ArticleJournal of cachexia, sarcopenia and muscle2024
Novel metabolic and lipidomic biomarkers of sarcopenia.
Article in Journal of cachexia, sarcopenia and muscle, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Cardiometabolic index (CMI) and sarcopenia as predictors of all-cause and cardiovascular mortality in chronic kidney disease: a NHANES-based cohort study.Renal failure · 2026Article
- Review
- Exploratory plasma metabolomics of aging-related associations with muscle quality and pulmonary function.GeroScience · 2026Article
- Plasma Citrate Levels Are Inversely Associated with Estimated Muscle Mass and Strength in Liver Transplant Recipients.International journal of molecular sciences · 2026Article
- Review
- The association between sarcopenia and carotid artery plaque: a mediation analysis of inflammatory biomarkers.BMC endocrine disorders · 2026Article
- Development of a sarcopenia identification model for older adults with multimorbidity in Xinjiang communities, Northwest China: a cross-sectional study.BMC geriatrics · 2026Article
- Sarcopenia and Muscle Aging: Updated Insights into Molecular Mechanisms and Translational Therapeutics.Endocrinology and metabolism (Seoul, Korea) · 2026Review
- MRI-Based Assessment of Etiology-Specific Sarcopenia Phenotypes in Chronic Liver Disease: A Comparative Study of MASH and Viral Hepatitis.Diagnostics (Basel, Switzerland) · 2026Article
- Multi-omics and molecular testing: A new insight into the genetic mechanisms of sarcopenia and arthritis.Clinical and experimental medicine · 2026Article
- The ageing microenvironment in sarcopenia: early alterations and targeted therapeutic strategies.Frontiers in immunology · 2026Review
- A distinct serum metabolic profile characterizes osteosarcopenia: identifying potential metabolic biomarkers.Frontiers in endocrinology · 2026Observational
- Development and external validation of a composite biomarker-based machine learning model for sarcopenia risk stratification in patients with cardiovascular disease.Frontiers in cardiovascular medicine · 2026Article
- Association between estimated glucose disposal rate and metabolic syndrome in older adults with sarcopenia.Frontiers in nutrition · 2026Article
- Creatinine, leucine, and tetrahydrocorticosterone emerge as potential biomarkers for the diagnosis of sarcopenic osteoarthritis in middle-aged and elderly individuals: a cross-sectional exploratory study.Frontiers in molecular biosciences · 2026Article
- Risk prediction of sarcopenia in a large health checkup population: development and validation of a dynamic online nomogram.Frontiers in public health · 2026Article
- HSF1 modulates lipid metabolism and ferroptosis in sarcopenia: a novel diagnostic biomarker and therapeutic target.Frontiers in molecular biosciences · 2026Article
- Development of machine learning-based models for predicting sarcopenia risk in stroke patients and analysis of associated factors.Scientific reports · 2025Article
- Amino acid metabolites as potential circulating biomarkers for sarcopenia.Scientific reports · 2025Article
- Unravelling the Complexity of Sarcopenia Through a Systems Biology Approach.International journal of molecular sciences · 2025Review
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6 authors.
Funding
Abstract
backgroundThe pathophysiology of sarcopenia is complex and multifactorial and has not been fully elucidated. The impact of resistance training and nutritional support (RTNS) on metabolomics and lipodomics in older adults with sarcopenia remains uncertain. This study aimed to explore potential biomarkers of sarcopenia and clinical indicators of RTNS in older sarcopenic adults.
methodsOlder individuals diagnosed with sarcopenia through routine health checkups at a community hospital were recruited for a 12-week randomized controlled trial focusing on RTNS. Plasma metabolomic and lipidomic profiles of 45 patients with sarcopenia and 47 matched controls were analysed using
resultsAt baseline, the patient and control groups had similar age, sex, and height distribution. The patient group had significantly lower weight, BMI, grip strength, gait speed, skeletal muscle index, lean mass of both the upper and lower limbs, and lower limb bone mass. There was a significant difference in 12 metabolites between the control and patient groups. They are isoleucine (patient/control fold change [FC] = 0.86 ± 0.04, P = 0.0005), carnitine (FC = 1.05 ± 0.01, P = 0.0110), 1-methylhistamine/3-methylhistamine (FC = 1.24 ± 0.14, P = 0.0039), creatinine (FC = 0.71 ± 0.04, P < 0.0001), carnosine (FC = 0.71 ± 0.04, P = 0.0007), ureidopropionic acid (FC = 0.61 ± 0.10, P = 0.0107), uric acid (FC = 0.88 ± 0.03, P = 0.0083), PC (18:2/20:0) (FC = 0.69 ± 0.03, P = 0.0010), PC (20:2/18:0) (FC = 0.70 ± 0.06, P = 0.0014), PC (18:1/20:1) (FC = 0.74 ± 0.05, P = 0.0015), PI 32:1 (FC = 4.72 ± 0.17, P = 0.0006), and PI 34:3 (FC = 1.88 ± 0.13, P = 0.0003). Among them, carnitine, 1-methylhistamine/3-methylhistamine, creatinine, ureidopropionic acid, uric acid, PI 32:1, and PI 34:3 were first identified. Notably, PI 32:1 had highest diagnostic accuracy (0.938) for sarcopenia. 1-Methylhistamine/3-methylhistamine, carnosine, PC (18:2/20:0), PI 32:1, and PI 34:3 levels were not different from the control group after RTNS. These metabolites are involved in amino acid metabolism, lipid metabolism, and the PI3K-AKT/mTOR signalling pathway through the ingenuity pathway analysis.
conclusionsThese findings provide information on metabolic changes, lipid perturbations, and the role of RTNS in patients with sarcopenia. They reveal new insights into its pathological mechanisms and potential therapies.
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