Biomarkers for physical frailty and sarcopenia: state of the science and future developments

Abstract

Physical frailty and sarcopenia are two common and largely overlapping geriatric conditions upstream of the disabling cascade. The lack of a unique operational definition for physical frailty and sarcopenia and the complex underlying pathophysiology make the development of biomarkers for these conditions extremely challenging. Indeed, the current definitional ambiguities of physical frailty and sarcopenia, together with their heterogeneous clinical manifestations, impact the accuracy, specificity, and sensitivity of individual biomarkers proposed so far. In this review, the current state of the art in the development of biomarkers for physical frailty and sarcopenia is presented. A novel approach for biomarker identification and validation is also introduced that moves from the 'one fits all' paradigm to a multivariate methodology.

Keywords: Ageing; Circulating markers; Disability; Imaging; Multivariate modelling; Physical performance.

Figure 1

Possible trajectories of physiological reserve during ageing. In the case of accelerated ageing, the decline in physiological reserve is steeper relative to the successful aging scenario. In this latter case, the development of physical frailty and sarcopenia may be compressed towards the end of life. Critical events (e.g. intercurrent illnesses, hospitalizations, and falls) may cause sudden decreases in physiological reserve, which correspond to proportional changes in biomarker levels. The dashed lines identify the diagnostic cutoffs of biomarkers. The yellow and the red areas correspond to clinically manifest physical frailty/sarcopenia and disability, respectively.

Figure 2

Example of a multivariate control chart (based on PCA or PLS squared X-residuals). The circles depict the resultant of multidimensional assessments over time. The dashed lines correspond to the 95% and 99% confidence limits of the corresponding statistics. Circles above the control limits indicate that the subject is departing from his/her ‘normal operating conditions’ and may account for the onset of an adverse health-related event (e.g. mobility disability). The building and inspection of a multivariate control chart could allow detecting the onset of a critical condition at a very early stage and the planning of timely interventions.