J. Muscedere¹, P.M. Kim², J. Afilalo³, C. Balion⁴, V.E. Baracos⁵, D. Bowdish⁶, M. Cesari⁷, J. D. Erusalimsky⁸, T. Fülöp⁹, G. Heckman¹⁰, S.e. Howlett¹¹, R.G. Khadaroo¹², J.L. Kirkland¹³, L. Rodriguez Mañas¹⁴, E. Marzetti¹⁵, G. Paré⁴, P. Raina16, K. Rockwood¹⁷, A. Sinclair¹⁸, C. Skappak¹⁹, C. Verschoor¹⁶, S. Walter²⁰ for the Canadian Frailty Network

1. Department of Critical Care Medicine, Queen’s University; 2. Canadian Frailty Network, Kingston, ON, Canada; 3. Division of Cardiology and Centre for Clinical Epidemiology, Jewish General Hospital, McGill University; 4. Department of Pathology and Molecular Medicine, McMaster University; 5. Department of Oncology, University of Alberta; 6. Department of Pathology and Molecular Medicine, Master University; 7. Department of Clinical Sciences and Community Health, Università di Milano; and Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy; 8. Department of Biomedical Sciences, Cardiff Metropolitan University, Cardiff, UK; 9 Research Center on Aging, University of Sherbrooke, Québec, Canada; 10. School of Public Health and Health Systems, Schlegel University of Waterloo Research Institute for Aging, University of Waterloo; 11. Departments of Pharmacology and Medicine (Geriatric Medicine), Faculty of Medicine, Dalhousie University; 12. Department of Surgery and Critical Care Medicine, University of Alberta; 13. Robert and Arlene Kogod Center on Aging, Mayo Clinic; 14. Department of Geriatrics, Hospital Universitario de Getafe, Madrid; 15. Fondazione Policlinico Universitario «Agostino Gemelli» IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy; 16. Department of Health Research Methods, Evaluation and Impact, McMaster University; 17. Division of Geriatric Medicine, Dalhousie University; 18. Foundation for Diabetes Research in Older People at Diabetes Frail Ltd; 19. Schwartz/Reisman Emergency Medicine Institute, Mount Sinai Hospital, University of Toronto, and the Division of Emergency Medicine, McMaster University; 20. Fundación de Investigación Biomédica Hospital Universitario de Getafe, Getafe, Spain. Dept. of Epidemiology and Biostatistics, University of California San Francisco, California, United States of America.
Corresponding author: Dr. John Muscedere, Kingston Health Sciences Centre, 76 Stuart Street, Kingston, Ontario, Canada, Email: john.muscedere@kingstonhsc.ca
J Frailty Aging 2019;in press
Published online April 30, 2019, http://dx.doi.org/10.14283/jfa.2019.12

Abstract

The Canadian Frailty Network (CFN), a pan-Canadian not-for-profit organization funded by the Government of Canada through the Networks of Centres of Excellence Program, is dedicated to improving the care of older Canadians living with frailty. The CFN has partnered with the Canadian Longitudinal Study on Aging (CLSA) to measure potential frailty biomarkers in biological samples (whole blood, plasma, urine) collected in over 30,000 CLSA participants.  CFN hosted a workshop in Toronto on January 15 2018, bringing together experts in the field of biomarkers, aging and frailty. The overall objectives of the workshop were to start building a consensus on potential frailty biomarker domains and identify specific frailty biomarkers to be measured in the CLSA biological samples. The workshop was structured with presentations in the morning to frame the discussions for the afternoon session, which was organized as a free-flowing discussion to benefit from the expertise of the participants. Participants and speakers were from Canada, Italy, Spain, United Kingdom and the United States.   Herein we provide pertinent background information, a summary of all the presentations with key figures and tables, and the distillation of the discussions.  In addition, moving forward, the principles CFN will use to approach frailty biomarker research and development are outlined.  Findings from the workshop are helping CFN and CLSA plan and conduct the analysis of biomarkers in the CLSA samples and which will inform a follow-up data access competition.

Key words: CFN, CLSA, frailty, frailty index, seniors, older adults, biomarkers, aging.

