LeBrasseur, Nathan K.

Objective Ceramides have been associated with several ageing-related conditions but have not been studied as a general biomarker of multimorbidity (MM). Therefore, we determined whether ceramide levels are associated with the rapid development of MM. Design Retrospective cohort study. Setting Mayo Clinic Biobank. Participants 1809 persons in the Mayo Clinic Biobank ≥65 years without MM at the time of enrolment, and with ceramide levels assayed from stored plasma. Primary outcome measure Persons were followed for a median of 5.7 years through their medical records to identify new diagnoses of 20 chronic conditions. The number of new conditions was divided by the person-years of follow-up to calculate the rate of accumulation of new chronic conditions. Results Higher levels of C18:0 and C20:0 were associated with a more rapid rate of accumulation of chronic conditions (C18:0 z score RR: 1.30, 95% CI: 1.10 to 1.53; C20:0 z score RR: 1.26, 95% CI: 1.07 to 1.49). Higher C18:0 and C20:0 levels were also associated with an increased risk of hypertension and coronary artery disease. Conclusions C18:0 and C20:0 were associated with an increased risk of cardiometabolic conditions. When combined with biomarkers specific to other diseases of ageing, these ceramides may be a useful component of a biomarker panel for predicting accelerated ageing.

Abstract Resilience, which relates to one's ability to respond to stressors, typically declines with age and the development of comorbid conditions in older organisms. Although progress has been made to improve our understanding of resilience in older adults, disciplines have employed different frameworks and definitions to study various aspects of older adults' response to acute or chronic stressors. “Overview of the Resilience World: State of the Science,” a bench‐to‐bedside conference on October 12–13, 2022, was sponsored by the American Geriatrics Society and National Institute on Aging. This conference, summarized in this report, explored commonalities and differences among the frameworks of resilience most commonly used in aging research in the three domains of resilience: physical, cognitive, and psychosocial. These three main domains are intertwined, and stressors in one domain can lead to effects in other domains. The themes of the conference sessions included underlying contributors to resilience, the dynamic nature of resilience throughout the life span, and the role of resilience in health equity. Although participants did not agree on a single definition of “resilience(s),” they identified common core elements of a definition that can be applied to all domains and noted unique features that are domain specific. The presentations and discussions led to recommendations for new longitudinal studies of the impact of exposures to stressors on resilience in older adults, the use of new and existing cohort study data, natural experiments (including the COVID‐19 pandemic), and preclinical models for resilience research, as well as translational research to bring findings on resilience to patient care.

Abstract Data evaluating change in body composition during treatment of advanced cancer are limited. Here we evaluated computed tomography (CT)–based changes in muscle mass during treatment for advanced ovarian cancer (OC) and association with outcomes. We analyzed the preoperative and posttreatment skeletal muscle index (SMI), skeletal muscle area normalized for height of 109 patients with advanced OC who underwent primary surgery and platinum-based chemotherapy from 2006 to 2016. Based on an SMI less than 39 cm2/m2, 54.1% of patients were never sarcopenic, 24.8% were sarcopenic on both CT scans, and 21.1% were newly sarcopenic upon treatment completion. Patients who lost muscle during treatment had the worst survival of the 3 groups identified: median survival 2.6 years vs 4.6 years if sarcopenic on both CT scans and 4.8 years if never sarcopenic. Loss of muscle portends a poor prognosis among patients with OC. Additional research is needed to better understand and best mitigate these changes.

