Evidence from two cohorts for the frailty syndrome as an emergent state of parallel dysregulation in multiple physiological systems

In Support of Multidimensional Frailty: A Structural Equation Model from the Canadian Positive Brain Health Now Cohort

The objective of this study was to estimate the structure and relationships between four h ypothesized frailty dimensions (physical, emotional, cognitive, and social) and the extent to which personal and HIV-related factors and comorbidity associate with these frailty dimensions. This is a secondary analysis of an existing dataset arising from Positive Brain Health Now study (n = 856) in people aging with HIV (mean age: 52.3 ± 8.1 years). Structural equation modeling (SEM) models were applied to two cross-sections of the data: one at study entry and one at second visit, 9-month apart. Multidimensional frailty was modeled based on the combined Wilson-Cleary and International Classification of Functioning, Disability and Health framework. Four dimensions were operationalized with patient-reported and self-report measures from standardized questionnaires. The SEM model from the first visit was replicated using data from the second visit, testing measurement invariance. The proposed model showed acceptable fit at both visits (including no violation of measurement invariance). The final model for the first visit showed that sex, body mass index, HIV diagnosis pre-1997, current or nadir CD4 counts, and comorbidity did not associate with any frailty dimension; however, age (β range: 0.12-0.25), symptoms (β range: -0.35 to -0.58), and measured cognition (β range: 0.10-0.24) directly associated with all frailty dimensions. The model remained stable across the two visits. This study contributes evidence for operationalizing multidimensional frailty. Evidence-based interventions are available for many of the measures considered here, offering opportunities to improve the lives of people with frailty in the context of HIV.

Associating frailty and dynamic dysregulation between motor and cardiac autonomic systems

Frailty is a geriatric syndrome associated with the lack of physiological reserve and consequent adverse outcomes (therapy complications and death) in older adults. Recent research has shown associations between heart rate (HR) dynamics (HR changes during physical activity) with frailty. The goal of the present study was to determine the effect of frailty on the interconnection between motor and cardiac systems during a localized upper-extremity function (UEF) test. Fifty-six individuals aged 65 or above were recruited and performed the previously developed UEF test consisting of 20-s rapid elbow flexion with the right arm. Frailty was assessed using the Fried phenotype. Wearable gyroscopes and electrocardiography were used to measure motor function and HR dynamics. In this study, the interconnection between motor (angular displacement) and cardiac (HR) performance was assessed, using convergent cross-mapping (CCM). A significantly weaker interconnection was observed among pre-frail and frail participants compared to non-frail individuals (p < 0.01, effect size = 0.81 ± 0.08). Using logistic models, pre-frailty and frailty were identified with sensitivity and specificity of 82%-89%, using motor, HR dynamics, and interconnection parameters. Findings suggested a strong association between cardiac-motor interconnection and frailty. Adding CCM parameters in a multimodal model may provide a promising measure of frailty.

Physiological Dysregulation Proceeds and Predicts Health Outcomes Similarly in Chinese and Western Populations

BACKGROUND

A decade ago, we proposed an index of physiological dysregulation based on Mahalanobis distance (DM) that measures how far from the norm an individual biomarker profile is. While extensive validation has been performed, focus was mostly on Western populations with little comparison to developing countries, particularly at a physiological system level. The degree to which the approach would work in other sociocultural contexts and the similarity of dysregulation signatures across diverse populations are still open questions.

METHODS

Using 2 data sets from China and 3 from Western countries (United States, United Kingdom, and Italy), we calculated DM globally and per physiological system. We assessed pairwise correlations among systems, difference with age, prediction of mortality and age-related diseases, and sensitivity to interchanging data sets with one another as the reference in DM calculation.

RESULTS

Overall, results were comparable across all data sets. Different physiological systems showed distinct dysregulation processes. Association with age was moderate and often nonlinear, similarly for all populations. Mahalanobis distance predicted most health outcomes, although differently by physiological system. Using a Chinese population as the reference when calculating DM for Western populations, or vice versa, led to similar associations with health outcomes, with a few exceptions.

CONCLUSIONS

While small differences were noticeable, they did not systematically emerge between Chinese and Western populations, but rather diffusively across all data sets. These findings suggest that DM presents similar properties, notwithstanding sociocultural backgrounds, and that it is equally effective in capturing the loss of homeostasis that occurs during aging in diverse industrial human populations.

