An elevation of resting metabolic rate with declining health in nonagenarians may be associated with decreased muscle mass and function in women and men, respectively

Higher baseline resting metabolic rate is associated with 1-year frailty decline among older adults residing in an urban area

BACKGROUND

Dysregulated energy metabolism is one hypothesized mechanism underlying frailty. Resting energy expenditure, as reflected by resting metabolic rate (RMR), makes up the largest component of total energy expenditure. Prior work relating RMR to frailty has largely been done in cross section with mixed results. We investigated whether and how RMR related to 1-year frailty change while adjusting for body composition.

METHODS

N = 116 urban, predominantly African-American older adults were recruited between 2011 and 2019. One-year frailty phenotype (0-5) was regressed on baseline RMR, frailty phenotype, demographics and body composition (DEXA) in an ordinal logistic regression model. Multimorbidity (Charlson comorbidity scale, polypharmacy) and cognitive function (Montreal Cognitive Assessment) were separately added to the model to assess for change to the RMR-frailty relationship. The model was then stratified by baseline frailty status (non-frail, pre-frail) to explore differential RMR effects across frailty.

RESULTS

Higher baseline RMR was associated with worse 1-year frailty (odds ratio = 1.006 for each kcal/day, p = 0.001) independent of baseline frailty, demographics, and body composition. Lower fat-free mass (odds ratio = 0.88 per kg mass, p = 0.008) was independently associated with worse 1-year frailty scores. Neither multimorbidity nor cognitive function altered these relationships. The associations between worse 1-year frailty and higher baseline RMR (odds ratio = 1.009, p < 0.001) and lower baseline fat-free mass (odds ratio = 0.81, p = 0.006) were strongest among those who were pre-frail at baseline.

DISCUSSION

We are among the first to relate RMR to 1-year change in frailty scores. Those with higher baseline RMR and lower fat-free mass had worse 1-year frailty scores, but these relationships were strongest among adults who were pre-frail at baseline. These relationships were not explained by chronic disease or impaired cognition. These results provide new evidence suggesting higher resting energy expenditure is associated with accelerate frailty decline.

Resting metabolic rate in relation to incident disability and mobility decline among older adults: the modifying role of frailty

BACKGROUND

Alterations in resting metabolic rate (RMR), the largest component of daily total energy expenditure, with aging have been shown in various studies. However, little is known about the associations between RMR and health outcomes in later life.

AIMS

To analyze whether RMR is associated with incident disability and mobility decline in a 10-year longitudinal study, as well as the moderating role of frailty in these associations.

METHODS

Data from 298 older adults aged 70 and over from the Frailty and Dependence in Albacete (FRADEA) study in Spain were used, including a baseline measurement in 2007-2009 and a follow-up measurement 10 years later. RMR was measured by indirect calorimetry. Outcomes were incident disability in basic activities of daily living (BADL, Barthel Index), incident disability in instrumental ADL (IADL, Lawton index), and mobility decline (Functional Ambulation Categories scores). Fried's frailty phenotype was used as an indicator of frailty. Logistic regression analyses were conducted.

RESULTS

Fully adjusted and stratified analyses revealed that only in the pre-frail/frail group, a higher RMR was associated with a lower risk of incident BADL disability (OR = 0.47, 95% CI = 0.23-0.96, p = 0.037), incident IADL disability (OR = 0.39, 95% CI = 0.18-0.84, p = 0.017), and mobility decline (OR = 0.30, 95% CI = 0.14-0.64, p = 0.002).

CONCLUSIONS

To our knowledge, this is the first study looking at the associations between RMR and functional health using a longitudinal research design. The results suggest that RMR could be used as an early identifier of a specific resilient group within the pre-frail and frail older population, with a lower risk of further health decline.

Association between walking energy utilisation and longitudinal cognitive performance in older adults

BACKGROUND

Human motor function is optimised for energetic efficiency, however, age-related neurodegenerative changes affects neuromotor control of walking. Energy utilisation has been associated with motor performance, but its association with cognitive performance is unknown.

METHODS

The study population included 979 Baltimore Longitudinal Study of Aging participants aged $\ge$50 years (52% female, mean age: 70$\pm$10.2 years) with a median follow-up time of 4.7 years. Energy utilisation for walking was operationalised as a ratio of the energy cost of slow walking to peak walking energy expenditure during standardised tasks ('cost-ratio'). Cognitive functioning was measured using the Trail Making Tests, California Verbal Learning Test, Wechsler Adult Intelligence Scale (WAIS), letter and category fluency and card rotation tests. Linear mixed models adjusted for demographics, education and co-morbidities assessed the association between baseline cost-ratio and cognitive functioning, cross-sectionally and longitudinally. To investigate the relationship among those with less efficient energy utilisation, subgroup analyses were performed.

