ReviewSarcopenia – The search for emerging biomarkers
Graphical abstract
Introduction
Lean body mass, in particular, skeletal muscular mass (SMM), represents one of the three major components of body composition, which also includes fat and bone mass. All components are highly important for normal physiology and metabolism, and deviations from normal values, in particular, related to age, are often associated with various pathological conditions. The health risks and complications caused by obesity and bone loss, as well as osteoporosis are well established, and the implications of age-related SMM loss have recently attracted increasing attention (Berger and Doherty, 2010).
Skeletal muscle is the largest organ in the human body and contributes up to 60% of the total body weight in young non-obese adults. After the age of 30, about 0.5–1% of SMM is lost per year, with a dramatic acceleration of the rate of decline after the age of 65 (Kyle et al., 2001, Melton et al., 2006). On average, 5–13% of older persons over 60 have low SMM, with the prevalence increasing to as high as 50% in persons over the age of 80 (Morley et al., 2014). Muscle functional capacity (strength and power) also decreases with advancing age, and even to a greater degree than SMM (Newman et al., 2003.) This age- related reduction in SMM and function is referred to as “sarcopenia” (from Greek sarx “flesh” and penia “loss”). It is associated with limitations of physical performance in older people, leading to increased risk of falls, fractures, hospitalization, dependency, frailty, profound metabolic consequences, and mortality (Abellan van Kan, 2009, Janssen, 2011, Liu et al., 2014). Moreover, although sarcopenia is generally observed and diagnosed in older adults, it may be present in different clinical settings, including critical illness. Recent data also demonstrated that sarcopenia in an intensive care unit negatively impacts patients’ outcomes and may promote functional disability in the long-term after hospital discharge (Muscaritoli et al., 2013).
Sarcopenia has been reported to affect more than 40% of elderly individuals >70 years of age, approximately 50 million people worldwide. Taking into account the increase in life expectancy that has occurred during the last decades, this number is estimated to increase 10-fold in the year 2050 (Hida et al., 2013). However, not all the individuals display the same rate of SMM loss, and considerable variation in SMM exists among individuals of the same age (Fig. 1). An important open question is what are the major factors that cause this variation? It is clear that a variety of intrinsic and extrinsic sources are involved in this situation, including (but not limited to) a mixture of life style as well as genetic and metabolic factors.
Currently the contribution of the genetic and familial factors to a variation of SMM is well established, and heritability estimates in studies reach 40% or even higher (Garatachea and Lucia, 2013, Korostishevsky et al., 2015, Nabulsi et al., 2013). However, replicated and confirmed specific genetic polymorphisms are rare and are able to explain only a minor part of this variation (Livshits et al., 2012, Rothammer et al., 2014, Urano et al., 2014). As such, no solid evidence currently exists supporting an “unfavorable” genotype associated with accelerated sarcopenia or frailty, or a combination of molecular-genetic factors explaining the significant part of the inter-individual variation in SMM.
Likewise, although the term “sarcopenia” has become widespread, the criteria for its definition and clinical diagnosis are not yet clear-cut and vary among studies and experts. Nevertheless, there is a consensus that sarcopenia is a multifactorial syndrome (Berardi et al., 2014, Lauretani et al., 2014, Santilli et al., 2014) and correlates include endocrine dysfunction and inflammation (Lang et al., 2010, Malafarina et al., 2012). It also became obvious that beyond the basic action of mechanical contraction, the skeletal muscles are involved in endocrine and metabolic activities such as glucose, glycogen, and lipid metabolism (Pedersen and Febbraio, 2012) and perform certain immunogenic functions (Nielsen and Pedersen, 2008).
Muscle-derived cytokines, myokines, such as myostatin, interleukin-6 (IL-6), irisin, and others were shown to exert auto-, para- and endocrine actions (Pedersen, 2013). They mediate crosstalk between muscle and other tissues, mainly bone, fat, and liver. Their effects include regulation of systemic inflammation, immune function, energy metabolism, insulin sensitivity, cell growth, myogenesis, osteogenesis, and others (Demontis et al., 2013, Iizuka et al., 2014, Pedersen, 2013, Raschke and Eckel, 2013). In addition, a number of factors related to chronic diseases and aging such as oxidative stress, neurodegeneration, anorexia, insulin resistance, mitochondrial dysfunction, and DNA mutations may accelerate sarcopenia (Biolo et al., 2014, Sakuma et al., 2015).
These findings indicate that strategies aimed at diagnosing sarcopenia and counteracting its development and progression have to cover multiple and not yet well-defined factors, thus introducing challenges in searching for sarcopenia biomarkers. To date, although numerous biomarkers have been suggested to be associated with SMM and function, only a few are in fact solely muscle-specific biomarkers. Moreover, correlating their blood levels to sarcopenia parameters is still a controversial issue (Cesari et al., 2014, Lippi et al., 2014).
In searching for potentially reliable sarcopenia biomarkers, we selected several molecules expressed by skeletal muscles and divided them into five clusters (Fig. 2). The rationale underlying this stratification is based on the supposed capability of the members of each cluster to significantly affect different aspects of muscle growth and function, finally leading to sarcopenia. This review was prompted by an analysis of these molecules’ mechanisms of action, their interrelationships in sarcopenia pathogenesis, and their role as emerging sarcopenia biomarkers. There are, of course, a variety of additional mechanisms potentially involved in sarcopenia pathogenesis such as mitochondria dysfunction, autophagy, apoptosis, endocrine factors, nutritional status, and immobility. These additional mechanisms have not been considered in the present paper but they have been comprehensively discussed by others (Cruz-Jentoft et al., 2014, Ilich et al., 2014, Kob et al., 2015, Malafarina et al., 2012, Marzetti et al., 2013, Prado and Heymsfield, 2014, Sakuma et al., 2015).
Section snippets
Definition of sarcopenia
As mentioned, sarcopenia remains a poorly defined phenomenon, even referring to it as a “describing rather than defining condition” (Alchin, 2014). This perhaps explains a huge variance in the estimates of sarcopenia prevalence, ranging from ≤10% (Dam et al., 2014) to ≥70% (Batsis et al., 2014) in individuals older than 60 years, thus, again emphasizing the urgency in clearly defining the sarcopenia cutoff points.
The term sarcopenia was first introduced by Rosenberg (1989), referring
Sarcopenia biomarkers
Sarcopenia biomarkers should fit the acceptable biomarker definition as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” (BDWG, 2001). Meeting such a requirement is not a simple task. Currently, it has become clear that muscle dysfunction, a main component of sarcopenia, along with muscle loss, embraces not only contractile impairment but also involves
Concluding remarks
Sarcopenia is a major public health problem that is anticipated to grow as our population ages. Unfortunately, we are still at an early stage of understanding the molecular mechanisms leading to sarcopenia. Clearly, deciphering these mechanisms is essential for achieving scientific progress in this area and for utilizing molecular research for the early identification of sarcopenia and for creating the basis for therapeutic interventions for this clinical entity. Based on the latest
Acknowledgement
This study was supported by Israel Science Foundation (grant #1018/13) to GL.
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