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基于(1)h NMR 光谱代谢组学在肺结核患者血清中的应用。

Application of (1)h NMR spectroscopy-based metabolomics to sera of tuberculosis patients.

机构信息

Laboratory of Bacterial Pathogenesis, Department of Microbiology and Immunology, Institutes of Medical Sciences, Shanghai Jiao Tong University School of Medicine , 280 South Chongqing Road, Shanghai 200025, China.

出版信息

J Proteome Res. 2013 Oct 4;12(10):4642-9. doi: 10.1021/pr4007359. Epub 2013 Sep 10.

Abstract

Nuclear magnetic resonance (NMR) spectroscopy is an ideal platform for the metabolic analysis of biofluids due to its high reproducibility, nondestructiveness, nonselectivity in metabolite detection, and the ability to simultaneously quantify multiple classes of metabolites. Tuberculosis (TB) is a chronic wasting inflammatory disease characterized by multisystem involvement, which can cause metabolic derangements in afflicted patients. In this study, we combined multivariate pattern recognition (PR) analytical techniques with (1)H NMR spectroscopy to explore the metabolic profile of sera from TB patients. A total of 77 serum samples obtained from patients with TB (n = 38) and healthy controls (n = 39) were investigated. Orthogonal partial least-squares discriminant analysis (OPLS-DA) was capable of distinguishing TB patients from controls and establishing a TB-specific metabolite profile. A total of 17 metabolites differed significantly in concentration between the two groups. Serum samples from TB patients were characterized by increased concentrations of 1-methylhistidine, acetoacetate, acetone, glutamate, glutamine, isoleucine, lactate, lysine, nicotinate, phenylalanine, pyruvate, and tyrosine, accompanied by reduced concentrations of alanine, formate, glycine, glycerolphosphocholine, and low-density lipoproteins relative to control subjects. Our study reveals the metabolic profile of sera from TB patients and indicates that NMR-based methods can distinguish TB patients from healthy controls. NMR-based metabolomics has the potential to be developed into a novel clinical tool for TB diagnosis or therapeutic monitoring and could contribute to an improved understanding of disease mechanisms.

摘要

核磁共振(NMR)光谱是生物流体代谢分析的理想平台,因为它具有高重现性、非破坏性、对代谢物检测的非选择性,以及同时定量多种代谢物类别的能力。结核病(TB)是一种慢性消耗性炎症性疾病,其特征是多系统受累,这可能导致受影响患者的代谢紊乱。在这项研究中,我们结合多元模式识别(PR)分析技术和(1)H NMR 光谱,探索了 TB 患者血清的代谢特征。共研究了 77 例来自 TB 患者(n=38)和健康对照者(n=39)的血清样本。正交偏最小二乘判别分析(OPLS-DA)能够区分 TB 患者和对照者,并建立 TB 特异性代谢物特征。两组之间有 17 种代谢物的浓度差异具有统计学意义。TB 患者的血清样本特征为 1-甲基组氨酸、乙酰乙酸、丙酮、谷氨酸、谷氨酰胺、异亮氨酸、乳酸、赖氨酸、烟酸、苯丙氨酸、丙酮酸和酪氨酸的浓度增加,同时伴随丙氨酸、甲酸盐、甘氨酸、甘油磷酸胆碱和低密度脂蛋白的浓度降低。本研究揭示了 TB 患者血清的代谢特征,并表明 NMR 方法可将 TB 患者与健康对照者区分开来。基于 NMR 的代谢组学有可能发展成为 TB 诊断或治疗监测的新型临床工具,并有助于更好地了解疾病机制。

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