RESULTS

In fully adjusted models, a higher cost-ratio was cross-sectionally associated with poorer performance on all cognitive tests except WAIS (P < 0.05 for all). Among those with compromised energy utilisation, the baseline cost-ratio was also associated with a faster decline in memory (long-delay free recall: β = -0.4, 95% confidence interval [CI] = [-0.8, -0.02]; immediate word recall: β = -1.3, 95% CI = [-2.7, 0.1]).

CONCLUSIONS

These findings suggest cross-sectional and longitudinal links between energy utilisation and cognitive performance, highlighting an intriguing link between brain function and the energy needed for ambulation. Future research should examine this association earlier in the life course to gauge the potential for interventive mechanisms.

Frailty and Biological Age

A reliable model of biological age is instrumental in the field of geriatrics and gerontology. This model should account for the heterogeneity and plasticity of aging and also accurately predict aging-related adverse outcomes. Epigenetic age models are based on DNA methylation levels at selected genomic sites and can be significant predictors of mortality and healthy/unhealthy aging. However, the biological function of DNA methylation at selected sites is yet to be determined. Frailty is a syndrome resulting from decreased physiological reserves and resilience. The frailty index is a probability-based extension of the concept of frailty. Defined as the proportion of health deficits, the frailty index quantifies the progression of unhealthy aging. The frailty index is currently the best predictor of mortality. It is associated with various biological factors and provides insight into the biological processes of aging. Investigation of the multi-omics factors associated with the frailty index will provide further insight.

Feature Selection Algorithms Enhance the Accuracy of Frailty Indexes as Measures of Biological Age

Biological age captures some of the variance in life expectancy for which chronological age is not accountable, and it quantifies the heterogeneity in the presentation of the aging phenotype in various individuals. Among the many quantitative measures of biological age, the mathematically uncomplicated frailty/deficit index is simply the proportion of the total health deficits in various health items surveyed in different individuals. We used 3 different statistical methods that are popular in machine learning to select 17-28 health items that together are highly predictive of survival/mortality, from independent study cohorts. From the selected sets, we calculated frailty indexes and Klemera-Doubal's biological age estimates, and then compared their mortality prediction performance using Cox proportional hazards regression models. Our results indicate that the frailty index outperforms age and Klemera-Doubal's biological age estimates, especially among the oldest old who are most prone to biological aging-caused mortality. We also showed that a DNA methylation index, which was generated by applying the frailty/deficit index calculation method to 38 CpG sites that were selected using the same machine learning algorithms, can predict mortality even better than the best performing frailty index constructed from health, function, and blood chemistry.

Greater Skeletal Muscle Oxidative Capacity Is Associated With Higher Resting Metabolic Rate: Results From the Baltimore Longitudinal Study of Aging

Resting metabolic rate (RMR) tends to decline with aging. The age-trajectory of decline in RMR is similar to changes that occur in muscle mass, muscle strength, and fitness, but while the decline in these phenotypes has been related to changes of mitochondrial function and oxidative capacity, whether lower RMR is associated with poorer mitochondrial oxidative capacity is unknown. In 619 participants of the Baltimore Longitudinal Study of Aging, we analyzed the cross-sectional association between RMR (kcal/day), assessed by indirect calorimetry, and skeletal muscle maximal oxidative phosphorylation capacity, assessed as postexercise phosphocreatine recovery time constant (τ PCr), by phosphorous magnetic resonance spectroscopy. Linear regression models were used to evaluate the relationship between τ PCr and RMR, adjusting for potential confounders. Independent of age, sex, lean body mass, muscle density, and fat mass, higher RMR was significantly associated with shorter τ PCr, indicating greater mitochondrial oxidative capacity. Higher RMR is associated with a higher mitochondrial oxidative capacity in skeletal muscle. This association may reflect a relationship between better muscle quality and greater mitochondrial health.

Energy Expenditure in Older People Hospitalized for an Acute Episode

Weight loss and worsening of nutritional state is a frequent downfall of acute hospitalization in older people. It is usually accepted that acute inflammation is responsible for hypercatabolism. However, several studies suggest, on the contrary, a reduction in resting energy expenditure (REE). This study aimed to obtain a reliable measure of REE and total energy expenditure (TEE) in older patients hospitalized for an acute episode in order to better assess patients’ energy requirements and help understand the mechanisms of weight loss in this situation. Nineteen hospitalized older patients (mean age 83 years) with C-reactive protein (CRP) level >20mg/L were recruited. REE and TEE were measured using gold standard methods of indirect calorimetry and doubly labeled water (DLW), respectively. REE was then compared to data from a previous study on aged volunteers from nursing homes who were free of an acute stressor event. Energy requirements measured by DLW were confirmed at 1.3 × REE. Energy intake covered the needs but did not prevent weight loss in these patients. TEE was not increased in hospitalized patients and was not influenced by inflammation, while the relationship between REE and inflammation was uncertain. Our results suggest that lean mass remains the major determinant of REE in hospitalized older people and that weight loss may not be explained solely by a state of hypercatabolism.

