Biomarkers of Sarcopenia: Current Status and Future Perspectives

ABSTRACT

Sarcopenia is an age‐related skeletal muscle disorder characterized by progressive declines in muscle mass, strength, and physical function, which profoundly impair quality of life in older adults. Although current clinical guidelines propose various diagnostic approaches and cutoff values, considerable heterogeneity among criteria and assessment tools continues to pose challenges for the accurate and early diagnosis of sarcopenia. In recent years, an increasing number of studies have identified potential biomarkers associated with sarcopenia, which can be broadly classified into biochemical, imaging‐based, and physical performance–related categories. The identification of these biomarkers has improved diagnostic accuracy, provided additional means for monitoring disease progression, and opened new avenues for therapeutic intervention. This narrative review aims to summarize currently established and emerging biomarkers related to sarcopenia, with a particular focus on their biological relevance, clinical applicability, and limitations. Furthermore, potential directions for future research are discussed to facilitate the development of integrated, multimodal biomarker strategies for the early detection, risk stratification, and personalized management of sarcopenia.

In this review, we summarize the various biomarkers discovered in recent years, including biochemical, imaging, and physical testing markers. We analyze their advantages and disadvantages and propose potential ways to improve the diagnostic accuracy of biomarkers, as well as future research directions.

1. Introduction

Sarcopenia, first proposed by Rosenberg in 1989, refers to the progressive, age‐related decline in skeletal muscle mass and function [1]. The International Working Group on Sarcopenia defines sarcopenia as a geriatric syndrome characterized by a reduction in skeletal muscle mass and/or muscle strength or physical performance associated with aging [2]. With the acceleration of global population aging, sarcopenia has emerged as a major public health concern in geriatric medicine.

Recent epidemiological studies in China have reported that the prevalence of sarcopenia among community‐dwelling older adults ranges from 8.9% to 38.8%, with a higher prevalence observed in men than in women. The prevalence increases markedly with advancing age and can reach up to 67.1% in individuals aged 80 years and older. Moreover, regional differences have been reported, with higher prevalence rates in western China compared with eastern regions. Globally, approximately 50 million individuals are currently affected by sarcopenia, and this number is projected to increase to 500 million by 2050 [3]. A substantial body of evidence indicates that sarcopenia significantly increases the risk of falls and fractures, contributes to declines in activities of daily living, and is closely associated with adverse health outcomes such as cardiovascular disease, respiratory disorders, and cognitive impairment. Consequently, sarcopenia severely compromises quality of life in older adults and imposes a considerable burden on healthcare systems.

To standardize disease identification and management, academic organizations in Asia, Europe, and China have successively proposed diagnostic algorithms for sarcopenia based on skeletal muscle mass, muscle strength, and physical performance. However, although computed tomography (CT) and magnetic resonance imaging (MRI) are regarded as the gold standards for assessing skeletal muscle mass and muscle quality and are noninvasive with high accuracy, their routine clinical application still has several limitations. These include high cost, limited accessibility, relatively long examination times, difficulty in repeated dynamic monitoring, and a limited ability to reflect functional changes and molecular‐level abnormalities [4]. In addition, during the early stages of the disease, reliance on imaging‐based assessments alone may fail to capture subtle pathological changes associated with the onset and progression of sarcopenia, thereby limiting early screening and risk stratification.

Against this background, the identification of objective and reliable biomarkers that reflect the onset and progression of sarcopenia has become a major focus of research. Biomarkers are defined as objectively measurable indicators of normal biological processes, pathogenic processes, or responses to therapeutic interventions [5]. In the context of sarcopenia, biomarkers have the potential to elucidate the molecular and biological mechanisms underlying changes in muscle mass, strength, and function, thereby complementing conventional diagnostic approaches.

Therefore, a systematic synthesis of current evidence on sarcopenia‐related biomarkers is of substantial importance for improving diagnostic strategies, enabling early detection and longitudinal monitoring, and providing a theoretical basis for individualized prevention and intervention. This review summarizes recent advances in biomarkers associated with sarcopenia and discusses their potential clinical applications in relation to disease pathophysiology. To provide an overall conceptual framework, Figure 1 illustrates a multilevel integration of the major biological mechanisms involved in sarcopenia and the corresponding categories of biomarkers discussed in this review.

FIGURE 1.

A multilevel framework of biomarkers associated with sarcopenia.

2. Search Strategy

A systematic literature search was conducted using PubMed, China National Knowledge Infrastructure (CNKI), and the Wanfang database to identify studies focusing on biomarkers of sarcopenia. Search terms included “sarcopenia,” “biomarkers of sarcopenia,” and “muscle loss biomarkers,” in both English and Chinese. Priority was given to studies published within the past 7 years, while earlier landmark studies were included when deemed highly relevant.

Eligible publications comprised original research articles and narrative or systematic reviews. Study populations primarily included individuals recruited from referral centers, hospitals, or community‐based cohorts, with explicit evaluation of sarcopenia or muscle health–related outcomes. Case reports, studies lacking assessments of muscle mass, strength, or physical performance, and articles with limited relevance to the topic of sarcopenia biomarkers were excluded. The selected studies provide the evidence base for the discussion of sarcopenia‐related biomarkers presented in this review.

3. Inflammation and Immune Dysregulation

Sarcopenia is widely regarded as a geriatric syndrome that develops in the context of chronic low‐grade inflammation associated with aging, commonly referred to as inflammaging. Persistent systemic inflammation promotes skeletal muscle catabolism by activating the ubiquitin–proteasome pathway and the autophagy–lysosome system, while simultaneously suppressing anabolic signaling pathways involved in muscle protein synthesis. In addition, inflammatory mediators exacerbate insulin resistance and impair muscle regeneration, thereby playing a pivotal role in the onset and progression of sarcopenia [6]. Consequently, biomarkers reflecting inflammatory burden and immune dysregulation have been proposed as important candidates for assessing sarcopenia risk and disease progression.

