflammatory states of the liver (HNF4α, IL-1β, and CRP) in multiple slow-aging mouse models. Together, these data suggest that NF-κB signaling, might be inhibited in liver of multiple varieties of slow aging mice. This establishes p65 as a potential target for novel longevity interventions.

Cognitive aging is described as the age-related decline in areas such as memory, executive function, reasoning, and processing speed. Super-Agers, adults over 80 years old, have cognitive function performance comparable to middle-aged adults. To improve cognitive reserve and potentially decrease Alzheimer’s disease (AD) risk, it is essential to contrast changes in regional brain volumes between “Positive-Agers” who have superior cognitive performance compared to their age peers but are not 80 years old yet and aging adults who show cognitive decline (i.e., “Cognitive Decliners”). Using longitudinal cognitive tests over 7–9 years in UK Biobank, principal component analysis (PCA) was first applied to four cognitive domains to create a general cognition (GC) composite score. The GC score was then used to identify latent cognitive groups. Given cognitive groups as the target variable and structural magnetic resonance imaging (sMRI) data and demographics as predictors, we developed a multi-stage feature selection algorithm to identify the most important features. We then trained a Random Forest (RF) classifier on the final set of 54 selected sMRI and covariate predictors to distinguish between Positive-Agers and Cognitive Decliners. The RF model achieved an AUC of 73%. The top 6 features were age, education, brain total surface area, the area of pars orbitalis, mean intensity of the thalamus, and superior frontal gyrus surface area. Prediction of cognitive trajectory types using sMRI may improve our understanding of successful cognitive aging.

Age-associated loss of muscle mass and function and subsequent mobility decline define poor health outcomes, reduced quality of life, and mortality risk. The rate and extent of aging-related muscle loss varies across older adults. It is challenging to understand the molecular pathogenesis of mobility decline, as anthropometric and imaging techniques, primarily used in muscle function assessment, do not offer much molecular information. Small extracellular vesicles (sEV) are lipid membrane-bound, nano-sized (≤ 200 nm) vesicles which carry a wide array of biomolecules as their cargo. sEV contain cell/tissue-specific signatures on their surface and can be isolated from biofluids. These properties pose sEV as a minimally invasive means to monitor the functional and biological health of difficult-to-access tissues, establishing them as a promising liquid biopsy tool. Here, we first isolated skeletal muscle-derived sEV (sEV^SKM) from the serum of vervet monkeys (16 to < 25 years old) using alpha sarcoglycan (SGCA) as a muscle-specific sEV surface marker. sEV^SKM were extensively characterized for size, concentration, purity, and specificity. Further, sEV^SKM isolated from young (11–15 years) and old (25–29 years) monkeys’ serum were characterized for oxidized proteins by mass spectrometry and miRNAs by small-RNAseq. Notably, the analysis of oxidized proteins indicated perturbation of metabolic pathways, actin cytoskeleton, muscle cytoskeleton regulation, and HIF-1 signaling in older monkeys. Furthermore, small-RNAseq analysis identified differential expression of several miRNAs regulating metabolic pathways, inflammation, and stress signaling. Altogether, these results suggest that it is feasible to isolate sEV^SKM and use them to identify molecular biomarkers that reflect the physiological state of muscle tissue.