{"title":"Metabolic signatures and potential biomarkers of sarcopenia in suburb-dwelling older Chinese: based on untargeted GC–MS and LC–MS","authors":"Peipei Han, Chunhua Yuan, Xiaoyu Chen, Yuanqing Hu, Xiaodan Hu, Zhangtao Xu, Qi Guo","doi":"10.1186/s13395-024-00337-3","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":21747,"journal":{"name":"Skeletal Muscle","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Skeletal Muscle","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13395-024-00337-3","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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大我们对肌肉疏松症发病机制的了解。然而,我们尚未对肌肉疏松症患者的代谢特征进行深入研究。在此,我们通过非靶向气相色谱(GC)/液相色谱(LC)-质谱法(MS)研究了与肌肉疏松症相关的代谢物,并确定了可能的诊断标志物。48 名患有肌肉疏松症的老年受试者与 48 名未患有肌肉疏松症的老年受试者在年龄和性别上进行了配对。我们首先使用非靶向气相色谱/液相色谱-质谱法对这些受试者的血浆进行分析,然后结合大量的多元统计分析对数据进行分析。最后,根据对代谢物的多维分析,认为最关键的代谢物是肌肉疏松症的生物标志物。根据变量在项目中的重要性(VIP > 1)和 t 检验的 p 值(p < 0.05),通过气相色谱-质谱联用仪(GC-MS)和液相色谱-质谱联用仪(LC-MS),共鉴定出 55 种代谢物存在于肌肉疏松症受试者和正常对照组之间,其中大部分是脂类和类脂分子。在前20种代谢物中,有7种磷脂酰胆碱、7种溶血磷脂酰胆碱(溶血磷脂酰胆碱)、磷脂酰肌醇、鞘磷脂、棕榈酰胺、L-2-氨基-3-氧代丁酸和棕榈酸在肌肉疏松症组中下调,只有乙胺上调。其中,LysoPC(17:0)、L-2-氨基-3-氧代丁酸和棕榈酸这三种代谢物显示出很好的预测能力,其AUC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,代谢组学分析在应用于肌肉疏松症方面具有很大的潜力。所鉴定的代谢物可能是潜在的生物标记物,可用于研究肌肉疏松症的病理机制。
期刊介绍:
The only open access journal in its field, Skeletal Muscle publishes novel, cutting-edge research and technological advancements that investigate the molecular mechanisms underlying the biology of skeletal muscle. Reflecting the breadth of research in this area, the journal welcomes manuscripts about the development, metabolism, the regulation of mass and function, aging, degeneration, dystrophy and regeneration of skeletal muscle, with an emphasis on understanding adult skeletal muscle, its maintenance, and its interactions with non-muscle cell types and regulatory modulators.
Main areas of interest include:
-differentiation of skeletal muscle-
atrophy and hypertrophy of skeletal muscle-
aging of skeletal muscle-
regeneration and degeneration of skeletal muscle-
biology of satellite and satellite-like cells-
dystrophic degeneration of skeletal muscle-
energy and glucose homeostasis in skeletal muscle-
non-dystrophic genetic diseases of skeletal muscle, such as Spinal Muscular Atrophy and myopathies-
maintenance of neuromuscular junctions-
roles of ryanodine receptors and calcium signaling in skeletal muscle-
roles of nuclear receptors in skeletal muscle-
roles of GPCRs and GPCR signaling in skeletal muscle-
other relevant aspects of skeletal muscle biology.
In addition, articles on translational clinical studies that address molecular and cellular mechanisms of skeletal muscle will be published. Case reports are also encouraged for submission.
Skeletal Muscle reflects the breadth of research on skeletal muscle and bridges gaps between diverse areas of science for example cardiac cell biology and neurobiology, which share common features with respect to cell differentiation, excitatory membranes, cell-cell communication, and maintenance. Suitable articles are model and mechanism-driven, and apply statistical principles where appropriate; purely descriptive studies are of lesser interest.