3.1. Systemic Immune‐Inflammation Index (SII)

The systemic immune‐inflammation index (SII) is a composite biomarker reflecting systemic inflammatory and immune status. Chronic low‐grade inflammation is recognized as a key pathophysiological driver of sarcopenia, as sustained inflammatory activation can promote protein degradation, inhibit protein synthesis, and aggravate insulin resistance, ultimately leading to declines in skeletal muscle mass and function.

First proposed by Hu et al., SII is calculated as the product of platelet count and neutrophil count divided by lymphocyte count (SII = P × N/L) [7]. By integrating multiple peripheral blood cell parameters closely associated with inflammation, SII has recently been explored as a potential indicator of sarcopenia risk. A study based on data from the National Health and Nutrition Examination Survey (NHANES), including 7258 individuals aged 18–59 years, demonstrated a positive association between SII levels and sarcopenia risk. This association remained significant after adjustment for age, sex, race, chronic kidney disease, hypertension, diabetes, body mass index, and dyslipidemia. In a cohort of 632 adults aged ≥ 65 years, Esra et al. identified an optimal SII cutoff value of > 765 for diagnosing sarcopenia, with a negative predictive value of 88.1% and a specificity of 88% [8].

Compared with individual inflammatory markers, SII offers advantages including ease of calculation, low cost, and good reproducibility, making it suitable for use in clinical practice and epidemiological studies. However, current evidence linking SII to sarcopenia is limited, and most available studies are cross‐sectional in design. The stability of SII across different populations, its longitudinal predictive value, and its ability to reflect disease progression remain to be clarified. At present, SII may be more appropriate as an adjunctive indicator of inflammatory burden, with potential utility when incorporated into multimarker models for sarcopenia diagnosis or risk stratification.

3.2. Extracellular Heat Shock Protein 72

Heat shock proteins (Hsps) are a family of highly conserved molecular chaperones that are constitutively expressed under basal conditions and inducible under various stress stimuli. They play a critical role in maintaining cellular proteostasis and protecting against stress‐induced damage. According to the free radical theory of aging, increased production of reactive oxygen species (ROS) with advancing age exceeds antioxidant defense capacity, leading to oxidative damage to proteins, lipids, and DNA, and ultimately contributing to tissue dysfunction [9]. Hsps mitigate the accumulation of damaged proteins by facilitating protein repair or promoting degradation of irreversibly damaged proteins, thereby exerting protective effects against age‐related cellular decline.

Hsp72, a key member of the Hsp70 family, can be released into the circulation as extracellular heat shock protein 72 (eHsp72) [10]. Because eHsp72 can be detected in peripheral blood, it is more clinically accessible than intracellular Hsps and has been proposed as a potential biomarker of sarcopenia. In a community‐based study involving 665 older adults aged 65–96 years, plasma eHsp72 levels were positively correlated with age and inflammatory markers such as tumor necrosis factor‐α (TNF‐α) and negatively correlated with muscle mass, handgrip strength, and 5‐m gait speed [11]. These findings suggest that elevated eHsp72 levels may reflect chronic inflammatory burden and muscle functional decline in older individuals.

Given that increased ROS production is considered a major driver of muscle aging and sarcopenia, and is closely linked to protein and DNA damage, further investigation into the relationship between eHsp72 and oxidative stress in individuals with sarcopenia may help clarify its pathophysiological significance and potential utility as a biomarker.

3.3. Inflammatory Cytokines

Chronic inflammation contributes to skeletal muscle wasting through the activation of multiple signaling pathways and represents a key mechanism underlying the imbalance between muscle protein synthesis and degradation in sarcopenia. Numerous studies have demonstrated that serum levels of interleukin‐6 (IL‐6) and tumor necrosis factor‐α (TNF‐α) are inversely associated with muscle mass and muscle strength in healthy older adults. Elevated concentrations of these pro‐inflammatory cytokines are commonly observed in aging populations and are considered important contributors to age‐related declines in muscle mass and strength [12].

In addition, older adults with sarcopenia exhibit dysregulation of pro‐ and anti‐inflammatory responses. Compared with nonsarcopenic individuals, those with sarcopenia show higher levels of IL‐6, IL‐10, and an increased IL‐6/IL‐10 ratio [13]. Relative to single cytokine measurements, cytokine ratios may better reflect overall inflammatory status while reducing the influence of interindividual variability and transient effects of acute inflammation or physical activity. Accordingly, composite indicators such as the IL‐6/IL‐10 ratio may be more suitable than individual cytokines as adjunctive biomarkers reflecting the inflammatory milieu associated with sarcopenia.

4. Mitochondrial Function and Genetic Regulation

Mitochondria are essential organelles responsible for maintaining energy metabolism and redox homeostasis in skeletal muscle, and mitochondrial dysfunction is widely regarded as one of the key molecular bases underlying sarcopenia. With advancing age, declines in mitochondrial biogenesis, reduced efficiency of oxidative phosphorylation, and increased production of reactive oxygen species (ROS) lead to an insufficient energy supply to muscle fibers and the accumulation of oxidative damage [14]. In parallel, genetic background and posttranscriptional regulatory mechanisms, such as microRNAs (miRNAs), play critical roles in regulating muscle growth, differentiation, and metabolic homeostasis. Molecular alterations associated with mitochondrial damage signaling and dysregulated genetic control may emerge early during the development of sarcopenia.