The relationships between sarcopenic skeletal muscle loss during ageing and macronutrient metabolism, obesity and onset of diabetes

Skeletal muscle is integral to the metabolism and utilisation of macronutrients; however, substantial muscle loss and morphological changes occur with ageing. These are associated with loss of muscle function and accelerate rapidly from the age of 60 years, leading to the conditions of sarcopenia and frailty. As the relationship between muscle ageing and macronutrient metabolism and utilisation has seen limited research to date, this review focuses on the interactions between skeletal muscle changes during ageing, metabolism and utilisation of fat, carbohydrates and overall energy expenditure.Skeletal muscle contributes less to resting energy expenditure during ageing, potentially contributing to onset of obesity from middle age. Age-related changes to skeletal muscle lead to glucose dysregulation, with consequent reduction in glycaemic control, increased insulin resistance and ultimately onset of type-2 diabetes. Recent studies indicate that high total fat and SFA intake are detrimental to skeletal muscle, while higher intakes of PUFA are protective. Age-associated changes in skeletal muscle may also reduce total fatty acid utilisation.In conclusion, further research is needed to understand the relationships between macronutrient metabolism and utilisation and age-related changes to skeletal muscle. No dietary recommendations exist specifically for skeletal muscle health during ageing, but we advise individuals to follow healthy eating guidelines, by consuming sufficient protein, fruit and vegetables, and limited SFA and to maintain physically active lifestyles. Clinicians responsible for managing type-2 diabetes need to be aware of growing evidence relating age-related skeletal muscle changes to diabetes onset and progression.

Network analysis of frailty and aging: Empirical data from the Mexican Health and Aging Study

BACKGROUND

Frailty remains a challenge in the aging research area with a number of gaps in knowledge still to be filled. Frailty seems to behave as a network, and in silico evidence is available on this matter. Having in vivo evidence that frailty behaves as a complex network was the main purpose of our study.

METHODS

Data from the Mexican Health and Aging Study (main data 2012, mortality 2015) was used. Frailty was operationalized with a 35-deficit frailty index (FI). Analyzed nodes were the deficits plus death. The edges, linking those nodes were obtained through structural learning, and an undirected graph associated with a discrete probabilistic graphical model (Markov network) was derived. Two algorithms, hill-climbing (hc) and Peter and Clark (PC), were used to derive the graph structure. Analyses were performed for the whole population and tertiles of the total FI score.

RESULTS

From the total sample of 10,983 adults aged 50 or older, 43.8% were women, and the mean age was 64.6 years (SD = 9.3). The number of connections increased according to the tertile level of the FI score. As the FI score raised, groups of interconnected deficits increased and how the nodes are connected changed.

CONCLUSIONS

Frailty phenomenon can be modeled using a Bayesian network. Using the full sample, the most central nodes were self-report of health (most connected node) and difficulty walking a block, and all deficits related to mobility were very interconnected. When frailty levels are considered, the most connected nodes differ, but are related with vitality, mainly at lower frailty levels. We derived that not all deficits are equally related since clusters of very related deficits and non-connected deficits were obtained, which might be considered in the construction of the FI score. Further research should aim to identify the nature of all observed interactions, which might allow the development of specific interventions to mitigate the consequences of frailty in older adults.

Examination of the Dimensions of Biological Age

The concept of biological age has been used more and more frequently in aging research in attempts to measure the progress of the biological aging process as opposed to the simple passage of time. Several approaches to quantify biological age have been utilized, including the use of biomarkers in the form of serum analytes, epigenetic markers, and deficit or frailty indices. Among these methods, the deficit index possesses a theoretical basis grounded in systems biology by incorporating networks, with their emergent properties, to describe the complex aging system. Application of the deficit index in human aging studies points to the increased energetic demands posed by an aging system that is losing integration. Different aspects of mitochondrial function appear to be responsible in males and females. The gut microbiome loses complexity in tandem with the host, as biological age increases, with likely impact on host metabolism and immunity. Specific DNA methylation changes are associated with biological age. They suggest declining connectivity within the aging network, at the cellular level. The deficit/frailty index may account for at least part of the departure at older ages of the observed mortality in the population from the exponential increase modeled by the Gompertz equation.

