Objective: 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.Methods: 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.Results: 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.Conclusions: 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.
Classification of evidence:This study provides Class II evidence that serum metabolite profiles accurately distinguish patients with different subtypes and stages of MS. Neurology ® 2014;83:1492-1499 GLOSSARY AD 5 Alzheimer disease; ALS 5 amyotrophic lateral sclerosis; AUC 5 area under the curve; MS 5 multiple sclerosis; NMR 5 nuclear magnetic resonance; PLS-DA 5 partial least squares discriminant analysis; PP 5 primary progressive; ROC 5 receiver operator characteristic; RR 5 relapsing-remitting; SP 5 secondary progressive.The transition from relapsing-remitting (RR) to secondary progressive (SP) multiple sclerosis (MS) occurs subtly and is difficult to define clinically.1 Identifying biomarkers that can distinguish between the different clinical phenotypes of MS is an important goal to ensure that the appropriate treatment regimens are adopted in a timely fashion.2-4 Furthermore, such biomarkers may provide new insight into the pathologic basis for the progressive process and lead to the development of effective treatments for disability prevention. Metabolomic profiling of biofluids with high-resolution proton nuclear magnetic resonance (NMR) spectroscopy and partial least squares discriminant analysis (PLS-DA), 6 a multivariate statistical pattern recognition technique, can be used to identify metabolites that vary in a correlated fashion within individual groups. 7,8 This approach enables patterns of metabolite variation that are characteristic of a specific disease to be defined, rather than requiring identification of a unique, candidate-led biomarke...