Background. Mortality risk assessment before kidney transplantation (KT) is imperfect. An emerging risk factor for death in nontransplant populations is physiological age as determined by the application of artificial intelligence to the electrocardiogram (ECG). The aim of this study was to examine the relationship between ECG age and KT waitlist mortality. Methods. We applied a previously developed convolutional neural network to the ECGs of KT candidates evaluated 2014 to 2019 to determine ECG age. We used a Cox proportional hazard model to examine whether ECG age was associated with waitlist mortality. Results. Of the 2183 patients evaluated, 59.1% were male, 81.4% were white, and 11.4% died during follow-up. Mean ECG age was 59.0 ± 12.0 y and mean chronological age at ECG was 53.3 ± 13.6 y. After adjusting for chronological age, comorbidities, and other characteristics associated with mortality, each increase in ECG age of >10 y than the average ECG age for patients of a similar chronological age was associated with an increase in mortality risk (hazard ratio 3.59 per 10-y increase; 95% confidence interval, 2.06-5.72; P < 0.0001). Conclusions. ECG age is a risk factor for KT waitlist mortality. Determining ECG age through artificial intelligence may help guide risk-benefit assessment when evaluating candidates for KT.

Abstract Background Based on studies from animal models, growth differentiation factor-11 (GDF-11) may have rejuvenating effects in humans. GDF-11 has high sequence homology with GDF-8 (also known as myostatin); follistatin and follistatin-like protein-3 (FSTL-3) are inhibitory proteins of both GDF-8 and GDF-11. Methods Using highly specific liquid chromatography with tandem mass spectrometry assays for GDF-11 and GDF-8 and immunoassays for follistatin and FSTL-3, we quantified the association of these factors with muscle size, strength, and physical performance in 2 prospective cohort studies of community-dwelling older adults (Health, Aging, and Body Composition study [Health ABC] and Cardiovascular Health Study [CHS]). Results GDF-8 levels were positively associated with thigh muscle cross-sectional area and density in Health ABC (data not available in CHS). GDF-8 levels were positively associated with lean mass (a surrogate of muscle mass) in Health ABC but not CHS, and grip strength in CHS but not Health ABC. FSTL-3 (and perhaps follistatin) was negatively associated with lean mass and had variable associations with other variables. In contrast, GDF-11 was not significantly associated with strength or performance. Conclusions GDF-8 and its binding proteins, follistatin and FSTL-3, may constitute a counterregulatory system (chalones) to restrain age-related loss of muscle mass and strength.

Abstract Background Studies using heterochronic parabiosis discovered that circulating factors mediate brain aging in animal models. Methods We assessed growth differentiation factors (GDF)-11 and GDF-8 using mass spectrometry and inhibitors follistatin and follistatin-like protein-3 (FSTL-3) with ELISA in the Cardiovascular Health Study (CHS; N = 1 506) and the Health, Aging and Body Composition (Health ABC) Study (N = 1 237). CLL-11 and beta-2 microglobulin (β2M) were measured with ELISA in a subset of 400 individuals in Health ABC. Associations were assessed with cognitive function, brain magnetic resonance imaging (MRI) findings (CHS only), and incident dementia using correlations, linear regression, and Cox proportional hazards models. Results In CHS, levels of GDF-11, GDF-8, and follistatin were not correlated cross-sectionally with the 3MSE or DSST, brain MRI findings of white matter hyperintensity, atrophy, or small infarcts, nor were they associated with incident dementia. FSTL-3 was modestly correlated with poorer cognitive function, greater white matter hyperintensities, and atrophy on MRI, as well as with incident dementia with an adjusted hazard ratio (HR) of 1.72 (95% CI = 1.13, 2.61) per doubling of FSTL-3. FSTL-3 was not associated with cognition or dementia in Health ABC, but GDF-8 was associated with both. The adjusted HR for incident dementia was 1.50 (95% CI = 1.07, 2.10) per doubling of GDF-8. Conclusions Total GDF-11 level was not related to cognition or dementia in older adults. Associations of GDF-8 with cognitive outcomes in Health ABC were not expected, but consistent with animal models. Associations of FSTL-3 with cognition, brain abnormalities, and incident dementia in CHS implicate TGFβ superfamily inhibition in the pathogenesis of dementia.