Changes of Maximum Leg Strength Indices During Adulthood a Cross-Sectional Study With Non-athletic Men Aged 19-91

Age-related loss of muscle mass and function, also called sarcopenia, was recently added to the ICD-10 as an independent condition. However, declines in muscle mass and function are inevitable during the adulthood aging process. Concerning muscle strength as a crucial aspect of muscle function, maximum knee extension strength might be the most important physical parameter for independent living in the community. In this study, we aimed to determine the age-related decline in maximum isokinetic knee extension (MIES) and flexion strength (MIFS) in adult men. The primary study hypothesis was that there is a slight gradual decrease of MIES up to ≈age 60 years with a significant acceleration of decline after this "changepoint." We used a closed kinetic chain system (leg-press), which is seen as providing functionally more relevant results on maximum strength, to determine changes in maximum isokinetic hip/leg extensor (MIES) and flexor strength (MIFS) during adulthood in men. Apart from average annual changes, we aimed to identify whether the decline in maximum lower extremity strength is linear. MIES and MIFS data determined by an isokinetic leg-press of 362 non-athletic, healthy, and community-dwelling men 19-91 years old were included in the analysis. A changepoint analysis was conducted based on a multiple regression analysis adjusted for selected co-variables that might confound the proper relationship between age and maximum strength. In summary, maximum isokinetic leg-strength decline during adulthood averaged around 0.8-1.0% p.a.; however, the reduction was far from linear. MIES demonstrated a non-significant reduction of 5.2 N/p.a. (≈0.15% p.a.) up to the estimated breakpoint of 52.0 years and an accelerated loss of 44.0 N/p.a. (≈1.3% p.a.; p < 0.001). In parallel, the decline in MIFS (10.0 N/p.a.; ≈0.5% p.a.) prior to the breakpoint at age 59.0 years was significantly more pronounced. Nevertheless, we observed a further marked accelerated loss of MIFS (25.0 N/p.a.; ≈1.3% p.a.) in men ≥60 years. Apart from the "normative value" and closed kinetic chain aspect of this study, the practical application of our results suggests that sarcopenia prophylaxis in men should be started in the 5th decade in order to address the accelerated muscle decline of advanced age.

Decreased Basal Metabolic Rate Can Be an Objective Marker for Sarcopenia and Frailty in Older Males

OBJECTIVES

The aim of this study is to demonstrate the ability of the basal metabolic rate (BMR) to detect frailty and sarcopenia in older males.

SETTING AND PARTICIPANTS

A total of 305 male patients undergoing comprehensive geriatric assessment were included in the study.

MEASURES

The frailty status was assessed with the Fried criteria. Sarcopenia was diagnosed according to the European Working Group on Sarcopenia in Older People criteria. BMR is calculated by bioimpedance analysis. Areas under the curves (AUCs) of receiver operating characteristic analyses were used to test the predictive accuracy of BMR in detecting sarcopenia.

RESULTS

The mean age was 74.52 ± 7.51 years. Among the patients in the sample, 95 (31.1%) had sarcopenia and 55 (18%) had frailty. Patients who had a BMR <1612 kcal/d had a higher frequency of frailty than those who had a BMR ≥1612 kcal/d (67.3 vs 32.7, P < .001). Results were similar for sarcopenia (77.9 vs 22.1, P < .001). When BMR was divided by body surface area (BSA), BMR/BSA with a cut-off of 874 kcal/m² had a sensitivity of 80% and a specificity of 68%, and the AUC was 0.82 for BMR/BSA, in diagnosing sarcopenia (P < .01). The participants without sarcopenia had a higher BMR/BSA for the unadjusted (OR = 8.00, 95% CI 4.52-14.19, P < .001) and adjusted analyses (OR = 6.60, 95% CI 3.52-12.38, P < .001).

CONCLUSIONS

Older male patients with sarcopenia and frailty have a higher BMR reduction. Therefore, it should be kept in mind that patients with low BMR should alert us to screen sarcopenia and frailty. BMR/BSA may play a role in objective screening to detect sarcopenia in older males.

