Experimental Gerontology 54 (2014) 6–13

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Experimental Gerontology

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Review

The Frailty Syndrome: Clinical measurements and basic underpinnings inhumans and animals

M. Jane Mohler a,b,c,1, Mindy J. Fain a,b,c,1, Anne M. Wertheimer a,b,d, Bijan Najafi a,b,c, Janko Nikolich-Žugich a,d,⁎a Arizona Center on Aging, University of Arizona College of Medicine—Tucson, 1501 N. Campbell Avenue, P.O. Box 245017, Tucson, AZ 85724, USAb Division of Geriatrics, General InternalMedicine and Palliative Medicine, Department of Medicine, University of Arizona College ofMedicine—Tucson, 1501 N. Campbell Avenue, P.O. Box 245017,Tucson, AZ 85724, USAc Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Department of Surgery, University of Arizona College of Medicine—Tucson, 1501 N. Campbell Avenue, P.O. Box 245017,Tucson, AZ 85724, USAd Department of Immunobiology, University of Arizona College of Medicine—Tucson, 1501 N. Campbell Avenue, P.O. Box 245017, Tucson, AZ 85724, USA

Abbreviations: CKD, chronic kidney disease; CMV, cyprotein; CVD, Cardiovasular Disease; DM, Diabetes Mellinsulin-like growth factor; IFN, interferon; IL, interleukinligand 1; NF-kB, nuclear factor kappa-light-chain-enhanperipheral bloodmononuclear cells; RA, Rheumatoid Arth⁎ Corresponding author at: P.O. Box 245221, 1501 N. C

USA. Tel.: +1 520 626 6065; fax: +1 520 626 6477.E-mail addresses: jmohler@aging.arizona.edu (M.J. Mo

(M.J. Fain), awertheimer@aging.arizona.edu (A.M. Webnajafi@surgery.arizona.edu (B. Najafi), Nikolich@email.a

1 These authors contributed equally to this review.

0531-5565/$ – see front matter © 2014 Elsevier Inc. All rihttp://dx.doi.org/10.1016/j.exger.2014.01.024

a b s t r a c t

a r t i c l e i n f o

Article history:Received 19 November 2013Received in revised form 23 January 2014Accepted 27 January 2014Available online 4 February 2014

Section Editor: Daniela Frasca

Keywords:FrailtySyndromeMeasuresAnimalHumanReview

Frailty is an increasingly recognized syndrome resulting in age-related decline in function and reserve acrossmultiple physiologic systems. It presents as a hyperinflammable state, characterized by high vulnerabilityfor adverse health outcomes, such as disability, falls, hospitalization, institutionalization, and mortality.The prevalence of Frailty Syndrome (FS) is of potentially enormous significance, as it potentially affects 20–30% of adults older than 75. Cellular and molecular basis of frailty has not been elucidated.The objective of this review is to discuss recent advances in: (i) the potential cellular andmolecular basis of FrailtySyndrome, including development of new models to study it; (ii) the human and animal measures of FrailtySyndrome; and (iii) the development of objective cross-species correlates to aid the basic understanding, diagno-sis, treatment and rehabilitation of Frailty Syndrome in older adults.

© 2014 Elsevier Inc. All rights reserved.

1. Introduction—overview of the clinical implications of theFrailty Syndrome (FS)

We live in an aging society, and themost rapidly growing segment ofour population are people over the age of ninety (Anon, 2011). Thisrelatively recent explosion of large numbers of very old people livingin our communities has brought to light a new and critically importanthealth problem—the Frailty Syndrome (FS in the text). Frailty manifestsas a limited capacity to maintain homeostasis and is characterizedby a clinical state of age-related biological vulnerability to stressorsand decreased physiological reserves with alterations in lower energymetabolism, decreased skeletal muscle mass and quality, and altered

tomegalovirus; CRP, C-reactiveitus; FS, Frailty Syndrome; IGF,; KC, chemokine (C-X-C motif)cer of activated B cells; PBMC,ritis; TNF, tumor necrosis factor.ampbell Ave.,Tucson, AZ 85724,

hler), mfain@aging.arizona.edurtheimer),rizona.edu (J. Nikolich-Žugich).

ghts reserved.

hormonal and inflammatory functions (Evans et al., 2010; Fried et al.,2004). FS is associated with excess functional decline, dependency,healthcare utilization, hospitalization, institutionalization, and death.The most important questions facing the field are: (i) how can wemea-sure and define frailty in an objectivemanner: (ii) is frailty an extensionof normal aging; (iii) what is the molecular basis of frailty? This reviewwill attempt to provide answers by summarizing our knowledge onthese issues as it stands today.