Introduction

Older adults living with frailty represent an increasing concern for health systems due to increased vulnerability to acute stressors, increased risk of functional impairment, increased healthcare utilization including emergency department visits, hospitalizations, and increased mortality (1-4). Therefore, it is critically important to identify, as early as possible, those at imminent risk of frailty and those living with frailty. In addition, there is a need to be able to assess the severity of frailty as objectively as possible for both prognostic purposes and monitoring of response to therapeutic interventions.
There are two main views of frailty; as a syndrome or as a state arising from an accumulation of deficits. Considerable progress and increased understanding of both approaches has occurred since their introduction (5). Frailty as a phenotype can be measured by Fried or Bergman phenotype criteria (1, 6). This model derives from an attempt to characterize the clinical manifestations of vulnerability outside of multimorbidity and disability. Frailty as an accumulation of deficits can be measured by the Frailty Index (FI), which is the number of physiological deficits affecting an individual divided by the total number of deficits measured (7, 8). The theoretical underpinning for the deficit model arises from the observation that deficits increase variably with age in humans and in animals and that the risk of morbidity, functional decline and death increases with an increasing number of deficits both individually and on a population basis (9, 10).
Although the concept of frailty is widely accepted, how to best detect and measure the severity of frailty remains controversial and as a consequence, there are many clinical frailty assessment instruments utilized in practice and research (11-13). Shortcomings of current instruments include the requirement for relatively large amounts of data, the use of specialized procedures, subjective assessments and the lack of responsiveness to therapeutic interventions (14-16). Frailty biomarkers have the potential to complement the clinical evaluation of frailty including aiding in its diagnosis, assessment of severity, and evaluation of prognosis (17, 18). Although clinical frailty assessment instruments may be more effective from a population-based approach, whereas frailty biomarkers, may be able to individualize diagnosis/prognosis and personalize care by determining an individual’s biological frailty profile.
The utility of biomarkers has been demonstrated in the diagnosis of some cancers and other disorders (19-21), and to assess treatment responses and disease progression in various diseases (22, 23). In addition, biomarkers offer the promise of precision medicine where a person’s care and treatment is based on one’s genetics and biology and there is a need to extend and explore this promise to the challenges posed by frailty.
A promising venue to study frailty biomarkers are longitudinal research initiatives that collect clinical data on aging in large numbers of participants coupled with biological samples. The Canadian Longitudinal Study on Aging (CLSA) (www.clsa-elcv.ca/) which studies the aging process in over 50,000 Canadians is one of the largest and most comprehensive initiatives in the world. Selected participants undergo comprehensive clinical evaluations including frailty assessments supplemented with hand grip-strength, timed up-and-go, chair rise, 4-metre walk and standing balance. Using a FI of 90 possible health deficits with 0.25 as the threshold for frailty, approximately 7% of CLSA participants are frail, increasing to approximately 11% in those over the age of 75 (24). Biological specimens are collected in a selected cohort every three years including whole blood, serum, plasma and buffy coat containing peripheral blood mononuclear cells (Table 1).  For a biomarker to be considered for inclusion in the CLSA, it needs to have at least preliminary evidence to link the biomarker to a pathophysiological frailty pathway or mechanism.
Here we report the proceedings of a symposium convened by the Canadian Frailty Network (CFN) (www.cfn-nce.ca) in collaboration with the CLSA. The overall objective of this meeting was to inform future efforts of CFN to improve the availability of frailty biomarkers and to guide further CFN funded analyses of biological samples held by the CLSA. Specific objectives of the symposium were to:
1.    Explore the current state of evidence of biomarkers for frailty.
2.    Obtain an understanding of other frailty biomarker initiatives around the world.
3.    Obtain guidance on biomarkers that could be measured in the CLSA biological samples, in addition to those already being assayed, to identify the biological, biochemical and genetic factors/markers associated with the onset and progression of frailty in order to develop predictive, prognostic and diagnostic tests to aid in the care and treatment of people living with frailty.