Frailty detection in older adults via fractal analysis of acceleration signals from wrist-worn sensors

Purpose

Frailty is a reversible multidimensional syndrome that puts older people at a high risk of adverse health outcomes. It has been proposed to emerge from the dysregulation of the complex system dynamics of physiologic control systems. We propose the analysis of the fractal complexity of hand movements as a new method to detect frailty in older adults.

Methods

FRAIL scale and Fried's phenotype scores were calculated for 1209 subjects-72.4 (5.2) y.o. 569 women-and 1279 subjects-72.6 (5.3) y.o. 604 women-in the pubicly available NHANES 2011-2014 data set, respectively. The fractal complexity of their hand movements was assessed with a detrended fluctuation analysis (DFA) of their accelerometry records and a logistic regression model for frailty detection was fit.

Results

Goodness-of-fit to a power law was excellent (R2 > 0.98 ). The association between complexity loss and frailty level was significant, Kruskal-Wallis test (df = 2, Chisq = 27.545, p-value < 0.001 ). The AUC of the logistic classifier was moderate (AUC with complexity = 0.69 vs. AUC without complexity = 0.67).

Conclusion

Frailty can be characterized in this data set with the Fried phenotype. Non-dominant hand movements in free-living conditions are fractal processes regardless of age or frailty level and its complexity can be quantified with the exponent of a power law. Higher levels of complexity loss are associated with higher levels of frailty. This association is not strong enough to justify the use of complexity loss after adjusting for sex, age, and multimorbidity.

[Frailty phenotype and risk factor for disturbed sleep]

Regardless of the nature of its operationalization, frailty has significant negative consequences for the person concerned and the community. Even if a generally accepted definition of frailty is still missing, there is no doubt about the existence of this phenomenon. Pathophysiologically, a dysfunctional interaction between multiple complex systems is discussed. Therapeutic interventions show that frailty is a dynamic state that can be improved. The pathophysiological characteristics of frailty and sleep disturbances show numerous similarities. In addition, the risk of frailty is increased in individuals with sleep disturbances. As the majority of sleep disorders can usually be well treated, screening for sleep disorders should be integrated into a comprehensive concept of management of frailty.

Assessment of Physical Resilience Using Residual Methods and Its Association With Adverse Outcomes in Older Adults

Background and Objectives

Physical resilience (PR) is recognized as the ability to recover from the adverse effects of a stressor. However, there is a lack of consensus on how to optimally measure PR in older adults in general. We aimed to measure PR using residuals from regression analyses and investigated its association with adverse outcomes in older adults.

Research Design and Methods

A total of 6 508 older adults were included from the National Health and Aging Trends Study, which was a population-based prospective cohort study. PR was assessed using residual methods from a linear model regressing the short physical performance battery on clinical diseases, age, sex, race/ethnicity, and health condition. Adverse outcomes included all-cause mortality, falls, and overnight hospitalization.

Results

The mean age was 77.48 (7.84) years. Increased PR was associated with a lower risk of all-cause mortality (hazard ratio [HR] = 0.85, 95% confidence interval [CI]: 0.83-0.87). Compared to participants with reduced PR, those with normal PR had a lower risk for mortality (HR = 0.51, 95% CI: 0.46-0.56). Specifically, restricted cubic spline regression revealed a dose-response relationship between PR and all-cause mortality (p-overall < .0001, p-nonlinear = .011). Additionally, we also found significant associations of increased PR with lower risks of falls (HR = 0.98, 95% CI: 0.96-0.99) and overnight hospitalization (HR = 0.98, 95% CI: 0.97-1.00).

Discussion and Implications

PR, measured by residual methods, was robustly and independently associated with all-cause mortality, falls, and overnight hospitalization. Our findings provide evidence that this approach may be a simple and feasible strategy to assess PR.

Frailty and comorbidities among young adult cancer survivors enrolled in an mHealth physical activity intervention trial

PURPOSE

The physical frailty phenotype identifies individuals at risk for adverse health outcomes but has rarely been assessed among young adult cancer survivors (YACS). This study describes frailty status among YACS participating in a physical activity (PA) intervention trial.

METHODS

YACS were categorized at baseline using the 5-item FRAIL scale: fatigue; weight loss; illness; ambulation; resistance. Chi-square tests compared frailty and non-cancer comorbidities by characteristics. Prevalence rates (PRs) for the independent associations between characteristics, frailty, and comorbidities were estimated using modified Poisson regression models.

