Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT05199207 |
Other study ID # |
20-AOI-11 |
Secondary ID |
|
Status |
Completed |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
January 11, 2022 |
Est. completion date |
July 5, 2022 |
Study information
Verified date |
July 2022 |
Source |
Centre Hospitalier Universitaire de Nice |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
Muscle failure (sarcopenia or dynapenia) is a factor of frailty and therefore, ultimately, of
loss of autonomy in the elderly. Currently, no biomarker of muscle failure has a high
sensitivity, specificity and positive predictive value. Several results, although
preliminary, suggest that metabolomics could facilitate the early identification of frail
patients, allowing the implementation of primary prevention strategies. Untargeted
high-resolution metabolomics analysis would identify discriminative biomarkers and biological
mechanisms associated with frailty. Finally, the hypothesis that metabolic signatures can be
identified as risk factors for the development of age-related dynapenia should be tested in a
longitudinal design.
Description:
Sarcopenia is defined as decreased muscle strength and low muscle quantity or quality.
Screening and management of sarcopenia was modified in early 2019 by the European Working
Group on Sarcopenia in Older People (EWGSOP) with the creation of the F-A-C-S
(Find-Assess-Confirm-Severity) protocol. The search for sarcopenia (Find) is done during the
interrogation of the patient expressing symptoms that may be related to the loss of muscle
mass, such as falls, asthenia, weight loss, decreased walking speed, or difficulty getting up
from a chair. A simple self-report questionnaire (SARC-F) has been created to facilitate
screening. Clinical suspicion of sarcopenia requires the performance of a functional
assessment (Assess), using for example grip strength.and the chair lift test to look for
decreased muscle strength. A pathological result already allows the suspicion of sarcopenia
and the introduction of secondary prophylactic measures. Diagnostic confirmation of
sarcopenia (Confirm) can be obtained by demonstrating a decrease in muscle mass by one of
four validated techniques: magnetic resonance imaging (MRI), computed tomography (CT),
dual-energy X-ray absorptiometry (DXA) (Buckinx et al., 2018), or bioimpedancemetry (Rossi et
al., 2014). Sarcopenia is considered severe (Severity) if there is a decrease in overall
physical performance objectified by physical tests such as the Time Up and Go Test, walking
speed, or the Short Physical Performance Battery (SPPB) test.
The development and validation of a single biomarker could be a simple and cost-effective way
to diagnose and monitor individuals with sarcopenia. Potential biomarkers could include
markers of neuromuscular junction, muscle protein turnover, behaviorally mediated pathways,
inflammation-mediated pathways, redox-related factors, and hormones or other anabolic factors
(Curcio et al., 2016). However, due to the complex pathophysiology of sarcopenia, it is
unlikely that a single biomarker can identify the disease in the heterogeneous population of
young and old. Instead, the development of a panel of biomarkers should be considered,
including potential serum markers and tissue markers. Implementing a multidimensional
methodology for modeling these pathways could provide a means to stratify risk for
sarcopenia, facilitate identification of worsening of the condition, and track treatment
efficacy.
In the context of physical frailty and sarcopenia, the study of dynamic metabolic responses
to stressors and the characterization of the biochemical pathways involved are particularly
relevant, as this condition is closely associated with metabolic disorders. Disturbances in
protein and amino acid metabolism may contribute substantially to the pathophysiology of
sarcopenia.
The hypothesis that metabolic signatures can be identified as risk factors for the
development of age-related sarcopenia needs to be tested in a longitudinal design.
The main objective is to Identify metabolomic signatures of muscle failure in the elderly.