Frailty is commonly used to indicate older persons at increased riskfor adverse outcomes. Although it is tempting to embrace an intuitiveunderstanding of frailty (a wasted, hunched and slow-moving eighty-five year old) it is critical to remember that frailty is a syndrome, andis not the result of normal aging. One of the cardinal laboratory findingsin FS is an accumulation of pro-inflammatory responses, the root causeof which is incompletely understood. Unlike physiological acute inflam-matory responses,which are of short duration and culminate in removalof the initial cause for inflammation (e.g., infection) and the resolutionof inflammation itself, FS is characterized by chronic inflammation andhigh levels of proinflammatory cytokines, which are higher than thoseseen in normal, non-Frail age matched individuals. The evolving con-cept of FS embraces the idea that the molecular, cellular, physiologicaland functional changes are distinct from the usual age-related changesand declines in organ systems, and distinct from disability and co-

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morbidity. Frailty is considered to be a dynamic condition thatcan improve or deteriorate over time, and is conceived to constitutea continuum from resilient, to pre-frail, to frail.

Consensus opinion is that the common pathway leading to thisconstellation of findings manifests itself as a decline in physical activityas a result of lifestyle or disease inputs. (Bortz, 2002) Thus, FS is largelyseparable from the aging process, although at the present it is unclearwhether and to what extent aging and FS should be susceptible to thesame, or different, specific and targeted interventions and reversal.Moreover, there may be a threshold effect, at which point reversibilityof FS is unlikely. Although the musculoskeletal system is an importanttarget for therapy, it is believed that FS is more complex thansarcopenia/dynopenia alone. Strength, endurance and balance trainingare considered the best strategies to improve frailty-related gait ability,balance, strength performance, and decrease the rate of falls in physicallyfrail older adults (Cadore et al., 2013). Other interventions have includednutritional and micronutrient support (protein, amino acids, calories,alkalosis through increased fruit and vegetable intake, vitamins D, B-12,and fish oil) (Inzitari et al., 2011; Kaiser et al., 2009; Kim et al., 2010;Mathers, 2013; Matteini et al., 2008, 2010; Millward, 2012; Morley,2013; Paddon-Jones, 2006), as well as reduction in polypharmacy(Tjia et al., 2013).

Community prevalence of FS varies widely (ranging from 4.0to 59.1%), with a marked increase in persons older than eighty years(Collard et al., 2012). It affects approximately thirty percent of peopleover the age of ninety years, a prevalence that closely parallels, butdoes not concordantly follow, the current dementia epidemic. Due tothe significant decline in health that the Frail elders experience, thissyndrome results in a financial, emotional and caregiving burden thatis similar to that of dementia.

Although,many geriatricians and gerontologists “know itwhen theysee it”, FS still lacks a consensus definition and a consensual clinicalassessmentmeasure (Morley andMalmstrom, 2013). One of the biggestissues in the field concerns distinctive features that would discriminateFS from progressively graded and increasing signs of “normal” aging.This is a non-trivial distinction. Basically, if FS was the extension ofnormal aging, then we would be simply looking at the same scale ofchanges over time and simply expect that, given the advanced age, allindividuals will become frail. However, clinical evidence suggests thatthis is not the case (Fried et al., 2001; Hamerman, 1999). Not all olderadults become frail, and, even in the very advanced age, that percentageremains under 50%. That said, this may be due to competing causes ofdeath. It is yet to be known if all individuals would become frail ifgiven the chance to escape competing causes of mortality. Moreover,many geriatricians feel that clinically, full-blown FS marks a precipitousdecline, fromwhich the overall health of many older adults deteriorateswith decreasing likelihood of recovery. That view of FS is compatiblewith, and has been shaped in the literature by, Fried, Walston and co-workers (Fried et al., 2001; Walston et al., 2005, 2006). It remains tobe established whether there is a specific molecular and cellular sub-strate underlying this phenotype, distinct from the most exaggeratedmanifestations of “normal” aging. By contrast to that, the Rockwoodindex (Rockwood et al., 2007; Searle et al., 2008) is aimed at a morethorough evaluation of a sum of deficits with aging, which is supposedto be a measure of biological age of the individual. The Rockwoodindex does not make a prediction of an underlying pathophysiologicalsubstrate/molecular/cellular defect and there are few studies investigat-ing possible existence of such a substrate. Most importantly, very fewstudies have compared in a cohort of older adults physiological param-eters and measures as they relate to the Fried and Rockwood tools.

As is obvious from the above discussion, this review primarilyapproaches frailty as a series of symptoms that finally (but not inevita-bly) leads to FS, in concert with the Fried approach. In that context, eachof themeasures of frailty (see below) fall on a continuum, from resilient,and average to prefrail to frail, with the final step being diagnosed as FS.However, we feel that improvements in definition of FS and of loss of

function as stipulated by Rockwood (Rockwood et al., 2007; Searle etal., 2008; Rockwood and Mitnintski, 2007.) can and should be madewith regard to objective metrics, and that these should be broadenedto include the use of biosensors and to be applicable to animal models,as discussed below.

