LipidQC: Method Validation Tool for Visual Comparison to SRM 1950 Using NIST Interlaboratory Comparison Exercise Lipid Consensus Mean Estimate Values.

As advances in analytical separation techniques, mass spectrometry instrumentation, and data processing platforms continue to spur growth in the lipidomics field, more structurally unique lipid species are detected and annotated. The lipidomics community is in need of benchmark reference values to assess the validity of various lipidomics workflows in providing accurate quantitative measurements across the diverse lipidome. LipidQC addresses the harmonization challenge in lipid quantitation by providing a semiautomated process, independent of analytical platform, for visual comparison of experimental results of National Institute of Standards and Technology Standard Reference Material (SRM) 1950, "Metabolites in Frozen Human Plasma", against benchmark consensus mean concentrations derived from the NIST Lipidomics Interlaboratory Comparison Exercise.

[1]  Oliver Fiehn,et al.  Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry. , 2014, Trends in analytical chemistry : TRAC.

[2]  M. Narváez-Rivas,et al.  Comprehensive untargeted lipidomic analysis using core-shell C30 particle column and high field orbitrap mass spectrometer. , 2016, Journal of chromatography. A.

[3]  Matej Oresic,et al.  Informatics and computational strategies for the study of lipids. , 2008, Molecular bioSystems.

[4]  Bernard Walther,et al.  The human plasma-metabolome: Reference values in 800 French healthy volunteers; impact of cholesterol, gender and age , 2017, PloS one.

[5]  Kelly M. Hines,et al.  Assessment of altered lipid homeostasis by HILIC-ion mobility-mass spectrometry-based lipidomics[S] , 2017, Journal of Lipid Research.

[6]  Stephen A. Wise,et al.  Standard Reference Materials: Definitions of terms and modes used at NIST for value-assignment of reference materials for chemical measurements , 2000 .

[7]  Matej Oresic,et al.  Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950–Metabolites in Frozen Human Plasma[S] , 2017, Journal of Lipid Research.

[8]  Jeremy P. Koelmel,et al.  LipidPioneer : A Comprehensive User-Generated Exact Mass Template for Lipidomics , 2017, Journal of The American Society for Mass Spectrometry.

[9]  Edith Seier,et al.  Confidence Interval for a Coefficient of Dispersion in Nonnormal Distributions , 2006, Biometrical journal. Biometrische Zeitschrift.

[10]  G. Kolovou,et al.  Lipidomics in vascular health: current perspectives , 2015, Vascular health and risk management.

[11]  S. Stein,et al.  Analysis of human plasma metabolites across different liquid chromatography/mass spectrometry platforms: Cross-platform transferable chemical signatures. , 2016, Rapid communications in mass spectrometry : RCM.

[12]  Yu Bai,et al.  Recent advances in lipidomics for disease research. , 2016, Journal of separation science.

[13]  Kim Ekroos,et al.  Gender, Contraceptives and Individual Metabolic Predisposition Shape a Healthy Plasma Lipidome , 2016, Scientific Reports.

[14]  N. Laird,et al.  Meta-analysis in clinical trials. , 1986, Controlled clinical trials.

[15]  Yu Bai,et al.  Recent advances of chromatography and mass spectrometry in lipidomics , 2011, Analytical and bioanalytical chemistry.

[16]  Hui Jiang,et al.  Non-targeted metabolomics and lipidomics LC–MS data from maternal plasma of 180 healthy pregnant women , 2015, GigaScience.

[17]  Stephen E. Stein,et al.  Metabolite profiling of a NIST Standard Reference Material for human plasma (SRM 1950): GC-MS, LC-MS, NMR, and clinical laboratory analyses, libraries, and web-based resources. , 2013, Analytical chemistry.

[18]  D. B. Duncan,et al.  Estimating Heteroscedastic Variances in Linear Models , 1975 .

[19]  Eoin Fahy,et al.  Lipidomics reveals a remarkable diversity of lipids in human plasma1[S] , 2010, Journal of Lipid Research.

[20]  Ursula Loizides-Mangold On the future of mass‐spectrometry‐based lipidomics , 2013, The FEBS journal.

[21]  Giuseppe Astarita,et al.  Metabolomics and lipidomics using traveling-wave ion mobility mass spectrometry , 2017, Nature Protocols.