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E. González-Bautista1, P. de Souto Barreto1,2, K. Virecoulon Giudici1, S. Andrieu1,2, Y. Rolland1,2, B. Vellas1,2, for the MAPT/DSA group*


1. Gerontopole of Toulouse, Institute of Aging, Toulouse University Hospital (CHU Toulouse), Toulouse, France; 2. UPS/Inserm UMR1027, University of Toulouse III, Toulouse, France; *The members are listed at the end of the manuscript.
Corresponding author: Emmanuel González-Bautista. Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), 37 Allée Jules Guesde, 31000 Toulouse, France. Mobile 06 22 10 14 96 emmanuel.scout@gmail.com

J Frailty Aging 2020;in press
Published online August 7, 2020, http://dx.doi.org/10.14283/jfa.2020.42



Background: The screening tool of the Integrated Care for Older People (ICOPE Step 1), designed to detect declines in the domains of intrinsic capacity, has been incipiently investigated in older adult populations. Objectives: To retrospectively estimate the frequency of priority conditions associated with declines in intrinsic capacity according to an adaptation of the screening tool ICOPE Step 1 among participants of the Multidomain Alzheimer Preventive Trial (MAPT). Design: A cross-sectional retrospective analysis from the baseline assessment of the MAPT. Setting: The data was gathered during a preventive consultation for cardiovascular risk factors in memory clinics in France. Participants : Seven hundred fifty-nine older adults aged 70-89 years with memory complaints, allocated to the multidomain groups of the MAPT study. Measurements: Five domains of intrinsic capacity (cognition, locomotion, nutrition, sensorial, and psychological) were assessed using a screening tool similar to the ICOPE Step 1 (MAPT Step 1). The frequency of six conditions associated with declines in intrinsic capacity (cognitive decline, limited mobility, malnutrition, visual impairment, hearing loss, and depressive symptoms) was obtained for older adults with memory complaints participating in the MAPT study. Results: Overall, 89.3% of the participants had one or more conditions associated with declines in intrinsic capacity. The overall frequency of each condition was: 52.2% for cognitive decline, 20.2% for limited mobility, 6.6% for malnutrition, 18.1% for visual impairment, 56.2% for hearing loss, and 39% for depressive symptoms. Conclusion: After being screened with an adaptation of the ICOPE step 1 (MAPT step 1) tool, 9/10 older adults had one or more conditions associated with declines in intrinsic capacity. The relative frequency differs across conditions and could probably be lower in a population without memory complaints. The frequency of screened conditions associated with declines in IC highlights how relevant it is to develop function-centered care modalities to promote healthy aging.

Key words: Intrinsic capacity, screening, physical functions, integrated care, older adults.

Abbreviations: CCHA: Clinical Consortium for Healthy Ageing; COPD: Chronic obstructive pulmonary disease; FA: Functional ability; IC: Intrinsic capacity; ICOPE: Integrated Care for Older People; MAPT: Multidomain Alzheimer Preventive Trial; NCD: Non-communicable disease; OA: Older adults; WHO: World Health Organization.



Screening for early declines of intrinsic capacity (IC) is crucial for the implementation of the Integrated Care for Older People (ICOPE)(1). The World Health Organization (WHO) Clinical Consortium for Healthy Ageing (CCHA) and other public health and aging experts developed the ICOPE guidelines. The objective of the ICOPE guidelines is to help key stakeholders in the health and social care arenas to design and implement integrated person-centered models of care (1–3).
The ICOPE approach might prevent care-dependency by timely detecting and managing conditions associated with declines in intrinsic capacity (IC). IC is the composite of all physical and mental capacities of an individual, organized in five domains: cognition, mobility, nutrition, sensorial, and psychological. The interaction between the IC and the environment determines functional ability and healthy aging (4,5). The WHO ICOPE approach has, thus, the goal of helping health systems support healthy aging (4) through the maintenance of optimal functional ability levels during aging.
The clinical care pathways proposed by the ICOPE (1) start with a screening process (ICOPE Step 1). The purpose of the screening is to detect conditions associated with declines in IC at the community level, namely cognitive decline, limited mobility, malnutrition, visual impairment, hearing loss, and depressive symptoms. People identified as having normal IC levels will receive general health advice (i.e., physical activity, nutrition). In contrast, those with IC declines will receive an in-depth assessment (ICOPE Step 2) to confirm or rule such declines. Afterward, they will follow the next steps in the care pathway (i.e., searching the causes of low IC levels, designing a person-centered care plan).
For health service providers, ICOPE Step 1 has a strategic role because it opens the door for the subsequent steps in the healthcare pathway. By managing the adequate «filter» to identify the individuals who can benefit the most from health and social interventions, the healthcare system could enhance the effective use of the available resources.
We have recently reviewed the literature on the topic (in press) and observed only ten original studies on the topic. None of those studies investigated the frequency of low levels of IC according to the screening tool. To our knowledge, measurements of conditions associated with declines in intrinsic capacity, according to ICOPE Step 1 have not been reported so far. Therefore, this study aimed to retrospectively estimate the frequency of conditions associated with declines in intrinsic capacity according to an adaptation of the screening tool ICOPE Step 1 among participants of the Multidomain Alzheimer Preventive Trial (MAPT).



This study uses cross-sectional data to describe the baseline frequency of conditions associated with IC declines among the participants of the Multidomain Alzheimer Preventive Trial (MAPT). The MAPT was not designed to assess the ICOPE screening; thus, we used a retrospective approach to define the variables of interest according to the availability of data. The detailed methodology of MAPT has been described elsewhere(6, 7). Briefly, MAPT was a 3-year randomized controlled trial on the effect of a multidomain intervention (nutritional and physical activity counseling, cognitive training, and annual preventive consultations for the management of cardiovascular risk factors and the detection of functional impairments) with and without supplementation of omega-3 polyunsaturated fatty acids (PUFA) on the prevention of cognitive decline among community-dwelling adults aged 70 years and older. The trial protocol (ClinicalTrials.gov identifier: NCT00672685) was approved by the French Ethical Committee located in Toulouse (CPP SOOM II) and was authorized by the French Health Authority. All participants signed their consent before any study assessment.


Inclusion criteria for the MAPT study were meeting at least one of three conditions: a) spontaneous memory complaint expressed to their physician, b) limitation in one instrumental activity of daily living (IADL), or c) slow gait speed (≤0.8 m/s). Exclusion criteria comprised participants with a Mini-Mental State Examination (MMSE) score < 24, diagnosis of dementia, the limitation for any of the basic activities of daily living, and those taking PUFA supplements at baseline.
The 759 subjects allocated to the multidomain intervention groups of MAPT constitute our study sample. Data on the five domains of IC was available only for them because they underwent a preventive consultation with a physician who assessed for the hearing and vision capacities. The rest of the 1,679 participants initially enrolled in MAPT were lacking data on the sensorial domain.

IC domains assessment – Step 1 (screening)

We followed the recommendations from the WHO ICOPE Handbook to operationalize the ICOPE Step 1 tool(1). To be consistent with the terms used in the Handbook, we used «cognitive decline,» «limited mobility,» «malnutrition,» «visual impairment,» «hearing loss» and «depressive symptoms» to refer to the conditions associated with declines in IC. These terms are not equivalent to clinical diagnoses.
The same items recommended by the WHO were used to evaluate three domains: cognition, locomotion, and vitality/nutrition. Nevertheless, due to data availability, we adapted the operationalization of the following conditions associated with declines in IC: visual impairment: was assessed by self-reported visual acuity items; hearing loss: was measured with item number 3 of the screening version of the hearing handicap inventory for the elderly (HHSE-S(8,9)); depressive symptoms: were defined according to items 2 and 7 of the Geriatric Depression Scale (GDS-15) (10), which were judged by three experts (one geriatrician, one general practitioner, and one researcher in clinical gerontology) as being the most similar items compared to those recommended by WHO. This resulting adapted screening tool was then called «MAPT Step 1» (Table 1).
Specifically, for hearing loss, we used the validated HHIE-S(8) because studies have validated this instrument against pure tone audiometry. Sindhusake et al. (11) concluded that HHIE-S has adequate sensitivity and specificity for detecting moderate hearing loss (audiometry hearing threshold of >40 dB). The HHIE-S cut-off >8 points is established in the guidelines of the American Speech-Language-Hearing Association(12) as a criterion for a referral to further audiological testing.
More sophisticated measurements of IC have been published but are not feasible in a clinical routine setting(13,14). A screening procedure like ICOPE Step 1 may help to target an at-risk population that would, then, receive in-depth assessments and a closer follow-up.

Table 1
Comparison of the operationalization of the conditions associated with declines in IC between the ICOPE handbook and the definitions applied in MAPT study

*Participants were explicitly asked for each of the items in the time and spatial orientation, and not only an open-ended question. The participant was recorded as with cognitive decline if he/she was wrong to tell the date (number and name of the day, month, year), or wrong to tell the name of the hospital, the level of the building, department and region.
†We used item number 3 of the HHIE-S because of its similarity with the whisper test.


