The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong Province, PR China.
Lupus. 2011 Nov;20(13):1411-20. doi: 10.1177/0961203311418707. Epub 2011 Oct 5.
Systemic lupus erythematosus (SLE) is a chronic inflammatory disease characterized by multi-system involvement, diverse clinical presentation, and alterations in circulating metabolites. In this study, a (1)H NMR spectroscopy-based metabolomics approach was applied to establish a human SLE serum metabolic profile. Serum samples were obtained from patients with SLE (n = 64), patients with rheumatoid arthritis (RA) (n = 30) and healthy controls (n = 35). The NOESYPR1D spectrum combined with multi-variate pattern recognition analysis was used to cluster the groups and establish a disease-specific metabolites phenotype. Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) models were capable of distinguishing SLE or RA patients from healthy subjects. The OPLS-DA model was able to predict diagnosis of SLE with a sensitivity rate of 60.9% and a specificity rate of 97.1%. For diagnosing RA, the model has much higher sensitivity (96.7%) and specificity (91.4%). The SLE serum samples were characterized by reduced concentrations of valine, tyrosine, phenylalanine, lysine, isoleucine, histidine, glutamine, alanine, citrate, creatinine, creatine, pyruvate, high-density lipoprotein, cholesterol, glycerol, formate and increased concentrations of N-acetyl glycoprotein, very low-density lipoprotein and low-density lipoprotein in comparison with the control population. The results not only indicated that serum NMR-based metabolomic methods had sufficient sensitivity and specificity to distinguish SLE and RA from healthy controls, but also have the potential to be developed into a clinically useful diagnostic tool, and could also contribute to a further understanding of disease mechanisms.
系统性红斑狼疮（SLE）是一种慢性炎症性疾病，其特征为多系统受累、临床表现多样以及循环代谢物改变。在本研究中，我们采用基于（1）H NMR 波谱的代谢组学方法建立了人类 SLE 血清代谢特征谱。我们从 SLE 患者（n=64）、类风湿关节炎（RA）患者（n=30）和健康对照者（n=35）中获得血清样本。我们采用 NOESYPR1D 谱结合多元模式识别分析对组进行聚类，并建立疾病特异性代谢物表型。主成分分析（PCA）和正交偏最小二乘判别分析（OPLS-DA）模型能够区分 SLE 或 RA 患者与健康受试者。OPLS-DA 模型能够以 60.9%的灵敏度和 97.1%的特异性预测 SLE 的诊断。对于 RA 的诊断，该模型具有更高的灵敏度（96.7%）和特异性（91.4%）。与对照组相比，SLE 血清样本的特征为缬氨酸、酪氨酸、苯丙氨酸、赖氨酸、异亮氨酸、组氨酸、谷氨酰胺、丙氨酸、柠檬酸、肌酐、肌酸、丙酮酸、高密度脂蛋白、胆固醇、甘油、甲酸盐的浓度降低，N-乙酰糖蛋白、极低密度脂蛋白和低密度脂蛋白的浓度升高。这些结果不仅表明基于血清 NMR 的代谢组学方法具有足够的灵敏度和特异性来区分 SLE 和 RA 与健康对照者，而且具有发展为临床有用的诊断工具的潜力，还可能有助于进一步了解疾病机制。