Table 1
Biomarkers currently being analysed in the CLSA samples

Workshop details

The workshop was held in Toronto, Canada on January 15th 2018. Participants for the workshop were international stakeholders, key opinion leaders and frailty and/or biomarker experts.  They were identified using one or more of the following criteria: they were leading large scale initiatives involving frailty and the measurement of biomarkers, they were investigators on CFN-funded research grants studying frailty and measuring biomarkers, they had published peer-reviewed studies on frailty and related biomarkers, were clinicians caring for older adults living with frailty and/or were in relevant decision-making roles. The twenty-two delegate attendees included basic researchers (e.g., biochemist, pharmacologist, immunologist), clinician researchers (e.g., intensivist, geriatrician, cardiologist) and health-care administrators/policy experts.

The current state of frailty biomarkers and frailty assessment

Multiple clinical frailty assessment instruments exist, each with advantages and disadvantages and it is not clear which instrument is optimal for a particular care setting (15). In addition, due to variability in their measurement characteristics, the prevalence of frailty depends on the instrument utilized (25, 26). This variability together with the subjective nature of some frailty assessments have generated increasing interest in integrating clinical assessments with objective laboratory-based biomarker tests.   The working definition for this discussion was that a biomarker is, “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.” (NIH working group) (27). Some potential uses of biomarkers conceived by the 2001 NIH working group are listed in Table 2.

Table 2
Potential utility of biomarkers

Biomarkers may lead to the identification of mechanisms and pathophysiological pathways leading to or causing frailty, and the early identification of frailty which, importantly, may be reversible in early stages (28, 29). In addition, identification and modification of treatment plans in those identified as frail may ameliorate poor outcomes from healthcare interventions (30-32). Lastly biomarkers may help with selecting interventions, monitor response to treatments, and identify those for whom some interventions are unlikely to be of benefit.
Although no single biomarker has yet proven to be of sufficient diagnostic or prognostic utility to be clinically useful for frailty, there has been increasing work on integrating laboratory evaluation in the assessment of frailty (33). As an example, a FI composed of laboratory results has been developed and shown to be effective in identifying frailty in individuals living in the community and those in long-term care facilities (17). This index of biomarkers (the FI-Lab) predicts increased risk of death in community-dwelling and institutionalized individuals and it can be combined with a clinical FI to improve prediction of outcomes in older adults (17, 18, 34-36).
A recent systematic review of frailty biomarker studies in community-dwelling individuals of trials using a validated definition of frailty and comparing two or more biomarkers was recently reported (33). Biomarkers related to immune function, inflammation, endocrine function and metabolic syndrome were the most frequently reported. There have been conflicting results regarding the utility of single biomarkers for the detection and assessment of frailty. Associations with frailty have been shown for inflammatory markers (e.g., interleukin-6 (IL-6), Tumor necrosis factor-alpha (TNF-alpha), C-reactive protein (CRP)), reduced total lymphocyte count and other markers of immunocompetence, although this has not been observed with some markers that have been associated with aging such as telomere length and oxidative stress, when studied individually (37). Other systematic reviews have come to the same conclusion. The variety of biomarkers reported in recent systematic reviews are summarized in Table 3 (33, 38-40).

Table 3
Summary of biomarkers examined in prior studies

Specific Frailty Biomarker Considerations

Frailty Index (FI) approach to biomarkers

Consistent with the deficit accumulation approach, Mitnitski et al. (18) re-analysed the data in Collerton et al. (37) to create an FI composed of 40 biomarkers of cellular ageing, inflammation and haematology. Like the FI-Lab, this suggests that currently available single biomarkers have relatively low information value by themselves when compared to a combination of multiple markers and an FI approach with a panel of biomarkers may be a more promising avenue of investigation, and more closely correspond to how deficits propagate to give rise to frailty (41, 42).
The deficit accumulation approach has been validated in animal models of frailty, where both laboratory-based and clinical FI tools have been developed and behave similarly as in humans (9, 43-45). Animal studies also indicate that levels of pro-inflammatory cytokines increase in proportion to FI scores (45). Further studies suggest that mechanisms that give rise to frailty are present at the cellular/subcellular levels and scale up to impact function at the level of the organ and ultimately the organism (46, 47). The availability of animal models of frailty with biomarker and clinical criteria has led to the study of possible interventions for frailty in pre-clinical models using resveratrol, caloric restriction and an angiotensin converting enzyme inhibitor (48, 49). All this is consistent with the multifactorial nature of frailty, thus requiring the evaluation of a biological network (and not a standalone biomarker) for adequately capturing the complexity of the state.
In conclusion, measuring a larger set of biomarkers (e.g., 40) is likely to be better than measuring a smaller set. Given current evidence, inflammatory markers should be included in any frailty biomarker panel as should measures of metabolism (large panel metabolomics) and other measures related to aging processes (e.g., telomere length, oxidative stress, DNA damage and repair).  Following a standard procedure for creating a FI from clinical data, for a biomarker to be included as a deficit in a FI, the biomarker should have the following characteristics, as outlined by Searle et al. (8):
•    Abnormal biomarker levels should be associated with a negative health-related outcome.
•    The risk associated with abnormal levels of the biomarker should be higher as age increases.
•    The biomarker should be neither too rare (i.e., < 1%) nor too common (i.e., > 80% by age 80).
•    Biomarker data should be available for at least 80% of individuals.

