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Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories

Quantitative MS of human plasma lipids is a promising technology for translation into clinical applications. Current MS-based lipidomic methods rely on either direct infusion (DI) or chromatographic lipid separation methods (including reversed phase and hydrophilic interaction LC). However, the use...

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Autores principales: Triebl, Alexander, Burla, Bo, Selvalatchmanan, Jayashree, Oh, Jeongah, Tan, Sock Hwee, Chan, Mark Y., Mellet, Natalie A., Meikle, Peter J., Torta, Federico, Wenk, Markus R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Biochemistry and Molecular Biology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6939597/
https://www.ncbi.nlm.nih.gov/pubmed/31732502
http://dx.doi.org/10.1194/jlr.D119000393
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author Triebl, Alexander
Burla, Bo
Selvalatchmanan, Jayashree
Oh, Jeongah
Tan, Sock Hwee
Chan, Mark Y.
Mellet, Natalie A.
Meikle, Peter J.
Torta, Federico
Wenk, Markus R.
author_facet Triebl, Alexander
Burla, Bo
Selvalatchmanan, Jayashree
Oh, Jeongah
Tan, Sock Hwee
Chan, Mark Y.
Mellet, Natalie A.
Meikle, Peter J.
Torta, Federico
Wenk, Markus R.
author_sort Triebl, Alexander
collection PubMed
description Quantitative MS of human plasma lipids is a promising technology for translation into clinical applications. Current MS-based lipidomic methods rely on either direct infusion (DI) or chromatographic lipid separation methods (including reversed phase and hydrophilic interaction LC). However, the use of lipid markers in laboratory medicine is limited by the lack of reference values, largely because of considerable differences in the concentrations measured by different laboratories worldwide. These inconsistencies can be explained by the use of different sample preparation protocols, method-specific calibration procedures, and other experimental and data-reporting parameters, even when using identical starting materials. Here, we systematically investigated the roles of some of these variables in multiple approaches to lipid analysis of plasma samples from healthy adults by considering: 1) different sample introduction methods (separation vs. DI methods); 2) different MS instruments; and 3) between-laboratory differences in comparable analytical platforms. Each of these experimental variables resulted in different quantitative results, even with the inclusion of isotope-labeled internal standards for individual lipid classes. We demonstrated that appropriate normalization to commonly available reference samples (i.e., “shared references”) can largely correct for these systematic method-specific quantitative biases. Thus, to harmonize data in the field of lipidomics, in-house long-term references should be complemented by a commonly available shared reference sample, such as NIST SRM 1950, in the case of human plasma.
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spelling pubmed-69395972020-01-03 Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories Triebl, Alexander Burla, Bo Selvalatchmanan, Jayashree Oh, Jeongah Tan, Sock Hwee Chan, Mark Y. Mellet, Natalie A. Meikle, Peter J. Torta, Federico Wenk, Markus R. J Lipid Res Methods Quantitative MS of human plasma lipids is a promising technology for translation into clinical applications. Current MS-based lipidomic methods rely on either direct infusion (DI) or chromatographic lipid separation methods (including reversed phase and hydrophilic interaction LC). However, the use of lipid markers in laboratory medicine is limited by the lack of reference values, largely because of considerable differences in the concentrations measured by different laboratories worldwide. These inconsistencies can be explained by the use of different sample preparation protocols, method-specific calibration procedures, and other experimental and data-reporting parameters, even when using identical starting materials. Here, we systematically investigated the roles of some of these variables in multiple approaches to lipid analysis of plasma samples from healthy adults by considering: 1) different sample introduction methods (separation vs. DI methods); 2) different MS instruments; and 3) between-laboratory differences in comparable analytical platforms. Each of these experimental variables resulted in different quantitative results, even with the inclusion of isotope-labeled internal standards for individual lipid classes. We demonstrated that appropriate normalization to commonly available reference samples (i.e., “shared references”) can largely correct for these systematic method-specific quantitative biases. Thus, to harmonize data in the field of lipidomics, in-house long-term references should be complemented by a commonly available shared reference sample, such as NIST SRM 1950, in the case of human plasma. The American Society for Biochemistry and Molecular Biology 2020-01 2019-11-15 /pmc/articles/PMC6939597/ /pubmed/31732502 http://dx.doi.org/10.1194/jlr.D119000393 Text en Copyright © 2020 Triebl et al. Published by The American Society for Biochemistry and Molecular Biology, Inc. http://creativecommons.org/licenses/by/4.0/ Author’s Choice—Final version open access under the terms of the Creative Commons CC-BY license.
spellingShingle Methods
Triebl, Alexander
Burla, Bo
Selvalatchmanan, Jayashree
Oh, Jeongah
Tan, Sock Hwee
Chan, Mark Y.
Mellet, Natalie A.
Meikle, Peter J.
Torta, Federico
Wenk, Markus R.
Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories
title Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories
title_full Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories
title_fullStr Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories
title_full_unstemmed Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories
title_short Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories
title_sort shared reference materials harmonize lipidomics across ms-based detection platforms and laboratories
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6939597/
https://www.ncbi.nlm.nih.gov/pubmed/31732502
http://dx.doi.org/10.1194/jlr.D119000393
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