Citations

Abstract Cellular senescence has emerged as a significant and potentially tractable mechanism of aging and multiple aging‐related conditions. Biomarkers of senescent cell burden, including molecular signals in circulating immune cells and the abundance of circulating senescence‐related proteins, have been associated with chronological age and clinical parameters of biological age in humans. The extent to which senescence biomarkers are affected by interventions that enhance health and function has not yet been examined. Here, we report that a 12‐week structured exercise program drives significant improvements in several performance‐based and self‐reported measures of physical function in older adults. Impressively, the expression of key markers of the senescence program, including p16, p21, cGAS , and TNFα , were significantly lowered in CD3 + T cells in response to the intervention, as were the circulating concentrations of multiple senescence‐related proteins. Moreover, partial least squares discriminant analysis showed levels of senescence‐related proteins at baseline were predictive of changes in physical function in response to the exercise intervention. Our study provides first‐in‐human evidence that biomarkers of senescent cell burden are significantly lowered by a structured exercise program and predictive of the adaptive response to exercise.

Senescent cells exacerbate COVID-19 Cellular senescence is a state elicited in response to stress signals and is associated with a damaging secretory phenotype. The number of senescent cells increases with advanced age and this in turn drives age-related diseases. Camell et al. show that senescent cells have an amplified inflammatory response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (see the Perspective by Cox and Lord). This response is communicated to nonsenescent cells, suppressing viral defense mechanisms and increasing the expression of viral entry proteins. In old mice infected with a SARS-CoV-2–related virus, treatment with senolytics to reduce the senolytic cell burden reduced mortality and increased antiviral antibodies. Science , abe4832, this issue p. eabe4832 ; see also abi4474, p. 281

Abstract Background: Glucocorticoid-induced myopathy is well-recognized in overt Cushing syndrome (CS), but the impact of mild cortisol secretion on muscle is unclear. Recent data suggest that patients with mild autonomous cortisol secretion (MACS) are frailer and report more weakness than patients with non-functioning adrenal adenomas. We hypothesized that MACS is associated with 1) objective measures of impaired muscle strength and performance and 2) increased tissue accumulation of advanced glycation end products (AGEs), a measure of accelerated aging. Aim: To determine the effect of MACS on muscle mass, strength, performance, and tissue accumulation of AGEs. Methods: We conducted a cross-sectional analysis as part of an ongoing cohort study in patients with MACS compared to age and sex-matched referent subjects without cortisol excess. MACS was defined as serum cortisol >1.8 mcg/dL after the 1 mg overnight dexamethasone suppression test (DST), in the absence of overt signs and symptoms of CS. We measured hand grip strength with hand grip dynamometer and evaluated functional performance on the timed up and go test, 6 minute walk test, and gait speed assessment. Tissue accumulation of AGEs was measured with point-of-care AGE reader. Appendicular lean mass was calculated and adjusted for height in participants who underwent body composition scan. Results: A total of 23 patients with MACS and 23 age and sex-matched referent subjects without cortisol excess were enrolled. The median age of diagnosis was 63 years (range, 51–81), and 26 (56%) were women. In the MACS cohort, median cortisol following 1 mg DST was 2.6 µg/dL (range, 1.9–13.0), median DHEA-S 37 µg/dL (range, 5.0- 141.0), and median ACTH 8.5 pg/mL (range, 5.0–38.0). Patients with MACS had lower hand grip strength (median 29.3 vs. 32.5 kg, p=0.052), slower gait speed (median 1.1 vs. 1.4 m/s, p=0.001), covered less distance during the 6 minute walk test (median 453 vs. 510 m, p=0.001), and took longer to complete the timed up and go test (median 10.1 vs. 8.6 s, p=0.04) than referent subjects without cortisol excess. Accumulation of AGEs was higher in patients with MACS (median 2.9 vs. 2.4, p=0.01). No significant difference was observed in appendicular lean mass (n=19 pairs, 7.8 vs. 7.5 kg/m2, p=0.57). Conclusions: MACS is associated with decreased muscle strength and performance without a significant change in muscle mass, suggesting poor muscle quality. We also observed increased tissue accumulation of AGEs in MACS patients, consistent with our hypothesis of MACS-induced accelerated aging. These findings may help explain the increased frailty observed in MACS, and suggest muscle assessment be considered in all patients with autonomous cortisol secretion. Further studies should examine the impact of muscle and functional impairments on morbidity in MACS, and its possible reversal with either a structured exercise intervention or adrenalectomy.

