Dickens Alex M, Larkin James R, Griffin Julian L, Cavey Ana, Matthews Lucy, Turner Martin R, Wilcock Gordon K, Davis Benjamin G, Claridge Timothy D W, Palace Jacqueline, Anthony Daniel C, Sibson Nicola R
From the CR-UK/MRC Gray Institute for Radiation Oncology and Biology (A.M.D., J.R.L., N.R.S.), Department of Pharmacology (A.M.D., D.C.A.), Department of Chemistry (A.M.D., B.G.D., T.D.W.C.), Nuffield Department of Clinical Neurosciences (A.C., L.M., M.R.T.), and Nuffield Department of Medicine (G.K.W.), University of Oxford; and the Department of Biochemistry (J.L.G., J.P.), University of Cambridge, UK.
Neurology. 2014 Oct 21;83(17):1492-9. doi: 10.1212/WNL.0000000000000905. Epub 2014 Sep 24.
We tested whether it is possible to differentiate relapsing-remitting (RR) from secondary progressive (SP) disease stages in patients with multiple sclerosis (MS) using a combination of nuclear magnetic resonance (NMR) metabolomics and partial least squares discriminant analysis (PLS-DA) of biofluids, which makes no assumptions on the underlying mechanisms of disease.
Serum samples were obtained from patients with primary progressive MS (PPMS), SPMS, and RRMS; patients with other neurodegenerative conditions; and age-matched controls. Samples were analyzed by NMR and PLS-DA models were derived to separate disease groups.
The PLS-DA models for serum samples from patients with MS enabled reliable differentiation between RRMS and SPMS. This approach also identified significant differences between the metabolite profiles of each of the MS groups (PP, SP, and RR) and the healthy controls, as well as predicting disease group membership with high specificity and sensitivity.
NMR metabolomics analysis of serum is a sensitive and robust method for differentiating between different stages of MS, yielding diagnostic markers without a priori knowledge of disease pathogenesis. Critically, this study identified and validated a type II biomarker for the RR to SP transition in patients with MS. This approach may be of considerable benefit in categorizing patients for treatment and as an outcome measure in future clinical trials.
This study provides Class II evidence that serum metabolite profiles accurately distinguish patients with different subtypes and stages of MS.
我们测试了使用核磁共振（NMR）代谢组学和生物流体的偏最小二乘判别分析（PLS-DA）相结合的方法，能否区分多发性硬化症（MS）患者的复发缓解型（RR）和继发进展型（SP）疾病阶段，该方法不对疾病的潜在机制做任何假设。
从原发进展型MS（PPMS）、继发进展型MS（SPMS）和复发缓解型MS（RRMS）患者、患有其他神经退行性疾病的患者以及年龄匹配的对照组中获取血清样本。通过NMR对样本进行分析，并推导PLS-DA模型以区分疾病组。
MS患者血清样本的PLS-DA模型能够可靠地区分RRMS和SPMS。该方法还确定了每个MS组（PP、SP和RR）与健康对照组代谢物谱之间的显著差异，并以高特异性和敏感性预测疾病组成员身份。
血清的NMR代谢组学分析是区分MS不同阶段的一种敏感且稳健的方法，无需先验的疾病发病机制知识即可产生诊断标志物。至关重要的是，本研究识别并验证了MS患者从RR向SP转变的II型生物标志物。这种方法在对患者进行治疗分类以及作为未来临床试验的结果指标方面可能具有相当大的益处。
本研究提供了II类证据，表明血清代谢物谱能够准确区分不同亚型和阶段的MS患者。
