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Sarcopenia Across the Lifespan: Risk Factors, Mechanisms, and Management in Aging and Disease

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Orthopedics".

Deadline for manuscript submissions: 15 July 2026 | Viewed by 9679

Special Issue Editors

Prof. Dr. Juan Mielgo-Ayuso

E-Mail Website
Guest Editor
Department of Health Sciences, Faculty of Health Sciences, University of Burgos, 09001 Burgos, Spain
Interests: sports performance; athletic performance; muscle recovery; sport nutrition; nutritional supplementation; muscle damage
Special Issues, Collections and Topics in MDPI journals
Dr. Natalia Busto

E-Mail Website
Guest Editor
Department of Health Sciences, Faculty of Health Sciences, University of Burgos, 09001 Burgos, Spain
Interests: cell culture; molecular biology; pharmaceutical development; kinetics; medicinal and pharmaceutical chemistry and biochemistry

Special Issue Information

Dear Colleagues,

Sarcopenia, defined by the progressive loss of muscle mass and function, remains a key challenge in aging populations. However, its impact is not limited to older adults—it also affects people living with chronic illnesses and other health conditions. This Special Issue aims to delve into the diverse facets of sarcopenia, from its underlying risk factors to current and emerging strategies for prevention and treatment. Topics will include the role of nutrition, physical activity, and pharmacological approaches, as well as the exploration of novel biomarkers, genetic influences, and other relevant contributors to muscle health. By bringing clinical perspectives, this Special Issue seeks to present a well-rounded overview of current findings and opportunities to enhance care and outcomes for those affected, regardless of age.

Prof. Dr. Juan Mielgo-Ayuso
Dr. Natalia Busto
Guest Editors

Manuscript Submission Information

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Keywords

  • sarcopenia
  • aging
  • chronic disease
  • risk factors
  • muscle physiology
  • prevention
  • nutrition
  • exercise
  • treatment strategies

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Related Special Issue

Published Papers (6 papers)

