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Celiac disease (CD) is a multifactorial disorder involving genetic and environmental factors, thus, having great potential impact on metabolism. This study aims at defining the metabolic signature of CD through Nuclear Magnetic Resonance (NMR) of urine and serum samples of CD patients. Thirty-four CD patients at diagnosis and 34 healthy controls were examined by ¹H NMR of their serum and urine. A CD patients’ subgroup was also examined after a gluten-free diet (GFD). Projection to Latent Structures provided data reduction and clustering, and Support Vector Machines provided pattern recognition and classification. The classification accuracy of CD and healthy control groups was 79.7−83.4% for serum and 69.3% for urine. Sera of CD patients were characterized by lower levels (P < 0.01) of several metabolites such as amino acids, lipids, pyruvate and choline, and by higher levels of glucose and 3 …