IC domains in-depth assessment

The following tests were performed for an in-depth assessment of the IC domains:
• Cognition: Mini-Mental State Examination (MMSE) (15).
• Locomotion: Short Performance Physical Battery (SPPB) (16)
• Vitality/nutrition: Mini Nutritional Assessment (full version MNA)(17).
• Vision: Monoyer vision chart (18).
• Hearing: Hearing Handicap Inventory for the Elderly – Screening version (HHIE-S) (8).
• Psychological: 15-item Geriatric Depression Scale (GDS-15) (10).

Statistical Analysis

We used percentages to report the frequency of the declines in IC in our study population and by age and sex subgroups. Scores of the in-depth assessments were described using means and standard deviation (SD). Data were analyzed using STATA 14®.



The mean age of our study population was 75.2 years (SD=4.3), 63.6% of them were women, and 28.9% reported 12 years or more of formal education (Table 2). Overall, 89.3% of the population presented one or more conditions associated with declines in IC (87.4% among females, 92.8% among males). Table 3 shows the frequency of conditions associated with declines in IC by domain. Relative frequency of the conditions of interest and mean scores of the tests used for in-depth assessment for sex and age-groups are reported in Supplementary Table S1.

Table 2
Sex, frailty status, number of instrumental activities impaired and mean values of functional performance tests by age group among participants of the MAPT Study

MMSE= mini-mental state examination. SPPB= short performance physical battery. MNA= mini nutritional assessment full version. HHIE-S= Hearing Handicap Inventory for the Elderly – Screening version. GDS= Geriatric Depression Scale; * provided in decimal acuity. For reference, 0.8 decimal = 20/25 imperial= 6/7.5 metric = 0.1 LogMAR.

Table 3
Frequency of conditions associated with declines in IC according to the ICOPE step 1 screening tool by age group among participants of the MAPT Study

*Maximum of possible conditions is six because the sensorial domain includes visual impairment and hearing loss


Cognitive domain

Half of the studied population presented signs of cognitive decline. Table 4 shows the details of the cognitive items of MAPT Step 1. Failing in the word recall section of the MMSE was three times more frequent than failing in the orientation section. In all age groups, the most frequently mistaken word recall was for the last word in the list given to the participants (i.e., cigarette, flower, door – participants less often recalled the word «door»).

Table 4
Prevalence of cognitive sub-domains and mistaken item from the Mini-Mental State Examination (MMSE) including alternative definitions for cognitive decline by age group among participants of the MAPT Study

* Areas of political division. †MAPT participants used the French version during the study.


Mobility domain

Overall, the mean of the time to perform five chair rises was 11.9 seconds (SD=4.5), with age-specific averages ranging from 11.0 (70-74 years) to 16.0 seconds (85-89 years). For the group aged 85-89 years (n=22), the cut-off of 14 seconds proposed by ICOPE Step 1 was at the percentile 52. Further details about the distribution of the sex- and age-specific chair rise times are provided in Supplementary Table S1.

Vitality/Nutrition domain

The mean score in the MNA was 27.6 points, ranging from 27.7 in the youngest group to 26.8 in the oldest group. The frequency of self-reported weight loss or appetite loss was lower than 5% for all the age groups, except for the appetite loss in those aged 80-84 years (7.3%).

Sensorial domain

Vision. In our study population, 92.1% of participants used glasses, contact glasses, implants, or magnifiers at the time of the interview. Even with their supportive devices, up to 14.5% of the participants found it hard to read a newspaper or watch television.
Hearing. Among the participants, 18.2% were using a hearing assistive device at the time of the interview. The screening question for hearing loss identified 55% of those aged 70-74 years and 68% of those aged 85-89 years as positive for hearing loss.



Our study is the first to describe the frequency of the IC declines according to an adaptation of the ICOPE Step 1 screening tool (MAPT step 1) in a selected cohort of memory clinic attendees. Overall, 89.3% of the participants had one or more conditions associated with declines in IC, according to MAPT Step 1 (87.4% among females, 92.8% among males). Nine in every ten screened older adults would be referred to a specialized, in-depth evaluation. It should be noted, however, that MAPT participants expressed memory complaints at recruitment.
We found a high demand for an in-depth assessment. Consider that the MAPT population is more fit than others reported in French studies (except perhaps for cognitive function due to the inclusion criteria). Compared to a random sample used in the French Three-City Study published by Avila-Funes et al. (19), our population was slightly older (mean age 74.1, SD=5.2 vs. 75.2 years, SD=4.3), reported higher levels of educational attainment (>12 years: 17.0% vs. 28.9%) and a lower frequency of frailty (7.0% vs. 3.2%). Therefore, our findings might be underestimating the frequency of IC declines detected by MAPT Step 1 in a real-world population of users of the healthcare system (except for cognitive decline). Our results highlight the need for adapting our health care system to improve the assessment of functions to prevent functional decline. For example, people detected with signs of cognitive decline using the screening tool ICOPE Step 1 could benefit from multidomain interventions (20–22).
Half of the study population showed signs of cognitive decline. Interestingly, participants more frequently failed in selected items (i.e., recalling the name of the day or the last word in a list of three). Therefore, it will be interesting to explore the domain and item’s capacity to predict health events such as frailty incidence in future studies.
Regarding locomotion, the cut-off time to perform five chair rises deserves further investigation (the ICOPE handbook suggests 14 seconds). A cut-off of 15 sec was used in a study measuring the time to complete ten rather than five chair-rises (23). A meta-analysis by Bohannon concluded that 11.4 and 12.7 seconds are suitable cut-off values among subjects aged 60-69 and 80-89, respectively (24). In the SPPB validation study, Guralnik et al. (16) found that 13.7 sec corresponded to the 50th percentile of performance in the chair rise test in a population of more than 5,000 American people aged 71 years or older in 1981. However, current generations might have a better physical performance than those assessed 30 years ago. Establishing age- tailored cut-offs for the chair rise test would allow for a better classification of the performance levels. They would not add difficulty to the implementation of the ICOPE care pathway.
Malnutrition was the least frequent condition. The average score for the full MNA was 27.6, which is higher than the cut-off often used to define the risk of malnutrition (23.5) (17). We think that clinicians should address anorexia and weight loss even if the MNA test if above the cut-off designed for malnutrition. According to the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition in adults (25), reduced food intake/assimilation and weight loss are sufficient to integrate the diagnosis of malnutrition. Also, the Beck depression inventory (26) and by the Center for Epidemiologic Studies Depression (CES-D) scale (27) consider the loss of appetite as a depressive symptom. Moreover, those who leave alone are at higher nutritional risk (28).
For the psychological domain, we did not use the exact questions suggested in the ICOPE screening tool Step 1 because they were not available in MAPT Study. Therefore, we selected from the GDS-15 the two items that more closely matched the ICOPE definition (Table 1). The frequency of depressive symptoms in our study was high (39%), compared to a previous investigation among French older adults (13.8% evaluated with the CES-D in people aged 75 years; SD=6.8) (29). Shared risk factors for cognitive decline and depressive symptoms can explain this difference. Due to MAPT inclusion criteria, participants were at increased risk for cognitive decline, and more than 40% presented mild cognitive impairment (MCI). For instance, using the MAPT Step 1 tool resulted in an overlap of 72% of the participants according to their cognitive decline and depressive symptoms status (7 out of 10 were simultaneously free from or afflicted by both conditions). The connexions across the IC domains are a hallmark of the ICOPE approach (30, 31). Timely interventions targeting these interactions can prevent further losses of ADL ADLs (32).
In the visual domain, we used three questions related to self-reported problems for vision, even when using correction devices (Table 1). Of note, the frequency of visual impairment in our study may have been underestimated because the questions used in MAPT are more specific than the general question proposed in ICOPE Step 1. Furthermore, we did not consider if the person had hypertension or diabetes, as suggested in the ICOPE tool. Evidence suggests that more than half of the cases of visual impairment in older ages are due to cataract and refractive errors, with less than 5% due to diabetic retinopathy (33–35). Perceived difficulty in reading a journal or watching television was reported in 15% of the population wearing vision aids. We consider this ratio as an indicator of unsatisfied demand for visual correction adjustment.
Our hearing loss estimates show that the age-specific frequency of hearing handicap was higher than the ones reported in the study of Wiley et al. performed with 3,471 non-Hispanic whites in Wisconsin, USA. Our figures were similar to those reported by Tomioka et al. (36), with 1,731 community-dwelling older adults from Nara and Osaka, Japan. The different age distribution could explain the dissimilarities.
Our study has strengths, such as being among the first to report the frequency of conditions associated with declines in the five IC domains in a selected cohort of memory clinic attendees. Moreover, the MAPT Step 1 and the ICOPE Step 1 use the same items for most of the IC domains. Therefore, the frequency of declines on visual, hearing, and psychological domains might have been different from our findings if the WHO ICOPE screening tool had been used. On the other hand, some limitations should be mentioned. There was a potential selection bias towards cognitive decline, given that having a spontaneous memory complaint was one of the inclusion criteria in MAPT. However, in a sensitivity analysis removing participants with a cognitive decline in the MAPT Step 1, 78% of the remaining population still had one or more conditions associated with declines in IC (Supplementary Table S2). Our data should not be generalized to other populations. Compared to the age and sex distribution of French older adults, our population overrepresented women (57.1% vs. 63.6%) and adults aged 70-79 years (39.1% vs. 49.8%) (37).
In summary, almost 90% of adults aged 70 years and older in a selected cohort of memory clinic attendees had at least one condition associated with declines in IC. Frequencies varied from 52.2% in the cognitive domain to 6.2% in the nutrition domain. These findings suggest that implementing the ICOPE Step 1 at the community level will help screen for conditions associated with declines in intrinsic capacity. The frequency of declines in IC can provide health systems managers with an estimation of the amount and the type of resources needed to implement the ICOPE clinical pathways. For example, satisfying the demand for visual aids adjustment, or recruitment of health workforce with psychological training. Interesting questions emerged from this descriptive study. For example, should some items be changed to increase the chances of detecting most of the people at risk? Also, are age-specific cut-offs the most suitable approach for some IC domains in the ICOPE screening tool (notably, locomotion)?