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Research

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17 pages, 749 KB  
Article
Comparative Performance of SARC-F, SARC-CalF, SARC-F + EBM, and Ishii Score for Detecting Sarcopenia in Hospitalised Geriatric Patients
by Ioana Daniela Rus, Vlad Ionuț Nechita, Lucreția Avram, Dana Crișan, Cristina Pamfil, Laura Muntean, Elisabeta Ioana Hirișcău and Valer Donca
J. Clin. Med. 2026, 15(7), 2663; https://doi.org/10.3390/jcm15072663 - 1 Apr 2026
Viewed by 448
Abstract
Background/Objectives: Sarcopenia is a progressive decline in skeletal muscle strength and mass, leading to decreased functionality, metabolic disorders, morbidity, and mortality. There are a number of sarcopenia screening tools, such as the SARC-F questionnaire (that includes noting strength, assistance with walking, ability to [...] Read more.
Background/Objectives: Sarcopenia is a progressive decline in skeletal muscle strength and mass, leading to decreased functionality, metabolic disorders, morbidity, and mortality. There are a number of sarcopenia screening tools, such as the SARC-F questionnaire (that includes noting strength, assistance with walking, ability to raise from the chair, climb stairs, and falls), with its augmented forms that have added calf circumference (SARC-CalF), BMI and age (SARC-F + EBM), and the Ishii score, which show variable performance across populations. However, these were developed and validated mostly in Asian cohorts. To evaluate the diagnostic accuracy of these tools for the European Working Group on Sarcopenia in Older People (EWGSOP2), as well as define sarcopenia in hospitalized East European older adults, with sex and obesity stratification. Methods: Sarcopenia was diagnosed using the EWGSOP2. ROC analyses with DeLong tests assessed SARC-F, SARC-CalF, SARC-F + EBM, and the Ishii score in 278 Romanian inpatients (probable sarcopenia n = 201/278, 72.3%; confirmed n = 77/278, 27.7%). Results: Probable sarcopenia was noted as good-excellent discrimination against across all tools (AUCs 0.764–0.812); confirmed sarcopenia was noted as SARC-CalF superior (AUC = 0.743), followed by SARC-F + EBM (0.697), the Ishii score as moderate (0.667), and SARC-F was limited (0.591; p < 0.001 vs. augmented). SARC-CalF optimal cut-offs varied significantly: 4–6 (probable) vs. ≥11 (confirmed). Sex-stratified outcomes had excellent probable detection in both sexes, and this was confirmed to be superior in men. The Ishii score thresholds were 152/244 vs. Asian ≥ 105/120. Obesity required higher cut-offs with high NPVs (77–100%), confirming rule-out utility and SARC-F + EBM performing the best, both in the obesity and sarcopenic obesity subgroups (AUCs 0.742, 0.964). Conclusions: Augmented SARC-F scores outperformed the original SARC-F for confirmed sarcopenia in multimorbid Europeans, with SARC-F CalF having the best performance overall. Population-specific (sex/obesity) data-driven thresholds are essential, especially for the Ishii score, as this first Romanian validation reveals limitations of Asian norms in European cohorts, thus advocating for European recalibration. Full article
(This article belongs to the Special Issue Sarcopenia Across the Lifespan: Risk Factors, Mechanisms, and Management in Aging and Disease)
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27 pages, 3594 KB  
Article
Machine Learning-Driven Personalized Risk Prediction: Developing an Explainable Sarcopenia Model for Older European Adults with Arthritis
by Xiao Xu
J. Clin. Med. 2026, 15(3), 1022; https://doi.org/10.3390/jcm15031022 - 27 Jan 2026
Viewed by 520
Abstract
Objectives: This study aimed to develop and validate an explainable machine learning (ML) model to predict the risk of sarcopenia in older European adults with arthritis, providing a practical tool for early and precise screening in clinical settings. Methods: We analyzed [...] Read more.
Objectives: This study aimed to develop and validate an explainable machine learning (ML) model to predict the risk of sarcopenia in older European adults with arthritis, providing a practical tool for early and precise screening in clinical settings. Methods: We analyzed data from the English Longitudinal Study of Aging (ELSA) and the Survey of Health, Aging and Retirement in Europe (SHARE). The final analysis included 1959 participants aged ≥65 years. The ELSA dataset was divided into a training set (n = 1371) and an internal validation set (n = 588), while the SHARE dataset (n = 1001) served as an independent external test cohort. From an initial pool of 33 variables, nine core predictors were identified using ensemble feature selection techniques. Six ML algorithms were compared, with model performance evaluated using the Area Under the Curve (AUC) and calibration analysis. Model interpretability was enhanced via SHapley Additive exPlanations (SHAP). Results: The Decision Tree model demonstrated the optimal balance between performance and interpretability. It achieved an AUC of 0.921 (95% CI: 0.848–0.988) in the internal validation set and maintained robust generalizability in the external SHARE cohort with an AUC of 0.958 (95% CI: 0.931–0.985). The nine key predictors identified were stroke history, BMI, HDL, loneliness, walking speed, disease duration, age, recall summary score, and total cholesterol. SHAP analysis visualized the specific contribution of these features to individual risk. Conclusions: This study successfully developed a high-performance, explainable, lightweight ML model for sarcopenia risk prediction. By inputting only nine readily available clinical indicators via an online tool, individualized risk assessment can be generated. This facilitates early identification and risk stratification of sarcopenia in older European arthritis patients, thereby providing valuable decision support for implementing precision interventions. Full article
(This article belongs to the Special Issue Sarcopenia Across the Lifespan: Risk Factors, Mechanisms, and Management in Aging and Disease)
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17 pages, 654 KB  
Article
Hierarchical Evaluation of Predictive Models for Confirmed Sarcopenia: Discrimination, Calibration, and Clinical Applicability in a Cross-Sectional Study of Older Adults
by Ludwig Álvarez-Córdova, Daniel Simancas-Racines, Claudia Reytor-González, Diana Fonseca-Pérez, Víctor Sierra-Nieto, Cecilia Arteaga-Pazmiño, Natasha Giler-Párraga, Jaen Cagua-Ordoñez and Martha Montalvan
J. Clin. Med. 2025, 14(24), 8707; https://doi.org/10.3390/jcm14248707 - 9 Dec 2025
Viewed by 757
Abstract
Background: Sarcopenia is a progressive and multifactorial condition linked to aging, malnutrition, and chronic diseases, presenting significant clinical and public health challenges. Current screening tools vary in complexity and diagnostic accuracy, emphasizing the need for simple, evidence-based predictive models suitable for settings [...] Read more.