Specifically, while several diagnostic tools have been developed andmay be used to measure FS-associated parameters, none can integratethe large spectrum of factors involved in a clinimetrically efficientmanner. An agreement upon an international common definition isneeded for use in screening, management and rehabilitation of olderpersons (Berrut et al., 2013). In addition to clinical use, a sensitive,specific and objective measure for identification of clinical FS is neededfor use in research, and policy planning (Sternberg et al., 2011).Clinimetrically sensitive measures of FS, that also respond to changein frailty status, are required to better understand the underlyingpathophysiology of frailty but also as outcome indicators for targetedintervention on FS individuals. Our state of fundamental cellular andmolecular understanding of FS (more appropriately a lack thereof)also greatly suffers from a dearth of animal models, which are urgentlyneeded to rapidly unpack etiologic factors and to test interventions. Theobjective of this review is to discuss basic biology theories and presentthe human and animal measures of FS, and to propose development ofobjective cross-species correlates to aid in the understanding, diagnosis,treatment and rehabilitation of FS in older adults. Other recent frailtyreviews have assessed the psychometric properties and clinical andresearch utility of frailty measures (de Vries et al., 2011; Farringtonet al., 2012; Gary, 2012; Lacas and Rockwood, 2012; Pal et al., 2010;Rockwood et al., 2000; Sternberg et al., 2011; Studenski et al., 2004;Wang et al., 2013; Zaslavsky et al., 2012). These issues are beyond thescope of this review.

2. Basic cellular and molecular biology of frailty/FS,or the “unknown unknowns”

There is very little solid evidence to explain how FS occurs at thelevel of molecules, cells and tissues and to decisively establish thatit is a molecularly distinct syndrome. The expanding number of report-ed biomarkers associated with FS include, but are not limited to, solublemediators of the inflammatory response including elevated cytokinesand chemokines reduced IGF-I, DHEAS and leptin, hormones,fibrin turnover and fibrinolysis, free radicals, antioxidants, macro- andmicro-nutrients (De Martinis et al., 2006; Leng et al., 2002; Paganelliet al., 2006; Qu et al., 2009).; and conflicting reports of irregular neutro-phil, monocyte, and white blood cell levels (Leng et al., 2007, 2009).These findings implicate a multisystem dysregulation in frailty(Fedarko, 2011) yet true causality remains unknown. At this time,there are two dominant and not mutually exclusive hypotheses,centering on cytokine dysregulation and mitochondrial/energeticdysfunction. We will consider these two theories separately, and willalso discuss other possibilities in the etiology of FS.

2.1. Cytokine dysregulation as a potential FS mechanism

This hypothesis stands upon the observation that most FS subjectsexhibit marked increase in pro-inflammatory cytokines, most remark-ably in IL-6 and C-reactive protein (CRP) (Leng et al., 2007; Walstonet al., 2002). There is less definitive data on other inflammatorymarkers,including IL-8, IFNγ and TNFα. Importantly, in FS, increased IL-6 levelshave been strongly predictive of increased odds of weight loss, infectionand sarcopenia. IL-6 also has potential to aggravate anemia and disruptiron metabolism (rev. in Espinoza and Walston, 2005).

A recent study fromScotland confirmed the association of IL-6, TNFαand CRP with frailty in a large cross-sectional cohort that included 845subjects N85 y of age (Collerton et al., 2012). Importantly in mice, thistheory has been tested in a germline knockout of IL-10 (Walston et al.,2008). In this mouse, lack of IL-10 results in derepression of the master

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transcription factor NF-kB, which controls expression of a number ofproinflammatory cytokines, including IL-6. Thus, the absence of IL-10,which acts largely in an antiinflammatory manner, was age-associatedwith severalmanifestations analogous to human FS, namely sarcopenia,muscle strength (grip) decline, weight loss, and an increase in proin-flammatory cytokines, including IL-6, which became more pronouncedwith age (Walston et al., 2008). Strengths of this study included the firstever characterization of a mouse model that approximates human FS.However, in this model, deregulated inflammation occurs potentiallyas early as in utero, which is very different in the onset, extent andscale compared to the aging-related human situation. Moreover, thedysregulation is systemic and pleiotropic, involving not only IL-6 butmany other cytokines. At present, it is entirely unclear what may becausing elevated proinflammatory cytokines in some, but not all,individuals that have the propensity to FS. As IL-6 is copiously producedin the gut, alterations of gut flora, or in gut wall permeability, or inregulation of IL-6 production in the gut, would all be candidates forprimary changes. Another possible source or potentiating factor of dys-regulated inflammation could be cytomegalovirus (CMV), a ubiquitousbeta-herpes virus associated with a number of age-related manifesta-tions of immune aging (Nikolich-Žugich, 2008) and other adverseoutcomes in the old age, particularly the cardiovascular diseases(Solana et al., 2012). This virus was linked to increased inflammation(Schmaltz et al., 2004) and increased cardiovascular mortality in FSwomen (Wang et al., 2010), and one hypothesis, that remains to betested, is that CMV reactivation over the lifespan would contribute tobouts of inflammation, potentiating the underlying pathogenesis of FS.