MAPT/DSA group: Principal investigator: Bruno Vellas (Toulouse); Coordination: Sophie Guyonnet; Project leader: Isabelle Carrié; CRA: Lauréane Brigitte; Investigators: Catherine Faisant, Françoise Lala, Julien Delrieu, Hélène Villars; Psychologists: Emeline Combrouze, Carole Badufle, Audrey Zueras; Methodology, statistical analysis and data management: Sandrine Andrieu, Christelle Cantet, Christophe Morin; Multidomain group: Gabor Abellan Van Kan, Charlotte Dupuy, Yves Rolland (physical and nutritional components), Céline Caillaud, Pierre-Jean Ousset (cognitive component), Françoise Lala (preventive consultation) (Toulouse). The cognitive component was designed in collaboration with Sherry Willis from the University of Seattle, and Sylvie Belleville, Brigitte Gilbert and Francine Fontaine from the University of Montreal. Co-Investigators in associated centres: Jean-François Dartigues, Isabelle Marcet, Fleur Delva, Alexandra Foubert, Sandrine Cerda (Bordeaux); Marie-Noëlle-Cuffi, Corinne Costes (Castres); Olivier Rouaud, Patrick Manckoundia, Valérie Quipourt, Sophie Marilier, Evelyne Franon (Dijon); Lawrence Bories, Marie-Laure Pader, Marie-France Basset, Bruno Lapoujade, Valérie Faure, Michael Li Yung Tong, Christine Malick-Loiseau, Evelyne Cazaban-Campistron (Foix); Françoise Desclaux, Colette Blatge (Lavaur); Thierry Dantoine, Cécile Laubarie-Mouret, Isabelle Saulnier, Jean-Pierre Clément, Marie-Agnès Picat, Laurence Bernard-Bourzeix, Stéphanie Willebois, Iléana Désormais, Noëlle Cardinaud (Limoges); Marc Bonnefoy, Pierre Livet, Pascale Rebaudet, Claire Gédéon, Catherine Burdet, Flavien Terracol (Lyon), Alain Pesce, Stéphanie Roth, Sylvie Chaillou, Sandrine Louchart (Monaco); Kristelle Sudres, Nicolas Lebrun, Nadège Barro-Belaygues (Montauban); Jacques Touchon, Karim Bennys, Audrey Gabelle, Aurélia Romano, Lynda Touati, Cécilia Marelli, Cécile Pays (Montpellier); Philippe Robert, Franck Le Duff, Claire Gervais, Sébastien Gonfrier (Nice); Yannick Gasnier and Serge Bordes, Danièle Begorre, Christian Carpuat, Khaled Khales, Jean-François Lefebvre, Samira Misbah El Idrissi, Pierre Skolil, Jean-Pierre Salles (Tarbes). MRI group: Carole Dufouil (Bordeaux), Stéphane Lehéricy, Marie Chupin, Jean-François Mangin, Ali Bouhayia (Paris); Michèle Allard (Bordeaux); Frédéric Ricolfi (Dijon); Dominique Dubois (Foix); Marie Paule Bonceour Martel (Limoges); François Cotton (Lyon); Alain Bonafé (Montpellier); Stéphane Chanalet (Nice); Françoise Hugon (Tarbes); Fabrice Bonneville, Christophe Cognard, François Chollet (Toulouse). PET scans group: Pierre Payoux, Thierry Voisin, Julien Delrieu, Sophie Peiffer, Anne Hitzel, (Toulouse); Michèle Allard (Bordeaux); Michel Zanca (Montpellier); Jacques Monteil (Limoges); Jacques Darcourt (Nice). Medico-economics group: Laurent Molinier, Hélène Derumeaux, Nadège Costa (Toulouse). Biological sample collection: Bertrand Perret, Claire Vinel, Sylvie Caspar-Bauguil (Toulouse). Safety management: Pascale Olivier-Abbal. DSA Group: Sandrine Andrieu, Christelle Cantet, Nicola Coley.
Funding: The present work was performed in the context of the Inspire Program, a research platform supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.
Acknowledgements: NA
Authors contributions: PB, BV and EG conceived the study. EG, statistics and manuscript writing. KV, PB, LM, BV and SA provided inputs and reviewed the manuscript. BV and SA are PIs in MAPT.
Funding section: The present work was performed in the context of the Inspire Program, a research platform supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript. “This study received funds from Alzheimer Prevention in Occitania and Catalonia (APOC Chair of Excellence – Inspire Program). The MAPT study was supported by grants from the Gérontopôle of Toulouse, the French Ministry of Health (PHRC 2008, 2009), Pierre Fabre Research Institute (manufacturer of the omega-3 supplement), ExonHit Therapeutics SA, and Avid Radiopharmaceuticals Inc. The promotion of this study was supported by the University Hospital Center of Toulouse. The data sharing activity was supported by the Association Monegasque pour la Recherche sur la maladie d’Alzheimer (AMPA) and the INSERM-University of Toulouse III UMR 1027 Unit».
Conflict of interest: The authors declare no competing interest relevant to this article.
Ethical standard: This study did not include any experiments involving humans or other animals.





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S. Guyonnet1,*, Y. Rolland1,*, C. Takeda2, P.-J. Ousset2, I. Ader3, N. Davezac4, C. Dray5, N. Fazilleau6, P. Gourdy5, R. Liblau6, A. Parini5, P. Payoux7, L. Pénicaud3, C. Rampon4, P. Valet5, N. Vergnolle8, S. Andrieu9, P. de Souto Barreto10, L. Casteilla3, B. Vellas1 for the INSPIRE Platform group


1. Inserm UMR 1027, Toulouse, France; University of Toulouse III, Toulouse, France; Gérontopôle, Department of Geriatrics, CHU Toulouse, Toulouse, France; 2. Gérontopôle, Department of Geriatrics, CHU Toulouse, Toulouse, France; 3. STROMALab, Etablissement Français du Sang-Occitanie (EFS), Inserm 1031, University of Toulouse, National Veterinary School of Toulouse (ENVT), ERL5311 CNRS, Toulouse, France; 4. Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France; 5. Institut des Maladies Métaboliques et Cardiovasculaires, Inserm/Université Paul Sabatier UMR 1048 – I2MC 1 avenue Jean Poulhès BP 84225 31432 Toulouse Cedex 4 – France; 6. Centre de Physiopathologie Toulouse Purpan, INSERM/CNRS/UPS UMR 1043, University of Toulouse III, Toulouse, France; 7. ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France; 8. IRSD, Université de Toulouse, INSERM, INRA, ENVT, UPS, U1220, CHU Purpan, CS60039, 31024, Toulouse, France; 9. Inserm UMR 1027, Toulouse, France; University of Toulouse III, Toulouse, France; Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France; 10. Inserm UMR 1027, Toulouse, France; University of Toulouse III, Toulouse, France; Gérontopôle, Institute of Aging, CHU Toulouse, Toulouse, France; *These authors contributed equally to this work.
Corresponding author: Sophie Guyonnet, Inserm UMR 1027, Toulouse, France; University of Toulouse III, Toulouse, France; Gérontopôle, Department of Geriatrics, CHU Toulouse, Toulouse, France, guyonnet.s@chu-toulouse.fr

J Frailty Aging 2020;in press
Published online July 10, 2020, http://dx.doi.org/10.14283/jfa.2020.38



Background: The Geroscience field focuses on the core biological mechanisms of aging, which are involved in the onset of age-related diseases, as well as declines in intrinsic capacity (IC) (body functions) leading to dependency. A better understanding on how to measure the true age of an individual or biological aging is an essential step that may lead to the definition of putative markers capable of predicting healthy aging. Objectives: The main objective of the INStitute for Prevention healthy agIng and medicine Rejuvenative (INSPIRE) Platform initiative is to build a program for Geroscience and healthy aging research going from animal models to humans and the health care system. The specific aim of the INSPIRE human translational cohort (INSPIRE-T cohort) is to gather clinical, digital and imaging data, and perform relevant and extensive biobanking to allow basic and translational research on humans. Methods: The INSPIRE-T cohort consists in a population study comprising 1000 individuals in Toulouse and surrounding areas (France) of different ages (20 years or over – no upper limit for age) and functional capacity levels (from robustness to frailty, and even dependency) with follow-up over 10 years. Diversified data are collected annually in research facilities or at home according to standardized procedures. Between two annual visits, IC domains are monitored every 4-month by using the ICOPE Monitor app developed in collaboration with WHO. Once IC decline is confirmed, participants will have a clinical assessment and blood sampling to investigate markers of aging at the time IC declines are detected. Biospecimens include blood, urine, saliva, and dental plaque that are collected from all subjects at baseline and then, annually. Nasopharyngeal swabs and cutaneous surface samples are collected in a large subgroup of subjects every two years. Feces, hair bulb and skin biopsy are collected optionally at the baseline visit and will be performed again during the longitudinal follow up. Expected Results: Recruitment started on October 2019 and is expected to last for two years. Bio-resources collected and explored in the INSPIRE-T cohort will be available for academic and industry partners aiming to identify robust (set of) markers of aging, age-related diseases and IC evolution that could be pharmacologically or non-pharmacologically targetable. The INSPIRE-T will also aim to develop an integrative approach to explore the use of innovative technologies and a new, function and person-centered health care pathway that will promote a healthy aging.

