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Maybe an urine test is closer than we think:

Source:

http://pubs.acs.org/doi/abs/10.1021/acs ... me.5b01111

Abstract

Urine is a metabolite rich bio-fluid that reflects the body’s effort to maintain chemical and osmotic homeostasis. Clinical diagnosis routinely relies on urine samples since the collection process is easy and non-invasive.

Despite these advantages, urine is an under-investigated source of biomarkers for multiple sclerosis (MS).

Nuclear magnetic resonance spectroscopy (NMR) has become a common approach for analyzing urinary metabolites for disease diagnosis and biomarker discovery. To illustrate the potential of urinary metabolites for diagnosing and treating MS patients, and for differentiating between MS and other illnesses; 38 urine samples were collected from healthy controls, MS patients, and neuromyelitis optica-spectrum disorder (NMO-SD) patients and analyzed with NMR and multivariate statistics. Urine from MS patients exhibited a statistically distinct metabolic signature from healthy and NMO-SD controls. A total of 27 metabolites were differentially altered in the urine from MS and NMO-SD patients; and were associated with synthesis and degradation of ketone bodies, amino acid, propionate and pyruvate metabolism, tricarboxylic acid cycle, and glycolysis.

Metabolites altered in urine from MS patients were shown to be related to known pathogenic processes relevant to MS, including alterations in energy and fatty acid metabolism, mitochondrial activity, and the gut microbiota.

More about urine tests. Not too much information for MS diagnosis, but at least it can help to make a difference respect NMO

The Urine Proteome Profile Is Different in Neuromyelitis Optica Compared to Multiple Sclerosis

http://www.neurology.org/content/86/16_ ... .304.short

Background: Inflammatory demyelinating diseases of the CNS comprise a spectrum of diseases like neuromyelitis optica spectrum disorders (NMO-SD) and multiple sclerosis (MS). Despite clear classification criteria differentiation can be difficult.

Objective: We hypothesized, that analysis of ”omics” in urine might have the capacity to yield quantitative biomarkers. In addition, MS and NMO-SD patients may exhibit specific differences in the molecular composition of the urine, which reflect the pathogenesis, and may enable early differentiation. Specifically, the hypothesis is tested by a thorough and unbiased analysis of the whole proteome.

Methods: Urine samples from anti-aquaporin 4 (AQP4) seropositive NMO-SD patients (n=32), patients with MS (n=46) and healthy subjects (HS, n=31) were examined by liquid chromatography- tandem mass spectrometry (LC-MS/MS).

Results: The analysis identified a total of 1112 proteins of which 333 were shared by all 109 subjects. Cluster analysis revealed differences in the proteome of NMO-SD compared to both HS and MS, but no clear clusters when MS was compared to HS. Principal component analysis and false discovery rate adjustments suggested that the NMO-SD proteome is useful for classification and indicated a panel of 31 proteins significant for NMO-SD/HS discrimination, 4 for NMO-SD/MS discrimination and 1 for MS/HS discrimination. Significant up-regulation of immunoglobulin components (IgG, γ3 heavy chain and κ and λ light chains) in the urine differentiated NMO from both HS and MS. Multivariate logistic regression analysis revealed a 3-protein profile for NMO/HS discrimination, a 6-protein profile for NMO-SD/MS discrimination and an 11-protein profile for MS/HS discrimination. Conclusion: The proteome profile of the urine in patients with NMO is different from urine of HS and MS patients. This may reflect differences in the pathogenesis of NMO and MS and suggest that urine may be a useful starting point for identifying biomarkers for MS and NMO.