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. 2017 Feb 3:7:41473.
doi: 10.1038/srep41473.

Kynurenine pathway metabolomics predicts and provides mechanistic insight into multiple sclerosis progression

Chai K Lim  1   2 , Ayse Bilgin  3 , David B Lovejoy  1 , Vanessa Tan  1 , Sonia Bustamante  4 , Bruce V Taylor  5 , Alban Bessede  6 , Bruce J Brew  7   8 , Gilles J Guillemin  1   7
Affiliations

Kynurenine pathway metabolomics predicts and provides mechanistic insight into multiple sclerosis progression

Chai K Lim et al. Sci Rep. .

Abstract

Activation of the kynurenine pathway (KP) of tryptophan metabolism results from chronic inflammation and is known to exacerbate progression of neurodegenerative disease. To gain insights into the links between inflammation, the KP and multiple sclerosis (MS) pathogenesis, we investigated the KP metabolomics profile of MS patients. Most significantly, we found aberrant levels of two key KP metabolites, kynurenic acid (KA) and quinolinic acid (QA). The balance between these metabolites is important as it determines overall excitotoxic activity at the N-methyl-D-Aspartate (NMDA) receptor. We also identified that serum KP metabolic signatures in patients can discriminate clinical MS subtypes with high sensitivity and specificity. A C5.0 Decision Tree classification model discriminated the clinical subtypes of MS with a sensitivity of 91%. After validation in another independent cohort, sensitivity was maintained at 85%. Collectively, our studies suggest that abnormalities in the KP may be associated with the switch from early-mild stage MS to debilitating progressive forms of MS and that analysis of KP metabolites in MS patient serum may have application as MS disease biomarkers.

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Conflict of interest statement

Several authors (C.K.L., G.J.G. and B.J.B.) are named inventors on international patent specifications “Method and prognostic kit for monitoring multiple sclerosis (MS)” initially published in 2013 (WO/2015/008111) that contain partial information found in this manuscript. All other authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Overview of the kynurenine pathway with box plots of tryptophan (A), kynurenine (B), kynurenine/tryptophan (Kyn/Trp or K/T) ratio (C), kynurenic acid (D), quinolinic acid (E) NAD+ (F) and quinolinic acid/kynurenic acid (QA/KA) ratio (G) in healthy control (HC), relapsing-remitting MS (RR), secondary progressive MS (SP) and primary progressive MS (PP) cohorts. The diagram illustrate how inflammation can influence the pathway leading to enhance (blue arrows) in some downstream metabolites such as 3-Hydroxykynurenine (3-HK), Anthranilic acid (AA) and 3-Hydroxyanthranilic acid (3-HAA) but not others (red dotted arrows), i.e. kynurenic acid, picolinic acid and nicotinamide adenine dinucleotide (NAD+) based on patients with MS when compared to healthy control. The aberrant KP change in MS can potentially lead to mood/behavioural and sleep abnormalities, excitotoxicity-induced neurodegeneration and energy depletion related to cognitive fatigue in MS.
Figure 2
Figure 2. Biomarker for predicting MS severity using in silico approach.
(A) Classification modelling was based on exploratory analysis on the variables in the dataset with the shortlisted six predictors, i.e., QA, PA, KA, FGF-basic, TRP and TNF-α and its ranked importance for the predictive analytics. (B) Training Set using a C5.0 Decision Tree comprised of pie chart proportions of healthy control or MS subtype after being split by the six predictors. To optimize the split, calculated cut-off concentrations for each predictor were determined by the analytic software. The aim is to define a set of predictors that results in a full circle for each experimental group. For example, a QA concentration ≥494 nM (#) results in isolation of the SP and PP MS subtypes, then applying a PA concentration of <313 nM (#), as the next predictor, results in 89.1% isolation of the PP MS subtype. The experimental groups are denoted: healthy control (HC; green), RRMS (RR; yellow), SPMS (SP; orange) and PPMS (PP; red). (C) The numbers of observed and correctly predicted HC and MS subtype in the Training Set are shown (blue boxes) along with proportions of true (sensitivity) and false (specificity) predictions. (D) A different Test Set was used to validate the predictive model built from the Training Set. The numbers of observed and correctly predicted HC and MS subtype in the Test Set are shown (blue boxes) along with proportions of true (sensitivity) and false (specificity) predictions.
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References

    1. Trapp B. D. & Nave K. A. Multiple sclerosis: an immune or neurodegenerative disorder? Annu Rev Neurosci 31, 247–269 (2008). - PubMed
    1. Weiner H. L. The challenge of multiple sclerosis: how do we cure a chronic heterogeneous disease? Ann Neurol 65, 239–248 (2009). - PubMed
    1. O’Connor J. C. et al.. Interferon-γ and Tumor Necrosis Factor-α Mediate the Upregulation of Indoleamine 2,3-Dioxygenase and the Induction of Depressive-Like Behavior in Mice in Response to Bacillus Calmette-Guérin. The Journal of Neuroscience 29, 4200–4209 (2009). - PMC - PubMed
    1. Guillemin G. J. et al.. IFN-beta1b induces kynurenine pathway metabolism in human macrophages: potential implications for multiple sclerosis treatment. J Interferon Cytokine Res 21, 1097–1101 (2001). - PubMed
    1. Guillemin G. J. Quinolinic acid, the inescapable neurotoxin. FEBS J 279, 1356–1365 (2012). - PubMed

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