Frailty and skeletal muscle

Muscle mass, has for the most part, been neglected in frailty assessment instruments, perhaps because there are no good practical tools to measure it.  Most current methods are crude (e.g., calipers, body mass index), complex or difficult to use or access (e.g., magnetic resonance imaging). Computerized tomography (CT) scans are of increasing promise due to their availability and growing evidence indicates that muscle mass seen on CT scans, as evidenced by psoas muscle area, correlates with outcomes including mortality (50-52). In particular, muscle mass analysis can be an important measure for frailty assessment in patients who are already undergoing CT scans for other medical reasons and can be of added prognostic value to other biochemical biomarkers/tests. Although CTs are of potential utility, further research is required before they can be recommended for routine clinical use. Bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DEXA) are also commonly used for the assessment of muscle mass but their availability are limited and their ability to guide clinical practice requires further evaluation (53, 54). Overall, skeletal muscle assessment should be tailored to the objectives desired and the availability of the diagnostic test. Also different tests may be required for different care settings (55).

Anemia and hypoalbuminemia

Anemia has been shown to increase rapidly with age and is associated with adverse geriatric outcomes such as disability, reduced physical function, cognitive dysfunction and dementia (56, 57). The presence of anemia is also associated with an increased likelihood of frailty (58). It is unknown whether this is due to reduced oxygen delivery, resulting in inactivity and fatigue, or if anemia is the result of other conditions linked to frailty, including chronic inflammation and/or malnutrition. In addition, it is unknown if the successful treatment of anemia can reverse or attenuate frailty?
Reduced serum albumin has been associated with disability and mortality (59). While hypoalbuminemia was previously thought to be a marker of malnutrition, it is now known that it is more likely due to systemic inflammation (60). The incorporation of albumin and anemia into clinical frailty criteria has been shown to be predictive of death and worsening disability in selected surgical populations (e.g., transcatheter aortic valve replacement) (www.frailtytool.com) (61, 62). Moreover, these two parameters are commonly measured clinically thereby increasing their availability for the assessment of frailty.

Other biomarkers

Other biomarkers such as vitamin D and androgen levels have also been linked to frailty.  A systematic review suggests that low levels of vitamin D are associated with an increase in the risk of frailty (63), although potential benefits of vitamin D supplementation on frailty requires additional evidence (64). There is no consensus in the literature with respect to the biological role of androgens in frailty. An earlier review concluded that more work needs to be done (65), although recent longitudinal studies show an association between testosterone and FI scores (66, 67). Evidence to date suggests that testosterone treatment may be beneficial in older people (68-70). However, further evidence is required before recommending that these biomarkers be incorporated into future frailty biomarker panels.

Current frailty studies and biomarker databases

Participants of this CFN sponsored workshop are leading a number of international initiatives investigating the potential utility of biomarkers for frailty assessment. These initiatives are discussed below.

