The metabonomic signature of celiac disease

J Proteome Res. 2009 Jan;8(1):170-7. doi: 10.1021/pr800548z.

Abstract

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 (1)H 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-hydroxybutyric acid, while urines showed altered levels (P < 0.05) of, among others, indoxyl sulfate, meta-[hydroxyphenyl]propionic acid and phenylacetylglycine. After 12 months of GFD, all but one of the patients were classified as healthy by the same statistical analysis. NMR thus reveals a characteristic metabolic signature of celiac disease. Altered serum levels of glucose and ketonic bodies suggest alterations of energy metabolism, while the urine data point to alterations of gut microbiota. Metabolomics may thus provide further hints on the biochemistry of the disease.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Autoantibodies / chemistry
  • Case-Control Studies
  • Celiac Disease / metabolism*
  • Celiac Disease / urine*
  • Energy Metabolism
  • Female
  • HLA Antigens / metabolism
  • Humans
  • Intestinal Mucosa / metabolism*
  • Intestinal Mucosa / microbiology
  • Intestines / microbiology
  • Magnetic Resonance Spectroscopy
  • Male
  • Metabolomics / methods*
  • Models, Statistical
  • Proteomics / methods*

Substances

  • Autoantibodies
  • HLA Antigens