Estimation of homeostatic dysregulation and frailty using biomarker variability: a principal component analysis of hemodialysis patients

Associations of healthy eating patterns with biological aging: national health and nutrition examination survey (NHANES) 1999-2018

BACKGROUND

Healthy dietary patterns have been negatively associated with methylation-based measures of biological age, yet previous investigations have been unable to establish the relationship between them and biological aging assessed through blood chemistry-based clinical biomarkers. We sought to assess the associations of 4 dietary metrics with 4 measures of biological age.

METHODS

Among 16,666 participants in NHANES 1999-2018, 4 dietary metrics [Dietary inflammatory index (DII), Dietary approaches to stop hypertension index (DASH), Alternate mediterranean diet score (aMED), and Healthy eating index-2015 (HEI-2015)] were calculated through the 'dietaryindex' R package. Twelve blood chemistry parameters were utilized to compute 4 indicators of biological age [homeostatic dysregulation (HD), allostatic load (AL), Klemera-Doubal method (KDM), and phenotypic age (PA)]. Binomial logistic regression models and restricted cubic spline (RCS) regression were employed to evaluate the associations.

RESULTS

All 4 dietary metrics were significantly associated with biological age acceleration or deceleration. In comparison to the lowest DII, the odds ratios (ORs) for accelerated HD, AL, KDM, and PA were 1.25 (1.08,1.45), 1.29 (1.11,1.50), 1.34 (1.08,1.65), and 1.61 (1.39,1.87) for the highest. The multivariable-adjusted ORs of the highest quartile of DASH, aMED, and HEI-2015 were 0.85 (0.73,0.97), 0.88 (0.74,1.04), and 0.84 (0.74,0.96) for HD, 0.64 (0.54,0.75), 0.61 (0.52,0.72), and 0.70 (0.59,0.82) for AL, 0.68 (0.54,0.85), 0.62 (0.50,0.76), and 0.71 (0.58,0.87) for KDM, and 0.50 (0.42,0.59), 0.64 (0.54,0.76), and 0.51 (0.44,0.58) for PA when compared with the lowest level. The findings were validated by the best-fitting dose-response curves for the associations. Among participants consuming dietary supplements (Pinteraction < 0.05), the positive effects of a healthy dietary pattern on biological aging were more pronounced. Systemic immune inflammation index (SII) and atherogenic index of plasma (AIP) were identified as being involved in and mediating the associations.

CONCLUSIONS

Biological aging assessed through blood chemistry-based clinical biomarkers is negatively associated with diet quality. The anti-aging benefits of improving the diet may be due to its ability to reduce inflammation and lower blood lipids.

Associations of daily eating frequency and nighttime fasting duration with biological aging in National Health and Nutrition Examination Survey (NHANES) 2003-2010 and 2015-2018

BACKGROUND

Information on the influences of daily eating frequency (DEF) and nighttime fasting duration (NFD) on biological aging is minimal. Our study investigated the potential associations of DEF and NFD with accelerated aging.

METHODS

Out of 24212 participants in NHANES 2003-2010 and 2015-2018, 4 predicted age metrics [homeostatic dysregulation (HD), Klemera-Doubal method (KDM), phenoAge (PA), and allostatic load (AL)] were computed based on 12 blood chemistry parameters. Utilizing 24-h dietary recall, DEF was measured by the frequency of eating occurrences, while NFD was determined by assessing the timing of the initial and final meals throughout the day. Weighted multivariate linear regression models and restricted cubic spline (RCS) were utilized to examine the associations.

RESULTS

Compared to DEF of ≤ 3.0 times, subjects with DEF ≥ 4.6 times demonstrated lower KDM residual [β: -0.57, 95% confidence-interval (CI): (-0.97, -0.17)] and PA residual [β: -0.47, 95% CI: (-0.69, -0.25)]. In comparison to NFD between 10.1 and 12.0 h, individuals with NFD ≤ 10.0 h were at higher HD [β: 0.03, 95% CI: (0.01, 0.04)], KDM residual [β: 0.34, 95% CI: (0.05, 0.63)], and PA residual [β: 0.38, 95% CI: (0.18, 0.57)]. Likewise, those with NFD ≥ 14.1 h also had higher HD [β: 0.02, 95% CI: (0.01, 0.04)] and KDM residual [β: 0.33, 95% CI: (0.03, 0.62)]. The results were confirmed by the dose-response relationships of DEF and NFD with predicted age metrics. Lactate dehydrogenase (LDH) and globulin (Glo) were acknowledged as implicated in and mediating the relationships.

