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• W1566655075 abstract "The ability to formulate a clear clinical mission while also addressing the needs of patients, families, policymakers, and third-party payers challenges many healthcare providers. Those of us who provide care for frail elderly adults must consider additional layers of complexity, as represented by geriatric syndromes that have often confounded existing disease-based approaches to clinical care, education, reimbursement, manpower recruitment, and research.1, 2 Thus, strategies to define, measure, and better understand the nature of the frailty that places some older adults at risk of adverse outcomes have understandably assumed a central position in the efforts of geriatricians to respond to all of these challenges. The paper by Gruenewald et al.3 published in this issue provides evidence that a higher baseline value for the allostatic load score, a measure that has been used as an index of multisystem physiological dysregulation,4, 5 is associated with greater likelihood of frailty6 at 3 years of follow-up. The authors provide conservative analysis of data obtained between 1988/89 and 1991/92 from 1,189 participants in the MacArthur Study of Successful Aging, a well-known prospective cohort of high-functioning older adults recruited based on baseline age, cognition, and physical performance.7 Moreover, their findings are in agreement with those of a cross-sectional examination of the relationship between allostatic load and frailty performed in two other population-based cohorts: the Women's Health and Aging studies I and II.8 Nevertheless, clinicians more comfortable with disease-based approaches might question the significance of these findings. First, a 10% greater likelihood of frailty risk for each 1-unit increase in allostatic load score at baseline may seem modest. Second, how could a constellation of 10 different risk factors5 predict the development of frailty, a geriatric syndrome that itself has been defined as the presence of six findings or symptoms6? Third, if, as others have also shown,9 the mere number of total conditions or deficits experienced by an individual irrespective of their specific nature predicts disability, is it possible to speak of diagnostic precision, much less understand underlying mechanisms? Fourth, what is the dysregulation involving multiple physiological systems thought to underlie frailty,10 and is it possible to identify certain overarching principles to such vulnerability that could then help advance research progress in this area? Gruenewald et al.3 should be complimented for a contribution that provides new insights into a dialogue framed by these questions. Most progress in medicine is slow and incremental. A reconciliation between different and seemingly divergent approaches to a problem often facilitates more-rapid advances, especially at the level of conceptual breakthroughs. Training and previous experiences may play a role in how an individual views, articulates, and approaches research.11 Although such differences can present obstacles, they may also offer attractive opportunities for generating new insights. As a result, this report3 represents far more than a mere evaluation of the ability of one score to predict another. The concept of allostatic load emerged from behavioral and physiological sciences as an effort to better understand interindividual differences in the vulnerability to stress and disease.12 It subsequently gained acceptance as an epidemiological marker of functional decline and mortality in highly functioning older adults.5 In contrast, a definition of the frailty phenotype was operationalized through clinical consensus6 and validated as a syndrome in large datasets,6, 13 permitting a subsequent move to the description of frailty-relevant mechanisms.10 The study by Gruenewald et al.3 represents a step in identifying the first unifying threads between different approaches to the prediction of future disability in older adults. The risk of future disability has been conceptualized as a syndrome involving alterations in specific mechanisms10 or as the accumulation of stochastic deficits.9 Both concepts receive support in this report,3 suggesting that these two perspectives need not be mutually exclusive. Literature supporting the allostatic load theory suggests a role for specific deficits involving critical regulatory physiological circuits, as best illustrated through the loss of negative feedback inhibition. This results in lowered homeostatic stability, providing an example of physiological dysregulation that involves multiple systems and may underlie frailty. At the same time, evidence of a small but graded relationship between allostatic load and frailty supports the concept that cumulative damage also enhances the risk of frailty. Therefore, within the multifactorial complexity that underlies the vulnerability of some older adults, one can identify specific deficits and phenotype(s) while also demonstrating that the accumulation of deficits engenders the risk of vulnerability and the