A metabonomics investigation of multiple sclerosis by nuclear magnetic resonance

Abstract

Multiple sclerosis (MS) is a nervous system disease that affects the fatty myelin sheaths around the axons of the brain and spinal cord, leading to demyelination and a broad range of signs and symptoms. MS can be difficult to diagnose because its signs and symptoms may be similar to other medical problems. To find out which metabolites in serum are effective for the diagnosis of MS, we utilized metabolic profiling using proton nuclear magnetic resonance spectroscopy ((1)H-NMR). Random forest (RF) was used to classify the MS patients and healthy subjects. Atomic absorption spectroscopy was used to measure the serum levels of selenium. The results showed that the levels of selenium were lower in the MS group, when compared with the control group. RF was used to identify the metabolites that caused selenium changes in people with MS by building a correlation model between these metabolites and serum levels of selenium. For the external test set, the obtained classification model showed a 93% correct classification of MS and healthy subjects. The regression model of levels of selenium and metabolites showed the correlation (R(2)) value of 0.88 for the external test set. The results indicate the suitability of NMR as a screen for identifying MS patients and healthy subjects. A novel model with good prediction outcomes was constructed between serum levels of selenium and NMR data.

Metabolomic profiling of CSF in multiple sclerosis and neuromyelitis optica spectrum disorder by nuclear magnetic resonance

“…Control group of reference [19, 21, 23, 28, 29] are healthy volunteers and control groups in reference [20, 24, 25, 27] have other disease except MS.…”

Application of metabolomics in autoimmune diseases: Insight into biomarkers and pathology

“…Recently, 1 H-NMR spectra has been employed to monitor serum from patients with multiple sclerosis (Mehrpour et al, 2013). There were nine metabolites including lipid, leucine/isoleucine, valine, lactate, alanine, glutamine, creatine and glucose being identified.…”

“…Sample and analysis technique Biomarkers Lynch et al (1993) CSF, NMR spectroscopy Acetate, formate Nicoli et al (1996) CSF, MRS spectroscopy Lactate, pyruvate, alanine, lysine, valine, leucine-isoleucine, tyrosine, glutamine Simone et al (1996) CSF, MRS spectroscopy Lactate, formate, choline, glucose Aasly et al (1997) CSF, NMR spectroscopy Lactate, glutamine Lutz et al (2007) CSF, NMR spectroscopy Lactate, glutamine, fructose phenylalanine, β-hydroxyisobutyrate, acetate, β-glucose, creatinine, Regenold et al (2008) CSF, GC-MS spectroscopy Sorbitol, fructose, lactate Reinke et al (2014) CSF, NMR spectroscopy Choline, myo-inositol, 3-hydroxybutyrate, threonate, 2-hydroxyisovalerate, citrate, mannose, phenylalanine, Kirov et al (2013) Brain, MRSI spectroscopy N-acetylaspartate, choline, creatine, myo-inositol Mehrpour et al (2013) Serum, NMR spectroscopy Lipid, leucine/isoleucine, valine, lactate, alanine, glutamine, creatine, glucose, selenium Vingara et al (2013) Brain, MRS spectroscopy N-acetyl aspartate, lipids, myo-inositol, choline, creatine, γ-aminobutyric acid, glucose, aspartate Moussallieh et al (2014) Serum, NMR spectroscopy Scyllo-inositol, glutamine…”

Protective Effects of Selol Against Sodium Nitroprusside-Induced Cell Death and Oxidative Stress in PC12 Cells

“…Se deficit is further escalated (along ROS accumulation) in neurodegenerative disorders, particularly in the brains of AD patients [18–22]. Se concentration tends to decrease also in the serum of patients with MS [23] and in autopsy brains from patients with Huntington’s disease [24]. …”