RESULTS

Among 280 YACS (82% female; mean (M) age = 33.4 ± 4.8 years, M=3.7 ± 2.4 years post-diagnosis), 11% frail, 17% prefrail; the most frequent criteria were fatigue (41%), resistance (38%), and ambulation (14%). Compared to BMI < 25, higher BMI was associated with increased likelihood of frailty (BMI 25-30, PR: 2.40, 95% CI: 1.38-4.17; BMI > 30, PR: 2.95, 95% CI: 1.71-5.08). Compared to 0, ≥ 30 min/week of moderate-to-vigorous PA was associated with reduced frailty (PR: 0.39, 95% CI: 0.25-0.60). Most YACS (55%) reported ≥ 1 comorbidity, most frequently depression (38%), thyroid condition (19%), and hypertension (10%). Comorbidities were more common for women (59% vs. 37%) and current/former smokers (PR: 1.71, 95% CI: 1.29-2.28).

CONCLUSION

Prevalence of frailty and comorbidities in this sample was similar to other YACS cohorts and older adults without cancer and may be an indicator of accelerated aging and increased risk for poor outcomes.

IMPLICATIONS FOR CANCER SURVIVORS

Assessment of frailty may help identify YACS at increased risk for adverse health outcomes.

Aging-Related Multisystem Dysregulation Over the Adult Life Span and Physical Function in Later Life: The Atherosclerosis Risk in Communities (ARIC) Study

BACKGROUND

Multisystem dysregulation (Dm) shows promise as a metric of aging and predicts mortality. However, Dm needs to be studied with less severe endpoints indicating modifiable aging stages. Physical function, reflecting healthy longevity rather than just longevity, is more relevant to the goals of geroscience but has not been well investigated.

METHODS

We tested the association of midlife Dm and its change over ~20 years with physical function in later life in 5 583 the Atherosclerosis Risk in Communities Study cohort participants (baseline mean age 54.7). Dm quantifies the multivariate statistical deviation of 17 physiologically motivated biomarkers relative to their distribution in a young healthy sample at baseline. Physical function was assessed from grip strength and the Short Physical Performance Battery (SPPB). Associations were quantified using linear regression and ordinal logistic regression adjusting for age, sex, race, and education.

RESULTS

Each unit increment in midlife Dm was associated with 1.71 times the odds of having a lower SPPB score. Compared to the first quartile of midlife Dm, the odds ratios of having a lower SPPB score were 1.25, 1.56, and 2.45, respectively, for the second-fourth quartiles. Similar graded association patterns were observed for each SPPB component test and grip strength. An inverse monotonic relationship also was observed between the annual growth rate of Dm and physical function.

CONCLUSION

Greater Dm and progression in midlife were associated with lower physical function in later life. Future studies on the factors that lead to the progression of Dm may highlight opportunities to preserve physical function.

Frailty and Comorbidities Among Young Adult Cancer Survivors Enrolled in an mHealth Physical Activity Intervention Trial

Purpose: The physical frailty phenotype identifies individuals at risk for adverse health outcomes but has rarely been assessed among young adult cancer survivors (YACS). This study describes frailty status among YACS participating in a PA intervention trial. Methods: YACS were categorized by frailty status at baseline using the 5-item FRAIL index: fatigue; weight loss; illness; ambulation; resistance. Chi-square tests compared frailty and comorbidities by characteristics. Prevalence rates (PRs) for the independent associations between characteristics, frailty, and comorbidities were estimated using modified Poisson regression models. Results: Among 280 YACS (82% female, M=33.4±4.8 years, M=3.7±2.4 years post-diagnosis), 14% had frailty, and 24% prefrailty; the most frequent criteria were fatigue (70%), resistance (38%), and ambulation (14%). Compared to BMI <25, higher BMI (BMI 25-30, PR: 1.65, 95% CI: 1.02-2.65; BMI > 30, PR: 2.36, 95% CI: 1.46-3.81) was associated with increased frailty status. Compared to 0, 1-50 minutes/week of moderate-to-vigorous PA was associated with reduced frailty (PR: 0.62, 95% CI: 0.43-0.90). Most YACS (55%) reported > 1 comorbidity, most frequently depression (38%), thyroid condition (19%), and hypertension (10%). Men were less likely to report comorbidities (PR: 0.63, 95% CI: 0.42-0.93). Current/former smokers (PR: 1.29, 95% CI: 1.01-1.64) were more likely to have comorbidities. Conclusion: Prevalence of frailty and comorbidities in this sample was similar to other YACS cohorts and may be an indicator of accelerated aging and increased risk for poor outcomes. Implications for Cancer Survivors: Assessment of frailty may help identify YACS at risk for adverse health outcomes.

