Metabolomic profile of systemic sclerosis patients

Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabo...

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Bibliographic Details
Published in:Scientific reports 2018-05, Vol.8 (1), p.7626-11, Article 7626
Main Authors: Murgia, Federica, Svegliati, Silvia, Poddighe, Simone, Lussu, Milena, Manzin, Aldo, Spadoni, Tatiana, Fischetti, Colomba, Gabrielli, Armando, Atzori, Luigi
Format: Article
Language:English
Subjects:
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Acetic acid
Alanine
Choline
Citric acid
Fibrosis
Fructose
Gluconeogenesis
Glutamine
Glycerol
Glycolysis
Humanities and Social Sciences
Ketones
Metabolism
Metabolites
Metabolomics
multidisciplinary
Multivariate analysis
NMR
Nuclear magnetic resonance
Pyruvic acid
Science
Science (multidisciplinary)
Scleroderma
Skin
Systemic sclerosis
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Summary:Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by 1 H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726–0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7–0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-018-25992-7