Key words: Gerosciences, integrated care, biological aging, intrinsic capacity, biology of aging, translational research on aging.



Aging is an important risk factor for several adverse health outcomes, particularly chronic and metabolic diseases and intrinsic capacity (IC) decline. Since chronological age differs from biological aging, operationally defining biological aging is an essential aspect to understand the interplay between aging and health outcomes. Individuals progress differently in the aging process (“normal” aging vs “accelerated” aging), which means, biological aging is a heterogeneous process. In this context, we need to develop researches to identify biomarkers of aging and healthy aging, and know how to measure biological aging. According to the Geroscience field, understanding aging and the links with age-related diseases would contribute to prevent and/or delay the onset of various diseases and the decline in IC domains, in particular in the six operational IC domains crucial for independent living defined by the World Health Organization (WHO) (mobility, cognition, psychological, vitality, hearing and vision capacities) (1-3).
The WHO has recently published the Integrated Care for Older People, ICOPE handbook Guidance, to support Healthy Aging and to propose to health-care providers appropriate approaches to detect and manage declines in IC. With this integrated and individualized approach, WHO aims to reduce the number of dependent people by 15 million Worldwide by 2025 (4-7).
Studying concomitantly biomarkers of aging and the natural history of IC evolution in people of different ages and functional status is to date very challenging to understand the relation between biological aging and health outcomes. In this context, the INSPIRE program was built to foster research in the field of Geroscience and healthy aging. INSPIRE is a research program dedicated to biological and healthy aging, aimed at constituting a bio-resource platform going from animals to humans, from cells to individuals, from research to clinical care. INSPIRE will provide clinical, biological and technological resources for research and development on aging. The resources will be open to both academic and industry worlds in order to promote healthy aging and prevent dependency. It is a public-private initiative that brings together internationally recognized experts from basic and translational science (in particular, in the fields of immunology, metabolism, neurosciences and mesenchymal stem/stroma cells), clinical gerontology (i.e., researchers, but also physicians and nurses involved in clinical care), primary care and public health (8).
One of the main challenges of INSPIRE is to identify markers capable of determining biological aging with the implementation of human and animal cohorts. The INSPIRE Human Translational Cohort (INSPIRE-T cohort) will recruit about 1000 individuals of several chronological ages (from 20 years to 100+) and functional capacity levels (from robust to frail, and even disabled) with baseline and follow-up biological, clinical, imaging and digital data over 10 years. These data should allow us to explore and identify a set of biomarkers of aging, age-related diseases and IC evolution. In addition, the INSPIRE-T cohort aims: i/ to test the feasibility and acceptability of a new app for smartphone and tablet developed to monitor the six IC domains (locomotion, cognition, vision, hearing, vitality/nutrition, psychological status) according to the WHO recommendations; and ii/ to explore the development of digital markers of aging. This paper describes the study design of the INSPIRE-T cohort.


Material and Methods

Study design

The INSPIRE-T cohort, started in October 2019, is a 10-year observational study. The study population will consist of 1000 subjects recruited in the city of Toulouse and surrounding areas, South-Western France, and covering the age range of 20 years and over (no upper limit for age). Several follow-up visits will be regularly scheduled during the 10-year period of this study. Additional visits will be conditioned by the remote monitoring of IC and the onset of other major clinical conditions.
At baseline, and then once a year, diversified data (clinical, digital, imaging) and biospecimens (blood, urine, saliva and dental plaques) are collected following standardized procedures. Data collection is performed in the Clinical Research Center (CRC) of the Gerontopole – CHU Toulouse. It can also be performed in participants’ home (for more frail and disabled volunteers), or in selected Gerontopole’s collaborating centers by a mobile research team trained by the CRC. Participants are assessed by appropriately trained clinical research members.
Between yearly waves of data collection, participants are asked to record major clinical information, including adverse events (e.g. new diagnosis, SARS COV-2 diagnosis, influenza, fracture…), medical consultations, hospitalizations, and changes in the drug prescription every 4-months. They also have the six IC domains monitored (with or without the help of a caregiver) (ICOPE program Step 1) (4,7) in either the application developed in collaboration with WHO (ICOPE Monitor app) or a web platform; or through a phone call by a Gerontopole’s trained research nurse. When declines are detected in the ICOPE Step 1, a phone call is organized by the research nurse within one week to confirm this decline and to investigate the causes in collaboration with the medical research team. Once an IC decline is confirmed, participants have a thorough clinical assessment following the recommendations of the ICOPE Step 2 (4,7) and blood sampling (data are collected by research nurses in a home visit or at the research facility). Such information will enable us to investigate the response of some markers of aging at the time declines are detected. The clinical assessments and biomarkers’ exploration also allow us to propose a personalized prevention care plan to maintain function according to the recommendations from the WHO ICOPE program for usual care (ICOPE Step 3) (4,7).
Participants are trained to monitor their IC during the baseline visit by the Gerontopole’ research team. The remote monitoring of IC will last the whole length of this research study, i.e., up to ten years. The figure 1 shows schematically the study procedures over one year. Table 1 describes the study flow chart with all data collected at each time point during the follow-up.
To ensure quality of data collected, standard operating procedures are implemented covering subject’s recruitment, biobanking, remote monitoring of IC, clinical assessments and digital data collection. All data are collected in the INSPIRE-T database. Preventive strategies to limit errors like miscoding, missing values, are applied before data entry to ensure the validity and quality of the performed data analysis. Tools will be implemented for data exploration and data sharing between INSPIRE consortium researches and later on with external scientists.

Table 1
The INSPIRE Human Translational Research cohort flow-chart

a. The cognitive composite score will be realized only in people lower than 70 years; b. Other examinations are proposed to a limited number of participants in a volunteer basis

Figure 1
INSPIRE-T study procedures over one year. The remote monitoring of intrinsic capacity will last the whole length of this research study, i.e., up to ten years



The main objective of the INSPIRE-T cohort is the appropriate data collection of key variables and biospecimens for at least 1000 people at baseline and 800 people with at least four years of follow-up (i.e. four yearly post-baseline assessments) over the 10-year study. The key variables are clinical data on all six IC domains (locomotion, cognition, vision, hearing, vitality/nutrition, psychological status), and the collection of blood, urine, saliva and dental plaque samples. Secondary objectives include: i/the identification of (a set of) biomarkers of aging through the constitution of a comprehensive biobank; ii/the assessment of the feasibility and acceptability of the ICOPE Monitor app used to measure and monitor intrinsic capacity; iii/ the study of the evolution of IC domains over time and its association with health outcomes; and finally, iv/ the study of the correlation between digital biomarkers to biological/imaging biomarkers and IC domains (Figure 1, online consultation).
A mouse cohort in mirror of the human INSPIRE-T cohort is being built in order to cross the results of translational research found in humans on aging animal models, and vice versa (8). The main objective of the INSPIRE Animal cohort is to define the relationship between the molecular mechanisms of cell premature senescence and frailty/accelerated aging (8).

Study population

We will recruit about 1000 subjects, men and women, aged 20 years-old or over (no upper limit for age), and affiliated to a social security scheme. People having a severe disease compromising life expectancy at 5 years (or at 1 year for subjects living in nursing homes) and people deprived of their liberty by administrative or judicial decision, or under guardianship, are excluded. Recruitment is stratified per 10-year age groups, oversampling older people in order to be able to investigate major clinical events (e.g., declines on IC, onset of age-related diseases).
Due to the heterogeneity of biological aging, we opted for no too stringent eligibility criteria. By diversifying our recruitment sources and monitoring key risk factors for accelerated aging (e.g., age, obesity, frailty, and activities of daily living), we will be able to recruit participants with different trajectories of aging.
Sample size calculation was not relevant as many objectives of the INSPIRE-T cohort are exploratory. We therefore considered an approach based more on the potential of the INSPIRE-T cohort in terms of the ability to obtain parameter estimates with sufficient precision with a recruitment of 1000 subjects that corresponds to the maximum number of subjects that can be recruited and monitored with the funding provided. In case of evident underpowered population (for a particular subgroup of subjects), a reasoned additional recruitment of subjects may be considered in a second phase. To limit the attrition rate, subjects will be monitored by both active (visits, telephone calls) and passive ways (monitoring of several functions using new technologies via mobile phones or other connected devices).