4.1. Circulating Cell‐Free Mitochondrial DNA (Ccf‐mtDNA)

Circulating cell‐free mitochondrial DNA (ccf‐mtDNA) refers to fragments of mitochondrial DNA released into the circulation from damaged or apoptotic cells. Because mtDNA contains unmethylated CpG motifs similar to bacterial DNA, circulating mtDNA can act as damage‐associated molecular patterns (DAMPs) and potentially activate inflammation‐related signaling pathways. Although ccf‐mtDNA is defined as freely circulating mtDNA, it may be taken up or bound by peripheral blood mononuclear cells (PBMCs); therefore, mtDNA detected within PBMCs may also reflect systemic exposure to circulating mtDNA.

A study involving 108 patients undergoing maintenance hemodialysis (MHD) investigated the association between circulating ccf‐mtDNA levels and sarcopenia. The results demonstrated that patients with sarcopenia exhibited significantly higher levels of ccf‐mtDNA in the circulation as well as in mitochondria‐depleted PBMCs compared with non‐sarcopenic patients. Furthermore, the mRNA expression levels of downstream inflammation‐related molecules, including toll‐like receptor 9 (TLR9) and interleukin‐6 (IL‐6), were significantly elevated in PBMCs from patients with sarcopenia [15]. These findings suggest activation of innate immune–related pathways in sarcopenia. However, this association does not directly establish ccf‐mtDNA as the primary driver of inflammation, as pro‐inflammatory cytokines originate from multiple innate immune cell types. Further mechanistic studies are required to clarify the causal relationship between ccf‐mtDNA and inflammatory activation in sarcopenia.

4.2. MicroRNAs (miRNA)

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the post‐transcriptional level and play crucial roles in skeletal muscle growth, differentiation, and metabolic homeostasis. A subset of miRNAs exhibiting muscle‐specific or muscle‐enriched expression patterns are collectively referred to as muscle‐related miRNAs (myomiRs). Identified members of the myomiR family include miR‐208a, miR‐208b, miR‐499, and the more recently studied miR‐486 [16]. Accumulating evidence indicates that miRNAs are involved not only in the regulation of structural muscle proteins and growth signaling pathways but also in mitochondrial biogenesis and energy metabolism, thereby contributing to age‐related declines in muscle function.

A study of 77 community‐dwelling older adults demonstrated that circulating miR‐486 (c‐miR‐486) levels were positively correlated with body mass index (BMI), lean mass index (LMI), and skeletal muscle mass index (SMI), with a particularly strong association observed between c‐miR‐486 and SMI. Further comparisons among individuals without sarcopenia, with presarcopenia, and with sarcopenia revealed a progressive decline in c‐miR‐486 levels across disease stages. Receiver operating characteristic (ROC) curve analysis showed that c‐miR‐486 exhibited moderate diagnostic performance for sarcopenia, with a sensitivity of 78%, a specificity of 61.1%, and an area under the curve (AUC) of 0.708 [17].

Notably, the same study evaluated associations between multiple circulating miRNAs and sarcopenia‐related phenotypes, revealing that different miRNAs were selectively associated with muscle mass or muscle strength. These findings suggest that individual miRNAs may reflect specific aspects of sarcopenia rather than the condition as a whole. Consequently, diagnostic models integrating multiple miRNAs that capture distinct sarcopenic phenotypes may offer greater clinical utility than single‐miRNA biomarkers.

4.3. Caveolin‐1 (CAV1), Cav1 G14713A

Caveolin‐1 (CAV1) is a structural protein localized to plasma membrane microdomains and participates in multiple signal transduction pathways. It plays a regulatory role in maintaining skeletal muscle cell integrity and metabolic homeostasis. Evidence suggests that CAV1 may indirectly influence mitochondrial function by modulating insulin signaling, energy metabolism, and cellular stress–related pathways, and its dysregulation has been implicated in skeletal muscle dysfunction and age‐related alterations.

Animal studies have shown that CAV1 deficiency leads to pronounced impairments in motor performance. Male CAV1⁻/⁻ mice exhibit structural abnormalities in skeletal muscle fibers, including tubular aggregate formation, mitochondrial proliferation and abnormal aggregation, and increased numbers of M‐cadherin–positive satellite cells, with these abnormalities worsening with age [18, 19]. These findings indicate that CAV1 deficiency not only compromises muscle structural stability but may also accelerate age‐related muscle functional decline through disrupted signaling and mitochondrial processes.

In human studies, an analysis involving 765 healthy individuals and patients with varying degrees of sarcopenia examined the association between CAV1 gene polymorphisms and sarcopenia risk. Among multiple CAV1 variants, the CAV1 G14713A polymorphism was significantly associated with sarcopenia in a Taiwanese population, with carriers of the A allele exhibiting a higher likelihood of developing sarcopenia and severe sarcopenia [20]. Additionally, a study including 44 young adults and 88 older adults across different stages of sarcopenia reported increased CAV3 expression in non‐sarcopenic and presarcopenic older individuals compared with younger participants, with a further increase observed in patients with sarcopenia [21]. Together, these findings suggest that caveolin proteins and related genetic polymorphisms may contribute to the development and progression of sarcopenia, although their precise mechanisms and clinical applicability require further investigation.

5. Anabolism and Endocrine Regulation

The maintenance of skeletal muscle mass depends on the dynamic balance between anabolic and catabolic processes, in which multiple hormones and growth factors play essential regulatory roles. During aging, declines in anabolic hormone levels and/or reduced sensitivity of their signaling pathways lead to diminished muscle protein synthesis and blunted responsiveness to nutritional and exercise stimuli. This phenomenon, commonly referred to as anabolic resistance, is considered a hallmark endocrine feature of sarcopenia. Accordingly, biomarkers related to hormonal status and anabolic signaling pathways may provide valuable insights into the metabolic state of sarcopenia and responses to intervention.