Sarcopenia & Physical fRailty IN older people: multi-componenT Treatment strategies (SPRINTT); www.mysprintt.eu/en/wp

The SPRINTT project (5 years) was started in 2014 as a private/public partnership between the European Commission and the European Federation of Pharmaceutical Industries and Associations.  The overall goal of SPRINTT is to develop innovative therapeutic interventions against physical frailty and sarcopenia as a prototype geriatric indication. SPRINTT includes a definitive large phase III randomized clinical trial (RCT) (71) comparing the efficacy of a multi-component intervention in preventing mobility disability, based on long-term structured physical activity, personalised nutritional counselling/dietary intervention and an information and communication technology intervention, versus a healthy ageing lifestyle education program.  The RCT completed recruitment in November 2018 and follow-up is planned to be completed in 2019.  One of the accomplishments of SPRINTT was the operationalization of a new condition incorporating physical frailty and sarcopenia, whose methodology was endorsed by the European Medicines Agency (EMA) (72).
For each participant biological samples are collected (whole blood, serum, plasma and urine) for future analysis (Table 4).  The collection of these biospecimens has two objectives: 1) development of discriminant biomarkers that will allow for comparison of biomarker levels between physical frailty and sarcopenia (at baseline) versus physical frailty and no sarcopenia. 2) development of prognostic and predictive biomarkers for the identification of study participants at high risk for the development of mobility disability and prediction of response to the multi-component intervention.

Table 4
Candidate biomarkers being considered for SPRINTT

FRAILOMIC; www.frailomic.org

The main goal of the FRAILOMIC initiative is to develop clinical instruments composed of clinical data, laboratory biomarkers and omics-based laboratory biomarkers. Specifically, the three objectives of FRAILOMIC are to develop clinical instruments that can: 1) improve diagnostic accuracy of frailty in day-to-day practice, 2) predict the risk of frailty and 3) assess the prognosis of frailty in terms of death, disability and other adverse outcomes.  FRAILOMIC has four main phases, with the first two phases now complete, which have identified the biomarkers listed in Table 5.  Preliminary results show that biomarkers potentially useful for the diagnosis of frailty are different from those useful for assessing frailty risk and prognosis.

Table 5
Biomarkers identified in exploratory phase. Biomarkers identified according to their relationship with function, muscle and longevity. Selection of biomarkers attempted to be as inclusive as practical

Discussion

Biomarkers, definition of frailty and fit within clinical practice

Key to the selection of biomarkers for frailty assessment will be an agreed upon definition of frailty. However, coming to a consensus definition of frailty and choosing the appropriate clinical instruments have proven to be difficult.  Current frailty instruments/tools in use today, whether based on a deficit accumulation model or a phenotypic model have varied sensitivity, specificity, and positive and negative predictive values (73-76). Moreover, frailty assessment tools may perform differently in different populations and settings (11-13). Overall, it is very likely that there will be no single best reference clinical frailty assessment instrument, so to proceed with biomarker work, a single measurement paradigm will need to be selected and used consistently.
In regards to the selection of the reference paradigm, it should be connected with the underlying biology of frailty. It is generally agreed that frailty is a result of the age-associated accumulation of deficits across multiple systems and therefore the FI paradigm seems to be a reasonable starting point. The FI is consistent in different care settings, countries and species because of its basis in systems biology. In addition, the FI is multi-dimensional and allows for grading of frailty severity, which is an important determinant of outcome. One drawback to the FI is that it may be impractical as a clinical assessment tool since it requires large amounts of data, stemming from the results of a comprehensive evaluation of the individual but this is less of a disadvantage when used for research purposes as a reference standard.
Any adopted biomarker needs to pair with the clinical instrument used to better diagnose, predict risk and determine therapeutic responsiveness (77). The utility of the FI is that it can utilize readily measured clinical deficits, many of which are currently recorded and even exist in electronic health records (10). The FI can utilize readily available and routine laboratory tests, that can also be augmented with novel biomarkers. This would apply to laboratory tests such hemoglobin, albumin, estimated glomerular filtration rate, low density lipoprotein and glycosylated hemoglobin. If a combination of these perform well in a frailty assessment tool such as the FI, the utility of more complex, more difficult to measure and more expensive biomarkers would need to be demonstrated before they are adopted. Overall, to be most applicable and advance the possibility of personalized medicine for people living with frailty, it would be better to start broadly with the FI and then tailor biomarkers to the specific needs of the person.