Data collection

From all subjects enrolled, investigations include data collection at baseline and during follow-up visits (annual visits and additional visits planed in case of decline in IC). Upon written informed consent, the following set of information is obtained by using a standardized questionnaire:
• Demographic information: marital status, education, occupation and housing conditions, use of healthcare services;
• Physical examination comprising measurement of the following classical markers: medical history, medication, vaccination, current diseases, body mass index, waist and hip circumference, heart rate, blood pressure, self-reported visceral pain, skin elasticity (cutometer measurement), cutaneous itching/pruritus;
• Lifestyle information: physical activity, sedentarity time, smoking, alcohol consumption, solar exposure;
• Fried frailty phenotype (9);
• Functional status: Activities of Daily Living (ADL) (10) and Instrumental Activities of Daily Living (IADL)(11);
• Cognitive status: Mini Mental State Examination (MMSE) (12) and for people lower than 70 years, neuropsychological tests including free and total recall of the Free and Cued Selective Reminding Test (13), ten MMSE (12) orientation items, the Digit Symbol Substitution Test score from the Wechsler Adult Intelligence Scale—Revised (14), and the Category Naming Test (15) (2-minute category fluency in animals);
• Nutritional status: Mini Nutritional Assessment (MNA) (16), food frequency questionnaire (17);
• Oral status: Oral Health Assessment Tool (OHAT) (18);
• Depressive symptoms: Patient Health Questionnaire (PHQ-9) (19);
• Physical performance: Short Physical performance battery (20) and chair rise test (30 seconds)(21-22);
• Participant-reported outcome for cognition (CFI) (23) and mobility, fatigue, and social isolation (PROMIS) (24);
• Objective physical activity and sleep parameters (parameters are collected for one week using activPAL accelerometer);
• Vision: WHO simple eye chart, and the AMSLER Grid;
• IC domains (ICOPE Step 1) by using the ICOPE Monitor app. This app will be used throughout the study for the remote (at-distance) evaluation and monitoring (self-monitoring). All cut-offs operationalizing a deficit in IC comes from the WHO ICOPE program (4,7). At the first visit, the research team explains to the participants how to use the ICOPE Monitor app and monitor their IC domains over time. At each annual regular visit, the research team will confirm participants apply the correct evaluation procedures for assessing their IC. The 6 domains of IC evaluated by the ICOPE Monitor app are:
o Mobility measured by the time (in sec) spent to raise from a chair, at 5-repetition at a maximum speed. Declines will be considered when the time needed to complete the test is higher than 14 sec.,
o Cognitive measured by the 3-word remember test of the MMSE (12) and the following questions: Do you have problems with memory or orientation (such as not knowing where one is or what day it is)? Did you notice a worsening of these disorders in the last 4 months or since the last evaluation? What is the full date today? (day, month, year, day of the week). For the 3-word remember test, three different sets of words will be used to avoid memory bias between two close assessments. Declines are present if the individual is unable to remember at least one word or if he/she provide a wrong response to the orientation question,
o Psychological measured by the following two questions: Over the past two weeks, have you been bothered by: 1. Feeling down, depressed or hopeless? 2. Little interest or pleasure in doing things? One “YES” response determines a decline,
o Vitality/nutrition measured by the following two questions: Have you unintentionally lost more than 3 kg over the last 3 months? Have you experienced loss of appetite? One “YES” response determines a decline. One further question will be asked: what is your actual weight (in kilograms)?
o Sensorial-hearing measured by the Whisper test according to the following procedures: the evaluator must 1/stand about an arm’s length away behind and to one side of the person; 2/ ask the person or an assistant to close off the opposite ear by pressing on the tragus (the tragus is the projection in front of and partly covering the opening of the ear); 3/ Breathe out and then softly whisper a word with two syllables (a set of words will be selected by the Inspire research team), use a common word; 4/Ask the person to repeat the word; and 5/ Move to the other side of the person and test the other ear, use a different word. Not repeating the correct words determines a decline. If the Whisper test can’t be realized, two questions are asked: Did you notice a worsening of these disorders in the last 4 months or since the last evaluation? Does your family complain an acute recent hearing loss?
o Sensorial-vision measured by the following questions: Do you have any problems with your eyes: difficulties in seeing far, reading, eye diseases or currently under medical treatment (e.g. diabetes, high blood pressure)? Declines are considered present when a person responds «yes» to this question and if she did not recently consult an ophthalmologist.

Other examinations are proposed to a limited number of participants (all age ranges and functional status) in a volunteer basis: Dual energy X-ray absorptiometry (DXA) for body composition assessment; Whole body and brain magnetic resonance (MRI); cardiorespiratory fitness (maximum oxygen consumption (V02 max) with blood sampling before and after the effort, and maximal aerobic power), and isokinetic muscle strength. These examinations are proposed annually for the DXA and, every two years for the other tests (MRI, VO2 max, Isokinetic muscle strength). Participant-reported outcome for sarcopenia (SARQoL) (25) is completed for volunteers who perform cardiorespiratory fitness exploration.

Digital assessments

Innovative digital assessments are also planned to be tested, such as home sensors (e.g., for measuring walking speed and its variability in daily environment), automated video analysis of mobility, and 3D facial images for the detection of digital markers of aging. A subgroup of 100 patients monitored by ambient sensors at home or sensors worn on the wrist over the long term will allow to remote and continuous monitoring of the trajectories of the IC domains (especially mobility, sleep parameters and nutrition) (CART/SmartHome research ancillary study, legal authorizations in process). This sub-study, developed in partnership with the CART research project team in United States (ORCATECH Team, Oregon Health and Science University, OR, USA; PI, Jeffrey Kaye; www.ohsu.edu) will allow us to detect subtle changes that are not clinically perceptible, well before the appearance of signs and symptoms and therefore determine innovative digital biomarkers and decision thresholds. These digital biomarkers will be correlated with clinical data but also biological and imaging biomarkers.


Biospecimens are collected during the INSPIRE-T cohort for the creation of a biobank.
Biospecimens, including blood, urine, saliva, dental biofilm, are collected from all subjects at baseline and then, annually (the genotyping sample will be collected only at the baseline visit). Nasopharyngeal swabs and cutaneous surface samples are collected from all subjects every two years. Feces, hair bulb, and skin biopsy, are collected optionally at baseline visit (see Table 2).
Aliquots of biological material are stored at -80°C (dental biofilm, saliva, serum, plasma and urine) or at -196° C liquid nitrogen (PBMC) at the central lab (CRB TBR, CHU Toulouse/IFB PURPAN, Toulouse, France). Analysis will be either performed in Toulouse by the local biological teams involved in the INSPIRE project or by any third party not yet determined. The modality of Laboratory Data Transfer from the central lab to other parties will be defined at a later stage. Samples from the biobank may be moved to other US and European countries if required.
The INSPIRE-T biobank is supervised by the CRB TBR where all measures are taken to ensure a quality service based on appropriate resources and adequate safety procedures: observance of Good Laboratory Practice guidelines (the CRB TBR is certified AFNOR since 2015), fully-equipped premises, appropriate, approved and safe equipment (17 freezers -80°C Eppendorf Cryocube, 2 liquid nitrogen tanks with manual and documented filling, Vigitemp probes provide metrological tracking), qualified personnel, safety test and system implementation, sample traceability (all of biological collections are tracked in a specific software (TD Biobank), and CHU servers are daily backed up). All freezers are equipped with an alarm system. Equipments are monitored three times per day. Every failure is reported in the Kalilab software as non-compliance statements.
All the participants will be tested for SARS COV-2 infection via serological tests from blood collection when these latter will be available.
All biological samples are processed within 110 min following a protocol elaborated for INSPIRE purpose and split into smaller aliquots at the INSPIRE-T biobank (Figures 2 &3, online consultation).

Table 2
Samplings proposed to the INSPIRE Human Translational Research Cohort participants for the creation of the biobank


Blood collection

For blood collection, all subjects are asked to donate blood (60 ml) by venipuncture after overnight fasting. The blood sample is processed to obtain whole blood, plasma, red blood cells, serum and peripheral blood mononuclear cells (PBMC).
For whole blood and serum, samples are immediately shipped after collection at room temperature to the CRB TBR for the preparation of whole-blood and serum aliquots for freezing at -80° in the INSPIRE-T biobank.
For PBMC, blood samples are immediately transported to the CRB TBR at room temperature and treated within 24 hours from time of collection. PBMC are collected after density gradient-based separation, counted and frozen at 8-14 millions/cells per vial. Frozen vials will be stored in liquid nitrogen.
For plasma and RBC (EDTA/Lithium Heparin/BDP100 Blood), aliquots are immediately prepared after collection in the CRC and stored at -80°C until their shipment to the INSPIRE-T biobank.
When visits are organized by the mobile research team, some blood samples are not performed to limit quality procedures deviations (it concerns the Lithium Heparin tube, the 2 whole blood EDTA tubes and the BD P100 blood tube).