CONCLUSIONS

DEF below 3.0 times and NFD less than 10.0 or more than 14.1 h were independently associated with higher predicted age metrics.

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.

Visit-to-visit variability in multiple biological measurements and cognitive performance and risk of cardiovascular disease: A cohort study

Background

Visit-to-visit variability in single biological measurements has been associated with cognitive decline and an elevated risk of cardiovascular diseases (CVD). However, the effect of visit-to-visit variability in multiple biological measures is underexplored. We investigated the effect of visit-to-visit variability in blood pressure (BP), heart rate (HR), weight, fasting plasma glucose, cholesterol, and triglycerides on cognitive performance and CVD.

Methods

Data on BP, HR, weight, glucose, cholesterol, and triglycerides from study visits in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial were used to estimate the association between visit-to-visit variability, cognitive performance (Mini Mental State Examination (MMSE) score) and CVD (non-fatal stroke, non-fatal myocardial infarction, or cardiovascular death). Visit-to-visit variation for each measurement was estimated by calculating each individuals visit-to-visit standard deviation for that measurement. Participants whose standard deviation was in the highest quarter were classified as having high variation. Participants were grouped into those having 0, 1, 2, 3, or ≥ 4 high variation measurements. Regression and survival models were used to estimate the association between biological measures with MMSE and CVD with adjustment for confounders and mean measurement value.

Results

After adjustment for covariates, higher visit-to-visit variability in BP, HR, weight, and FPG were associated with poorer MMSE and a higher risk of CVD. Effect sizes did not vary greatly by measurement. The effects of high visit-to-visit variability were additive; compared to participants who had no measurements with high visit-to-visit variability, those who had high visit-to-visit variability in ≥4 measurements had poorer MMSE scores (-0.63 (95 % CI -0.96 to -0·31). Participants with ≥4 measurements with high visit-to-visit variability compared to participants with none had higher risk of CVD (hazard ratio 2.46 (95 % CI 1.63 to 3.70).

Conclusion

Visit-to-visit variability in several measurements were associated with cumulatively poorer cognitive performance and a greater risk of CVD.

Application of early warning signs to physiological contexts: a comparison of multivariate indices in patients on long-term hemodialysis

Early warnings signs (EWSs) can anticipate abrupt changes in system state, known as "critical transitions," by detecting dynamic variations, including increases in variance, autocorrelation (AC), and cross-correlation. Numerous EWSs have been proposed; yet no consensus on which perform best exists. Here, we compared 15 multivariate EWSs in time series of 763 hemodialyzed patients, previously shown to present relevant critical transition dynamics. We calculated five EWSs based on AC, six on variance, one on cross-correlation, and three on AC and variance. We assessed their pairwise correlations, trends before death, and mortality predictive power, alone and in combination. Variance-based EWSs showed stronger correlations (r = 0.663 ± 0.222 vs. 0.170 ± 0.205 for AC-based indices) and a steeper increase before death. Two variance-based EWSs yielded HR95 > 9 (HR95 standing for a scale-invariant metric of hazard ratio), but combining them did not improve the area under the receiver-operating curve (AUC) much compared to using them alone (AUC = 0.798 vs. 0.796 and 0.791). Nevertheless, the AUC reached 0.825 when combining 13 indices. While some indicators did not perform overly well alone, their addition to the best performing EWSs increased the predictive power, suggesting that indices combination captures a broader range of dynamic changes occurring within the system. It is unclear whether this added benefit reflects measurement error of a unified phenomenon or heterogeneity in the nature of signals preceding critical transitions. Finally, the modest predictive performance and weak correlations among some indices call into question their validity, at least in this context.

Association of dietary inflammatory potential, dietary oxidative balance score and biological aging

BACKGROUND & AIMS

The interaction between diet, inflammation, and oxidative stress significantly influences aging, but the available evidence has been limited. We evaluated potential associations of dietary inflammatory index (DII), dietary oxidative balance score (DOBS), and measures of biological aging.

