ArticleFrontiers in endocrinology2024
Metabolic signatures and risk of sarcopenia in suburb-dwelling older individuals by LC-MS-based untargeted metabonomics.
Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Metabolomic biomarker differences of sarcopenia in older patients with sepsis.Frontiers in medicine · 2026Article
- Integrated Proteomic and Metabolomic Profiling for Developing Novel Plasma-Based Diagnostic Models of Sarcopenia.Journal of cachexia, sarcopenia and muscle · 2026Article
- Amino acid metabolites as potential circulating biomarkers for sarcopenia.Scientific reports · 2025Article
- Diabetes and Sarcopenia: Metabolomic Signature of Pathogenic Pathways and Targeted Therapies.International journal of molecular sciences · 2025Review
- Towards Precision in Sarcopenia Assessment: The Challenges of Multimodal Data Analysis in the Era of AI.International journal of molecular sciences · 2025Review
- Association of the cardiometabolic index with sarcopenia among U.S. adults: NHANES 2011-2018 findings.PloS one · 2025Article
- Nontargeted and targeted metabolic profile of metabolic syndrome patients: a study based on Yi and Han populations in Yunnan.Frontiers in endocrinology · 2025Article
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11 authors.
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Abstract
Background: Untargeted metabonomics has provided new insight into the pathogenesis of sarcopenia. In this study, we explored plasma metabolic signatures linked to a heightened risk of sarcopenia in a cohort study by LC-MS-based untargeted metabonomics. Methods: In this nested case-control study from the Adult Physical Fitness and Health Cohort Study (APFHCS), we collected blood plasma samples from 30 new-onset sarcopenia subjects (mean age 73.2 ± 5.6 years) and 30 healthy controls (mean age 74.2 ± 4.6 years) matched by age, sex, BMI, lifestyle, and comorbidities. An untargeted metabolomics methodology was employed to discern the metabolomic profile alterations present in individuals exhibiting newly diagnosed sarcopenia. Results: In comparing individuals with new-onset sarcopenia to normal controls, a comprehensive analysis using liquid chromatography-mass spectrometry (LC-MS) identified a total of 62 metabolites, predominantly comprising lipids, lipid-like molecules, organic acids, and derivatives. Receiver operating characteristic (ROC) curve analysis indicated that the three metabolites hypoxanthine (AUC=0.819, 95% CI=0.711-0.927), L-2-amino-3-oxobutanoic acid (AUC=0.733, 95% CI=0.598-0.868) and PC(14:0/20:2(11Z,14Z)) (AUC= 0.717, 95% CI=0.587-0.846) had the highest areas under the curve. Then, these significant metabolites were observed to be notably enriched in four distinct metabolic pathways, namely, "purine metabolism"; "parathyroid hormone synthesis, secretion and action"; "choline metabolism in cancer"; and "tuberculosis". Conclusion: The current investigation elucidates the metabolic perturbations observed in individuals diagnosed with sarcopenia. The identified metabolites hold promise as potential biomarkers, offering avenues for exploring the underlying pathological mechanisms associated with sarcopenia.
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