Urine collection

Participants are asked to collect at least 20 ml urine in a sterile screw-top container. The obtained volume is transferred into two vacutainer tubes of 10 ml each and directly shipped at room temperature to the CRB TBR where urine aliquots of 1 ml are prepared and stored at -80°C in the INSPIRE-T biobank.


Participants are asked to collect 10 ml saliva in 50 ml Falcon tube (at least 30 min after a meal). The Falcon tube is immediately shipped at room temperature to the CRB TBR where saliva aliquots of 1 ml are prepared and stored at -80°C in the INSPIRE-T.

Dental biofilm collection

Biofilm sampling consists in recovering the biofilm from the external surfaces of the teeth (from natural teeth in priority, from prosthetic teeth if not possible), at the juxta-gingival level by curettage at 4 sites distributed over the dental arches: a sample from the upper anterior teeth, a sample from the upper posterior teeth, a sample from the lower anterior teeth, a sample from the lower posterior teeth. The product of each curettage is individualized in a sterile 1 ml cryotube. The four cryotubes are frozen at -80° in the CRC after the collection and regularly shipped to the CRB TBR.

Nasopharyngeal swabs

Nasopharyngeal swab will be addressed to the Institute of Biology of the CHU Toulouse within 4 hours from time of collection for their analysis (detection and identification of multiple respiratory viral and bacterial nucleic acids). Residuals samples will be stored at -80° to the CRB TBR in the INSPIRE-T biobank.

Skin swab and stripping

Swab samples are done on a skin exposed area (posterior face of the forearm) and a non-exposed area (lower back). Specimens are stored immediately at -80°C in the CRC. Frozen tubes are regularly shipped to the CRB and stored at -80°C in the INSPIRE-T biobank.
In addition, two 14 mm diameter D-squames are applied successively on the exact same area of the posterior face of the forearm: the first one is discarded and the second one is stored in a 2 ml tube. The same procedure is performed on the lower back. Both tubes are regularly shipped to the CRB and stored at -80°C in the INSPIRE-T biobank.

Feces collection (optional)

Feces are collected at the first visit and immediately stored at -80°C. If it is not possible, the participant can return to the research facility within one week with its frozen sample in a coproculture pot, placed in a cool box. The frozen feces samples are regularly shipped to the CRB TBR and stored at -80°C in the INSPIRE-T biobank.

Hair bulb collection (optional)

Twenty hairs are taken with the bulb and immediately stored after the collection in a sterile 2 ml cryotube in the CRC until their shipment to the INSPIRE-T biobank.

Skin biopsy (optional)

A 4 mm skin biopsy is obtained by using a punch. Skin samples are prepared according two different procedures: half of the samples are immediately rinsed, dried and stored at -80°C until its shipment to the CRB TBR; the other are immediately placed in a cryotube with PBS for cells cultures to organize a biobank of skin fibroblasts.
A biobank scientific committee will be set up, in the aim of determining the scientific directions and research priorities, of evaluating ongoing projects and their state of progress, and of resolving any methodological and ethical concerns raised by the studies. It shall i/examine the relevance, feasibility and conditions of implementation of the propositions concerning any analyses; ii/ ensure that national and international partnerships are made formal; iii/ control use of data, especially sample use, and iv/ ensure that participants rights are protected. The data disclosed will be made anonymous (coded, traceable data).

Statistical methods

Since the primary outcome measure of the INSPIRE-T cohort is related to reaching prespecified numbers for recruitment and retention, we will use numbers and percentages. Hypothesis-testing statistics will be employed for some of the secondary outcome measures and the new hypothesis arising through the 10 year duration of the INSPIRE program. Specific statistical analysis plan (SAP) will be written to answer each research question. Big data methods of analysis will be considered when examining the large and diversified amount of data that will be gathered from clinical and para-clinical evaluations, biospecimens, and digital assessments.
Significance will be set at p ≤ 0.05. Analyses will be performed using Stata (v14, StataCorp), SAS (v9.4, Cary, NC, USA), and R (v3.5.2). Statistical analyses will be done by researchers of the Inspire program and professional statisticians. Analyses by gender will be conducted.

Ethical and regulatory considerations

The INSPIRE-T cohort is carried out in accordance with the declaration of Helsinki, which is the accepted basis for clinical study ethics, and must be fully followed and respected by all engaged in research on human beings. The INSPIRE-T cohort protocol has been approved by the French Ethical Committee located in Rennes (CPP Ouest V) in October 2019. This research has been registered on the site http://clinicaltrials.gov (ID NCT04224038).


Current progress of the INSPIRE -T cohort

Recruitment status

The first participant was recruited on October 16 2019. Our objective is to recruit at least, 1000 people at baseline (500 during the first year and 500 during the second year of the project) from 20 onwards, including robust, prefrail and frail older adults, as well as disabled people, to be able to better understand the biology of aging across age-ranges and functional status. All the recruiting work is currently carried out by the Toulouse Gerontopole research team on a single site; a mobile clinical research team is also currently active to recruit frailer population (e.g. people unable to come to research facilities) in Toulouse and surrounding areas. Current inclusion rates are 4 participants per day. This rate will allow us to reach our objective of 1000 inclusions in 2 years. Two hundred and forty participants have been included by March 13 2020 (137 women / 103 men; mean age: 74.6 years), and 400 new inclusions are planed until September 2020. Among the 240 enrolled participants, 168 are robust, 60 prefrail and 6 frail with Fried criteria (9). All participants gave their consent for the complete biobanking, 112 participants have accepted the skin biopsy, 231 hair bulb collection and 216 feces collection. All subjects have accepted the DXA, and 211 VO2 max and muscle strength assessment. The sub-study on MRI is planned to start on September 2020. However, recruitment has been temporarily suspended during the COVID-19 pandemic.

Recruitment strategies

Our first plans were to recruit a representative sample of users of primary care services, by inviting people to participate using patients’ list of several family physicians in different areas (with different deprivation levels) of Toulouse (all patients aged 20 years or over being invited to be screened for participation). However, this recruitment approach proved to be unfeasible, mainly because many physicians have been very busy taking care of several viral pathologies during winter 2019-2020 (including COVID-19 from February 2020) (26, 27). Consequently, we decided to diversify the sources of recruitment.
Current recruitment relies mainly on the following strategies: flyers, community outreach strategies, media coverage, newspaper advertising, posters, online promotion, mass mailing, presentations at public events, conferences, study website, dissemination through institution newsletters, identification of participants from previous studies or existing registries, onsite recruitment /medical records review (by investigators/clinical research assistants), dissemination through health care providers : coordination with primary care, memory centers, hospital outpatient clinics, medical centers, physicians (site investigators, primary care physicians), specialists, hospital inpatient lists, private clinics, and finally, dissemination through residential homes, and nursing homes. The recruitment channels of the participant included (and planed over the next 6 months) is detailed in Table 3. Applied strategies are constantly followed and adapted if necessary throughout the recruitment study period (weekly meeting with investigators and study staff).

Table 3
Recruitment strategies implemented in the INSPIRE Human Translational Cohort


A mobile research team was implemented in January 2020 to recruit frailer population by collaborating with residential homes, long-term care facilities and post-acute and rehabilitation facilities. Next collaborations are considered with the CRCT in Oncopole-Toulouse (an institution dedicated to cancer research and care) and a private clinic focused on the management of obese people.
Retention strategies are implemented in parallel. It consists of participant-centered values and strategies including (but not limited to) identify proxy contacts, minimize waiting time during study visits, facilitate transportation from and to research facilities, adapt comfortable waiting room facilities, build relationships with study participants; remind nonresponsive participants (contact via phone or email, make phone calls during optimal hours; offering regular feed-back during the follow-up (mailing study updates); offering regular gadgets during the follow up and postcards.


