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Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring
[Image: see text] Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics’ technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standa...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8674878/ https://www.ncbi.nlm.nih.gov/pubmed/34859676 http://dx.doi.org/10.1021/acs.analchem.1c02826 |
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author | Ghorasaini, Mohan Mohammed, Yassene Adamski, Jerzy Bettcher, Lisa Bowden, John A. Cabruja, Matias Contrepois, Kévin Ellenberger, Mathew Gajera, Bharat Haid, Mark Hornburg, Daniel Hunter, Christie Jones, Christina M. Klein, Theo Mayboroda, Oleg Mirzaian, Mina Moaddel, Ruin Ferrucci, Luigi Lovett, Jacqueline Nazir, Kenneth Pearson, Mackenzie Ubhi, Baljit K. Raftery, Daniel Riols, Fabien Sayers, Rebekah Sijbrands, Eric J. G. Snyder, Michael P. Su, Baolong Velagapudi, Vidya Williams, Kevin J. de Rijke, Yolanda B. Giera, Martin |
author_facet | Ghorasaini, Mohan Mohammed, Yassene Adamski, Jerzy Bettcher, Lisa Bowden, John A. Cabruja, Matias Contrepois, Kévin Ellenberger, Mathew Gajera, Bharat Haid, Mark Hornburg, Daniel Hunter, Christie Jones, Christina M. Klein, Theo Mayboroda, Oleg Mirzaian, Mina Moaddel, Ruin Ferrucci, Luigi Lovett, Jacqueline Nazir, Kenneth Pearson, Mackenzie Ubhi, Baljit K. Raftery, Daniel Riols, Fabien Sayers, Rebekah Sijbrands, Eric J. G. Snyder, Michael P. Su, Baolong Velagapudi, Vidya Williams, Kevin J. de Rijke, Yolanda B. Giera, Martin |
author_sort | Ghorasaini, Mohan |
collection | PubMed |
description | [Image: see text] Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics’ technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950–Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231–Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials. |
format | Online Article Text |
id | pubmed-8674878 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-86748782021-12-17 Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring Ghorasaini, Mohan Mohammed, Yassene Adamski, Jerzy Bettcher, Lisa Bowden, John A. Cabruja, Matias Contrepois, Kévin Ellenberger, Mathew Gajera, Bharat Haid, Mark Hornburg, Daniel Hunter, Christie Jones, Christina M. Klein, Theo Mayboroda, Oleg Mirzaian, Mina Moaddel, Ruin Ferrucci, Luigi Lovett, Jacqueline Nazir, Kenneth Pearson, Mackenzie Ubhi, Baljit K. Raftery, Daniel Riols, Fabien Sayers, Rebekah Sijbrands, Eric J. G. Snyder, Michael P. Su, Baolong Velagapudi, Vidya Williams, Kevin J. de Rijke, Yolanda B. Giera, Martin Anal Chem [Image: see text] Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics’ technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950–Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231–Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials. American Chemical Society 2021-12-03 2021-12-14 /pmc/articles/PMC8674878/ /pubmed/34859676 http://dx.doi.org/10.1021/acs.analchem.1c02826 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Ghorasaini, Mohan Mohammed, Yassene Adamski, Jerzy Bettcher, Lisa Bowden, John A. Cabruja, Matias Contrepois, Kévin Ellenberger, Mathew Gajera, Bharat Haid, Mark Hornburg, Daniel Hunter, Christie Jones, Christina M. Klein, Theo Mayboroda, Oleg Mirzaian, Mina Moaddel, Ruin Ferrucci, Luigi Lovett, Jacqueline Nazir, Kenneth Pearson, Mackenzie Ubhi, Baljit K. Raftery, Daniel Riols, Fabien Sayers, Rebekah Sijbrands, Eric J. G. Snyder, Michael P. Su, Baolong Velagapudi, Vidya Williams, Kevin J. de Rijke, Yolanda B. Giera, Martin Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring |
title | Cross-Laboratory Standardization of Preclinical Lipidomics
Using Differential Mobility Spectrometry and Multiple Reaction Monitoring |
title_full | Cross-Laboratory Standardization of Preclinical Lipidomics
Using Differential Mobility Spectrometry and Multiple Reaction Monitoring |
title_fullStr | Cross-Laboratory Standardization of Preclinical Lipidomics
Using Differential Mobility Spectrometry and Multiple Reaction Monitoring |
title_full_unstemmed | Cross-Laboratory Standardization of Preclinical Lipidomics
Using Differential Mobility Spectrometry and Multiple Reaction Monitoring |
title_short | Cross-Laboratory Standardization of Preclinical Lipidomics
Using Differential Mobility Spectrometry and Multiple Reaction Monitoring |
title_sort | cross-laboratory standardization of preclinical lipidomics
using differential mobility spectrometry and multiple reaction monitoring |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8674878/ https://www.ncbi.nlm.nih.gov/pubmed/34859676 http://dx.doi.org/10.1021/acs.analchem.1c02826 |
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