Clinical frailty assessment instruments versus biomarker-based frailty assessment tools

Biomarkers may direct clinicians, but do not replace geriatric expertise. Any biomarker(s) chosen will need to assist clinical activities beyond what already exists, be easier to use and be more cost-effective. Biomarkers that are difficult and expensive to measure or require specialized equipment should be reserved for environments dealing with complex cases or for research purposes.  Some assessments, such as gait speed combined with grip strength, may already provide data that biomarkers promise to do (74, 75). Biomarkers will need to increase the sensitivity, specificity, negative predictive value and positive predictive value of clinical evaluations or instruments, especially for risk prediction and this will need to be demonstrated in clinical use. Also, for their adoption, it will need to be demonstrated that their utilization is associated with better outcomes.
When a clinical frailty assessment tool is used in combination with biomarkers, it is important that the biomarker(s) increase the utility of the tool as follows: 1) It allows the tool to better identify a population as truly frail than the clinical tool alone, and 2) It allows for better selection of a care plan for an individual than the clinical tool alone. To determine if a biomarker has these key characteristics, further research will be required once candidate biomarkers are identified. As an example, if a biomarker(s) identifies a nutrient deficiency, we need to know that acting on that information would improve outcomes. This will likely only be answered by doing randomized clinical trials with the ability to detect changes in patient-centered outcomes such as quality of life. Overall, the identification of frailty in a more rigorous manner, with attendant care plans, would be a major step forward.

Generally available versus novel biomarkers

Biomarkers that are only associated with a particular disease may not be of high interest when considering frailty since they are likely specific for the disease. Biomarkers more applicable to frailty are likely those that are closer to the physiology and basic biology of aging. Studies of the basic biology of aging has led to a number of new interventions targeting fundamental aging processes that have been found to impact development of age-related disorders, including many chronic diseases, geriatric syndromes and loss of resilience/loss of ability to respond to stressors in animal models (78, 79). These new interventions will need to be tested in human clinical trials. Biomarkers may be better able to characterize the populations enrolled in these trials to avoid the heterogeneity that is characteristic of frailty and aging. If successful, these interventions may be able to fundamentally change geriatric medicine, with the ultimate goal of increasing health-span and not necessarily life-span.

Need for a variety of biomarkers

An ideal biomarker would present early in the course of frailty and correlate with its severity. There are indications that different biomarkers are needed for risk stratification, diagnosis and prognosis. Overall, it is unlikely that a single biomarker can address all these objectives (80). Moreover, the utility of a diagnostic biomarker is dependent on the prevalence of the condition which in frailty are care setting dependent increasing from a small percentage of the general population to as much as 60% in hospital, and majority in long-term care (81-84). In very high prevalence environments, diagnostic frailty biomarkers may have limited utility. For prognosis, we need to be as precise as possible as to what they predict to make them useful to clinicians; risk of poor functional outcomes may be as important as mortality.

Broader versus narrower sets of biomarkers

For discovery, there may be value in adopting a biomarker approach based on metabolomic profiling, understanding that this approach might not have clinical value as yet but will help to generate a wide range of markers, which from a research perspective may have great utility. The added benefit of utilizing metabolomics on whole blood, plasma or urine is that once mass spectrometry (MS) or nuclear magnetic resonance (NMR) data are captured, these data can be reanalyzed in the future for new markers. Metabolomics has already produced results that are leading to frailty interventions, such as ketogenic compounds, for which clinical trials are about to start (85, 86). There are at least 20 proteins or peptides in mice related to frailty where preliminary human trials are being considered (87, 88). Also with newer techniques, proteins can be measured in very small quantities of sample (e.g., 10 microlitres). The caveat is that although MS and NMR are both powerful technologies with great discovery (research) potential, at this time translating their application to clinical settings is more difficult than other approaches, such as determining inflammation by measuring interleukins or acute phase CRP.
There are large studies utilizing metabolomics but no such large study exists for frailty investigation. However, this work has already commenced in the CLSA with 1,000 people having metabolomics analysis. Further metabolomics analysis within the CLSA database will be a unique opportunity to significantly add to the evidentiary base.