Multisystem physiological perspective of human frailty and its modulation by physical activity

"Frailty" is a term used to refer to a state characterized by enhanced vulnerability to, and impaired recovery from, stressors compared with a nonfrail state, which is increasingly viewed as a loss of resilience. With increasing life expectancy and the associated rise in years spent with physical frailty, there is a need to understand the clinical and physiological features of frailty and the factors driving it. We describe the clinical definitions of age-related frailty and their limitations in allowing us to understand the pathogenesis of this prevalent condition. Given that age-related frailty manifests in the form of functional declines such as poor balance, falls, and immobility, as an alternative we view frailty from a physiological viewpoint and describe what is known of the organ-based components of frailty, including adiposity, the brain, and neuromuscular, skeletal muscle, immune, and cardiovascular systems, as individual systems and as components in multisystem dysregulation. By doing so we aim to highlight current understanding of the physiological phenotype of frailty and reveal key knowledge gaps and potential mechanistic drivers of the trajectory to frailty. We also review the studies in humans that have intervened with exercise to reduce frailty. We conclude that more longitudinal and interventional clinical studies are required in older adults. Such observational studies should interrogate the progression from a nonfrail to a frail state, assessing individual elements of frailty to produce a deep physiological phenotype of the syndrome. The findings will identify mechanistic drivers of frailty and allow targeted interventions to diminish frailty progression.

Intercorrelated variability in blood and hemodynamic biomarkers reveals physiological network in hemodialysis patients

Increased intra-individual variability of a variety of biomarkers is generally associated with poor health and reflects physiological dysregulation. Correlations among these biomarker variabilities should then represent interactions among heterogeneous biomarker regulatory systems. Herein, in an attempt to elucidate the network structure of physiological systems, we probed the inter-variability correlations of 22 biomarkers. Time series data on 19 blood-based and 3 hemodynamic biomarkers were collected over a one-year period for 334 hemodialysis patients, and their variabilities were evaluated by coefficients of variation. The network diagram exhibited six clusters in the physiological systems, corresponding to the regulatory domains for metabolism, inflammation, circulation, liver, salt, and protein. These domains were captured as latent factors in exploratory and confirmatory factor analyses (CFA). The 6-factor CFA model indicates that dysregulation in each of the domains manifests itself as increased variability in a specific set of biomarkers. Comparison of a diabetic and non-diabetic group within the cohort by multi-group CFA revealed that the diabetic cohort showed reduced capacities in the metabolism and salt domains and higher variabilities of the biomarkers belonging to these domains. The variability-based network analysis visualizes the concept of homeostasis and could be a valuable tool for exploring both healthy and pathological conditions.

Energy metabolism and frailty: The potential role of exercise-induced myokines - A narrative review

Frailty is a complex condition that emerges from dysregulation in multiple physiological systems. Increasing evidence suggests the potential role of age-related energy dysregulation as a key driver of frailty. Exercise is considered the most efficacious intervention to prevent and even ameliorate frailty as it up-tunes and improves the function of several related systems. However, the mechanisms and molecules responsible for these intersystem benefits are not fully understood. The skeletal muscle is considered a secretory organ with endocrine functions that can produce and secrete exercise-related molecules such as myokines. These molecules are cytokines and other peptides released by muscle fibers in response to acute and/or chronic exercise. The available evidence supports that several myokines can elicit autocrine, paracrine, or endocrine effects, partly mediating inter-organ crosstalk and also having a critical role in improving cardiovascular, metabolic, immune, and neurological health. This review describes the current evidence about the potential link between energy metabolism dysregulation and frailty and provides a theoretical framework for the potential role of myokines (via exercise) in counteracting frailty. It also summarizes the physiological role of selected myokines and their response to different acute and chronic exercise protocols in older adults.