METHODS

This cross-sectional study was performed among 8839 individuals from NHANES 2003-2014. DII and DOBS were determined by aggregating data from 26 to 17 a priori selected dietary components. Biological aging metrics included homeostatic dysregulation (HD), Klemera-Doubal method (KDM), phenotypic age (PA), and allostatic load (AL). Binomial logistic regression models and multivariate linear regression models were conducted.

RESULTS

The associations of dietary inflammation and oxidative stress potential and biological aging metrics were significant among American adults nationwide. Consuming foods with higher DII was significantly associated with accelerated HD 1.26 (1.10, 1.44), KDM 1.24 (1.06, 1.45), and PA 1.54 (1.33, 1.78). Compared with the lowest DOBS, the hazard ratios of accelerated HD, KDM, PA, and AL were 0.74 (0.64, 0.86), 0.80 (0.70, 0.92), 0.61 (0.52, 0.72) and 0.78 (0.63, 0.97), respectively. The adverse effects of pro-inflammatory and pro-oxidative diets on accelerated HD, KDM, and PA were 1.39 (1.18, 1.62), 1.28 (1.08, 1.51), and 1.76 (1.47, 2.10). Serum AST/ALT ratio and globulin were implicated in and mediate the aging effects.

CONCLUSIONS

Higher DII and/or lower DOBS are associated with higher markers of biological aging. Our research elucidates that diets may mitigate biological aging resulting from inflammation and/or oxidative stress.

Use of frailty assessment instruments in nephrology populations: a scoping review

BACKGROUND

Frailty is a clinical syndrome of accelerated aging associated with adverse outcomes. Frailty is prevalent among patients with chronic kidney disease but is infrequently assessed in clinical settings, due to lack of consensus regarding frailty definitions and diagnostic tools. This study aimed to review the practice of frailty assessment in nephrology populations and evaluate the context and timing of frailty assessment.

METHODS

The search included published reports of frailty assessment in patients with chronic kidney disease, undergoing dialysis or in receipt of a kidney transplant, published between January 2000 and November 2021. Medline, CINAHL, Embase, PsychINFO, PubMed and Cochrane Library databases were examined. A total of 164 articles were included for review.

RESULTS

We found that studies were most frequently set within developed nations. Overall, 161 studies were frailty assessments conducted as part of an observational study design, and 3 within an interventional study. Studies favoured assessment of participants with chronic kidney disease (CKD) and transplant candidates. A total of 40 different frailty metrics were used. The most frequently utilised tool was the Fried frailty phenotype. Frailty prevalence varied across populations and research settings from 2.8% among participants with CKD to 82% among patients undergoing haemodialysis. Studies of frailty in conservatively managed populations were infrequent (N = 4). We verified that frailty predicts higher rates of adverse patient outcomes. There is sufficient literature to justify future meta-analyses.

CONCLUSIONS

There is increasing recognition of frailty in nephrology populations and the value of assessment in informing prognostication and decision-making during transitions in care. The Fried frailty phenotype is the most frequently utilised assessment, reflecting the feasibility of incorporating objective measures of frailty and vulnerability into nephrology clinical assessment. Further research examining frailty in low and middle income countries as well as first nations people is required. Future work should focus on interventional strategies exploring frailty rehabilitation.

Frailty Syndrome as a Transition from Compensation to Decompensation: Application to the Biomechanical Regulation of Gait

Most gait parameters decrease with age and are even more importantly reduced with frailty. However, other gait parameters exhibit different or even opposite trends for aging and frailty, and the underlying reason is unclear. Literature focuses either on aging, or on frailty, and a comprehensive understanding of how biomechanical gait regulation evolves with aging and with frailty seems to be lacking. We monitored gait dynamics in young adults (19-29 years, n = 27, 59% women), middle-aged adults (30-59 years, n = 16, 62% women), and non-frail (>60 years, n = 15, 33% women) and frail older adults (>60 years, n = 31, 71% women) during a 160 m walking test using the triaxial accelerometer of the Zephyr Bioharness 3.0 device (Zephyr Technology, Annapolis, MD, USA). Frailty was evaluated using the Frail Scale (FS) and the Clinical Frailty Scale (CFS). We found that in non-frail older adults, certain gait parameters, such as cadence, were increased, whereas other parameters, such as step length, were decreased, and gait speed is maintained. Conversely, in frail older adults, all gait parameters, including gait speed, were decreased. Our interpretation is that non-frail older adults compensate for a decreased step length with an increased cadence to maintain a functional gait speed, whereas frail older adults decompensate and consequently walk with a characteristic decreased gait speed. We quantified compensation and decompensation on a continuous scale using ratios of the compensated parameter with respect to the corresponding compensating parameter. Compensation and decompensation are general medical concepts that can be applied and quantified for many, if not all, biomechanical and physiological regulatory mechanisms of the human body. This may allow for a new research strategy to quantify both aging and frailty in a systemic and dynamic way.