accumulation of yet more deficits. Homeostasis represents a key concept that arose from the writings of Claude Bernard in the 19th century.14 It resonates with geriatricians and is frequently mentioned in the context of aging and frailty.14 Homeostasis also provided the conceptual framework for McEwen's formulation of the theory of allostatic load.12 Earlier definitions emphasized homeostasis as the body's ability to maintain a constancy of the “milieu intérieur.”14 Since then, many individuals, starting with Walter Cannon in the early 20th century14 and ending with today's proponents of systems-based approaches to biology and medicine,15 began to recognize the need to address the dynamic features of complex regulatory systems that contribute to homeostasis as opposed to simply focusing on any single static outcome variable. This approach, in which an individual's capacity to respond to a glucose challenge or orthostatic tilt is a more-relevant indicator of physiological robustness than basal serum glucose levels or basal heart rate, is attractive to geriatricians, because it captures the essence of the sensitivity to homeostatic challenges that, from a clinical perspective, renders frail elderly adults vulnerable.14 The term allostasis was developed to define the operating range of the compensatory homeostatic mechanisms, describing their capacity to appropriately modify vital functions as a means of achieving new steady states in response to challenges.12 However, allostasis does not take into consideration the long-term effects of stress and generally requires assessments that do not lend themselves to population-based studies.12 Allostatic stress was introduced as a means of estimating the effects of repeated stress, as well as wear and tear at the level of various organ systems, that could predispose an individual to developing different types of disease.4 The original allostatic score index included 10 biomarkers of cardiovascular, metabolic, and endocrine stress regulatory systems (systolic and diastolic blood pressure, high-density lipoprotein cholesterol (HDL-C), the ratio of total cholesterol to HDL-C glycosylated hemoglobin, waist:hip ratio, dehydroepiandrosterone, urinary cortisol, urinary norepinephrine, and urinary epinephrine).4 Three inflammatory markers (fibrinogen, C-reactive protein, and interleukin-6) were added later.5 Given the nature of these measurements, it became possible to apply principles learned in individual research subjects or animal models to large population-based studies. Therefore, having linked allostasis to frailty risk,3 is it now possible to reveal some new insights into the nature of the physiological dysregulation that has been postulated to underlie frailty? Feedforward stimulation and negative feedback represent two broad mechanisms by which stress may contribute to frailty and disease through allostatic load.12, 16 Feedforward pathways involve anticipatory activation of stress pathways in response to psychological or physiological cues,16 with aging augmenting stress-induced adrenocorticotropic hormone and cortisol release.16 Although basal system stability may be maintained, chronic stress can exert a long-term toll through insulin resistance and end-organ damage.12, 16 Such damage, which can contribute to osteopenia, sarcopenia, hypertension, vascular disease, visceral adiposity, and hippocampal neuronal losses,16-19 may also diminish the capacity of affected individuals to respond to future homeostatic challenges.14, 20 High glucocorticosteroid levels feed back onto specific brain regions to inhibit further release.16 Recognition that the hippocampus plays a role in such feedback regulation helped advance the allostatic load theory by illustrating the potentially catastrophic consequences of allostatic damage when a specific site within a critical physiologic circuit is affected.16, 21 Because hippocampal atrophy may result from high basal glucocorticoid levels and also contribute to such levels, stress-mediated damage within the hippocampus could lead to a cascade of events, increasing allostatic damage and associated functional declines in memory.16, 21 In healthy older adults, prolonged high cortisol levels predict hippocampal atrophy18 and declines in hippocampal-related memory tasks.18, 19 The relevance of these principles may extend beyond corticosteroid physiology, providing overarching insights into the nature and specific sites of critical allostatic damage to complex regulatory systems that render frail older individuals more vulnerable to decompensation in the face of homeostatic challenges. For example, a large body of research has demonstrated evidence of robust physiological changes involving the aged sympathetic nervous system.14, 22 Not only are serum norepinephrine (but not epinephrine) levels high in healthy older adults under basal conditions, after multiple different challenges, these individuals demonstrate significantly greater and longer increases in this particular allostatic biomarker than younger subjects.14, 22 Diverse challenges, including task-related psychological