Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
College of Rehabilitation Sciences, Pudong New Area, Shanghai University of Medicine and Health Sciences, 279 Zhouzhu Highway, Shanghai, 201318, China.
Skelet Muscle. 2024 Mar 7;14(1):4. doi: 10.1186/s13395-024-00337-3.
Untargeted metabolomics can be used to expand our understanding of the pathogenesis of sarcopenia. However, the metabolic signatures of sarcopenia patients have not been thoroughly investigated. Herein, we explored metabolites associated with sarcopenia by untargeted gas chromatography (GC)/liquid chromatography (LC)-mass spectrometry (MS) and identified possible diagnostic markers.
Forty-eight elderly subjects with sarcopenia were age and sex matched with 48 elderly subjects without sarcopenia. We first used untargeted GC/LC-MS to analyze the plasma of these participants and then combined it with a large number of multivariate statistical analyses to analyze the data. Finally, based on a multidimensional analysis of the metabolites, the most critical metabolites were considered to be biomarkers of sarcopenia.
According to variable importance in the project (VIP > 1) and the p-value of t-test (p < 0.05), a total of 55 metabolites by GC-MS and 85 metabolites by LC-MS were identified between sarcopenia subjects and normal controls, and these were mostly lipids and lipid-like molecules. Among the top 20 metabolites, seven phosphatidylcholines, seven lysophosphatidylcholines (LysoPCs), phosphatidylinositol, sphingomyelin, palmitamide, L-2-amino-3-oxobutanoic acid, and palmitic acid were downregulated in the sarcopenia group; only ethylamine was upregulated. Among that, three metabolites of LysoPC(17:0), L-2-amino-3-oxobutanoic acid, and palmitic acid showed very good prediction capacity with AUCs of 0.887 (95% CI = 0.817-0.957), 0.836 (95% CI = 0.751-0.921), and 0.805 (95% CI = 0.717-0.893), respectively.
These findings show that metabonomic analysis has great potential to be applied to sarcopenia. The identified metabolites could be potential biomarkers and could be used to study sarcopenia pathomechanisms.
非靶向代谢组学可用于扩展我们对肌少症发病机制的理解。然而，肌少症患者的代谢特征尚未得到彻底研究。在此，我们通过非靶向气相色谱（GC）/液相色谱（LC）-质谱（MS）探索与肌少症相关的代谢物，并确定可能的诊断标志物。
将 48 例肌少症老年患者与 48 例非肌少症老年患者按年龄和性别匹配。我们首先使用非靶向 GC/LC-MS 分析这些参与者的血浆，然后结合大量多元统计分析来分析数据。最后，基于对代谢物的多维分析，将最关键的代谢物视为肌少症的生物标志物。
根据变量在项目中的重要性（VIP>1）和 t 检验的 p 值（p<0.05），通过 GC-MS 共鉴定出 55 种代谢物，通过 LC-MS 共鉴定出 85 种代谢物，这些代谢物主要为脂质和类脂分子。在排名前 20 的代谢物中，7 种磷脂酰胆碱、7 种溶血磷脂酰胆碱（LysoPCs）、磷脂酰肌醇、神经鞘磷脂、棕榈酰胺、L-2-氨基-3-氧代丁酸和棕榈酸在肌少症组中下调；仅乙基胺上调。其中，LysoPC（17:0）、L-2-氨基-3-氧代丁酸和棕榈酸的三种代谢物具有非常好的预测能力，AUC 值分别为 0.887（95%CI=0.817-0.957）、0.836（95%CI=0.751-0.921）和 0.805（95%CI=0.717-0.893）。
这些发现表明代谢组学分析在肌少症中有很大的应用潜力。鉴定出的代谢物可能是潜在的生物标志物，可用于研究肌少症发病机制。