5.1. Growth Differentiation Factor‐15

Growth differentiation factor‐15 (GDF‐15) is a member of the transforming growth factor‐β (TGF‐β) superfamily and is classified as a stress‐responsive cytokine. Increasing evidence suggests that GDF‐15 is closely associated with enhanced oxidative stress and mitochondrial dysfunction during aging, and elevated circulating levels are thought to reflect adaptive responses to metabolic and inflammatory stress [22].

Animal studies have demonstrated that aging mice exhibit progressive declines in skeletal muscle mass and endurance accompanied by significant increases in circulating GDF‐15 levels. Notably, sustained physical exercise in aged mice markedly reduced GDF‐15 concentrations [23]. In human studies, an investigation involving 1305 healthy men and women aged 20–93 years reported that circulating GDF‐15 levels increased with age and were inversely associated with relative muscle strength. These findings indicate a close relationship between elevated GDF‐15 levels, reduced muscle strength, and impaired physical performance, while an active lifestyle may exert protective effects on muscle health through modulation of GDF‐15.

GDF‐15 has been proposed as a potential biomarker of sarcopenia, with a suggested cutoff value of 1541 pg/mL demonstrating moderate predictive value [24]. However, given that GDF‐15 levels can be elevated in various stress‐related and chronic disease states, its specificity for sarcopenia and applicability across different populations require further validation.

5.2. Myostatin

Growth differentiation factor‐8 (GDF‐8), commonly known as myostatin, is a highly conserved member of the TGF‐β superfamily and a key negative regulator of skeletal muscle growth [25]. Experimental studies have shown that myostatin deficiency results in pronounced muscle hypertrophy, whereas excessive myostatin expression leads to severe muscle atrophy [26, 27], underscoring its central role in maintaining muscle mass homeostasis.

In a study involving 20 patients aged ≥ 65 years who underwent total hip arthroplasty following osteoporotic hip fracture, serum myostatin levels were significantly reduced after 2 months of combined nutritional supplementation and rehabilitation therapy [28]. These findings suggest that myostatin is not only associated with the presence of sarcopenia but may also reflect improvements in muscle status during intervention.

Currently, several pharmacological inhibitors targeting the myostatin signaling pathway have been developed. Clinical trials have demonstrated increases in appendicular muscle mass following myostatin inhibition; however, consistent improvements in muscle strength, such as handgrip strength, have not been conclusively established [29]. Thus, myostatin may be more suitable as a biomarker of muscle mass changes and a potential therapeutic target, whereas its predictive value for functional outcomes remains uncertain.

5.3. Dehydroepiandrosterone

Dehydroepiandrosterone (DHEA) is a steroid hormone precursor secreted by the adrenal glands and can be converted within skeletal muscle into biologically active androgens and estrogens. Sex steroid hormones play a critical role in promoting protein synthesis and anabolic metabolism, thereby contributing to the maintenance of muscle mass and strength [30].

Animal studies have shown that aged mice exhibit significantly reduced cross‐sectional area of the tibialis anterior muscle along with marked declines in serum DHEA levels compared with younger mice, suggesting that age‐related muscle loss may be associated with decreased DHEA availability [31]. In a population‐based study of 478 postmenopausal women aged 50–90 years, serum DHEA levels were positively correlated with handgrip strength and gait speed and were significantly lower in individuals with sarcopenia than in those without sarcopenia [32].

Current evidence regarding the relationship between DHEA and sarcopenia has primarily focused on postmenopausal women, with limited data available for older men. Nevertheless, a study reported that men receiving daily supplementation of 50 mg DHEA for 6 months exhibited higher handgrip strength compared with placebo‐treated controls [33], suggesting a potential role for DHEA in regulating muscle function in men. Further studies are needed to clarify the suitability of DHEA as a biomarker for sarcopenia in male populations.

5.4. Insulin‐Like Growth Factor‐1

Insulin‐like growth factor‐1 (IGF‐1) is predominantly synthesized in the liver under stimulation by growth hormone (GH), although peripheral tissues such as bone, cartilage, and skeletal muscle can also produce IGF‐1 via autocrine and paracrine mechanisms [34]. IGF‐1 promotes muscle hypertrophy by activating anabolic signaling pathways involved in protein synthesis and suppresses muscle atrophy by inhibiting forkhead box O (FOXO) transcription factor–mediated catabolic pathways [35].

A study involving 168 patients with type 1 diabetes mellitus and 59 nondiabetic controls demonstrated that lower serum IGF‐1 levels were significantly associated with sarcopenia in individuals with Type 1 diabetes. Notably, IGF‐1 levels were independently correlated with skeletal muscle mass index (SMI) but not with handgrip strength or gait speed [36]. Given that diabetes‐related complications such as peripheral neuropathy may confound associations with functional outcomes, caution is warranted when interpreting the relationship between IGF‐1 and muscle performance.

Overall, current evidence suggests that IGF‐1 primarily reflects anabolic status related to muscle mass in sarcopenia, whereas its utility in assessing muscle strength and physical function requires further validation in broader aging populations.

6. Nutrition and Energy Metabolism

Nutritional status and energy metabolism constitute the fundamental basis for maintaining skeletal muscle structure and function. Older adults frequently experience inadequate energy intake, deficiencies in key nutrients, and reduced metabolic flexibility, all of which impair muscle protein synthesis and mitochondrial function. In recent years, the gut microbiota has emerged as an important regulator linking diet, metabolism, and immune responses, and has been proposed to influence muscle health through the so‐called “gut–muscle axis” [37]. Molecular alterations related to nutrient sensing, metabolic substrate availability, and gut microbial composition may act synergistically during the development of sarcopenia.