stress, oral glucose ingestion, orthostatic tilt, and the insertion of a limb in ice-cold water can all uncover this type of age-related dysregulation.14, 22 In addition to evidence of age-related declines in the ability of the sympathetic nervous system to suppress its own activity through negative feedback mechanisms involving the brain, altered baroreceptor function with diminished capacity to sense elevations in blood pressure may also contribute.14, 22 Could aging- and disease-related declines in negative feedback mechanisms represent an example of allostatic damage that would reflect greater likelihood of decompensation in the face of homeostatic challenges, thus representing an initial overarching physiological biomarker of frailty and future functional decline? Observational studies offer few opportunities to address these questions within the framework of dynamic systems, but computational models are relevant. Using a mathematical modeling approach, Varadhan et al.23 demonstrated that a decrease in negative feedback or a decrease in positive feedforward loops decreases the resilience of a hypothetical dynamic system (modeled after the hypothalamic–pituitary–adrenal axis) by increasing the length of time required to regain a homeostatic baseline after perturbation. Any modeling approach needs to be validated in vivo within an intact functioning system. Initial proof of concept was provided in a study involving a simple gene circuit in a bacterium.24 Simply by genetically altering the ability of the final gene product to exert negative feedback on its own synthesis, the investigators were able to lengthen response times25 and diminish the circuit's overall stability.24 In the face of these findings, sometimes drawn from distant disciplines, what can we as geriatricians do to help pull all of these concepts together in a manner that will help us better predict and influence the course of aging in our patients? Because these issues lie at the core of what geriatricians know and do, we must provide leadership, ensuring that research into frailty continues to be grounded in clinical reality. At the same time, as many have begun to do, we also need to move beyond our individual “comfort zones” and reach out to content experts in other fields whose only previous exposure to aging issues may have been through an older family member. Successfully engaging such individuals in questions about which we are passionate does not happen overnight and is not without risk. Nevertheless, a failure to even try runs the risk of leaving us feeling increasingly isolated and frustrated. Moving predictive gerontology from the level of a concept toward clinical reality may also require that we gain a deeper understanding of the nature of successful frailty markers. For example, weak muscle strength and poor mobility performance represent better predictors of mortality than does muscle mass.26 Dynamic functional assessments involving the entire motor system seem preferable to static measurements of one body composition parameter, although older adults do not die simply because they walk a little more slowly. Therefore, the ability of muscle strength or gait speed to perform as a highly predictive biomarker may also reflect the capacity of these measurements to reveal the presence of underlying physiological dysregulation involving muscle and relevant regulatory systems that then enhances individual vulnerability. Unfortunately, all such predictive information will become clinically useful only if we can convince current and future patients to pursue strategies that may help them age better. The terms “frailty” and “resilience” or “vigor” are not only antonyms, but also appear to be intimately related at the level of underlying mechanisms and risk. As geriatricians, we have tended to focus primarily on addressing frailty-related issues, because our primary expertise and passion lie in the care of frail elderly patients. Nevertheless, a case can be made for devoting a research effort to both sides of this equation and for studying the same concepts in populations with low3 and high levels8 levels of baseline frailty. Finally, as regards our ability to stimulate health-promotion activities, evidence exists that an individual's ultimate decision bears a relationship to how they perceive their risk27 and whether the message is framed by emphasizing benefits (gains) or costs (losses).28 All of these issues, as well as the formulation of optimal messages, will need to be defined through research involving a broad spectrum of older adults if we wish to reach a point at which we will be able to truly predict and then influence the direction of the trajectory through which our patients age. Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this editorial. Author Contributions: The author is the sole contributor to this editorial. Sponsor's Role: None." @default.
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• W1566655075 title "Frailty, Allostatic Load, and the Future of Predictive Gerontology" @default.
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