Adaptation to metabolic dysfunction during aging: Making the best of a bad situation

Mitochondria play a central role in energy metabolism in the process of oxidative phosphorylation. As importantly, they are key in several anabolic processes, including amino acid biosynthesis, nucleotide biosynthesis, heme biosynthesis, and the formation of iron‑sulfur clusters. Mitochondria are also engaged in waste removal in the urea cycle. Their activity can lead to the formation of reactive oxygen species which have damaging effects in the cell. These organelles are dynamic, undergoing cycles of fission and fusion which can be coupled to their removal by mitophagy. In addition to these widely recognized processes, mitochondria communicate with other subcellular compartments. Various components of mitochondrial complexes are encoded by either the nuclear or the mitochondrial genome necessitating coordination between these two organelles. This article reviews another form of communication between the mitochondria and the nucleus, in which the dysfunction of the former triggers changes in the expression of nuclear genes to compensate for it. The most extensively studied of these signaling pathways is the retrograde response whose effectors and downstream targets have been characterized. This response extends yeast replicative lifespan by adapting the organism to the mitochondrial dysfunction. Similar responses have been found in several other organisms, including mammals. Declining health and function during human aging incurs energetic costs. This compensation plays out differently in males and females, and variation in nuclear genes whose products affect mitochondrial function influences the outcome. Thus, the theme of mitochondria-nucleus communication as an adaptive response during aging appears very widespread.

Differences in the daily activity of patients with diabetic foot ulcers compared to controls in their free-living environments

The aims of our study were to investigate multiple daily activity outcomes in patients with diabetic foot ulcers (DFU) compared to diabetic peripheral neuropathy (DPN) and diabetes (DM) controls in their free-living environments. We examined daily activity outcomes of 30 patients with DFU, 23 DPN and 20 DM. All patients wore a validated multi-sensor device for > 5 days (>22 hours per day) to measure their daily activity outcomes: steps, energy expenditure (kJ), average metabolic equivalent tasks (METs), physical activity (>3·0 METs) duration and energy expenditure, lying duration, sleep duration and sleep quality. We found that DFU patients recorded fewer median (interquartile ranges, IQR) daily steps [2154 (1621-4324)] than DPN [3660 (2742-7705)] and DM [5102 (4011-7408)] controls (P < 0·05). In contrast, DFU patients recorded more mean ± SD daily energy expenditure (kJ) (13 006 ± 3559) than DPN (11 085 ± 1876) and DM (11 491 ± 1559) controls (P < 0·05). We found no other differences in daily activity outcomes (P > 0·1). We conclude that DFU patients typically take fewer steps but expend more energy during their normal daily activity than DPN and DM controls. We hypothesise that the increased energy expenditure for DFU patients may be due to wound healing or an inefficient gait strategy. Further investigations into this energy imbalance in DFU patients may improve healing in future.

Metabolic and Genetic Markers of Biological Age

Biological age is a concept that takes into account the heterogeneity of the aging process in different individuals that results in differences in survival and variations in relative health. Any measure of biological age must be better than chronological age at predicting mortality. Several quantitative measures of biological age have been developed. Among them are frailty indices, one of which called FI₃₄ is discussed here in greater detail. FI₃₄ increases exponentially with age reflecting decline in health and function ability. It readily depicts different patterns and trajectories of aging, and it is moderately heritable. Thus, it has been used to identify a genomic region on chromosome 12 associated with healthy aging. FI₃₄ has also been useful in describing the metabolic characteristics of this phenotype, revealing both sex and genetic differences. These differences give rise to specific, testable models regarding healthy aging, which involve cell and tissue damage and mitochondrial metabolism. FI₃₄ has been directly compared to various metrics based on DNA methylation as a predictor of mortality, demonstrating that it outperforms them uniformly. This and other frailty indices take a top-down, systems based view of aging that is cognizant of the integrated function of the complex aging system.

Thyroid hormones in extreme longevity

The aim of the present review was to summarize knowledge about thyroid hormones (THs) and longevity. Longevity is a complex multifactorial phenomenon on which specific biological pathways, including hormonal networks involved in the regulation of homeostasis and survival, exert a strong impact. THs are the key responsible for growth, metabolism rate and energy expenditure, and help in maintaining cognition, bone and cardiovascular health. THs production and metabolism are fine tuned, and may help the organism to cope with a variety of environmental challenges. Experimental evidence suggests that hypothyroid state may favor longevity by reducing metabolism rate, oxidative stress and cell senescence. Data from human studies involving healthy subjects and centenarians seem to confirm this view, but THs changes observed in older patients affected by chronic diseases cannot be always interpreted as a protective adaptive mechanism aimed at reducing catabolism and prolonging survival. Medications, selected chronic diseases and multi-morbidity can interfere with thyroid function, and their impact is still to be elucidated.