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.

Efficient representations of binarized health deficit data: the frailty index and beyond

We investigated efficient representations of binarized health deficit data using the 2001-2002 National Health and Nutrition Examination Survey (NHANES). We compared the abilities of features to compress health deficit data and to predict adverse outcomes. We used principal component analysis (PCA) and several other dimensionality reduction techniques, together with several varieties of the frailty index (FI). We observed that the FI approximates the first - primary - component obtained by PCA and other compression techniques. Most adverse outcomes were well predicted using only the FI. While the FI is therefore a useful technique for compressing binary deficits into a single variable, additional dimensions were needed for high-fidelity compression of health deficit data. Moreover, some outcomes - including inflammation and metabolic dysfunction - showed high-dimensional behaviour. We generally found that clinical data were easier to compress than lab data. Our results help to explain the success of the FI as a simple dimensionality reduction technique for binary health data. We demonstrate how PCA extends the FI, providing additional health information, and allows us to explore system dimensionality and complexity. PCA is a promising tool for determining and exploring collective health features from collections of binarized biomarkers.

Stratified Multivariate Multiscale Dispersion Entropy for Physiological Signal Analysis

Multivariate entropy quantification algorithms are becoming a prominent tool for the extraction of information from multi-channel physiological time-series. However, in the analysis of physiological signals from heterogeneous organ systems, certain channels may overshadow the patterns of others, resulting in information loss. Here, we introduce the framework of Stratified Entropy to prioritize each channels' dynamics based on their allocation to respective strata, leading to a richer description of the multi-channel time-series. As an implementation of the framework, three algorithmic variations of the Stratified Multivariate Multiscale Dispersion Entropy are introduced. These variations and the original algorithm are applied to synthetic time-series, waveform physiological time-series, and derivative physiological data. Based on the synthetic time-series experiments, the variations successfully prioritize channels following their strata allocation while maintaining the low computation time of the original algorithm. In experiments on waveform physiological time-series and derivative physiological data, increased discrimination capacity was noted for multiple strata allocations in the variations when benchmarked to the original algorithm. This suggests improved physiological state monitoring by the variations. Furthermore, our variations can be modified to utilize a priori knowledge for the stratification of channels. Thus, our research provides a novel approach for the extraction of previously inaccessible information from multi-channel time series acquired from heterogeneous systems.

A complex systems approach to aging biology

Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging.

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.

Pre-Frailty and Frailty in Dialysis and Pre-Dialysis Patients: A Systematic Review of Clinical and Biochemical Markers

Patients under dialysis are known to be more vulnerable to frailty, a dynamic geriatric syndrome defined as a state of vulnerability to stressors, due to numerous metabolic changes. With rise of life expectancy globally, it is important to understand the complexity of the pathophysiology of frailty and identify possible markers that can help with the prognosis and diagnosis of frailty. The aim of this systematic review is to give an overview of the knowledge regarding clinical and biochemical markers associated with pre-frailty and frailty in dialysis and pre-dialysis patients. In November 2020, PubMed, Embase and Web of Science were searched. Studies regarding biomarkers associated with (pre-)frailty in (pre-)dialysis patients were included. This systematic review identified clinical and biochemical markers in pre-frail and frail patients under dialysis or pre-dialysis published in the literature. This study shows that more investigation is necessary to identify markers that can differentiate these processes to be used as a diagnostic and prognostic tool in routine care and management of geriatric needs. Interventions that can improve health outcomes in pre-frail and frail older adults under dialysis or pre-dialysis are essential to improve not only the individual's quality of life but also to reduce the burden to the health systems.

