Neurology · 2014
A type 2 biomarker separates relapsing-remitting from secondary progressive multiple sclerosis.
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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
Аннотация
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.
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.
Предметные рубрики MeSH
AdultAgedAlzheimer DiseaseAmyotrophic Lateral SclerosisBiomarkersCase-Control StudiesCohort StudiesDiscriminant AnalysisFemaleHumansMagnetic Resonance SpectroscopyMaleMetabolomicsMiddle AgedMultiple Sclerosis, Chronic ProgressiveMultiple Sclerosis, Relapsing-RemittingROC CurveReproducibility of Results