However, other sources of proinflammatory cytokines all need to beconsidered, including, but not limited to: 1) the adipose tissue, especiallyin those with sarcopenic adiposity (Grant et al., 2013), with an unclearrole of lipodystrophy seen in FS, 2) the aging immune systemwith an in-crease in cytokine producing T cellswith low activation/trigger threshold(Nikolich-Žugich, 2008), 3) the dysregulated activation of the NLRP3inflammasome (Youm et al., 2013) (sterile inflammation), and 4)chronic disease states and sub-acute disease states that have the poten-tial to increase production of pro-inflammatory cytokines, (Ferrucciet al., 2004a; Maggio et al., 2006) which could very well operate viathemechanismunder #3 above. Below,we discuss some of the possiblesteps in buildingmousemodels tomore conclusively test this and otherhypotheses of FS molecular substrate.

2.2. Mitochondrial/energy dysregulation

Mitochondria are integral to the energy dynamics and influencemetabolism (Wallace, 1999). Mitochondria dictate the dynamics of cel-lular metabolism, apoptosis, and reactive oxygen species production(Wallace, 1999), which could further influence functional decline andvulnerability to disease. Mitochondrial genetic variationmay contributeto increased susceptibility to FS (Moore et al., 2010). Moreover, alteredglucose–insulin dynamics are associated with FS (Kalyani et al., 2012).Compared to non-frail older adults, FS subjects express lower levels ofseveral hormones including DHEAS, IGF-1, and the orexigenic hormoneghrelin (Fried et al., 2001), all of which critically dictate or modulatecellular metabolism and mitochondrial function. These changes clearlycan also impair function of muscles and other tissues, disturb energyflow and introduce other adverse outcomes.

2.3. Sarcopenia/apoptosis

Sarcopenia, the age-related loss of muscle mass and function, isbelieved to be caused by two synergistic factors: apoptotic loss ofmuscle cells and/or myonuclei (Marzetti and Leeuwenburgh, 2006)and lack of renewal from muscle stem cells–satellite cells (Nikolicet al., 2005), although the latest results from Charlotte Peterson andcolleagues (Lee et al., 2013) may question this latter belief. Increasedextrinsic and intrinsic apoptotic pathway signaling in skeletal myocytes

occurs with aging, and downregulated myocyte apoptosis is evidentwith calorie restriction, exercise training, hormonal supplementation,and specific drugs, and is linked with preservation of muscle integrityand improved physical function (Walston, 2012). Of interest, in thestudy of the frail mouse IL-10-knockout model (Walston et al., 2008),the authors performed microarray analysis of gene expression in theskeletal muscle, and found that amongst the 125 genes differentiallyexpressed between 50-week old IL-10-knockout and wild-type C57BL/6 littermates, many were related to mitochondrial metabolism andapoptosis. Those results seem to suggest that cytokine dysregulationmay be proximal tomuscle changes, and in-depth studieswill be neededto confirm this link. However, independent testing is also sorely neededto assess whether changes in muscle mitochondrial/energy metabolismor changes in actomyosin structure and function, and infiltration of adi-pocytes into muscle fibers (Manini and Clark, 2012), can cause FS-likechanges in model organisms.

2.4. Multicause basis of FS

The above mentioned changes in growth and anabolic hormonal/energy regulation and in cytokine networks are certainly not mutuallyexclusive. They could be sequential, parallel, or could quite conceivablysynergize to accelerate and pronounce FS symptoms. Indeed, in thatregard, Roubenoff et al. (2003) found that low levels IGF-1 combinedwith high cellular production of TNFα and IL-6 can synergisticallypredict increased death rates in a cohort of community-dwelling olderadults. Similarly, in a cohort of community-dwelling older females,increased levels of IL-6 and low IGF-1 correlated with increased risk ofdisability and death which was higher than either of the two measuresalone (Cappola et al., 2003), which would support synergistic action.However, blunted IGF-1 signaling is also a landmark of several nutri-tional, pharmacological or genetic interventions that extend lifespan,and possibly healthspan in model organisms (Barzilai et al., 2012;Berryman et al., 2008; Masternak et al., 2010), so one could expect itto be potentially beneficial in FS too. That, however, has not been testedso far. It will be critical to first test individual factors—cytokines andhormones/mitochondrial factors—separately before approaching theirmechanistic interaction, which is certain to occur in humans, butwhere untangling of individual components will be difficult if notimpossible.

3. Approaches to measuring frailty

There aremany approaches to themeasurement of frailty developedthat do not include direct measures of complex processes of dysregula-tion. A consensus report on frailty research design by a group of ItalianandAmerican geriatricians advocated inclusion of impairments in phys-iological domains that includemobility, balance,muscle strength,motorprocessing, cognition, nutrition, and physical activity (Ferrucci et al.,2004b). A recent systematic review also suggests that frailty could beidentified by subject's spatio-temporal parameters of gait (Schwenket al., 2013). The aim of the Frailty Operative Definition-Consensus Con-ference Project, was to reach a consensus definition of FS useful in dailypractice using a Delphi process (thirty-one international experts). Theconsensus group agreed on the value of screening for frailty, but noagreement was reached concerning a specific set of clinical/laboratorybiomarkers useful for diagnosis. (Rodriguez-Manas et al., 2013) Overall,differing syndrome definitions of FS have included differing componentsof the following: weakness, fatigue, weight loss, low levels of physicalactivity, slowed motor processing and performance, decreased balance,social withdrawal, depression, cognitive changes, and increased vulner-ability to stressors (reviewed inWalston et al., 2006).