Background: Sarcopenia is a progressive and multifactorial condition linked to aging, malnutrition, and chronic diseases, presenting significant clinical and public health challenges. Current screening tools vary in complexity and diagnostic accuracy, emphasizing the need for simple, evidence-based predictive models suitable for settings with limited resources. Methods: A cross-sectional study was conducted among community-dwelling older adults to develop and internally validate hierarchical predictive models for sarcopenia using readily available primary care variables. Three models were built: (1) a basic clinical model (age, sex, BMI, calf circumference, and SARC-F), (2) a model including nutritional status (Mini Nutritional Assessment, MNA), and (3) an extended model adding bioelectrical impedance parameters (phase angle, PhA). Model performance was assessed using AUC, Brier score, Hosmer–Lemeshow test, and decision curve analysis. Results: The parsimonious model demonstrated excellent discrimination (AUC = 0.91) and good calibration (Hosmer–Lemeshow p = 0.36), while the extended model with MNA and PhA achieved the highest overall performance (AUC = 0.95; Brier = 0.064; p = 0.97). Incorporating MNA and PhA enhanced calibration and clinical utility, especially for risk probabilities between 0.10 and 0.40. Internal validation showed minimal optimism and stable coefficients, with BMI, sex, and PhA as consistent predictors. Conclusions: A model combining anthropometric, nutritional, and bioelectrical variables provides high diagnostic accuracy for sarcopenia while remaining practical for clinical use. Its stepwise design facilitates application at various healthcare levels, supporting early detection and targeted interventions in aging populations. Full article
(This article belongs to the Special Issue Sarcopenia Across the Lifespan: Risk Factors, Mechanisms, and Management in Aging and Disease)
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15 pages, 1704 KB  
Article
Progressive Loss of Muscle Strength: The Effects of Ageing and Sarcopenia on Muscle Function in Older Females
by Katarzyna Nowakowska-Lipiec, Hanna Zadoń, Robert Michnik and Agnieszka Nawrat-Szołtysik
J. Clin. Med. 2025, 14(20), 7276; https://doi.org/10.3390/jcm14207276 - 15 Oct 2025
Cited by 2 | Viewed by 5734
Abstract
Background/Objectives: Sarcopenia is the progressive loss of muscle mass, strength, and/or function, leading to reduced physical performance, independence, and social participation. This study aimed to analyze the effects of age-related muscle strength loss and sarcopenia on muscle function during standing in older [...] Read more.
Background/Objectives: Sarcopenia is the progressive loss of muscle mass, strength, and/or function, leading to reduced physical performance, independence, and social participation. This study aimed to analyze the effects of age-related muscle strength loss and sarcopenia on muscle function during standing in older females. Methods: This study included experimental and modeling analyses using the AnyBody Modeling System in 20 older females. Based on DEXA results, participants were divided into older females without sarcopenia (OF) and with sarcopenia (OFS). Body posture while standing was assessed using the Zebris APGMS Pointer system. A model of muscular strength changes due to natural aging and progressive sarcopenia was developed based on literature data. The experimental results informed model studies in the AnyBody Modeling System, which incorporated changes in body posture and loss of muscle strength. Results: Total muscle activity during standing increases with age; however, this increase is significantly more pronounced in individuals with sarcopenia, especially after the age of 65. At 65, total muscle activity was 15% higher in the OFS model than in the OF model, while the difference was 44% at 80. After age 65, muscle fatigue increased considerably with progressive sarcopenia. At age 80, muscle fatigue while standing with sarcopenia can be more than three times higher than in those without sarcopenia. Conclusions: Aging leads to increased muscle activity while standing, and sarcopenia further amplifies this effect, particularly in individuals over 65. Modeling results highlight the pronounced impact of sarcopenia on muscle fatigue, demonstrating its significant functional consequences in older females. Full article
(This article belongs to the Special Issue Sarcopenia Across the Lifespan: Risk Factors, Mechanisms, and Management in Aging and Disease)
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12 pages, 747 KB  
Article
Relationship Between Bone Metabolic Markers and Presence of Sarcopenia in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study
by Tomoyuki Matsuyama, Yoshitaka Hashimoto, Noriyuki Kitagawa, Takafumi Osaka, Masahide Hamaguchi and Michiaki Fukui
J. Clin. Med. 2025, 14(17), 5973; https://doi.org/10.3390/jcm14175973 - 24 Aug 2025
Viewed by 1204
Abstract
Objectives: We investigated the relationship between bone metabolic markers or bone mineral density (BMD) and sarcopenia in patients with type 2 diabetes mellitus (T2DM). Methods: In this cross-sectional study involving 119 subjects (76 women and 43 men), bone metabolic markers were [...] Read more.
Objectives: We investigated the relationship between bone metabolic markers or bone mineral density (BMD) and sarcopenia in patients with type 2 diabetes mellitus (T2DM). Methods: In this cross-sectional study involving 119 subjects (76 women and 43 men), bone metabolic markers were evaluated by bone alkaline phosphatase and bone tartrate-resistant acid phosphatase (TRACP-5b). BMD was measured using the dual-energy X-ray absorptiometry method, and sarcopenia was diagnosed using skeletal muscle mass index (SMI), evaluated by body composition measurement and handgrip strength. Results: Significant correlation was observed between handgrip strength or SMI and TRACP-5b in both sexes (correlation coefficients were −0.50 in handgrip strength and −0.41 in SMI in men; −0.25 in handgrip strength and −0.21 in SMI in women). Furthermore, significant correlation was observed between handgrip strength or SMI and BMD of the femoral neck in both sexes (correlation coefficients were 0.33 in handgrip strength and 0.44 in SMI in men; 0.34 in handgrip strength and 0.47 in SMI in women). The concentrations of TRACP-5b with sarcopenia were significantly higher than those without (643.8 ± 261.9 vs. 455.7 ± 165.6 mU/dL), and BMD of femoral neck with sarcopenia was significantly lower than those without (0.54 ± 0.12 vs. 0.66 ± 0.16 g/cm2). TRACP-5b (odds ratio 1.05, 95% confidence interval 1.01–1.10) and femoral neck BMD (odds ratio 0.30, 95% confidence interval 0.14–0.68) were associated with the presence of sarcopenia after adjustment for confounders. Conclusions: TRACP-5b and BMD of the femoral neck were associated with sarcopenia in patients with T2DM. Full article
(This article belongs to the Special Issue Sarcopenia Across the Lifespan: Risk Factors, Mechanisms, and Management in Aging and Disease)
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Review