6.1. Bioavailable 25‐Hydroxyvitamin D

Vitamin D plays a crucial role in maintaining skeletal muscle strength, function, and physical performance, and is closely associated with independent living capacity in older adults. Multiple biological mechanisms have been proposed to explain its effects on muscle, including initiation of muscle regeneration, regulation of cell cycle progression, and promotion of muscle fiber hypertrophy [38]. Vitamin D deficiency may adversely affect muscle contraction kinetics and function by inducing hypocalcemia, impairing insulin secretion, and disrupting muscle protein metabolism [39].

Given that vitamin D exists in multiple circulating forms, identifying the indicator that most accurately reflects sarcopenia‐related changes is of clinical relevance. A study involving 83 older patients with hip fracture compared various serum vitamin D–related biomarkers and their associations with sarcopenia. The results demonstrated that bioavailable 25‐hydroxyvitamin D [25(OH)D] levels were significantly lower in individuals with sarcopenia than in those without sarcopenia and showed a stronger association with sarcopenia than total 25(OH)D levels. When a cutoff value of 1.70 ng/mL was applied, bioavailable 25(OH)D achieved a sensitivity of 62.5% and a specificity of 68.6% for identifying sarcopenia [40].

These findings suggest that bioavailable 25(OH)D may better reflect muscle metabolic status related to sarcopenia than total 25(OH)D. Nevertheless, its stability and predictive value across different populations and clinical contexts warrant further investigation.

6.2. Carnitine

Carnitine (β‐hydroxy‐N‐trimethylaminobutyric acid) is an amino acid derivative abundantly present in skeletal and cardiac muscle and serves as a key molecule in mitochondrial fatty acid transport and energy production. By facilitating the transport of long‐chain fatty acids into mitochondria, carnitine supports β‐oxidation and meets the high energy demands of skeletal and cardiac muscle [41]. Given the close association between mitochondrial metabolic dysfunction and declines in muscle mass and strength, alterations in carnitine and its derivatives may indirectly reflect metabolic abnormalities related to sarcopenia.

A study involving 114 older patients with gastrointestinal cancer undergoing curative surgery reported a significant association between serum carnitine levels and skeletal muscle mass index (SMI). Patients with sarcopenia exhibited significantly lower carnitine levels, whereas acylcarnitine concentrations were elevated [42]. Similarly, a population‐based study of 289 community‐dwelling older adults in Taiwan demonstrated that individuals with sarcopenia and severe sarcopenia had higher plasma acylcarnitine levels—particularly butyrylcarnitine—compared with healthy controls. Moreover, the ratio of butyrylcarnitine to creatinine effectively distinguished between different severities of sarcopenia [43].

Taken together, changes in acylcarnitine profiles may provide a more comprehensive reflection of energy metabolism dysregulation in sarcopenia than single carnitine measurements. If future studies confirm their stability and consistency across sex, ethnicity, and health status, acylcarnitines may serve as promising metabolic biomarkers for monitoring sarcopenia progression.

6.3. Gut Microbiota

The development of sarcopenia is closely linked to nutritional status in older adults, and long‐term dietary patterns can influence skeletal muscle metabolism by modulating gut microbiota composition. Increasing evidence indicates that the gut microbiota plays a regulatory role in multiple muscle metabolic pathways. Experimental studies have shown that the absence of gut microbiota leads to significant reductions in skeletal muscle mass [44]. On the one hand, gut microbial composition affects the bioavailability of dietary amino acids, thereby indirectly regulating muscle protein synthesis and degradation. On the other hand, gut dysbiosis is closely associated with inflammaging, a hallmark of aging characterized by chronic low‐grade inflammation, which is considered a key mechanism promoting declines in muscle mass and strength [45].

To investigate differences in gut microbiota between older adults with sarcopenia and healthy controls, a study comparing elderly women with sarcopenia to age‐matched non‐sarcopenic individuals found a significantly reduced relative abundance of Bifidobacterium longum in the sarcopenia group [46]. Further receiver operating characteristic (ROC) curve analysis using B. longum abundance as a continuous variable demonstrated moderate diagnostic performance for sarcopenia, with a sensitivity of 53.1% and a specificity of 74.0%. These findings suggest that reduced B. longum abundance may serve as an auxiliary biomarker for sarcopenia in specific populations, although its predictive capacity remains limited and should be interpreted in conjunction with other clinical or biological indicators.

In addition, a recent meta‐analysis reported that gut microbiota capable of producing short‐chain fatty acids may exert protective effects against sarcopenia and confirmed that such bacteria—including Lactobacillus reuteri , Faecalibacterium, and Prevotella species—are generally less abundant in individuals with sarcopenia than in healthy controls [47]. These findings suggest that specific microbial taxa and their metabolites may represent potential microbiome‐related biomarkers associated with sarcopenia.

7. Muscle Signaling and the Neuromuscular Junction

Skeletal muscle is not only a contractile organ but also an important endocrine organ that secretes a variety of myokines involved in systemic metabolic regulation. In addition, the structural and functional integrity of the neuromuscular junction (NMJ) is essential for effective motor unit recruitment and force generation. During aging, reductions in myokine secretion and progressive degeneration of the NMJ contribute to declines in muscle function and, in some cases, muscle fiber denervation [48]. Circulating molecules reflecting muscle–systemic signaling axes and NMJ stability have therefore been proposed as candidate biomarkers for assessing functional impairments in sarcopenia.