A successful measure should be multifactorial, associated withdisability, multi-morbidity and self-rated health, and other adverse out-comes (Rockwood, 2005). Recently, Chang et al. examined whether ahigher count of inflammatory-related diseases was associated with a

Table 1Current Frailty Syndrome (FS) screening measures and associations highlighted in this review.

Human Animal

Frailty Syndrome (FS)screening tools and indices

Fried 5 broad functional areas(Fried and Walston, 2004; Fried et al., 2001);Rockwood accumulation of detriments (Rockwood and Mitnitski, 2007;Rockwood et al., 2007); Buchman et al. (Buchman et al., 2009);Gill et al. (Gill et al., 2006) Studenski et al. (Studenski et al., 2004).

Mouse 31 measure objective (Parks et al., 2012);Mouse practical clinical 31 measures(Whitehead et al., 2013)

Motor performance(gait, balance, activity)sensor-based/instrument

Gait speed, mobility (Kim et al., 2010; Najafi et al., 2009;Najafi et al., 2013; Schwenk et al., 2013; Schwenk et al., 2014)In home activity monitoring(Mohler et al., 2013)

Rotorod, grip strength (Graber et al., 2013);body mass composition (Parks et al., 2012)

Physiologic Metabolic status, pulmonary, cardiac and renal assessments(Rockwood and Mitnitski, 2007; Sundermann et al., 2011;Tang et al., 2013; Tjia et al., 2013) associations withdisease burden (Chang WWW et al., 2012),also reviewed in (Walston et al., 2006)

Metabolic status, pulmonary,cardiac and renal assessments (Whitehead et al., 2013)

Inflammatory and immunologicCellular(mitochondrial/energy dysregulation)

IL-6, CRP elevated (Leng et al., 2007);IL6, TNFα, Neutrophils increased;T cell subset and telomere changes not robust (Collerton et al., 2012);CMV+ associated with frailty (Schmaltz et al., 2004)Mitochondrial decay (Moore et al., 2010);altered glucose–insulin dynamics (Kalyani et al., 2012);hormonal dysregulation (Fried et al., 2001)

IL-10 tm/tm mouse serum(IL6, TNFα,IL1β,IFNγ, IGF-1 and KC)elevated and mortality increased (Ko et al., 2012);mitochondrial metabolism and apoptosisfrail mouse IL-10-knockout model (Walston et al., 2008)

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greater likelihood of being frail. Theywent on to identify the specific dis-ease patterns, based upon the total number of prevalent inflammatory-related diseases, which were most frequently associated with beingfrail in 70–79 yr old women (WHAS). They found six combinationswere significantly more prevalent in Frail vs. non-Frail participants:1) CKD and depressive symptoms, 2) CVD and depressive symptoms,3) CKD and anemia 4) CVD, CKD and pulmonary disease, 5) CKD,anemia,and depressive symptoms, and 6) CVD, anemia, pulmonary disease anddepressive symptoms, respectively. Of particular note is that neither RAnor DM was found within the top 10 most frequent inflammatorydisease patterns associatedwith frailty in this population. They concludethat “longitudinal ascertainment of chronic inflammatory-related dis-eases with respect to incident frailty in older adults will help establisha temporal relationship between a higher total disease count and therisk of frailty” (ChangWWWet al., 2012). Thus, taking into considerationadditional quantitative physiologic clinical measures such as renal, pul-monary as well as cardiac function into the measure would be beneficialin a screening/diagnostic tool.

Therefore, a robust measure set (which incorporates quantitativephysical measures as well as key biological parameters) would provideclinically meaningful categorical classification of an individual person(e.g., non-frail, pre-frail, frail) and should also be sensitive to changeover time (Gill et al., 2006; Studenski et al., 2004). Furthermore, sincefrailty and FS are multidimensional constructs and their operationalcomponents likely change at different rates, we would strongly suggesta continuous composite measure for examining the rate of changein frailty over time with greater precision and more power to identifyrisk factors and the adverse outcomes associated with frailty, assuggested by Buchman et al. (2009). Finally, such definition shouldalsohave animal corollaries and be relevant to animalmodeling. Relatedto that, Table 1 specifies the human and animal measures, by category,providing the current state-of-the art comparisons, which remain inthe very early developmental stages.