The INSPIRE-T cohort will gather clinical, biological (including imaging), and digital data for subjects of several chronological ages and functional capacity status regularly followed over up to 10 years. One of the most innovative aspects of the INSPIRE-T cohort is that, through a close monitoring of participants with the ICOPE Monitor app, we will obtain clinical and biological data at the moment declines in IC come up. The cohort will provide us the needed resources to improve our understanding of the biological mechanisms of aging and the natural history of loss of IC leading to dependency during aging. By following and monitoring the IC of participants over time, this study will provide information about a new, function-centered healthcare pathway, which would agree with WHO recommendations for an integrated care for older people. At the medium term, this data may inform the development of a pragmatically interventional study testing the effects of this new healthcare pathway on clinical outcomes in older people; this healthcare pathway may be integrated in daily practice in healthcare systems, becoming thus the usual care. Innovative digital solutions (including sensors) proposed in the INSPIRE-T cohort are a promising way to remotely collect and analyze real-life and continuous health related data and thus longitudinal trajectories over time. It makes it possible to detect subtle variation in the IC before a clinical event.
The INSPIRE-T cohort will also perform relevant and extensive bio banking to allow basic and translational research in humans in the field of Geroscience and Healthy Aging. The INSPIRE-T biobank might lead to improving our understanding about molecular and physiological mechanisms involved in healthy aging, interacting with changes linked to specific chronic diseases. This may contribute to establish a set of biomarkers, that could be pharmacologically or non-pharmacologically targetable, and that would characterize biological aging and, then, permit to identify an accelerated aging phenotype. In their recent paper, Ahadi S et al (28) have defined different types of aging patterns in different individuals, termed “ageotypes”, on the basis of the types of molecular pathways that changed over time in a given individual. According to the authors, “ageotypes” may provide a molecular assessment of personal aging, reflective of personal lifestyle and medical history that may ultimately be useful in monitoring and intervening in the aging process”. One of the main objectives of the INSPIRE-T cohort is to identify biological markers that could detect the inter-individual variability of biological processes before it becomes clinically perceptible (29). The identification of biomarkers of aging may help us to identify individuals who are with a high risk of developing age-associated diseases, decline in IC or disability, and to propose personalized strategies, including innovative therapeutics, to prevent or restore impaired functions. Our clinical and biological data will give the opportunity to explore the interaction between changes with aging on inflammation, metabolism, gerosciences in general, and neurodegenerative process leading to Alzheimer’s disease (30, 31) or physical frailty (32), two major causes of loss of functions. The INSPIRE-T cohort will benefit from the availability of plasma neurodegenerative biomarkers (plasma amyloid beta 42/40, neurofilaments, plasma phospho tau) (31). The development of biological markers of frailty is also required to improve the treatment of frail individuals. The etiology of frailty is complex. Proposed biomarkers of frailty include markers of inflammation. As recently proposed by the ICSFR Task Force perspective on biomarkers for sarcopenia and frailty, «machine learning and information technology innovation could thus be used to develop risk scores that could be used in clinical and research settings. Other technologies, such as induced pluripotent stem cells (iPSCs) or skin fibroblasts, could be used to study markers of senescence and could also enable a move towards personalized medicine» (32). Interventions to promote healthy aging will be more effective in people with a risk of decline (29). Hallmarks of aging are under scrutiny in particular DNA alteration, epigenetics, unusual protein production, senescent cells secreting pro-inflammatory factors and others. New therapies aim to target senescent cells or their secretory proteins (the senolytic molecules) and therefore promote healthy ageing are presently under development (33-36).
Finally, the INSPIRE-T cohort gives us the opportunity to federate clinical and biological research teams in Toulouse and Occitania Region to build a research platform of gerosciences discovery to explore mechanisms of aging, and to implement comprehensive translational projects towards the goal of preventing the consequences of aging for a healthy, and long-lived society (37). The animal cohort, generated to “mirror” the human translational cohort, will facilitate the translation of results from basic research to humans and to the clinics. The identification of markers of aging will take advantage of three complimentary approaches to look for the best markers of aging: without a priori approaches (transcriptomics, proteomics, metabolomics); semi a priori approach (metabolism, inflammation, cell cycle, mitochondrial network…); and targeted approach (pre-identified targets such as (but not limited to) Growth Differentiating Factor 15 (GDF-15), apelin, senescent cells, amyloid protein in plasma) (38). From a biological viewpoint, the function-centred approach recommended by WHO represents a challenge due to the multidimensionality that characterizes IC’ trajectories during aging. We will develop an integrative view of biological aging (Figure 2). Three classes of parameters transversal to the whole organism, present in all organs, strongly interrelated and crucial in tissue homeostasis have been selected: i) inflammation and immunity that represents both a warning signals and the house keeping guard of tissue integrity, ii) mesenchymal stem/stroma cells (MSC) allowing support for all function and their adaptation and iii) metabolism that controls any cell decision and the fate of most of them. For all these transversal components, senescence mechanisms will be carefully investigated.

Figure 2
The INSPIRE approach: an integrative view of biological aging


Due to the Covid19, teleconsultation has been added for the pre-inclusion and some of the assessment, we will be able also to assess the” stay at home order” on the INSPIRE-T cohort subjects (39).
In conclusion, the INSPIRE-T cohort, nested in the INSPIRE Platform, will contribute to healthy aging and dependency prevention. The INSPIRE-T cohort will foster discoveries of human markers (i.e., biological, clinical, digital) of healthy aging capable of predicting functioning and resilience.


Acknowledgments: The Inspire Program is supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175), the European Regional Development Fund (ERDF) (Project number: MP0022856), MSD Avenir and the Inspire Chairs of Excellence funded by: Alzheimer Prevention in Occitania and Catalonia (APOC), EDENIS, KORIAN, Pfizer, Pierre-Fabre.
Conflict of interest: All authors of the paper “The INSPIRE research initiative: a program for GeroScience and healthy aging research going from animal models to humans and the healthcare system” declare no Conflicts of Interest related to this manuscript.
Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.





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M. Maggio1,2, M. Barbolini3, Y. Longobucco2, L. Barbieri4, C. Benedetti2, F. Bono5, I. Cacciapuoti4, A. Donatini4, E. Iezzi3, D. Papini6, P.M. Rodelli5, S. Tagliaferri2, M.L. Moro6

1. Medicine-Geriatric-Rehabilitation Department, University-Hospital of Parma; 2. Department of Medicine and Surgery, University of Parma; 3. Parma Local Health Trust; 4. Emilia Romagna Region; 5. Research and Innovation Unit, University Hospital of Parma; 6. Regional Health and Social Agency, Emilia Romagna Region.
Corresponding author: Marcello Maggio, Universita degli Studi di Parma Dipartimento di Medicina e Chirurgia, Parma, Parma, Italy, marcellogiuseppe.maggio@unipr.it
J Frailty Aging 2020;9(2)101-106
Published online November 28, 2019, http://dx.doi.org/10.14283/jfa.2019.41



Objectives: Frailty is a pre-disability condition in older persons providing a challenge to Health-Care Systems. Systematic reviews highlight the absence of a gold-standard for its identification. However, an approach based on initial screening by the General Practitioner (GP) seems particularly useful. On these premises, a 9-item Sunfrail Checklist (SC), was developed by a multidisciplinary group, in the context of European Sunfrail Project, and tested in the Community. Objectives: – to measure the concordance between the judgments of frailty (criterion-validity): the one formulated by the GP, using the SC, and the one subsequently expressed by a Comprehensive Geriatric Assessment Team (CGA-Team); – to determine the construct-validity through the correspondence between some checklist items related to the 3 domains (physical, cognitive and social) and the three tools used by the CGA-Team; – to measure the instrument’s performance in terms of positive predictive value (PPV) and negative predictive value (NPV). Design: Cross-sectional study, with a final sample-size of 95 subjects. Setting: Two Community-Health Centers of Parma, Italy. Participants: Subjects aged 75 years old or more, with no disability and living in the community. Measurements: We compared the screening capacity of the GP using the SC to that one of CGA-Team based on three tests: 4-meter Gait-Speed, Mini-Mental State Examination and Loneliness Scale. Results: 95 subjects (51 women), with a mean age of 81±4 years were enrolled. According to GPs 34 subjects were frail; the CGA-Team expressed a frailty judgment on 26 subjects. The criterion-validity presented a Cohen’s k of 0.353. Construct-validity was also low, with a maximum contingency-coefficient of 0.19. The analysis showed a PPV of 58.1% and a NPV equal to 84.6%. Conclusions: Our data showed a low agreement between the judgements of GP performed by SC and  CGA-Team. However, the good NPV suggests the applicability of SC for screening activities in primary-care.

Key words: Ageing, frailty, multimorbidity, integrated care, sunfrail.



Bio-psycho-social model of frailty

Frailty is a condition of vulnerability to adverse events (1), traditionally considered a clinical entity; given its multidimensional nature (2), authors have proposed the bio-psycho-social model of frailty (2, 3). According to this approach, the assessment of frailty requires a comphrehensive analysis of physical-functional, socio-environmental-economic, educational and psychological contributors (3). Studies underline the reversible nature of frailty and suggest the need for interventions able to slow down the progression towards disability (4).

Identification of frailty

Although numerous tools are already available, there is no recognized gold-standard in the literature (3). Most of the istruments are also targeting one-dimension/domain, are difficult to be administered with numerous items and scores calculation and are often targeting advanced-frailty and disability. All these factors explain why none is currently and widely used in the daily practice.
An approach based on initial screening by the General Practitioner (GP) seems useful [4], especially if followed by Comprehensive Geriatric Assessment (CGA) which is the key step for the implementation of an integrated management (5, 6).
However, the tools currently available are not suitable for satisfying the needs of the GPs and most of them haven’t been validated for use in primary care (5).
An exception is the EASY-Care-TOS tool (5, 6), designed to be used in a complex two-phase model, where the GP makes a judgment following a 14 item checklist. However, in case of «uncertain» patients, the instrument requires the appliication of a second part composed of 49 items to make posssible the final judgment of frailty (6).