7.1. Irisin

Irisin is a myokine predominantly secreted by skeletal muscle, and its production is closely associated with the Ca²⁺–AMPK–PGC‐1α–FNDC5 signaling pathway. Irisin can act in an autocrine or paracrine manner to activate downstream pathways such as ERK1/2 and interleukin‐6 (IL‐6), thereby promoting myoblast differentiation and playing a key role in the regulation of muscle growth and metabolism [49].

Animal studies have demonstrated that physical exercise markedly increases FNDC5 mRNA expression in skeletal muscle and elevates circulating irisin levels in mice, indicating a strong link between irisin secretion and physical activity [50]. In human studies, a community‐based investigation involving 715 Korean adults aged 18–90 years found that older individuals (≥ 65 years) exhibited significantly lower circulating irisin levels compared with younger participants, accompanied by marked reductions in muscle mass and muscle strength. After adjustment for confounding factors such as sex, age, and body fat index, low circulating irisin levels remained significantly associated with pre‐sarcopenia and sarcopenia. The optimal cutoff values for serum irisin concentration at maximal sensitivity and specificity were < 1.00 μg/mL in men (92% sensitivity, 83% specificity) and < 1.16 μg/mL in women (77% sensitivity, 67% specificity) [51].

These findings suggest that irisin may reflect the secretory function and activity status of skeletal muscle, and that reduced irisin levels are closely associated with sarcopenia‐related phenotypes. However, because irisin levels are strongly influenced by physical activity and metabolic factors, its stability as an independent diagnostic biomarker requires further validation across diverse populations.

7.2. Sarcopenia Index (SI)

The sarcopenia index (SI) was proposed by Kashani et al. in 2017 and is defined as the ratio of serum creatinine (Cr) to cystatin C (CysC), multiplied by 100. Serum creatinine partially reflects total skeletal muscle mass but is influenced by glomerular filtration rate, whereas cystatin C is largely independent of muscle mass and primarily reflects renal function. Consequently, the Cr/CysC ratio is considered a relatively accurate indicator of whole‐body muscle reserves [52, 53].

A longitudinal study of 1118 community‐dwelling older women demonstrated that the Cr/CysC ratio was positively associated with appendicular skeletal muscle mass and handgrip strength, and inversely associated with the risk of falls and fall‐related hospitalization [54]. Furthermore, a large‐scale analysis of 458,702 participants from the UK Biobank confirmed that SI exhibited acceptable diagnostic performance for identifying sarcopenia (AUC = 0.731 in men and 0.711 in women). However, its ability to detect possible sarcopenia or isolated low muscle mass was relatively limited [55].

Overall, SI offers advantages including simplicity of calculation and high clinical accessibility, making it a useful adjunctive biomarker for estimating global muscle reserves. Nevertheless, its sensitivity for early‐stage sarcopenia or functional decline remains suboptimal.

7.3. Circulating C‐Terminal Agrin Fragment (CAF)

With advancing age, the neuromuscular junction undergoes progressive structural and functional remodeling. During this process, neurotrypsin‐mediated cleavage inactivates agrin—a key molecule involved in NMJ formation and maintenance—resulting in the generation of a 22‐kDa C‐terminal agrin fragment (CAF) [56]. CAF has therefore been proposed as a circulating biomarker reflecting NMJ disintegration and muscle fiber denervation.

Studies have shown that community‐dwelling older adults with multimorbidity and very old individuals with sarcopenia exhibit significantly higher serum CAF levels compared with non‐sarcopenic counterparts. In women, declines in skeletal muscle mass, muscle strength, and physical performance were consistently associated with elevated CAF levels, whereas in men, CAF was primarily associated with reduced gait speed and handgrip strength [57]. Additionally, a study involving 300 participants aged 50–83 years further confirmed that CAF may serve as an indicator of muscle atrophy in healthy older adults, with its association with muscle strength becoming more pronounced at later stages of muscle degeneration [58].

Collectively, these findings suggest that CAF may function as a potential biomarker of NMJ degeneration and neurogenic muscle damage, particularly in the evaluation of sarcopenia‐related functional impairments driven by neural mechanisms.

8. Structural and Functional Phenotypes

Regardless of the initial molecular drivers of sarcopenia, the condition ultimately manifests as reductions in skeletal muscle mass, diminished muscle strength, and impaired physical performance. Imaging‐based assessments and physical function tests directly capture these terminal phenotypes and therefore constitute essential components of current diagnostic frameworks for sarcopenia. Although their sensitivity to early molecular alterations is limited, they remain indispensable for disease staging, severity assessment, and clinical decision‐making.

8.1. Ultrasound

Ultrasound is a noninvasive imaging modality characterized by ease of operation, good reproducibility, and relatively low cost. Compared with other muscle assessment methods included in sarcopenia diagnostic guidelines, ultrasound offers superior accessibility and patient acceptability. With advances in imaging technology, emerging ultrasound techniques—including elastography, contrast‐enhanced ultrasound, and speed‐of‐sound imaging—have been applied to evaluate muscle elasticity, perfusion under resting and dynamic conditions, and intramuscular fat infiltration, thereby expanding the potential utility of ultrasound in sarcopenia assessment.

Among these techniques, ultrasound elastography quantifies tissue stiffness by measuring shear wave propagation velocity and has been widely used in the evaluation of tendons, muscles, and joint disorders. In skeletal muscle assessment, elastography enables quantification of muscle stiffness under both resting and contractile conditions, thereby providing insights into muscle structural and functional status [59]. Studies comparing shear wave elastography findings across different age groups have demonstrated significantly lower shear wave velocities in older adults compared with younger and middle‐aged individuals, with significant correlations observed between shear wave velocity and muscle mass, muscle strength, and multiple physical performance measures [60]. These findings suggest that elastography may reflect age‐related degenerative changes in muscle structure.