Multidimensional associations between nutrient intake and healthy ageing in humans

BACKGROUND

Little is known about how normal variation in dietary patterns in humans affects the ageing process. To date, most analyses of the problem have used a unidimensional paradigm, being concerned with the effects of a single nutrient on a single outcome. Perhaps then, our ability to understand the problem has been complicated by the fact that both nutrition and the physiology of ageing are highly complex and multidimensional, involving a high number of functional interactions. Here we apply the multidimensional geometric framework for nutrition to data on biological ageing from 1560 older adults followed over four years to assess on a large-scale how nutrient intake associates with the ageing process.

RESULTS

Ageing and age-related loss of homeostasis (physiological dysregulation) were quantified via the integration of blood biomarkers. The effects of diet were modelled using the geometric framework for nutrition, applied to macronutrients and 19 micronutrients/nutrient subclasses. We observed four broad patterns: (1) The optimal level of nutrient intake was dependent on the ageing metric used. Elevated protein intake improved/depressed some ageing parameters, whereas elevated carbohydrate levels improved/depressed others; (2) There were non-linearities where intermediate levels of nutrients performed well for many outcomes (i.e. arguing against a simple more/less is better perspective); (3) There is broad tolerance for nutrient intake patterns that don't deviate too much from norms ('homeostatic plateaus'). (4) Optimal levels of one nutrient often depend on levels of another (e.g. vitamin E and vitamin C). Simpler linear/univariate analytical approaches are insufficient to capture such associations. We present an interactive tool to explore the results in the high-dimensional nutritional space.

CONCLUSION

Using multidimensional modelling techniques to test the effects of nutrient intake on physiological dysregulation in an aged population, we identified key patterns of specific nutrients associated with minimal biological ageing. Our approach presents a roadmap for future studies to explore the full complexity of the nutrition-ageing landscape.

Chronotropic Response and Heart Rate Variability before and after a 160 m Walking Test in Young, Middle-Aged, Frail, and Non-Frail Older Adults

The frailty syndrome is characterized by a decreased capacity to adequately respond to stressors. One of the most impaired physiological systems is the autonomous nervous system, which can be assessed through heart rate (HR) variability (HRV) analysis. In this article, we studied the chronotropic response (HR and HRV) to a walking test. We also analyzed HRV indices in rest as potential biomarkers of frailty. For this, a 160 m-walking test and two standing rest tests (before and after the walking) were performed by young (19−29 years old, n = 21, 57% women), middle-aged (30−59 years old, n = 16, 62% women), and frail older adults (>60 years old, n = 28, 40% women) and non-frail older adults (>60 years old, n = 15, 71% women), classified with the FRAIL scale and the Clinical Frailty Scale (CFS). Frequency domain parameters better allowed to distinguish between frail and non-frail older adults (low-frequency power LF, high-frequency power HF (nu), LF/HF ratio, and ECG-derived respiration rate EDR). Frail older adults showed an increased HF (nu) and EDR and a reduced LF (nu) and LF/HF compared to non-frail older adults. The increase in HF (nu) could be due to a higher breathing effort. Our results showed that a walk of 160 m is a sufficient cardiovascular stressor to exhibit an attenuated autonomic response in frail older adults. Several HRV indices showed to be potential biomarkers of frailty, being LF (nu) and the time required to reach the maximum HR the best candidates.

Synchrony of biomarker variability indicates a critical transition: Application to mortality prediction in hemodialysis

Critical transition theory suggests that complex systems should experience increased temporal variability just before abrupt state changes. We tested this hypothesis in 763 patients on long-term hemodialysis, using 11 biomarkers collected every two weeks and all-cause mortality as a proxy for critical transitions. We find that variability-measured by coefficients of variation (CVs)-increases before death for all 11 clinical biomarkers, and is strikingly synchronized across all biomarkers: the first axis of a principal component analysis on all CVs explains 49% of the variance. This axis then generates powerful predictions of mortality (HR95 = 9.7, p < 0.0001, where HR95 is a scale-invariant metric of hazard ratio; AUC up to 0.82) and starts to increase markedly ∼3 months prior to death. Our results provide an early warning sign of physiological collapse and, more broadly, a quantification of joint system dynamics that opens questions of how system modularity may break down before critical transitions.