Abstract There are no circulating markers exclusive to cell senescence for clinical trials in middle-aged/older adults. In this study we evaluated T-cell expression of tumor suppressor protein p16INK4a and plasma senescence associated secretory proteins (SASP)-factors in the context of an 18-week randomized trial of caloric restriction (CR) compared to a weight stable Control. The analysis includes 55 middle-aged/older adults (75%Women; 33%African American; 57.6±5.8 years) with obesity and prediabetes. We measured mRNA expression of select senescence and apoptosis gene transcripts (p16INK4a, p21, BCL2L, BAK1) in peripheral blood CD3+ T-cells (quantitative-RT-PCR) and a panel of 27 plasma SASP proteins (Luminex/multiplex; ELISA). Weight loss in those randomized to CR was -10.8±0.9 kg compared to +0.5±0.9 kg in Control. Using mixed models, T-cell expression of senescence-biomarkers p16INK4a, p21, BCL-2L, and apoptosis-marker BAK1 were not different between CR and control at 18 weeks (time × treatment adjusted for age, race, and sex, all p&gt;0.05). We explored associations between biomarkers with weight loss; moderate spearman correlations (rs=0.28 to 0.64) were observed between weight loss and change in plasma SASP-factors (Activin A, I-CAM, MMP1, PAI-1, TNF-RI, TNF-RII, VEGF, uPAR, p&lt; 0.05 all), but not T-cell biomarker expression. We evaluated associations between biomarkers and found change in T-cell p16INK4a was associated with change in plasma SASP-factors, Fas (rs=0.51), osteopontin (rs=0.34), myeloperoxidase (rs=0.39), and MMP2 (rs=0.40) (CR+Control combined). Among middle-aged/older persons with obesity undergoing 18-weeks CR, changes in T cell p16INK4a expression were correlated with reductions in key SASP factors, and weight loss was associated with lower pro-inflammatory SASP profile.

Abstract Skeletal muscle aging is marked by the loss and atrophy of resident fibers, and the accumulation of functionally diverse cell types including fibroblasts, adipocytes, and immune cells. Senescent cells amass in multiple tissues with advancing age where they contribute to aging, chronic disease, and physical decline. The role of senescence in mediating muscle aging has become a popular and sometimes contentious topic. However, to date, this concept has not been methodically tested. In this study, we characterized the changes in cell abundance and, importantly, cell-specific transcriptional profiles with skeletal muscle aging using scRNAseq. Interestingly, we identified a small population of p16 positive fibro-adipogenic progenitors (FAPs) which, upon further investigation using immunohistochemical methods, were found to express other senescence markers. This subpopulation of FAPs did not exhibit elevation in p21 levels with age. Instead, terminally differentiated myofibers were the source of the p21 increase. Myofibers with high p21 expression exhibit a strong inflammatory phenotype, which includes activated p53 signaling pathways together with strong cytokine-cytokine receptor interactions. We further identified large amounts of cross-talk between different cell types, suggesting that senescent FAPs and myofibers could contribute to skeletal muscle aging in a paracrine manner. Importantly, these observations in mice were confirmed in human samples, suggesting the strong translational power of these findings.

Abstract Skeletal muscle aging is marked by the loss and atrophy of resident fibers, and the accumulation of functionally diverse cell types including fibroblasts, adipocytes, and immune cells. Senescent cells amass in multiple tissues with advancing age where they contribute to aging, chronic disease, and physical decline. The role of senescence in mediating muscle aging has become a popular and sometimes contentious topic. However, to date, this concept has not been methodically tested. In this study, we characterized the changes in cell abundance and, importantly, cell-specific transcriptional profiles with skeletal muscle aging using scRNAseq. Interestingly, we identified a small population of p16 positive fibro-adipogenic progenitors (FAPs) which, upon further investigation using immunohistochemical methods, were found to express other senescence markers. This subpopulation of FAPs did not exhibit elevation in p21 levels with age. Instead, terminally differentiated myofibers were the source of the p21 increase. Myofibers with high p21 expression exhibit a strong inflammatory phenotype, which includes activated p53 signaling pathways together with strong cytokine-cytokine receptor interactions. We further identified large amounts of cross-talk between different cell types, suggesting that senescent FAPs and myofibers could contribute to skeletal muscle aging in a paracrine manner. Importantly, these observations in mice were confirmed in human samples, suggesting the strong translational power of these findings.