title: Putting the 'Ome' in lipid metabolism.
abstract: The recognition that altered lipid metabolism underlies many metabolic disorders challenging Western society highlights the importance of this metabolomic subset, herein referred to as the lipidome. Although comprehensive lipid analyses are not a recent concept, the novelty of a lipidomic approach lies with the application of robust statistical algorithms to highlight subtle, yet significant, changes in a population of lipid molecules. First-generation lipidomic studies have demonstrated the sensitivity of interpreting quantitative datasets with computational software; however, the innate power of comprehensive lipid profiling is often not exploited, as robust statistical models are not routinely utilized. Therefore, the current review aims to briefly describe the current technologies suitable for comprehensive lipid analysis, outline innovative mathematical models that have the ability to reveal subtle changes in metabolism, which will ameliorate our understanding of lipid biochemistry, and demonstrate the biological revelations found through lipidomic approaches and their potential implications for health management.
authors.affiliation: Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland.
authors.forename: David M
authors.initials: DM
authors.lastname: Mutch
authors.forename: Laetitia
authors.initials: L
authors.lastname: Fauconnot
authors.forename: Martin
authors.initials: M
authors.lastname: Grigorov
authors.forename: Laurent B
authors.initials: LB
authors.lastname: Fay
mesh_terms: D001709:Biotechnology / Q000379:methods; D002849:Chromatography, Gas / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D023281:Genomics / Q000379:methods; D050356:Lipid Metabolism; D008055:Lipids / Q000032:analysis; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D013058:Mass Spectrometry / Q000379:methods; D025341:Principal Component Analysis
chemical_list: D008055:Lipids