BACKGROUND: Derangements of one-carbon metabolism have been related to the development of chronic diseases. Metabolic profiling as part of epidemiological studies in this area should include intermediates involved in the transfer of one-carbon units, cofactors for the relevant enzymes and markers of inflammation, kidney function and smoking. METHODS: We established five platforms that measured 6-16 analytes each. Platforms A (gas chromatography-mass spectrometry; GC-MS) and B (gas chromatography-tandem mass spectrometry; GC-MS/MS) involved methylchloroformate derivatization of primary amines, thiols and carboxylic acids. Platform C determined basic compounds by liquid chromatography-tandem mass spectrometry (LC-MS/MS), using an ether-linked phenyl reversed-phase column. Platforms D and E (LC-MS/MS) exploited the efficient ionization and high sensitivity obtained for a wide range of analytes, using a mobile phase containing a high concentration of acetic acid. The chromatographic run times ranged from 3 to 8 min. RESULTS: The analyte concentrations ranged from 0.2 nmol/L to 400 micromol/L. Platforms A and B both measured methylmalonic acid, total homocysteine and related amino acids. Platform B also included sarcosine, cystathionine, tryptophan and kynurenine. Platform C was optimized for the measurement of choline and betaine, but also included arginine, asymmetric and symmetric dimethylarginine and creatinine. A diversity of low abundance compounds mainly occurring in the nanomolar range were measured on platform D. These were vitamin B(2) and B(6) species, neopterin, cotinine and tryptophan metabolites. Platform E measured folates and folate catabolites. CONCLUSIONS: Approximately 40 analytes related to one-carbon metabolism were determined in less than 1 mL of plasma/serum using five complementary analytical platforms. As a method control, several metabolites were measured on two or more platforms. Logistics and data handling were carried out by specially designed software. This strategy allows profiling of one-carbon metabolism in large-scale epidemiological studies.
BACKGROUND: Derangements of one-carbon metabolism have been related to the development of chronic diseases. Metabolic profiling as part of epidemiological studies in this area should include intermediates involved in the transfer of one-carbon units, cofactors for the relevant enzymes and markers of inflammation, kidney function and smoking. METHODS: We established five platforms that measured 6-16 analytes each. Platforms A (gas chromatography-mass spectrometry; GC-MS) and B (gas chromatography-tandem mass spectrometry; GC-MS/MS) involved methylchloroformate derivatization of primary amines, thiols and carboxylic acids. Platform C determined basic compounds by liquid chromatography-tandem mass spectrometry (LC-MS/MS), using an ether-linked phenyl reversed-phase column. Platforms D and E (LC-MS/MS) exploited the efficient ionization and high sensitivity obtained for a wide range of analytes, using a mobile phase containing a high concentration of acetic acid. The chromatographic run times ranged from 3 to 8 min. RESULTS: The analyte concentrations ranged from 0.2 nmol/L to 400 micromol/L. Platforms A and B both measured methylmalonic acid, total homocysteine and related amino acids. Platform B also included sarcosine, cystathionine, tryptophan and kynurenine. Platform C was optimized for the measurement of choline and betaine, but also included arginine, asymmetric and symmetric dimethylarginine and creatinine. A diversity of low abundance compounds mainly occurring in the nanomolar range were measured on platform D. These were vitamin B(2) and B(6) species, neopterin, cotinine and tryptophan metabolites. Platform E measured folates and folate catabolites. CONCLUSIONS: Approximately 40 analytes related to one-carbon metabolism were determined in less than 1 mL of plasma/serum using five complementary analytical platforms. As a method control, several metabolites were measured on two or more platforms. Logistics and data handling were carried out by specially designed software. This strategy allows profiling of one-carbon metabolism in large-scale epidemiological studies.
Authors: Roy M Nilsen; Anne-Lise Bjørke-Monsen; Oivind Midttun; Ottar Nygård; Eva R Pedersen; Arve Ulvik; Per Magnus; Håkon K Gjessing; Stein Emil Vollset; Per Magne Ueland Journal: Obstet Gynecol Date: 2012-06 Impact factor: 7.661
Authors: Gary M Shaw; Stein Emil Vollset; Suzan L Carmichael; Wei Yang; Richard H Finnell; Henk Blom; Per M Ueland Journal: Pediatr Res Date: 2009-11 Impact factor: 3.756
Authors: Vanessa R da Silva; Maria A Ralat; Eoin P Quinlivan; Barbara N DeRatt; Timothy J Garrett; Yueh-Yun Chi; H Frederik Nijhout; Michael C Reed; Jesse F Gregory Journal: Am J Physiol Endocrinol Metab Date: 2014-05-13 Impact factor: 4.310
Authors: Øystein Fluge; Olav Mella; Ove Bruland; Kristin Risa; Sissel E Dyrstad; Kine Alme; Ingrid G Rekeland; Dipak Sapkota; Gro V Røsland; Alexander Fosså; Irini Ktoridou-Valen; Sigrid Lunde; Kari Sørland; Katarina Lien; Ingrid Herder; Hanne Thürmer; Merete E Gotaas; Katarzyna A Baranowska; Louis Mlj Bohnen; Christoph Schäfer; Adrian McCann; Kristian Sommerfelt; Lars Helgeland; Per M Ueland; Olav Dahl; Karl J Tronstad Journal: JCI Insight Date: 2016-12-22
Authors: Vanessa R da Silva; Luisa Rios-Avila; Yvonne Lamers; Maria A Ralat; Øivind Midttun; Eoin P Quinlivan; Timothy J Garrett; Bonnie Coats; Meena N Shankar; Susan S Percival; Yueh-Yun Chi; Keith E Muller; Per Magne Ueland; Peter W Stacpoole; Jesse F Gregory Journal: J Nutr Date: 2013-08-21 Impact factor: 4.798