Overall, ultrasound offers advantages such as the absence of radiation exposure, dynamic assessment capability, and bedside applicability, making it a promising adjunctive tool for sarcopenia screening and follow‐up. However, its measurements remain operator‐dependent, and further standardization of protocols and measurement sites is essential for widespread clinical adoption.

8.2. Computed Tomography

The International Working Group on Sarcopenia (IWGS 2012) recognizes computed tomography (CT) and magnetic resonance imaging (MRI) as gold standards for body composition assessment, as both modalities enable objective and precise quantification of skeletal muscle mass [61]. Previous studies have demonstrated that skeletal muscle cross‐sectional area measured at the third lumbar vertebra (L3) level is highly correlated with whole‐body skeletal muscle mass, while mid‐thigh imaging also provides robust estimates of appendicular and total muscle mass.

To enhance the clinical utility of CT in sarcopenia assessment, several studies have examined the relationship between muscle measurements obtained from routine abdominal CT scans and whole‐body skeletal muscle mass. Findings indicate that skeletal muscle area at the L3 level effectively predicts paraspinal muscle mass, whereas upper‐thigh muscle area reflects appendicular muscle mass. The combined assessment of these regions may therefore provide a more comprehensive estimation of total muscle reserves [62]. Furthermore, investigations into correlations between cervical or thoracic muscle measurements and L3‐derived indices have identified the C3 and T12 levels as having the strongest associations with L3 muscle area. These findings suggest that opportunistic assessment of paraspinal muscle mass during routine chest or abdominal CT examinations may reduce the need for additional imaging and radiation exposure [63, 64].

In recent years, artificial intelligence and deep learning techniques have been increasingly applied to CT image analysis for the automated identification of specific muscle groups—such as the psoas and erector spinae muscles—and rapid calculation of cross‐sectional areas. These approaches improve measurement efficiency and reduce observer‐related bias; however, their robustness and generalizability across different imaging platforms and populations require further validation.

8.3. Handgrip Strength Asymmetry

Handgrip strength (HGS) is a simple and reliable measure of muscle strength that is strongly associated with multiple adverse health outcomes and is widely used in both community and clinical screening. In the context of sarcopenia, HGS has been incorporated into diagnostic criteria, with the Asian Working Group for Sarcopenia (AWGS) recommending cutoff values of < 28 kg for men and < 18 kg for women.

Recent studies have suggested that bilateral handgrip strength asymmetry may serve as an earlier indicator of generalized muscle decline than maximal grip strength alone [65]. Handgrip strength asymmetry is typically defined as a difference exceeding 10% between the two hands and has been proposed as a clinically relevant screening marker of muscle health. Evidence indicates that individuals with grip strength asymmetry have a 2.67‐fold higher risk of sarcopenia compared with those with symmetrical grip strength, and this risk exceeds that associated with low grip strength or low skeletal muscle mass index (SMI) alone [66]. In diagnostic analyzes, handgrip strength asymmetry yielded an AUC of 0.727 (95% CI: 0.658–0.796), demonstrating high specificity but relatively limited sensitivity at an optimal ratio threshold of 1.24.

Accordingly, handgrip strength asymmetry may be best utilized as a complementary indicator for identifying individuals with potential muscle function abnormalities, rather than as a standalone diagnostic criterion for sarcopenia.

8.4. Combined Gait Parameters Under Dual‐Task Walking

Gait parameters—including gait speed, cadence, step length, and gait variability—provide quantitative insights into motor control and physical function. Among these, gait speed is a key functional criterion for sarcopenia diagnosis, with a 6‐m walking speed of < 1.0 m/s incorporated into AWGS diagnostic recommendations [67].

Recent research has explored the integration of multiple gait parameters, particularly under dual‐task conditions in which individuals walk while performing a concurrent cognitive task, to enhance sarcopenia detection. Studies comparing predictive performance under single‐task and dual‐task conditions have shown that turning duration during dual‐task walking exhibits good predictive value for sarcopenia (AUC = 0.736). Moreover, combining dual‐task gait speed with turning duration further improved diagnostic performance (AUC = 0.763) [68].

These findings introduce a novel approach to functional assessment in sarcopenia, and advances in wearable sensor technology make the acquisition of detailed gait parameters increasingly feasible. However, existing studies are limited by small sample sizes and a focus on frail older adults, and the applicability of these findings to the general aging population remains to be established. In addition, although multimodal gait parameter combinations may improve diagnostic accuracy, their complexity and clinical feasibility must be carefully balanced against existing, simpler assessment tools.

9. Conclusions and Perspectives

The identification and application of biomarkers provide valuable tools for the early prediction, precise diagnosis, and prognostic assessment of sarcopenia. This review systematically summarizes a wide range of candidate biomarkers that have been reported to exhibit positive or negative associations with sarcopenia and categorizes them into biochemical, imaging‐based, and physical performance–related biomarkers according to their characteristics. Biochemical biomarkers are further classified into inflammation‐related, genetic‐related, hormone‐related, nutrition‐ and metabolism‐related, and circulating mediator–related categories based on their biological properties and functional roles. Based on the evidence summarized throughout this review, Table 1 provides an integrated overview of representative biomarkers associated with sarcopenia, categorized according to their underlying biological mechanisms, along with their key clinical associations and major advantages or limitations. Given the rapid expansion of research on sarcopenia biomarkers in recent years, the systematic integration and classification of these indicators are essential for guiding future study design and facilitating clinical translation.