Abstract Background: Frailty is characterized by an increased vulnerability and a decline in physiological reserve. Frailty has been previously linked to cortisol concentrations and blunted diurnal cortisol secretion. Our objective was to determine the association of urine steroid metabolome and its diurnal variation with frailty and prefrailty in older adults. Methods: Cross-sectional study of community-dwelling adults ≥ 50 years. Participants with adrenal disorders, end-stage renal or liver disease, on exogenous steroids or drugs affecting steroid metabolism were excluded. All participants completed day and night separate urine collection. Frailty was assessed using a phenotype model (weight loss, exhaustion, grip strength, low physical activity, and slow walking pace). Participants were characterized as frail if they met at least three criteria, pre-frail if they fulfilled one or two criteria, and robust if no criteria were met. Urine samples were analyzed with the liquid-chromatography, high-resolution, accurate-mass mass spectrometry for 25 urine steroid metabolites. Results: Of 119 participants, 60 (50.4%) were women, without sex differences in age or education status. On frailty assessment, 5 (4.2%) participants were frail and 33 (27.7%) were prefrail, with equal sex distribution. Urine steroid metabolome analysis demonstrated 21/25 steroids were higher in men vs women. In an age adjusted model, presence of prefrailty or frailty was associated with a higher ratio of total cortisol metabolites/total androgen metabolites (TCM/TAM) in men (estimate 0.64, P-value= 0.0004), but not in women. In men, after adjusting for age, among cortisol metabolites, lower day to night ratio of 5α-Tetrahydrocortisol (estimate -0.36, P-value= 0.0419) and β-Cortol (estimate -0.35, P-value= 0.0238) were associated with frail or prefrail phenotype. After adjusting for age, higher ratio of TCM/TAM was associated lower gait speed in men (estimate -1.2, P-value= 0.046) and women (estimate -3.9, P-value= 0.012); and lower hand grip strength in men (estimate -0.04, P-value= 0.046) but not in women. Conclusion: We showed that a higher glucocorticoid to androgen ratio and a flattened circadian steroid variation were associated with presence of frail or prefrail phenotype in men. Further studies should examine the role of steroid metabolism and HPA axis impairment, and the associated sex differences, in the functional decline in aging population.

Abstract Background We have demonstrated that a neural network is able to predict a person’s age from the electrocardiogram (ECG) [artificial intelligence (AI) ECG age]. However, some discrepancies were observed between ECG-derived and chronological ages. We assessed whether the difference between AI ECG and chronological age (Age-Gap) represents biological ageing and predicts long-term outcomes. Methods and results We previously developed a convolutional neural network to predict chronological age from ECGs. In this study, we used the network to analyse standard digital 12-lead ECGs in a cohort of 25 144 subjects ≥30 years who had primary care outpatient visits from 1997 to 2003. Subjects with coronary artery disease, stroke, and atrial fibrillation were excluded. We tested whether Age-Gap was correlated with total and cardiovascular mortality. Of 25 144 subjects tested (54% females, 95% Caucasian) followed for 12.4 ± 5.3 years, the mean chronological age was 53.7 ± 11.6 years and ECG-derived age was 54.6 ± 11 years (R2 = 0.79, P < 0.0001). The mean Age-Gap was small at 0.88 ± 7.4 years. Compared to those whose ECG-derived age was within 1 standard deviation (SD) of their chronological age, patients with Age-Gap ≥1 SD had higher all-cause and cardiovascular disease (CVD) mortality. Conversely, subjects whose Age-Gap was ≤1 SD had lower all-cause and CVD mortality. Results were unchanged after adjusting for CVD risk factors and other survival influencing factors. Conclusion The difference between AI ECG and chronological age is an independent predictor of all-cause and cardiovascular mortality. Discrepancies between these possibly reflect disease independent biological ageing.

Abstract Cellular senescence is characterized by an irreversible cell cycle arrest and a pro‐inflammatory senescence‐associated secretory phenotype (SASP), which is a major contributor to aging and age‐related diseases. Clearance of senescent cells has been shown to improve brain function in mouse models of neurodegenerative diseases. However, it is still unknown whether senescent cell clearance alleviates cognitive dysfunction during the aging process. To investigate this, we first conducted single‐nuclei and single‐cell RNA‐seq in the hippocampus from young and aged mice. We observed an age‐dependent increase in p16 Ink4a senescent cells, which was more pronounced in microglia and oligodendrocyte progenitor cells and characterized by a SASP. We then aged INK ‐ ATTAC mice, in which p16 Ink4a ‐positive senescent cells can be genetically eliminated upon treatment with the drug AP20187 and treated them either with AP20187 or with the senolytic cocktail Dasatinib and Quercetin. We observed that both strategies resulted in a decrease in p16 Ink4a exclusively in the microglial population, resulting in reduced microglial activation and reduced expression of SASP factors. Importantly, both approaches significantly improved cognitive function in aged mice. Our data provide proof‐of‐concept for senolytic interventions' being a potential therapeutic avenue for alleviating age‐associated cognitive impairment.