Association between serum lactate dehydrogenase and frailty among individuals with metabolic syndrome

While metabolic syndrome (MetS) is associated with frailty, the correlation of serum lactate dehydrogenase (sLDH) and frailty with MetS remain uncertain. To investigate the relationship between sLDH and frail components in the US with MetS. A total of 4,066 participants aged 40-90 years were assessed from the database of the third National Health and Nutrition Examination Survey, 1988-1994. The participants were classified into MetS and non-MetS groups. Multivariate logistic regression analysis with four models were performed to assess the odds ratio (OR) of the divided tertiles of sLDH levels with frailty, and frail components including slow walking (SW), weakness, exhaustion, low physical activity (LPA), and low body weight (LBW). Higher sLDH levels were positively associated with frailty in the MetS group (p = 0.024) but not in non-MetS group (p = 0.102). After covariate adjustments, the OR of frailty in the upper two tertiles compared to the lowest tertile and revealed statistical significance (p < 0.05). Frail components of SW, weakness, exhaustion, and LPA were associated with higher sLDH (p < 0.05) except for LBW in MetS and non-MetS groups. The results demonstrated the strong association of higher sLDH levels and frailty among US individuals with MetS.

Mahalanobis distance, a novel statistical proxy of homeostasis loss is longitudinally associated with risk of type 2 diabetes

Background

The potential role of individual plasma biomarkers in the pathogenesis of type 2 diabetes (T2D) has been broadly studied, but the impact of biomarkers interaction remains underexplored. Recently, the Mahalanobis distance (MD) of plasma biomarkers has been proposed as a proxy of physiological dysregulation. Here we aimed to investigate whether the MD calculated from circulating biomarkers is prospectively associated with development of T2D.

Methods

We calculated the MD of the Principal Components (PCs) integrating the information of 32 circulating biomarkers (comprising inflammation, glycemic, lipid, microbiome and one-carbon metabolism) measured in 6247 participants of the PREVEND study without T2D at baseline. Cox proportional-hazards regression analyses were performed to study the association of MD with T2D development.

Findings

After a median follow-up of 7·3 years, 312 subjects developed T2D. The overall MD (mean (SD)) was higher in subjects who developed T2D compared to those who did not: 35·65 (26·67) and 30.75 (27·57), respectively (P = 0·002). The highest hazard ratio (HR) was obtained using the MD calculated from the first 31 PCs (per 1 log-unit increment) (1·72 (95% CI 1·42,2·07), P < 0·001). Such associations remained after the adjustment for age, sex, plasma glucose, parental history of T2D, lipids, blood pressure medication, and BMI (HR_adj 1·37 (95% CI 1·11,1·70), P = 0·004).

Interpretation

Our results are in line with the premise that MD represents an estimate of homeostasis loss. This study suggests that MD is able to provide information about physiological dysregulation also in the pathogenesis of T2D.

Funding

The Dutch Kidney Foundation (Grant E.033).

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.

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

Frailty is a clinical syndrome often present in older adults and characterized by a heightened vulnerability to stressors. The biological antecedents and etiology of frailty are unclear despite decades of research: frailty is associated with dysregulation in a wide range of physiological systems, but no specific cause has been identified. Here, we test predictions stemming from the hypothesis that there is no specific cause: that frailty is an emergent property arising from the complex systems dynamics of the broad loss of organismal homeostasis. Specifically, we use dysregulation of six physiological systems using the Mahalanobis distance approach in two cohorts of older adults to test the breadth, diffuseness, and nonlinearity of associations between frailty and system-specific dysregulation. We find clear support for the breadth of associations between frailty and physiological dysregulation: positive associations of all systems with frailty in at least some analyses. We find partial support for diffuseness: the number of systems or total amount of dysregulation is more important than the identity of the systems dysregulated, but results only partially replicate across cohorts. We find partial support for nonlinearity: trends are exponential but not always significantly so, and power is limited for groups with very high levels of dysregulation. Overall, results are consistent with-but not definitive proof of-frailty as an emergent property of complex systems dynamics. Substantial work remains to understand how frailty relates to underlying physiological dynamics across systems.