TABLE 1.

Classifications of sarcopenia biomarkers.

Category	Biomarker	Key association with sarcopenia	Main advantages/limitations
Inflammation	SII	Higher SII associated with increased sarcopenia risk	Simple, inexpensive; mainly cross‐sectional evidence
	IL‐6/TNF‐α	Elevated levels correlate with reduced muscle mass and strength	Sensitive to acute inflammation
Mitochondrial and genetic	ccf‐mtDNA	Increased levels observed in sarcopenia	Reflects mitochondrial damage; mechanisms unclear
	miR‐486	Progressive decline across sarcopenia stages	Moderate diagnostic accuracy
Anabolic and endocrine	GDF‐15	Elevated levels linked to muscle weakness and poor performance	Low specificity
	Myostatin	Reflects muscle mass changes and response to intervention	Limited prediction of function
Nutrition and metabolism	Bioavailable 25(OH)D	Lower levels more strongly associated than total 25(OH)D	Cutoffs not standardized
	Acylcarnitines	Altered profiles indicate metabolic imbalance	Higher analytical complexity
	Gut microbiota ( B. longum )	Reduced abundance associated with sarcopenia	Moderate diagnostic value
Muscle signaling/NMJ	Irisin	Lower circulating levels associated with sarcopenia	Influenced by physical activity
	Sarcopenia index (Cr/CysC)	Correlates with muscle mass and fall risk	Low sensitivity for early disease
	CAF	Elevated levels reflect NMJ degeneration	Stronger for functional decline
Structure and function	Ultrasound	Muscle thickness and stiffness correlate with sarcopenia	Operator‐dependent
	CT muscle area	Strongly reflects total skeletal muscle mass	Radiation exposure
	Grip strength asymmetry	Associated with increased sarcopenia risk	High specificity, low sensitivity

At present, biochemical biomarkers represent the most active area of sarcopenia research. Compared with imaging‐based or functional assessments, biochemical biomarkers generally exhibit good reproducibility and can often be measured using blood samples, conferring relatively high clinical feasibility. However, most currently proposed biochemical biomarkers face common challenges, including limited diagnostic performance, modest strength of association with sarcopenia, susceptibility to confounding factors such as sex, age, and ethnicity, and, in some cases, high detection costs or technical complexity. Consequently, an increasing number of studies have adopted multimarker approaches, combining multiple biochemical indicators to construct composite diagnostic or predictive models with improved accuracy and stability.

Imaging‐based assessment remains a cornerstone of sarcopenia diagnosis, with commonly used modalities including dual‐energy X‐ray absorptiometry (DXA), computed tomography (CT), ultrasound (US), and magnetic resonance imaging (MRI). Each technique has distinct advantages and limitations in terms of assessment principles, accuracy, accessibility, and cost. Although several guidelines recommend DXA‐derived muscle mass as a diagnostic criterion, CT and ultrasound are more widely applied in routine clinical practice. CT is mature and readily available, and opportunistic analysis of existing imaging data in patients undergoing chronic disease follow‐up allows for sarcopenia screening without additional cost or radiation exposure. Ultrasound, by contrast, offers advantages such as the absence of ionizing radiation, operational flexibility, and suitability for use in primary care settings. With the increasing integration of artificial intelligence into imaging analysis, further improvements in objectivity, automation, and efficiency are anticipated.

Physical performance–based biomarkers are particularly suitable for the initial screening and risk assessment of sarcopenia. These indicators typically require minimal equipment and are noninvasive, enabling rapid acquisition through simple tests or wearable devices. In recent years, sensor‐based and wearable technology–driven approaches have increasingly been explored to identify sarcopenia using movement amplitude, gait parameters, and surface electromyography signals. Although these methods have demonstrated diagnostic potential in small‐scale studies, further validation is required to establish their reliability and clinical applicability.

It is important to note that many of the candidate biomarkers discussed in this review—such as inflammatory cytokines, mitochondrial function–related indicators, and certain hormonal markers—are closely linked to the aging process itself. Abnormalities observed in individuals with sarcopenia may therefore reflect shared pathophysiological mechanisms underlying both aging and skeletal muscle degeneration, rather than being specific to sarcopenia. Accordingly, the clinical value of these biomarkers lies less in absolute specificity and more in their enrichment in sarcopenic populations, dose–response relationships, and utility in monitoring disease progression and responses to intervention. Future studies should further delineate differences between healthy aging and sarcopenia and enhance discriminatory power through multimarker integration.

In summary, multiple sarcopenia‐related biomarkers with potential clinical value have been identified across biochemical, imaging, and physical performance domains. Some of these indicators, owing to their accessibility or favorable diagnostic performance, show promise for clinical translation. Given that sarcopenia is a multifactorial syndrome driven by complex and interacting pathophysiological mechanisms, no single biomarker can fully capture its heterogeneous features. Multimodal and multimarker assessment strategies therefore represent a key direction for future research. In parallel, the incorporation of artificial intelligence and machine learning techniques offers new opportunities for sarcopenia diagnosis and risk prediction by enabling rapid quantification of muscle mass from imaging data and the integration of sensor‐derived functional metrics with clinical and biochemical variables. With continued advances in these fields, screening and diagnostic frameworks for sarcopenia are expected to become increasingly refined, ultimately supporting the implementation of precision and individualized management strategies.

Author Contributions

Ping He, Bijin Luo: conceptualization. Bijin Luo: writing – original draft. Ping He, Wenhan Li, Yi Zhang, Mengchen Liu, Kemeng Zhang, Sui Huang: writing – review and editing.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

Data openly available in a public repository.