Abstract Purpose Skeletal muscle is the primary site for insulin-stimulated glucose disposal, and muscle insulin resistance is central to abnormal glucose metabolism in obesity. Whether muscle insulin signaling to the level of Akt/AS160 is intact in insulin-resistant obese humans is controversial. Methods We defined a linear range of insulin-stimulated systemic and leg glucose uptake in 14 obese and 14 nonobese volunteers using a 2-step insulin clamp (Protocol 1) and then examined the obesity-related defects in muscle insulin action in 16 nonobese and 25 obese male and female volunteers matched for fitness using a 1-step, hyperinsulinemic, euglycemic clamp coupled with muscle biopsies (Protocol 2). Results Insulin-stimulated glucose disposal (Si) was reduced by > 60% (P < 0.0001) in the obese group in Protocol 2; however, the phosphorylation of Akt and its downstream effector AS160 were not different between nonobese and obese groups. The increase in phosphorylation of Akt2 in response to insulin was positively correlated with Si for both the nonobese (r = 0.53, P = 0.03) and the obese (r = 0.55, P = 0.01) groups. Total muscle GLUT4 protein was 17% less (P < 0.05) in obese subjects. Conclusions We suggest that reduced muscle glucose uptake in obesity is not due to defects in the insulin signaling pathway at the level of Akt/AS160, which suggests there remain significant gaps in our knowledge of muscle insulin resistance in obesity. Our data imply that models of acute lipotoxicity do not replicate the pathophysiology of obesity.

Abstract In response to various forms of age-associated damage, cells can enter a state of senescence. Senescent cells can compromise the health and function of a tissue, and their accumulation with advancing age is believed to contribute to age-related diseases and geriatric syndromes. In preclinical models (i.e., mice), selective elimination of senescent cells through either genetic approaches or a new class of pharmacological agents, termed “senolytics”, has been show to effectively delay, prevent, or reverse the onset and/or progression of pulmonary disease, osteoporosis, atherosclerosis, diabetes, cognitive decline, and several other conditions. Thus, considerable efforts are underway to optimize pharmacological strategies and test their effectiveness in human populations. This seminar will highlight the state-of-the-science of senolytic drugs, and the opportunities and challenges for early phase clinical trials in humans.

Abstract Dynamic measures of physical resilience—the ability to resist and recover from a challenge—may be informative of biological age far prior to overt manifestations such as age-related diseases and geriatric syndromes (i.e., frailty). If true, physical resilience at younger or middle ages may be predictive of future healthspan and lifespan, and provide a unique paradigm in which interventions targeting the fundamental biology of aging can be tested. This seminar will discuss research on the development of clinically-relevant measures of physical resilience in mice, including anesthesia, surgery, and cytotoxic drugs. It will further highlight how these measures compare between young, middle-aged, and older mice, and how mid-life resilience relates to later-life healthspan. Finally, it will provide insight into whether interventions targeting the biology of aging can modify physical resilience in mice. Part of a symposium sponsored by Epidemiology of Aging Interest Group.

Abstract Background Delirium is underdiagnosed in clinical practice and is not routinely coded for billing. Manual chart review can be used to identify the occurrence of delirium; however, it is labor-intensive and impractical for large-scale studies. Natural language processing (NLP) has the capability to process raw text in electronic health records (EHRs) and determine the meaning of the information. We developed and validated NLP algorithms to automatically identify the occurrence of delirium from EHRs. Methods This study used a randomly selected cohort from the population-based Mayo Clinic Biobank (N = 300, age ≥65). We adopted the standardized evidence-based framework confusion assessment method (CAM) to develop and evaluate NLP algorithms to identify the occurrence of delirium using clinical notes in EHRs. Two NLP algorithms were developed based on CAM criteria: one based on the original CAM (NLP-CAM; delirium vs no delirium) and another based on our modified CAM (NLP-mCAM; definite, possible, and no delirium). The sensitivity, specificity, and accuracy were used for concordance in delirium status between NLP algorithms and manual chart review as the gold standard. The prevalence of delirium cases was examined using International Classification of Diseases, 9th Revision (ICD-9), NLP-CAM, and NLP-mCAM. Results NLP-CAM demonstrated a sensitivity, specificity, and accuracy of 0.919, 1.000, and 0.967, respectively. NLP-mCAM demonstrated sensitivity, specificity, and accuracy of 0.827, 0.913, and 0.827, respectively. The prevalence analysis of delirium showed that the NLP-CAM algorithm identified 12 651 (9.4%) delirium patients, the NLP-mCAM algorithm identified 20 611 (15.3%) definite delirium cases, and 10 762 (8.0%) possible cases. Conclusions NLP algorithms based on the standardized evidence-based CAM framework demonstrated high performance in delineating delirium status in an expeditious and cost-effective manner.