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14 pages, 551 KB  
Review
Ultrasound Elastography for the Assessment of Sarcopenia
by Chenzi Zhang and Lin Kang
J. Clin. Med. 2026, 15(7), 2566; https://doi.org/10.3390/jcm15072566 - 27 Mar 2026
Viewed by 403
Abstract
Background: Sarcopenia is an age-related syndrome characterized by progressive loss of skeletal muscle mass and strength, representing a major contributor to disability and increased mortality in older adults. Current diagnostic frameworks increasingly emphasize muscle quality alongside quantity, creating a clinical need for [...] Read more.
Background: Sarcopenia is an age-related syndrome characterized by progressive loss of skeletal muscle mass and strength, representing a major contributor to disability and increased mortality in older adults. Current diagnostic frameworks increasingly emphasize muscle quality alongside quantity, creating a clinical need for bedside tools that can objectively assess muscle mechanical properties. Shear-wave elastography (SWE), an ultrasound-based technique that quantifies muscle stiffness, has emerged as a promising biomechanical biomarker of muscle quality. Aim: This narrative review evaluates the evidence supporting SWE for assessing muscle quality and its association with aging, sarcopenia, and functional outcomes. Methods: We searched PubMed, Embase, and Web of Science (from January 2010 to December 2025) using terms related to elastography and sarcopenia. Based on relevance and methodological quality, approximately 50 key studies were selected for in-depth discussion and synthesis. Synthesis: Observational studies consistently demonstrate that SWE detects age-related reductions in muscle stiffness, which correlate significantly with declines in muscle strength and physical performance. Unlike conventional B-mode ultrasound, which primarily provides morphological parameters, SWE directly reflects intrinsic tissue mechanics, enabling more direct assessment of muscle quality. In high-risk populations such as patients with type 2 diabetes, reduced muscle stiffness is also associated with sarcopenia and poor functional outcomes. However, reported stiffness trends with aging remain heterogeneous, and validated diagnostic thresholds are lacking. Stiffness changes vary by muscle group, acquisition protocol, and loading state. Clinical implementation is currently limited by inter-device variability, operator dependence, and sensitivity to muscle loading conditions. Conclusions: Current evidence suggests that SWE holds promise as an adjunctive research tool for assessing muscle quality and risk stratification, but it is not yet ready for standalone clinical diagnosis due to methodological heterogeneity, lack of validated cutoffs, and limited longitudinal data. Future large-scale, longitudinal, multicenter studies with standardized protocols are needed to establish its definitive diagnostic utility. Full article
(This article belongs to the Special Issue Sarcopenia Across the Lifespan: Risk Factors, Mechanisms, and Management in Aging and Disease)
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