title: Untargeted metabolomic analysis of human serum samples associated with different levels of red meat consumption: A possible indicator of type 2 diabetes?
abstract: Red meat consumption has been associated with negative health effects. A study to identify biomarkers of meat consumption was undertaken using serum samples collected from combining high resolution mass spectrometry (UPLC-QTof-MS) and chemometrics. Using orthogonal partial last-squares discriminant analysis (OPLS-DA), multivariate models were created for both modes of acquisition (ESI-/ESI+) and red meat intake classes (YES/NO). In the serum samples, a total 3280 and 3225 ions of interest were detected in positive and negative modes, respectively. Of these, 62 were found to be significantly different (p<0.05) between the two groups. Glycerophospholipids as well as other family lipids, such as lysophospholipids or sphingomyelin, were found significantly (p<0.05) different between yes and no red meat intake groups. This study has shown metabolomics fingerprints have the capability to identify potential biomarkers of red meat consumption, as well as possible health risk factors (e.g., key metabolic families related to the risk of development type 2 diabetes).
authors.affiliation: Institute for Global Food Security, Queen's University Belfast, 18-30 Malone Road, BT9 5BN Northern Ireland, United Kingdom; Astrobiology Centre (INTA-CSIC), Dept. of Planetology and Habitability, Torrejón de Ardóz 28850, Madrid, Spain. Electronic address: dcarrizo@cab.inta-csic.es.
authors.forename: Daniel
authors.initials: D
authors.lastname: Carrizo
authors.affiliation: Institute for Global Food Security, Queen's University Belfast, 18-30 Malone Road, BT9 5BN Northern Ireland, United Kingdom.
authors.forename: Olivier P
authors.initials: OP
authors.lastname: Chevallier
authors.affiliation: UKCRC Centre of Excellence for Public Health (Northern Ireland), Institute of Clinical Science B, Royal Victoria Hospital, Grosvenor Road, Belfast BT12 6BJ, United Kingdom.
authors.forename: Jayne V
authors.initials: JV
authors.lastname: Woodside
authors.affiliation: Centre for Public Health, School of Medicine, Dentistry and Biomedical Science, Queen's University Belfast, Belfast BT12 6BA, United Kingdom.
authors.forename: Sarah F
authors.initials: SF
authors.lastname: Brennan
authors.affiliation: Centre for Public Health, School of Medicine, Dentistry and Biomedical Science, Queen's University Belfast, Belfast BT12 6BA, United Kingdom.
authors.forename: Marie M
authors.initials: MM
authors.lastname: Cantwell
authors.affiliation: Institute for Global Food Security, Queen's University Belfast, 18-30 Malone Road, BT9 5BN Northern Ireland, United Kingdom.
authors.forename: Geraldine
authors.initials: G
authors.lastname: Cuskelly
authors.affiliation: Institute for Global Food Security, Queen's University Belfast, 18-30 Malone Road, BT9 5BN Northern Ireland, United Kingdom.
authors.forename: Christopher T
authors.initials: CT
authors.lastname: Elliott
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood*; D015992:Body Mass Index; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000175:diagnosis; D004032:Diet; D016002:Discriminant Analysis; D005260:Female; D020404:Glycerophospholipids / Q000097:blood; D006801:Humans; D008246:Lysophospholipids / Q000097:blood; D008297:Male; D013058:Mass Spectrometry; D055442:Metabolome; D000069466:Red Meat; D012307:Risk Factors; D013109:Sphingomyelins / Q000032:analysis
chemical_list: D015415:Biomarkers; D020404:Glycerophospholipids; D008246:Lysophospholipids; D013109:Sphingomyelins
keywords: Biomarkers analysis; Diabetes; Health risk factors; Lipids; Metabolomics; Red meat consumption; UPLC-QTof-MS