3.1. Common frailty screening tools

3.1.1. HumanThe Fried Frailty phenotype (Fried et al., 2001) is the most well-

known and widely used frailty screening tool (Bouillon et al., 2013),and identifies frailty as the presence of ≥three of five criteria: weightloss, exhaustion, weak grip strength, slow walking speed, and low

physical activity. Fried's model identifies frailty with sarcopenia as akey pathophysiological feature, and its strength is that it has been vali-dated as a predictor of adverse outcomes in large epidemiological stud-ies. However, it is not particularly precise: population based norms areneeded for grading of responses, and its reliance on performance-based tests limits its feasibility for medical and surgical inpatients, andthose with mobility impairment.

Rockwood et al. have taken two approaches in the Canadian Study ofHealth and Aging (CSHA) (Rockwood, 2012). Their first method countsa patient's clinical deficits (identified by means of signs, symptoms andabnormal test results), allowing grading of frailty and providing insightinto the complex problems of older adults as their deficits accumulate.Though this approach is reproducible and correlates with mortality,it is clinically unwieldy, and relies upon a full geriatric assessment.Their second approach is that of a 7-point Clinical Frailty Scale,which relies on subjective clinical judgment to interpret the resultsof history-taking and clinical examination (Rockwood et al., 2005).Reliability and sensitivity to measurement of change may beproblematic.

Buchman et al. (2009) developed a continuous composite measureof frailty based on Fried's (Fried et al., 2001) and Ferrucci's (Ferrucciet al., 2004b) four components: strength, gait, body composition, andfatigue, demonstrating sensitivity to change over time, with a 1-unitincrease in annual change in frailty associated with a fivefold risk ofmortality (Buchman et al., 2009). This approach is an improvementof the Fried Scale, but while it may be suitable for research purposes,is not easily clinically applied.

Studenski et al. developed the Clinical Global Impression of Changein Physical Frailty (CGIC-PF) instrument that includes: mobility,balance, strength, endurance, nutrition, and neuromotor performancein addition to seven consequences domains (i.e., medical complexity,healthcare utilization, appearance, self-perceived health, activitiesof daily living, emotional status, and social status) (Studenski et al.,2004). Change is scored on a 7-point scale from markedly worse tomarkedly improved. This scale is useful where outcomes are captured,but is not widely applicable. Morley et al. developed the 5-item FRAILscale (i.e., fatigue, resistance, ambulation, illnesses, and loss of weight),as a clinical screening test (Morley et al., 2012). Other less commonlyused screening tools reviewed by Pialoux et al. in a recent review ofscreening tools for frailty in primary health care include the TilburgFrailty Indicator, and the SHARE-FI (Pialoux et al., 2012).

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3.1.2. Common frailty tools: animalRecently, important results were published by Howllet, Rockwood

and coworkers (Parks et al., 2012; Whitehead et al., 2013), for thefirst time establishing Frailty tools in laboratorymicewhichwere other-wise unmanipulated (no geneticmanipulations). Parks et al. initially de-veloped a quantitative objective physiologic 31 parameter frailtyscreening tool covering the following four categories: activity, hemody-namic measures, body composition (measured using dual energy X-rayabsorptiometry) and basic metabolic state (Parks et al., 2012). These pa-rameters were subsequently reduced to an eight item tool representingfive underlying factors: activity, cardiovascular function, respiration,animal weight, and bone mass density/body mineral content (Parkset al., 2012). Whitehead et al. followed up on this report by creating apractical non-invasive clinical frailty index also consisting of 31measuresto quantify frailty in mice (Whitehead et al., 2013). This tool is based onseven clinical systems/categories (Integument, Physical/Musculoskeletal,Vestibulo-cochlear/Auditory, Ocular/Nasal, Digestive/Urogenital,Respiratory, Discomfort) reflecting overall activity levels and systemsbased detriment accumulation, plus temperature and weight. The ad-vantage of this tool is that it could be adapted for rapid (4min) longitu-dinal assessment of individual mice in a cage, by processing a mouse inabout 4 min (Whitehead et al., 2013) and by collecting all 31 measuresrequiring telemetry only. As this instrument is very new to the field,we have no information at the present as to whether a state analogousto FS actually spontaneously develops in a subset of aged mice. Suchlongitudinal studies on a larger number of animals will be of criticalimportance.

3.2. Physical performance measures

3.2.1. Physical performance measures: humanThe European, Canadian and American Geriatric Advisory Panel

(GAP) recommended gait speed as the most suitable instrument to beimplemented both in clinical and research evaluation of older adults,as a quick, inexpensive and highly reliable measure of frailty. Gaitspeed at usual pace over 4 m was the most often used method inliterature, and it was found to be a consistent risk factor for disability,cognitive impairment, institutionalization, falls, and/or mortality (vanKan et al., 2009). It is measured as time required to travel over a givendistance. One issue with it remains the ability of subjects to mimictheir “usual pace”. For instance, Najafi et al. (2009) demonstrated thatgait speed in older adults is highly dependent on walking distance. Intheir study, they examined gait velocity of 27 older adults over a dis-tance of 10mand20manddemonstrated that gait speed is significantlyincreased in average by 5.2% by asking participants to walk a 20 mwalking distance instead of 10 m. This suggests that a standardizationprotocol is required for assessing walking speed in older adults foridentification of facility. Despite this limitation, gait speed remains avery useful measure to identify frailty (Schwenk et al., 2014). Gripstrength measured by a dynamometer is measured commonly threetimes on each hand, and has been found to be a robust objective mea-sure. Sit-to-stand time has likewise been proven a sensitive measureof frailty; however it is less sensitive to differentiate FS than gait assess-ments (Kim et al., 2010). Finally, a recent study (Mohler et al., 2013)suggests that monitoring spontaneous daily physical activity couldbe sensitive to identify frailty. Specifically, duration of standing andwalking as percentage of 24 h as well as number and duration ofwalking bout during 24 h are sensitive parameters to identify frailty(Mohler et al., 2013).