Frailty Risks of Prescription Analgesics and Sedatives across Frailty Models: the Health and Retirement Study

INTRODUCTION

Limited evidence for incident frailty risks associated with prescription analgesics and sedatives in older (≥ 65 years) community-living adults prompted a more comprehensive investigation.

METHODS

We used data from older Health and Retirement Study respondents and three frailty models (frailty index, functional domain, frailty phenotype with 8803, 10,470, and 6850 non-frail individuals, respectively) and estimated sub-hazard ratios of regular prescription drug use (co-use, analgesic use, and sedative use), by frailty model. We addressed confounding with covariate adjustment and propensity score matching approaches.

RESULTS

The baseline prevalence of analgesic and sedative co-use, analgesic use, and sedative use among non-frail respondents was 1.8%, 12.8%, and 4.7% for the frailty index model, 4.2%, 16.2%, and 5.3% for the functional domain model, and 4.3%, 15.4%, and 6.1% for the frailty phenotype model, respectively. Cumulative frailty incidence over 10 years was 39.3%, 36.1%, and 14.2% for frailty index, functional domain, and frailty phenotype models, respectively; covariate-adjusted sub-hazard ratio estimates were 2.00 (1.63-2.45), 1.83 (1.57-2.13), and 1.68 (1.21-2.33) for co-use; 1.72 (1.56-1.89), 1.38 (1.27-1.51), and 1.51 (1.27-1.79) for analgesic use; and 1.46 (1.24-1.72), 1.25 (1.07-1.46), and 1.31 (0.97-1.76) for sedative use. Frailty risk ranking (co-use > analgesic use > sedative use) persisted across all model sensitivity analyses.

DISCUSSION

Consistently significant frailty risk estimates of regular prescription analgesic and sedative co-use and of prescription analgesic use support existing clinical, public health, and regulatory guidance on opioid and benzodiazepine co-prescription, on opioid prescription, and on NSAID prescription. Frailty phenotype measurement administration limited power to detect significant frailty risks. Research into specific pharmaceutical exposures and comparison of results across cohorts will be required to contribute to the deprescribing evidence base.

Multisystem derangements in frailty and sarcopenia: a source for biomarker discovery

PURPOSE OF REVIEW

Multisystem derangements, encompassing metabolic, musculoskeletal and stress-response systems, occur during aging and are associated with the development of physical frailty and sarcopenia. These modular changes are relevant sources for the identification of biomarkers for the two conditions. Here, we provide an up-to-date overview on existing biomarkers of physical frailty and sarcopenia and discuss emerging approaches for biomarker discovery.

RECENT FINDINGS

Inflammatory, metabolic and hematologic markers are shared between physical frailty and sarcopenia. Gut microbial derivatives and damage-associated molecular patterns transferred via extracellular vesicles have been indicated as possible gut-muscle axis regulators and candidate markers of physical frailty and sarcopenia.

SUMMARY

Mediators of metabolic, musculoskeletal and stress-response system dysregulation are shared by physical frailty and sarcopenia and indicate the existence of common pathophysiological pathways. Multiplatform biomarker analyses have been proposed as an innovating approach for tracking the multifaceted and dynamic nature of physical frailty and sarcopenia. Upon validation, the identified biomarkers may support diagnostic makeup and tracking of the two conditions in both research and clinical settings.

An objective metric of individual health and aging for population surveys

BACKGROUND

We have previously developed and validated a biomarker-based metric of overall health status using Mahalanobis distance (DM) to measure how far from the norm of a reference population (RP) an individual's biomarker profile is. DM is not particularly sensitive to the choice of biomarkers; however, this makes comparison across studies difficult. Here we aimed to identify and validate a standard, optimized version of DM that would be highly stable across populations, while using fewer and more commonly measured biomarkers.

METHODS

Using three datasets (the Baltimore Longitudinal Study of Aging, Invecchiare in Chianti and the National Health and Nutrition Examination Survey), we selected the most stable sets of biomarkers in all three populations, notably when interchanging RPs across populations. We performed regression models, using a fourth dataset (the Women's Health and Aging Study), to compare the new DM sets to other well-known metrics [allostatic load (AL) and self-assessed health (SAH)] in their association with diverse health outcomes: mortality, frailty, cardiovascular disease (CVD), diabetes, and comorbidity number.