Conclusions

This workshop brought together experts in the field of biomarkers, aging and/or frailty to discuss frailty biomarkers. This discussion will inform CFN and CLSA in planning for the analysis of a select group of biomarkers in the CLSA samples and a follow-up data access competition to utilize these new biomarker data in conjunction with the wealth of clinical data collected by the CLSA.
There was considerable discussion regarding the appropriate way to think about frailty and how the frame of reference will influence the choice of biomarkers to analyze.  Considerations discussed included probabilistic medicine and population-based care versus precision medicine or individualized medicine and how these overall approaches should influence the use of biomarkers and their incorporation into practice and ultimately influence policy.  There was debate about care settings and biomarker utility across care settings. In addition, the overall objective of using biomarkers as diagnostic tools for frailty versus their use to quantify frailty risk versus their use as frailty prognostic tools were topics of high interest and discussion. By the end of the workshop, there was a clear sense that research and clinical trials need to be conducted regarding frailty biomarkers and the need for the development of biomarker tools to be used either alone or with currently existing clinical frailty assessment instruments such as the FI.
Arising from the meeting, the list of principles to guide future CFN biomarker initiatives including its partnership with the CLSA, are as follows:
1)    Biomarkers should reflect a pathophysiological pathway or mechanism that is fundamental to frailty onset, development/progression and severity. Conceptually there maybe two categories of biomarkers:
i)    Biomarkers that are linked with frailty but are not causal to the pathophysiology of frailty. These would not be actionable.
ii)    Biomarkers that are a component of the pathophysiology of frailty and have a causal role. These would be actionable such that the modulation of the biomarker could directly affect the onset or severity of frailty and/or progression of frailty.
2)    The utility of biomarkers can be classified into two different types:
i)    Biomarkers to increase the utility of (or support) existing clinical frailty measures (e.g., FI).
ii)    Biomarkers to be used independently of clinical frailty measures.
3)    Biomarkers should be able to be embedded in clinical assessments and tools, but more research on how to best achieve this is needed. Concomitant use of both a clinical frailty assessment instrument and biomarkers is likely to be the optimal method to bring about personalized frailty assessment and individualized care plans.
4)    Biomarkers chosen for a clinical tool should be evaluated on their ability to accomplish the ultimate clinical purpose. For instance, biomarkers used for diagnosis may be different from those used for risk assessment, which may differ from those used for prognosis.
5)    Different care settings are likely to require different biomarkers due to variation in prevalence of both frailty and biomarkers in different populations.
6)    Any candidate biomarker should be validated in different populations, care settings and environments.
7)    An ideal frailty biomarker would be able to measure the effectiveness of an intervention.
8)    Practical considerations related to ease of measurement (i.e., special instruments and/or expertise required) and ease of securing biological samples (e.g., tissue biopsy vs blood sample collection) should be considered when selecting frailty biomarkers.

Acknowledgements: The Canadian Frailty Network (CFN) is a pan-Canadian network focused on the care of older citizens living with frailty. CFN is comprised of nearly 3,500 corporate and non-profit partners, researchers, scientists, health-care professionals, citizens, students, trainees, educators, and decision-makers. CFN supports and catalyzes original research and innovations to improve the care and quality of life of Canadians living with frailty across all settings of care. The Network also trains the next generation of health-care professionals and scientists. CFN is funded by the Government of Canada through the Networks of Centres of Excellence (NCE) Program. In early 2017, in recognition of the work done in its first five years of operation, the Government of Canada announced funding for a second five-term (2017-2022).

Conflict of interest disclosures: Matteo Cesari, Emanuele Marzetti and Leocadio Rodriguez Mañas are partners of the SPRINTT consortium, which is partly funded by the European Federation of Pharmaceutical Industries and Associations (EFPIA) . Kenneth Rockwood is President and Chief Science Officer of DGI Clinical, which in the last five years has contracts with pharma and device manufacturers (Baxter, Baxalta, Shire, Hollister, Nutricia, Roche, Otsuka) on individualized outcome measurement. In 2017 he attended an advisory board meeting with Lundbeck. He is Associate Director of the Canadian Consortium on Neurodegeneration in Aging, which is funded by the Canadian Institutes of Health Research, and with additional funding from the Alzheimer Society of Canada and several other charities, as well as, in first phase (2013-2018), from Pfizer Canada and Sanofi Canada.   He receives career support from the Dalhousie Medical Research Foundation as the Kathryn Allen Weldon Professor of Alzheimer Research, and research support from the Canadian Institutes of Health Research, the Nova Scotia Health Research Foundation, the Capital Health Research Fund and the Fountain Family Innovation Fund of the Nova Scotia Health Authority Foundation.

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