3.2.2. Physical performance measures: animalIn the assessment of the IL-10 knockout mouse, Walston et al.

(2008) measured grip strength using a meter with a sensor range,travelling time in the cage, standing/rearing behavior, laboratoryinflammatory markers (IL-6, IFNγ, etc.). Other measures of physicalactivity used included swimming, climbing and maze tests, as well

as cage activity, all measured mostly in the rat (Carter et al., 2002).They were not applied to frail animal models but clearly could be ofuse in such situations.

3.3. Sensor-based measures

3.3.1. Sensor-based measures: humanNew technologies for motion assessment are emerging and have

provided new avenues for objectively measuring motor functionsincluding gait, balance, and physical activities characteristics in homeand clinic (Aminian and Najafi, 2004; Najafi et al., 2012). Wearable sen-sor technology based on inertial sensors such as accelerometers offers apractical and low cost method of objectively monitoring human move-ments, and has particular applicability to themonitoring of FS.Wearablesensors have been used to monitor a range of different movements, in-cluding gait, sit to stand transfers, postural sway, and physical activities(e.g. duration of sitting, standing, lying, and walking) (Aminian andNajafi, 2004; Najafi et al., 2012, 2013). However, these parameters,beyond speed, have received insufficient attention in frailty research(Schwenk et al., 2014). A recent review by Schwenk et al. shows gaitspeed has the highest effect size to discriminate between frailty sub-groups, in particular during habitual walking (Schwenk et al., 2014).They reported that gait variability, which might reflect multisystemchange, could also discriminate between categories especially duringfast walking. Other useful parameters were reduced cadence, increasedstep width variability, reduced step length during habitual walking andincreased double support during fast walking. Dual-task walking speedcould predict prospective frailty development, thus a demanding tasksuch as fast walking or a cognitive distractor might enhance the sensi-tivity and specificity of frailty risk prediction and classification, and isrecommended for frailty assessment using gait analysis (Schwenket al., 2014). A recent study byMohler et al. (2013) suggested that spon-taneous daily physical activity usingwearable sensors could be sensitiveto identify frailty categories. In their study, the 24 hour physical activityof 20 older adults was monitored using a single wearable sensor inte-grated into a comfortable shirt. They demonstrated that severalmeasur-able parameters allowed between-group discrimination (i.e., betweenfrail, pre-frail, and non-frail.) Specifically, duration of standing andwalking, as well as number and duration of walking episodes per day,were sensitive parameters to identify FS (Mohler et al., 2013). Finally,sit to stand parameters such as velocity peaks, impulse, and orientationrange have been shown to accurately differentiate frailty levels (Kimet al., 2010; Millor et al., 2013).

3.3.2. Sensor-based measures: animalGraber et al. recently developed a neuromuscular healthspan

scoring system in C57BL/6 mice (Graber et al., 2013). Male C57BL/6mice grouped in age groups 6–7mo, 24–26moand N28mowere placedin ROTOROD test and the grip strength test. By both tests, theauthors found negative correlation with age and performance. Rotorodperformance was statistically different between adult and old, and be-tween adult and elderly (N28 mo), but not between old (24–26 mo)and elderly. Finally, EDL peak tetanic force (whole muscle physiology-instrumentation; Dula bath physiology system: Aurora Scientific,Aurora Ontario, Canada) was employed and found not to correlate orto correlate only weakly with the other measurements. Nonetheless,all three sensor-based measurements provided an informative tool ofneuromuscular function (Graber et al., 2013).