The frailty index outperforms DNA methylation age and its derivatives as an indicator of biological age

The measurement of biological age as opposed to chronological age is important to allow the study of factors that are responsible for the heterogeneity in the decline in health and function ability among individuals during aging. Various measures of biological aging have been proposed. Frailty indices based on health deficits in diverse body systems have been well studied, and we have documented the use of a frailty index (FI₃₄) composed of 34 health items, for measuring biological age. A different approach is based on leukocyte DNA methylation. It has been termed DNA methylation age, and derivatives of this metric called age acceleration difference and age acceleration residual have also been employed. Any useful measure of biological age must predict survival better than chronological age does. Meta-analyses indicate that age acceleration difference and age acceleration residual are significant predictors of mortality, qualifying them as indicators of biological age. In this article, we compared the measures based on DNA methylation with FI₃₄. Using a well-studied cohort, we assessed the efficiency of these measures side by side in predicting mortality. In the presence of chronological age as a covariate, FI₃₄ was a significant predictor of mortality, whereas none of the DNA methylation age-based metrics were. The outperformance of FI₃₄ over DNA methylation age measures was apparent when FI₃₄ and each of the DNA methylation age measures were used together as explanatory variables, along with chronological age: FI₃₄ remained significant but the DNA methylation measures did not. These results indicate that FI₃₄ is a robust predictor of biological age, while these DNA methylation measures are largely a statistical reflection of the passage of chronological time.

Screening for Frailty in Thoracic Surgical Patients

BACKGROUND

The presence of frailty or prefrailty in older adults is a risk factor for postsurgical complications. The frailty phenotype can be improved through long-term resistance and aerobic training. It is unknown whether short-term preoperative interventions targeting frailty will help to mitigate surgical risk. The purpose of this study was to determine the proportion of frail and prefrail patients presenting to a thoracic surgical clinic who could benefit from a frailty reduction intervention.

METHODS

A prospective cohort study was performed at a single-site thoracic surgical clinic. Starting October 1, 2014, surgical candidates 60 years of age or older who consented to be screened were included. Patients were screened using an adapted version of Fried's phenotypic frailty criteria: weakness (grip strength), slow gait (15-foot walk), unintentional weight loss, self-reported exhaustion, and low self-reported physical activity (Physical Activity Scale for the Elderly). Prefrailty was identified when participants demonstrated one to two frailty characteristics; frailty was identified when participants demonstrated three to five frailty characteristics.

RESULTS

Of 180 eligible patients, 126 consented, and 125 completed screening. Thirty-nine participants (31%) were not frail, 71 (57%) were prefrail, and 15 (12%) were frail. Exhaustion was the most common frailty symptom (34%). Frailty prevalence did not significantly differ among men and women (men: 10%, women: 14%; p = 0.75).

CONCLUSIONS

We found a high proportion of prefrail and frail patients among patients deemed candidates for thoracic surgical procedures. This finding indicates that frailty may be underrecognized. Substantial numbers of patients may be considered for a presurgical frailty reduction intervention.

Single nucleotide polymorphisms linked to mitochondrial uncoupling protein genes UCP2 and UCP3 affect mitochondrial metabolism and healthy aging in female nonagenarians

Energy expenditure decreases with age, but in the oldest-old, energy demand for maintenance of body functions increases with declining health. Uncoupling proteins have profound impact on mitochondrial metabolic processes; therefore, we focused attention on mitochondrial uncoupling protein genes. Alongside resting metabolic rate (RMR), two SNPs in the promoter region of UCP2 were associated with healthy aging. These SNPs mark potential binding sites for several transcription factors; thus, they may affect expression of the gene. A third SNP in the 3'-UTR of UCP3 interacted with RMR. This UCP3 SNP is known to impact UCP3 expression in tissue culture cells, and it has been associated with body weight and mitochondrial energy metabolism. The significant main effects of the UCP2 SNPs and the interaction effect of the UCP3 SNP were also observed after controlling for fat-free mass (FFM) and physical-activity related energy consumption. The association of UCP2/3 with healthy aging was not found in males. Thus, our study provides evidence that the genetic risk factors for healthy aging differ in males and females, as expected from the differences in the phenotypes associated with healthy aging between the two sexes. It also has implications for how mitochondrial function changes during aging.