RESULTS

A nine- (DM9) and a seventeen-biomarker set (DM17) were identified as highly stable regardless of the chosen RP (e.g.: mean correlation among versions generated by interchanging RPs across dataset of r = 0.94 for both DM9 and DM17). In general, DM17 and DM9 were both competitive compared with AL and SAH in predicting aging correlates, with some exceptions for DM9. For example, DM9, DM17, AL, and SAH all predicted mortality to a similar extent (ranges of hazard ratios of 1.15-1.30, 1.21-1.36, 1.17-1.38, and 1.17-1.49, respectively). On the other hand, DM9 predicted CVD less well than DM17 (ranges of odds ratios of 0.97-1.08, 1.07-1.85, respectively).

CONCLUSIONS

The metrics we propose here are easy to measure with data that are already available in a wide array of panel, cohort, and clinical studies. The standardized versions here lose a small amount of predictive power compared to more complete versions, but are nonetheless competitive with existing metrics of overall health. DM17 performs slightly better than DM9 and should be preferred in most cases, but DM9 may still be used when a more limited number of biomarkers is available.

Frailty assessment using a novel approach based on combined motor and cardiac functions: a pilot study

BACKGROUND

Previous research showed association between frailty and an impaired autonomic nervous system; however, the direct effect of frailty on heart rate (HR) behavior during physical activity is unclear. The purpose of the current study was to determine the association between HR increase and decrease with frailty during a localized upper-extremity function (UEF) task to establish a multimodal frailty test.

METHODS

Older adults aged 65 or older were recruited and performed the UEF task of rapid elbow flexion for 20 s with the right arm. Wearable gyroscopes were used to measure forearm and upper-arm motion, and electrocardiography were recorded using leads on the left chest. Using this setup, HR dynamics were measured, including time to peak HR, recovery time, percentage increase in HR during UEF, and percentage decrease in HR during recovery after UEF.

RESULTS

Fifty-six eligible participants were recruited, including 12 non-frail (age = 76.92 ± 7.32 years), and 40 pre-frail (age = 80.53 ± 8.12 years), and four frail individuals (age = 88.25 ± 4.43 years). Analysis of variance models showed that the percentage increase in HR during UEF and percentage decrease in HR during recovery were both 47% smaller in pre-frail/frail older adults compared to non-frails (p < 0.01, effect size = 0.70 and 0.62 for increase and decrease percentages). Using logistic models with both UEF kinematics and HR parameters as independent variables, frailty was predicted with a sensitivity of 0.82 and specificity of 0.83.

CONCLUSION

Current findings showed evidence of strong association between HR dynamics and frailty. It is suggested that combining kinematics and HR data in a multimodal model may provide a promising objective tool for frailty assessment.

Immunogenicity of the BNT162b2 mRNA COVID-19 vaccine in older residents of a long-term care facility: relation with age, frailty and prior infection status

Clinical and biological assessment of the COVID-19 vaccine efficacy in the frail population is of crucial importance. The study focuses on measuring the levels of anti-SARS-CoV-2 IgG antibodies before and after BNT162b2 mRNA COVID-19 vaccination among long-term care facility (LTCF) elderly residents. We conducted a prospective, single-center, observational study among LTCF residents. The study protocol was based on three blood sample acquisitions: first taken at baseline-5 days before the first dose of the vaccine, second-20 days after the first dose, and third-12 days after the second shot of the vaccine. The comparison was made for two cohorts: patients with and without prior COVID-19 infection. The data was collected from January to March 2021. A total number of 78 LTCF residents (55 women and 23 men) aged 62-104, 85.72 ± 7.59 years (mean ± SD), were enrolled in the study. All study participants were investigated for the presence of SARS-CoV-2 anti-spike (S) protein IgG, using a chemiluminescent immunoassay. Frailty was assessed with the Clinical Frailty Scale. Among elderly COVID-19 survivors in LTCF, a single dose of vaccine significantly increased anti-SARS-CoV-2 IgG antibody levels. IgG concentration after a single and double dose was comparable, which may suggest that elderly COVID-19 survivors do not require a second dose of vaccine. For residents without a previous history of COVID-19, two doses are needed to achieve an effective serological response. The level of anti-SARS-CoV-2 IgG antibodies after vaccination with BNT162b2 mRNA COVID-19 did not correlate with the frailty and age of the studied individuals.