3.4. Inflammatory/immunologic measures

3.4.1. Inflammatory/immunologic measures: humanWithin the Newcastle cohort 85+ (n= 845), Collerton et al. (2012)

tested a large spectrum of parameters related to cellular senescence,immune measures and inflammatory markers, and correlated themto both Fried and Rockwood tools. In plasma/serum, they have

11M.J. Mohler et al. / Experimental Gerontology 54 (2014) 6–13

measured CRP (elevated), isoprostanes iPF2a-III and iPF2a-VI (elevated)and albumin (low), but did not assess circulating IL6 or TNFα. Withregard to blood cells, lymphocytes were decreased and neutrophilselevated in frail as defined by both Fried and Rockwood; total whiteblood cell count was elevated in frail defined by Rockwood index. Thisgroup further analyzed peripheral blood mononuclear cells (PBMC)stimulated or not with LPS and measured supernatant IL6 and TNFα,which were increased in the Frail (Collerton et al., 2012). They furtherphenotyped PBMC for B and T cells, and defined memory cells asCD45RO+/CD27− and naïve as CD45RO−/CD27+; surprisingly, theyfound that increased memory/naïve CD8 T cell ratio correlated withlower Risk of Frailty by Fried but not Rockwood; also surprisingly, lowmemory/naïve B cell ratio correlated with more FRAIL (RockwoodIndex) (Collerton et al., 2012). This group did not evaluate activationstatus or function of either T cells or monocytes, or the numbers orphenotype of NK cells. Finally, in unseparated PBMC, they found thatneither telomere length nor DNA damage and repair correlated withfrailty (Collerton et al., 2012). A known risk in assessing unseparatedPBMC is that populations and subpopulations within different cellularcompartments change with aging, and controlling for such changes iscritical to correct interpretation of data. Nonetheless, these findingsprovide interesting initial data, particularly valuable because the authorsdirectly compared Fried and Rockwood indices in a single study.

3.4.2. Inflammatory/immunologic measures: animalMost of these measures come from the genetically modified IL10tm/

tm animals (Walston et al., 2008), studied at different times over thelifespan (Ko et al., 2012). Compared to control wild-type animals IGF-1 difference was found only at 48 weeks, and it resolved by 72 weeks;serum levels of IL-6, IFNγ and chemokine ligand KC were elevated at12, 48 and 90 weeks. Likewise, serum levels of IL-1β were elevated at24, 48, 72 and 90, and of serum TNFα at both 24 and 48 weeks (onlytime points tested) (Ko et al., 2012). In this model, cellular sources ofthementioned cytokines were not investigated, which is one of the pri-orities for the future. Mortality was significantly higher in the knockoutanimals.

4. Conclusions and recommendations: towards the“known knowns”

FS is affecting nearly a third of older adults over 90, and is of anincreasing socioeconomic importance. It is very clear from the abovediscussion that we have preciously few animal or tissue culture modelsto distinguish between the current mechanistic hypotheses of frailtyand that we are not particularly good at measuring it precisely andobjectively in humans. To further our basic understanding of frailty/FSand to improve diagnostics and management of this condition, wepropose the following action items:

1. Animal frailty models are required to tease out cross-species frailtycorrelates, to better understand the underlying pathophysiology offrailty and to build interventions for frail elders.

2. An agreement with an international common definition of frailtyis needed for use in screening, management and rehabilitation ofolder persons. In addition to clinical use, a sensitive and specificmeasure for identification of clinical FS is needed for use in researchand policy planning.

3. Objective remote sensor supported, clinimetrically sensitivemeasures of Frailty Syndrome are required to better understandthe underlying pathophysiology of FS, which are sensitive tochange in frailty status, and as outcome indicators for targetedintervention of frail individuals.

4. Gait characteristics in people with frailty are insufficiently analyzedin the literature and represent a major area for innovation. Gaitparameters beyond speed, such as gait variability and dual taskwalking, could be helpful in identifying different categories of frailty

and might enhance the sensitivity and specificity of frailty riskprediction and classification.

5. Monitoring of daily physical activities using wearable sensorstechnology or other home based monitoring technology, may offera sensitive tool to identify and track change in frailty status.

6. Mechanistic studies are urgently needed to address the hypothesisthat dysregulated inflammatory cascades cause frailty and FS. Thesestudies should begin with high-throughput, unbiased “omics”approaches testing cellular stress responses (cellular resilience andfrailty) on samples from non-frail, pre-frail and frail human subjectsto generate and validate the initial specific hypotheses and should befollowed by hypothesis testing in genetically engineered animalmodels to mechanistically dissect the foundation of frailty/FS.

7. Next, other candidate root causes of FS could be addressed using asimilar strategic approach as in #6. Muscle and plasma/serumcould be initially examined, to ensure that we are not missing themain potential producers and targets, and they should be connectedto both Fried and Rockwood indices to test their relationship tomolecular profiles. Blood cells from these subjects should bepreserved and used for both confirmatory and more mechanisticanalysis of the potential cellular sources of dysregulated cytokines(note that the muscle could be merely a target that producesthe most debilitating symptoms).

8. Finally, animal studieswould have to be related to human longitudinalcohorts, and modeled to mimic other aspects of human complexity,such as deliberate exposure to infection and stress, may haveto be added to this approach. Regardless of these potential com-plicating issues, animal longitudinal studies would have signifi-cant and considerable value in that context.

Conflict of interest

The authors have no conflicts of interests.

Funding source

This review has been generously funded by the Arizona Center onAging and in part from the NIH ADB Contract HHSN 272201100017C(NIH/NIAID N01-AI 00017) and the Bowman Endowed Professorshipin Medical Research (both to J.N-Z).

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