Programmed Cell Death Genes Are Linked to Elevated Creatine Kinase Levels in Unhealthy Male Nonagenarians

Declining health in the oldest-old takes an energy toll for the simple maintenance of body functions. The underlying mechanisms, however, differ in males and females. In females, the declines are explained by loss of muscle mass; but this is not the case in males, in whom they are associated with increased levels of circulating creatine kinase. This relationship raises the possibility that muscle damage rather than muscle loss is the cause of the increased energy demands of unhealthy aging in males. We have now examined factors that contribute to the increase in creatine kinase. Much of it (60%) can be explained by a history of cardiac problems and lower kidney function, while being mitigated by moderate physical activity, reinforcing the notion that tissue damage is a likely source. In a search for genetic risk factors associated with elevated creatine kinase, the Ku70 gene XRCC6 and the ceramide synthase gene LASS1 were investigated because of their roles in telomere length and longevity and healthy aging, respectively. Single nucleotide polymorphisms in these two genes were independently associated with creatine kinase levels. The XRCC6 variant was epistatic to one of the LASS1 variants but not to the other. These gene variants have potential regulatory activity. Ku70 is an inhibitor of the proapoptotic Bax, while the product of Lass1, ceramide, operates in both caspase-dependent and -independent pathways of programmed cell death, providing a potential cellular mechanism for the effects of these genes on tissue damage and circulating creatine kinase.

Rising Energetic Cost of Walking Predicts Gait Speed Decline With Aging

BACKGROUND

Slow gait is a robust biomarker of health and a predictor of functional decline and death in older adults, yet factors contributing to the decline in gait speed with aging are not well understood. Previous research suggests that the energetic cost of walking at preferred speed is inversely associated with gait speed, but whether individuals with a rising energetic cost of walking experience a steeper rate of gait speed decline has not been investigated.

METHODS

In participants of the Baltimore Longitudinal Study of Aging, the energetic cost of overground walking at preferred speed (mL/kg/m) was assessed between 2007 and 2014 using a portable indirect calorimeter. The longitudinal association between the energetic cost of walking and usual gait speed over 6 meters (m/s) was assessed with multivariate linear regression models, and the risk of slow gait (<1.0 m/s) was analyzed using Cox proportional hazards models.

RESULTS

The study population consisted of 457 participants aged 40 and older who contributed 1,121 person-visits to the analysis. In fully adjusted models, increases in the energetic cost of walking predicted the rate of gait speed decline in those older than 65 years (β = -0.008 m/s, p < .001). Moreover, those with a higher energetic cost of walking (>0.17mL/kg/m) had a 57% greater risk of developing slow gait compared with a normal energetic cost of walking (≤0.17mL/kg/m; adjusted hazard ratio = 1.57, 95% confidence interval: 1.01-2.46).

CONCLUSIONS

These findings suggest that strategies to maintain walking efficiency hold significant implications for maintaining mobility in late life. Efforts to curb threats to walking efficiency should focus on therapies to treat gait and balance impairments, and reduce clinical disease burden.

Non-coding genomic regions possessing enhancer and silencer potential are associated with healthy aging and exceptional survival

We have completed a genome-wide linkage scan for healthy aging using data collected from a family study, followed by fine-mapping by association in a separate population, the first such attempt reported. The family cohort consisted of parents of age 90 or above and their children ranging in age from 50 to 80. As a quantitative measure of healthy aging, we used a frailty index, called FI34, based on 34 health and function variables. The linkage scan found a single significant linkage peak on chromosome 12. Using an independent cohort of unrelated nonagenarians, we carried out a fine-scale association mapping of the region suggestive of linkage and identified three sites associated with healthy aging. These healthy-aging sites (HASs) are located in intergenic regions at 12q13-14. HAS-1 has been previously associated with multiple diseases, and an enhancer was recently mapped and experimentally validated within the site. HAS-2 is a previously uncharacterized site possessing genomic features suggestive of enhancer activity. HAS-3 contains features associated with Polycomb repression. The HASs also contain variants associated with exceptional longevity, based on a separate analysis. Our results provide insight into functional genomic networks involving non-coding regulatory elements that are involved in healthy aging and longevity.

Gender-Specific Associations in Age-Related Changes in Resting Energy Expenditure (REE) and MRI Measured Body Composition in Healthy Caucasians

BACKGROUND

The effect of gender as well as gender-specific changes of fat free mass (FFM) and its metabolic active components (muscle mass and organ masses [OMs]) and fat mass (FM) on age-related changes in resting energy expenditure (REE) are not well defined. We hypothesized that there are gender differences in (1) the age-specific onset of changes in detailed body composition (2); the onset of changes in body composition-REE associations with age.

METHODS

Using a cross-sectional magnetic resonance imaging database of 448 Caucasian participants (females and males) with comprehensive data on skeletal muscle (SM) mass, adipose tissue (AT), OMs, and REE.