Sunfrail checklist

The Sunfrail checklist (SC) was developed following the standard methodology used for creating questionnaires (7-9), as part of a project funded by the third Health Program 2014-2020 of the European Commission. It was built by an international group, composed of geriatricians, sociologists, and public health experts.
This study aimed at validating the SC in primary care, in order to verify its discriminating capacity of identifying patients requiring CGA. We hypothesize that the GP, by using Sunfrail, will be able to identify individuals at risk of frailty.



The primary objective was to measure the concordance between the two judgments of frailty (criterion validity), the one formulated by the GP, using the SC, and the one expressed by a Comprehensive Geriatric Assessment Team (CGA-T) using three tools (4m-Walking Test, Mini-Mental State Examination, Loneliness-Scale). These tests were chosen because considered as gold standard in the physical, neuropshycological and socio-economic domain, respectively.
The secondary objectives were:
– to determine the construct validity through the correspondence between some SC items related to the 3 domains and the outcomes of 3 tools (1 per domain) used by the CGA-T.
– to measure the predictive ability of SC in terms of positive predictive value (PPV) and negative predictive value (NPV).

Study design

Descriptive observational study, with transversal enrollment and prospective method on data collection.

Target population

Community-dwelling older persons with no disability evaluated by GP’s. Since patients who benefit most from screening for frailty in primary care are usually very old people (3), those aged 75 or over, a category at greatest risk of frailty, were enrolled in the Study.

Sunfrail Checklist development

A literature review was performed during the time period 2015-2016, focusing on manuscripts concerning community-dwelling older persons. The group identified a set of items selected from existing tools, especially the Edmonton Frailty Scale (10), the Tilburg Frailty Indicator (11), and the Gerontopole Frailty Screening Tool (12) all inspired to the biopsychosocial model of frailty. Items were discussed with experts of Frailty, in particular with European Working Group on Frailty of the European Union Geriatric Medical Society. After that, SC was translated from English into Italian, French, Polish, Spanish and backtranslated. The verification of the understandability and comprehensibility of the tool was performed with professionals, community actors, caregivers and beneficiaries. Finally, nine items were selected: 5 in the physical domain, 2 in the neuropsychological domain and 2 in the socio-economic one.

Comprehensive Geriatric Assessment as the comparator

Given the lack of an unanimous gold-standard screening tool adopting the bio-psycho-social-model (3), it was decided to compare the GP judgement with the one formulated by the CGA-T, and based on the administration of three tests, selected for their role as gold standard as referenced in the literature (6).
The 4m-walking test to address the physical frailty, with a 5-second cut-off score (13); the Mini-Mental State Examination (MMSE) for the evaluation of the cognitive status, with a cut-off of ≤24 points suggesting cognitive impairment (14); the UCLA-Loneliness Scale (UCLA-LS), which uses a cut-off of ≥25 to indicate a greater perceived sense of loneliness (15).
The CGA-T was composed by a geriatrician, a nurse and a social assistant (16).

Setting and procedures

The study was carried out in two Community Health Centers of two rural areas in Parma, preceded by 3-hour education training.
Subjects who met eligibility criteria were offered to participate. Disability was assessed by GPs, verifying the presence of any social-assistance paths activated. After the inclusion, the GP using the SC and the CGA-T produced their judgment, independently.


Assuming a degree of agreement, measured with the Cohen’s k index, higher than 0.70, a type I error of 0.05 and a test power of 80%, the minimum size was 88 patients. Estimating a 10% drop-out rate, we planned to recruit 97 subjects.

Statistical analysis

Cohen’s kappa was used to evaluate the agreement between the two judgments, assessed with the categorization proposed by Altman (17).
To measure the construct validity, the Pearson x2 test was used and the strength of the relation was interpreted according to the following Cohen’s criterion (18).
Furthermore, the predictive capacity was evaluated using the Positive-Predictive-Value (PPV) and the Negative-Predictive-Value (NPV).


Characteristics of the participants

GPs enrolled 122 subjects, but due to a 22% drop-out, we had complete data for the analysis for 95 patients: these subjects had characteristics superimposable to those of the total sample (table 1).

Table 1 Characteristics of the study population

Table 1
Characteristics of the study population

Table 2 and Figure 1 indicate the distribution of affirmative answers to the questions in the SC, divided by the GP’s judgment.

Table 2 Distribution of affirmative answers to the questions in the SUNFRAIL checklist divided by the GP’s judgment (% of column)

Table 2
Distribution of affirmative answers to the questions in the SUNFRAIL checklist divided by the GP’s judgment (% of column)

*Question 8 and 4, were «turned

Figure 1 Positive and negative answers to single checklist items allowing the final judgement of frailty by GP (N=122)

Figure 1
Positive and negative answers to single checklist items allowing the final judgement of frailty by GP (N=122)

Criterion validity (Primary Endpoint)

GPs suspected a frailty condition in 31,1% of subjects, CGA identified 27% of subjects as frail (table 1).
The degree of agreement between GP and CGA is 66.3%, with a Cohen k of 0.353 [95% CI: 0.19-0.52, p <0.001], indicating a low agreement.

Construct validity

The 4m-walking test showed a contingency coefficient of 0.12 with the question 3, and 0.18 with the question 5; MMSE displayed a coefficient of 0.17 with the question 6, while UCLA-LS had a coefficient of 0.19 with the question 7 and 0.14 with the question 8 (table 3).

Instrument performance

The analysis of the instrument’s performance, determined by excluding the cases for which the CGA did not provide a certain suspicion, showed NPV equal to 84.6% (table 4).

Table 3 Construct validity

Table 3
Construct validity

Table 4 Instrument performance measurements

Table 4
Instrument performance measurements



GPs suspected a frailty condition in 31.1% of subjects. These data are consistent with EASY-Care TOS that estimated in Nimega, a similar area in terms of population sample and rural areas, a frailty prevalence of 39.4% (6). The concordance (k=0.35) was lower compared to instruments like the EASY-Care TOS (k=0.63). This can be due to many factors: firstly, an exaustive CGA cannot be the administration of 3 simple tests, but it must be customized to the patient’s needs (4). This can also explain the uncertain judgments formulated by CGA-T. The SC is more an alert questionnaire rather than a screening tool and is more oriented towards an earlier state of frailty than EASY-Care TOS, which is more devoted to address the condition of mobility-disability. Although the education training was carried out at the GPs, the concept of frailty has become just recent matter of education in the Medicine Courses and the overlapping and interchangeability with multimorbidity in the GP perspective cannot be excluded (19). Furthermore, the Sunfrail was not designed to be specifically used by the GP and just for clinical purpose, but also by other “actors” in settings closer to the user’s life context. The percentages of subjects identified as frail during screening activities can be greater in social-health rather than specifically clinical settings (20). Future studies should focus on the applicability of SC in these settings, with the potential administration by non-medical personnel. The low agreement between the judgements suggests that frailty assessment by GP using SC is far to replace the CGA, which remains the best method to assess and confirm the frailty status (4). Construct validity shows a small relationship between the 5 items of the SC and the tests used for the CGA (18). This may be due to a discrepancy between these tests and the meaning of some SC’s questions. Regarding the question 3, recent studies have linked the 0.8 m/s cut-off to a condition of mobility-disability, and not of frailty (21). Moreover, although MMSE is the most widely used screening tool, it isn’t sensitive for mild cognitive impairments. This may have affected the agreement between this test and question 6 (22). The question 8 cannot also competely be captured by the UCLA-LS: family support, which offers instrumental support, can be less important than peers support (23). The exclusion of non-frail subjects (NPV) with correct exclusion of CGA, is crucial for assessing the performance of the instrument. Any screening of elderly subjects by the GP, must have a high NPV (>75%). The analysis here presented showed a NPV equal to 84.6%, confirming the goodness of SC (24).
Despite similar performance in terms of NPV, the SC offers advantages in comparison with other tools such as care assessment need (CAN) (24). In fact SC requires less time for the administration, is one-phase model, it’s validated for use in primary and it’s more devoted to address the risk of early-frailty condition than advanced-frailty and disability. Other tools, including GSFT, as reported in recent systematic reviews, have not been considered gold standard at least in the specific setting of primary care.
This study has some limitations.
The pre-set sample size was not reached due to a high percentage of drop-out. This inconvenience was caused by the presence of two clinics in one center, with subjects who didn’t reach the CGA-T.
The education carried out at the GPs of the 2 recruiting centers was inhomogeneous, and this may have caused differences in the approach of frailty concept.
Disability was not assessed by ADLs and IADLs, but only by GPs judgement.
Given also the specific rural nature of the setting, the complete translation of our findings in different areas cannot be guaranted.
In conclusion, the concordance between GP and CGA-T judgement of frailty was very low. This suggests that the SC cannot replace the CGA. However, due to the high NPV the SC seems to be an excellent screening tool of frailty, thanks to its high discriminating power of false negatives. Its wide use by the GP could improve the appropriateness in the request of CGA.

Acknowledgements: We would like to thanks all the GPs and the participants involved.
Funding: The SUNFRAIL (project 664291), has received funding from the European Union’s Health Programme (2014-2020).
Conflicts of Interest: All the authors have nothing to disclose.
Ethical standards: The project was approved by the local ethics committee on 12 december 2017, protocol number 44605.


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