Kelimu Alimujiang, Xie Rong, Zhang Kuiming, Zhuang Zhongwei, Mamtimin Batur, Sheyhidin Ilyar
Department of Thoracic Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Neurol India. 2016 Mar-Apr;64(2):246-51. doi: 10.4103/0028-3886.177606.
The presence of a glioma is associated with increasing mortality. In this study, nuclear magnetic resonance (NMR) based metabonomics has been applied to investigate the metabolic signatures of a glioma in plasma. The purpose of this study was to assess the diagnostic potential of this approach and gain novel insights into the metabolism of glioma and its systemic effects.
Plasma samples were collected prospectively by centrifugation of blood samples from patients with a glioma (n = 70) or a control group (n = 70). NMR spectra of these plasma samples were analyzed using orthogonal partial least square discriminant analysis (OPLS-DA) to identify the potential biomarkers.
The OPLS-DA model showed a good differentiation between the glioma and the control groups. A total of 20 metabolites were identified, which are closely correlating with the presence of a glioma. Compared to the control group, patients with a glioma were associated with lower concentrations of isoleucine, leucine, valine, lactate, alanine, glycoprotein, glutamate, citrate, creatine, myo-inositol, choline, tyrosine, phenylalanine, 1-methylhistidine, α-glucose, β-glucose, and higher concentrations of very low density lipoprotein, low density lipoprotein (LDL), unsaturated lipid, and pyruvate. These 20 metabolites, which are involved in energy, fatty acid, and amino acid metabolism, may be associated with a human glioma.
Our study is the first one to identify the plasma metabolites that have the potential to distinguish between patients with a glioma and healthy subjects. NMR-based metabonomics provides a good sensitivity and selectivity in differentiating the healthy control group from patients suffering form the disease. Plasma metabolic profiling may have a potential in diagnosing a glioma in the early phase and may help in enhancing our understanding of its underlying mechanisms.
胶质瘤的存在与死亡率增加相关。在本研究中,基于核磁共振(NMR)的代谢组学已被应用于研究血浆中胶质瘤的代谢特征。本研究的目的是评估这种方法的诊断潜力,并获得对胶质瘤代谢及其全身影响的新见解。
通过离心收集来自胶质瘤患者(n = 70)或对照组(n = 70)的血液样本,前瞻性地获取血浆样本。使用正交偏最小二乘判别分析(OPLS-DA)分析这些血浆样本的NMR光谱,以鉴定潜在的生物标志物。
OPLS-DA模型显示胶质瘤组与对照组之间有良好的区分。共鉴定出20种代谢物,它们与胶质瘤的存在密切相关。与对照组相比,胶质瘤患者的异亮氨酸、亮氨酸、缬氨酸、乳酸、丙氨酸、糖蛋白、谷氨酸、柠檬酸、肌酸、肌醇、胆碱、酪氨酸、苯丙氨酸、1-甲基组氨酸、α-葡萄糖、β-葡萄糖浓度较低,而极低密度脂蛋白、低密度脂蛋白(LDL)、不饱和脂质和丙酮酸浓度较高。这20种参与能量、脂肪酸和氨基酸代谢的代谢物可能与人类胶质瘤有关。
我们的研究是首次鉴定出有可能区分胶质瘤患者和健康受试者的血浆代谢物。基于NMR的代谢组学在区分健康对照组和患病患者方面具有良好的敏感性和选择性。血浆代谢谱分析在早期诊断胶质瘤方面可能具有潜力,并可能有助于增强我们对其潜在机制的理解。