RESULTS

We observed gender-specific differences in the onset of age-related changes in metabolic active components and REE. Declines in body composition and REE started earlier in females than in males for SM (29.4 vs 39.6 years), AT (38.2 vs 49.9 years), OM (34.7 vs 45.7 years), and REE (31.9 vs 36.8 years). The age-related decrease of AT was significantly higher in females than in males (-5.69kg/decade vs -0.59kg/decade). In females adjusted REEmFFM&FM (resting energy expenditure measured adjusted for FFM and FM) and REEmSM/OM/AT (resting energy expenditure measured adjusted for skeletal muscle and organ mass and adipose tissue) decreased by -145 kJ/d/decade and -604.8 kJ/d/ decade after the age of 35.2 respectively 34.3 years. SM was main determinant of REEm in females (R (2) = .67) and males (R (2) = .66) with remaining variance mainly explained by kidney mass (R (2) = .07) in females and liver mass (R (2) = .09) in males.

CONCLUSION

We concluded that gender affects the age-related changes in body composition as well as changes in body composition-REE relationship. This trial was registered at linicaltrials.gov as NCT01737034.

Energetics of Aging and Frailty: The FRADEA Study

BACKGROUND

Resting metabolic rate (RMR) and total daily energy expenditure (TDEE) decrease with aging, but it is not known whether frailty modulates this association. We hypothesize that RMR and TDEE values are similar between younger and older nonfrail older adults, whereas they are lower in older prefrail and frail compared with younger adults.

METHODS

A cross-sectional analysis of the FRADEA study, Albacete (Spain), including 402 participants (213 women) older than 70 years (mean age 76 years; range 70-91), was conducted. Estimated RMR (eRMR), oxygen consumption (VO2), expired volume (Ve), and respiratory frequency (RF) were determined using indirect calorimetry; TDEE was determined with the Calcumed instrument; and fat-free mass was determined by bioimpedanciometry. General linear models were used for analysis.

RESULTS

Mean TDEE was 1,889 (SD 470) kcal and eRMR was 1,071 (SD 323) kcal. Both TDEE (B = -24 kcal/day; 95% confidence interval: -35.4 to -14.2; p < .001) and eRMR (B= -15.8 kcal/day; 95% confidence interval: -23.1 to -8.5; p < .001) diminished linearly with age, with lower values in frail and prefrail participants. There was a strong trend between frailty and lower eRMR (F = 2.9; p = .058), with a modifying effect between age and frailty (F = 3.6; p = .002). eRMR in prefrail and frail participants were on average 160 and 114 kcal/day less than that in the nonfrail participants, respectively, and taken together, 154 kcal/day less (F = 5.4; p = .020). Frail and prefrail participants also presented lower Ve and VO2 values that were partially compensated by an RF increase.

CONCLUSION

Frailty status modulates the energy requirements of aging. Frail and prefrail older adults present lower eRMR than nonfrail adults.

Quantitative measures of healthy aging and biological age

Numerous genetic and non-genetic factors contribute to aging. To facilitate the study of these factors, various descriptors of biological aging, including 'successful aging' and 'frailty', have been put forth as integrative functional measures of aging. A separate but related quantitative approach is the 'frailty index', which has been operationalized and frequently used. Various frailty indices have been constructed. Although based on different numbers and types of health variables, frailty indices possess several common properties that make them useful across different studies. We have been using a frailty index termed FI34 based on 34 health variables. Like other frailty indices, FI34 increases non-linearly with advancing age and is a better indicator of biological aging than chronological age. FI34 has a substantial genetic basis. Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians. Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity.

Energy Metabolism and the Burden of Multimorbidity in Older Adults: Results From the Baltimore Longitudinal Study of Aging

Excessively elevated resting metabolic rate (RMR) for persons of a certain age, sex, and body composition is a mortality risk factor. Whether elevated RMR constitutes an early marker of health deterioration in older adult has not been fully investigated. Using data from the Baltimore Longitudinal Study of Aging, we hypothesized that higher RMR (i) was cross-sectionally associated with higher multimorbidity and (ii) predicted higher multimorbidity in subsequent follow-ups. The analysis included 695 Baltimore Longitudinal Study of Aging participants, aged 60 or older at baseline, of whom 248 had follow-up data available 2 years later and 109 four years later. Multimorbidity was assessed as number of chronic diseases. RMR was measured by indirect calorimetry and was tested in regression analyses adjusted for covariates age, sex, and dual-energy x-ray absorptiometry-measured total body fat mass and lean mass. Baseline RMR and multimorbidity were positively associated, independent of covariates (p = .002). Moreover, in a three-wave bivariate autoregressive cross-lagged model adjusted for covariates, higher prior RMR predicted greater future multimorbidity above and beyond the cross-sectional and autoregressive associations (p = .034). RMR higher than expected, given age, sex, and body composition, predicts future higher multimorbidity in older adults and may be used as early biomarker of impending health deterioration. Replication and the development of normative data are required for clinical translation.