Physiological Dysregulation, Frailty, and Impacts on Adverse Health and Functional Outcomes

Background: Multi-system physiological dysregulation (PD) may represent a biological endo-phenotype of clinical frailty. We investigated the co-occurrence of PD with physical frailty and its contributions to the known impact of frailty on adverse health outcomes.

Methods: Data of 2,725 participants from the Singapore Longitudinal Aging Studies (SLAS-2), included baseline measures of physical frailty and PD derived from Mahalanobis distance (Dm) value of 23 blood biomarkers. We analyzed their concurrent association and their impacts on 9-year mortality, MMSE cognition, GDS depression, number of medications, disability, and hospitalization at baseline and follow up (mean 4.5 years).

Results: Global PD (Log₁₀Dm, mean = 1.24, SD = 0.24) was significantly but weakly associated with pre-frailty-and-frailty. Controlling for age, sex and education, pre-frailty-and-frailty (HR = 2.12, 95% CI = 1.51–3.00) and PD (HR = 3.88, 95% CI = 2.15–6.98) predicted mortality. Together in the same model, mortality HR associated with pre-frailty-and-frailty (HR = 1.83, 95% CI = 1.22–2.73) and PD (HR = 3.06, 95% CI = 1.60–5.85) were reduced after additionally adding global PD to the prediction model. The predictive accuracy for mortality were both approximately the same (PD: AUC = 0.62, frailty: AUC = 0.64), but AUC was significantly increased to 0.68 when combined (p < 0.001). Taken into account in the same model, frailty remained significantly associated with all health and functional outcomes, and PD was significantly associated with only MMSE, disability and medications used. In secondary analyses, there were mixed associations of system-specific PDs with frailty and different adverse outcomes.

Conclusions: Co-existing PD and physical frailty independently predict mortality and functional and health outcomes, with increased predictive accuracy when combined. PD appears to be a valid representation of a biological endo-phenotype of frailty, and the potential utility of such subclinical measures of frailty could be further studied.

Prediction of Mortality in Hemodialysis Patients Using Moving Multivariate Distance

There is an increasingly widespread use of biomarkers in network physiology to evaluate an organism’s physiological state. A recent study showed that albumin variability increases before death in chronic hemodialysis patients. We hypothesized that a multivariate statistical approach would better allow us to capture signals of impending physiological collapse/death. We proposed a Moving Multivariate Distance (MMD), based on the Mahalanobis distance, to quantify the variability of the multivariate biomarker profile as a whole from one visit to the next. Biomarker profiles from a visit were used as the reference to calculate MMD at the subsequent visit. We selected 16 biomarkers (of which 11 are measured every 2 weeks) from blood samples of 763 chronic kidney disease patients hemodialyzed at the CHUS hospital in Quebec, who visited the hospital regularly (∼every 2 weeks) to perform routine blood tests. MMD tended to increase markedly preceding death, indicating an increasing intraindividual multivariate variability presaging a critical transition. In survival analysis, the hazard ratio between the 97.5th percentile and the 2.5th percentile of MMD reached as high as 21.1 [95% CI: 14.3, 31.2], showing that higher variability indicates substantially higher mortality risk. Multivariate approaches to early warning signs of critical transitions hold substantial clinical promise to identify early signs of critical transitions, such as risk of death in hemodialysis patients; future work should also explore whether the MMD approach works in other complex systems (i.e., ecosystems, economies), and should compare it to other multivariate approaches to quantify system variability.

The physical frailty syndrome as a transition from homeostatic symphony to cacophony

Frailty in aging marks a state of decreased reserves resulting in increased vulnerability to adverse outcomes when exposed to stressors. This Perspective synthesizes the evidence on the aging-related pathophysiology underpinning the clinical presentation of physical frailty as a phenotype of a clinical syndrome that is distinct from the cumulative-deficit-based frailty index. We focus on integrating the converging evidence on the conceptualization of physical frailty as a state, largely independent of chronic diseases, that emerges when the dysregulation of multiple interconnected physiological and biological systems crosses a threshold to critical dysfunction, severely compromising homeostasis. Our exegesis posits that the physiology underlying frailty is a critically dysregulated complex dynamical system. This conceptual framework implies that interventions such as physical activity that have multisystem effects are more promising to remedy frailty than interventions targeted at replenishing single systems. We then consider how this framework can drive future research to further understanding, prevention and treatment of frailty, which will likely preserve health and resilience in aging populations.