title: Dietary intake patterns are reflected in metabolomic profiles: potential role in dietary assessment studies.
abstract: BACKGROUND
  It has been suggested that metabolomics could play a role in dietary assessment and identification of novel biomarkers of dietary intake.
  
  
  OBJECTIVE
  This study examined the link between habitual dietary patterns and metabolomic profiles.
  
  
  METHODS
  A total of 160 volunteers participated in a double-blind, randomized, placebo-controlled dietary intervention. We collected biofluids and recorded 3-d food diaries. Food data were reduced to 33 food groups, and a k-means cluster analysis was performed to identify dietary patterns. (1)H Nuclear magnetic resonance (NMR) spectra were acquired for plasma and urine samples, and gas chromatography was used for plasma fatty acid profiling.
  
  
  RESULTS
  Cluster analysis identified 3 distinct dietary patterns on the basis of the energy contribution of different food groups. Dietary clusters were reflected in plasma fatty acid profiles and in metabolomic data. (1)H NMR spectra of urine allowed the identification of metabolites associated with different dietary patterns. Several of the metabolites identified were linked to the intake of specific food groups; in particular, there was a positive association between O-acetylcarnitine and phenylacetylglutamine and red-meat and vegetable intakes, respectively.
  
  
  CONCLUSIONS
  Habitual dietary patterns are shown in metabolomic data. This approach successfully identified potential biomarkers of red-meat and vegetable intakes.
authors.affiliation: Institute of Food and Health, University College Dublin, Dublin, Ireland.
authors.forename: Aifric
authors.initials: A
authors.lastname: O'Sullivan
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Gibney
authors.forename: Lorraine
authors.initials: L
authors.lastname: Brennan
mesh_terms: D000108:Acetylcarnitine / Q000652:urine; D000293:Adolescent; D000328:Adult; D015415:Biomarkers / Q000032:analysis* / Q000097:blood / Q000652:urine; D002849:Chromatography, Gas; D016000:Cluster Analysis; D004032:Diet; D015930:Diet Records; D004311:Double-Blind Method; D002149:Energy Intake; D005227:Fatty Acids / Q000097:blood; D005260:Female; D005973:Glutamine / Q000031:analogs & derivatives / Q000652:urine; D006801:Humans; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D008460:Meat; D055442:Metabolome; D008875:Middle Aged; D015596:Nutrition Assessment; D014675:Vegetables; D055815:Young Adult
chemical_list: D015415:Biomarkers; D005227:Fatty Acids; D005973:Glutamine; D000108:Acetylcarnitine; C003089:phenylacetylglutamine