培养肌管和空腹血浆代谢物谱与2型糖尿病患者线粒体功能障碍的关系

IF 3.743 Q2 Biochemistry, Genetics and Molecular Biology
Mohamad Hafizi Abu Bakar and Mohamad Roji Sarmidi
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引用次数: 19

摘要

越来越多的证据表明,骨骼肌线粒体功能障碍诱导的胰岛素抵抗是2型糖尿病(T2D)最大特征的根本原因。然而,与T2D线粒体功能障碍相关的特定代谢物标记物的鉴定尚未得到充分解决。因此,我们试图确定与T2D相关的线粒体功能障碍的标志物代谢组学。首先,用抗霉素a(一种氧化磷酸化抑制剂)处理的人肌管建立细胞疾病模型。然后确定培养的线粒体功能障碍肌管中细胞内定义代谢物的非靶向代谢组学谱。此外,在一项横断面研究中,对正常(n = 32)和T2D (n = 37)受试者的空腹血浆进行了靶向MS-based代谢谱分析。多项逻辑回归分析用于确定95%组中前5%的代谢物,以确定区分代谢物。线粒体功能障碍的肌管表现出胰岛素抵抗、氧化应激和炎症,并伴有胰岛素信号活性受损。在培养的肌管中发现了四种代谢途径与线粒体功能障碍密切相关。来源于这些途径的代谢物在健康和患病受试者空腹血浆的独立试点调查中得到了验证。基于p值<的正交偏最小二乘判别分析(PLS-DA),针对特定基线调整的空腹血浆进行针对性代谢分析,发现245个显著特征;0.05. 在这些特征中,20种重要的代谢物主要包括支链和芳香氨基酸、谷氨酰胺、氨基丁酸、羟基异丁酸、焦谷氨酸、酰基肉碱(乙酰肉碱、丙酰肉碱、十二烷基肉碱、十四烷基肉碱、十六烷基肉碱和油基肉碱)、游离脂肪酸(棕榈酸酯、花生四烯酸酯、硬脂酸酯和亚油酸酯)和鞘磷脂(d18:2/16:0)被确定为T2D受试者线粒体功能障碍的预测标志物。目前的研究阐明了细胞代谢物如何提供与患病受试者体内代谢失调的生化变化相关的潜在特征。我们的发现为鉴定与培养肌管线粒体功能障碍相关的T2D强有力的生物标志物提供了额外的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Association of cultured myotubes and fasting plasma metabolite profiles with mitochondrial dysfunction in type 2 diabetes subjects

Association of cultured myotubes and fasting plasma metabolite profiles with mitochondrial dysfunction in type 2 diabetes subjects

Accumulating evidence implicates mitochondrial dysfunction-induced insulin resistance in skeletal muscle as the root cause for the greatest hallmarks of type 2 diabetes (T2D). However, the identification of specific metabolite-based markers linked to mitochondrial dysfunction in T2D has not been adequately addressed. Therefore, we sought to identify the markers-based metabolomics for mitochondrial dysfunction associated with T2D. First, a cellular disease model was established using human myotubes treated with antimycin A, an oxidative phosphorylation inhibitor. Non-targeted metabolomic profiling of intracellular-defined metabolites on the cultured myotubes with mitochondrial dysfunction was then determined. Further, a targeted MS-based metabolic profiling of fasting blood plasma from normal (n = 32) and T2D (n = 37) subjects in a cross-sectional study was verified. Multinomial logical regression analyses for defining the top 5% of the metabolites within a 95% group were employed to determine the differentiating metabolites. The myotubes with mitochondrial dysfunction exhibited insulin resistance, oxidative stress and inflammation with impaired insulin signalling activities. Four metabolic pathways were found to be strongly associated with mitochondrial dysfunction in the cultured myotubes. Metabolites derived from these pathways were validated in an independent pilot investigation of the fasting blood plasma of healthy and diseased subjects. Targeted metabolic analysis of the fasting blood plasma with specific baseline adjustment revealed 245 significant features based on orthogonal partial least square discriminant analysis (PLS-DA) with a p-value < 0.05. Among these features, 20 significant metabolites comprised primarily of branched chain and aromatic amino acids, glutamine, aminobutyric acid, hydroxyisobutyric acid, pyroglutamic acid, acylcarnitine species (acetylcarnitine, propionylcarnitine, dodecenoylcarnitine, tetradecenoylcarnitine hexadecadienoylcarnitine and oleylcarnitine), free fatty acids (palmitate, arachidonate, stearate and linoleate) and sphingomyelin (d18:2/16:0) were identified as predictive markers for mitochondrial dysfunction in T2D subjects. The current study illustrates how cellular metabolites provide potential signatures associated with the biochemical changes in the dysregulated body metabolism of diseased subjects. Our finding yields additional insights into the identification of robust biomarkers for T2D associated with mitochondrial dysfunction in cultured myotubes.

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来源期刊
Molecular BioSystems
Molecular BioSystems 生物-生化与分子生物学
CiteScore
2.94
自引率
0.00%
发文量
0
审稿时长
2.6 months
期刊介绍: Molecular Omics publishes molecular level experimental and bioinformatics research in the -omics sciences, including genomics, proteomics, transcriptomics and metabolomics. We will also welcome multidisciplinary papers presenting studies combining different types of omics, or the interface of omics and other fields such as systems biology or chemical biology.
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